A Review of the Forest Service 

Remote Automated Weather 

Station (RAWS) Network

John Zachariassen

Karl Zeller

Ned Nikolov

Tom McClelland

United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical

Report RMRS-GTR-119

December 2003
Zachariassen, John; Zeller, Karl F.; Nikolov, Ned; and McClelland, Tom. 2003. A review of 

the Forest Service Remote Automated Weather Station (RAWS) network. Gen. Tech. 

Rep. RMRS-GTR-119. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station. 153 p + CD.

Abstract

The RAWS network and RAWS data-use systems are closely reviewed and summarized in 

this report. RAWS is an active program created by the many land-management agencies 

that share a common need for accurate and timely weather data from remote locations for 

vital operational and program decisions specific to wildland and prescribed fires. A RAWS 

measures basic observable weather parameters such as temperature, relative humidity, wind 

speed, wind direction, and precipitation as well as “fuel stick” temperature. Data from almost 

1,900 stations deployed across the conterminous United States, Alaska, and Hawaii are now 

routinely used to calculate and forecast daily fire danger indices, components, and adjective 

ratings. Fire business applications include the National Fire Danger Rating System (NFDRS), 

fire behavior, and fire use. Findings point to the fact that although the RAWS program works 

and provides needed weather data in support of fire operations, there are inefficiencies and 

significant problem areas that require leadership attention at the National level.

Keywords: weather data, fire business, fire use, National Fire Danger Rating System, NFDRS, 

fire danger, RAWS, forest fire, wildland fire, weather observations, prescribed burns

The Authors

John Zachariassen, Karl F. Zeller, and Ned Nikolov are with the USDA Forest Service, 

Rocky Mountain Research Station, Fort Collins, CO 80526 USA.

Tom McClelland is with the USDA Forest Service. Watershed, Fish, Wildlife, Air, and Rare 

Plants Management Office, Washington Office, Washington, DC, 20090 USA.

Rocky Mountain Research Station

Natural Resources Research Center

2150 Centre Avenue, Building A

Fort Collins, CO 80526

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mailing information in label form through one of the following media. 

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FAX (970) 498-1396

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The use of trade or firm names in this publication is for reader information and 

does not imply endorsement by the U.S. Department of Agriculture of any 

production or service
A Review of the Forest Service 

Remote Automated Weather 

Station (RAWS) Network

John Zachariassen

Karl Zeller

Ned Nikolov

Tom McClelland
Acknowledgements

We would like to thank all those who have helped in the preparation of this report; technical support, providing RAWS documentation, history, points of contact, personal communications, and answers to long lists of questions, etc.: Constance Lemos, Joyce VanDeWater, 

Rosemary Reinhart, Kolleen Shelley, Linnea Keating, Phil Sielaff, Buddy Adams, Bob Hamre, 

Charles Kazimir, Jeff Barnes, Mike Barrowcliff, Rick Ochoa, Dave Clement, Barry Shindelar, 

Chuck Maxwell, Russ Gripp, Beth Little, Barry Garten, personnel at the Northern California 

Training Center and Ft. Collins dispatch office, Mark Nelson, Paul Schlobom, Larry Bradshaw, 

Greg McCurdy, Kelly Redmond, Tim Mathewson, Steve Marien, Ann Stegmaier, Sue Stillings, 

Keth McGillivary, Ken Reninger, and Terry Marsha. We are sure we have forgotten some people who were also a great help and for that we apologize.

We would also like to thank the USDA Forest Service Watershed, Fish, Wildlife, Air, and 

Rare Plants Management Washington Office and the USDA Forest Service Air Program 

Washington Office (Richard Fisher) for funding support.

ii

We acknowledge Kelly Homstad, our Metro State College student intern during the summer

of 2002, for her help with this report, especially the Appendices W, X and Y.
Contents

Introduction......................................................................................................................................... 1

What Is RAWS? ............................................................................................................................... 1

Is the RAWS Network Working? ...................................................................................................... 3

Report Organization......................................................................................................................... 3

Background of the RAWS Network................................................................................................... 3

A Brief History .................................................................................................................................. 3

RAWS Classification Schemes ........................................................................................................ 4

RAWS Information Management Systems ...................................................................................... 5

National Fire Danger Rating System (NFDRS)........................................................................... 6

Administrative and Forest Fire Information Retrieval and Management System (AFFIRMS) .... 6

National Interagency Fire Management Integrated Database (NIFMID) .................................... 6

Automatic Sorting, Conversion, and Distribution System (ASCADS)......................................... 6

Wildland Fire Assessment System (WFAS)................................................................................ 7

Western Region Climate Center (WRCC)................................................................................... 7

Multiagency Resource...................................................................................................................... 7

NFDRS 2000 Standards .................................................................................................................. 7

Data Stream and Products................................................................................................................. 8

Summary of Data Flow..................................................................................................................... 8

Findings ....................................................................................................................................... 9

Operations, Protocols, and Organization........................................................................................ 9

Installation and Deployment........................................................................................................... 10

Sensor Equipment.......................................................................................................................... 10

Sampling Protocols ........................................................................................................................ 10

Standard Sampling Protocols.................................................................................................... 10

NFDRS 2000 Sampling Protocol............................................................................................... 11

Recent Updates to NFDRS 2000 Standards ............................................................................ 12

Findings on Solar Radiation Data. ............................................................................ 12

Positions and Responsibilities (RAWS, WIMS, and NFDRS)........................................................ 12

NFDRS 2000 Standards............................................................................................................ 12

Findings................................................................................................................................. 13

Local Quality Control and Assurance (QA/QC)............................................................................. 13

Operating Period ............................................................................................................................ 14

Maintenance and Calibration ......................................................................................................... 14

Service Contracts...................................................................................................................... 14

Staffing Needs........................................................................................................................... 15

Findings................................................................................................................................. 15

Administrative Organization ........................................................................................................... 15

FS Funding ..................................................................................................................................... 16

Funding for Station Purchase, Repair, and Upgrades............................................................... 16

Funding for WIMS...................................................................................................................... 16

Current Station Classification and Numbers of RAWS.................................................................. 17

ASCADS Classification Scheme ............................................................................................... 17

Current Forest Service Classification Scheme ......................................................................... 17

New NFDRS 2000 Classification Scheme................................................................................ 19

Findings on Conformance with NFDRS 2000 Standards................................ 20

Use of RAWS Data in Fire-Related Applications .......................................................................... 20

NFDRS Use.................................................................................................................................... 20

Fire Behavior .................................................................................................................................. 20

Fire Use .......................................................................................................................................... 21

Data Retrieval .................................................................................................................................... 21

Automatic Sorting, Conversion, and Distribution System (ASCADS)............................................ 21

Access ....................................................................................................................................... 21

Watchdog Function....................................................................................................................22

Upgrades ...................................................................................................................................22

Findings.................................................................................................................................22

Western Regional Climate Center (WRCC)...................................................................................22

Data Management ..................................................................................................................... 23

iii
Archival Function .......................................................................................................................23

Access ....................................................................................................................................... 23

Findings................................................................................................................................. 24

National Interagency Fire Management Integrated Database (NIFMID: WIMS/KCFast).............. 24

WIMS......................................................................................................................................... 25

KCFast....................................................................................................................................... 25

Other Modules ........................................................................................................................... 25

National Weather Service (NWS) .................................................................................................. 25

BLM/NIFC Wildland Fire Management Information (WFMI).......................................................... 25

Wildland Fire Assessment System (WFAS)................................................................................... 26

Geospatial Multi-Agency Coordination Group (GEOMAC) ...........................................................26

Findings ..................................................................................................................................... 27

RAWS Projects Under Development .............................................................................................. 27

NFDRS 2000 Standards ................................................................................................................ 27

The RSFWSU Strategic Plan in Support of NFDRS 2000 Standards ........................................... 27

Long-Term Upgrades to ASCADS ............................................................................................ 28

Increase in Transmission Frequencies and Rates .................................................................... 29

IWOS Development...................................................................................................................29

WIMS Upgrades .............................................................................................................................29

New Web Sites/Data Access/RAWS Products.............................................................................. 29

Geographic Area Coordination Centers (GACCs).........................................................................30

Studies and Surveys ........................................................................................................................30

Previous RAWS Use Studies ......................................................................................................... 31

Marsha Study: Identification of Priority Stations Within Zones................................................. 31

Findings................................................................................................................................. 32

Brown Study: Optimization of Intraregional RAWS Deployments............................................. 32

Other Studies............................................................................................................................. 32

Survey of RAWS Users .................................................................................................................. 32

Multiple Uses .............................................................................................................................33

Assessment of Current RAWS Network....................................................................................33

Survey of Commercially Available Meteorological Sensors...........................................................33

Experimental Prototype Super-RAWS...........................................................................................34

Description.................................................................................................................................34

Comparison of RAWS and Super-RAWS Data Sets ................................................................34

Method of Comparison of RAWS and Super-RAWS Data Sets ...............................................35

Results of Comparison of RAWS and Super-RAWS Data Sets ...............................................35

Findings of Comparison of RAWS and Super-RAWS Data Sets ................36

Comparison of WRCC and KCFast Data Sets...............................................................................36

Description of WRCC and KCFast Data Sets ...........................................................................36

Method of Comparison of WRCC and KCFast Data Sets......................................................... 37

Results of Comparison of WRCC and KCFast Data Sets......................................................... 37

Findings.................................................................................................................................38

Effect of Changes in Tower Height and Sensor Placement...........................................................39

Description of Changes in Sensor Mounting Heights ...............................................................39

Method of Calculating Effect of Changes in Sensor Mounting Height ......................................39

Findings from Calculation of Effect of Changes in Sensor 

 Mounting Height............................................................................................................ 42

Issues Around GOES Transmit Times and 13:00 Hour 

 Observation Time.............................................................................................................. 42

DCP Transmission Protocols (Vaisala/Handar 540 and 555, FTS 12s, 

 and Campbell Scientific 23X) ..................................................................................................... 42

Vaisala/Handar Models ............................................................................................................. 42

FTS Models ............................................................................................................................... 43

Campbell Scientific Models .......................................................................................................43

Findings Regarding DCP Transmission Protocols............................................43

Additional Uses of RAWS Data .......................................................................................................44

Air Quality Monitoring.....................................................................................................................45

Measurement of Aerosols (Airborne Particulate Matter) ...............................................................45

Climatological Analyses .................................................................................................................46

iv
Studies of Environmental Aerodynamics .......................................................................................46

Ecosystem Process Modeling ........................................................................................................48

Weather Research .........................................................................................................................48

Mesoscale Weather Forecasting Support......................................................................................48

Management Implications ...............................................................................................................49

Current Issues ................................................................................................................................ 49

Findings .....................................................................................................................................50

Personnel...................................................................................................................................50

Upgrades to Stations................................................................................................................. 52

Upgrades to Product and Data Retrieval Systems....................................................................53

Other..........................................................................................................................................53

Conclusion.........................................................................................................................................54

Glossary of Terms and Acronyms ..................................................................................................55

References......................................................................................................................................... 62

Appendix A. Lists of RAWS-Related Entities and Web Sites ...........................................................65

Appendix B. NFDRS Structure and Operations................................................................................ 74

Appendix C-1. NIFMID Flow Chart.................................................................................................... 78

Appendix C-2. WIMS/WEB Application Menu Hierarchy ................................................................. 79

Appendix D. KCFast Flow Chart........................................................................................................ 82

Appendix E. Fire Danger Pocket Cards for Firefighters ....................................................................83

Appendix F. ASCADS Flow Chart .....................................................................................................84

Appendix G. WFAS Background and Evolution ................................................................................85

Appendix H. RAWS Data Access via WRCC.................................................................................... 87

Appendix I. RAWS Operations and Personnel Responsibilities .......................................................89

Appendix J. Sample of the Fort Collins, CO, RAWS Operating Plan ...............................................93

Appendix K. Sample Position Description of RAWS-Related Duties at the Operational Level........98

Appendix L. Sample of Daily SOP from NF Dispatch Center ...........................................................99

Appendix M. Regional RAWS Coordinator Responsibilities and Duty Guidelines ......................... 105

Appendix N. Forest Service Region 9 RAWS Operating Plan for FY03.........................................106

Appendix O. Data Retrieval ............................................................................................................. 110

Appendix P. ASCADS Watchdog Alerts and Data Flags ................................................................ 112

Appendix Q. KCFast Data File Formats .......................................................................................... 116

Appendix R. SIT – Interagency Situation Report ............................................................................ 120

Appendix S. 209 Incident Report Form........................................................................................... 122

Appendix T. GeoMac Site Hierarchy and Options........................................................................... 125

Appendix U. Summary of Responses to RAWS Survey ................................................................. 126

Appendix V. Summary of Meteorological Station Instrument Specification Survey ....................... 131

Appendix W. Super-RAWS Data Element List................................................................................ 134

Appendix X. Comparison of RAWS and Super-RAWS Data Sets.................................................. 135

Appendix Y. Comparison of KCFast and WRCC Data Sets............................................................ 142

Appendix Z. RAWS Contacts at Regional and National Levels of USFS, NPS, and FWS............. 148

Index................................................................................................................................................. 150

Inside Back Cover: CD Companion for Appendix V

v

USDA Forest Service RMRS-GTR-119. 2003. 1

Introduction

All fire managers and fire weather forecasters rely on weather data from Remote Automated 

Weather Stations (RAWS). Incident meteorologists (IMET) forecasters from the National 

Weather Service and predictive service meteorologists from Geographic Area Coordination 

Centers (GACC) (see Glossary for terms and acronyms) extol the critical importance of the 

RAWS network for their daily work. In response to a RAWS-use survey, a Nevada IMET 

writes, “Having the weather data is critical to making forecasts for the future. Without data, 

we have no idea if we are making reasonable forecasts.” A respondent from New Mexico 

asks, “If you don’t have the ground-truth data, how can you make an intelligent decision?” An 

IMET from Missouri writes, “This is our only source for 10-hour fuel moisture determinations 

which are a key component in our Fire Weather Watch and Red Flag Warning decisions.”

GACC meteorologists use RAWS data on a daily basis to calculate localized fire danger 

indices, components, and intermediate fire-related products. Comments from GACC meteorologists in the Rocky Mountain Area Coordination Center (RMACC), the Southwest Area 

Coordination Center, and the Eastern Great Basin Coordination Center range from, “Without 

high-quality fire weather data, how can we generate quality products to support fire business?” 

to “If I don’t get operational support for the RAWS network in this Region, I’ll do it myself....” 

In some geographic areas, such as places where maintenance of RAWS stations is a low priority and data quality has not been acceptable, GACC meteorologists have recently become 

directly involved in RAWS operations.

Given the severe fire seasons in recent years, it has become clear that we need to ensure 

that the overall effectiveness of the Forest Service RAWS network continues. Thus, there is a 

need to revisit the RAWS system to ensure high-quality, useful fire weather data. This report 

examines the extent to which RAWS affects fire management at all levels and explores opportunities for improvement.

We were selected to generate this report because we had no prior working knowledge of RAWS 

or of its integrated fire business role. This lack of working experience with RAWS allowed us to 

function as unbiased reviewers. It has been a challenge to understand the intricacies of RAWS, the 

interagency nature of the network, and to separate RAWS facts from myths. But Forest Service 

(FS) and Bureau of Land Management (BLM) personnel directly involved with RAWS and fire 

business have been extremely helpful and patient during the preparation of this report.

We were specifically asked to focus on the FS’s RAWS network because the FS manages 

its RAWS differently than other agencies. Given that RAWS is an interagency program, it was 

impossible to completely segregate FS RAWS. Rather than restricting the final report to FS 

RAWS, we decided to make it inclusive of all RAWS-related parts. In order to give the reader 

as complete a picture as possible, we also decided to include many loose ends that have RAWS 

implications. Hence, we hope this review document will serve not only a useful role in understanding and improving FS RAWS, but also as an interagency RAWS reference.

What Is RAWS?

Many Federal, State, and other wildland resource management agencies share a common 

need for accurate and timely weather data to make vital operational and program decisions 

related to all aspects of wildland and prescribed fires. In the mid-1970s, the Forest Service 

(FS) and Bureau of Land Management (BLM) began research, development, and deployment 

of a RAWS utilizing a satellite data transmission system, the Geostationary Operational 

Environmental Satellite (GOES). RAWS has been developed using input from many operational users. The RAWS network has evolved into a valuable interagency resource providing 

essential weather data from remote locations nationwide for critical fire business support and 

decisionmaking.
2 USDA Forest Service RMRS-GTR-119. 2003. 

The RAWS network as a whole is a weather station mesonet, which is defined as a collection of surface observing stations that cover a region in sufficient detail both in space and time 

to be able to monitor and nowcast the progression of mesoscale weather features (structure of 

fronts, outflow boundaries from mesoscale convective complexes, terrain circulations, and so 

forth). As of 2002 there were almost 1,900 stations deployed across the conterminous United 

States, Alaska, and Hawaii (fig. 1). The wildfire management agencies participating in the 

network include FS; BLM; Bureau of Indian Affairs (BIA); Federal Emergency Management 

Agency (FEMA); National Park Service (NPS); U.S. Fish and Wildlife Service (FWS), and 

state agencies. Personnel in the U.S. Department of Defense (DOD) and Department of 

Energy (DOE) also utilize RAWS for their own purposes.

A RAWS measures basic observable weather parameters: temperature, relative humidity, wind speed, wind direction, and precipitation in addition to fuel stick temperature. 

Increasingly, the capacity to measure barometric pressure and solar radiation has been added 

to many stations, particularly those meeting the new National Fire Danger Rating System 

(NFDRS) standards.

Data from the stations are now routinely used to calculate and forecast daily fire danger 

indices, components, and adjective ratings. Fire business applications such as NFDRS, fire 

behavior, and fire use constitute the primary uses of RAWS data. Often these data are also 

requested for uses other than fire weather support. Sensors and instrumentation other than the 

standard meteorological RAWS set have been added to provide weather data for nonfire applications such as air quality monitoring, climatology, ecological modeling, and environmental 

impact assessments.

Figure 1. RAWS locations as of December 2001; adapted from the Wildland Fire Assessment System 

(WFAS-MAPS).
USDA Forest Service RMRS-GTR-119. 2003. 3

Is the RAWS Network Working?

Even though RAWS is an interagency operation implementing different management 

approaches, we found that the current network, although pieces outdated and inefficient, is 

functioning and slowly improving based on current data base maintenance, physical station 

maintenance standards, and data used regularly and appropriately to calculate fire danger. 

The RAWS network is constantly changing. Hardware and software are being repaired and 

upgraded on an as-needed basis, and operational standards and protocols are being improved. 

New NFDRS weather station standards have been published (NWCG – National Fire Danger 

Rating System, Weather Station Standards 2003), and short- and long-term strategic plans 

drafted. Also since the Internet has made it easy to access and retrieve RAWS data, databases 

are being upgraded to Internet-based applications and data access is being simplified.

Nevertheless, the RAWS network is not currently as efficient as it could be. Quality assurance of data, data streams, and station maintenance vary with location and ownership. Also, 

management and position responsibilities are not always clearly defined. This is not a criticism 

of those who support and operate the RAWS system nor of their dedication to maintaining the 

network, but a recognition that the RAWS network needs more attention, management, and support than it currently receives. There is an important distinction to be made between the RAWS 

data as measured and the many uses of RAWS data when assessing the RAWS program.

Finally, we have discovered some systematic errors in historical RAWS data records that 

may have serious operational impacts on current fire use decisions.

Report Organization

In this report, we summarize different aspects of RAWS function and performance, and we 

provide findings about its performance. We hope this review will serve as a valuable source 

of RAWS information and a users guide for searching and retrieving RAWS data. There are 

many aspects of RAWS that are not fully documented; hence, many references are personal 

communications and draft documents are not easily obtained.

The report is organized into 10 sections: Introduction, Background of the RAWS Network; 

Data Stream and Products; Operations, Protocols and Oranization; Use of RAWS Data in 

Fire-Related Applications; Data Retrieval; RAWS Projects under Development; Studies and 

Surveys; Additional Uses of RAWS Data, and Management Implications. We also include a 

Reference section, a Glossary of Terms and Acronyms; and Appendices. To make the report 

easier to comprehend and to use, we have relegated a fair amount of technical information and 

details to the appendices. For example, appendix A provides a list of RAWS-related Web sites 

and of entities affiliated or related to RAWS (see appendix A).

Background of the RAWS Network

This section relates the history of the RAWS network; the research, development, and testing involved; and the deployment of hardware and software. The latter has been a continuous 

process as the network has grown in size, requiring upgraded software and new databases to 

handle the enormous amount of data being collected.

A Brief History

Prior to station automation, weather data for fire danger rating calculations and general fire 

weather support were collected manually. The stations were usually located near an FS ranger 

station or BLM fire base. Typically, an operator would visit each weather station once per day 

during the fire season (Warren and Vance 1981; K. Shelley, personal communication 2001). It 
4 USDA Forest Service RMRS-GTR-119. 2003. 

usually took 10 minutes to obtain the manual readings, which consisted of the following steps 

(Finklin and Fischer 1990; K. Shelley, NWCG – Fire Danger Working Team, Gaining a Basic 

Understanding of the National Fire Danger Rating System, January 2002):

1. Record the start wind-run count of the wind odometer.

2. Determine inches of last 24-hour rainfall with a ruler.

3. Record the dry and wet-bulb temperatures using a sling psychrometer.

4. Record the max/min air temperature for the past 24-hour and reset the instrument.

5. Record max/min relative humidity using hydrothermograph; check current relative 

humidity against wet-bulb temperature.

6. Observe wind direction for 1 minute and record it.

7. Observe and record the current state of the weather (SOW).

8. Record end wind-run odometer reading and time lapse from step 1 (typically 

approximately 10 minutes) and calculate and record the average wind speed (count per 

unit time).

9. After departing from the site, determine past 24-hr rain duration and lightning occurrence 

by asking local people.

10. Call the local agency supervisor’s office to relay complete observation record for 

subsequent calculation of fire danger indices and components using look-up tables and 

nomograms, slide-rule, or hand-held calculator if available.

The historical procedure is an important aspect of the present-day RAWS program because 

current automated sampling protocols still reflect data collection limitations inherent in 

the manual observations. Modern electronic methods exist that make it possible to extract 

additional and useful information from existing RAWS (for example, more frequent sampling, 

longer averaging periods, measurement statistics, and so forth). These are not currently employed, however, due to data transmission, manipulation, and storage limitations as well as an 

underlying ‘if-it-works-don’t-change-it’ philosophy among users.

In 1975, the FS began investigating the use of an automatic data collection system utilizing the GOES to transmit fire weather data from remote locations (table 1). The GOES-based 

RAWS system was chosen to avoid the disadvantages of radio- or telephone-linked stations. 

Such limitations included the need for a line of sight to a base station for radio transmission 

or proximity to telephone lines for a telephone transmission. BLM soon became involved in a 

cooperative project with the FS to develop, evaluate, and deploy GOES-based RAWS (Warren 

and Vance 1981). In 1978, FS and BLM engineers developed the specifications for the final 

RAWS-GOES platform. These were based on experience gained during the development phase 

and on requirements set by the RAWS Steering Committee and the NFDRS Implementation 

Team. Except for hardware and data-logger software upgrades, the basic station configuration 

has not changed since then.

RAWS Classification Schemes

During the late 1970s many other Federal and State land management agencies began deploying RAWS in support of fire operations including the BIA, FWS, NPS, and California 

Department of Forestry (CDF). With the increasing numbers of RAWS deployed by various 

agencies and States, the need to distinguish between station types and to define station function became apparent (for example, NFDRS versus non-NFDRS; GOES versus non-GOES). 

Even today many stations are not GOES-capable. The proliferation of RAWS also generated 

the need to automate data collection, centralize databases, and calculate fire business related 

products, such as indices and components, that use RAWS data. The FS Pacific Northwest 

Region, followed by other FS regions and the BLM, informally adopted the weather station 
USDA Forest Service RMRS-GTR-119. 2003. 5

classification standards, which were formally implemented in the late 1980s (B. Adams, personal communication 2002).

These weather station classification standards continue to be used by BLM’s initial data 

handling system: the Automatic Sorting, Conversion, and Distribution System (ASCADS). 

The FS, however, has adopted a number code system for different types and classes of stations. 

Other land management agencies at the State and Federal level use both classification systems 

because all must use BLM’s ASCADS and the FS’s Weather Information Management System 

(WIMS) to process and manage RAWS data.

The National Wildfire Coordinating Group (NWCG)—an interagency group established 

to coordinate efforts of the participating agencies—has recently published new station classes 

and minimum standards.

For a description of these classification schemes, see Operations, Protocols, and 

Organization section.

RAWS Information Management Systems

With the increased number of weather stations being fielded came the necessity to automate 

and streamline data handling. At the same time that RAWS data-loggers, sensors, transmitters, 

Table 1: General Timeline of RAWS and Database Development.

Year Occurrence

Late 1920s to present Manual weather stations

1970 National Fire Danger research group formed; research initiated that

 generated the 1972 version of NFDRS

1975 RAWS/GOES planning and development initiated

AFFIRMS launched on a time-share computer, also hosted NFDRS

1977 – late 1970s Final RAWS specifications established 

10 stations purchased and deployed – evaluated for 5 months

1978 version of NFDRS implemented

Early 1980s First RAWS manual GTR-IMT-116; Other state and federal land management

 agencies began deploying RAWS

Late 1980s 1988 version of NFDRS released and implemented

ASCADS version 1 released/implemented

1990 WIMS development initiated, designed to replace AFFIRMS

1990 Weather Station Handbook published

1993 AFFIRMS replaced by WIMS (Weather Information Management system)

WIMS is new host for 1978 and 1988 NFDRS

Mid-1990s WFAS development initiated

WIMS development continues along with NIFMID/KCFast, etc.

1997 WFAS development initiated

WIMS development continues along with NIFMID/KCFast, and so forth

1998 Experimental fire potential map added to WFAS

WIMS/WEB development continues

2000 Fire Family Plus V 2.0 released

NWCG-NFDRS (RAWS) Weather Station Manual released

2001 WIMS/WEB implemented along with NIFMID/KCFast/SIT/209/PocketCard,

 and so forth

Still host of NFDRS 1978 and 1988

Present-day GACC Meteorologists take initiative to inventory and correct

 individual (cross agency) problems (siting, quality control, and so forth)

2002 Fire Family Plus V 3.0 released

ASCADS re-engineering specifications established, to be implemented

2003 ASCADS patch implemented

Update of NWCG-NFDRS (RAWS) Weather Station Manual released
6 USDA Forest Service RMRS-GTR-119. 2003. 

and other hardware were being integrated, tested, and deployed, databases and software were 

also developed to manage the new influx of data. The automation of data collection allowed 

for the deployment of more RAWS and greatly enhanced the ability to collect weather information from areas that were difficult or impossible to visit on a daily basis. This led to the 

progressive development and upgrading of RAWS information management systems. In this 

section, we will take a look at the development of these systems.

National Fire Danger Rating System (NFDRS)

The National Fire Danger Rating System (NFDRS) is a computer model that calculates 

fire danger rating indices and components. It is used for fire business decisionmaking and 

as a management decision tool (see also appendix B). The manual version of the NFDRS 

was released in 1972, the first computerized version in 1975. New versions of NFDRS were 

released in 1978 and 1988. The 1988 version was in answer to concerns for better model response to drought and precipitation in the Southeast United States. As a decision support tool, 

NFDRS assumes that accurate 13:00 hour weather observations have been input to the system. 

It then uses these to generate fire danger indices and components. When this assumption was 

tested, it was found to be problematic. These findings are presented later in this report (see 

Management Implications section).

Administrative and Forest Fire Information Retrieval and Management 

System (AFFIRMS)

The Administrative and Forest Fire Information Retrieval and Management System 

(AFFIRMS) was a prototype information management system that initially hosted the 1975 

computerized version of NFDRS. It was developed in response to the need to automate the 

manual version of NFDRS that had been released in 1972. Designed to be interactive and userfriendly, AFFIRMS was available nationally on a time-share computer system via commercial 

telephone lines. It allowed simultaneous entry of fire weather observations from numerous 

remote terminals at fire dispatch centers across the network. The data were then displayed 

along with the fire danger indices and components for specific RAWS sites. It continued to 

host the NFDRS models until 1993 when it was replaced by the NIFMID Weather Information 

Management System (WIMS).

National Interagency Fire Management Integrated Database (NIFMID)

The National Interagency Fire Management Integrated Database (NIFMID) is an ORACLE 

relational database that contains historic fire weather and fire occurrence information (see 

NIFMID flow chart in appendix C-1). It serves as a database warehouse for archiving fire 

business/management information, including RAWS weather observations. WIMS, which is 

part of NIFMID, is a weather information database (see WIMS webb application menu hiarchy, appendix C-2). It produces the daily and forecast fire danger indices and components using the NFDRS model(s) and archives all hourly RAWS observations for 18 months. Another 

NIFMID module, the Kansas City Fire Access Software (KCFast) database, stores all 13:00 

hour observations for the entire period of record (see also KCFast flow chart in appendix D). 

In addition to the 13:00 hour observations, KCFast also contains all the hourly observations 

for 18 months as well as fire occurrence information – statistics by region, forest, and so forth. 

Other modules in NIFMID include firefighter pocket cards (see example in appendix E) and 

report generators and forms (for example, the national fire situation report, incident situation 

reports, and aircraft use). We describe NIFMID, WIMS, and KCFast in more detail in the 

Data Retrieval section.

Automatic Sorting, Conversion, and Distribution System (ASCADS)

In the late 1980s the Remote Sensing Fire Weather Support Unit (RSFWSU) at the National 

Interagency Fire Center (NIFC), also known as the Boise Depot, was instrumental in developing 
USDA Forest Service RMRS-GTR-119. 2003. 7

the Automatic Sorting, Conversion, and Distribution System (ASCADS). It has remained 

relatively unchanged to date but upgrades have been identified (see long-term upgrades to 

ASCADS section). ASCADS was originally designed as the single data handling entity to 

perform all RAWS functions including ingesting data, re-formatting, checking for quality 

assurance, and sorting raw data received through GOES. It also merged all data streams for 

distribution to various users, and provided both a short-term database (30 days) of RAWS data 

and long-term database of RAWS metadata. The original primary user was the RSFWSU, 

with only limited use by others. As the system evolved, an increasing number of clients began 

accessing the database for both weather and metadata. ASCADS is now the central shortterm data cache and distribution point for all of the GOES RAWS. From ASCADS, weather 

data are sent to WIMS, the Western Regional Climate Center (WRCC), the National Weather 

Service (NWS) in Boise, and to the BLM/NIFC Wildland Fire Management Information 

System (WFMI) (USDI/BLM/RSFWS 2002). We describe ASCADS in more detail in the 

Data Retrieval section and see ASCADS flow chart in appendix F.

Wildland Fire Assessment System (WFAS)

The Wildland Fire Assessment System (WFAS) is not a RAWS database; it queries WIMS 

each afternoon to retrieve NFDRS products and to generate maps of selected fire weather 

parameters that are archived. WFAS was developed by the Fire Behavior Unit, Fire Sciences 

Laboratory, Rocky Mountain Research Station in Missoula, MT, as an Internet-based tool for 

fire business managers (see appendix G). Initially available in 1994 through the Fire Science 

Laboratory, WFAS was transferred to NIFC in 1999. WFAS is currently supported by NIFC, 

the USDA FS F&AM, and the National Information Systems Team (NIST). A WFAS Web site 

was redesigned in 2002 to provide easier access to current and archived products. We describe 

WFAS in more detail in the Data Retrieval section.

Western Region Climate Center (WRCC)

The Western Region Climate Center (WRCC) has taken on the responsibility of archiving 

and quality assuring RAWS hourly data. The WRCC database is the only systemwide archive 

of long-term hourly data for all active and inactive RAWS. The WRCC database also maintains a Station Metadata Summary for each RAWS. The historical record is documented for 

each station and has been quality assured for consistency. We describe WRCC in more detail 

in the Data Retrieval section (see also appendix H).

Multiagency Resource

The RAWS network has evolved over the past 24 years into a multiagency resource that 

serves the common need for remote area weather data in support of fire operations and 

the NFDRS. Today the most immediately useful RAWS data stream is distributed through 

ASCADS to NIFMID and WFAS. The RAWS network directly serves the interagency fire 

community by providing weather data through ASCADS to the NWS, NIFMID, WRCC, 

and indirectly to WFAS. NIFMID and WFAS provide the backbone weather support for the 

nation’s fire business decisionmaking. RAWS also provides for immediate field operational 

weather needs at some stations through direct dial-up and/or station alert features.

NFDRS 2000 Standards

As part of the ongoing upgrade of RAWS, the National Wildfire Coordinating Group 

(NWCG)—an interagency group established to coordinate programs of the participating wildfire management agencies—published the NFDRS 2000 Weather Station Standards (NWCG 

2000). It is intended to supplement (and update) parts of The Weather Station Handbook: An 

Interagency Guide for Wildland Managers (Finklin and Fischer 1990). The aim of the publication is to standardize procedures across agencies for the entire network. Contents include 
8 USDA Forest Service RMRS-GTR-119. 2003. 

discussions of a station’s operational period; site selection and station frame criteria; annual 

maintenance and repair; sensor suite and data stream transmission requirements; and a new 

station classification system. The NFDRS update recognizes that hardware upgrades are 

ongoing. The sensor suite will stay the same, although new methods are being developed to 

calculate fuel moisture and state-of-the-weather (SOW). Also under investigation is a handsoff method to validate and flag the 13:00 hour observation. The new operations protocols are 

briefly described below and in greater detail in appendix I.

Data Stream and Products

Summary of Data Flow

This section summarizes how RAWS data flows through various databases. The NWCG 

Information Resource Management Working Team (IRMWT) and the NWCG Data 

Administration Working Group (DAWG) are two entities working to standardize data handling. Their mission is to ensure the smooth exchange of data by providing a standardized 

format for entering metadata and weather data.

The flow of data from modern RAWS as currently required by NWCG is shown in figure 2. From the DCP-transmitter, RAWS data are transmitted to a GOES satellite (East or 

West satellite depending on location). RAWS data are then retransmitted to the National 

Oceanic and Atmospheric Administration’s (NOAA) National Environmental Satellite, Data, 

Figure 2. RAWS Data Stream.

RAWS/ ata ollection

latform

D C

P

G O

E S

eostationary perational

nvironmental atellite

Domestic Satellite

(DOMSAT)

ASCADS BLM /

Boise, Idaho

see flow chart:

Appendix F

ASCADS

see flow chart:

Appendix H

WRCC see flow chart:

Appendix C-1

NIFMID

N l F

M I

D

ational nteragency ire

anagement ntegrated

atabase

Kansas City, MO

W F A

S

ildland ire ssessment

ystem (WFAS)

Appendix G

W R

C C

estern egional

limate enter

DRI, Reno, NV

N W S

B

ational eather ervice

oise, ID

-NOAA-climatology, forecasts

BLM/NIFC

Wildland Fire

Management

Information

Redundant data stream

(under development)

Direct Readout

Ground Station

(DRGS)

ASCADS II

W D

A

S

allops Island/ ata

utomated Processing

ystem
USDA Forest Service RMRS-GTR-119. 2003. 9

and Information Service (NESDIS) center on Wallops Island, VA. From there, the data are 

again retransmitted via the Domestic Satellite (DOMSAT) to Boise, ID, to be ingested and 

processed by the BLM database, ASCADS, which is part of RSFWSU (also known as the 

Boise Depot). ASCADS is also used for metadata storage, maintenance documentation, and 

short-term data storage. From ASCADS, data are forwarded to the FS database, WIMS; to the 

WRCC; to the Boise NWS; and to the BLM/NIFC Wildland Fire Management Information 

System (WFMI).

WIMS receives additional RAWS data from stations (called dial-ups) that can only be accessed via telephone. A stand-alone multimodem computer (the HUB) located in Kansas City/

NITC queries the dial-ups for data retrieval on a regular schedule (every 3, 6, 9, or 24 hours, 

depending on local needs). This system should be phased out of service by 2005 as part of the 

RAWS and WIMS upgrade programs.

The NFDRS fire danger indices and components are the fire-related primary products for 

which RAWS data are used; fire behavior and fire use are two others. All RAWS weather data 

are combined with their respective site information and NFDRS parameters that are contained 

within the station catalog file such as: climate class, slope class, fuel model, humidity code, 

and so forth. These are then processed through NFDRS algorithms daily to generate fire danger rating indices, components, adjective fire danger ratings, and fuel moisture (Cohen and 

Deeming, 1985; see also appendix B). Fire danger rating predictions are also made for the 

next day.

NWS uses RAWS data to prepare fire weather forecasts for regions and zones throughout 

the United States.

WFAS queries WIMS once a day to retrieve and then map NFDRS products for the entire 

United States. WFAS products include: indices and components, greenness, drought, weather 

forecasts (processed from NWS forecasts), adjective fire danger, atmospheric stability (Haines 

index), and lightning ignition efficiency (see appendix G). The Haines Index and lightning 

ignition efficiency are not NFDRS products.

The Western Regional Climate Center (WRCC) has recently introduced a RAWS monitoring Internet Web site (WRCC RAWS) that provides short- and long-term data summaries, 

current conditions, wind roses, site metadata, and so forth for most stations (see below and 

also appendix H).

The BLM/NIFC Wildland Fire Management Information System (WFMI) also provides 

RAWS data summaries, but this system is accessed primarily by local dispatch centers when 

using SIGs for their immediate area of operations. Greater detail about data access is provided 

in the Data Retrieval section.

Findings

Dial-up RAWS data are not processed through ASCADS. NWCG requirements are not 

currently satisfied per se; rather they are goals to live into.

Operations, Protocols, and Organization

This section summarizes station standards including RAWS site selection, sensor suite, 

data management, QA/QC, and personnel positions and duties. In pertinent sections, we describe both the standard protocol and the new NFDRS 2000 sampling protocol, maintenance 

program, and classification schemes. In this section, we also tabulate the number of RAWS 

stations by agency and type according to the ASCADS, FS, and NFDRS 2000 schemes. Also 

described are administrative organization and funding. (See also appendix I.)
10 USDA Forest Service RMRS-GTR-119. 2003. 

 Installation and Deployment

Once a site has been selected that meets all criteria, the RAWS can be deployed; involved 

personnel should receive formal training or help from those already trained. Station metadata 

parameters must be determined, recorded, and entered into both ASCADS and WIMS; these 

include slope; aspect; lat/long; elevation; sensor serial numbers; owner agency and unit; fuel 

model(s); current year green-up and freeze dates; and NFDRS indices and components, and 

their breakpoints.

An NFDRS 2000 RAWS should be located on level ground in a large open area with low 

vegetation cover. It should be sited away from dust and moisture sources and distant from 

obstructions such as buildings and trees. It should be oriented in such a way as to receive full 

sunlight for the greatest number of hours per day during the fire season. If positioned on a 

slope, a south or southwest aspect is required.

Sensor Equipment

The basic RAWS sensor suite includes a rain gauge; anemometer; wind vane; air temperature and relative humidity sensor; fuel stick to measure fuel temperature; and an instrument to 

monitor the battery voltage of the data logger or data collection platform (DCP). Optional sensors include a barometer; a fuel moisture sensor that may be combined with the fuel temperature 

stick; and a pyranometer to monitor global solar radiation. Dial-up stations require a modem 

and a cellular telephone. Most RAWS are either Vaisala/Handar or Forest Technology Systems 

(FTS) platforms; however, NPS uses Campbell Scientific Inc. systems as do some States.

The station must be synchronized with coordinated universal time. A GPS unit or a WWV 

synchronization clock is required for RAWS transmissions even though time records themselves are not part of the data stream. Currently as the older model DCPs (FTS 11 and Handar 

540 series) are replaced by new models (FTS 12 and Handar 555 series), the WWV clocks are 

being replaced by GPS units. The older FTS 11 model had neither GPS units nor WWV synchronization clocks; owner/operators had to adjust the clocks in these DCP’s by synchronizing 

them with computer clocks when the station was queried.

Cost is not the only consideration when choosing RAWS equipment: sensors and frames 

must be able to function and survive in remote locations, often under extreme weather conditions. Conformity to a common station standard provides ease of maintenance and calibration 

and lowers system costs in the long term.

Sampling Protocols

Standard Sampling Protocols

The measurements in standard reporting order are:

1. Rain gauge/precipitation (PPT) – tipping bucket, continuous cumulative 0.01 inch increments; some may be heated to melt snow. Mounted at 1 to 6 feet depending on tower 

model.

2. Wind speed (WS) – mph, 10 min mean prior to data transmission. Mounted at 20 feet.

3. Wind direction (WD) – degrees, 10 min mean prior to data transmission. Mounted at 20 

feet.

4. Air temperature (AT) – oF, instantaneous value at time of data transmission. Mounted at 

4 to 8 feet.

5. Fuel temperature (FT - optional) - oF instantaneous value at time of data transmission. 

Mounted at 10 to 12 inches above a prepared ground surface.
USDA Forest Service RMRS-GTR-119. 2003. 11

6. Relative humidity (RH) – percent, 10 min mean prior to data transmission. Mounted at 

4 to 8 feet.

7. Battery voltage (BV) – volts, instantaneous value at time of data transmission. Inside the 

DCP box.

8. Barometric pressure (BP - optional) – inches of Hg, instantaneous value at time of data 

transmission. Mounted at 4 to 8 feet. This sensor is optional.

9. Direction of peak gust (item 10) during hour prior to transmission – degrees.

10. Peak wind speed (gust) – max mph during previous hour prior to data transmission.

11. Fuel moisture (FM - optional) – grams H2O in a 100 g pine dowel, instantaneous value

 at time of transmission. Mounted adjacent to the fuel stick. This sensor is optional.

12. Solar radiation (SR) – watts/m2, instantaneous value at time of data transmission.

 Mounted at 5 to 8 feet above the ground on south side of platform.

Although this sampling protocol is followed by most RAWS at the current time (spring 

2003), the newer Vaisala/Handar 555 and FTS 12s follow a slightly different protocol. (See 

DCP Transmission Protocols below for details.) We have been informed that some stations 

transmit hourly averages of weather data. However, neither the RSFWSU nor the Fire and 

Aviation Management Applications Helpdesk (F&AM Helpdesk) could provide further information.

NFDRS 2000 Sampling Protocol

The new NFDRS update, NWCG NFDRS Weather Station Standards, PMS 426-3, 2000, 

proposes the following standard order for meteorological data transmission:

1. rainfall

2. 10-minute-average wind speed

3. 10-minute-average wind direction

4. air temperature (instantaneous)

5. 10-minute-average relative humidity

6. battery voltage

7. solar radiation (instantaneous)

Important parameters beyond the above basic seven are to be output in the following order:

8. barometric pressure

9. direction of peak wind gust

10. speed of peak gust

11. fuel temperature

12. fuel moisture

Solar radiation (SR) data will soon be used to calculate SOW and fuel moisture—two 

important inputs to the NFDRS model. Parameters such as max/min humidity, max/min air 

temperature, and fuel moisture are extracted from the 24, hourly transmissions prior to the 

13:00 observation.

The NRDRS 2000 standards require and re-emphasize that the RAWS wind speed and 

direction sensors are to be mounted at a height of 20 feet. Due to NRDRS 2000 standards and 

also to new OSHA requirements, the height of wind sensor placement for some FS RAWS has 

been lowered. In the Studies and Surveys section, we discuss the effect of these height changes 

on RAWS data.
12 USDA Forest Service RMRS-GTR-119. 2003. 

Recent Updates to NFDRS 2000 Standards

Three updates were recently made (March 2003) to the NFDRS 2000 Standards (NWCG 

publication PMS 426-3). The Station siting criteria regarding proximity to reflective surfaces 

was reworded for clarification. Also reworded was the wind direction sampling criteria: from a 

10-minute average from 600 samples to 10-minute vector average from 600 samples. Another 

update, perhaps the most significant of the three, involved a change in the solar radiation 

sampling procedure: from an instantaneous, single measurement prior to transmission to a 

calculated 60-minute average using 60 once/min. samples prior to transmission. The instantaneous solar radiation data were randomly erroneous due to spurious reflections impacting the 

sensor. If a reflective cloud happened to be passing at the time of SR measurement, it can lead 

to unrealistically high radiation readings. (An analysis of this effect is presented in the Studies 

and Surveys section). This change will require reprogramming the data collection platform 

and will be implemented during 2003 as station owners and operators conduct annual site 

maintenance (K. Shelley, personal communication 2003; NWCG – NFDRS Weather Station 

Standards, 2003)

Findings on Solar Radiation Data

Questions have been raised as to whether the current SR sampling protocol (instantaneous 

or hour average) and sensor placement (4 to 8 feet) will provide inaccurate data (the authors, 

G. McCurdy of WRCC, and T. Brown of CEFA, personal communications, 2002). We find 

that sensor placement is not optimal for SR measurements, at least on Handar tripod frames 

because the sensor is currently mounted on the top cross beam adjacent to the white or light 

gray rain gauge. Reflections from the rain gauge may also affect SR readings. Hence, it may 

be preferable to raise the solar sensor to the same height as the top rim of the rain gauge or, 

alternatively, place it at the top of the mast. (The advisability of the latter placement would 

depend on mast strength.)

Positions and Responsibilities (RAWS, WIMS, and NFDRS)

RAWS, WIMS, and NFDRS responsibilities are defined and assigned to personnel in fire 

operating plans. (See appendix J. See also the Fire Danger Operating Plan—Arizona Strip 

field office, July, 1999, NFDRS Operating Plan Shasta, USFS Trinity Ranger Unit, April 1999; 

these latter can also be found in the 2002 intermediate-level NFDRS course reference materials.)

NFDRS 2000 Standards

The positions, responsibilities, and duties that appear in the NFDRS 2000 Standards 

(NWCG 2000) handbook are summarized as follows:

1. Station owner/program manager: is responsible for site selection and deployment of new 

stations, maintenance of new and old stations, QA/QC of data, WIMS duties, and response to ASCADS watchdog alerts. (See appendix K.)

2. Local dispatch centers: have a variety of responsibilities that may vary from center to 

center. For example, at the Fort Collins CO/Northern Front Range/Arapahoe-Roosevelt 

NF Dispatch Center, these duties include determining daily fire fighting resource availability; generating incident reports as required; entering required RAWS data into 

WIMS; posting NFDRS indices and components, and so forth (see appendix L). The 

Fort Collins Center has been given the responsibility of operating, managing, and maintaining seven RAWS in their immediate area (appendix J).

3. Field support and first responder: Annual maintenance, emergency repairs within 3 days 

of a breakdown occurrence, maintenance of ASCADS documentation, and so forth. Note 

that there is some overlap with station owner/manager and dispatch center duties. (The 
USDA Forest Service RMRS-GTR-119. 2003. 13

USFS RAWS Web site is an extremely good source of RAWS information; see appendix 

A for Internet address. Links to procedures, FAQ’s, example forms, and tech notes can 

be found on the USFS RAWS Web site; see Field Guide, RAWS 101, and Tech Notes 

items on the Web site.)

4. Agency regional coordinator: has agency RAWS oversight within a regional area (see 

appendix M for detailed regional coordinator responsibilities).

5. Agency coordinator: For the USFS, currently an individual and an assistant whose duties 

include oversight and coordination, such as responding to phone and e-mail queries; ensuring NWCG standards are adhered to; serving on various RAWS-associated working 

groups and teams (fire danger, fire weather, satellite transmission, and so forth); assigning and coordinating station transmission channels and transmission times; and organizing and training personnel in the deployment and operation of a RAWS. The Agency 

Coordinator manages the RAWS Web site, which received 6,680 unique hits in 2002, almost half of these in May and June alone. Operationally the FS RAWS Coordinator also 

functions as a USFS RAWS Helpdesk. (Note that the USFS RAWS help desk is separate 

and distinct from the F&AM help desk.) During FY02, the USFS RAWS Coordinator:

• Responded to roughly 2,000 e-mail queries.

• Responded to 2,000 telephone queries.

• Performed work-related travel: 77 days for fire-related working groups and teams, and 

professional groups.

• Conducted RAWS training/teaching for field operators.

6. Depot technician: is responsible for testing, maintenance, and calibration of sensors at 

the RSFWSU.

7. Depot manager: performs administrative oversight of RSFWSU operations, RAWS station contracts, and RSFWSU personnel.

Findings

RAWS or WIMS-related administration and operational responsibilities are seldom explicitly stated in an individual’s position description. The informal and vague language in these 

position descriptions contains phrases such as weather-related duties or additional duties or 

collateral duties. Often personnel directly involved in RAWS-related operations interpret 

lack of specific duties in these position descriptions as an indication of lack of interest in the 

RAWS program by upper management. Thus, parts of the network are managed and function 

well while others that are not as well-managed function poorly. The result is a lack of or questionable quality in critically needed fire weather data (personal observations; D. Clements, F. 

Hesselbarth, T. Mathewson, and M. Nelson, personal communication 2002).

Local Quality Control and Assurance (QA/QC)

The local owner/operator or a dispatch center person is typically responsible for initial QA/

QC of RAWS data (see above). Depending on the type of service contract, the local operator might also perform the annual sensor exchange and emergency repairs. Responsibilities 

include care and maintenance of the ASCADS and WIMS metadata files, and WIMS daily 

editing for NFDRS runs (e.g., the 13:00 hour data record is flagged from an R to an O). The 

local operator reviews recent data, especially the 13:00 LST observation, to verify reasonableness. Using WIMS/WEB, local personnel are also required to manually add the SOW and the 

lightning activity level (LAL) values to the 13:00 record. Note: the 13:00 RAWS observation 

should be the transmitted RAWS data recorded closest in time to 13:00.

The SOW is manually entered as a code number describing the weather at the time of 

observation. The index or code ranges from 0 (clear) to 9 (thunderstorms in progress). This 
14 USDA Forest Service RMRS-GTR-119. 2003. 

is a critical input to the NFDRS model because many of the model products are based on 

the current observed SOW. For example, steady rain or snow will zero out NFDRS indices 

and components. Currently (spring 2003) the SOW input is based upon a number of sources: 

Web-cameras, local RH and precipitation (if any), or direct field observations. In the future 

SOW will be calculated from SR, RH, and precipitation and entered in WIMS automatically.

The LAL is a measurement of cloud-to-ground lightning activity observed within a 30-mile 

radius of the RAWS observation point. The NFDRS requires two inputs for LAL: the first 

covers the period from when the previous day’s 13:00 observation was taken until midnight, 

and the second covers the period from midnight until the current day’s 13:00 observation 

time. The scale ranges from 1 (no thunderstorms or cumulus clouds) to 6 (dry lightning occurrence). A 5 indicates frequent and intense lightning, thunderstorms, and moderate to heavy 

rain. These data are obtained from the BLM/NIFC Wildland Fire Management Information 

System (WFMI) in the form of maps generated for a given area. Based on this mapped data, 

an estimate of the LAL is manually recorded.

During the NFDRS course held in Lakewood, CO, in April 2003, students were advised 

NOT to enter LAL or human-caused risk into WIMS. No documentation was provided and 

none has been found by the authors of this report (M. Nelson, personal communication, May 

2003. S. Peterson, course instructor, April 2003).

Operating Period

The optimal RAWS operating period for NFDRS requirements is year-round. The minimum 

is for the fire season with a 30-day initialization and equilibration period before the season begins – except for portable fire RAWS, which are usually deployed on a per incident basis. The 

local or regional Fire Management Officer or the GACC meteorologist decides upon the start 

and end of the fire season, which can vary from year to year. Some areas have a split season (for 

example, spring and autumn). Those using data from a station not owned by the user typically 

inform the station owner of their intended use of the data.

Maintenance and Calibration

At least once per year the RAWS sensors must be replaced by newly calibrated, refurbished, 

or repaired units. The replaced sensors are then processed at the RSFWSU (see below). The 

RSFWSU performs all meteorological sensor calibrations and necessary repairs either at the 

Boise Depot or, occasionally, in situ. The RSFWSU provides two, soon to be three, service 

contract options: full ride, depot, and NFDRS 2000 certification.

Service Contracts

Under the full ride contract, personnel from the RSFWSU visit each site once a year to 

perform the required maintenance, relieving local owners/operators of the duty (apart from 

emergency repairs). Under the depot contract, the local operator receives replacement sensors 

from RSFWSU, visits the RAWS, replaces sensors with replacement units, and performs any other 

station repairs. The local operator returns the replaced sensors to the RSFWSU for recalibration.

In the near future, the NIFC depot will begin to provide a third contract option: NFDRS 

2000 certification. This certification will support those stations that are NFDRS 2000 compatible (NWCG 2000). RAWS designated as NFDRS 2000 data providers must be formally 

certified by RSFWSU technicians with the new NFDRS 2000 certification service option. 

Under the NFDRS 2000 certification contract, depot technicians will make site visits once 

per year and perform documented calibration/certification for the site. When the NFDRS 

2000 certification is implemented, the RSFWSU will also continue to support the full-ride and 

depot service contracts. A full-ride service contract costs $2,500 per year (soon to increase 
USDA Forest Service RMRS-GTR-119. 2003. 15

to $2,625 per year); the depot contract is $650 per year (soon to increase to $675 per year); 

and the new NFDRS certification will cost $1,875 per year.

Staffing Needs

Given that almost 1,900 RAWS are deployed across the United States, completing the calibration and repair work is an enormous task. During FY 2001, the RSFWSU processed 221 

nonmeteorological sensors/instruments and 7,880 meteorological sensors, 8,101 total, an average of about 22 per day. (P. Sielaff RSFWSU, personal communication 2002). The average for 

the past 10 years is 35 pieces/day, with a maximum of 11,000+ pieces of equipment processed 

in 1 year (P. Sielaff RSFWSU, personal communication 2002). The nonmeteorological instruments included modems, WWV clocks, display units, GPS units, and battery packs. The busiest 

months of the year are October through March, the nonfire season, when field operators are returning equipment to the depot. RSFWSU staffed 20 people for sensor and equipment maintenance as of July 2002. Eight were employed in-house at the depot itself. Twelve worked in field 

deployments servicing stations under the full ride contract. In addition to regular duties, depot 

staff also conducted research and development on sensors and weather station systems.

Findings

At present, it takes roughly 5 days for local and NIFC staff to respond to equipment failures. If more than 3 days of data are lost, NFDRS model applications must be reinitialized 

and stabilized. Hence, NFDRS modelers recommend that failure be repaired within 3 days. 

Realistically, due to personnel shortages and other assigned duties, response time will continue to be greater than 3 days.

Administrative Organization

Various land management agencies have different funding arrangements for their RAWS. 

The BLM has a centralized approach. Its Washington headquarters provides all funding from 

start-up to continuing operations; all stations are on the full ride contract. The NPS provides 

centralized financial support, but individual Parks must conduct yearly maintenance. The BIA 

has contracted directly with the BLM RSFWSU to provide for full ride maintenance for nearly 

all its stations. Although each of the FWS regions has its own agreement with the BLM, the 

arrangements are similar to those of the NPS. Individual States (usually State forest services) 

must work with the BLM via the USFS for start-up and ongoing operations. Some States deal 

directly with private sector vendors.

Management of the FS RAWS network flows from the Fire and Aviation Management 

(F&AM) Washington DC Office to the Fire (Applied) Operations/Boise, ID, to the Office 

of the FS RAWS Coordinator (currently located in Orifino, ID) and finally to Regional 

Coordinators. For example, in FS Region 2 (Rocky Mountain) the network is owned and 

maintained primarily at the Regional Office level, whereas in Region 3 (Southwest) ownership, management, and maintenance are divided between individual Forests and the Region 

(D. Clement, Region 1, and R. Shindelar, Region 3, personal communication2001). The 

management approach taken in FS Region 3 changed dramatically with the establishment of 

the Southwest GACC Predictive Services Center in 2001. Since the addition of GACC meteorologists, quality assurance and control and station maintenance have improved significantly 

(personal observation; K. Shelley, personal communication 2002).

In many cases, the Regional Coordinator will delegate further to the Forest or Dispatch 

Center level. For example, as indicated previously, in the FS Region 2, personnel in the 

Arapahoe/Roosevelt NF manage the RAWS in the Arapahoe/Roosevelt National Forest. 

When NF staff is not delegated to maintain stations, the Regional Coordinator has to do it. FS 

F&AM supports a user’s help desk for WIMS/KCFast users in Boise, ID. This office is staffed 

during normal working hours.
16 USDA Forest Service RMRS-GTR-119. 2003. 

FS Funding

Funding for Station Purchase, Repair, and Upgrades

Within the FS, each Forest or Region must provide justification and initial local funding to 

purchase a station with its own operating budget. Once a site is purchased and implemented, 

funds for yearly maintenance are then drawn from a separate RAWS fund established at the 

F&AM Washington Office—not from the budgets of individual Forests or Regions. The local and regional area fund support is based upon Annual Operating Plans submitted by FS 

Regions to the FS RAWS Coordinator. An example from Region 9 – Eastern is given in appendix N; note that the plan only includes maintenance costs for depot or full ride contracts. 

Contractual arrangements with the RSFWSU are made directly by the FS F&AM WO. Any 

additional costs associated with RAWS operations—salary, travel, vehicle use, WIMS-related 

duties, and so forth—are borne by the individual Forest or Region. All FS RAWS, except for 

10 in the Umatilla and Malheur National Forests in the Pacific Northwest Region, are maintained through a depot contract.

A typical new RAWS costs about $12,500 to purchase. The Forest Service alone has approximately $10 million invested in RAWS stations based on the RAWS count. This estimate 

includes portable RAWS.

We estimate RAWS operating costs to be approximately $1,350 per station per year, which 

includes the depot contract cost, travel, salary, vehicle use, and so forth. (L. Holsapple, R. 

Powell, D. Clement, personal communication 2002). Using the depot contract as $650 per 

year, and the $1,350, we estimate that the yearly costs to operate FS network at approximately 

$1,068,450 to $1,121,100. (The authors base these estimates on interviews with RAWS personnel and access to RAWS databases.)

Once a RAWS station is purchased and part of a RFSFWSU program, there are no additional acquisition costs. There is no formal provision for station life-cycle funding; currently, 

this is part of the overall RAWS upgrade program (D. Clement, K. Shelley, personal communication 2002). For example, if a sensor or data-logger fails at some point, it is replaced by 

a functioning unit, and repairs are paid out of the depot or full ride service contract. Also, as 

new equipment becomes available, requests to upgrade are made through the annual regional 

maintenance/operating plan. Sometimes these requests are granted and sometimes not. If the 

request is approved, the old equipment is returned to the RSFWSU and the new equipment 

installed at the given station. The latter is paid for out of the maintenance contract. However, if 

a Region wants to upgrade a DCP, the Region must fund the new DCP. Sometimes old equipment is cannibalized. Sometimes the RSFWSU uses old equipment as full replacements for 

stations using older hardware. Except for testing a few sonic anemometers, there has been little 

change in meteorological sensor models over the years. The wind speed and direction instruments used on the portable fire RAWS, however, are single combination speed and direction units.

Funding for WIMS

WIMS is funded by the FS from the top. Traditionally, the FS Washington Office of 

Watershed and Air pays for maintaining and running NIFMID. (Note that F&AM pays for 

RAWS maintenance under the depot contract.) The WIMS reengineering effort is a multiyear 

project that includes development of WIMS/WEB and the upgrade. For FY 2002, $227,000 

was originally budgeted for NIFMID operations, but the actual amount grew to $461,000. 

Discussions are still under way as to where the difference is to come from. In FY2001 

$250,000 was budgeted; in FY2002 the figure grew to $350,000 for WIMS hardware and software re-engineering. (These figures were provided by Michael Barrowcliff and Jeff Barnes, 

National Systems Team, WO F&AM, 2002.) These funds have been provided by F&AM. Due 

to budget reductions in 2002, software upgrades were on hold. However, some hardware upgrades were continuing as of spring 2002. (See also WIMS Upgrades in the RAWS Projects 

Under Development section.)
USDA Forest Service RMRS-GTR-119. 2003. 17

Current Station Classification and Numbers of RAWS

As of summer 2002 the number of RAWS stations had grown to almost 1900. They are 

located throughout the conterminous United States, Alaska, and Hawaii, most are concentrated in the Western States (see fig. 1). In the late 1970s when RAWS were first deployed, 

the BLM and FS informally adopted weather station classification standards (Finklin and 

Fischer 1990); they were formally implemented in the late 1980s (B. Adams, personal 

communication 2002). These weather station classification standards continue to be used 

by ASCADS, the BLM’s initial data handling system. The FS later adopted a number code 

system for different station classes, which is now to be replaced again by a new NFDRS 2000 

classification (NWCG 2000).

Other State and Federal land management agencies use both classification systems because 

both ASCADS and WIMS are used to process and manage RAWS data. In addition to the FS, 

BLM, NPS, and BIA, the ASCADS database also hosts RAWS from agencies such as DOD, 

DOE, FWS, CDF, various State Departments of Natural Resources, and State and private 

forests.

ASCADS Classification Scheme

ASCADS uses five classes for stations (a description of Classes I through IV can also be 

found in Finklin and Fischer 1990):

• Class I: Permanent RAWS that operate year-round and receive the highest maintenance 

priority. Instrument suite includes tipping bucket rain gauge, anemometer, wind vane, 

air temperature/relative humidity sensor, fuel temperature sensor, barometer, and fuel 

moisture sensor. Depending on management needs, additional sensors can be added (for 

example, soil temperature and moisture probes, stream water gauge level, or air pollution monitoring instruments).

• Class II: Semipermanent RAWS that operate only during the fire season. Depending on 

immediate fire conditions these have either primary or secondary maintenance priority. 

The sensor suite is the same as for Class I stations.

• Class III: Portable RAWS used for controlled burn studies, prescribed burns, or special 

projects as needed. They are only deployed on a temporary basis. After use, they are 

returned to program owners. The BLM Class III units are cached at RSFWSU or redeployed to another site or project. All Class III units have secondary maintenance priority. 

The sensor complement is the same as for Class I.

• Class IV: These weather stations are essentially the same as Class III units but use radio 

communications to transmit data via either a voice synthesizer or RS232 port. They are 

used for the same purposes as Class III and can carry the same sensor suite.

• Class IX: This classification is reserved for stations deployed on military installations 

and at DOE facilities. It is hardly used because the stations in this classification are so 

few in number. The 15 Class IX USFS stations are all portables, perhaps deployed to 

Department of Defense (DOD) and Department of Energy (DOE) sites on loan for special projects or circumstances.

Table 2 tabulates the total number of stations counted under the ASCADS classification 

system.

Current Forest Service Classification Scheme

Table 3 gives the FS-coded count by agency and class as of May 2002. We extracted the 

information from raw data provided by the F&AM Applications Helpdesk.

The following agency and station types were coded according to the current FS classification system:
18 USDA Forest Service RMRS-GTR-119. 2003. 

Table 2: Number of RAWS stations per ASCADS count,1 April, 2002.

II IV

I Semi- III Radio IX

Agency/Class Permanent Permanent Portable Communications Portable Total

USFS 73 611 52 85 15 836

BLM 64 246 34 41 385

NPS 12 109 6 5 132

BIA 3 44 34 5 86

States2 3 181 4 20 208

Other3 2 138 4 7 40 191

Total 157 1329 134 163 55 1838

1

 Raw data was obtained from ASCADS; see report for Current Station Classification Systems.

2

 States: CDF+DNR+S&PF.

3

 Other: other federal agencies such as DOD, DOE, FWS, and others

Table 3: Number of RAWS stations per FS count,1 April, 2002.

Agency MnF2 MF3 SnF4 SF5 Total Historic

USFS (1) 20 201 65 496 782 265

BLM (2) 3 25 43 270 341 102

NPS (3) 2 85 8 85 180 56

BIA (4) 0 17 2 27 46 1

States (5) 8 231 8 101 348 148

Other6 (6+7+8) 29 74 16 60 179 39

Total 62 633 142 1039 1876 611

1

 Raw data obtained from F&AM Helpdesk.

2

 MnF: manual,non-NFDRS

3

 MF: manual, NFDRS

4

 SnF: satellite, non-NFDRS

5

 SF: satellite, NFDRS

6

 Other: other fed and city, county, and district

Agency Number Agency

1 USDA FS

2 USDI BLM

3 USDI NPS

4 USDI BIA

5 State

6 City, county, district

7 Private or commercial

8 Other Federal

9 Unknown

For the purpose of tabulating the data in table 3, we combined agency codes 6, 7, and 8 

(above) and included them in the Other category.

Station types or classes are coded as follows:

Code number Type/class

1 Manual, non-NFDRS (manual person must visit site)

2 Manual, NFDRS (note that NFDS here indicates the old NDRS 

 standard and not the new NFDRS 2000 standard)

3 RAWS, satellite, non-NFDRS

4 RAWS, satellite, NFDRS

5 RAWS, nonsatellite, non-NFDRS (nonsatellite: dial-up, and so forth)

6 RAWS, nonsatellite, NFDRS
USDA Forest Service RMRS-GTR-119. 2003. 19

7 Historic, nonactive

8 Dummy (temporary or test bed stations)

9 Unknown

For the count in table 3, we combined non-NFDRS station types 1 and 5 (above). We also 

combined NFDRS station Types 2 and 6 (above).

We excluded from the count in table 3 the 34 stations that were grouped into the Type 

8 category above; these came from a cross-section of agencies, including Other. Although 

information for Type 9 stations was obtainable, we did not include these stations in table 3. 

This lowered the historical nonactive count by more than 1,100. Apparently, these Type 9 stations had been deployed for one to four fire seasons from the late 1960s through the 1990s. 

No agency currently claims ownership of such Type 9 stations. Hence, the Historic column 

in table 3 refers to stations that are no longer active but claimed by individual agencies. Their 

archived data are also still available through KCFast.

The total number of stations in table 2 for the ASCADS count is slightly less than the 

count provided by WIMS/F&AM Helpdesk in table 3—1,876 versus 1,838 (tables 2 and 3 

respectively). Comparing the number of stations listed in the two databases by type or class 

proved somewhat difficult due to the different classification schemes and agency information. 

However, the results are presented in table 4; the highlighted pairs indicate similar counts for 

similar classes from the two databases. From table 4 it is evident that an exact determination 

of RAWS stations is not precisely known.

New NFDRS 2000 Classification Scheme

New station classes and minimum standards for NFDRS 2000 are as follows:

• NFDRS – Year-round Stations:

} Operate 12 months to support wildland fire season

} Are equipped with minimum NFDRS sensor suite (see above)

} Meet minimum QA requirements

} Deliver hourly readings to WIMS via GOES (24/7) and ASCADS

} Provide the only data for NFDRS calculations processed regularly in WIMS

} Use a heated or weighing rain gauge as necessary

• NFDRS – Seasonal Stations:

} Operate to support fire season (but can operate 12 months)

} Are equipped with minimum NFDRS sensor suite (see above)

} Meet minimum QA requirements

Table 4: Comparison of RAWS station counts from F&AM Helpdesk (WIMS) 

and ASCADS, April, 2002. 

ASCADS WIMS ASCADS WIMS

Agency 1+2 SF+MF 3+4 MnF+SnF

USFS 684 697 137 85

BLM 310 295 75 46

NPS 121 170 11 10

BIA 47 44 39 2

States 184 332 24 16

Other 140 134 11 45

Totals:

ASCADS 1838

F&AM 1876
20 USDA Forest Service RMRS-GTR-119. 2003. 

} Deliver hourly readings to WIMS via GOES (24/7) and ASCADS

} Provide data for NFDRS calculations that are processed regularly in WIMS (during 

fire season operational period)

• Other:

} Includes all other stations that provide accurate weather data but do not meet NFDRS 

standards, hence are not used for NFDRS calculations.

• Manual Stations:

} Manual stations (telephone telemetry via the HUB or queried directly by local operators) are still used and provide basic 13:00 hour NFDRS inputs to WIMS during operational seasons: transmits one observation per day. Many of these are being upgraded.

Findings on Conformance with NFDRS 2000 Standards

Although the NFDRS 2000 standards above are being implemented across the network, we 

found that a station’s current classification as an NFDRS station is based on the old standard 

and may not fully conform to the NFDRS 2000 standards. We also found that there is no official 

authority or entity to track or enforce compliance with the NFDRS 2000 standards, nor is there a 

deadline for the transition from NFDRS station to NFDRS 2000 station to be completed.

Use of RAWS Data in Fire-Related Applications

Brown and others (2001) identified four primary uses for RAWS data: NFDRS, fire behavior, fire use, and other. The first three categories are the primary justification for the RAWS 

network. Other refers to RAWS data use by agencies, businesses, universities, and miscellaneous groups for assessments other than fire. For example, the RAWS data set is one of many 

that are used for initialization and verification of mesoscale weather models used to generate higher 

resolution fire weather predictions (FCAMMS). (See Additional Uses of RAWS Data below.)

NFDRS Use

NFDRS use includes calculation of daily fire danger indices components and ratings: 

RAWS weather data provide the primary daily input used to parameterize the NFDRS model 

to generate daily fire danger ratings, indices, and components. Other NFDRS inputs include 

fuel model and types, slope and aspect, latitude, and average annual precipitation. NFDRS 

also includes intermediate products such as live and dead fuel moistures and lightning and human-caused occurrence indices (LOI and HCOI respectively, see Glossary). These two indices 

are considered indicators of ignition possibility and are independent of fire danger indices and 

components. appendix B provides an overview of the NFDRS model.

Fire Behavior

Fire behavior includes assessing real events and/or modeling fire spread and intensities for 

planning purposes (for example, for an initial attack or additional fire fighter deployments). 

BehavePlus and FARSITE (Fire Area Simulator) are the current fire behavior and fire spread 

models used by the FS. BehavePlus is used to predict incident wildland or prescribed fire 

behavior for fire management purposes. It uses site-specific input data, including weather, to 

predict fire behavior for a point in time and space. FARSITE is a model used to simulate the 

spread and behavior of fire in space and time for heterogeneous terrain, fuels, and weather. It 

is run on a PC but requires the support of ArcView, a Geographic Information System (GIS) 
USDA Forest Service RMRS-GTR-119. 2003. 21

application. FireFamily Plus (FF+) is a PC-based application that integrates historical fire 

occurrence with climatological and current RAWS data for calculating fire danger indices 

and components, fire business troubleshooting, analysis, gaming, or training. It can uniquely 

provide historical, seasonal, and current perspectives of fire danger that are either site-specific 

or weather-zone specific.

Fire Use

Fire use refers to management practices such as prescribed burning. Short- and long-term 

fire business planning (for example, managing preparedness levels) entails additional fire use 

applications supported with RAWS data products. For short-term planning, RAWS data is 

used for: determining staffing levels; duty hours; fire behavior modeling; fire danger rating 

(daily and short-term forecasts); tactical planning during a fire; prescribed burn go/no-go 

decisions; prepositioning of fire fighting/containment resources; and weather information to 

incident commanders and fire crews. There are also many management decisions based on 

RAWS data and NFDRS output: dispatch contingency plans for wildfires at different fire danger levels, fire danger preparedness levels, forest closure criteria, seasonal trend analyses, and 

as input for the National Fire Management Analysis System (NFMAS).

For longer-term planning, RAWS data provide for: severity funding requests; budget preparation; fire resource needs; planning for fire prevention and presuppression; restoration of forest and range lands; understanding seasonal droughts; modeling; seasonal fire danger analysis; 

and long-term climate analysis.

Data Retrieval

RAWS data can be accessed through WRCC and through WIMS/KCFast. RAWS data are 

also available via the NWS, ASCADS, WFMI, WFAST, and through the map-intensive Web 

site operated by the USGS Geospatial Multi-Agency Coordination Group (GeoMAC). Some 

RAWS data gateways archive data and others only store it for short periods. For example, 

ASCADS archives data for only 30 days. GeoMAC and the NWS provide the most recent 48 

hours of data for easy retrieval.

Except for ASCADS, the above data gateways are accessible online; ASCADS access is 

via a terminal emulator. Appendix A provides Web addresses along with brief descriptions of 

each gateway. Additional details can also be found in appendix O.

 Automatic Sorting, Conversion, and Distribution System 

(ASCADS)

ASCADS is the single entry point for all satellite-transmitted RAWS data. After ASCADS 

ingests RAWS data from the DomSat Receive System (DRS), it sorts and re-formats it into a 

relational database. ASCADS then distributes the processed data to the BLM/NIFC/WFMI; 

the NIFMID/KCFast; the NIFMID/WIMS; the NWS in Boise, ID; and the WRCC. In addition to hourly weather observations, ASCADS provides extensive metadata information for 

every station, including platform descriptions; location descriptions; site visit descriptions; 

maintenance history; and sensor complement and type. ASCADS stores the metadata permanently in addition to the weather data for 30 days. It also allows for text notation of station 

changes.

Access

ASCADS is menu-driven and gives dial-in users the ability to view and print reports of the 

most current RAWS site information, including site-specific watchdog alerts, recent weather 
22 USDA Forest Service RMRS-GTR-119. 2003. 

data, and station metadata. Access to ASCADS is via a terminal emulator package such as 

Powerterm, Webterm, or Netterm; the password and username required for access can be 

obtained from the agency-specific RAWS coordinator. To facilitate display, associated data 

have been grouped into several screens. In appendix F, we provide a diagram of the data flow 

and menu choices (user interface) adapted from the ASCADS Field Users Guide Version 2.1 

(2002).

Watchdog Function

The ASCADS watchdog is an important function within the database. It advises the owner/

operator of invalid data (for example, data values that are out of range, missing, or not changing) and flags transmission errors or failures. The owner/operator must log onto ASCADS to 

obtain the most current advisories and data flags, which are limited to the last 2 days. The 

actual numbers defining the watchdog criteria vary from station to station; from region to region; and seasonally for any given station. For some sensors and data elements, such as wind 

speed and air temperature, the upper and lower limits are entered in ASCADS as part of the 

station’s meta data. For others, such as rain gauge and solar radiation, there are no entries. 

There appears to be no watchdog master list short of examining the meta-data for all stations 

one at a time. In appendix P, we provide a list of alerts, data flags, and criteria for the basic 

RAWS 12 data set (personal communication, K. McGillivary). This list was provided by the 

BLM/NIFC/Applications Software Group, which is the group that maintains and programs 

ASCADS (P. Sielaff, RSFWSU/BLM/NIFC, personal communication, 2002).

Upgrades

Beginning in April 2003, ASCADS will be undergoing its first upgrade. The initial five 

upgrades are described in RAWS Projects Under Development section. There have also been 

extensive discussions leading to the draft of new ASCADS Business Rules for the two main 

user groups: weather data users and support/maintenance personnel. These rules, ASCADS 

Business Rules (Straub 2002), primarily concern formalizing procedures for maintaining 

RAWS metadata files and notifying users of any changes to these files.

Findings

ASCADS Helpdesk. The RSFWSU and the BLM/NIFC/National Systems Development 

group, in effect, act as the ASCADS Helpdesk but only during normal working hours. For example, no one was available to provide assistance during the weekend of June 8-9, 2002, when 

ASCADS crashed. It points to the need for a formal ASCADS help desk operational 24 hours 

per day, at least during fire season.

ASCADS Watchdog Criteria. We were unable to locate actual ASCADS watchdog criteria (minimum/maximum thresholds, maximum time limit without a change, and so forth) 

short of examining each station from within ASCADS. Even then, some data elements had no 

criteria entered while others did. The ASCADS Programming/Development Team was able to 

provide a list of qualitative information, and these are given in appendix P. Are the quantitative criteria hard coded for each station, taking into account different locations and changing 

seasons? Or are they entered by regional and/or local RAWS personnel as part of a station’s 

metadata? We have been unable to determine this.

Western Regional Climate Center (WRCC)

WRCC is one of six regional climate centers in the United States. It is administered by 

NOAA’s National Climate Data Center and NESDIS. The mission of WRCC is to archive 

and distribute climate data and information, facilitate, and improve use of such information 

for decisionmaking, conduct applied research related to climate, and improve coordination of 

climate-related activities from the local to the national level. The WRCC receives formatted 
USDA Forest Service RMRS-GTR-119. 2003. 23

RAWS data from ASCADS, retabulates and reformats the data, and archives them. The center 

is a major long-term data archive for all RAWS in the United States, storing all 24 hourly observations per day, including the 13:00-hour observation used for NFDRS calculations.

Data Management

ASCADS sends meteorological data for all active RAWS to WRCC though a dedicated 

Internet line. The data, sent every 15 minutes, are automatically assimilated, reformatted, and 

saved in the WRCC database using their special in-house format. If the RAWS metadata has 

changed, WRCC receives a metadata file from ASCADS within 15 minutes of the update. 

This file is cross-referenced against the WRCC metafile of that station, and the WRCC file is 

updated. WRCC keeps the original NESDIS ID and NWS ID received from ASCADS for all 

RAWS, but it archives data based on its own WRCC ID system. The metadata file of each station archived at WRCC also contains the information contained in the metadata file provided 

by ASCADS.

The WRCC database maintains a Station Metadata Summary for each RAWS that contains 

information about all NESDIS IDs used at different times in the history of a particular station. 

This information is cross-referenced with another table, which tracks the history of individual 

NESDIS IDs with respect to their different locations over time and the duration of their operation. The fact that stations and transmitters are mixed has lead to the wrong data being aligned 

with the wrong location. Finally, the WRCC conducts ongoing QA/QC of incoming RAWS 

weather data; these criteria are listed in Brown and others (2002).

Archival Function

The WRCC database is the only systemwide archive of long-term hourly data from RAWS. 

It contains complete data records for all active and inactive RAWS. In some instances, these 

records go back more than 20 years. Other data archives such as ASCADS, WIMS/KCFast, 

and the University of Utah maintain only partial records. WIMS/KCFast keeps hourly records 

for up to 18 months while also supporting the long-term archive of manually adjusted 13:00 

hour observations for each station. The University of Utah maintains an hourly RAWS database for the past 5 years only.

A unique aspect of the WRCC RAWS data archive, as compared to other RAWS databases, 

is that the historical record is documented for each station and thoroughly examined and 

quality assured for consistency. This is important because the RAWS NESDIS ID used by 

ASCADS and other information systems to track individual stations actually identifies specific satellite equipment rather than station locations. The six-digit NWS ID identifies station 

location but may also change through time. Circumstance may require the station to receive 

a new NESDIS ID despite the fact that its physical location remains the same. This creates 

discontinuity and confusion in the data record associated with a particular NESDIS ID. The 

research group at WRCC has spent an enormous amount of effort to recover the history of 

each NESDIS ID and restore the actual data records of all individual RAWS to ensure that all 

meteorological data archived for a particular RAWS have actually been measured at the location of that station. This type of work has not been conducted by other information systems 

except perhaps the one recently developed at the University of Utah.

Access

There are two ways to retrieve RAWS data from the WRCC: through special arrangements 

with WRCC or through the new WRCC Web site called the RAWS USA Climate Archive. 

This site allows the user to select a RAWS from either a list or a clickable map. Further options 

include: different graphing choices, tabulated data, and date ranges (see appendix A for the 

Web address). The site is similar to the BLM/NIFC WFMI site (see below). Development of 

this Web site began in 1999 and has been an ongoing project in collaboration with RSFWSU, 

which has provided limited funding as part of its long-term strategic plan. Some portions of 
24 USDA Forest Service RMRS-GTR-119. 2003. 

the site are still under construction. (See a diagram of data flow, search options, and criteria in 

appendix H.) The existence of this Web site is not widely known and information about it has 

been mainly through word of mouth.

Clearly, the best method for obtaining data from multiple sites and/or extended date ranges 

is to contact the WRCC directly and request data files. The Web site provides information such 

as telephone numbers and other products. (See appendix A for the Web site address.)

Findings

A number of questions have been raised concerning the WRCC and ASCADS:

1. Should personnel be assigned to WRCC to manage RAWS metadata function as human 

watchdogs? There are considerable gaps in the ASCADS metadata base, but the planned 

integration of ASCADS and WIMS metadata would make this a moot point. If they are 

not integrated, then we find that, given the size and complexity of the database and the 

long learning curve on understanding the metadata issues, such a position would have to 

be permanently based at the Climate Center.

2. Should the WRCC play a more significant role in how ASCADS will function and how it 

will look in the short- and long-term future? The WRCC has already passed on recommendations addressing this subject to RSFWSU and the BLM/NIFC/National Systems 

Development Unit.

3. Should the WRCC take over some functions of ASCADS such as data ingestion and 

distribution? The WRCC seems disinclined to take on this role (G. McCurdy and K. 

Redmond, personal communication 2002). But the WRCC is willing to develop a wider 

range of fire weather-related products such as data analysis, QA/QC analyses, and spatial and network analyses. Such work has been recommended in studies carried out by 

Marsha (2002a, b), Brown and Hall (1997), Brown and others (2001), Brown and Hall 

(2001), and Brown and others (2002).

4. Current WRCC QA/QC of RAWS data remains at WRCC. There is no mechanism to 

update other databases (i.e., WIMS, ASCADS, etc.) with WRCC corrected data.

National Interagency Fire Management Integrated Database 

(NIFMID: WIMS/KCFast)

The National Interagency Fire Management Integrated Database (NIFMID) is an ORACLE 

application that contains historic fire weather and fire occurrence information. It serves as a 

database warehouse for archiving fire business/management information, including RAWS 

weather observations. All modules contained within NIFMID are accessible via the F&AM 

Web site (see appendix A for the Web address). A diagrammatic description of NIFMID and 

its modules is provided in appendix C-1. Accessing the NIFMID/WIMS/(KCFast database 

allows member users to retrieve historical weather, fire occurrence, and station catalog data. 

(For more details, see appendix A in the Fire Family Plus Users Guide V2.0 (RMRS 2000). 

Other modules in NIFMID include report generators and forms (for example, the national fire 

situation report, incident situation reports, and aircraft use), and firefighter pocket cards (see 

example of pocket cards in appendix E).

WIMS

The Weather Information Management System (WIMS) is also included within NFMID. 

WIMS is a weather information database that has hosted the NFDRS model(s) since 1993 (see 

appendix B and Current Status, Operations, and Protocols for more details on NFDRS and 

its relation to WIMS). WIMS produces the daily and forecasted fire danger indices and components using the NFDRS model(s). The main difference between WIMS and KCFast is that 

WIMS allows edits or new inputs to be made to these data or metadata sets; for more detail, 
USDA Forest Service RMRS-GTR-119. 2003. 25

see the WIMS/WEB Application User Guide, June 2001; appendix A of the Fire Family Plus 

Users Guide V2.0 (RMRS 2000).

Up to September 2001 WIMS was accessed via a terminal emulator, in the same way that 

users access ASCADS today (see above). The WIMS system uses two servers – an IBM mainframe and an IBM RISC6000/AIX; the IBM mainframe hosts the ORACLE database and 

the AIX machine hosts the Web/application server. Both WIMS and NIFMID are physically 

located at the USDA National Information Technology Center (NITC) in Kansas City, MO. 

Access is 24 hours a day, 7 days a week.

In June 2001, an Internet-based and interactive version of WIMS, the WIMS/WEB, was 

released (for the user interface with a hierarchy of menus and forms, see appendix C-2). The 

WIMS/WEB user interface and look are similar to that of WIMS. WIMS/WEB is a Webbased interactive package that allows the user to enter and manipulate data; retrieve weather 

information, fire weather forecasts, and smoke management forecasts; display NFDRS indices 

and components; and enter and retrieve point and trend forecasts and other NWS products.

Access to both WIMS and KCFast is initially the same; one can use the same user ID and 

password for both. To obtain a WIMS/KCFast user name and password, Forest Service personnel must contact their Regional Computer Security office to apply and to arrange for payment. At the time of this report (spring 2003), the fee is about $1.00 per day. With the move of 

the WIMS/NIFMID database to a dedicated server (see below: WIMS Upgrades) there will 

be no user fee.

KCFast

The NIFMID Kansas City Fire Access Software (KCFast) database stores RAWS data in 

two formats: The 1972 format that contains all the recorded 13:00 hour observations for the 

entire period of record, and the 1998 format that retains all the hourly observations for 18 

months, including fire occurrence information (accessed via a different link within KCFast) 

and statistics by Region, Forest, and so forth. KCFast does not allow edits or new inputs to be 

made to these data or metadata sets. (See appendix Q for KCFast Data File Formats.)

Other Modules

Other modules that require weather information are Interagency Situation Report (SIT) (appendix R); the Incident Report Form 209 (appendix S); and Pocket Cards (appendix E). The 

SIT and Form 209 include general weather data during an incident, and pocket cards include 

graphs of NFDRS output as well as fire occurrence over time. The Aviation Management 

Information System (AMIS) and the Federal Excess Property Management System (FEPMIS) 

are also part of NIFMID, but neither requires weather data.

National Weather Service (NWS)

The National Weather Service provides a short-term RAWS data archive for the last 48 

hours. The Boise Fire Weather/National Fire Page provides links to RAWS observations, data 

summaries, model output statistics, RAWS location information, current conditions, WFAS, 

satellite imagery, and various fire indices. (See appendix A for the Web address for the Boise 

Fire Weather/National Fire Page.)

BLM/NIFC Wildland Fire Management Information (WFMI)

The WFMI is a Web-based fire weather database managed by the BLM in Boise, ID. It 

replaced the BLM’s Initial Attack Management System (IAMS) in the late 1990s. WFMI 

receives fire weather data from ASCADS hourly. The user can request access to weather data 

summaries in a tabular or graphical format. Summaries of the standard RAWS observations 

can be accessed for periods from the most recent to the last 90 days. Also available are clickable maps for RAWS data access, station locations (latitude/longitude), and site descriptions. 
26 USDA Forest Service RMRS-GTR-119. 2003. 

The site descriptions consist of general information about the individual site: name, owner, 

point of contact, location, slope, aspect, vegetation, cover class, elevation, climate zone, ID 

numbers, sensor calibration or replacement dates, and so forth.

Also available at this site is information about local lightning activity (mapped strikes); fire 

reporting (restricted to BLM users); aviation (military training routes, FAA Airports, agency 

airbases; Very High Frequency Omnidirectional Radio Range (VOR) locations; and Dispatch 

Mission Planning and contacts for Aviation Wildland Firefighting resources; firefighter pocket 

cards (the same site linked from the F&AM Web application[s] page), and fire planning (for 

example, developing prevention and fuels management programs).

Wildland Fire Assessment System (WFAS)

WFAS is not an application to retrieve RAWS data but a Web-based interface to display 

NFDRS products. It generates and displays daily maps of selected fire weather parameters and 

fire danger indices and components. It also maps daily and forecast adjective fire danger ratings. WFAS queries WIMS every afternoon to generate these maps from current weather observations and NFDRS products. Each afternoon IMET forecasters from the NWS view these 

products and issue trend forecasts for fire weather zones. WIMS processes these forecasts into 

next-day index and component predictions. (See appendix G for details.)

The WFAS Observed (and Forecast) Fire Potential Index (FPI) maps are relatively new 

products; they are experimental as of August 2002. These maps use satellite-derived greenness indices, an NFDRS fuel model map (both at 1 km resolution), and an interpolated 10-

hour time-lag fuel map as drivers to weight the relative influence of live and dead vegetation 

on fire potential. The 10-hour fuel moistures are calculated from weather station data and 

interpolated to 1 km resolutions. The FPI ranges from 0 (low) to 100 (high). The FPI appears 

to be strongly correlated with fire occurrence and can describe fire danger potential from a 

regional scale to a few square kilometers (Burgan and others 1998).

Geospatial Multi-Agency Coordination Group (GeoMAC)

The GeoMAC Web site was developed by USGS and implemented in 2001 in response to the 2000 fire season. During the 2000 fire season, 122,827 fires burned an estimated 8,422,237 acres along with hundreds of structures and valuable natural resources 

(North Central Research Station 2001). Over 25,000 firefighters, 900 fire engines, 200 

helicopters, and all available air tankers were deployed. Long-term weather forecasts indicated 

that the hot, dry conditions throughout the Western United States would continue until fall 

weather brought enough rain to extinguish the large fires. Across the West, geographic fire 

coordination centers set priorities for deployment of firefighting resources based on human 

safety, protection of property, and natural resources. Determining these priorities required 

more information than provided by the existing standard printed maps and situation reports, 

fire managers decided that a visual representation of the active fires would give managers a better idea of where to focus resources. So they requested an application that would provide realtime geo-spatial information on the status, location, and proximity of wildfires to life, property, 

and infrastructure—hence, the GeoMAC.

GeoMAC is a map-intensive Web site. One of many options allows agency users and the 

public to access the last 24 hours of transmitted RAWS weather data via NWS links. If a 

particular station transmits only once per day, the 13:00 (LST) observation is provided. The 

RAWS sites can be displayed on a clickable map and are hyperlinked to the NWS database 

in Boise, ID. GeoMAC displays various information layers such as a situation report of active fires; fire perimeters; RAWS weather data; major cities, roads, lakes, and streams; and so 

forth. For detecting active fires, it can display thermal satellite images. (Appendix T provides 

a flow chart of GeoMAC choices, maps, and active layers). 
USDA Forest Service RMRS-GTR-119. 2003. 27

Findings

As in the case of the WRCC Web site, no official release information concerning GeoMAC 

use and standards was received by FS Dispatch Centers (at least not by Fort Collins Dispatch). 

There appears to be no mechanism for informing local Dispatch Centers about new ways (and systems under development) to access RAWS data.

RAWS Projects Under Development

A number of projects are currently under development. Primarily, they pertain to new 

ways of accessing and displaying RAWS data via a Web-based interface. Both BLM and FS 

plan to reengineer and upgrade their RAWS databases (ASCADS and WIMS respectively). 

The RSFWSU plans to deploy a Direct Readout Ground Station (DRGS) at the National 

Interagency Fire Center (NIFC) in Boise, ID, as a backup to the GOES-DOMSAT system 

(field test phase as of October 2003). Data sampling will be increased from once per hour to 

every 30 minutes and eventually to once every 15 minutes. A new portable fire RAWS is under 

development.

As covered previously, the Western Regional Climate Center (WRCC) is in the process 

of developing a new Web-based RAWS data monitoring application called WRCC RAWS 

USA. A similar site has been developed as a collaborative project between the RMACC, 

the Eastern Great Basin GACC, and the University of Utah. Also being established are 

mesoscale weather forecasting centers (FCAMMS). Such a center has been in operation in 

the Pacific Northwest for some years and new centers are being established in the Rocky 

Mountain Region, California and Eastern Great Basin, the North Central Great Plains, and 

in the Southeast.

NFDRS 2000 Standards

As we have already discussed, the NFDRS 2000 standards are intended to standardize 

RAWS procedures across agencies for the entire network. As part of the NFDRS 2000 update, 

ongoing hardware upgrades are continuing. Although the sensor suite will stay essentially the 

same, new methods are being developed to calculate fuel moisture and SOW. The new operations protocols are briefly described in Operations, Protocols, and Organization section above 

and in detail in appendix I.

The RSFWSU Strategic Plan in Support of NFDRS 2000 

Standards

In January 2002, a RSFWSU Strategic Plan was drafted by the BLM in cooperation with 

a number of other land management partners (FS, FWS, NPS, and BIA). Several issues were 

addressed and recommendations made relative to improvements in hardware and software 

technology and maintenance, in support of the NFDRS 2000 update. The Strategic Plan was 

further refined for the short term by the RSFWSU and the Systems Development Unit at the 

end of June 2002.

The proposed long-term upgrades call for an ASCADS with new hardware, software, and 

a mapping module, redundant data entry pathways (from DOMSAT as well as directly from 

GOES), shared databases with WIMS, and improved database capabilities (in other words, 

site photographs, metadata, and online accessibility). The secondary data transmission path 

would be via a Direct Readout Ground Station (DRGS; item 5 below). The DRGS would be 
28 USDA Forest Service RMRS-GTR-119. 2003. 

able to mimic the GOES Data Collection System at Wallops Island by monitoring the GOES 

directly from NIFC/Boise.

Long-Term Upgrades to ASCADS

A meeting of the RSFWSU and ASCADS Systems Development team in Boise, ID, was 

held on June 27, 2002, in Boise, ID (meeting notes and P. Sielaff, personal communication 2002). 

Five ‘must-have’ upgrades or patches were identified to be implemented as soon as possible:

1. Increase number of transmissions to four per hour (15-minute transmission capability) 

with 5-second transmission windows (we note that this implies a transmission baud rate 

greater than the current 100 baud).

2. Increase the number of ASCADS data elements to 64 user-defined elements with the ability to display and distribute these additional elements for some stations. Standardization 

issues were not addressed.

3. Include a NFDRS (YES/NO) field in station metadata to advertise NFDRS 2000 compatibility.

4. Reconfigure ASCADS with a Web-based interface.

5. Interface ASCADS with a DRGS.

These RSFWSU Strategic Plan upgrades have now been agreed upon to essentially define 

the initial upgraded ASCADS configuration. Release is scheduled for April 2003 followed by 

a field testing prior to fire season.

In addition to the above critical modifications, RSFWSU identified a number of other requirements to be included in ASCADS in the future; among these were:

• Increased Watchdog capabilities

} Alerts to be e-mailed to more than one user

} Notification to multiple users if an NFDRS station goes offline or a sensor fails

• Mapping capability

} User-generated maps showing RAWS by State, Region, and so forth

} Increased report capabilities for users

• Property management reports

• Better functionality with user Annual Operating Plans

• Monthly maintenance calendar (another option off the main menu)

• Maintenance and/or improvement in ASCADS response speed with improvements in 

hardware and software

• Redefinition of the Station Classification database field to document new NFDRS 2000 

standards

• Daily e-mails to notify identified users if annual calibration has not been performed for 

NFDRS 2000 stations

• Data shutdown option for NFDRS 2000 stations if annual calibration has not been completed

• Shutdown authority to RSFWSU for any RAWS coming through ASCADS

• Easier access into ASCADS in the Unit and/or Agency database fields (users with multiple jurisdiction currently have to trick the system)

• Implementation of an upgraded user-friendly interface.

As of mid-April 2003 the ASCADS database was moved to a new and faster server; in 

addition users must now use the SecureNetTerm terminal emulator. USDA Forest Service 

users must also obtain a new ASCADS profile (username and password) prior to setting up 

SecureNetTerm and connecting to ASCADS. Only one of the priority patch items (see above) 
USDA Forest Service RMRS-GTR-119. 2003. 29

is being implemented as of June 2003, and that is the DRGS, which has been installed but is 

still undergoing testing (B. Adams, personal communication June 2003).

Increase in Transmission Frequencies and Rates

Under the NFDRS 2000 standards, fire danger indices and components (BI, IC, ERC, and 

SC; see Glossary and appendix B for definitions) will be generated four times a day rather than 

only once. Some RAWS stations are being reprogrammed to transmit at 300 baud every 15 or 

30 minutes. With the introduction of faster data transmission rates and frequency, RAWS data 

could be used to drive fire behavior models (for example, BehavePlus 1.0). New equipment upgrades are helping to make such applications possible, but the RSFWSU Strategic Plan notes 

that not all stations in the network would require this kind of sophistication.

RSFWSU had planned to test four transmissions per hour (that is, once every 15 minutes) at 

300 baud during the 2002 fire season in cooperation with fire behavior analysts. However, preliminary work indicated that Wallops Island and WIMS could not handle the amount of data 

being sent. In addition, Wallops Island was experiencing problems in demodulating the 300 

baud rate signal. The result was that stations transmitting at 300 baud missed transmissions 

frequently, with no regular pattern. This problem persists as of early spring 2003. As a result, 

several RAWS already transmitting at 300 baud were reassigned to 100 baud rate channels at 

the beginning of the 2002 fire season (K.Shelley, C. Maxwell, personal communication 2002). 

As of mid-May 2003 NOAA/NESDIS engineers believe they have resolved these problems 

with the 300 baud transmission rate. Limited testing has been conducted by the RSFWSU 

subsequent to the repairs at Wallops Island and vast improvement has been noted (B. Adams, 

personal communication June 2003; see also the FS RAWS Web site link to RAWS News). The 

authors have also observed a significant decrease in the number of missed transmissions from 

the Fernberg, MN super-RAWS station (on 300 baud since winter 2001-2002).

IWOS Development

Development of the Incident Weather Observing System (IWOS) is under way; it will replace 

the aging portable Fire RAWS (FRWS). The new system will also be a portable RAWS with 

the same sensor suite. In addition to the hourly observations transmitted via GOES, IWOS will 

be accessible via a hand-held radio to obtain current information. If critical thresholds are exceeded, it will also be able to provide alerts using a voice synthesizer and a radio.

WIMS Upgrades

Upgrades to WIMS will automate several processes that are now manual. When the WIMS 

upgrade is complete, the following manually entered observations will be automated: SOW, 

LAL, and the daily 13:00 hour (LST) observation (this latter required manually changing the 

R designation to an O). As of spring 2003, software upgrades have been put on hold due to budget constraints. Some hardware upgrades are still planned: specifically the WIMS/NIFMID 

database will be moved from the System D mainframe to an IBM AIX server at NITC. 

(J. Barnes, NST, personal communications 2003, FAMWEB Technote 2003-01, May 2003).

New Web Sites/Data Access/RAWS Products

The Rocky Mountain Area GACC (RMACC) contracted with the U.S. Geological Survey 

Mapping Center/Geospatial Multi-Agency Coordination Group (GeoMAC) to develop a Web 

site (titled Rocky Mountain Area Red Flag, see appendix A for address). The Web site described previously in the Data Retrieval section displays fire weather watches and red flag 

warnings at near real time for fire danger zones within the region. Fire weather watches are 

issued when red flag warning criteria are expected within 12 to 48 hours. The NWS issues 

red flag warnings to alert fire managers when specific weather conditions, combined with dry 
30 USDA Forest Service RMRS-GTR-119. 2003. 

fuels, could lead to dangerous fires. Criteria may be dry lightning storms, high atmospheric 

instability coupled with low fuel moistures, low humidity, or winds above a threshold speed. 

These warnings help managers plan resource allocation and appropriate fire containment 

activities. The Web site also provides map layers with links to fire fuels, RAWS weather, 

situation reports, geographical features, cities, roads, and political boundaries. Some pages 

within this site are still under development.

The RMACC is also collaborating with the Eastern Great Basin GACC and the University 

of Utah Cooperative Institute for Regional Prediction (CIRP) to develop a Web site to display 

near real time RAWS data and weather information collected by other networks. Included 

are trends, low- and high-resolution maps, satellite images, station data summaries and metadata, tabular weather data, and meteograms. Development criteria include: a field-accessible 

information-access platform, an easily understood format, quick download, and a minimum 

number of links to retrieve desired information. Although still under development, some 

products are available: maps; some mesoscale model (MM5) products; and weather data and 

summaries for the RMACC, Great Basin, the Southwest, California and other Forest Service 

Regions. (The Web address is given in appendix A under University of Utah—Cooperative 

Institute for Regional Prediction.)

Geographic Area Coordination Centers (GACCs)

Geographic Area Coordination Centers (GACCs) as they are organized today have been 

in operation since spring 2001. Modern GACCs were established to provide support for 

fighting large fires at regional levels when National Forest or county dispatch centers need 

additional support. Following the 2000 fire season, the need for daily and short-term forecast 

fire danger assessments was recognized. Previously, assessments had been made on an asneeded basis, but often were out-of-date by the time they were completed. These fire danger 

assessments take the form of fire business products (daily and forecast): fire intelligence; fire 

weather; fire safety and prevention information; and fire danger rating indices and components; and fire safety. Detailed roles and responsibilities have been described in a strategy 

document prepared by the National Multi-Agency Coordinating Group (NMAC: NMAC 

Predictive Services Task Group and Charter 2002; R. Ochoa, personal communication 2002) 

at the National Interagency Coordinating Center (NICC), in Boise, ID.

The National Fire Plan provides funding for personnel, logistics, and physical plant to create these 

fire danger assessments on a day-to-day basis, especially during the fire season (R. Ochoa, personal 

communication 2002). Two full-time predictive service meteorologists support each GACC. If the 

GACCs cannot meet requests because they are supporting multiple incidents, or when GACCs 

are competing for resources, requests for equipment and supplies are referred to NICC.

Studies and Surveys

We present an overview of previous RAWS use studies. Then we summarize the responses to a RAWS-use survey and present the results of a survey of commercially available 

meteorological sensors with specifications. The latter was specifically requested to document 

the currently available, off-the-shelf, state-of-the-art meteorological sensors (for example, the 

sonic anemometer model currently being tested by RSFWSU). We next describe a prototype 

RAWS (super-RAWS) deployed in northern Minnesota and provide a comparison between 

RAWS fire-data specific protocols and more traditional hourly averaged data. We also investigate some other issues: a comparison of WRCC and KCFast data sets; the effects of changes 

in tower height and placement; the reporting of the 13:00 hour observation time; and DCP 

transmission protocols.
USDA Forest Service RMRS-GTR-119. 2003. 31

Previous RAWS Use Studies

RAWS data have been used in climatology studies (Brown and Hall 1997), fire-danger 

ratings, fire behavior analyses, and for quality control and assurance of the data itself. The 

use of RAWS data in regional spatial assessments has often been hampered by inadequate 

RAWS data quality. In attempts to correct this problem, GACC meteorologists have focused 

on analyzing individual RAWS data series within their regions. Several recent studies (Brown 

and others 2001; Marsha 2001a,b) have explored statistical approaches to analyze RAWS 

data in order to develop a methodology for optimizing intraregional RAWS deployments, 

to help define fire weather zones, and to identify priority stations within those zones. Brown 

and others (2002) conducted a quality control study on historical RAWS data from 242 sites 

in California. The goal was to examine data records and to flag or remove records deemed 

questionable, unacceptable, or implausible. The resulting clean data files are now used for fire 

danger rating analyses and climatological studies.

Marsha Study: Identification of Priority Stations Within Zones

Marsha (2001a,b) defined an objective method to design a more efficient RAWS network, 

in terms of number and siting, to meet the weather needs of wildland fire managers in the 

Pacific Northwest. The analysis consisted of two parts: (1) a wind rating was employed for 

each RAWS in the States of Washington and Oregon; and (2) cross-correlation matrices were 

computed for daily minimum relative humidity (RH) of each RAWS within the sub-areas.

Wind Rating. The wind rating was designed to identify and assess those RAWS that are 

wind sensitive (in other words, show good response to elevated wind speeds and have good 

variability). These criteria were evaluated by examining the distribution of the RAWS hourly 

wind speeds. Archived historical data were used to construct a climatological distribution 

of the peak wind speed for every 4-hour time period over several years. From the latter the 

median and 90th percentile peak wind speeds were determined. The spread statistic was then 

defined as the following:

 m

m

u

u − u 90

where u90 = 90th percentile peak WS and um = the median peak WS. Marsha’s wind sensitivity 

rating used the following criteria:

1. 90th percentile peak wind speed >= 4.47 m/s (10 mph) during a 4-hour time period, and

2. the spread statistic for the same time period >= 0.50

The assigned ratings were:

0 - if the above criteria were not met for any of the six 4-hour time periods of the day

1 - if the above criteria were met for at least one 4-hour time period of the day

2 - if the above criteria were met for at least one daytime and one nighttime 4-hour 

time period

RAWS with zero were considered inadequate, 1 adequate, and 2 good.

Relative Humidity Matrices. Part two of Marsha’s study was a cross-correlation analysis of minimum daily afternoon RH for each RAWS within a zone, resulting in correlation 

matrices for all RAWS. It defined a nonrepresentative RAWS as a station with the highest 

number of correlations at or above a given threshold (in this study, an ‘r’ coefficient value of 

0.90 was chosen based on the geographic area being examined). Such stations were removed 

from the matrix as were the other sites that correlated with it at or above the threshold r value. 

A high r value was taken as an indicator of a redundant or nonprimary weather station. Those 
32 USDA Forest Service RMRS-GTR-119. 2003. 

stations that were most similar in terms of RH were removed from the matrix. The process 

was repeated until a sub-set of key RAWS remained that were uniquely different from one 

another. If a draw occurred between sites, priority was given to the site or sites with a wind 

sensitivity rating of 1 or 2.

Due to local concerns over losing a site, no station was physically removed from the PacNW 

network, the non-representative RAWS were simply labeled as secondary stations.

Findings

The Marsha study was designed to provide a specific result for a specific area. It may not be 

a useful approach for other regions: NFDRS products from the selected study stations will no 

doubt reflect the selection criteria.

Brown Study: Optimization of Intraregional RAWS Deployments

Brown and others (2001) used two approaches in an analysis of the Great Basin (primarily 

Nevada) RAWS network. The first was similar to that taken by Marsha (2001a, b), correlating 

July monthly mean air temperatures, relative humidity (RH), and wind speed (WS) for six 

RAWS over periods of at least 9 years. This analysis was designed to examine how station 

separation related to climate characteristics. Results indicated that stations as close as 11 km 

(about 7 miles) demonstrated low correlations for wind speed, while stations as far apart as 30 

km (about 19 miles) had high correlation for temperature. Thus, use of single parameter correlation statistics alone in determining a site’s importance or redundancy could be misleading.

Geostatistical Approach. The Brown study applied a more formal geostatistical approach 

than was commonly used in the analysis of meteorological networks (Gandin 1970) to establish the maximum distance between stations based upon a single climate variable. Variogram 

plots (a graph of the variance of paired observations as a function of distance) were calculated 

for July monthly mean air temperatures for the 116 RAWS in the region. The study then used 

the results to fit a mathematical model which, in turn, was used to generate a uniform field of 

estimated temperature. Brown and others (2001) found that the optimum distance for station 

spacing (and highest spatial correlation) was about 43 km (roughly 27 miles). The actual correlation (r) was only 0.45, interpreted as quite low.

Study Results. The authors suggested that elevation variation across the region caused 

significant climate differences; they attributed the low correlation values to these elevation 

differences. In a subsequent analysis, temperature data grouped into three elevation ranges 

greatly improved the results and also indicated that the maximum distance between stations 

should be no more than about 80 km (50 miles).

Other Studies

Meteorologists from the RMACC (T. Mathewson and R. Mann) and the SWACC (C. 

Maxwell and R. Wooley) have recently conducted informal, unpublished, applied studies 

similar to those of Marsha (2001a,b) in efforts to define weather zones and to study NFDRS 

indices and component variations within their respective GACC regions.

Survey of RAWS Users

At the suggestion of the FS WO Research Staff (D. Cleaves), we constructed a user survey 

with questions targeting RAWS data use, type of data, importance of data, and sampling 

protocols. More than 100 surveys were sent to users through various means, including mail, 

e-mail, and personal delivery. A total of 44 responses were received, evenly divided between 

the NWS Weather Forecast Offices and Federal and State land management agencies. We 

tabulated responses and summarized the answers to those that were open-ended. Specific 

questions and a summary with greater detail are provided in appendix U.
USDA Forest Service RMRS-GTR-119. 2003. 33

Multiple Uses

Most respondents reported multiple uses for RAWS data. The prevalent uses for RAWS 

data are weather prediction and forecasting followed by incident management and monitoring 

weather for prescribed fires. Almost 90 percent of respondents used hourly and daily (specifically, the 13:00 hour observation) RAWS data. The real-time and event specific categories accounted for the remainder.

Nearly all data parameters plus NFDRS outputs are used by land management personnel. 

NWS forecasters use all the meteorological data. However, less than half use NFDRS products. Fuel temperature was the datum least frequently used by all respondents. NWS forecasters use RAWS data almost exclusively for specific locations or for weather climate zones, 

while nearly all land management agency personnel use the data set for a specific region or 

GACC area.

The majority of land management agency respondents use RAWS data for fire business applications – to calculate NFDRS indices, components, and adjective ratings; and to determine 

staffing levels, incident management, and longer term preparedness. Respondents from the 

NWS use RAWS data primarily for producing fire weather forecasts, determining red flag 

warning and fire weather watches, public weather forecasts, point/spot forecasts for specific 

incidents, and severe weather warnings.

Assessment of Current RAWS Network

All respondents considered RAWS critical for supporting their decisionmaking process; 

staffing; ensuring fire fighter safety; for calculating NFDRS indices and components; making both area and spot fire weather forecasts; and for real-time weather monitoring during 

prescribed burns and wildfires. All meteorological data were rated of high importance by all 

respondents, but NWS/WFO personnel tended to rate NFDRS products lower compared to the 

personnel from land management agencies.

No respondent indicated station overlap in his or her area (agency region or weather forecast 

zone). Coverage was deemed pretty good or adequate in the Western United States except for 

eastern Colorado, east of the Mississippi River, and some areas in the FS Southern Region.

Almost all respondents indicated a desire for a change in the traditional RAWS sampling 

protocol: more frequent sampling and data transmission; NFDRS product calculation/output 

more than once per day; and ready access to the larger data set. Three respondents suggested 

leaving the system alone, making no changes at all.

Four respondents indicated an explicit inclusion of RAWS duties and/or responsibilities 

in their respective position descriptions (PDs) and one included PD specifics: see appendix 

K for a sample PD of RAWS related duties. (See also Findings on Personnel Issues in the 

Management Implications section on the need to explicitly describe RAWS-related duties in 

individual FS PDs.)

Survey of Commercially Available Meteorological Sensors

We were asked by our WO sponsor to conduct a meteorological sensor/instrument survey 

as part of our review. The purpose of these results is to give planners, managers, and operators 

associated with RAWS a thorough list of available off-the-shelf sensors for potential future 

use with fire weather stations. Although current operational features of the RAWS system demand uniformity of instrumentation across the network, it makes sense to keep abreast of new 

sensor technologies. The survey includes sensor specifications that are sometimes overlooked 

when choosing manufacturers.

Air Resource Specialists, Inc. was funded to gather and compile technical information from 

known meteorological equipment vendors and prepare a comprehensive tabular summary of sensors associated with RAWS operations:
34 USDA Forest Service RMRS-GTR-119. 2003. 

• Wind speed

• Wind direction

• Ambient air temperature

• Relative humidity

• Precipitation

• Barometric pressure

• Solar radiation

• Fuel moisture

• Fuel temperature

• Soil moisture

• Soil temperature

Appendix V with attached CD provides a detailed list of currently available, off-the-shelf sensors, their technical specifications, manufacturers, current price, and a narrative for each sensor 

type. This information was compiled between January and April 2002. Each section in the appendix V CD is preceded by a narrative describing each factor or specification within the survey. 

The manufacturer and model number for each sensor group are highlighted in a separate color. 

Since there are more parameters than will fit on one 8 1⁄2 by 11 inch page, successive pages give 

the additional parameters for each group of sensors. Color changes denote when new groups of 

instruments are listed.

Experimental Prototype Super-RAWS

Description

The USDA FS WO Air Resource Management Program and the FS WO National Weather 

Program, with support from FS RMRS scientists, have funded a prototype enhanced RAWS 

station. This super-RAWS is equipped with the standard suite of sensors as well as additional 

sensors and alternative sensors not used on standard RAWS and not limited to fire-related 

parameters. Super-RAWS was deployed within the Superior National Forest at the Fernberg 

tower site, 20 miles east of Ely, MN. Operational since September 2001, the super-RAWS transmits 

data as per NFDRS standards using a Campbell Scientific data-logger and GOES transmitter.

An assessment of future weather data needs of Federal land management agencies and the 

expanding list of uses and applications of RAWS weather data led to the deployment of the 

super-RAWS. These include: leaf wetness; soil temperature and moisture; air and soil vertical 

temperature difference (delta temperature); vector wind speed; moisture content of decomposing surface litter (duff); and associated statistics (see appendix W for the complete data 

list). Super-RAWS data may support climatological studies, pollution dispersion modeling, 

and modeling of ecosystem carbon exchange and water vapor flux (Zeller and Nikolov 2000). 

The latter ecosystem modeling may also provide a new approach for the analyses of future fire 

potential since the amount of water within the ecosystem is accounted for.

Comparison of RAWS and Super-RAWS Data Sets

The Fernberg super-RAWS data set provided an opportunity to: (1) compare traditional 

RAWS protocol 10-minute and instantaneous data with hourly average data routinely used in 

other meteorological and environmental assessments, and (2) evaluate new sensor technologies such as sonic anemometry for wind speed and wind direction versus the standard cupvane wind sensors used at most RAWS.

According to the standard RAWS protocol, wind speed, wind direction, and relative humidity are provided as 10-minute averages, while temperature and solar radiation are instantaneous 
USDA Forest Service RMRS-GTR-119. 2003. 35

measurements obtained just prior to transmission. The super-RAWS was programmed to provide 

both RAWS protocol and averaged hourly data. Thus, the super-RAWS collects the standard RAWS 

10-minute averages and instantaneous measurement as subsets of the hourly averaged super-RAWS 

data. Two different protocols were programmed to simultaneously record and report data allowing 

the same instruments to be used to record both standard RAWS and super-RAWS outputs.

Super-RAWS obviously increased the number of data elements measured and transmitted. 

Because ASCADS can only handle a maximum of 12 data records, the standard RAWS component of super-RAWS was limited to 12. These standard RAWS parameters were previously 

listed in the Sampling Protocols subsection. The super-RAWS measures and transmits 48 data 

elements. The remaining data elements available on the super-RAWS are: weather data for each 

hour (for example, averaged 00:01 to 01:00 data are recorded as 01:00) in terms of means and 

statistical measures (for example, standard deviations and maximum values). The mean hourly 

wind speed and direction were recorded at the RAWS protocol 20 feet (6 m) as well as at 50 feet 

(15 m) above ground level; ambient temperature was measured at heights of 9 to 10 feet (3 m) and 

50 feet (15 m).

Method of Comparison of RAWS and Super-RAWS Data Sets

We analyzed data that were obtained using standard and super-RAWS protocols during 

the period March 21 through June 17, 2002. In a statistical comparison of the time series of 

RAWS 10-minute and instantaneous values versus the super-RAWS hourly averages data, 

we calculated and studied the coefficient of determination (R2), slope (S – a nondimensional 

variable in this case), and intercept (I – where the regression plot intercepts the y-axis) of the 

regression line, and a frequency distribution (histogram) of the residuals. We chose the hourly 

means as the independent variable against which standard RAWS data were compared. The 

comparison included: wind speed, wind direction, solar radiation, ambient temperature, and 

relative humidity. We also evaluated discrepancies in hourly measurements between the sonic 

anemometer and cup/vane sensors by plotting cup/vane data versus sonic for both wind speed 

and wind direction.

Results of Comparison of RAWS and Super-RAWS Data Sets

All data described in this section are provided in appendix X. The analysis indicates that 

solar radiation, wind speed, and wind direction, as measured using standard RAWS protocols, 

demonstrate larger deviations from hourly values than do temperature and relative humidity.

Solar Radiation. Given the high temporal variability of solar radiation, we conclude that 

instantaneous solar measurements do not adequately represent average hourly conditions. In 

about 30 percent of all cases, instantaneous solar radiation values deviated from true hourly 

means by more than 50 W m-2 (fig. X-1). Updates to the solar radiation sampling procedure 

should significantly reduce these differences (see Recent Updates to NFDRS 2000 Standards 

subsection). In fact, new NWCG weather station standards (NWCG – National Fire Danger 

Rating System, Weather Station Standards. 2003) call for the use of an hourly average of 

solar radiation (from 60 samples). This change will begin to be implemented in 2003 as dataloggers are reprogrammed.

Truncation of Wind Speed Data. As shown in figure X-2, deviations of reported wind 

speed from the true values can be substantial. We found that the RAWS 10-minute wind speed 

data are truncated to a whole integer with .0 added back by the data-logger/program (for example, 6.9 becomes 6.0). This presents a systematic bias in the values reported for WS that is 

reflected in the low slope of the regression between hourly averages and 10-minute means (fig. 

X-2). Because of the high variability of wind speed within any hour in addition to the artificial 

truncation of 10-minute data, values reported by RAWS can underestimate the actual mean 

hourly wind speed by at least 1 mph and often by as much as 3 mph. This happened about 80 

percent of the time.
36 USDA Forest Service RMRS-GTR-119. 2003. 

Wind Direction Measurements. Measurements of wind direction (WD) showed a lesser 

bias than those for wind speed. Yet, in about 15 percent of cases, the 10-minute average WD 

departed from the hourly WD by more than 20 degrees (fig. X-3). Occasionally the RAWS 

WD was reported as opposite (180o) the hourly WD average. Wind direction data obtained 

from the vane and the sonic were similar (fig. X-4). In most cases, discrepancies in the sonic 

WD were within ± 20 degrees (see fig. X-4, lower panel).

Temperature and Relative Humidity Measurements. RAWS standard measurements of 

temperature and relative humidity were relatively close to hourly averages of these elements 

(see fig. X-5 and X-6). Relative humidity data showed somewhat larger deviations compared to 

temperature (fig. X-6). However, the accuracy of RH sensors is typically ±5 percent.

Differences Between Wind Speed Measured by Cup Versus by Sonic Anemometer.

The super-RAWS was equipped with colocated cup and a sonic anemometers. A comparison 

of the two hourly wind speeds revealed that the cup anemometer tended to record larger values, especially at higher wind speeds (fig. X-7). This is most likely due to the well-known cupresponse phenomenon: turbulence causes cups to over-spin. Also, the cup anemometers have 

start/stop thresholds at lower wind speeds (for example, the cup will not start spinning below 

a threshold WS). But the sonic anemometer does not have this threshold limitation. In the case 

of the super-RAWS, the minimum cup WS was programmed to be 0.5 mph. So if the WS was 

zero, the data logger would record and report 0.5 mph while the sonic anemometer, with no 

starting threshold, would report 0 mph. Hence, the frequency distribution (of cup – sonic) is 

shifted slightly to the right . (See fig. X-7, lower panel.)

Findings of Comparison of RAWS and Super-RAWS Data Sets

There are discrepancies in the standared RAWS protocols and in comparing RAWS data 

with 1-hour averages. Since fire danger is evaluated daily, perhaps further study is needed to 

address the impact of using the current RAWS sampling protocols.

Comparison of WRCC and KCFast Data Sets

Description of WRCC and KCFast Data Sets

We have made direct comparisons between four RAWS congruent data-sets from WRCC 

and from KCFast in an effort to evaluate database integrity. These comparisons quantify differences over the years when the data overlapped. We have also used the FF+ application 

to calculate fire danger indices and components (historical means and daily minimums and 

maximums) over the course of a fire season for these data sets. A summary is given below and 

additional details are given in appendix Y.

As previously discussed, WIMS/KCFast is a major long-term archive of RAWS observations. To review, the database supports two formats. The 1998 format retains all hourly data 

but stores it for only 18 months. The 1972 data format contains only 13:00-hour RAWS observations, and it stores the data for the entire period of record. The WIMS/KCFast archive based 

on the 1972 format is currently the information source used to compute NFDRS indices and 

components used in fire business support.

The 1998 KCFast file format provides a time tag for individual data records, which contains year, month, day, and observation time. However, the 1972 format does not provide an 

observation time since it is implicitly assumed that each daily observation refers to the 

13:00, and only 13:00.

Due to the great operational significance of the KCFast RAWS dataset, the quality of 

archived 13:00-hour observations is important. Since operators manually flag these observations in the WIMS data base (along with entering SOW and LAL), the possibility exists 

for human errors such as using the wrong observation time for the 13:00 hour; accidentally 

changing numerical values of meteorological elements; entering incorrect SOW and/or LAL; 
USDA Forest Service RMRS-GTR-119. 2003. 37

and so forth. Human errors were assessed by comparing KCFast historical records of 13:00-

hour RAWS observations with the WRCC long-term archive of quality-controlled 13:00-hour 

RAWS observations. (See the section on the WRCC in this report.) We also evaluated differences in meteorological observations between KCFast and WRCC databases in terms of their 

impact on computed NFDRS indices and components.

In an attempt to quantify the likely magnitude of such human errors and their impact on 

computed NFDRS indices and components, we analyzed the historical record of several 

RAWS (specifically, Doyle, CA; Cheeseman, CO; Lake George, CO; and Redfeather, CO). 

We selected the Colorado stations to represent mainly FS-operated RAWS in Colorado with 

data record lengths of at least 10 years. The selection of the Doyle, CA site was random.

Method of Comparison of WRCC and KCFast Data Sets

We obtained meteorological data in the 1972 format for each of the four RAWS sites from 

the official KCFast Web site. The WRCC provided standard hourly data for the same RAWS 

from their database. The WRCC files were processed to extract 13:00-hour observations for 

each evaluated element and site. KCFast records were processed to extract archived values for 

the four elements being compared: ambient temperature, relative humidity, wind speed, and 

precipitation.

Using the time tags provided by the two databases, we aligned the 13:00-hour daily observations extracted from the WRCC database with corresponding records from the KCFast 

archive for each RAWS. Arithmetic differences were computed between KCFast and WRCC 

in the data records of each meteorological element for each of the four RAWS sites. The daily 

differences in recorded 13:00 hour values were plotted against time for the entire period of 

data archive overlap between KCFast and WRCC.

We also evaluated differences between the two data records in terms of correlation coefficient, slope, and intercept of the regression between the two time series for each element. 

Results were plotted using SigmaPlot 2001. We assumed that the WRCC data record was the 

correct one because it has been thoroughly examined by the WRCC staff; WRCC QA/QC 

criteria can be found in Brown and others 2002. Where the KCFast 13:00-hour observations 

differed from corresponding WRCC data, we interpreted this difference as an error caused by 

human factors.

Using FF+ as previously discussed, we evaluated the impact of KCFast data errors on 

NFDRS indices and components. FF+ as currently used by most fire managers in the United 

States is designed to ingest meteorological data in the KCFast 1972 format. It also requires a 

KCFast Station Catalog file for input. For each RAWS, we ran FF+ twice using (1) an original 

KCFast data file and (2) the WRCC 13:00-hour values. The comparison of FF+ runs only 

differed in the values of the main four meteorological elements: temperature, RH, WS, and 

precipitation. The rest of the support data were identical. We studied the behavior of four 

NFDRS indices and components: Spread Component (SC); Energy Released Component 

(ERC); Burning Index (BI); and Ignition Component (IC). Each index and component was 

represented by seasonal time series of its mean and maximum values, respectively. As with the 

meteorological data comparison, NFDRS indices computed from WRCC data were assumed 

to be the control against which the KCFast-based indices were compared.

Results of Comparison of WRCC and KCFast Data Sets

The comparisons above revealed significant differences between KCFast and WRCC data 

archives for all RAWS sites studied. Figure Y-1 in appendix Y shows the temporal dynamics between the 13:00-hour weather observations in WRCC and those in KCFast for the 

Cheeseman station in Colorado (NWS ID: 053102) over a period of about 15 years. (Figure 

Y-2 presents scatter plots and correlation statistics of the two time series. All figures and 

table Y-1 can be found in appendix Y.) As evident from the graphs, data in the KCFast 

record can deviate from WRCC values by as much as 54 oF for temperature, 68 percent 
38 USDA Forest Service RMRS-GTR-119. 2003. 

for relative humidity, and 23 mph for wind speed. The pattern of differences and their 

magnitude appear to be random.

After carefully examining numerous days with nonzero differences and comparing KCFast 

13:00 values with the complete hourly record from WRCC, we discovered that many data 

points entered in the KCFast archive as 13:00-hour observations actually came from other 

hours during the same day and, in some cases, even from early morning hours of the next day! 

In several instances, we found that not all values of meteorological elements originated from 

the same hour (in other words, temperature and humidity data were taken from the 11:00-hour 

while wind speed came from the 12:00-hour). This occurred over several days at the Doyle 

station during the early 1990s. We found that meteorological data entered into WIMS/KCFast 

as 13:00-hour observations, were often taken from hours ranging from 10:00 to 17:00. The 

pattern of discrepancies in meteorological data described for Cheeseman is similar to that 

found for all other three RAWS. It appears that station operators have systematically either 

made random errors by incorrectly flagging the 13:00-hour observations or chose to change 

the data to better represent the conditions as they saw it.

Discrepancies in meteorological records between the KCFast and WRCC databases had a 

sizable impact on computed NFDRS indices and components. Figure Y-3 shows deviations of 

mean values of the Spread Component (SC) for Doyle, CA. Errors in the KCFast data archive 

caused the mean SC to be overestimated for this site by 10 to 40 percent over most of the fire 

season. The SC maximum daily values showed much larger deviations (for example, 20 to 

100 percent) compared to WRCC results (fig. Y-4). As indicated by the correlation statistics, 

the maximum SC values based on the KCFast record are poorly related to those derived from 

WRCC data. In this case, deviations tend to be positively biased. In other words, the KCFast 

data seem to consistently cause an overestimation of SC values for Doyle. Figure Y-5 shows 

errors in the calculation of the BI for the same site. Other indices and components computed 

for Doyle showed a similar error pattern. Table Y-1 provides coefficients of determination (R2) 

and regression slopes (S) for indices and components computed comparing the KCFast and 

WRCC datasets for all four RAWS.

Figure Y-1 reveals another interesting pattern, which seems to be more or less present at the 

other three RAWS as well: after 1997, the KCFast record appears to match WRCC data considerably better than in previous years. Data discrepancies for all elements, while still occurring, 

are significantly less frequent after 1997. We suspect that this improvement was the result of a 

coordinated effort by the FS, BLM, and other land management agencies to improve the quality of RAWS observations as well as the accuracy of fire weather and business applications. We 

think this was achieved mainly through training and impressing upon personnel the critical 

importance of RAWS data in calculating fire danger ratings. This was especially the case after 

the South Canyon (Colorado) fire in 1994 where 14 firefighters lost their lives. There were also 

vast improvements in hardware and software during the 1990s: in 1993 WIMS was implemented and training became available. In the mid-1990s, an increasing number of stations were 

being upgraded with new DCPs, with an increase in transmission frequency from once every 

3 hours to one per hour, with transmissions close to the top of the hour for priority stations, and 

with the conversion of dial-up stations to GOES platforms. And finally, concerted efforts 

were made at the local FS level to properly maintain the stations. This also entailed new 

training efforts that continue to this day (K. Shelley and R. Gripp personal communication 2002). Nevertheless, the potential for human error in the current manual data-entering requirement is still a weak link for RAWS data going to WIMS.

Findings

This analysis indicates that the errors in the KCFast data archive tend to produce biased 

estimates of the mean and maximum values for most NFDRS indices and components. 

Maximum values are more adversely affected than means. An important implication is that 

biases in long-term means and maximums could create a false impression about the actual fire 
USDA Forest Service RMRS-GTR-119. 2003. 39

danger at a site. For example, in the case of Doyle, an overestimation of historical values of BI 

and SC over a significant portion of the fire season could lead to an incorrect conclusion that 

fire danger was not exceptional in year 2002 at this site. On the other hand, NFDRS indices 

computed for Cheesman using the KCFast dataset tend to be underestimated (as indicated by 

the regression slopes in table Y-1). In addition, indices for Cheesman such as BI, SC, and IC 

show a significant dispersion around the values derived from the WRCC record. An important 

implication then is that biases in long-term means and maximums could create a false impression about the actual fire danger at a site and affect real-time decisions about staffing and 

resource allocation during actual firefighting.

These discrepancies must be addressed immediately since the KCFast data set is an active 

part of current fire business.

Effect of Changes in Tower Height and Sensor Placement

Description of Changes in Sensor Mounting Heights

RAWS data users must be aware that changing sensor mounting heights (NWCG 2000) will 

affect the data being collected. For example, wind speed (WS) decreases logarithmically as 

height decreases while relative humidity (RH) increases as the height decreases or the ground 

is approached. RH, which is a function of evaporating soil moisture and transpiring vegetation 

(Oke 1978), also has diurnal fluctuations related to temperature changes. If WS or RH sensor 

height is changed, or if sensors are moved, NFDRS indices and components will be affected. 

Wind speed, slope, and fine fuel moisture (sensitive to current RH and temperature) are direct 

inputs for the spread component (SC) calculation, which in turn, along with ERC, is used in 

calculating the ignition component (IC) and burn index (BI). Wind speed does not enter into 

the calculation of the ERC but 100- and 1000-hour fuel moistures do, which over the long 

term (days to weeks) respond to day length, max/min temperature, RH, and precipitation (see 

NWCG 2000; Cohen and Deeming 1985).

According to the NFDRS 2000 standards (NWCG 2000), the RAWS wind speed and direction sensors should be mounted at a height of 20 feet and the RH sensors at 4 to 8 feet (NWCG 

Weather Station Standards 2000). The international meteorological surface observation standard for wind measurement height is 10m (32.8 feet.). In FS Region 6 (Pacific Northwest), FS 

once used 10m Rohn25 towers as RAWS and, hence, meteorological wind sensors on these 

RAWS were often above 20 feet. Since these towers are no longer OSHA compliant, they have 

been phased out of service over the past 4 to 5 years and replaced with either Vaisala/Handar 

or FTS RAWS frames. In most cases, the replacement has caused sensors to be placed approximately 13 feet lower.

At this lower height, we would expect the measured wind speeds to be noticeably less than 

the recorded climatology for the location. If this were the case, it would present a continuity 

problem in using such data for FF+ and other fire danger calculations. To get a rough estimate 

of the effect of height change, we decided to examine an actual example of a change from a 

10-meter tower to a 20-foot tower at Redfeather, CO. In August 2002, the 20-foot replacement 

tower was installed at Redfeather west of the 10-m tower, which, due to location, resulted in 

an actual 20.8 foot difference in aboveground WS sensor height. (The base of the 10 m tower 

was sited on a large boulder 8 feet above base of the new 20-foot tower: 32.8+8=40.8.) We 

caution the reader that the following example is an oversimplification since the example does 

not take into account variable atmospheric stability conditions. Use of these methods should 

be preceded by consultation with a trained meteorologist.

Method of Calculating Effect of Changes in Sensor Mounting Height

Calculating wind speed differences as a function of height are typically performed using 

either the power-law method or the logarithmic profile method. The power law is used for full 
40 USDA Forest Service RMRS-GTR-119. 2003. 

boundary layer applications, while the logarithmic profile is usually recommended for applications close to the ground. Both are shown below:

Power law: 

m

z

z

U

U















 =

40.8

20

40.8

20

where U is wind speed; z is measurement height; and m is the power law exponent. Although 

m is dependent on the site and meteorological conditions, the value m≈0.1 is used for smooth 

surfaces and m≈0.4 for rougher surfaces;

Logarithmic profile: 

40.8

40.8

* 20

20 ln U

z

z

k

u U +













 =

 

where u* is the site and meteorology dependent friction velocity; and k = 0.4 is the so-called 

von Karman constant.

We first plotted actual Redfeather mean wind speeds for each hour of the day: August 21 

through September 24, 2001 and August 21 through September 24, 2002—pre- and post-tower 

height change (see fig. 3). Then using the power law approach with m=0.9 during nighttime 

hours and m=0.45 during daylight, and with a 20.8 foot reduction in anemometer height we 

adjusted the year 2001 data set, and then we did the same using the logarithmic profile method 

with u = 1.3 (night and day) and k = 0.4. We also calculated and plotted the 2001:2002 ratio for 

each hour of the day. The results from both adjustment methods reflect the actual 2002 data. 

The 2001:2002 ratio of actual data show a diurnal multiplier, equal to about 2 for the nighttime 

and 1.5 for the daytime.

Figure 4 shows the percent difference in the BI and SC for the Redfeather, CO, RAWS for 

the 1970 through 2001 fire seasons using adjusted and unadjusted winds from the KCFast database. The adjusted wind speeds were calculated using the logarithmic profile equation with a 

u* = 1.3, k = 0.4, and a height decrease of 20.8 feet. Mean and maximum SC and BI for the fire 

seasons 1970 through 2001 were then calculated (FF+) using the actual and adjusted data sets. 

0

1

2

3

4

5

6

7

8

9

0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00

Time of day

WS_2001

WS_2002

2001_LOG

2001_POWER

2001/2002

Wind Speed (mph)

Figure 3: Mean wind speeds for each hour of the day between August 21 and 

September 24 in 2001 and in 2002.
USDA Forest Service RMRS-GTR-119. 2003. 41

The SC and BI were chosen because they are influenced directly by wind speed (compared to 

ERC). Given that wind speed decreases with height, these differences will always be greater 

than zero. For SC throughout the fire season, percent decrease ranged from 14 to 20 percent 

for daily means, and differences in the maximum values varied from 5 to 20 percent . For BI, 

decreases in daily means ranged from 8 to 11 percent, and differences in the maximum values ranged from 4 to 10 percent. The reduction in wind speeds also lowered the 90th and 97th

percentile SC and BI values.

Figure 4: Percent decrease in daily mean spread component (SC) and burning index (BI), 1970-2001 

at Redfeather CO RAWS.
42 USDA Forest Service RMRS-GTR-119. 2003. 

Findings from Calculation of Effect of Changes in Sensor Mounting Height

If the wind speed and direction sensors are lowered, actual fire danger could be underestimated when compared to the unadjusted historical record. This could have far-reaching 

consequences for fire business decision support and ultimately resource allocation. Further 

discussion of this topic is beyond the purpose of this review, except to alert fire managers that 

using unadjusted climatology for sites where the height of sensors has been changed may result 

in incorrect management decisions. It will take many years of new measurements to affect the 

unadjusted climatology.

Issues Around GOES Transmit Times and 13:00 Hour 

Observation Time

Because all GOES RAWS transmit times cannot occur exactly at the top of the hour, for 

example, 13:00 LST, priority stations are usually assigned transmit times as close as possible 

to the top of the 13:00 hour. But the difference in transmission times raises the question about 

how the 13:00 hour observation (or any hour for that matter) is defined. Although there is no 

formal rule, the general RAWS rule is that any data record transmitted between 12:30 and 13:

30 is defined as the 13:00 hour observation (in other words, the 12:30 to 12:59 time is 

moved up and the 13:01 to 13:30 time is moved back). These times are all Local Standard 

Time (LST). However, it takes anywhere from 10 to 15 minutes for an observation to 

reach WIMS, so if the transmit time is 13:25 the observation will not be seen or available 

for human editing until at least about 13:40. So, does the Dispatch Center or Regional 

Coordination Center use the 12:25 as seen at 12:40 or the 13:25 observation for their 

13:00 hour values? The decision becomes a judgment call but is usually made through 

consultation and discussions between personnel of the Dispatch Center, GACC, and the 

NWS fire weather forecasters. The decision criteria are based on what each center needs 

in terms of fire weather data. This uncertainty is reflected in the results shown in the WRCC 

versus KCFast data comparison previously presented (also appendix Y).

Complicating matters, different RAWS databases record observation time in different 

ways. ASCADS archives the actual transmit time, in minutes and seconds after the hour in 

Greenwich Mean Time (GMT). The NWS reports the observation time rounded to the nearest 

hour (as described above). WIMS reports observation times numbered from 0 to 23 for the ‘R’ 

observations (LST hours) with the implicit understanding that the actual time is that which is 

given plus the number of minutes to the transmission time after the hour which is reported. This 

format is followed in the DOBS (or Display Observations) interface option within WIMS. The 

DRAWS (Display RAWS observations) gives the actual transmission time stamp. The WRCC 

reports both GMT and LST depending on the sub-database that is being accessed (old or new 

interface respectively) or the time stamp chosen by the user – LST or GMT.

DCP Transmission Protocols (Vaisala/Handar 540 and 555, 

FTS 12s, and Campbell Scientific 23X)

Most RAWS DCPs are either Handar or FTS models, but some DCPs are Campbell Scientific, 

Inc. models. Each model uses slightly different data collection and transmission protocols.

Vaisala/Handar Models

The Vaisala/Handar 540 begins collecting data for transmission 10 minutes before the 

transmit time. Averages are calculated immediately prior to transmission, instantaneous parameters are recorded, and the DCP transmits to the GOES.

Although the Vaisala/Handar 555 is the newest state-of-the-art DCP, it is less efficient 

than the 540 model in calculating even a small number of averages. Theoretically these 
USDA Forest Service RMRS-GTR-119. 2003. 43

calculations should take only 30 seconds (by the 555), but 2 minutes was programmed to ensure enough time (B. Adams, personal communication 2002). Thus, the Vaisala/Handar 555 

begins collecting data 12 minutes prior to transmission and ends data collection at 2 minutes 

prior to transmission. Instantaneous values are recorded, averages calculated, and values are 

formatted/truncated. Precipitation, a cumulative value reported in 0.01 inch increments, is 

transmitted in a xx.xx format. Wind speed and direction averages are transmitted as three 

characters each (as xxx). For example, if WS is recorded as 7.9 mph, it is truncated to 7 mph, 

two zeroes are added and it is transmitted as 007. All other elements are reformatted in a 

similar way (NWCG Weather Station Standards, 2000). At the assigned transmission time, 

the data are sent to GOES and retransmitted to Wallops Island/Data Collection System (DCS) 

Automated Processing System (DAPS), thence to ASCADS via DOMSAT.

FTS Models

The FTS 12s follow a similar procedure: their DCP begins collecting and calculating a 5-

second running average on the required parameters 12 minutes before transmission. At minus 

2 minutes, values are truncated, and instantaneous parameters and averages are moved to the 

transmitter and, at the assigned time, sent to GOES.

The FTS 11 follows a different procedure: At 12 minutes prior to transmission, data collection begins for WS and WD. RH for both FTS models is an instantaneous reading, contrary 

to NFDRS 2000 protocols. For WD, the FTS 11 assigns integer values depending on the wind 

quadrant; a 5-second running average (for 10 minutes) is calculated and the last 5-second average is transmitted. The FTS 12 calculates a running 5-second vector average (for 10 minutes) 

in degrees; similarly to the model 11, the last average is transmitted. For WS, both the model 

11 and 12 measure a wind count per minute for 10 minutes; in effect, the amount of wind 

passing a given point—similar to the old wind odometers. Counts per minute data are collected and converted to actual WS; a once-per-minute running average is calculated. The final 

10-minute average WS is transmitted. At minus 2 minutes, values are truncated and instantaneous parameters and averages are moved to the transmitter and transmitted to GOES.

The older model FTS 11s are all dial-ups. They are contacted via telephone by the NITCHUB computer on a schedule that is set by the station owner/operator. The actual schedule 

depends on the season, local needs, and whether data in addition to the 13:00-hour observation 

is needed.

Campbell Scientific Models

Campbell Scientific data-loggers also truncate data: values are formatted prior to transfer 

to the GOES transmitter. When the Campbell Scientific data-logger program is executed, each 

data element is formatted to conform to RAWS/BLM standards so that the first 12 elements 

of the data stream can be ingested by ASCADS. Each data point is configured with a fixed 

number of characters. Decimal points are treated as characters. (The exact first 12 formatting 

is given in appendix W, far right column—elements 1-12.) The data are then copied to the 

transmitter and subsequently transmitted.

Findings Regarding DCP Transmission Protocols

Data Truncation. When we compared data retrieved from the super-RAWS via telephone modem with raw data ingested by ASCADS, we found that the Campbell’s data-logger 

program/algorithm for the transmitted RAWS was truncating data elements. This was confirmed by Campbell engineers/programmers (D. Brown, personal communication 2002). This 

issue may not seem important because we are discussing an underestimation of WS by 1 mph 

or less. However, when one considers that RAWS data are primarily used for NFDRS, fire 

business decision support, and for fire severity funding requests, one recognizes that accuracy 

and precision become more and more important as lives, property, and funding are at stake. 

We investigated the difference between the satellite-transmitted and telephone-transmitted 
44 USDA Forest Service RMRS-GTR-119. 2003. 

super-RAWS data and concluded that the probability for a wind speed being, say, 7.0 versus 7.1 

versus 7.2 and so on up to 7.9 was exactly the same (see fig. X-2c). Hence, a recorded RAWS 

wind speed of 7.0 is more precisely stated as 7.45±0.45. This is true for all RAWS data: past, 

present, and future unless corrected.

DAPS does not reformat the data it receives from GOES. Prior to retransmission through 

DOMSAT to ASCADS, DAPS adds the NESDIS ID, year, day, and a GMT stamp to the top 

of the data stream. ASCADS performs minimal formatting of RAWS data, removing the 

front-end zeroes on data and adding a decimal point and a zero (.0). So, the 007 described 

above for WS will appear as 7.0 in the WSM column of the view converted OBS data option 

(see ASCADS flow chart in appendix F, bottom left). If the user chooses raw OBS data, he/she 

will see the most current transmission in exactly the same format that DAPS used when it 

retransmitted the data stream.

Handar, FTS, and Campbell DCPs (data-logger plus transmitter) truncate data elements 

except for precipitation and battery voltage (which is truncated to one decimal place). Data 

truncation could have consequences in calculating fire danger indices and components over 

the long term; in addition, information is lost. We find that the issue of truncated versus untruncated data will affect indices and components.

DCP Data Sampling. We find that Handar and Campbell DCPs use different sampling 

protocols to calculate measured averages.

Additional Uses of RAWS Data

Beyond fire-related applications discussed earlier, RAWS data are used in support of 

climatological analyses, air quality monitoring, ecological process modeling, and weather data 

mapping. In this section, we summarize RAWS support for indirect fire and nonfire business applications.

Brown and others (2001) developed the following list of uses for historical and climatological RAWS data:

• support for court cases

• forecasts of fire severity based on historical information

• prescribed burn planning

• fire severity funding requests

• development of fire management plans

• monitoring soil erosion

• environmental restoration and risk assessment

• budget analysis

• forest health assessment

• ground water, watershed, and hydrologic assessments

• impact studies on wild life

• soils studies

• climatological studies

• ecosystem model parameterization

• weather forecast model initialization and verification

• interpolation of meteorological parameters to locations where no weather stations exist
USDA Forest Service RMRS-GTR-119. 2003. 45

This review discusses these other uses of RAWS data:

• air quality modeling and monitoring in the atmospheric boundary layer including air 

pollutant trajectory studies

• aerosol (airborne particulate matter) and trace gas flux measurements

• physical, regional, and seasonal climatological analyses

• environmental aerodynamics

• ecosystem process modeling

• weather research;

• mesoscale weather forecasting support

Air Quality Monitoring

In addition to helping define weather and forecast zones and performing basic weather network analyses, RAWS has been used to support air quality monitoring in the Southwest and 

elsewhere.

An outcome of the New Clean Air Act, the Western Regional Air Partnership (WRAP) is a 

collaborative air quality related effort of Tribal, State, and various Federal governmental agencies organized to implement the recommendations of the Grand Canyon Visibility Transport 

Commission (GCVTC) and to develop technical and policy tools needed by Western States 

and Tribes to comply with the Environmental Protection Agency (EPA) regional haze regulations. A network of committees, forums, and stakeholders representing a wide range of 

interests manage the activities of the WRAP. Public involvement is an integral part of the 

Partnership. For example, WRAP supported an effort to monitor particulate matter (PM10, 

particulates less than 10 microns in size) and ozone (O3) concentration several years ago. The 

instruments used to monitor these parameters were integrated with a standard portable fire 

RAWS platform using the Handar DCP and the standard suite of meteorological sensors. The 

sampling protocol was not standard RAWS since wind speed and direction followed EPA’s 

hour average protocol. PM10 (ug/m3), ozone concentration (parts per billion: ppb), solar radiation, and all other meteorological elements were also hour averages. A running 24-hour average for PM10 was also calculated (Peter Lahm, personal communication 2002). Unfortunately, 

no formal records were kept. Although transmission is limited to 12 data records, this application illustrates a potential flexibility within the existing RAWS-ASCADS-WIMS systems that 

is not commonly used.

Measurement of Aerosols (Airborne Particulate Matter)

For smoke and visibility monitoring programs and for fire manager smoke management 

programs, air resource and fire managers have indicated that the ideal situation would be 

to have remote access (via satellite and/or Internet accessible database) to both weather and 

particulate matter data from the same location and at the same time. In 1998 and 1999 the 

FS Technology and Development Program (in Missoula, MT) and the WO Air Resource 

Management Program, field- and laboratory-tested five instruments that measure airborne 

particulate matter (Trent and others 2000). The key items evaluated were accuracy in measuring smoke concentrations, comparison of results from two identical instruments, reliability, 

portability, power needs, data collection, and cost. Based on these criteria, the Air Resource 

Management Program chose and purchased a number of MIE DataRams. The DataRam is 

small, human-portable, and affordable. It is able to measure PM2.5 or PM10, upon deployment 

and immediately transmit data via a commercial satellite (Orbcomm). It is sufficiently accurate for the smoke and particulate monitoring needs for wildfire and prescribed burns. A 

unique capability of this system is that data are sent and posted to a publicly available Web site 

(address given in appendix A), so data can be viewed in near real-time.
46 USDA Forest Service RMRS-GTR-119. 2003. 

During summer 2002, a number of these instruments were deployed on two large Colorado 

wildfires: Hayman and Missionary Ridge. Both deployments were successful (R. Fisher, 

personal communication 2002). One drawback is the need to acquire simultaneous meteorological data; hence, it must be colocated with a weather station. To solve this need, however, 

DataRAM tests were conducted in FS Region 3 (in 2002) that connected the DataRAM with 

a FTS portable RAWS weather station. Forest Technology Systems developed the interface 

that converts analog output from the DataRAM for digital input to the weather station and 

subsequent transmission with meteorological data via GOES. The tests were successful and 

the data can be ingested by ASCADS (K. Shelley and C. Maxwell, personal communications 

2002; authors’ personal observations 2002).

Climatological Analyses

Typical climatological analyses using RAWS data include wind roses that provide information about wind direction and speed. Conditional wind roses can be generated to assist in planning fire operations by combining wind rose data with other data such as RH and temperature. 

For example, figure 5 shows that RH data for the Redfeather Lakes, CO, RAWS from July 

2000 to July 2001 are almost linear with respect to rank probability. However, the amount 

of actual water vapor mass, perhaps a useful measure of dryness, during the same period is 

distributed logarithmically (fig. 6). By combining the wind and water mass data, conditional 

wind roses (fig. 7 and 8) were prepared for the Redfeather RAWS site for the same time period: 

July 2000 to July 2001. Note that wind velocities and directions during periods of dry weather 

(greater than 2 g H2O m-3) are higher and more westerly compared to wet conditions (less than 

5 g H2O m-3) when velocities were lower and wind directions more southeasterly.

In addition to studies covered previously in the Studies and Surveys section, quality control 

analyses of RAWS data along with regional and seasonal climatologies have been published for 

the Nevada RAWS network and year 2000 fire season (Brown and Hall 1997 and 2001, respectively). All these types of climatological use of RAWS data can help plan fire operations.

Studies of Environmental Aerodynamics

Weather data are being used to help solve wind engineering or environmental aerodynamics problems, including house siting and orientation, mitigating existing problems, locating 

industrial emission stacks, assessing biohazards and radioactive exhausts, and determining 

wind loads on high- and low-rise buildings and bridges. Texas Tech University, Colorado State 

University, many Engineering Departments, and private consulting companies are actively 

involved in this type of research and using RAWS data.

Rank (probability)

Figure 5: Percent relative humidity (RH – y 

axis) vs rank probability at the Redfeather 

RAWS July 2000 – July 2001.
USDA Forest Service RMRS-GTR-119. 2003. 47

Rank (probability)

Figure 6: Water mass (g m-3) vs rank probability 

at the Redfeather RAWS July 2000 – July 

2001.

Figure 7: Conditional wind-rose (for water mass 

< 2 g m-3) for the Redfeather RAWS July 1, 

2000 – July 31, 2001.

Figure 8: Conditional wind-rose (for water mass 

< 5 g m-3) for the Redfeather RAWS July 1, 

2000 – July 31, 2001.
48 USDA Forest Service RMRS-GTR-119. 2003. 

Ecosystem Process Modeling

Modeling of ecosystem processes (cycling of nitrogen, carbon, phosphorous, and sulfur) requires environmental data. In the case of the Century model (Parton and others 1987), two of 

the most important parameters are soil temperature and moisture. These data can be collected 

by adding additional sensors to a RAWS platform as was done for super-RAWS. Forest stand 

and individual tree growth models also require weather data input: JABOWA (Botkin and 

others 1972; Botkin 1993); TREGRO (Weinstein and Beloin 1990); and FORFLUX (Zeller 

and Nikolov 2000).

Figure 9 shows modeled and measured ecosystem CO2 flux (μ mole-2 s-1) versus day of year 

at Toolik Lake, Alaska, 1996 using Long Term Ecological Site (LTER) network weather data 

that is similar to the super-RAWS data.

1996 Net Ecosystem Flux

-6

-4

-2

0

2

4

6

210 215 220 225 230

Julian Day

u mole m-2 s-1

FORFLUX DH: nc

DH: T+ DH: s+T+

MT: nc MT: s+

MT: T+ MT: s+T+

DH: s+

Figure 9: Modeled ecosystem CO2 flux (μ mole-2 s-1) vs. day of year at Toolik Lake, Alaska 1996. This 

site is part of the Long Term Ecological Site (LTER) network (DH: dry health; MT: moist tundra; 

ST: enhanced snow; T+: enhanced temperature).

Weather Research

WFAS, discussed above, is an ongoing research/operation project. Supported by the USDA 

FS F&AM, it uses RAWS data to generate maps of selected fire weather and to provide the 

NFDRS fire danger indices and components on a daily basis (see also appendix G).

Mesoscale Weather Forecasting Support

The Northwest Regional Modeling Consortium, which is part of the Fire Consortia for 

Advance Modeling of Meteorology and Smoke (FCAMMS), is a group of local, State, and 

Federal agencies and cooperating private companies formed during the 1990s in the Pacific 

Northwest. Its purpose is to provide funding and continuing support for a regional weather 

prediction system by combining resources and personnel. The system is based on the Penn 

State/National Center for Atmospheric Research (NCAR) mesoscale atmospheric model 

(MM5). The consortium produces 60-hour forecasts twice a day at 4-, 12-, and 36-km 

resolution. This is one of the highest resolution weather forecasting programs in the United 

States. The RAWS data set is one of many used to initialize model runs and to verify forecast 

results. Future FCAMMS products will include air quality and smoke modeling, a ventilation 
USDA Forest Service RMRS-GTR-119. 2003. 49

potential (winds forecasting), and fire danger forecasts driven by local weather data (RAWS 

data among them).

The Eastern Area Modeling Consortium (EAMC) is a multiagency group founded in 2001 

to support the National Fire Plan (NFP) by using mesoscale models (MM5) to:

• Make accurate and useful fire weather forecasts and develop improved fire weather indices at national and regional scales.

• Link forecast information with fuel loadings and fire potential.

• Develop improved model predictions of smoke transport and diffusion.

EAMC is also composed of researchers, and fire, air-quality, and natural resource managers at the Federal, State, and local levels.

Three other consortia have been established in other parts of the United States to encompass regions roughly corresponding to those of the USFS: the Rocky Mountain Center, 

the Southeastern United States, and California and Nevada. All five consortia have essentially the same objectives and work together to achieve these goals under the FS program: 

FCAMMS.

MesoWest is another cooperative modeling MM5 project between researchers at the 

University of Utah, forecasters at the Salt Lake City NWS office, the NWS Western Region 

Headquarters, and personnel of participating agencies, universities, and commercial firms. 

The goals of this project are to provide access to current weather observations in the Western 

States, and provide regional weather forecasts using MM5. The NWS, among others, helps 

support this project.

MesoWest relies upon weather observing networks that are managed by Federal, State, 

and local agencies and private firms. The Federal networks include RAWS, Snowpack 

Telemetry (SNOTEL), Automated Surface Observing System (ASOS), and Automated 

Weather Observing System (AWOS) among others (see Glossary for brief identification 

information). Temperature, relative humidity, wind speed and direction, precipitation, and 

other parameters are available through MesoWest from several hundred locations. MesoWest 

surface observations are used in high-resolution spatial and temporal analyses centered on 

Utah.

The data archive is operated by the NWS to monitor weather conditions around the region. 

Researchers also use MesoWest extensively to study severe weather events such as winter 

snowstorms and damaging winds. MesoWest is available to the educational community as 

well.

The Advanced Regional Prediction System Data Analysis System (ADAS) at the University 

of Oklahoma is another mesonet similar to MesoWest that has been configured to perform 

three-dimensional and surface-based analyses over regions with complex terrain. ADAS relies 

on archived MesoWest observations as an important source of local data to modify an initial 

background data field provided by NCEP RUC2 analyses (see Glossary for brief identification 

information of NWS’s NCEP and RUC2).

Management Implications

Current Issues

As of spring 2003, the status of FS-operated RAWS was ‘adequate’ to ‘improving’ to ‘hard 

to pin down’. As the GACC meteorologists in FS Regions 3 and 9 have taken over some coordination, maintenance, and data processing, they have vastly improved network operations, 

and continue to make improvements (C. Maxwell, K. Shelley, and S. Marien, personal communication 2002; authors’ personal observation, 2001 and 2002). During FY2002 a number 
50 USDA Forest Service RMRS-GTR-119. 2003. 

of priority NFDRS RAWS stations that had been poorly maintained were moved, replaced, 

or refurbished (e.g., Penasco in Region 3, and Camp 4 and Douglas Ingram in Region 6; C. 

Maxwell, R. Shindelar, and K. Shelley, personal communications 2002). Operations in other 

FS Regions also continue to improve with ongoing network hardware upgrades. Maintenance 

on stations is occurring on a more or less regular basis and an increasing number of FS personnel are being trained on station hardware and software, WIMS, and NFDRS (authors’ 

personal observations).

ASCADS and WIMS metadata and weather data file maintenance is random with need for 

improvement (T. Mathewson, C. Maxwell, R. Shindelar, M. Nelson, and R. Powell, personal 

communications, 2002):

• RAWS site visits not always reported or, in some areas, not made at all.

• Incorrect fuel model, climate class, or location are used for NFDRS calculations at some 

stations.

• Stations remain coded as frozen well into spring.

• ASCADS metadata not maintained routinely by users.

• WIMS not maintained by all users (for example, 13:00 hour observation is not flagged; 

SOW not entered; LAL not entered).

In informal interviews, FS personnel involved in the RAWS program primarily at the dispatch center level described ASCADS and WIMS as difficult to use (especially ASCADS). 

They also claimed that ASCADS and WIMS failed to provide products in a timely fashion 

and that personnel have not received adequate training as to their use and retrieval of products 

(R.Powell, F. Hesselbarth, M. Nelson, C. French, personal communication 2002). Some of 

these problems may be resolved when planned training on WIMS and NFDRS takes place 

(courses are offered on a yearly basis and in different FS Regions) and, as discussed in the 

Projects Under Development section, the reengineering of ASCADS and WIMS is completed.

The WRCC, NIFMID/WIMS, NIFMID/KCFast, NWS, and the BLM/NIFC databases 

all rely on an antiquated system, ASCADS, for data. ASCADS has, in effect, become a wellknown choke point for the RAWS data stream. The proposed ASCADS upgrades will, we hope, 

solve these problems. Some database erroneous-data problems are not being addressed.

We have found discrepancies in the station locations—and even station existence—listed 

in different RAWS databases such as ASCADS and Fire and Aviation Management (F&AM) 

Helpdesk (T. Mathewson, R. Mann, personal communication 2002).

Most RAWS, as a mesonet function, lack the capability to record year-round precipitation. 

Cost and power considerations preclude equipping all RAWS with all-weather precipitation 

gauges, but selected site upgrades to provide this important piece of information would improve the system.

Findings

In this section we list a number of findings. The order in which these findings are presented does not indicate priority. Given the fluidity of the RAWS system, some findings may 

already be in the correction implementation process. Before any new studies are contemplated 

and/or proposed, individuals should read through this study for orientation, then contact and 

coordinate with agency and regional RAWS coordinators/personnel. A contact list is given in 

appendix Z.

Personnel

1. Additional Personnel and Enlarged Work Area at RSFWSU. Given the current and 

increasing number of RAWS stations and given the new NFDRS 2000 certification requirements, the RSFWSU workload will increase. The RSFWSU processes and maintains 
USDA Forest Service RMRS-GTR-119. 2003. 51

thousands of RAWS meteorological sensors and other station-related equipment every year 

(see table 5; a total of 8,101 during FY2001). This is a staggering workload for eight inhouse technicians and 12 field personnel. Given the critical importance of the RAWS data, 

current manning and existing space limitations at the RSFWSU (authors’ personal observations and communication with Boise Depot staff), there is a potential negative impact on 

the overall RAWS data quality.

2. Additional USFS RAWS Coordination Office and Regional Office Personnel. The 

USFS RAWS Coordination Office has a heavy work schedule as indicated by the figures 

and description of duties in the Operations, Protocols, and Organization section above. 

Duties were scaled back in June 2002 (K. Shelley, personal communication 2002), and in 

the future, regional coordinators will take over teaching the RAWS maintenance training 

courses. This may necessitate the transfer of existing personnel or the addition of trained 

regional personnel to help in the management and administration of the network. For example, utilize the part-time Web master who maintains and supports the official FS RAWS 

Web site at the coordinator level to help in responding to queries made through the Web 

site, and so forth.

3. Updated Position Descriptions to Include RAWS-Associated Duties in Position 

Description of All Personnel Involved in RAWS-Related Activities. FS RAWS are 

currently managed as an extra duty in most cases. At all levels of involvement, detailed 

descriptions of RAWS maintenance, administration and other responsibilities should be 

included and explicitly stated in individual Position Descriptions (PD). This would provide 

the incentive and accountability as well as management support and interest for the RAWS 

program and the need for high-quality weather data. Examples of PD phrasing are provided 

in appendices K and M.

4. Ongoing Followup of RAWS Training. Continuing efforts must be made to impress upon 

personnel tasked with WIMS daily duties how critically important the RAWS network, 

data collected, and fire danger indices and components are. This is currently stressed in 

training courses (WIMS, fire behavior, NFDRS, and others; advanced courses are also 

offered for the last two), but ongoing followup is needed. Training courses might be made 

mandatory for personnel tasked with WIMS daily duties.

Table 5: RSFWSU RAWS sensor maintenance report for FY 2001 - (P. Sielaff/RSFWSU 2002)

FM/FT, FT, Non-Met Sensor 

WS WD RH/AT SR SM/ST, TB Hardware TOTALS

Region 1 46 39 51 25 74 177 412

Region 2 37 37 56 1 35 149 315

Region 3 20 19 36 10 48 91 224

Region 4 51 52 51 19 91 198 462

Region 5 102 101 137 33 160 538 1071

Region 6 84 74 110 16 141 225 650

Region 8/9 97 95 128 2 191 182 695

Region 10 0 0 0 0 0 0 0

BLM FIELD 194 184 399 188 367 280 1612

CSEPP 134 134 82 0 7 173 530

NPS 72 72 75 11 132 247 609

OTHER 124 124 134 26 159 621 1188

FWS 44 40 37 7 67 138 333

TOTALS 1005 971 1296 338 1472 3019 8101

Region 1-10: All FS Regions; BLM FIELD: BLM RAWS and others on full ride contract; CSEPP: Chemical Stockpile 

Emergency Preparedness Program; OTHER: BIA, States, City, County, District, Private, or Commercial

Sensors: WS: anemometer; WD: wind vane; RH/AT: relative humidity/air temperature; SR: Solar Radiation

FM/FT: fuel moisture/fuel temperature; FT: fuel temperature; SM/ST: soil moisture/soil temperature; TB tipping 

bucket

Non-Met Sensor Hardware: data collection platform; antenna; solar panel; cable for sensors; telephone modem; 

battery pack; clock, keypad display; GPS
52 USDA Forest Service RMRS-GTR-119. 2003. 

5. Standardization of FS RAWS Duties at Regional and Local Dispatch Level. RAWS 

duties are not standardized across the FS, which result in nonstandard maintenance and 

operational procedures, which is not an optimum management strategy for such a critically 

important weather station network.

6. Increase in ASCADS Support During Fire Season. To avoid interruption of the RAWS 

data flow, ASCADS support during fire season should ideally be increased to 24 hours per 

day, 7 days per week. The RSFWSU and the BLM/NIFC/National Systems Development 

group in effect act as the ASCADS Helpdesk but only during traditional working hours. 

For example, no one was available to provide help when, over the weekend of June 8 and 9, 

2002, ASCADS crashed. A formal ASCADS help desk could have immediately fixed that 

situation.

Upgrades to Stations

1. Additional RAWS Sensors and parameters. The ability to add non-NFRDS user-specified sensors to the basic RAWS sensor suite would provide useful flexibility. This would 

provide for additional site-specific support for fire weather forecasters, meteorologists, 

climatologists, nonfire researchers such as ecological modelers, and regional modeling 

consortia. For example, monitoring soil temperature and moisture could help in improving 

the calculation of the KBDI. Depending on the number and type of sensor, the cost/benefit 

ratio need not be prohibitively high (see the appendix V CD for sensor costs). Along these 

lines, to support weather data use and research activities by the interagency fire community (forecasting, NFDRS, fire behavior models, fire severity requests, and so forth), the 

establishment of a number of expanded RAWS similar to the experimental super-RAWS 

site in Fernberg, Minnesota discussed earlier may be useful. They could provide for 

weather data use by nonfire groups, including university research groups, mesoscale modeling groups, aviation, severe weather forecasting, business applications, climatological 

analyses, air quality monitoring, and others. The number of data parameters that ASCADS 

can ingest should be increased and made adjustable depending on the need and uses of the 

station owner/operators. The latter is part of the ASCADS patch currently (spring/summer 

2003) being implemented.

2. Faster Paced Upgrades. The ongoing RAWS upgrade program addresses many RAWS 

problems. However, the pace might be quickened to replace existing 1980s technology. 

An example of aging stations still in service was found in the Washington-Jefferson NF, 

Virginia: all stations visited were Forest Technology Systems FTS11 models; all are well 

maintained and data are currently being retrieved via telephone (at the local and national 

levels). These stations will become obsolete and non-NFDRS 2000 compliant within 2 to 3 

years. Unfortunately the Washington-Jefferson NF does not have the funds to upgrade to a 

GOES capable system at the present time.

3. New Emerging Sensor Technologies. There are a vast number of manufacturers of meteorological equipment and sensors in addition to those used at present by the RAWS. Our 

sensor survey (appendix V and attached CDROM) was included to give planners, managers, and operators associated with RAWS a thorough listing of available sensors for use in 

gathering fire weather data. Although standardization makes for ease of maintenance, it 

makes sense to keep abreast of new sensor technologies. The question must be asked: Could 

some of these other manufacturers provide less expensive, more reliable equipment without 

sacrificing data quality?

4. Solar Radiation (SR) Data Collection Protocol and Sensor Placement. The instantaneous SR measurement problem is being corrected; however, sensor placement is still not 

optimal for SR measurements, at least on Handar (lunar lander) frames. At present, the instrument is mounted on the top cross beam adjacent to the rain gauge (painted white or light 
USDA Forest Service RMRS-GTR-119. 2003. 53

gray). Reflection from the rain gauge could affect SR readings, so we recommend that the 

sensor be raised to at least to the same height as the top rim of the rain gauge. An alternative 

placement is at the top of the mast if it can support the SR sensor weight.

5. More Frequent and On-Demand Outputs. Increase station transmission frequency to two 

and possibly four times per hour as weather affecting fires can and often does changes at 

these temporal scales. This increase in transmission frequency is currently being planned 

for. Fire danger indices and components also change rapidly – in less than 24 hours – in response to rapidly changing weather as well as diurnally. We recommend that these outputs 

be calculated hourly or possibly on demand during the fire season and especially during an 

incident or prescribed burn.

6. Verification of Conformity of Station to New NFDRS Standards. We note that there does 

not appear to be a specific plan to switch from the old to new NFDRS RAWS standards.

Upgrades to Product and Data Retrieval Systems

1. Continued Development of WFAS. The Wildland Fire Assessment System (WFAS) generates valuable products that are used and understood by both meteorologists and nonmeteorologists from dispatch centers to regional coordination centers (see above and appendix 

G). For these reasons, the continued development of WFAS and its products is in order.

2. Support for ASCADS Re-engineering. ASCADS is at the beginning of a reengineering 

process. Five priority upgrades will hopefully be implemented within 1 year; additional 

items will be added in stages (discussed above in the RSFWSU Strategic Plan in spport of 

NFDRS 2000 standards). It is critical to include in this plan both Quality Assurance and 

Quality Control of RAWS data. One suggestion is to produce a master list of watchdog 

criteria which would be used to determine numerical limits of metadata in ASCADS and to 

correct metadata discrepancies between ASCADS and WIMS. The watchdog criteria exist 

(appendix P), but the authors were unable to locate the actual numerical values short of logging on each individual station through ASCADS.

3. Support of GACCs and Predictive Service Participartion in RAWS. Regional 

Geographic Area Coordination Center (GACC) Predictive Services have been in active 

operation for almost 2 years. In addition to the services and products discussed above, 

new and unique products are being generated. GACC meteorologists have taken personal 

interest in the RAWS within their own areas and in some cases have taken over QA/QC of 

data, maintenance and other site activities. It may be reasonable to establish a permanent 

mechanism for these GACC meteorologists to assume RAWS responsibilities.

4. Correct Data Discrepancies. It should be a priority to plan for correction of errors in 

the existing WIMS/KCfast 13:00 observation climatology; correction of the RAWS datatruncation problem; automation of the daily 13:00 hour RAWS human interface to ensure 

data accuracy; and combine ASCADS and WIMS station classification schemes, including 

auditing station inventories to track the number of RAWS stations in the system.

5. Combination of ASCADS and WIMS functions in One Application/Database: It is 

obvious that the functionality of ASCADS and WIMS overlap and that that overlap is the 

cause of some problems in the integrity of the RAWS data itself. The combination of these 

databases and information management systems into one application is considered in the 

RSFWSU Strategic Plan. It would also most likely provide a cost saving.

Other

1. Periodic Reviews. Periodic reviews of regional FS RAWS programs would result in greater 

uniformity and accountability at dispatch and regional levels and provide a check for proper maintenance and operating procedures. In turn, it would ensure that high-quality data 

reaches ASCADS and WIMS.
54 USDA Forest Service RMRS-GTR-119. 2003. 

2. Exploration of Outsourcing of Limited RAWS Functions. Forest Service RAWS operating costs are roughly $1,350 per year per station, and about $1.1 million per year for 

the entire FS network. Could the private sector manage and maintain the RAWS network 

(functioning as an outsource) at the field level more efficiently? Could these functions be 

outsourced? Basic RAWS data collection and delivery and field maintenance might be outsourced while retaining the functionality of the data processing for value-added fire use 

products. If such changes were ever made, we strongly recommend that data handling, 

access, and retrieval functions remain within the land management agencies: specifically within the operational fire interagency management government community. It 

would be a costly and a significant mistake to allow privatization of the data and its 

use because data is needed by users regardless of ability to pay.

3. QA/QC of All RAWS Metadata. All RAWS metadata and data must be critically and 

objectively examined – a QA/QC process. This has been done for all RAWS in California 

(Brown and others 2002) and is beginning in FS Regions 2 and 3 (T. Mathewson and C 

Maxwell, personnal communication 2002) but not for the entire network. Such a study is 

overdue.

4. Unification of RAWS under One Management Authority. It is clear after reading this 

report that it is difficult to thoroughly grasp the RAWS program and describe the exact 

direction it is moving. Several entities are working on several upgrades, some coordinated, 

some not. Perhaps a single interagency authority to operate RAWS is in order.

Conclusion

The RAWS monitoring network is a national asset and is functioning, even with the inefficiencies of being a multiagency network with many user and owner choices for individual 

station’s operation. At the FS level, station and data quality vary with management of the network within each region. The BLM funds and operates its RAWS stations from the national 

level, top down, under a single quality assurance (QA) authority, while in the FS each Region 

determines its own management approach.

Individual stations meeting NFDRS standards provide data in support of fire weather forecasting and for calculating fire danger rating indices – the primary mission of the network. 

The entire network is in perpetual transition as hardware and software are upgraded and 

data transmission is streamlined. Apart from the standard maintenance and upgrade schedule for RAWS stations, there are other factors driving this process. An increasing number 

of institutions other than those directly involved with fire weather (both public and private) 

are requesting and using RAWS data for fire and nonfire uses and applications. Even more 

important, the Federal interagency fire community is demanding more frequent and higher 

quality weather data for more precise and timely calculation of fire danger indices and components.

Streamlining, upgrading, and maintaining the network are priorities for those directly involved in RAWS management and fire business decisionmaking (K. Shelley, P. Sielaff, and R. 

Gripp, personal communication 2001). Also, suggestions have been discussed and recommendations are being made to improve quality control and quality assurance (QA/QC) of data and 

metadata for NFDRS calculations. The new NFDRS 2000 protocol is designed to ensure that 

each NFDRS station and its sensors receive regularly scheduled maintenance and calibration. 

The NFDRS 2000 (NWCG 2000) establishes strict standards and procedures for NFDRS 

stations that are necessary to maintain a high level of QA/QC. Changes in the RAWS data 

transmission pathway are also under consideration: a DRGS has been installed at NIFC so that 

GOES can transmit data directly to Boise for ingestion by ASCADS. RAWS administration, 

maintenance, and first response personnel in a given FS Region provide critically important 

support and are directly involved in data QA/QC.
USDA Forest Service RMRS-GTR-119. 2003. 55

Finally, separating RAWS monitoring from the overall RAWS function, there are errors in 

existing official RAWS databases that are accessed daily to provide managers with indicies used 

for fire resource deployment decisions—some of these errors are potentially life threatening.

This review has hopefully integrated the general knowledge base of RAWS information, 

and provided an understanding of the network. A consideration of its findings will improve 

RAWS efficiency and performance.

Glossary of Terms and Acronyms

209: Specific fire incident report form; accessed through NIFMID; must be filed daily during 

an incident.

ACC: Area Coordination Center; for example RMACC is the Rocky Mountain Area 

Coordination Center in Lakewood, CO. The Southwest ACC is in Albuquerque, NM.

ADAS: Advanced Regional Prediction System Data Analysis System.

Adjective fire danger rating: An application of NFDRS indices and components based upon 

the primary station fuel model and staffing index (such as ERC or BI). Used primarily 

for public information releases, and fire and resource management decision making.

AFFIRMS: Administrative and Forest Fire Information Retrieval and Management System; 

proto-weather information management system replaced by WIMS in 1993.

AMIS: Aviation Management Information System; generates aviation use reports for FS regions; accessed through NIFMID.

ARF: Arapahoe-Roosevelt National Forest.

ARS: Air Resource Specialists, Inc.; environmental/atmospheric consulting company based 

in Fort Collins, CO.

AFFIRMS: Administrative and Forest Fire Information Retrieval and Management System; a 

computerized proto-weather information management system; no longer in use.

ASCADS: Automated Sorting Conversion and Distribution System, BLM-administered (interagency) database/ system used as a primary method of retrieving data from the GOES 

(see below) satellite and forwarding to BLM Web server, WIMS, the NWS, and the 

WRCC. (ASCADS ingests the retrieved RAWS data from DOMSAT and sorts it into a 

relational database that is menu driven but DOS-based.) It is used for metadata storage, 

maintenance documentation, and produces watchdog alerts. ASCADS is a single source 

for all RAWS data such as maintenance history, sensor suite, location, route, and raw 

weather data; but it is not a long-term storage archive. It is essentially a pump converting data derived from GOES/Wallops Island/DOMSAT to formats accessible to other 

systems.

ASOS: Automated Surface Observing System; sponsored by the NWS, DoD, and the FAA.

ASTM: American Society for Testing and Materials.

AT: Air temperature; measured in degrees Fahrenheit .

AWIPS: Advanced Interactive Processing System; a NWS application used for interactive processing, display of hydrometeorological data, and the rapid disseminations of warnings 

and forecasts in a highly reliable manner.

AWOS: Automated Weather Observing System; primarily located at airports; maintained by 

the FAA or State, local or private organizations.
56 USDA Forest Service RMRS-GTR-119. 2003. 

AWS: Automatic Weather Station, non-GOES telemetered station.

BEHAVE: A fire behavior model; it is a Windows application used to predict wildfire behavior for fire management purposes and uses a minimum amount of site-specific input 

data to predict fire behavior for a single point in time and space. The current version is 

BEHAVEPlus 1.0.

BIA: Bureau of Indian Affairs.

BI: Burn index; see appendix B.

BLM: Bureau of Land Management; part of the USDI (see below).

BP: Barometric pressure.

CDF: California Department of Forestry.

CEFA: Climate, Ecosystem, and Fire Applications; a research group that is part of the DRI 

Division of Atmospheric Sciences, Reno, NV, that is concentrating on fire weather applications. Has carried out numerous climatological and QA/QC studies using RAWS 

data.

CIFFC: Canadian Interagency Forest Fire Centre.

CIRP: Cooperative Institute for Regional Prediction; is developing a Web site for the display 

of recent RAWS data at hourly, daily, and weekly times scales. A collaborative project 

between the RMACC and Eastern Great Basin CC.

Components: Calculated (by the NFDRS model) values related to fire danger, for example, 

spread, energy release, and ignition components.

COTS: Commercial off-the-shelf, referring to a package of software or program or hardware 

available for purchase and use from a commercial vendor.

CSEPP: Chemical Stockpile Emergency Preparedness Program; deals with chemical and 

weapons emergencies.

DAWG: Data Administration Working Group.

DAPS: Data Collection System (DCS) Automated Processing System; all simply known as 

DAPS.

DCP: Data Collection Platform; data-logger of the RAWS.

Delta temperature: Vertical difference in temperature, in air used for atmospheric stability, in 

soil used for heat transport direction and intensity.

Dimensionality: Dimensionality may be viewed as an attempt within the logical mind to resolve the hierarchy of energy into discrete bands, or ranges of experience, so that they 

may be referenced separately. The reality is that there is no separation. There are no clear 

boundaries between one vibrational experience and another. There is only a gradation, 

a phasing of varying states experience. These altered states of awareness are known as 

dreams. Though deceptively simple in appearance, this premise of “oneness” has proven 

difficult to resolve within the rational mind. The ancient texts however have offered this 

very concept, through many different languages, for thousands of years. (Braden 1977)

DOBS: Display observation.

DoD: Department of Defense.

DOE: Department of Energy.

DOMSAT: Domestic satellite transmits RAWS data from Wallops GOES ground station to 

ASCADS.
USDA Forest Service RMRS-GTR-119. 2003. 57

DRI: Desert Research Institute is a part of the University and Community College System of 

Nevada. DRI pursues a full-time program of basic and applied environmental research 

on a local, national, and international scale. Areas include water resources and air quality, global climate change and the physics of the earth’s atmosphere.

EOS: Earth Observing System; a long-term NASA project and the center piece of NASAs 

Earth Science Enterprise.

EPA: Environmental Protection Agency (USA).

ERC: Energy release component; see appendix B.

FAA: Federal Aviation Administration.

F&AM: Fire and Aviation Management, Forest Service, Washington Office responsible for 

national RAWS systems.

F&AM Applications Helpdesk: Fire and Aviation Management Applications Helpdesk; 

real time help via telephone with WIMS, KCFast, SIT, 209, Pocket Cards, AMIS, and 

FEPMIS (1-800-253-5559 or 1-208-387-5290).

FAQ: Frequently asked question.

FARSITE: Fire Area Simulator 2.0; spatially referenced fire behavior model.

FCAMMS: Fire consortia for advance modeling of meteorology and smoke, mesoscale 

weather forecasting centers.

FDWT: Fire Danger Working Team; part of the NWCG (see below).

FEMA: Federal Emergency Management Agency.

FEPMIS: Federal Excess Property Management System; accessed through NIFMID.

FF+ or FFP: Fire Family Plus; a desktop computer application used widely for fire weather 

and occurrence analysis (see appendix B for more details).

Fire danger indices: e.g. Burn Index (BI), NFDRS, 100-hr fuel, etc.

Fire season: Generally, May 1 through October 31, but it depends on the area.

Fire use: Prescribed burns and wildfires that are allowed to burn to achieve management goals.

FM: Fuel moisture as percent of oven dry weight.

FPI: Fire Potential Index; experimental, uses satellite derived greenness, a NFDRS fuel model 

map, and calculated 10-hour fuel moisture to determine potential fire danger, scale 

ranges from 0 percent (low) to 100 percent (high).

FRWS: Fire RAWS; portable weather stations deployed during an incident or prescribed burn.

FS: Forest Service.

FSL: Forecast System Laboratory conducts applied meteorological research and development 

to improve and create short-term warning and weather forecast systems, models, and 

observing technology.

FT: Fuel temperature measured in degrees Fahrenheit.

FTP: File Transfer Protocol, process used to transfer files between different types of systems 

(such as internet, pc to pc, servers, and so forth).

FTS: Forest Technology Systems, Ltd. is a Canadian company that sells fully operational 

RAWS stations. Handar, a subsidiary of Vasaila, Inc. and Campbell Scientific Inc. and 

FTS are the current three major suppliers of RAWS stations.
58 USDA Forest Service RMRS-GTR-119. 2003. 

Fuel model: A simulated fuel complex for which all fuel and site descriptors (such as type of 

fuels, slope, aspect, climate class, and so forth) required by the NFDRS model have been 

supplied.

FWS: Fish and Wildlife Service.

FWWT: Fire Weather Working Team.

Frozen: Opposite of green-up, frozen and green-up dates are specific to each RAWS, each fire 

season.

GACC: Geographic Area Coordination Center; regional level fire business coordination center.

GeoMAC: Geospatial Multi-Agency Coordination Group.

GMT: Greenwich Mean Time or Universal Time Coordinate (UTC).

GOES: Geostationary Operational Environmental Satellite, the satellite used for data relay 

from NFDRS weather stations to ASCADS.

GPS: Geo-Positioning System.

Green-up: The beginning of a new cycle of plant growth used within the NFDRS model.

Haines Index: Also called the Lower Atmosphere Stability Index (LASI); calculated from 

the difference in temperature of two atmospheric levels and dew-point depression (see 

Haines 1988).

HOIC: Human caused occurance index.

HUB: Multimodem PC housed at NITC calling telephone telemetered weather stations, delivering the data to WIMS.

IIAA: Interagency Initial Attack Assessment.

IAMS: Initial Attack Management System; no longer in use, replaced by the BLM/NIFC 

Wildland Fire Management Information system in the late 1990s.

IC: Ignition component; see appendix B.

IMET: Incident Meteorologist; a NWS meteorologist issuing fire weather forecasts from 

Weather Forecast Offices. The term IMET has also been used for GACC meteorologists 

when they work in the field on fires.

Incident Report: A brief report on a wildland fire containing information resources available, 

local weather, size of burned area, expected containment date, and so forth. This form is 

either e-mailed or faxed to a local Forest or Regional (GACC) dispatch center.

IRMWT: Information Resource Management Working Team, chartered to identify policylevel information issues that affect, or are likely to affect, interagency fire management 

activities and to provide advice to NWDG members on how to address those issues 

through information and communication systems.

ISO 9000: International Organization for Standardization.

IWOS: Incident Weather Observing System; new portable fire RAWS under development.

JABOWA: Forest stand growth model; named after the original developers.

KBDI: Keetch-Byram Drought Index; a measure of cumulative moisture deficit in deep duff 

and organic soils; used as an input in the 1988 NFDRS model.

KCFast: Kansas City Fire Access Software; long term RAWS data archive; part of NIFMID.

LAL: Lightning activity level; a numerical rating ranging from 1 to 6 that represents observed 

or forecast strike frequency and characteristics of cloud-to-ground (CG) lightning for a 

fire zone.
USDA Forest Service RMRS-GTR-119. 2003. 59

LOI: Lightning Occurrence Index; a numerical rating of the potential for lightning caused fires.

LST: Local Standard Time.

MCOI: Man Caused Occurrence Index; a numerical rating of the potential for human caused 

fires.

Metadata: information about information; usually nonnumeric. For example as this relates to 

RAWS the station catalog is a metadata file containing general information about the 

station/site (station ID, site description, State and county codes, lat/long, station type and 

name, station owner, conversion codes, access control, site physical description, and so 

forth) and NFDRS parameters (fuel model(s), live fuel type, climate class, annual precipitation, lat/long, and so forth).

METAR: Meteorological Aviation Routine Weather Report.

Meteograms: A time graph of several meteorological elements on a single plot such as AT, 

dew point, and RH).

MIE: Company that manufactures instrumentation (called DATA RAWS) for smoke particulate monitoring.

MODIS: Moderate Resolution Imaging Spectroradiometer; high-resolution satellite images.

MOS: Model Output Statistics.

NAGFDR: National Advisory Group Fire Danger Rating; recently renamed the Fire Danger 

Working Team.

NASF: National Association of State Foresters.

Natural Resource Project-EOS Training Center, University of Montana, Missoula MT: Offers 

training and workshops for natural resource managers in the use of advanced satellite and 

model applications available for evaluating difficult landscape-level measurements – fire 

business decisionmaking. Collaborates with the USDA Forest Service, Rocky Mountain 

Research Station (RMRS) - Fire Sciences Laboratory/WFAS development group (among others) in the development of Surface Moisture Index (SMI) maps and smoke/visibility and wildland fire detection/monitoring programs; the last two involve the use of satellite imagery.

NCAR: National Center for Atmospheric Research.

NCEP: National Centers for Environmental Prediction.

NDVI: Normalized Difference Vegetation Index.

NESDIS: National Environmental Satellite Data Information Service; provides access to 

global environmental data from satellites and other sources. Formed in 1980 by combining the National Environmental Satellite Service (NESS) and the Environmental Data 

Service (EDS) two line offices of NOAA, NESDIS acquires and manages the United 

States operational environmental satellites, provides data and information services, and 

conducts related research.

NFDRS: National Fire Danger Rating System; a computer model that calculates fire danger 

rating indices and components, used for fire business decisionmaking and as a management decision tool. The NFDRS set of computer programs and algorithms allows land 

management agencies to estimate the current day’s and the following day’s fire danger at 

multiple scales and areas. NFDRS characterizes fire danger by evaluating the approximate upper limit of fire behavior in a fire danger rating area during a 24-hour period. 

Calculations of fire behavior are based on fuels, topography and weather: the fire triangle. NFDRS output gives relative ratings of the potential growth and behavior of any 

wildfire. Fire danger ratings are guides for initiating presuppression activities and selecting the appropriate level of initial response to a reported wildfire rather than detailed 
60 USDA Forest Service RMRS-GTR-119. 2003. 

real time site-specific information. NFDRS computations are based on once daily, midafternoon observations (2 p.m. LST) from the Fire Weather Network comprising some 

1,500 weather stations throughout the conterminous United States and Alaska. These 

observations are sent to WIMS where they are processed by NFDRS programs. Many of 

the stations are seasonal and do not report during the nonfire season.

NF: National Forest.

NFMAS: National Fire Management Analysis System; a strategic fire management and budget planning tool based upon a cost-benefit analysis of firefighting activities to support 

fire program budget requests. NFMAS was later adopted by other non-FS wildland firemanagement agencies. NFMAS-based analyses affect the composition, structure, and 

budgets of fire-management organizations.

NICC: National Interagency Coordination Center; based in Boise, ID.

NIFC: National Interagency Fire Center.

NIFMID: National Interagency Fire Management Integrated Database, database/warehouse 

for archiving fire business/management information; includes RAWS weather observations.

NIST: DOC, National Institute for Standards and Technology, Boulder, CO.

NITC: National Information Technology Center, located in Kansas City, MO; the NIFMID/

WIMS/KCFast host.

NMAC: National Multi Agency Coordinating Group; part of NICC (see above).

NOAA: National Oceanographic and Atmospheric Administration, Department of 

Commerce.

NPS: National Park Service, Department of Interior.

NST: National System Team, Information Systems Team for F&AM fire applications.

NWS: National Weather Service, each afternoon NWS Fire Weather Forecasters from the 

National Weather Service also analyze these local observations and issue forecasts for 

fire weather forecast zones.

NRC: Nuclear Regulatory Certification.

NWCG: National Wildfire Coordinating Group, an interagency group established to coordinate programs of the participating wildfire management agencies. Interagency fire 

weather and fire danger working teams within this group make recommendations for 

network and individual station life-cycle management, network standards, better planning, and technology transfer.

O: The 13:00 hour observation, which is the observation used in the fire danger model.

ORACLE: A commercial computer database system.

OSHA: Occupational Safety and Health Administration.

PacNW: Pacific Northwest; common acronym for this FS Region.

PCHA: Personal Computer Historical Analysis.

PC: Personal computer.

PD: Position Description; an FS document detailing job duties and responsibilities.

Pocket Card: The Fire Danger Pocket Card is a method of communicating information on fire 

danger to firefighters. The objective is to lead to greater awareness of fire danger and 

increased firefighter safety. The Pocket Card provides a description of seasonal changes 
USDA Forest Service RMRS-GTR-119. 2003. 61

in fire danger in a local area using graphics and short text. It is used by both local and 

out-of-area firefighters.

Predictive Service Meteorologist: A new breed of meteorologist who work for Federal land 

management agencies in GACCs. They provide “predictive” services for fire business 

purposes as opposed to forecast services provided by NWS. The distinction is a matter of 

semantics and forecast authority.

PSD: EPA Prevention of Significant Deterioration monitoring.

R: All non-13:00 hour observations; they are not used in the NFDRS model; commonly called 

the RAWS observations.

RAWS: Remote Automatic Weather Station, fire weather station network.

Red flag warning: Initiated when weather conditions are such that fire danger is high.

Remote Sensing Unit:

RH: Relative humidity; measured in percentage

Rocky Mountain Area Fire and Aviation Management Web site: This Web site for the Northern 

Rockies Coordination Center provides links to fire intelligence, fire weather, fire danger, 

training, incident management, fire aviation, other GACC’s, and so forth.

RMACC: Rocky Mountain Area Coordination Center, Lakewood, CO.

RMRS: Rocky Mountain Research Station, USDA Forest Service.

RSFWSU: Remote Sensing Fire Weather Support Unit (also known as the Boise Depot); operated by the BLM as an interagency weather station repair and maintenance facility 

located in Boise, ID.

RUC2: Rapid Update Cycle version 2; a numerical weather forecast model.

S-491: Basic intermediate level National Fire Danger Rating System course; taught at various 

times in different parts of the country at Regional training centers, such as Redding, CA, 

Missoula, MT, and other places.

SC: Spread component; see appendix B.

SIG: Special interest group, as used in grouping one or more RAWS data sets for fire applications in WIMS and FF+.

SIT: Interagency Situation Report: report form typically filled out at the dispatch center level 

forwarding to regional level; accessed through NIFMID.

SNOTEL: SNOwpack TELemetry; sponsored by the Natural Resources Conservation Service 

(NRCS); collects and transmits snowpack and related climatic data.

SOP: Standard operating procedure.

SOW: State of the weather; scale of 1 to 9: clear to thunder storms. A SOW of 5,6,7 will zero 

out all NFDRS indices and components.

SR: Solar radiation; usually measured in watts/m2.

SWACC: Southwest Area Coordination Center, Albuquerque, NM.

TREGRO: A tree physiology simulation model that predicts the growth and patterns of carbon 

allocation expected for an isolated tree exposed to various levels of ozone, nutrient stress, 

and water availability.

Tx: Abbreviation for transmission.

USDA: United States Department of Agriculture.

USDAFS: United States Department of Agriculture Forest Service.
62 USDA Forest Service RMRS-GTR-119. 2003. 

USDAFS RAWS Web site: Official RAWS Web site provides an introduction to RAWS and an 

overview of the network, including history, description, rationale for it’s establishment, 

news, technical information, FAQ’s, contacts, and many links.

USDI: United States Department of the Interior.

USGS: United States Geological Survey.

VOR: Very High Frequency Omnidirectional Radio Range.

Watchdog: Automated alert process in ASCADS for assessing weather station performance.

WD: Wind direction.

WFAS: Wildland Fire Assessment System; Web-based interface providing weather and 

NFDRS products, primarily maps. WFAS-MAPS generates national maps of selected 

fire weather and fire danger components (ignition, energy release, and spread components) of the NFDRS. To generate these maps, WFAS queries WIMS each afternoon for 

the daily weather observations.

WFMI: Wildland Fire Management Information; a BLM managed fire weather database it 

replaced the BLM Initial Attack Management System (IAMS) in the late 1990s.

WFO: Weather Forecast Office; part of the National Weather Service (NWS).

WIMS: Weather Information Management System; weather information database; also the host 

for the NFDRS model. WIMS archives (short term) and manages all RAWS data (GOES 

and non-GOES). The 13:00-hour data points are permanently archived, but the 24 hourly 

points are kept for 1 year. WIMS, which was implemented in 1993, was developed as a 

cooperative venture between the Forest Service Weather Program and Fire & Aviation 

Management (F&AM) staffs. WIMS also provides station metadata, fire history, and 

other information,and is accessible via the Internet (user name and password protected).

WO: Washington Office of the USDA Forest Service.

WRAP: Western Regional Air Partnership is a collaborative air quality related effort of tribal, 

state, and various Federal governmental agencies organized to implement the recommendations of the Grand Canyon Visibility Transport Commission (GCVTC) and to 

develop technical and policy tools needed by Western States and Tribes to comply with 

the Environmental Protection Agency (EPA) regional haze regulations.

WRCC: Western Regional Climate Center is one of six regional climate centers in the United 

States, is administered by NOAA and specifically by the National Climate Data Center 

and NESDIS. The mission of the WRCC is to archive and distribute climate data and 

information; promote better use of this information in decisionmaking, conduct applied 

research related to climate; and improve coordination of climate-related activities ranging from local to national scales.

WS: Wind speed.

WWV: Call sign for worldwide universal time radio transmission; used for clock synchronization on RAWS.

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USDA Forest Service RMRS-GTR-114. 2003. 65

Appendix A. Lists of RAWS-Related Entities and Web 

Sites

1. Related Entities

Institution, Dept., Agency 

Database, etc. Affiliation Relation to RAWS/Comments

Arapaho Roosevelt NF USDAFS Arapaho Roosevelt NF dispatch center – fire information for ARNF; 

Interagency Wildfire provides links to other wildland fire sites. Operates RAWS in ARNF.

Dispatch

Automated Sorting, BLM Receives RAWS data from DOMSAT and stores data for 

Conversion, and 30 days. Re-distributes fire weather data to WIMS, WRCC,

Distribution System BLM/NIFC databases.

(ASCADS)

Boise Fire Weather NOAA NOAA/NWS fire weather web site for southern ID. Links to recent RAWS data.

Climate, Ecosystem, DRI/Univ. A research division of the DRI concentrating on fire weather 

and Fire Applications Nevada applications. Has carried out numerous climatological and QA/QC studies 

(CEFA) using RAWS data. 

CA Wildfire Coord. Group Interagency Southern CA Fire Operations web site; displays RAWS data for S.CA.

Fire Application User USDAFS Internet web page listing fire related software and their user guides – both 

Guides can be downloaded.

Fire & Aviation USDAFS FS section working to advance technologies in fire business management 

Management Washington and suppression, maintains and improves mobilization and tracking 

Office systems. Provides funding for the RAWS network and RAWS databases.

Forecast Systems NOAA FSL conducts applied meteorological research and development to improve 

Laboratory (FSL) and create short-term warning and weather forecast systems, and models. 

Uses the RAWS data set among others. 

Geospatial Multi- USGS/ Map-intensive web site, provides recent RAWS data, mapped locations across the 

Agency Coordination GEOMAC United States.

Group

Geostationary Operational NASA GOES home page; satellite initially used for global weather monitoring now

Environmental Satellite also used for data transmission relay for RAWS.

(GOES)

Interagency Geographic Interagency A web site with links to regional GACC sites. GACC Predictive 

Area Coordination GACC Services use RAWS data for fire weather guidance.

Center’s 

Kansas City Fire Access Interagency Long-term RAWS data archive (13:00 hr obs.) and mid-term (18 month)

Software (KCFast) archive of all obs. See text and Appendix D.

MesoWest University Meso-scale forecasting (MM5) group based at the Univ. Utah; see 

of Utah text for brief description. Uses RAWS data set among others.

MM5 Smoke and Fire Univ. of Smoke and fire weather information/resources, MM5 forecast 

Weather Resources Washington output etc. Part of the Northwest Regional Modeling Consortium based at 

the University of Washington, Seattle. See FCAMMS.
66 USDA Forest Service RMRS-GTR-114. 2003. 

MODIS – Moderate NASA High-resolution satellite images; instruments deployed on the EOS Terra and 

Resolution Imaging Aqua satellites. Can detect thermal sources such as fires. Not RAWSSpectroradiometer related as such but used for fire support.

MODIS Rapid Response University Satellite imagery of active fires in the continental United States; taken with the – 

Web Fire Maps of Maryland Moderate Resolution Imaging Spectroradiometer.

National Fire Danger NWS/Inter- A NOAA web site providing a very good summary of the NFDRS 

Rating System (NFDRS) agency which uses RAWS data.

National Fire Plan Interagency Overview, links to other sites, firefighting, rehab., fuels reduction, community 

Web Site assistance. Link to NFP maps by the GeoMAC group.

National Fire Weather NOAA/NWS A NWS Forecast Office, Boise ID. Links RAWS data access from the NWS by state.

/National Weather Service

National Interagency Interagency The nation’s support center for wildland firefighting; coordinates and 

Fire Center (NIFC) supports wildland fire and disaster operations.

National Interagency Interagency BLM fire weather data archive at NIFC – most recent 12/24 hour. Hosted by 

Fire Center (NIFC)/ BLM. RAWS data access for local/dispatch center users. Password protected.

BLM Weather

National Interagency Interagency National interagency Coordination Center; national center for coordination 

Coordination Center and support of wildland fire fighting.

(NICC)

National Wildfire Interagency An operational group designed to coordinate programs of the participating 

Coordinating Group wildfire management agencies. Sets standards for RAWS stations and 

(NWCG) procedures.

National RAWS Data NWS NWS list of RAWS stations by state with access to recent data.

Server/NWS, Boise

Natural Resource University Links to fire and climatological applications; maps of surface moisture 

Project-EOS of Montana stress, temperature, precipitation, etc.

Training Center

NFDRS Forecasting NOAA Instructions for NWS fire weather forecasters on using RAWS data for 

for forecasters NFDRS modeling. 

Northwest Coordination Interagency Pacific Northwest Region GACC. Uses RAWS data for fire business 

Center (NWCC) guidance.

Numerical Weather Data UCAR Central web site providing links to meso-scale weather modeling groups. All 

use RAWS data to help parameterize forecasting models, but not exclusively.

NWS/Portland Fire NOAA/NWS Web site for Portland OR area forecasts, clickable maps, fire weather etc. 

Weather Program NOAA/NWS local office. Access to RAWS and METAR data.

RAWS/AWS USFS USDAFS Internet links to configure PC’s for ASCADS and links to technical notes for 

Fire Application Support RAWS/AWS and the HUB.

RAWS Contact List Interagency USFS, NPS, BLM and FWS regional coordinator’s telephone and email 

contact list.

RAWS Model output NWS Guidance for making forecasts using RAWS data. A statistical approach.

statistics (MOS)

Institution, Dept., Agency 

Database, etc. Affiliation Relation to RAWS/Comments
USDA Forest Service RMRS-GTR-114. 2003. 67

RAWS Temperature/ BLM A statistical assessment/interpretation of the max and min temperature

Humidity and humidity for some key RAWS in the PacNW based on regression

Forecast Guidance equations.

RAWS: Remote Automated USDAFS Official USFS RAWS site, many links. An excellent web site to begin 

Weather Stations learning about the RAWS network.

Remote Sensing Fire BLM Location in Boise ID (at NIFC) where all maintenance and

RAWS calibration of Weather Support Unit equipment is carried out.

(RSFWSU)

Rocky Mountain Area USDAFS Site provides internet links to fire weather, red flag warnings, NWS 

Fire and Aviation websites, RAWS data access, and more for the Rocky Mtn. Region.

Management

Scripps Institution of Univ. CA Developing fire management products from the ECPC regional 

Oceanography/ San Diego spectral model (RSM) and performing verification analysis of RSM fire 

Experimental forecast products. Both in collaboration with CEFA.

Climate Prediction

Center (ECPC)

University of Utah- University Access to RAWS fire weather data, data summaries, model (MM5) 

Cooperative Institute of Utah products, and maps. Parts still under development.

for Regional Prediction

USFS Fire Applications USDAFS User guide for SIT – how to and what to input for the first step in creating 

Support-SIT User Guide the National (fire) Situation Report. Done from the Dispatch Center level. 

The form requires some general weather data input.

USFS National USDAFS Internet home page for the USDA Forest Service.

Home page

USFS/PacSW/Riverside USDAFS USFS laboratory conducting research in fire weather forecasting, fire 

Fire Laboratory behavior, and fire management.

USFS Southwest Region- USDAFS USFS Southwest Region (R3) internet home page for fire operations: fire 

Wildland Fire Operations weather and intelligence, incident management, and predictive services. 

Access to regional RAWS data. 

USFS/RMRS/Missoula USDAFS The Fire Sciences Lab (FiSL), an arm of the Rocky Mountain Research 

Fire Science Laboratory Station located in Missoula, MT, is home to the Fire Behavior Project, Fire 

Chemistry Project, and the Fire Effects Project.

US/Satellite radar java Plymouth St. GOES infrared satellite imagery of thermal sources from Plymouth 

GIF animation College State College weather center.

Ventilation Climate USDAFS/ Mapped and graphed data of wind speed, mixing height, and ventilation 

Information System PNWRS index. Collaborative effort between USDAFS and PacNW Research Station. 

(VCIS) Funded by USDOI-USDA-Joint Fire Science Program.

Watershed, Fish, Widlife, USDAFS FS section studying and managing watersheds, riparian systems, wildlife, 

Air, Rare Plants, and Soil air quality, and so forth. Provides funding for NIFMID maintenance and 

operations, for this report, and Super-RAWS, Fernberg, MN.

Weather Information USDAFS/ Internet site/page providing access to NIFMID and on to WIMS, 

Management System Interagency KCFast, PocketCards, and other non-fire related databases. NIFMID= 

(WIMS)/F&AM Web Apps. National Interagency Fire Management Integrated Database.

Institution, Dept., Agency 

Database, etc. Affiliation Relation to RAWS/Comments
68 USDA Forest Service RMRS-GTR-114. 2003. 

Western Regional DRI/Univ. A division within the DRI; serves as a complete RAWS data 

Climate Center Nevada archive for all hourly obs. and period of record.

(WRCC)

Western Regional DRI/Univ. Welcome page for access to RAWS maps, locations, data

Climate Center Nevada summaries, lister, and so forth. Out of Service.

(WRCC)_RAWS_USA

Western Regional DRI/Univ. RAWS data/access: maps, tables, time series, wind roses, some metadata, etc.

Climate Center Nevada

(WRCC) RAWS and

METAR images and data

Wildland Fire Assessment USDAFS Provides maps of NFDRS components and indices, FWx forecasts, Haines,

System (WFAS) KBDI, Palmer etc. See Appendix G.

Wildland Fire Assessment USDAFS A web site with links to WFAS maps and experimental products: fire 

System (WFAS) – weather, danger ratings, drought, greenness, KBDI, indices and 

Quick Links components, and RAWS weather data (current days and predicted).

Wildland Fire Training USDAFS Interagency list of various fire training courses.

2. List of Selected RAWS-Related Web Sites

Web Site Agency Address/Comments/Reference

Arapaho Roosevelt USDAFS http://www.fs.fed.us/arnf/fire/fire.html

NF Interagency Arapaho Roosevelt NF dispatch center – fire information for ARNF; provides links 

Wildfire Dispatch to other wildland fire sites. 

Automated Sorting, BLM http://www.fs.fed.us/raws/book/primer/ascadsfieldguide.htm

Conversion, and ASCADS tips: http://www.fs.fed.us/raws/book/primer/ascads/tips.shtml

Distribution System These are links to a ASCADS user guide and to a file of helpful hints. RAWS

(ASCADS) database; access is via a terminal emulator and is password protected. See

Appendix P and body of text for more details

Boise Fire Weather NOAA http://www.boi.noaa.gov/fwx.htm

NOAA fire weather Internet site; based in Boise, ID.

Canada Fire Canadian http://www.nofc.forestry.ca/fire/frn/English/frames.htm

Research Service Provides information about the Canadian version of NFDRS.

Network Forest

(Canadian Forest

Service)

Canadian Centre Canadian http://www.ciffc.ca/

Interagency Forest Canadian version of NICC; members include federal, provincial, and territorial

Forest Fire Service forest fire managers.

(CIFFC)

Climate, Ecosystem, DRI/Univ. http://www.dri.edu/Programs/CEFA/

and Fire Nevada A research division of the DRI concentrating on fire weather applications.

Applications (CEFA)

CA Wildfire Interagency http://www.fs.fed.us/r5/fire/south/fwx/raws.shtml

Coord. Group Riverside/South Ops interagency fire forecast and warning unit.

Institution, Dept., Agency

Database, etc. Affiliation Relation to RAWS/Comments
USDA Forest Service RMRS-GTR-114. 2003. 69

DataRAM page USDAFS http://www.satguard.com/usdafs/

Access to airborne particulate matter/smoke/visibility data from deployed

DataRAMS at: wildfires, Rx burns, and so forth. Near real time.

Desert Research University http://www.dri.edu/

Institute (DRI) of Nevada DRI internet home page.

Fire Application USDAFS http://www.fs.fed.us/fire/planning/nist/distribu.htm

User Guides Internet page listing software and their user guides – both can be downloaded.

Forecast Systems NOAA http://laps.fsl.noaa.gov/usfs/usfs_home.html

Laboratory (FSL) Fire weather forecasts/guidance using the MM5/Local Analysis Prediction

System (LAPS) mesoscale model for most of USFS Region 2.

Forecast Systems NOAA http://www.fsl.noaa.gov/

Laboratory (FSL) FSL conducts applied meteorological research and development to improve 

and create short-term warning and weather forecast systems, models, and 

observing technology.

Geospatial Multi- USGS/ http://geomac.usgs.gov/

Agency GEOMAC Map-intensive site, provides RAWS data, mapped locations across the United 

Coordination Group States. Public access does not require password.

Geostationary NASA http://rsd.gsfc.nasa.gov/goes/

Operational GOES home page; satellite initially used for global weather monitoring 

Environmental now also used for data transmission relay for RAWS.

Satellite (GOES)

Interagency Interagency http://www.fs.fed.us/fire/fire_new/links/links_regional.html

Geographic Area GACC Internet links to regional GACC sites.

Coordination

Center’s

Kansas City Interagency http://famweb.nwcg.gov/

Fire Access Long term RAWS and fire data archive; password protected,

Software see text and Appendix D for details.

(KCFast)

MesoWest University http://meteor.met.utah.edu/mesowest/

of Utah Mesonet and forecasting (MM5) group based at the Univ. Utah.

Mesoscale Modeling Interagency/ http://www.atmos.washington.edu/~cliff/consortium.html

Consortia: FCAMMS Northwest All have been established to provide accurate, timely, and useful fire weather 

forecasts, link forecast information with fuel loadings and fire potential, and 

develop improved model predictions of smoke transport and diffusion.

Interagency/ http://www.cefa.dri.edu/Operational_Products/operational_index.htm

California and CEFA products.

Nevada

Interagency/ Rocky Mountain Center

Rocky http://www.fs.fed.us/rmc

Mountains

Interagency/ http://www.ncrs.fs.fed.us/eamc/

Eastern

Interagency/ http://shrmc.ggy.uga.edu/

Southern

Web Site Agency Address/Comments/Reference (section)
70 USDA Forest Service RMRS-GTR-114. 2003. 

MM5 Smoke and University http://www.atmos.washington.edu/gcg/smokeandfire/

Fire Weather of Washington Smoke and fire weather information/resources, MM5 forecast output, and 

Resources so forth. 

MODIS – Moderate NASA http://modis.gsfc.nasa.gov/

Resolution Imaging High-resolution satellite images; instrument deployed on the EOS Terra 

Spectroradiometer and Aqua satellites. Can detect thermal sources such as fires.

MODIS Rapid University http://firemaps.geog.umd.edu/Cont_US_HTML/viewer.htm

Response Web of Maryland Satellite imagery of active fires in the continental United States; taken with the Moderate 

Fire Maps Resolution Imaging Spectroradiometer.

National Fire NWS/ http://www.seawfo.noaa.gov/fire/olm/nfdrs.htm

Danger Rating Interagency NOAA site providing a very good summary of the NFDRS.

System (NFDRS)

National Fire NOAA/ NWS:http://www.wrh.noaa.gov/Boise/index.htm

Weather/National NWS RAWS data access: http://raws.boi.noaa.gov/rawsobs.html

Weather Service NWS Forecast Office, Boise, ID. RAWS data access from the NWS by state.

National Climatic NOAA http://lwf.ncdc.noaa.gov/oa/ncdc.html

Data Center (NCDC) National weather data archive, links to NOAA, NESDIS.

National Fire Interagency http://www.fireplan.gov/index.cfm

Plan Web Overview, links to other sites, firefighting, rehab., hazardous fuel reduction, 

Site community assistance. Link to NFP maps by the GeoMAC group.

National Interagency http://www.nifc.gov/

Interagency The nation’s support center for wildland firefighting; coordinates and 

Fire Center supports wildland fire and disaster operations.

(NIFC)

National Interagency http://www.nifc.blm.gov/nsdu/weather/index.html

Interagency BLM fire weather data archive at NIFC – most recent 12/24 hour. Hosted by Fire Center

(NIFC)/BLM BLM. RAWS data access for local/dispatch center users. Password protected.

Weather

National Interagency http://www.nifc.gov/nifctour/nicc.html

Interagency National interagency Coordination Center; national center for coordination 

Coordination and support of wildland fire fighting.

Center (NICC)

National Interagency http://www.nwcg.gov/

Wildfire An operational group designed to coordinate programs of the participating 

Coordinating wildfire management agencies. Provides links to publications and other 

Group (NWCG) fire sites.

National RAWS NWS http://www.boi.noaa.gov/FIREWX/Raws/TABLES/rawsText.htm

Data Server/ NWS list of RAWS stations by state with access to recent data.

NWS, Boise

Natural Resource University http://eostc.umt.edu/forestry/default.asp

Project-EOS of Montana Links to fire and climatological applications; maps of surface moisture 

Training Center stress, temperature, precipitation, and so forth.

NFDRS Forecasting NOAA http://www.wrh.noaa.gov/portland/nfdrs.htm

for forecasters Web page on NFDRS ‘how to’ for forecasters.

Web Site Agency Address/Comments/Reference (section)
USDA Forest Service RMRS-GTR-114. 2003. 71

NOAA Fire NOAA http://www.spc.noaa.gov/fire/

Weather site NOAA Storm Prediction Center: fire weather forecasts.

Northwest Interagency http://www.or.blm.gov/nwcc

Coordination Northwest region GACC.

Center

(NWCC)

Numerical Weather UCAR http://www.rap.ucar.edu/weather/model/

Data Central web site providing links to meso-scale weather modeling pages 

(see also Interagency Modeling Consortia).

NWS/Portland Fire NOAA/ http://nimbo.wrh.noaa.gov/portland/fwx.htm

Weather Program NWS Portland, OR, area forecasts, clickable maps, fire weather, and so forth. 

NOAA/NWS local office.

Public Broadcasting PBS/NOVA http://www.pbs.org/wgbh/nova/fire

System PBS/NOVA web site of a television program about wildland fire broadcast 

on May 7, 2002.

RAWS/AWS USFS USDAFS http://www.fs.fed.us/land/fire/planning/nist/raws_aws.htm

Fire Application Internet links to configure PCs for ASCADS and links to technical notes for 

Support RAWS/AWS and the HUB.

RAWS Contact Interagency http://www.fs.fed.us/raws/contacts.shtml

List USFS, NPS, BLM and FWS regional coordinator’s telephone and 

e-mail contact list.

RAWS: Remote USDAFS http://www.fs.fed.us/raws/

Automated Official USFS RAWS site, many links.

Weather Stations

RAWS data NWS http://raws.boi.noaa.gov/rawssum.html

summaries NWS RAWS data summaries by state.

(12 and 24 hour

obs)_NWS

RAWS Fact Sheet BLM http://www.fire.blm.gov/FactSheets/raws.htm

RAWS FAQS.

RAWS location NWS http://raws.boi.noaa.gov/rawsidx.html

information List of all RAWS sites (NWS)by state, lat/long, elev., and abbreviated 

list of sensor suite.

RAWS Model NWS http://www.wrh.noaa.gov/Saltlake/projects/ifp/data/RAWSMOS/rmoslist.html

output statistics RAWS/MOS fire weather forecasts and guidance for making such forecasts.

(MOS)

RAWS Temperature BLM http://www.or.blm.gov/nwcc/nwcc-reports/rawsguide/product.htm

/Humidity Forecast A statistical assessment/interpretation of the max and min temperature and

Guidance humidity for some key RAWS in the PacNW based on regression equations.

Real-time Observation University http://www.met.utah.edu/roman/

Monitor and Analysis of Utah/ Access to RAWS fire weather data, data summaries, links to model (MM5) products, 

Network (ROMAN) MesoWest maps, GACCs, NWS, and AWOS.

Regional (USFS) USDAFS Northern Rocky Mountain (R1): http://www.fs.fed.us/r1/

websites Regional (USFS) websites – links to regional information.

Web Site Agency Address/Comments/Reference (section)
72 USDA Forest Service RMRS-GTR-114. 2003. 

USDAFS Rocky Mountain Area (R2): http://www.fs.fed.us/r2/

USDAFS Southwestern (R3): http://www.fs.fed.us/r3/

USDAFS Intermountain (R4): http://www.fs.fed.us/r4/

USDAFS Pacific Southwest (R5): http://www.fs.fed.us/r5/

USDAFS Pacific Northwest (R6): http://www.fs.fed.us/r6/

USDAFS Southern (R8): http://www.fs.fed.us/r8/

USDAFS Eastern (R9): http://www.fs.fed.us/r9/

USDAFS Alaska (R10): http://www.fs.fed.us/r10/

Remote Sensing BLM http://www.nifc.gov/nifctour/remsens.html

Fire Weather RSFWSU web tour plus information about the Boise Depot.

Support Unit

(RSFWSU)

Rocky Mountain USDAFS http://www.fs.fed.us/r2/fire/rmacc.html

Area Fire and Site provides Internet links to fire weather, red flag warnings, NWS websites, 

Aviation Management RAWS data access, and more for the Rocky Mtn. Region.

Rocky Mountain USDAFS/ http://rockys28.cr.usgs.gov/fweather_dev/viewer.htm

Area Red Flag USGS Mapped information of red flag warnings, fire weather watches as well

as links to information on fire fuels, RAWS weather, situation reports,

geographical features, cities, roads, and political boundaries.

Scripps Institution Univ. CA http://ecpc.ucsd.edu/

of Oceanography/ San Diego Developing fire management products from the ECPC regional spectral model 

Experimental (RSM) and performing verification analysis of RSM fire forecast products. 

Climate Prediction Both in collaboration with CEFA.

Center (ECPC)

University of Utah University http://www.met.utah.edu/

– Dept. of of Utah University of Utah – Dept. of Meteorology internet home page.

Meteorology

US/Satellite radar Plymouth http://vortex.plymouth.edu/psc_satrad_an.html

java GIF animation St. College GOES IR satellite imagery from Plymouth State College weather center.

USFS Fire USDAFS http://www.fs.fed.us/land/fire/planning/nist/sit_ug/situserguide2001_a.pdf

Applications User guide for SIT – how to and what to input for the first step in creating 

Support-SIT the National (Fire) Situation Report.

User Guide

USFS National USDAFS http://www.fs.fed.us/

Home page Home page for the USDA Forest Service.

USFS/RMRS/ USDAFS http://www.firelab.org/

Missoula Fire The Fire Sciences Lab (FiSL), an arm of the Rocky Mountain Research Station

Science Laboratory located in Missoula, MT, is home to the Fire Behavior Project, Fire Chemistry

Project, and the Fire Effects Project.

USFS/PacSW/ USDAFS http://www.rfl.psw.fs.fed.us/index.html

Riverside Fire USFS laboratory conducting research in fire weather forecasting, fire

Laboratory behavior, and fire management.

USFS Southwest USDAFS http://www.fs.fed.us/r3/fire/

Region-Wildland USFS Southwest Region (R3) Internet home page for fire operations:

Fire Operations weather, intelligence, and management. 

Web Site Agency Address/Comments/Reference (section)
USDA Forest Service RMRS-GTR-114. 2003. 73

Ventilation Climate USDAFS/ http://www.fs.fed.us/pnw/fera/vent

Information PNWRS Mapped and graphed data of wind speed, mixing height, and ventilation index. 

System (VCIS) Collaborative effort between USDAFS and PacNW Research Station.

Weather Information USDAFS http://www.fs.fed.us/fire/planning/nist/wims.htm

Management Interagency http://famweb.nwcg.gov/

System Internet site/page providing access to WIMS/KCFast/SIT/209/Pocket

(WIMS)/F&AM Cards/AMIS/FEPMIS. Password protected, interactive.

Web Apps.

Western Regional DRI/Univ. http://www.wrcc.dri.edu/index.html

Climate Center Nevada A division within the DRI; serves as a RAWS data archive as well as weather 

(WRCC) + data from other networks. Provides many other weather-related products.

multiple links

Western Regional DRI/Univ. http://www.wrcc.dri.edu/wraws/

Climate Center Nevada Welcome page for access to RAWS maps, locations, data summaries, and 

(WRCC)_ so forth. Inactive.

RAWS_USA

Western Regional DRI/Univ. http://www.wrcc.dri.edu/raws/raws2.html

Climate Center Nevada RAWS weather data access: maps, tables, ime series, wind roses, etc..

(WRCC) RAWS

and METAR images 

and data

Wildland Fire – USDAFS http://www.fs.fed.us/land/wfas/

Assessment Provides maps of NFDRS components and indices, FWx forecasts, Haines,

System (WFAS) KBDI, Palmer etc.

Home Page

Wildland Fire – USDAFS http://wfas.net/cgi-bin/nav.cgi?pages=wfas&mode=6&fullpageview

Assessment Links to WFAS maps and experimental products: fire weather, danger ratings,

System (WFAS) drought, greenness, KBDI, and indices and components.

Quick Links

Wildland Fire USDAFS http://www.fs.fed.us/fire/fire_new/training/fire_training.html

Training Interagency list of various fire training courses.

WRCC RAWS DRI/Univ. http://wrcc.sage.dri.edu/fire/RAWS.html

Climatology Nevada Access to Nevada RAWS climatology: single images, animations for the 

Products period 1985-1995.

 

Web Site Agency Address/Comments/Reference (section)
74 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix B. NFDRS Structure and Operations

Prior to the late 1960s, a number of fire danger rating systems were used by different land 

management agencies and in different parts of the United States; there was no consistency. 

The National Fire Danger Rating System (NFDRS) was developed to address this problem; it 

was released for use in 1972. The design resulted in a model that is scientifically based, adaptable by local fire managers, applicable anywhere in the United States, and fairly inexpensive to 

operate. The model was upgraded in 1978 and again in 1988; the basic structure of the present 

day NFDRS is given below in Figure B-1.

Fire danger is commonly described as: The resultant descriptor of the combination of both 

constant and variable factors which affect the initiation, spread, and difficulty of control of 

wildfires on an area. Factors such as fuels, weather, topography, and risk are integrated to 

evaluate the daily fire potential in an area. The NDDRS combines the effects of current and 

expected conditions of certain fire danger attributes into one or more adjective or numeric 

indices that reflect an area’s protection needs. The rating for an area provides the manager a 

tool to evaluate and make day-to-day (and even 2-3 days in advance) fire business decisions 

such as staffing levels, pre-positioning or re-distribution of resources, and severity requests 

(emergency funding). Danger ratings reflect the general conditions for very large areas – tens 

Figure B-1: Basic structure of the National Fire Danger Rating System (from: NWCG – Fire Danger 

Working Team. January 2002. Gaining a Basic Understanding of the National Fire Danger Rating 

System: A Self-Study Course. Sponsored by: USDA, USDI, NASF).
USDA Forest Service RMRS-GTR-119. 2003. 75

of thousands of acres – affecting an initiating fire and can be calculated for both current and 

predicted conditions. The interpretation and application of NFDRS products is based upon 

four underlying assumptions:

• It relates to the potential of an initiating fire that spreads without extreme behavior, through 

continuous fuels on a uniform slope,

• Fire activity is addressed from the standpoint of containment not putting out a fire,

• Danger ratings are relative and are linearly related,

• Ratings reflect near worst-case circumstances in exposed locations and during the warmest 

and driest part of the day.

The NFDRS is comprised of three major parts:

• The parameters, constants, and formulae used to calculate fire-spread, rates of combustion, 

and ignition temperatures,

• Site descriptors (meta data) for the rating area – fuel model(s), slope class, grass type (annual vs. perennial), climate class, annual rainfall, etc.

• Data used to calculate daily ratings take two forms: weather observations and the parameters used to control the actual calculations with the NFDRS model.

Changes in the weather can affect the daily danger ratings significantly. Quality control is 

thus extremely important - of the data itself and at every step of the data stream, as well as of 

the instruments used to collect it. The other parameters are user-defined and may change during the course of a fire season; they include state of herbaceous vegetation, shrub type, staffing 

index thresholds, fuel moisture, season codes and greenness, and KBDI.

Today there are three processors generating daily fire danger indices and components all 

using the same computer code: WIMS, Fire Family Plus, and Fire Weather Plus. WIMS is a 

system that helps users manage weather data/information. It is also the host for the NFDRS 

and many federal and state fire and resource management agencies use WIMS to generate 

their fire danger ratings. Hourly data from RAWS across the United States are sent to WIMS 

and archived (but only for a maximum of two years) in the NIFMID for future reference and/

or analysis. Station meta-data is also stored in WIMS. The advantage of a central management system and processor such as WIMS/NFDRS is that data are stored automatically and 

available to all users. Anyone can directly access station records, data, and outputs from any 

station in the RAWS network. The NFDRS model itself has been described in great detail by 

Cohen and Deeming (1985).

Fire Family Plus is a recently released desk-top PC Windows application operating against 

a MS Access database; version 3.1 was released in summer 2003. The package is a suite of 

modules with which the user can generate summaries of fire weather, danger ratings, and fire 

occurrence for one or more RAWS in a given area or adjacent areas from data extracted from 

NIFMID. This allows the user to analyze fire danger as it affects fire business, generating fire 

danger and climatology trends, fire business decision thresholds, fire fighter pocket cards, and 

weather and NFDRS product troubleshooting.

Fire Weather Plus is a PC-based application originally developed by Forest Technology 

Systems (FTS) to support fire danger calculations for RAWS (and other remote stations) 

marketed by the company. The developers have recently added modules enabling the user to 

interface with other (non-FTS) weather stations. Because the core of the package is the same 

code as that used by WIMS/NFDRS and Fire Family Plus, the same input parameters would 

result in the same output as WIMS/NFDRS or FF+.
76 USDA Forest Service RMRS-GTR-119. 2003. 

NFDRS Outputs/Products

Interrmediate

These are the modeled moistures for the different classes of live and dead fuels, which are 

in turn used to calculate the final NFDRS indices and components. Live fuel moisture (FM) 

is calculated for herbaceous and woody vegetation; parameters for both types tend to start 

low at the beginning of a fire season, reach a peak mid-season, and decline as the vegetation 

senesces. Climate class will affect values as will vegetation type within each broader class, 

thus, annuals will dry at a faster rate than will perennials.

• Dead fuel moisture is calculated based upon precipitation and relative humidity. Fuel moistures are determined for each of the four time-lag fuel classes: 1 hr, 10 hr, 100 hr, and 1000 

hr; the 10 hr FM is also measured directly. The time-lag of a fuel class is proportional to 

its diameter and is loosely defined as the time it takes a fuel particle to lose (or gain) 2/3 

of the difference between the current level of moisture within the fuel and the equilibrium 

moisture content.

• The X-1000 hr FM is not a dead FM, but rather a fuel moisture recovery value and is used 

to calculate the live herbaceous FM over the course of the fire season.

Indices and Components

The ignition component (IC) is the probability that a firebrand introduced into a fine fuel 

complex will cause a fire requiring containment action. The ignition component can range 

from 0 when conditions are cool and damp, to 100 on days when the weather is dry and windy. 

Because such a fire must have the potential to spread, the spread component is one of the drivers used in the calculation of the IC; the other is 1 hr FM which in turn is driven by hourly 

and daily weather (AT/RH, SOW, and indirectly WS). As a result the IC can change rapidly, 

as frequently as hour to hour.

The burn index (BI) is a number relating fire behavior to the amount of effort needed to 

contain a single fire in a particular fuel type within a rating area, and is directly driven by the 

spread component (SC) and the energy release component (ERC).

The SC is the forward rate of spread at the head of the fire in feet per minute. The SC value 

is derived from a mathematical model that integrates the effects of wind and slope with fuel 

bed and fuel particle properties to calculate the forward rate of spread. The SC is different for 

each fuel model.

The ERC is defined as the potential available energy per square foot of flaming fire at the 

head of a fire, and is given in units of BTUs per square foot. Like the SC, the ERC is unique 

for each fuel model. The rate of combustion is almost totally dependent on the same fuel properties as are considered in the SC calculation. However, the main difference in the calculation 

of the two components is that the FM of finer fuels determines SC whereas ERC calculations 

require moisture inputs of the entire fuel complex, live and dead. Because WS does not enter 

the calculation of the ERC, day-to-day variation is not large.

The fire load index (FLI) is a rating of the maximum effort required to contain all probable fires in a given danger rating area during a given period of time. Because the FLI is a 

composite of the IC, SC, and ERC plus human and lightning caused risk inputs, it is highly 

variable from one administrative unit to another. This index provides no information as to 

the potential fire danger as the other indices and components do, and so is seldom used in fire 

business decision making.

The Keetch-Byram drought index (KBDI) is not a product of the NFDRS, but is a standalone index used to gauge the effects of drought on fire potential. The actual value of the index 

is an estimate of the amount of precipitation (in 0.01 inches) needed to saturate soil so a value 

of 0 is complete saturation of the soil. The index only deals with the top 8 inches of the soil 
USDA Forest Service RMRS-GTR-119. 2003. 77

profile, so a KBDI value of 800 (the maximum) means 8.00 inches of precipitation would be 

needed to bring the soil back to saturation. The Keetch-Byram Drought Index’s relationship 

to fire danger is that as the index value increases, the vegetation is subjected to increased 

moisture stress and begins to dry and live fuel is added to the dead fuel load in a given area. 

The KBDI can be used in combination with other 1978 NFDRS products to help in decision 

making, KBDI is a requisite input if using the 1988 NFDRS model.

Applications of NFDRS Products

Geographic Area Coordination Centers (GACCs) assess their readiness levels on a daily 

basis based upon forecast fire activity. Actions can include pre-positioning of resources, recalling off duty personnel, ordering additional equipment, or pre-planning dispatch and response actions. These contingencies are all part of fire business and can be very expensive, so 

high-quality fire danger information (NFDRS product) is critical which in turn requires highquality data used for model input. The last includes site descriptions (fuel models and fuel 

types, climate class, slope, aspect, mean ann. rainfall etc.) and hourly and 13:00 hr weather 

data (RAWS).

For fire management pre-planning, individual GACC’s or fire danger zones must decide 

which index or component reflects the unit’s response needs. Comparison of past fire sizes 

with corresponding SC, IC, ERC, or BI can help in making this decision. Examining the 

meaning of each can help in deciding what resource is best suited in containing a fire. For 

example: how well does an individual component or index correlate to ultimate fire size? Fire 

Family Plus and NFDRS can provide these answers. Plans for initial and continued response 

to an incident can be made based on these types of analyses.

The NFDRS model also calculates fire danger adjective ratings; these are primarily for 

public use and range from low to extreme. The ratings are driven by weather, the primary 

fuel model specified for the area, the slope, aspect, climate class, and grass type, and the fire 

danger index or component associated with the fire zone.

The USFS and other land management agencies have a process whereby local units (national 

forests or ranger districts) can request additional funding to augment their basic fire suppression budget. Criteria for such severity requests require supporting data showing that current 

conditions are significantly worse than originally forecast (and so planned for). One method 

is to compare current NFDRS indices or components with historic worst case and ‘normal’ 

data for the same dates. The ERC and 1000-hr fuel moisture are often used for these types of 

comparisons and Fire Family Plus is an excellent tool for analyses at this spatial scale.

NFDRS products are also used in the creation of firefighter pocket cards; the cards contain 

information relative to current conditions, seasonal trends, and comparisons with historic patterns. In addition the cards contain information about NFDRS indices and components for the 

local area, thresholds of extreme fire behavior, and local fire danger interpretations. The cards 

can be created through the National Fire and Aviation Management Web Applications web site 

or by using Fire Family Plus, see Appendix E for an example.

Finally, NFDRS ouput is used to calculate daily industrial (logging) fire precaution level 

(IFPL), to guide public use restrictions, and to help in wildland fire suppression go-no go decisions.
78 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix C-1. NIFMID Flow Chart N I F M I D (NIFMID) ational nteragency ire anagement ntegrated atabase Kansas City, MO Pocket Cards Firefighter Pocket Cards 209 Incident Situation Report regular documentation of a given incident web-based application

All part of NIFMID, see Appendix C2, D, E, R and S for details

Also part of NIFMID but require no weather data input

guidelines generates aviation use

reports for FS regions, user

units, aircraft type, contract

number, start/end date,

supplying unit

call F&AM help desk for

some info how to’s

createactual pocket cards fromsome FS regions/forests

web-based application historical weather & fire

occurrence datalinks to other products

web based application tomanage RAWS weatherdata and help manageinformation stored in theNational Interagency FireManagement IntegratedDatabase (NIFMID)short term archive for RAWSdata (2 yrs)see Appendix C2 forWIMS/WEBApplication MenuHierarchyNFDRS generates fire dangerRA

ratings

WS weather data are

input variables to primar

NFDRS

y

IC, SC, ERC, BI, OI, FLI

reportssoftware

graphics

along with station cataloginfo staffing levels andadjective ratings aregenerated

local (SIG’s, Nf’s) NFDRS

products fed into local

situation report

see Appendix D forKCFast flow chart

passed to regional/gacc

level for larger scalesituation report

passed to NICC to generatenational situation report

date, time, location, name,

current situation, committed

resourcesupdated 12 hrs. during

incident

SIT

National Situation

Report

KCFast

Kansas City Fire

Access Software

see Appendix R for an

example & description

see Appendix S for an

example & description

see Appendix E for an

example & description

WIMS

Weather Information

Management System

FEPMIS AMIS

Aviation Management

Information System

Federal Excess Property

Management System

Appendix C1: National Interagency Fire Management Integrated Database (NIFMID): Umbrella Structure for WIMS/KCFast/SIT/209/Pocket Cards/AMIS/FEPMIS
USDA Forest Service RMRS-GTR-119. 2003. 79

Appendix C-2. WIMS/WEB Application Menu 

Hierarchy

This appendix shows the WIMS/WEB application hierarchy of menus and forms (adapted 

from WIMS User Guide, June 2001). Top level menu choices are in blue, second tier are 

shown in red, third tier in black, and fourth tier in green. The WIMS Web Application User 

Guide provides significantly greater detail than this appendix; it is also available for download from the Internet USDA Forest Service Fire Application Support, User Guides (http:

//www.fs.fed.us/fire/planning/nist/distribu.htm). Acronyms are defined in the Glossary. Page 

numbers of major headings in the User Guide are also given where applicable.

DATA – Data entry and manipulation

OBS – Observations (p. 84)

NOBS – To display the create observation form i.e. enter a new observation for a station or a 

station within a special interest group (SIG) for all fields – station ID, time, type, SOW, AT, RH, 

WS, WD, etc.

EOBS – Edit observations; user can edit previous observations or correct invalid archived data

DOBS – Display observations – allows user to display observations from a RAWS

DRAWS – Display RAWS – allows user to display RAWS observations from a single station or 

from all stations within a SIG

HOBS – Help for user on the OBS menu choice

FCST – (p.100) Forecasts – allows user to display, create, and edit weather forecasts. The NWS 

does in fact provide these narrative forecasts which are stored in WIMS in a shared file directory

DFCST – Display forecasts

DPFCST – Display point forecasts; display a site specific weather forecast for a station or 

SIG for a specific day and time

DTFCST – Display trend forecasts; displays forcasted weather information for a station or 

SIG over a given time period

DNFCST – Display narrative forecasts

SPOT – Spot

SMOKE - Smoke

NFCST – New forecasts; enter new forecasts – for NWS-user authorized only

NPFCST – Enter new point forecasts

NTFCST – Enter new trend forecasts

EFCST – Edit forecasts; with the two options directly below allows user to:

EPFCST – Edit point forecast for a station or SIG

ETFCST – Edit trend forecast for a station or SIG

STA – Station information (p.43); before weather observations can be entered for a given station 

associated information (meta data) must be entered and stored in WIMS

MSTA – maintain station; allows user to create a new manual or RAWS station, edit an existing 

station, list existing stations, edit NFDRS parameters

NSTA – New station; enter meta data for a new station (becomes part of the station catalog) 

– station ID, site description, state and county codes, lat/long, station type and name, station 

owner, conversion codes, access control etc. general station information

ESTA – Edit station; display or edit station catalog information or add or delete sensors of a 

RAWS station. This also includes editing NFDRS parameters

LSTA – List station; list station numbers (NESDIS ID) of a specific owner, list all station 

numbers of a specific agency, list all station numbers of a specific owner for a given 

observation time

ENFDR – Display/edit default NFDRS parameters; after creating a new station and saving 

the information WIMS displays the Create Default/Edit NFDRS Parameters form; the user 

must enter additional meta data for use by the NFDRS model in order for fire danger indices 

and components to be calculated (see Appendix 8 for more NFDRS details)

MSIG – Maintain special interest groups (SIG’s); stations in different locations, regions, or 
80 USDA Forest Service RMRS-GTR-119. 2003. 

administrative boundaries can be grouped together to form a special interest group this also 

applies to stations within an area, region, or admin. unit. A station within one SIG can also be a 

member of one or more other SIGs. Each station within a SIG is weighted reflecting its relative 

importance within the group; the sum of weights for the group must equal one. Fire danger 

indices and components can be calculated for the group as a whole.

NSIG – New SIGs; create a new special interest group – enter the station number of each 

station to be included in the group

ESIG – Edit SIGs; the user can add or delete station numbers of a SIG

DSIG – Delete SIGs; the user can delete an entire SIG or SIGs if no longer needed or used

LSIG – List SIGs; allows user to list SIGs owned by the user or another user

EAVG – Display/edit NFDRS weight assignments; mentioned above and allows the user to 

assign weights to individual stations within a SIG to calculate weighted average values for 

NFDRS indices and components. The weights are a reflection of the importance of a station 

relative to the others within the group. Criteria for assigning weights include such factors as 

the area a station represents, historic fire occurrence, public use patterns, importance to local 

managers

MACL – Maintain access list; a list of those who are allowed access to enter or edit weather 

station data for an individual station or SIG

NACL – New access control list; create a new access control list for specific WIMS users

EACL – Edit access control lists; add, delete, and change access designations

DACL – Delete access control list; delete a list that is no longer needed

LACL – List access control list; allows a user to identify access lists that the user or another 

WIMS user owns

HMACL – Help MACL; help with access lists

HSTA – Help with station information (STA)

DNFDR – Display National Fire Danger Rating (p.124); display NFDRS information

DIDX – Display index format; allows user to display key fire weather variables for regular and 

special observations and forecasts; variables include fuel model, fuel moisture content, wind 

speed, wind direction, IC, ERC, SC, BI, FLI, staffing leveladjective fire danger rating, KBDI 

etc.

DIDM – Display moisture index form; allows the user to track and compare key NFDRS carry 

over values for a list of observations including the x1000 live fuel moisture. Calculated vs. 

measured woody fuel moisture can be compared. Live fuel moisture recovery value for the 1, 

10, 100, 1000, and x1000 hour fuels can be compared on a daily basis.

DMGR – Display manager format; allows the user to display a number of different fire weather 

elements/parameters as well as NFDRS indices and components

DSHR – Display short format; displays station information such as fuel model/slope class/grass 

type/climate class, total precipitation (ppt.), hours of ppt., adjective fire danger, staffing level

DAVG – Display weighted averages for a SIG; combines NFDRS indices and components from 

individual weighted) stations within a SIG into a single index or component

DABR – Display abbreviated format; user can display a shortened version of the Index form 

(DIDX above) for regular and special observations; key fields include IC, SC, ERC, BI, etc.

PLST – (p.37) Data capture from OBS/FCST/NFDR; capture and save data in a simple text format 

for stations or SIGs; the user can specify type and number of observations, number of NFDRS 

observations, number of forecasts, and number of NFDRS forecasts

UTIL – Utilities (p.138); the user can custom tailor a WIMS profile, send and receive e-mail, and 

access different WIMS files from Private and Shared File directories

PROFILE – Profile setup and edit; fields include name, agency, WIMS menu to display, 

financial accounting information, telephone numbers, etc.

LUSER – WIMS user list (logon ID’s and names); provides a listing of WIMS logon IDs and 

WIMS user names and telephone numbers

NWSPROD - National Weather Service products (p.119)

FWFCST – Fire weather forecasts; fire weather forecasts are issued twice daily by the NWS 

fire weather forecast office and contain: discussion of weather activity for an area and an 

overall forecast for each zone. These forecasts remain in WIMS for three days. This option 

displays a list of available forecasts.

REDFLAG – Red Flag Warnings; these warnings outline specific areas where the forecasted 
USDA Forest Service RMRS-GTR-119. 2003. 81

fire weather conditions indicate imminent fire danger i.e. high temperature, low humidity, and/

or high wind speed. Criteria can vary depending on local conditions. Similar to fire weather 

forecasts this option displays a file directory/listing of red flag warnings for the current day and 

the previos three days

SPOT – Spot forecasts; these are issued by the NWS as requested by the user for a specific 

location and time; they include forecast location information, a discussion of weather activity, 

and an overall forecast, forecasted temperature, and forecasted humidity. All spot forecasts 

currently available are listed.

SMOKE – Smoke management forecasts; these are issued by state meteorologists and display 

wind and airflow forecast information for prescribed burn purposes

ONARR – Various other narratives; these include all other available forecast information in 

narrative format such as marine forecasts

FMWS – Fire management web sites: internet hyperlinks to a number of fire weather and RAWS 

related web sites

NIFC – National Interagency Fire Center

FAMAH – F&AM Fire Application Helpdesk

WFAS – Wildland Fire Assessment System

FWX – Boise Fire Weather Page

WRCC – Western Rgional Climate Center

NWS – National Weather Service, main page

USFSFTP – U.S.Forest Service ftp site

RAWS – Official USFS RAWS site

ADMIN – System administration; unavailable to the general user and not discussed in the WIMS 

User Guide

MSHARE -

SETUP – DBA maintenance menu

LOGS – NWS/RAWS log display

EOWN –

DSTA – Delete station information

HADMIN –

HWIMS – WIMS help; on-line help with WIMS

EXIT – Exit; exit/log-off from WIMS
82 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix D. KCFast Flow Chart

KCFast is a web-based, long-term RAWS data archive for weather, fire occurrence, fire 

numbers, and fire reports. The application also provides various products such as situation reports and Internet links to graphics and software. Weather data for the entire period of record 

can be retrieved in two different formats: The 1972 (only the 13:00 hour observations) or the 

1998 (all hourly observations if they archived). All details are given below in the flow chart; 

for acronyms see the glossary. 

Weather

data extract

standard extract

reports

graphics

software: WIMS software library

fire reports

fire number summary: by region, forest, and

date range

fire number by forest: all forests in the us

station catalog

other sources

Fire

Products

Setup

About KCFast

historical

station information

no. fires & acres burned by year for admin. unit

NICC daily SitRep

enter e-mail address

very brief description of KCFast web application

enter FTP site for extracted data files

all

BEHAVE43

ACHA

IIAA FARSITE

WFAS

NAS morning report

KCFast PC: KCFast PC-DOS

CIFFC firewire report

CIFFC firewire report

no. fires & acres burned by

district by year for admin. unit

fire causes & acres burned by year for admin. unit

fire causes by year for admin. unit

fire causes by year by district for admin. unit

resources used by fire for admin. unit

Fire occurrence by

region, forest and

date range

(see Appendix Q for output format Table Q-3)

NCAR: National Center for Atmospheric Research

MIT: Mass. Institute of Technology Weather site

UMICH: Univ. of Michigan Weather Underground

SNOTEL: SNOpack TELmetry

‘72 format

missing data ‘98 format

station year count

by state

by single station

utilities

Fire and Aviation

Management (F&AM)

Web applications

KCFast:

Historical RAWS

Weather and fire occurrence

Appendix D-Kansas City Fire Access (KCFast)

KCFast is a web based long term RAWS data archive for weather,

fire occurrence, fire numbers, and fire reports. The application also

provides various products such as the situation reports and internet

links to graphics and software. Weather data for the entire period

of record can be retrieved in two different formats: The 1972 (only

the 13:00 hour observations) or the 1998 (all hourly observations

if they are archived). All details are given below in the flow chart;

for acronyms see the glossary.
USDA Forest Service RMRS-GTR-119. 2003. 83

Appendix E. Fire Danger Pocket Cards for 

Firefighters

The Fire Danger Pocket Card is a way to communicate information about fire danger to 

firefighters. (See example below.) The goal is to provide a greater awareness of fire danger 

and subsequently increased firefighter safety. The Pocket Card gives a description of seasonal 

changes in fire danger potential in a local area, which makes it useful to both local and out-ofarea firefighters. It can be generated via NIFMID or FF+

.

The Pocket Card has an important day-to-day pre-suppression use. When the morning and 

afternoon weather are read each day, the actual and predicted indices are announced. The 

firefighters can reference their card to establish their position in the range of possible values 

for danger rating. More importantly, the card provides a method for everyone involved with 

wildland and prescribed fire operations to communicate a common understanding of key index values provided by the NFDRS. Local fire management personnel can produce the cards 

using Fire Family Plus. Cards are data input choice dependent and should be developed locally 

with local fire management involvement to meet local fire management needs.

The F&AM web applications/Pocket Card site provides additional information, publications, real examples, and guidelines for creating a Pocket Card using Fire Family Plus. 

North Zone

Lassen National Park

Eagle Lake District

Fuel Model G - ERC
84 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix F. ASCADS Flow Chart

The flow chart below describes the Automated Sorting, Conversion, and Distribution 

System (ASCADS), which is the main/central distribution point from which all other databases receive RAWS data. The flow charts show the main, report, and station menu hierarchies 

(adapted from ASCADS User Guide Version 2.1, BLM, Section Data Retrieval/ASCADS).

Appendix F - Flow chart describing the Automated Sorting, Conversion and Distribution

System (ASCADS) user interface/screen options. It is the main/central

distribution point from which all other databases receive RAWS data. The

flow charts show the main, report, and station menu hierarchies (adapted

from ASCADS User Guide Version 2.1, BLM). See text for a more detailed

description.

user

login

state, station name

read mail

calibration date, state, unit, name

annual operating plan

NESSDIS ID

send mail

calibration date, state, unit, NESSDIS ID

RAWS summary (selected by region)

state, unit, NESSDIS ID

transmit time, NESSDIS ID

review mail

state, unit, calibration date

RAWS summary (selected by DAPS user ID)

master listing

state, unit, name

custom listing

change

password

target location

& range

view DAPS

error messages

view watchdog

information

user

validation

main

menu

stations reports utilities ASCADS

mail system

station

inventory

listing reports

rehab

report

FS

reports

stn admin

data

select a

station

print options/

screen

stn selected

reports

full sta description

sensor list

route

last 48 hr’s headers

last 24 hr observations

more information

serial number’s

view recent obs

data

transmit information

obs data

maintenance

data

physical data

element list

sensor list

narrative

route

converted

observations data

raw obs

data

next set

more channels

header

information
USDA Forest Service RMRS-GTR-119. 2003. 85

Appendix G. WFAS Background and Evolution

This Appendix supplements the information about WFAS that was provided in the text.

Background 

The Wildland Fire Assessment System (WFAS) was developed initially as an Internetaccessible experimental tool for fire business managers by the USDAFS Rocky Mountain 

Research Station, Fire Sciences Laboratory, Missoula MT. The current version provides a 

national view of weather and fire potential, including national fire danger and weather maps 

and satellite-derived greenness maps. As of Spring 2003 the USDAFS Washington Office of 

Fire and Aviation Management and the National Information Systems Team (NIST), Boise, ID 

support the program. The broad area component of the WFAS (see Appendix A for Internet 

address) is generating maps of selected fire weather parameters and fire danger indices and 

components of the NFDRS (see Appendix B). Adjective fire danger ratings (daily and forecast) are also mapped. WFAS queries WIMS each afternoon and generates maps from the daily 

13:00 weather observations and NFDRS products. Each afternoon Fire Weather Forecasters 

from the National Weather Service also view these local observations and issue trend forecasts 

for fire weather forecast zones. WIMS processes these forecasts into next-day index forecasts. 

On the maps RAWS data and NFDRS products are reported for clusters of 12 stations. 

Values between stations are estimated with an inverse distance-squared technique on a 10-km 

grid. This works fairly well in areas of relatively high station density, but has obvious shortcomings in other areas. Station location is based on the latitude/longitude cataloged by local 

station managers in WIMS. These maps are updated daily year round. They are prototype 

WFAS products and are subject to change.

Daily fire weather and next day forecast maps are based on the mid-afternoon (1 pm LST) 

observations from the RAWS network as reported to WIMS by 5 pm (MST). Mapped parameters include average wind speed, 24 hour total precipitation, air temperature, relative humidity, and dew point. (These forecast maps are generally issued only during the fire season, 

and many areas of the country will not have forecasted information. As a result, some large 

data gaps and resulting bizarre interpolations will result as compared to the day’s observed 

maps). Forecast maps of NFDRS indices and components are based on the afternoon fireweather zone trend forecasts issued by National Weather Service Fire Weather Forecasters. 

Intermediate NFDRS products such as dead and live fuel moisture are mapped. Dead fuel 

moisture products are a function of air temperature and humidity - and are critical in determining potential fire danger. Live fuel moisture or greenness maps are generated weekly and are 

based on comparisons with standard references, on the Normalized Difference Vegetation Index 

(NDVI), and on differences from historic NDVI data. 

Finally, in addition to all the above, the Keetch-Byram drought index and lower atmosphere 

stability index (LASI or Haines) maps are generated. The former is a measure of soil moisture 

content and responds to air temperature, daily and annual precipitation. The Haines index is 

used to forecast the probability of generating large wildfires often associated with low humidity and unstable atmospheric conditions above canopy in upper air.
86 USDA Forest Service RMRS-GTR-119. 2003. 

System Status and Update Information up to June 2002

June 2002: The WFAS site was redesigned to provide easier access to products. Archived 

data is accessible and organized by calendar date. Comparisons between years can be displayed. 

Animation of a sequence of images can be viewed.

 -Apr-01: Year 2001 transition in greenness maps.

21-Sep-00: Lightning ignition efficiency extended to conterminous United States. 

15-Mar-00: Map Archives Updated. 

10-May-99: NIST assumes responsibility for support and maintenance. 

29-Mar-99: Haines Index available again. 

23-Mar-99: Haines Index temporarily unavailable. 

26-Feb-99: Map Archives now include 1998 maps. 

19-Jan-99: Name of lightning ignition potential map changed to lightning ignition efficiency. 

The content is the same as before. 

23-Sep-98: Greenness Support Tools updated. 

26-Jun-98: Experimental forecast experimental fire potential map added. 

12-Jun-98: References to lightning location removed; link to the Oklahoma Mesonet 

Experiment updated; greenness map data archival extended from one week to four. 

24-Nov-97: 1 Km Resolution NFDRS Fuel Map available. 

18-Jul-97: A new look reflects the completion of converting WFAS-MAPS to the USDA, 

Forest Service’s new computing platform using ARC/INFO instead of GRASS4.1. Some of 

the features include: 

• Inclusion of Alaska Information 

m Daily fire weather maps (as reported through WIMS) 

m Morning 12Z Haines Index Maps 

m Greenness Maps 

• On-line access to Map Archives 

m Weekly Greenness Maps, 1989-1996 (Lower 48 Only) 

m Daily WFAS Maps, 1996 (Lower 48, Fire Danger, KBDI, FM1000) 

• A Experimental Products link for a new 1km Resolution Fire Potential Map. 

18-Feb-97: Greenness Departure data unavailable from EROS in Winter. 

15-Oct-96: Daily observations and forecasts (text format), sorted by state may be viewed 

09-Sep-96: Greenness DATA and Support Tools Available via FTP.
USDA Forest Service RMRS-GTR-119. 2003. 87

Appendix H. RAWS Data Access via WRCC

Figure H-1 describes the old data access hierarchy with search criteria indicated. Figure H2 describes a new web-accessible archive still under construction; stations can be chosen either 

from a list or a clickable map. Graphing options (some still under development) can then be 

chosen from the displayed list. (See also Data Retrieval section of text and Appendix O.)

Figure H1 - “Old” Data Access Hierarchy

RAWS Station Search

“old data access”

station name

RAWS station metadata

Search & display

RAWS data by criteria

More station details

NESDIS ID

get data

select data range

(1 month max) or day

state

lat/long

(No longer in service)
88 USDA Forest Service RMRS-GTR-119. 2003. 

List of RAWS stations

(linked to data/graph options

daily summary

RAWS USA Climate Archive

Figure H2 - New web-accessible RAWS USA Climate

Archive

Map of US

(clickable)

State map

Graphing options

RAWS stations mapped/located:

clickable - linked to data/graph options

monthly summary

monthly summary (with Et data

under construction)

graph of last 7 days

time series graph

wind rose and tables

(under construction)

data lister

(under construction)

station metadata

(current, 2003, WRCC RAWS data portal)
USDA Forest Service RMRS-GTR-119. 2003. 89

Appendix I. RAWS Operations and Personnel 

Responsibilities

This Appendix gives an overview of RAWS operations and hardware, sensor and data 

requirements, and personnel duties and responsibilities. It provides details of information 

summarized in the text.

The optimal operating period for all RAWS used for the NFDRS is year-round. However, the 

minimum operational period is determined by the following criteria (NWCG-NFDRS, PMS 

426-3):

1. A minimum 30-day start up and data collection period prior to the need for NFDRS indices 

is required for each seasonal weather station to properly calibrate the model. 

2. Wildland fire season as designated by the local manager, Region, or Geographic Area 

Coordination Center but generally beginning in late spring and ending in early autumn.

3. Fluctuations in fire season length can occur from one year to the next. Use of the visual 

greenness images available through the Wildland Fire Assessment System (WFAS) is recommended to assist the local or regional fire manager in determining the beginning and 

end of the fire season.

Non-owner use. The following guidelines are recommended for any use of weather station 

data for NFDRS that is not owned by the user.

1. Notify the station owner/operator that you are using this station for NFDRS or other applications.

2. When a longer operating season is required by an adjacent unit, the non-owner should assist 

in the management of that station, including contributing to any additional costs for operation or maintenance.

Sensor and Data Requirements, Data Flow

The minimum sensor complement for a RAWS requires the following: hourly measurements of precipitation (cumulative), 10-minute average wind speed, direction, and RH, instantaneous air temperature and fuel temperature. The NFDRS upgrade requires hour average 

solar radiation. The National Fire Danger Working Team has recommended that fuel moisture 

data obtained from sensors being used at the present time not be used in NFDRS calculations; 

only observed data from manual fuel sticks are to be used. In the NFDRS upgrade, solar radiation sensors will provide input to the model in order to calculate fuel temperature and moisture 

values as well as ‘state of the weather’.

Present-day fire weather observations as now required by the NWCG are sent from each 

RAWS via satellite transmitter to a GOES, then to Wallops Island/DAPS, to Domestic Satellite 

(DOMSAT), and finally to the BLM/Remote Sensing Fire Weather Support Unit (RSFWSU)/

ASCADS. From ASCADS data are distributed to the NIFMID (which includes WIMS and 

KCFast), the Western Regional Climate Center (WRCC), National Weather Service (NWS)/

Boise, and another database called BLM Wildland Fire Management Information - Support. 

Some RAWS data are sent to WIMS from the HUB. The HUB is a multi-modem PC computer 

installed next to the WIMS system in Kansas City. This computer calls telephone-telemetered 

stations on a pre-set schedule; data are automatically uploaded to WIMS. All RAWS data 

are combined with site fuel type and topographic parameters (the station catalog/meta-data) 

then processed through NFDRS algorithms to generate fire danger indices and components. 

Forecasts are also made for next day NFDRS products and dead fuel moisture, and nonNFDRS products such as: greenness, drought (KBDI), atmospheric stability (Haines index), 

and lightning ignition efficiency (see Wildland Fire Assessment System (WFAS) see Appendix 

A and G for web site address and more information about WFAS respectively).
90 USDA Forest Service RMRS-GTR-119. 2003. 

Local Dispatch Center Data Management Responsibilities 

At roughly 14:00 hr LST at local dispatch centers around the United States, the 13:00 hr 

RAWS observations for that area’s stations are processed. This involves accessing the representative stations through WIMS within the given area/weather zone(s) which in turn are 

within fire danger rating zones. The data/observation flag ‘R’ (record) is changed to an ‘O’ 

(observation) for each station, this is done to ‘alert’ the NFDRS model to use only the “O” 

(daily 13:00 hr) for calculating intermediate and final fire products. The SOW and lightning 

activity is entered for the ‘O’ data.

The NFDRS model is then automatically run and products displayed for the primary fuel 

model for each station originally specified. There may be more than one RAWS within a fire 

danger rating zone; in such cases, composite products may be calculated. Results are then 

entered into SIT – the first step in creating the national situation report. The results are also 

posted at dispatch centers.

Site Selection

Site selection criteria and considerations are given in the National Fire Danger Rating 

System Weather Station Standards (NWCG 2000). Administratively, a fire weather forecaster, 

GACC meteorologist, or other interagency fire weather personnel should be involved in the 

process, as well as the National Weather Service (NWS), because a unique NWS identification 

(ID) number must be assigned to any new or re-located station. In addition, data transmission 

via GOES requires a separate National Environmental Satellite Data Information Systems 

(NESDIS) ID number obtained through the owner’s agency NESDIS ID coordinator.

Equipment Selection

Equipment cost is not the only consideration in choosing sensors and tower frames to purchase: other criteria include life cycle costs, data transmission, maintenance and calibration, 

data storage and retrieval, the value of shared data, ease of installation and turn-around, and 

compatibility with equipment used in the RAWS network. Data needs beyond NFDRS may be 

factored into equipment selection as well as upgrading the DCP when required. A final question to be considered is: Can the data logger accept additional sensors beyond those required 

for NFDRS data needs? Part of this RAWS review and upgrade study includes a detailed list 

with specifications of most current weather sensors available in the United States. (See appendix V and CD-ROM)

Tower Specifications

Many NFDRS weather stations are located in remote and rugged locations, where they 

may be either permanent or semi-permanent. Some collect and transmit data year round, often 

under severe conditions. There are three common tower configurations used in the RAWS 

network: Rohn tower, Handar (lunar lander), and portable. All have several characteristics 

in common – ruggedness and the ability to survive in remote locations and extreme weather 

conditions. 

If a tower is to be climbed, it must conform to the Occupational Safety and Health 

Administration (OSHA) regulations; non-climable towers must have pivoting masts so that 

the operator can service all sensors mounted on the mast while operator stays close to the 

ground.

General tower specifications

1. Able to survive 125 mph winds.

2. No vertical or horizontal movement after installation.
USDA Forest Service RMRS-GTR-119. 2003. 91

3. Able to withstand snow loads typical of high mountain locations in the western USA.

4. Able to support technical personnel on the tower while servicing sensors (applies to Rohn 

configuration).

5. Provide mounting surfaces and locations to meet NFDRS sensor requirements.

The OSHA requirements are new and have necessitated the replacement of several older, 

non-standard 33-foot (10-m) towers. This change has introduced a change in wind speed 

climatology that must be addressed (see main text for discussion: p39 Effects of Changes in 

Tower Height and Sensor Placement).

Installation/Deployment

Once a site that meets all criteria has been selected it can be prepared for installation of a 

RAWS. Personnel involved should have attended a RAWS maintenance class or be assisted by 

trained personnel. 

The minimum meta-data needed for a RAWS as stored in ASCADS are: Slope, aspect, position, antenna angle and azimuth, elevation, latitude and longitude, and all serial numbers for 

sensors and data loggers. Additional information includes noting local magnetic declination 

when aligning the tower, GOES antenna, and wind vane. A hard copy of all this information 

should be kept by the station owner and updated (in ASCADS as well) when any changes are 

made.

Quality Assurance

Quality assurance/control (QA/QC) of weather data used for NFDRS calculations is the 

responsibility of the local station owner/manager, and should be monitored at all levels of data 

acquisition and storage. These responsibilities include field data acquisition, transmission, and 

data archive to NIFMID/WIMS/KCFast. The local operator is also responsible for ensuring that maintenance is performed, that all activities are documented in ASCADS, visually 

checking data on a daily basis to ensure that the information corresponds to actual conditions 

– that it makes sense. There is also an automated detection and notification system within 

ASCADS ‘watchdog’ that monitors data for gross errors and alerts local operators to out-ofrange observations and performance problems such as non-functioning sensors. This function 

of ASCADS requires that the operator, owner, or personnel in a local dispatch center access 

‘watchdog’ through ASCADS. Additionally, an Agency or Fire Weather Coordinator should 

periodically review RAWS operations at the local level.

Maintenance and Calibration

To ensure quality control and assurance of the collected weather data, regularly scheduled 

maintenance and calibration and quick response to sudden or unexpected system failures are 

required. Two maintenance contract options are currently available through the BLM: ‘depot 

maintenance’ and ‘full-ride’. The former requires that the owner/operator of a station be responsible for annual station maintenance and emergency repair. At least once a year sensors 

are removed, returned to the Boise, ID BLM Depot, and replaced with calibrated sensors. 

The full-ride contract requires that personnel from the BLM’s Remote Sensing/Fire Weather 

Support Unit (RSFWSU) respond to emergencies and perform annual station rehabilitation. 

Depot sensor calibration standards and priorities are given in NWCG: National Fire Danger 

Rating System Weather Station Standards (2000).

Not all RAWS will be NFDRS 2000 compatible, but for those that are fully documented 

maintenance/calibration will be required. The RSFWSU has proposed to introduce a third 

level of maintenance contract ‘NFDRS 2000 certification’; under this contract each RAWS 
92 USDA Forest Service RMRS-GTR-119. 2003. 

providing data to the NFDRS 200 network will be visited once per year for documented 

calibration/certification by technicians from the NIFC depot.

Positions, Responsibilities, and Training Standards

Station owner/program manager: Responsible for site selection, station placement, maintenance; ensures QA/QC of data, that the data are sent to WIMS, and that correct NFDRS 

calculations are made. Also, ensures that personnel are available to respond to weather station 

failures.

Field support technician/first responder: Responsible for performing annual maintenance 

and responding to station system failures, maintaining up-to-date documentation in ASCADS. 

Required to attend systems training (i.e. FTS and/or Handar systems).

Depot technician: Responsible for bench maintenance and calibration of station sensors and 

subsequent testing. Provide support to field personnel and first responders as needed.

Agency/regional fire weather coordinator: Responsible for agency or regional oversight and 

coordination and QA/QC; ensures that station meta-data and documentation are current in 

both ASCADS and WIMS; ensures that training is available; assists with station operations 

and long term management planning.

Depot manager: is responsible for administration of depot and full-ride contracts.

Funding and financial support

Within the FS, each Region, Forest, or Ranger District must provide the initial justification 

and funding to obtain a station (frame, sensors, DCP etc. – $12,500). Funding for continued 

operation (full ride ($2,500), NFDRS certification (proposed at $1,800), or depot contract 

($650)) is paid out of the owners overall operating budget at the Washington Office level; the 

regional or local FS owner never manages these RAWS operating funds. The BLM has taken a 

different approach: their Washington headquarters provides all funding from startup through 

continued operation.

Other land management agencies have different arrangements: The NPS provides centralized overall funding for their RAWS, but individual Parks deal with station maintenance (full 

ride, depot, or NFDRS certification contracts). The BIA has contracted directly with the BLM 

for full ride contracts for nearly all their RAWS. The FWS has a centralized funding arrangement for maintenance, but each Region has its own agreement with the BLM for maintenance. 

Individual States must work through the FS to make purchasing (stations) and maintenance 

arrangements with the BLM, and must make their own user agreement with NESDIS for data 

transmission. Some States have gone directly to private vendors to purchase and maintain a 

RAWS, bypassing the BLM depot altogether.

Operating costs for information and data processing and management are handled at a very 

informal level thereby avoiding inherent administrative costs. At the current time the FS does 

not pay the BLM directly for the use of ASCADS, nor does the BLM pay the FS for the use of 

WIMS; an informal ‘trade’ arrangement is in place. Also, part of the ASCADS operating budget comes out of the various depot contracts of each RAWS not part of the BLM network.
USDA Forest Service RMRS-GTR-119. 2003. 93

Appendix J. Sample of the Fort Collins, CO, 

RAWS Operating Plan

NORTHERN FRONT RANGE INTERAGENCY 

WILDLAND FIRE COOPERATORS

WEATHER STATION MAINTENANCE 

OPERATING PLAN

Last Revision: May 2003

WEATHER STATION NETWORK WEBSITE:

http://www.fs.fed.us/arnf/fire/gallery_wx.html
94 USDA Forest Service RMRS-GTR-119. 2003. 

PREPARED BY: Mark S. Nelson

PROJECT MANAGER

Table of Contents

I. Purpose Statement

II. Weather Station Network Overview

III. NFDRS Calculations/Distribution

IV. Maintenance Agreement/Funding/Ownership

V. Maintenance Procedures

VI. List of Station Maintenance Technicians

VII. To-Do Items/Future planning
USDA Forest Service RMRS-GTR-119. 2003. 95

I. The purpose of this document is to outline procedures, identify responsible personnel and 

track fiscal responsibility for the installation, maintenance, and planning of the remote access 

fire weather stations used by the cooperating agencies of the northern front range of Colorado. 

The project manager is Mark Nelson (970) 498-1040.

II. The Northern Front Range Interagency Wildland Fire Cooperators (NFRWFC) maintain and use a network of Remote Access Weather Stations to provide National Fire Danger 

Ratings (NFDRS) and general weather and seasonal trend information. These stations are all 

electronic in nature and require various levels of Satellite, Solar power, Cell Phone and Data 

logger technology. Proper maintenance and care of the stations is critical for proper use and 

interpretation of National Fire Danger Ratings, Preparedness planning, fire planning, smoke 

management and Public and firefighter safety and numerous fire management activities. The 

network currently consists of seven remote access weather stations. Five are Handar Satellite 

telemetry units and the other two are Forest Technologies Systems incorporating telephone 

modems. The Handar stations are located at Redfeather Lakes, RMNP headquarters building in Estes Park, near Sugar Loaf fire station in Boulder County, Gilpin County near the 

Pickle Gulch Picnic Area, and Corral Creek at the Mount Evans Outdoor Lab. The FTS units 

are located in Redstone canyon behind Horsetooth Reservoir, and the Keewaneeche Visitor 

center at the west entrance of Rocky Mountain National Park. The stations at Kewaneeche is 

scheduled to be replaced by Handar 555 GPS, Radio Alert systems in 2003. Redfeather, Estes 

Park, Boulder, and Clear Creek stations were upgraded to 555 DCP’s with GPS, and radio alert 

systemsin 2000/01. The Corral Creek station was installed in the spring of 2001.

III. All agencies have agreed that baseline NFDRS fire danger ratings and FireFamily Plus 

Seasonal Severity charts, and Pocket Cards will be generated by the Fort Collins Interagency 

Dispatch office and distributed by electronic means including e-mail, Fax machines, and the 

FTC website.

(http://www.fs.fed.us/arnf/fire/fire.html See Fire Danger Section). The Dispatch Center will 

maintain all software programs, WIMS access, and current knowledge of the NFDRS applications and weather station maintenance agreements. Center staff will have training in WIMS 

(Weather Information Management System). The project manger will have responsibility for 

WIMS station catalog maintenance, NFDRS (National Fire Danger Rating System), Fire 

Family Plus software, Fire Weather Plus software, FIRES, and NetTerm/ASCADS applications.

IV. All of the Remote access weather stations will be covered under the National Raws 

Maintenance agreement. The Arapaho-Roosevelt National Forests will maintain this agreement through the Regional offfice. As decided by the Northern Front Range Wildland Fire 

Cooperators Board of Directors, funding for these agreements will be provided by cooperating agencies. The current year agreements will be for the following:

Redfeather: Arapaho-Roosevelt will finance $650.00 Station Owner: ARF

Larimer: Poudre Fire Authority will finance $650.00 Station Owner: PFA

Estes Park: Rocky Mountain National Park will finance $650.00 Station Owner: ARF

Boulder: Arapaho-Roosevelt will finance $650.00 Station Owner: ARF

Gilpin: Arapaho-Roosevelt will finance $650.00 Station Owner: ARF

Clear Creek:Arapaho-Roosevelt will finance $650.00 Station Owner: ARF

Sulphur: Arapaho-Roosevelt will finance $650.00 Station Owner: ARF
96 USDA Forest Service RMRS-GTR-119. 2003. 

These funds will be collected as part of the annual funding agreement(s) for support of the 

Fort Collins Interagency Dispatch Center. The Project Manager will consolidate and coordinate the National Maintenance agreement. Maintenance agreement costs will be reviewed 

annually and adjustments to annual funding agreements will be reviewed by the NFRWFC 

Board of Directors.

V. The following is a generic outline of annual maintenance procedures:

1. The project manager will ensure that all stations are covered by the national contract each 

fiscal year.

2. The project manager will review, update and present this Operating Plan to the NFRWFC 

Board of Directors in the spring of each year.

3. The project manager will order replacement sensors for each of the stations. These sensors 

will be shipped to the responsible Maintenance technician listed in this Operating Plan. 

4. The identified technician will change the sensors at the station. Inspect station for damage, 

identify needed repairs and check operation.

5. Complete the RAWS station maintenance documentation and send it to the Project manager.

6. Return the used Sensors within two weeks of receiving sensors. 

7. Coordinate with the project manager on any additional needs, training, problems.

8. Any station programming changes will be coordinated by the Project manager. 

VI. Station Maintenance Technicians

Project Manager: Mark Nelson

Redfeather Handar Arapaho-Roosevelt Mark Nelson 498-1040

Larimer FTS Poudre Fire Authority Phil Kessler 282-1301

Estes Park Handar Rocky Mountain Doug Watry 586-1237

 National Park

Boulder Handar Arapaho-Roosevelt Mark Nelson 498-1040

Gilpin Handar Arapaho-Roosevelt Mark Nelson 498-1040

Clear Creek Handar Arapaho-Roosevelt Mark Nelson 498-1040

Sulphur FTS/Handar Arapaho-Roosevelt Doug Watry 568-1237

Gunsight Handar BLM Craig Dsp

VII. Short- and long-term issues to address with the current Remote access weather station 

network.

SHORT TERM ISSUES/PLANS:

Replace weather stations with the new generation of Handar RAWS station (GPS, Satellite, 

and Voice Alert Capabilities) at Sulphur and Larimer. All stations will need to meet national 

standards by 2005. These new stations will allow hourly transmission of weather data, meet 

future station requirements and allow for voice alert capabilities over a radio system when 

pre-determined variables are reached at the station site. Example: station will transmit alert 

when wind speed exceeds 12 mph and relative humidities are below 15%. The follow outlines 

short- and long-term implemetaion and maintenance goals.

1. Order and replace sensors for all weather stations under National contract in April/May.

2. Update seasonal FireFamily + (ERC/BI/1000-Hours) charts and Firefighter Pocket Cards 

and post on website as needed.

3. Review Fire Restriction and Closure Criteria annually.

4. Document all weather station changes in ASCADS.
USDA Forest Service RMRS-GTR-119. 2003. 97

LONG TERM GOALS AND PLANS:

1. Review of existing equipment and technology and evaluation on a yearly basis. Conversion 

of FTS stations to new satellite technology, standardization of station type should be evaluated and addressed for short- to long-term planning applications. Prepare for implementation of expected national weather station standards.

2. Software development and changes in fire weather data processing (Fire Wx Plus, WIMS, 

Firefamily +, NFDRS, FIRES, ASCADS, Handar Programming Software, etc... need to be 

maintained. 

3. Development of RAWS maintenance capabilities, particularly of the Handar station(s), 

needs to be established and maintained. 

4. Training for field personnel needs to be formalized to address understanding and implementation related to NFDRS, preparedness planning, pre-dispatch plans, Fire Restriction/

Closure Criteria, fire behavior, safety, etc...
98 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix K. Sample Position Description of 

RAWS-Related Duties at the Operational 

Level

Major Duties

Directs collection of weather data at stations on the forest. Maintains Forest RAWS 

(Remote Automatic Weather Stations) network, including field maintenance and programming. Trains others in station maintenance and repair. Receives and interprets weather forecasts; determines daily staffing plans for forest and districts. Provides daily fire weather data, 

and burning indices to ranger districts, cooperators and industry.

Factor 1, Knowledge Required by the Position

Working knowledge of RAWS including the ability to plan for the maintenance and repair 

to the assigned network of stations and train other technicians as necessary.

Factor 2, Physical Demands

The work sometimes requires above normal physical exertion when making site visits to the 

RAWS stations for set-up and maintenance, or functioning as the site manager. This includes 

some lifting of heavy objects.

Position Description as related to fire weather stations and 

fire weather program2

1. To manage the fire weather data collection network to ensure that accurate weather data is 

collected and processed.

2. Monitor the collect fire weather data from automated fire weather stations.

3. Monitor and approve calculated Fire Danger Indices.

4. Ensure the (organization’s)= automated weather station sensors are properly maintained.

5. Provide quality control of fire weather observations generated from the weather stations i.e. 

checking for erroneous readings.

6. Properly maintain the (organization’s)= weather station catalog information (green up, 

freeze dates, fuel models etc) in the national Weather Information Management System 

(WIMS).

7. Provide quality control for the fire danger maps produced daily for the Wildfire Information 

Center internet web site.

8. Monitor National Fire Danger Rating System (NFDRS) indices and Canadian Fire Danger 

Indices.

9. Investigate any indices that appear to be erroneous.

10. Alert supervisor/MIFC Coordinator when indices indicate potential problem.

11. Monitor long-term drought indicators and climatology and graph trends. 

2

 D. Miedtke, MN Interagency Fire Center, 2002
USDA Forest Service RMRS-GTR-119. 2003. 99

Appendix L. Sample of Daily SOP from NF 

Dispatch Center

FTC Daily Routine

**NOTE** MOST of the websites listed below can also be accessed from our Fort 

Collins Interagency Dispatch Center home page http://www.fs.fed.us/arnf/fire/fire.html

by going down through the various sites. You can do it either through that page or by 

checking for these sites in the Favorites. Use the direct address listed if the WO server 

goes down.

08:00 -Take phone off forward, retrieve any voice mail messages

 -Broadcast: Fort Collins Dispatch Center is in service at 08:00, KAC-249 using 

 select group on radio select the following repeaters: Roosevelt: DIR, 

 Arap-CCRD: SQW, Arap-SRD: SCW.

 -Check DMS mail profiles (COFTC/COFTCMOB) and read/forward/print as 

 necessary.

To take phone off forward:

Pick up phone using line 1348; get a dial tone. Press forward. Light next to 1348 will stop 

blinking.

To retrieve messages:

Dial 2650 on FS phone. Wait for message and hit #. Dial 1348. Enter password XXXX listen to instructions and hit 5 to play messages. After messages have played completely hit 9. At 

prompt, hit 9 again and this will delete messages and close you out of the system.

To broadcast on Simulcast:

Go to the SELECT GROUPS button and click on it, at the bottom of the screen there will 

appear a row of buttons. Select DAILY BRDCST 1 and reset the repeaters to Roosevelt: DIR, 

Arap-CCRD: SQW, Arap-SRD: SCW.

To check DMS mail profiles:

Double-click on DMS icon. Click on the DMS profile (and inbox) you want to look at 

(COFTC or COFTCMOB). When it asks for a password for each profile, it is the same as the 

user (type in coftc or coftcmob). Read inbox items and determine who needs to see them...

your options: you deal with the item immediately, you print the item and distribute it, or you 

forward it to whomever needs to see it. Once the item is dealt with, delete it. If you do not 

know who should get it, don’t be afraid to ask

09:00 -Confirm tactical and administrative aircraft and pilots availability/status with 

 Tom Landon (xxx-xxx-xxxx), his designee, or Airtanker Base Manager.

 -Status SEAT (T182) with Fred Winkler (xxx-xxxx) if it is positioned in FTC area.

 -Update any resource (aircraft, overhead, crew, equipment) availability changes 

 in ROSS.

To confirm aircraft and pilots:

MOST OF THE TIME TOM LANDON AND FRED WINKLER WILL CALL IN THE 

MORNING AND STATUS THE AIRCRAFT, IF THEY ARE UNAVAILABLE: IF Tom 

Landon is NOT shown to be committed to an incident, call Tom at his cell phone (xxx-xxxxxxx). If Tom is shown as committed or unavailable, try Ivan Pupulidy (xxx-xxx-xxxx or 
100 USDA Forest Service RMRS-GTR-119. 2003. 

xxx-xxx-xxxx) or Mark Michelsen (Jeffco Airtanker Base Mgr., xxx-xxx-xxxx). Ask what the 

status is of each aircraft and each pilot (ask for location, status, which plane they will fly, and 

ask if there is anything odd or in the works we should know about). Write this information 

on aviation white board. Usually, Fred Winkler will contact us by phone to tell us the SEAT’s 

availability. Call helicopter manager for area helicopters.

09:15 -Confirm Pre-Dispatch cards are set at appropriate levels for yesterday’s declared

 action class.

 -Determine Preparedness Level.

 -Retrieve, print, and post the National Situation Report, R-2 Sit. Report, and 

 National Weather Service morning fire weather forecasts from the web sites.

 -Retrieve, print, and post the 24-hour lightning map (Do NOT distribute).

To determine preparedness level:

Read preparedness level cards on sliding map board. Determine likely level and confirm 

with Mark Nelson or Mike Foley then ensure that the pre-dispatch cards are set to the corresponding preparedness level.

To get Sit. Report and fire weather forecasts:

Use the links from the FTC home page to get to the National Weather Service-fire weather 

forecasts area and print the forecasts for zones 212, 218, 215, and 216. Many times the forecasts for zones 212 and 218 are combined, as are the forecasts for zones 215 and 216. You can 

tell by looking at the header just before the long geographical descriptions of the zones. The 

sit reports are the first links under the Fire Intelligence header. Print and post all of these items 

to the clipboards in the hall.

To get to the lightning report, follow the link and enter Username: COFTC, Password: 

XXXXXX. THIS CHANGES MONTHLY. Print this on the color printer.

National Sit. Report: http://www.nifc.gov/news/sitreprt.pdf

Weather: http://www.crh.noaa.gov/den/fir2znft.html

RMACC Detailed Sit. Report: http://www.fs.fed.us/r2/fire/rmasit.htm

24-Hour Lightning Map: http://www.nifc.blm.gov/cgi/nsdu/Lightning.cgi/Page/ViewSelec

t?Submit=Continue

09:30 -If the preparedness level is 1 or 2 ensure participation in a weekly conference call

 on Monday. If the preparedness level is higher than 2 the conference call 

 becomes daily.

 -Adjust resource staffing/location on IA map based on the above information.

To adjust map:

Place magnets on Initial Attack map (on the sliding board) corresponding to engines, crews, 

etc. and their current locations.

10:00 -Broadcast abbreviated versions of weather reports on simulcast.

 -Broadcast and post regional aviation resource status on High fire danger or above 

 days.

You will have to broadcast the weather on Simulcast as done at 0800. First let folks know 

it’s coming by broadcasting All stations, stand by for today’s fire information report and 

forecast and then releasing the transmit button and waiting a few seconds. Broadcast just the 

weather discussion and the today part of the forecast. We do not broadcast 10K free winds. Try 

to listen to someone do this before you attempt it alone.
USDA Forest Service RMRS-GTR-119. 2003. 101

BETWEEN 11:00 – 13:00 Take a lunch break---I MEAN IT!!! You never know when the day 

will get so busy that you will not have a chance to stop for a breather, let alone a snack!

14:00 -Determine observed weather at WIMS stations from the web, phone calls, etc.

To determine observed weather at WIMS stations:

FROM NORTH TO SOUTH:

50505 – Red Feather (up by Red Feather Lakes)

50508 – Larimer (above Lory State Park/Horsetooth Reservoir) (13:00)

50507 – Estes Park/Utility (right by Estes Park)

50402 – Sulphur/Kawuneeche (west of Grand Lake, north of Granby) (13:00)

50604 – Boulder (just west of Boulder)

51901 – Pickle Gulch (just west of Golden Gate Canyon State Park)

51804 – Corral Creek (just east of the north end of Mt. Evans Wilderness)

You want to get the weather over the sites within 5 minutes of 2 PM. Report thunderstorms 

if they are obviously building and will happen soon, but not if they may happen sometime this 

evening or did happen and were done an hour ago.

-Compare weather to codes and determine appropriate code, using the attached codes to 

determine sky conditions.

14:15 -Enter weather observations into WIMS from all stations by 14:30 at the latest 

 (EOBS).

-Retrieve weather observations, FTC weighted average, and actual fire danger 

 rating (DOBS, DAVG, DIDX). Process and upload to the web site.

To enter and retrieve weather:

-Go to the WIMS page, which is linked off of the FTC home page under the header FTC 

 Mobilizations Guides/Operating Plan then under CHAPTER 20: Administrative 

 Procedures

-Click on the WIMS button.

-Enter the username and password. This changes, so ask one of the permanent party. As of 

 5JUNE03 it is: Username, XXXXXX, Password, XXXXXX.

-At the top of the page is a quick path option window. Type EOBS into this window.

-In next screen: Station ID should be blank, SIG should contain ftc2, Type should read R, the 

date should be today’s, and the time should read 12

-Click the find button

-A list of weather stations should appear. If they do not, then it is possible you are trying to 

early. Wait and try again later.

-Use the mouse to change the R value in the OT column to O. This changes the data from raw 

data to an observation.

-In the W column, correlate the sky conditions that you collected at 1400 with the numbers of 

the weather stations and enter the approriate value.

-Click in the Save box.

-Once the data has been saved, it should appear in green. If it appears in a red box an error 

message will inform you why.

-Close the pop-up window and reset ftc2 to read ftc3, and the time to 13.

-Repeat all of the data entry and saving functions already performed, on these two stations.

-In the Fast Path window, enter DOBS (display observations)
102 USDA Forest Service RMRS-GTR-119. 2003. 

-Leave Station ID blank, in SIG enter ftc, change Type to O, ensure the Date is correct, and 

leave the time blank.

-Click Find

-Click in the Print box

-A new window will open, go to the File menu then the Save As item and overwrite the file 

that appears. This is yesterday’s data.

-In the Fast Path window, enter DAVG (daily average)

-SIG should read ftc, Type should be O, the date should be correct, and the Time should be 

blank.

-Click the Find box.

-Click in the Print box

-A new window will open, go to the File menu then the Save As item and overwrite the file 

that appears. This is yesterday’s data.

-In the Fast Path window, enter DIDX (display indices)

-Leave Station ID blank, SIG should be ftc, Type should be O, the Date should be correct, and 

the Time block should be blank.

-Click the Find box.

-Click in the Print box.

-A new window will open, go to the File menu then the Save As item and overwrite the file 

that appears. This is yesterday’s data.

-Now, YOU ARE DONE IN WIMS, and you can exit the page.

-Minimize your applications until you can see the desktop and click on the Upload DOBS, 

DAVG, DIDX icon. This will run a routine that posts the data to the web site. When the program pauses and asks you to press any botton, ensure that the window is active beforehand 

by clicking in it with the mouse.

-Check the web page under Fire Danger/Severity and Northern Front Range Fire Danger 

Ratings to ensure the right data is posted and it is current. This ensures you did the WIMS 

entry correctly.

IF you miss a day or two, you WILL have to enter observation data anyway...just make sure 

you do it in CHRONOLOGICAL order OR that Mark does a recalculation of the station data

15:30 -Print and post afternoon weather forecast.

-Access WIMS and retrieve forecasted fire danger ratings (DMGR).

-Update and post the Fire Management Forecast form.

To print/post afternoon weather:

Go to the same site as morning weather, http://www.crh.noaa.gov/den/fir2znft.html, and 

repeat the process.

To access WIMS and retrieve forecasted fire danger ratings:

-Enter WIMS program as at 2:15.

-In the Fast Path area enter DMGR (data manager)

-Leave Station ID blank, set SIG to ftc, set Type to F for forecasted, and enter the date in format DD-MMM-YY (05-JUN-03). Be sure and enter the FOLLOWING DAY’S DATE.

-Click the Find box.

-Click in the Print box.
USDA Forest Service RMRS-GTR-119. 2003. 103

-A new window will open, go to the File menu then the Save As item and overwrite the file 

that appears. This is yesterday’s data.

-Close the WIMS window, and upload the data to the web site using the Upload DMGR icon. 

Check the web site to ensure that it has been updated.

To record and post the NFDRS (Fire Management Forecast):

Retrieve the clipboard that contains the Fire Management Forecast form, this is in the 

hallway in one of the bins. the top portion is filled out using the FTC Average data from the 

web page. The Haines Index is on the national weather service forecast. The bottom portion 

is filled out using Today’s Actuals from the web page for the first data set. BE SURE TO USE 

THE TOP LINE FOR EACH STATION (the G fuel model). Use Tomorrow’s forecast to fill 

in the data for the bottom data set.

THFM=1000 hour fuels

EC=Energy Release Component

SL=Action Class

R=Fire Danger Rating

16:00 -Broadcast the Fire Management Forecast and the afternoon fire weather forecast on 

simulcast.

To broadcast the afternoon weather and Fire Management Forecast:

Read only the today portion of the fire weather forecast. Read the Afternoon Fire 

Management Forecast by breaking it up into time efficient chunks with breaks in the flow. 

Read each station completely, todays values and forecast values, before proceeding to the 

following station. Finish by saying This concludes the fire management forecast at _______

__(time), KAC-249.

17:30 -Call CRC, PBC, RMMC and determine need for Tanker/Base coverage. Close out 

 with Tanker Base/pilots.

To determine need for Tanker and Tanker Base coverage:

Call Craig (xxx-xxx-xxxx), Pueblo (xxx-xxx-xxxx), and RMACC (xxx-xxx-xxxx) dispatch 

centers. Ask if they’ll need Airtanker or Tanker Base coverage past 1800. Check with Pueblo 

if they could use SEAT past 1800. Call tanker base to let them know what time they should be 

done based on your calls to the dispatch centers.

17:45 -Prepare and process the daily Fire Situation Report.

 -Update, print, and post to the website the FTC Status Report.

To prepare and send Situation Report:

-Go to internet explorer to http://famweb.nwcg.gov/. THIS IS THE SAME PAGE YOU USED 

TO ACCESS WIMS, AND SHOULD BE BOOKMARKED.

-Click on the Sit Report button.

-Use the same password as WIMS to access the site. 

-Use the tabs at the top of the screen and input the data required. At the end of each screen 

click on the Submit Data button. On the last screen, click on submit. When you are done, simply exit the window and the data will be saved.

To prepare and post the FTC Status Report:

-Open Microsoft Frontpage from the Start Menu

-Once the program is open, go to File and Open

-Open K:/eco/ftc web page/Morning_Report
104 USDA Forest Service RMRS-GTR-119. 2003. 

-Edit the report and save it using the save command.

-Close Frontpage

-On the desktop, click on the Upload FTCSIT icon.

-Check the web page to ensure the FTC Status Report has posted.

18:00 -Broadcast: Fort Collins Dispatch is out of service at 18:00, KAC-249 on 

 simulcast.

 -Place the phone on forward to the on-call dispatcher’s voicemail or pager.

To broadcast out-of-service:

Just like all the other group broadcasts.

To forward phone:

Pick up phone using line 1348; get a dial tone. Press forward. Dial in WHOLE pager number or WHOLE extension number (so for Mark’s pager, dial 9-490-5291 or for his extension, 

9-498-1040). Hang up the phone. Light next to 1348 should be blinking.

Confirm that all duties, obligations, AIRCRAFT, and resource orders are complete & 

close out with all initial attack resources.

MONDAY: -Conduct Weekly PL 1,2,3 (Daily at PL 4 & 5) Conference call. xxx-xxx-xxxx

 Pass code: xxxx# Conference Leader: Mark Nelson

 -Distribute weekly availability request to COFTC-REDCARD mailing list

SUNDAY: -Print and post appropriate documents for hallway display. Seasonal Trend 

 Chart updates.

AS NEEDED: RX Burn Reports
USDA Forest Service RMRS-GTR-119. 2003. 105

Appendix M. Regional RAWS Coordinator 

Responsibilities and Duty Guidelines1

The duties of Regional RAWS Coordinators vary throughout the different regions of the 

Forest Service. However, several responsibilities are common to all Regional positions. The 

level of involvement in the program varies based on the Regional needs and management direction. However, at a minimum, the individuals are expected to:

1. Assure that the Automated Sorting, Conversion and Distribution System (ASCADS) database is complete and current. This includes:

• Requests for NESDIS ID’s and transmit times are received from the field and forwarded 

to the National RAWS Coordinator. These include: new RAWS stations, moved stations, 

and upgrades from 3 hrly to 1 hrly and to high data rate. 

• Monitor network to make sure that the assigned transmit times meet the needs of the users. Coordinate with National RAWS Coordinator to obtain better times as necessary.

• Manage the portable RAWS platforms used for project work to ensure maximum utilization.

• Verify in their Region, that there is a platform data file (PDF) in ASCADS for each automatic weather station that the Forest Service owns (regardless of telemetry method).

• Notify the National RAWS Coordinator when new stations are purchased, or old stations 

are taken down or moved.

• Assure that maintenance information is tracked in the narrative portion of ASCADS for 

each station.

2. Through the ASCADS database, annually prepare a Regional Annual Operating Plan 

(AOP) for their automatic weather station network and verify the accuracy via email to the 

National RAWS Coordinator. This needs to be done by the reply due date established in 

annual letter requesting the AOP (usually August of each year). This information includes 

maintenance support needs requested through the BLM.

3. Facilitate information sharing throughout their Region on new technology, changes in procedures, overall network design and operation. 

• Represent Region at weather and RAWS meetings (FS and interagency)

• Review and recommend additions, removal and placement of RAWS on NFS lands.

• Call upon the National RAWS Coordinator, manufacturer’s representatives, and/or the 

BLM REMS Depot for latest technology information.

• Support the corporate data concept regarding weather data collected by providing guidance to local units on short and long term weather data storage.

4. Recognize maintenance deficiencies and take steps to correct problems. Those steps can 

include, but are not limited to: 

• Assure that RAWS Watchdog is monitored by local units.

• Monitor RAWS Watchdog and notify forests when problems have not been responded to 

in a timely manner.

• Monitor the quality of data coming out of the RAWS network thru WIMS. (Sometimes this is 

an indicator of sensor problems that are not picked up with the technical watchdog report.)

• Schedule maintenance training at a Regional level. Assistance in this effort is usually 

available from the National RAWS Program.

• Work one-on-one with the local units to train and assure proper maintenance methods 

are understood and followed.

• Share training opportunity information that becomes available. This information will 

normally come from the National RAWS Program.

• Contact the National RAWS Coordinator, manufacturer’s representatives, or the BLM 

REMS Depot for support as necessary.

1 (Kolleen Shelley, 1/22/1999). Some of these points could certainly be used in a position description. Referenced from Draft: 

Operations and Protocols/Positions and Responsibilities item 4.
106 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix N. Forest Service Region 9 RAWS 

Operating Plan for FY031

REMOTE WEATHER ANNUAL OPERATI NG PLAN

 USFS REGION 09

 Repor t D at e: 07/31/02 15:32 GMT

 Uni t: ALLEGHENY NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

~~~~~~~~ ALLEGHENY TEL-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for A LL EGHENY N F : $ 675 .00

 Unit: CHEQUAMEGON -NICOLET

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

3284818C LAONA SATELLI TE FTS DEPOT 675 .00

~~~~~~~~ GLIDDEN - FTS TEL-DAT A FTS DEPOT 675 .00

~~~~~~~~ WASHBURN - FTS TEL-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for C HE QUAMEGON-N ICOLET : $ 2025.00

 Unit: CHIPPEWA NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

~~~~~~~~ CASS LAKE TEL-DAT A FTS DEPOT 675 .00

~~~~~~~~ CUTFOOT - FTS TEL-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for C HI PPEWA NF : $ 1350.00

 Unit: GRN MTN & FINGER LKS

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

32760078 SWEEZY SATELLI TE FTS DEPOT 675 .00

~~~~~~~~ ELMORE TEL-DAT A FTS DEPOT 675 .00

~~~~~~~~ ESSEX JUNCT ION TEL-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for G RN MTN & F IN GER LKS : $ 2025.00

 Unit: HIAWATHA & OTTAW A N F

 1 This excerpt is repr oduc ed here w ith the permission of S. Marien, Eastern Region (9) GACC

Meteor ologist.
USDA Forest Service RMRS-GTR-119. 2003. 107

 Unit: HIAWATHA & OTTAW A N F

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

328355D0 BLUE LAKE SATELLI TE FTS DEPOT 675 .00

3283604A ELKHORN SATELLI TE FTS DEPOT 675 .00

3283733C RACO SA TELLI TE FTS DEPOT 675 .00

328346A6 WATERSMEET SATELLI TE FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for H IA WATHA & OTTAWA NF : $ 2700.00

REMOTE WEATHER ANNUAL OPERATI NG PLAN

 USFS REGION 09

 Repor t D at e: 07/31/02 15:32 GMT

 Unit: HOOSIER N F

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

3284D1F0 HARDIN RIDGE SAT,TEL FTS DEPOT 675 .00

328530F8 TIPSAW LAKE SAT,TEL FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for H OO SIER NF : $ 1350.00

 Unit: HURON-MANIS TEE NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

32851614 BALDWIN SAT,TEL FTS DEPOT 675 .00

3285238E MIO SA T,TEL FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for H UR ON-MANISTE E N F : $ 1350.00

 Uni t: MARK TWAIN NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

32720542 AVA SA TELLI TE FTS DEPOT 675 .00

3233E796 CARR CREEK SATELLI TE FTS DEPOT 675 .00

3271F2C8 DONIPHAN SATELLI TE FTS DEPOT 675 .00

3271E1BE SINKIN SATELLI TE FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for M AR K T WA IN NF : $ 2700.00

 Unit: MIDEWIN T AL L G RA SS

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

326F42B0 MIDEWIN T AL L G RA SS PRARI E SATELLI TE FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for M ID EWIN TALL GRASS : $ 675 .00
108 USDA Forest Service RMRS-GTR-119. 2003. 

 Unit: MONONGAHELA NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

~~~~~~~~ DAVIS (BEAR DEN) - FTS TE L-DAT A FTS DEPOT 675 .00

~~~~~~~~ MARLINTON - FTS TEL-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for M ON ONGAHELA NF : $ 1350.00

 Unit: SHAWNEE N F

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

3282B4D8 DIXON SPRIN GS SAT,TEL FTS DEPOT 675 .00

3282D13E BEAN RIDGE SATELLI TE FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for S HA WNEE NF : $ 1350.00

 Unit: SUPERIOR NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

32728356 SUPERIOR #1 RAD-VOI CE FTS DEPOT 675 .00

327273D2 SUPERIOR #2 RAD-VOI CE FTS DEPOT 675 .00

~~~~~~~~ SUPERIOR #3 RAD-VOI CE HANDAR D EPOT 675 .00

~~~~~~~~ SUPERIOR #4 RAD-VOI CE HANDAR N ONE $.00

327F5658 FERNBERG SATELLI TE OTHER NONE $.00

~~~~~~~~ ELY - FTS TEL-DAT A FTS DEPOT 675 .00

~~~~~~~~ ISABELLA - FTS TEL-DAT A FTS DEPOT 675 .00

~~~~~~~~ MEANDER F TS TEL-DAT A FTS DEPOT 675 .00

~~~~~~~~ SEAGULL - FTS TEL-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for S UP ERIOR NF : $ 4725.00

 Unit: WAYNE NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

~~~~~~~~ DEAN TE L-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for W AY NE NF : $ 6 75 .00

 Unit: WHITE MOUNT AIN NF

NESS ID N ame TX Method DCP Maint . Cha rge

----------- ---------- -------- ---------- ---------- ---------- ---------- --------

32352246 GREAT GULF SATELLI TE HANDAR D EPOT 675 .00

~~~~~~~~ LANCASTER TEL-DAT A FTS DEPOT 675 .00

~~~~~~~~ WHITE MTN NF TEL-DAT A FTS DEPOT 675 .00

 ------- ---

 Total M ai ntenance Charge for W HI TE MOUNTAI N N F : $ 2025.00
USDA Forest Service RMRS-GTR-119. 2003. 109

 Remote Weather Annual Operati ng Plan

 FY 2003

 Reg ion 09

 July 31, 2002

 -- S TA TIONS --

 Total HANDA R Stations: 3

 Total FTS Stations: + 35

 Total CAMPB ELL Stations: + 1

 --- ---------- --

 Total Stati ons: 39

 -- M AI NTENANCE --

 Stations on Full Mainten ance: 0

 HANDAR Station s o n Depot Maintenan ce: 2

 FTS Station s on D ep ot Mainten ance: 35

 Stations on Data Only Mainten ance: 0

 Stations on Warrant y M ai ntenance: 0

 Full Maintenan ce Charge: $ 0.0 0

 Depot Maint enance Charge (HANDAR): + $ 1350.00

 Depot Maint enance Charge (FTS): + $ 23 625.0 0

 Data Only Maintenan ce Charge: + $ 0.0 0

 Warranty Maint enance C ha rge: + $ 0.0 0

 --- ---------- --

 Total Maint enance Charge: $ 24975.0 0

 -- R EG ION SUMMARY - -

 Total Stati ons Cataloged : 39

 TOTAL NETWO RK FUNDI NG REQUIRE D: $ 24975.0 0
110 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix O. Data Retrieval

This Appendix provides more detail on the information summarized in the Data Retrieval 

section of the report. The following RAWS databases are major sources for recent and archived data as of spring 2003, but may change if Internet addresses change or if new sites are 

generated.

Western Regional Climate Center (WRCC)

There are two ways to retrieve RAWS data from the WRCC via the Internet or direct arrangements with WRCC. A new WRCC project/web site (http://www.wrcc.dri.edu/wraws/

RAWS USA Climate Archive) released in spring 2003, allows the user to select a RAWS from 

either a list or a clickable map. The user can then select from a list of different graphing options to retrieve data summaries, time series graphs, monthly or weekly summaries, and so 

forth. Data flow, search options and criteria are diagrammed in Appendix H-Z.

A third alternative is to contact the WRCC directly and request data files; for data from 

multiple sites and/or extended date ranges this is clearly the best method. Appendix A gives 

their web site address which in turn provides additional information such as telephone numbers, other products, etc.

National Interagency Fire Management Integrated Database 

(NIFMID)

Accessing NIFMID/KCFast allows member users to retrieve historical weather, fire occurrence, and station catalog data but does not allow changes to be made to these data and 

meta-data sets. (An excellent How-to... can be found in Appendix A of the Fire Family Plus 

Users Guide V2.0 (RMRS Fire Sciences Lab, Systems for Environmental Management, July 

2000)).

Steps include:

1. Via internet – see Appendix A for web address and Appendix C-1 and D for more detail,

2. Login as usual (requires user ID and password) and follow instructions to retrieve data set; 

KCFast will send data file to a FTP site,

3. Go to the FTP site indicated,

4. Find and select the file that was requested,

5. Go up to the FILE menu, scroll down to ‘Copy to folder’, click on browse, select a destination folder, and click on OK. The raw data file will be copied into the selected folder.

Access to WIMS is initially the same as that for KCFast, and one can use the same user ID 

and password. WIMS/WEB is a web-based interactive package that allows the user to enter 

and edit data; retrieve weather data, fire weather forecasts, and smoke management forecasts, 

display NFDRS indices and components, enter and retrieve point and trend forecasts, and 

other NWS products.

WIMS/Web came on-line in mid 2001. It is a web-based interactive application ingesting, 

archiving (meso-term – 2 years), and managing RAWS weather data stored in other modules of 

the NIFMID. These other modules include KCFast (long-term archive for 13:00 hour weather 

and fire occurrence), report generators (for the national fire situation report, incident situation 

reports, and aircraft use), and firefighter pocket cards. The WIMS is also host for the NFDRS 

model producing daily and forecasted) fire danger indices and components. WIMS, KCFast, 

and the other modules contained within NIFMID are accessible via the internet – F&AM web 

applications (http://famweb.nwcg.gov/).

WIMS and KCFast usernames and passwords can only be obtained from FS Regional level 

computer security offices.
USDA Forest Service RMRS-GTR-119. 2003. 111

Geospatial Multi-Agency Coordination Group (GeoMAC)

GeoMAC is a map-intensive website that allows all users to access the last 24 hours of 

transmitted RAWS weather data, if that particular station transmits once per hour, otherwise 

the 13:00 (LDT) observations are given. Various map (information) layers are available such 

as thermal images (of active fires), situation report of active fires, available perimeters, RAWS 

weather, major cities, major roads, lakes, streams, and so forth. Multiple layers can be called 

up at any one time but only the top layer is active at a time.

Steps are:

1. Go to the Wildland fire access page (http://geomac.usgs.gov/),

2. Click on the Wildland fire maps button under ‘Public Server’, which takes the user to the 

GeoMAC overview map,

3. On the right hand side the user can choose map layers to display; each time different layers 

are chosen the map needs to be refreshed – the refresh button is at the bottom,

4. In the lower left hand corner are application buttons: locator, zoom, pan, hyperlink, etc.

5. If RAWS weather is the active layer then sites will be indicated on the map by small blue 

squares,

6. Click on the hyperlink button, then click on a mapped RAWS site, these are hyperlinked to 

a data archive housed by the NWS in Boise, ID.

The National Weather Service (NWS)

The National Weather Service is another RAWS data archive; the Boise Fire Weather/

National Fire Page (http://www.boi.noaa.gov/firewx.htm) provides links to RAWS observations, data summaries, model output statistics, RAWS location information, current conditions, the WFAS, satellite imagery, and various fire indices.

ASCADS

ASCADS takes selected RAWS data from the DomSat Receive System (DRS) and sorts 

and re-formats it into a relational database. ASCADS then passes the converted and formatted data to the BLM Web Server, the NIFMID/WIMS, the NWS, and WRCC. ASCADS is 

a single source for all RAWS information such as maintenance history, sensor complement, 

location, route, point of contact, and observation data. It was moved onto new server hardware 

spring 2003.

ASCADS is a user-friendly, menu driven interface that gives users the ability to view and 

print reports of the most current information associated with a RAWS. Extensive information 

is associated with every station. To ease viewing of station data, associated data have been 

grouped into several screens. Data flow and screen menu choices have been diagrammed 

in Appendix F (adapted from the ASCADS Field Users Guide Version 2.1 2002). Access to 

ASCADS is via a terminal emulation package such as Secure Netterm in the FS. All passwords, user names, and edit access must be obtained from RAWS agency coordinators.
112 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix P. ASCADS Watchdog Alerts and 

Data Flags

Complete list of the ASCADS Watchdog alerts and data flags (provided by K. McGillivary 

(Applications Software Group/BLM/NIFC) and P. Sielaff (RSFWSU/BLM/NIFC 2002). 

Note that many of the parameters are not actually used.

WATCHDOG EVENT DESCRIPTION 8/19/2002

DAPS ERROR Parity Error Detected

DAPS ERROR See Incidental Info for Detail

INCONSISTENCY Fuel Temp Not Consistent With Air Temp

STATION Offline

STATION Station Description Changed

STATION Transmissions Resumed

TRANSMISSION Arrival Time is Drifting

TRANSMISSION Bad Character Count

TRANSMISSION Frequency

TRANSMISSION Missing Entire Transmission

TRANSMISSION Missing Header

TRANSMISSION Missing Observation

TRANSMISSION Modulation

TRANSMISSION Power (Signal Strength)

TRANSMISSION Wrong Character Count Received

AIR QUALITY Change Too Large

AIR QUALITY Format Error Detected

AIR QUALITY Invalid Data

AIR QUALITY Parity Error Detected

AIR QUALITY Reading Missing

AIR QUALITY Reading Too High

AIR QUALITY Reading Too Low

AIR QUALITY Reading Unchanged Too Long

AIR TEMPERATURE Change Too Large

AIR TEMPERATURE Format Error Detected

AIR TEMPERATURE Invalid Data

AIR TEMPERATURE Parity Error Detected

AIR TEMPERATURE Reading Missing

AIR TEMPERATURE Reading Too High

AIR TEMPERATURE Reading Too Low

AIR TEMPERATURE Reading Unchanged Too Long

BAROMETRIC PRESSURE Change Too Large

BAROMETRIC PRESSURE Format Error Detected

BAROMETRIC PRESSURE Invalid Data

BAROMETRIC PRESSURE Parity Error Detected

BAROMETRIC PRESSURE Reading Missing

BAROMETRIC PRESSURE Reading Too High

BAROMETRIC PRESSURE Reading Too Low

BAROMETRIC PRESSURE Reading Unchanged Too Long

BATTERY VOLTAGE Change Too Large

BATTERY VOLTAGE Format Error Detected

BATTERY VOLTAGE Invalid Data

BATTERY VOLTAGE Parity Error Detected

BATTERY VOLTAGE Reading Missing

BATTERY VOLTAGE Reading Too High

BATTERY VOLTAGE Reading Too Low

BATTERY VOLTAGE Reading Unchanged Too Long

CLOUD LAYER Change Too Large

CLOUD LAYER Format Error Detected

CLOUD LAYER Invalid Data

CLOUD LAYER Parity Error Detected

CLOUD LAYER Reading Missing

CLOUD LAYER Reading Too High
USDA Forest Service RMRS-GTR-119. 2003. 113

CLOUD LAYER Reading Too Low

CLOUD LAYER Reading Unchanged Too Long

DEW POINT Change Too Large

DEW POINT Format Error Detected

DEW POINT Invalid Data

DEW POINT Parity Error Detected

DEW POINT Reading Missing

DEW POINT Reading Too High

DEW POINT Reading Too Low

DEW POINT Reading Unchanged Too Long

FUEL MOISTURE Change Too Large

FUEL MOISTURE Format Error Detected

FUEL MOISTURE Invalid Data

FUEL MOISTURE Parity Error Detected

FUEL MOISTURE Reading Missing

FUEL MOISTURE Reading Too High

FUEL MOISTURE Reading Too Low

FUEL MOISTURE Reading Unchanged Too Long

FUEL TEMPERATURE Change Too Large

FUEL TEMPERATURE Format Error Detected

FUEL TEMPERATURE Invalid Data

FUEL TEMPERATURE Parity Error Detected

FUEL TEMPERATURE Reading Missing

FUEL TEMPERATURE Reading Too High

FUEL TEMPERATURE Reading Too Low

FUEL TEMPERATURE Reading Unchanged Too Long

GAMMA RADIATION Change Too Large

GAMMA RADIATION Format Error Detected

GAMMA RADIATION Invalid Data

GAMMA RADIATION Parity Error Detected

GAMMA RADIATION Reading Missing

GAMMA RADIATION Reading Too High

GAMMA RADIATION Reading Too Low

GAMMA RADIATION Reading Unchanged Too Long

RAIN GAGE Change Too Large

RAIN GAGE Format Error Detected

RAIN GAGE Invalid Data

RAIN GAGE Parity Error Detected

RAIN GAGE Reading Missing

RAIN GAGE Reading Too High

RAIN GAGE Reading Too Low

RAIN GAGE Reading Unchanged Too Long

RELATIVE HUMIDITY Change Too Large

RELATIVE HUMIDITY Format Error Detected

RELATIVE HUMIDITY Invalid Data

RELATIVE HUMIDITY Parity Error Detected

RELATIVE HUMIDITY Reading Missing

RELATIVE HUMIDITY Reading Too High

RELATIVE HUMIDITY Reading Too Low

RELATIVE HUMIDITY Reading Unchanged Too Long

SHAFT ENCODER Change Too Large

SHAFT ENCODER Format Error Detected

SHAFT ENCODER Invalid Data

SHAFT ENCODER Parity Error Detected

SHAFT ENCODER Reading Missing

SHAFT ENCODER Reading Too High

SHAFT ENCODER Reading Too Low

SHAFT ENCODER Reading Unchanged Too Long

SNOW DEPTH Change Too Large

SNOW DEPTH Format Error Detected

SNOW DEPTH Invalid Data

SNOW DEPTH Parity Error Detected

SNOW DEPTH Reading Missing
114 USDA Forest Service RMRS-GTR-119. 2003. 

SNOW DEPTH Reading Too High

SNOW DEPTH Reading Too Low

SNOW DEPTH Reading Unchanged Too Long

SNOW PILLOW Change Too Large

SNOW PILLOW Format Error Detected

SNOW PILLOW Invalid Data

SNOW PILLOW Parity Error Detected

SNOW PILLOW Reading Missing

SNOW PILLOW Reading Too High

SNOW PILLOW Reading Too Low

SNOW PILLOW Reading Unchanged Too Long

SOIL MOISTURE Change Too Large

SOIL MOISTURE Format Error Detected

SOIL MOISTURE Invalid Data

SOIL MOISTURE Parity Error Detected

SOIL MOISTURE Reading Missing

SOIL MOISTURE Reading Too High

SOIL MOISTURE Reading Too Low

SOIL MOISTURE Reading Unchanged Too Long

SOIL TEMPERATURE Change Too Large

SOIL TEMPERATURE Format Error Detected

SOIL TEMPERATURE Invalid Data

SOIL TEMPERATURE Parity Error Detected

SOIL TEMPERATURE Reading Missing

SOIL TEMPERATURE Reading Too High

SOIL TEMPERATURE Reading Too Low

SOIL TEMPERATURE Reading Unchanged Too Long

SOLAR RADIATION Change Too Large

SOLAR RADIATION Format Error Detected

SOLAR RADIATION Invalid Data

SOLAR RADIATION Parity Error Detected

SOLAR RADIATION Reading Missing

SOLAR RADIATION Reading Too High

SOLAR RADIATION Reading Too Low

SOLAR RADIATION Reading Unchanged Too Long

VISIBILITY MILES Change Too Large

VISIBILITY MILES Format Error Detected

VISIBILITY MILES Invalid Data

VISIBILITY MILES Parity Error Detected

VISIBILITY MILES Reading Missing

VISIBILITY MILES Reading Too High

VISIBILITY MILES Reading Too Low

VISIBILITY MILES Reading Unchanged Too Long

VISIBILITY MTNCE Change Too Large

VISIBILITY MTNCE Format Error Detected

VISIBILITY MTNCE Invalid Data

VISIBILITY MTNCE Parity Error Detected

VISIBILITY MTNCE Reading Missing

VISIBILITY MTNCE Reading Too High

VISIBILITY MTNCE Reading Too Low

VISIBILITY MTNCE Reading Unchanged Too Long

WATER FLOW Change Too Large

WATER FLOW Format Error Detected

WATER FLOW Invalid Data

WATER FLOW Parity Error Detected

WATER FLOW Reading Missing

WATER FLOW Reading Too High

WATER FLOW Reading Too Low

WATER FLOW Reading Unchanged Too Long

WATER LEVEL Change Too Large

WATER LEVEL Format Error Detected

WATER LEVEL Invalid Data

WATER LEVEL Parity Error Detected
USDA Forest Service RMRS-GTR-119. 2003. 115

WATER LEVEL Reading Missing

WATER LEVEL Reading Too High

WATER LEVEL Reading Too Low

WATER LEVEL Reading Unchanged Too Long

WATER PRESSURE Change Too Large

WATER PRESSURE Format Error Detected

WATER PRESSURE Invalid Data

WATER PRESSURE Parity Error Detected

WATER PRESSURE Reading Missing

WATER PRESSURE Reading Too High

WATER PRESSURE Reading Too Low

WATER PRESSURE Reading Unchanged Too Long

WATER QUALITY Change Too Large

WATER QUALITY Format Error Detected

WATER QUALITY Invalid Data

WATER QUALITY Parity Error Detected

WATER QUALITY Reading Missing

WATER QUALITY Reading Too High

WATER QUALITY Reading Too Low

WATER QUALITY Reading Unchanged Too Long

WATER TEMPERATURE Change Too Large

WATER TEMPERATURE Format Error Detected

WATER TEMPERATURE Invalid Data

WATER TEMPERATURE Parity Error Detected

WATER TEMPERATURE Reading Missing

WATER TEMPERATURE Reading Too High

WATER TEMPERATURE Reading Too Low

WATER TEMPERATURE Reading Unchanged Too Long

WATER TURBIDITY Change Too Large

WATER TURBIDITY Format Error Detected

WATER TURBIDITY Invalid Data

WATER TURBIDITY Parity Error Detected

WATER TURBIDITY Reading Missing

WATER TURBIDITY Reading Too High

WATER TURBIDITY Reading Too Low

WATER TURBIDITY Reading Unchanged Too Long

WEIGH GAGE Change Too Large

WEIGH GAGE Format Error Detected

WEIGH GAGE Invalid Data

WEIGH GAGE Parity Error Detected

WEIGH GAGE Reading Missing

WEIGH GAGE Reading Too High

WEIGH GAGE Reading Too Low

WEIGH GAGE Reading Unchanged Too Long

WIND DIRECTION Change Too Large

WIND DIRECTION Format Error Detected

WIND DIRECTION Invalid Data

WIND DIRECTION Parity Error Detected

WIND DIRECTION Reading Missing

WIND DIRECTION Reading Too High

WIND DIRECTION Reading Too Low

WIND DIRECTION Reading Unchanged Too Long

WIND SPEED Change Too Large

WIND SPEED Format Error Detected

WIND SPEED Invalid Data

WIND SPEED Parity Error Detected

WIND SPEED Reading Missing

WIND SPEED Reading Too High

WIND SPEED Reading Too Low

WIND SPEED Reading Unchanged Too Long
116 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix Q. KCFast Data File Formats

Table Q-1 contains the 1972 Data File Format of RAWS 13:00-hour observations. Table 

Q-2 contains the 1998 Data File Format of all hourly observations. Table Q-3 contains the 

Standard Extract: Fire Occurrence Output Format. 

Table Q-1: RAWS Weather Station 1972 Data Format (*.fwx).

Field Field Name Columns

1 STATION NUMBER 1-6

2 YEAR 7-8

3 MONTH 9-10

4 DAY 11-12

5 STATE OF WEATHER (CODE) 13

6 DRY BULB TEMPERATURE (oF) 14-16

7 RELATIVE HUMIDITY (%) 17-19

8 HERBACEOUS GREENNESS FACTOR 20-22

9 HERBACEOUS VEGETATION CONDITION 23-24

10 HUMAN-CAUSED RISK 25-27

11 WIND DIRECTION (8 POINT) 28

12 WIND SPEED (MPH) 29-31

13 WOODY VEGETATION CONDITION 32

14 10-HR FUEL MOISTURE (%) 33-35

15 WOODY GREENNESS FACTOR 36-38

16 MAXIMUM TEMPERATURE (oF) 39-41

17 MINIMUM TEMPERATURE (oF) 42-44

18 MAXIMUM RH (%) 45-47

19 MINIMUM RH (%) 48-50

20 SEASON CODE 51

21 PRECIPITATION DURATION (HRS) 52-53

22 PRECIPITATION AMOUNT (IN) 54-57

23 LIGHTNING ACTIVITY LEVEL 58-60

24 RELATIVE HUMIDITY VARIABLE (see note) 61

25 FORECAST FLAG 79

26 REGION NUMBER 80

Note: RH variable 1 = Wet bulb, 2 = RH%, 3 = dew point.
USDA Forest Service RMRS-GTR-119. 2003. 117

Table Q-2: RAWS Weather 1998 Data Format.

Item Cols Type Description

1 01-03 3A Record type (W98). All records begin with this record type identifier code.

2 04-09 6N Station Number.

3 10-17 8N Observation date (YYYYMMDD).

4 18-21 4N Observation time (0000-2359).

5 22 1A Observation type (O=NFDRS, R=RAWS other than at the standard 

 NFDRS observation time, F=Forecast, X=Other).

6 23 1N State of weather code

7 24-26 3N Dry bulb temperature (degrees Fahrenheit or degrees Celsius based on 

 Measurement Type code [col. 63]).

8 27-29 3N Atmospheric moisture (wet bulb temperature, relative humidity (percent), 

 or dewpoint temperature based on Moisture Type code [col. 62]).

9 30-32 3N Wind direction azimuth measured from true north. 0 (zero) means no 

 wind direction, 360 is north.

10 33-35 3N Average windspeed over a 10-minute period (miles or kilometers per 

 hour based on Measurement Type code).

11 36-37 2N Measured 10-hour time lag fuel moisture.

12 38-40 3N Maximum Temperature (degrees Fahrenheit or degrees Celsius based 

 on Measurement Type code [col. 63]).

13 41-43 3N Minimum Temperature (degrees Fahrenheit or degrees Celsius based on 

 Measurement Type code [col. 63]).

14 44-46 3N Maximum relative humidity (percent).

15 47-49 3N Minimum relative humidity (percent).

16 50-51 2N Precipitation duration (hours).

17 52-56 5N Precipitation amount based on Measurement Type code [col. 63]. 

 Blanks=no precipitation. U.S. measurement: inches with implied 

 decimal nn.nnn format; trace shown as 00005. Metric measurement: 

 measured in millimeters, no implied decimal; trace shown as 00001.

18 57 1A Wet flag (Y/N).

19 58-59 2N Herbaceous greenness factor (0-20).

20 60-61 2N Shrub greenness factor (0-20).

21 62 1N Moisture Type code (1=Wet bulb, 2=Relative Humidity, 3=Dewpoint).

22 63 1N Measurement Type code: 1=U.S.,2=Metric. Affects temperature (oF or 

 oC), wind (miles or kilometers per hour), and precipitation (decimal 

 inches or millimeters).

23 64 1N Season code (1=Winter, 2=Spring, 3=Summer, 4=Fall).

24 65-68 4N Solar radiation (watts per square meter).
118 USDA Forest Service RMRS-GTR-119. 2003. 

Table Q-3: Standard Extract: Fire Occurrence Output Format.

Field Field Name Columns

1 REPORTING FS REGION 1-2

2 REPORTING FS UNIT 3-4

3 FIRE NUMBER 5-7

4 DISTRICT NUMBER 8-9

5 STATISTICAL CAUSE 10

6 GENERAL CAUSE 11

7 SPECIFIC CAUSE 12-13

8 CLASS OF PEOPLE 14

9 FIRE SIZE CLASS 15

10 TOTAL AREA BURNED 16-24

11 FS AREA BURNED 25-33

12 NON-FS, UNDER FS PROTECTION AREA BURNED 34-42

13 NON-FS AREA BURNED 43-51

14 VEGETATION COVER TYPE 52-53

15 NFMAS ASPECT 54

16 TOPOGRAPHY CODE 55

17 FMZ_CODE 56-59

18 BLANK 60

19 REPRESENTATIVE WEATHER STATION NUMBER 61-66

20 NFDRS FUEL MODEL 67

21 FIRE INTENSITY LEVEL 68

22 FIRE INTENSITY SOURCE 69-70

23 LATITUDE (DDMMSS) 71-76

24 LONGITUDE (DDDMMSS) 77-83

25 TOWNSHIP 84-88

26 RANGE 89-93

27 SECTION 94-95

28 SUB-SECTION 96-99

29 PRINCIPAL MERIDIAN 100-101

30 SLOPE PERCENT 102-104

31 ASPECT CLASS 105

32 ELEVATION (FEET) 106-110

33 STATE CODE 111-112

34 COUNTY CODE 113-115

35 PROTECTION AGENCY 116-118

36 OWNERSHIP AT ORIGIN 119

37 PRESCRIBED FIRE (Y/N) 120

38 ESCAPED FIRE (Y/N) 121

39 INITIAL SUPPRESSION STRATEGY 122
USDA Forest Service RMRS-GTR-119. 2003. 119

40 FFF COST, IN DOLLARS 123-131

41 FIRE IGNITION DATE (YYYYMMDD) 132-139

42 FIRE IGNITION TIME (HH24MI) 140-143

43 FIRE DISCOVERY DATE (YYYYMMDD) 144-151

44 FIRE DISCOVERY TIME (HH24MI) 152-155

45 FIRST ACTION DATE (YYYYMMDD) 156-163

46 FIRST ACTION TIME (HH24MI) 164-167

47 SECOND ACTION DATE (YYYYMMDD) 168-175

48 SECOND ACTION TIME (HH24MI) 176-179

49 DECLARED WILDFIRE DATE (YYYYMMDD) 180-187

50 DECLARED WILDFIRE TIME (HH24MI) 188-191

51 FIRE CONTAINED DATE (YYYYMMDD) 192-199

52 FIRE CONTAINED TIME (HH24MI) 200-203

53 FIRE CONTROLLED DATE (YYYYMMDD) 204-211

54 FIRE CONTROLLED TIME (HH24MI) 212-215

55 FIRE OUT DATE (YYYYMMDD) 216-223

56 FIRE OUT TIME (HH24MI) 224-227

57 FIRE NAME 228-247

58 FIRE ID (NIFMID ID#) 248-254

59 PCODE 255-259

60 WILDERNESS 260-262
120 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix R. SIT – Interagency Situation Report

The Interagency Situation Report (SIT) program is a web application; rather than information being mailed first to the GACC’s then to NICC, the GACC’s and NICC can go directly 

to the SIT web server and generate reports using the data that the local dispatch offices had 

entered. The last includes daily fire statistics, resource information, incident information, 

planned fires, and preparedness levels. During the fire season this information and situation 

reports are generated daily; during non-fire season the report is submitted irregularly depending on the level of incident activity. Examples are provided of input and output for the Fort 

Collins Dispatch Center as of September 12, 2003 (see below). 
USDA Forest Service RMRS-GTR-119. 2003. 121

Dispatch Office Detailed Situation Report 10/8/2003

Ft Collins Dispatch Center

Wildfire Activity New

Human

New

Lightning Uncntrld

YTD

Human

YTD

Unit Lightning

ID

Fire

Dngr

P

Unit Name Agency L Fires Acres Fires Acres Fires Fires Acres Fires Acres

FTC 

COUNTIES CNTY COFTX NR 6 8 15 148

sum 6 8 15 148

Rocky Mountain 

Arsenal FWS CORMR NR 0 0 0 0

sum 0 0 0 0

ROCKY 

MOUNTAIN 

NATIONAL 

PARK

NPS CORMP NR 0 0 1 0

sum 0 0 1 0

ARAPAHOROOSEVELT 

N.F./PAWNEE 

N.G.

USFS COARF NR 12 1 38 33

sum 12 1 38 33

total 18 9 54 181

No report for fire danger levels.

Prescribed Fires daily Report

Prescribed Fires Wildland Fire Use (WFU)

New Year to Date New Year to Date

Unit Agency Fires Acres Fires Acres Fires Acres Fires Acres

CO-FTX CNTY NR 1 10 NR 0 0

sum 1 10 0 0

CO-RMR FWS NR 4 275 NR 0 0

sum 4 275 0 0

CO-RMP NPS NR 4 64 NR 0 0

sum 4 64 0 0

CO-ARF USFS NR 7 890 NR 0 0

sum 7 890 0 0

total 16 1,239 0 0

Remarks for office.

Large Fire Totals

Acreage Personnel CRW1 CRW2 HEL1 HEL2 HEL3 ENGS OVHD

0 0 0 0 0 0 0 0 0

Resource status ( a = Available, c = Committed)

AIRT SEAT LEAD AAAC SJAC HEL1 HEL2 HEL3 CRW1 CRW2

Unit a c a c a c a c a c a c a c a c a c a c

 

Totals 

Total Committed Resources (Large Fire and IA/Extended Attack)

CRW1 CRW2 HEL1 HEL2 HEL3 ENGS OVHD

0 0 0 0 0 0 0

Who is on call?

Return to the Select Dispatch Office Menu 

Report executed on: 08-Oct-2003 1438 mountain time
122 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix S. 209 Incident Report Form

The incident Status Summary Form 209 is used for reporting information on a regular basis 

about incidents of significance. The 209 form is now web based and can be accessed through 

NIFMID at local, geographic, and national levels. When possible, information is entered at the 

management level that is nearest to the incident or at the dispatch level and so on. Information 

inputs include: date, time, location, incident name, current situation and outlook, committed 

resources, size, percent contained, threat level, basic current weather data and forecast (when 

available), and major problems and concerns. An example form is provided below.

Incident Status Summary (ICS-209)

1: Date

09/12/2003

2: Time

1800 | |

3: Initial | Update | Final

XX

4: Incident Number

WA-OWF-398

5: Incident Name

NEEDLE

6: Incident Kind

Wildland Fire

7: Start Date Time

08/05/2003 2000

8: Cause

Lightning

9: Incident Commander

Hart

10: IMT Type

1

11: State-Unit

WA-OWF

12: County

OKANOGAN "

13: Latitude and

Longitude

Lat: 48° 36 ́ 0

Long: 120° 40 ́ 0"

14: Short Location Description (in reference to nearest town):

12 MILES NW OF WINTHROP, WA. near the Town of

Mazama

Current Situation

15: Size/Area

Involved

21,250 ACRES

16: % Contained

or

MMA

60 Percent

17: Expected

Containment

Date:

Time:

18: Line to

Build

19: Costs

to Date

$3,227,297

20: Declared

Controlled

Date:

Time:

21: Injuries this

Reporting Period:

22: Injuries

to Date: 23: Fatalities 24: Structure Information

1 2 0 Type of Structure # Threatened # Damaged # Destroyed

25: Threat to Human Life/Safety:

Evacuation(s) in progress ----

No evacuation(s) imminent -- XX

Potential future threat -------- XX

No likely threat --------------- 

Residence 100

Commercial Property

Outbuilding/Other

26: Communities/Critical Infrastructure Threatened (in 12, 24, 48 and 72 hour time frames):

12 hours:

24 hours:

48 hours:

72 hours:

27: Critical Resource Needs (kind & amount, in priority order):

1. HCWM (3)

2. SEC 1 or 2 (6)

3. SPUL (1), COST (1), TIME(1)

28: Major problems and concerns (control problems, social/political/economic concerns or impacts, etc.) Relate critical

resources needs identified above to the Incident Action Plan.

STEEP RUGGED TERRAIN, FALLING SNAGS MAKE CONTROL EFFORTS

DIFFICULT IN DIVISION A AND C. ACCESS VIA HELISPOTS ALSO OF CONCERN.

29: Resources threatened (kind(s) and value/significance):

COMMUNITY WATERSHEDS, VIEW SHED

30: Current Weather Conditions

Wind Speed: 8-12G20 mph Temperature: 65

Wind Direction: WEST Relative Humidity: 35

31: Resource benefits/objectives (for prescribed/wildland

fire use only):

32: Fuels/Materials Involved: 10 Timber (litter and understory)

heavy down and dead fuels

ICS-209 Form 10/10/03 3:08 PM

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USDA Forest Service RMRS-GTR-119. 2003. 123

33: Today's observed fire behavior (leave blank for non-fire events):

FIRE IS CREEPING TO THE EAST TOWARD THE LOST RIVER DEVELOPMENT

CARRIED BY THE LARGE FUELS. HIGH HUMIDITY IS LIMITING THE FINE FUELS

TO BURN AGGRESSIVELY AND SPOTTING FROM THE OCCASIONAL TORCHING

OF SMALL POKESTS OF TIMBER WITHIN THE PERIMETER.

34: Significant events today (closures, evacuations, significant progress made, etc.):

DIRECT LINE CONSTRUCTION IN DIVISION C ALONG CALOWAY CREEK AND

DIVISION A BETWEEN METHOW RIVER AND H-4.

Outlook

35: Estimated

Control

Date and Time:

36: Projected Final

Size:

115,000

37: Estimated Final

Cost:

$6,670,000

38: Tomorrow's Forecasted Weather

Wind Speed: 2-3 mph Temperature: 70

Wind Direction: UP CANYON Relative

Humidity: 25%

39: Actions planned for next operational period:

CONTINUE LINE CONSTRUCTION IN DIV. C. BEGIN LINE CONSTRUCTION IN DIV.

D BETWEEN CALOWAY CREEK AND MC GEE CREEK. MOP UP AND LINE

IMPROVEMENT CONTINUING IN DIV. A AND E.

40: Projected incident movement/spread during next operational period:

SHOULD NOT BE ANY SIGNIFICANT MOVEMENT OF SPREAD DURING NEXT

OPERATIONAL PERIOD HOWEVER ALL DIVISIONS ARE TO BE MORE CAUTIOUS

DUE TO A WARMING AND DRYING TREND.

41: For fire incidents, describe resistance to control in terms of:

1. Growth Potential - Medium

2. Difficulty of Terrain - Extreme

42: How likely is it that containment/control targets will be met, given the current resources and suppression/control

strategy?

GOOD CHANCE CONTROL OBJECTIVES WILL BE MET WITH THE ADDITION OF

FIVE TYPE 1 HAND CREWS OVER THE NEXT SEVERAL OPERATIONAL PERIODS.

43: Projected demobilization start date:

44: Remarks:

ALL HIKING TRAILS IN THE VICINITY OF THE FIRE REMAIN CLOSED. HIGHWAY

20 IS BEING MONITORED TO KEEP TRAVELERS FROM STOPPING AND

OBSERVING THE FIRE ACTIVITY AND CREATING PARKING HAZARDS BECAUSE

OF THE INCREASED HELICOPTERS. THE NEEDLES INCIDENT IS BURNING

APPROXIMATELY 12 MILES NORTHWEST OF WINTHROP IN VERY STEEP

RUGGED TERRAIN WITH LITTLE TO NO ACCESS. THE ONE INJURY WAS SEVERE

ANKLE SPRAIN. HARTS PASS ROAD WAS OPEN TODAY OF SNAGS AND

DISCOVERED ONE OUTBUILDING AND CAMPGROUND WAS BURNED OVER AT

HARTS PASS.

45: Committed Resources

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124 USDA Forest Service RMRS-GTR-119. 2003. 

Agency

CRW1 CRW2 HEL1 HEL2 HEL3 ENGS DOZR WTDR OVHD Camp

Crews

Total

SR ST SR ST SR SR SR SR ST SR ST SR SR Personnel

NPS 6 6

PRI 3 4 1 3 22 2 17 55 163

OTHR 12 12

CNTY 8 8

USFS 4 4 66 224

BIA 1 1

FWS 2 2

BLM 2 2 17 99

ST 2 1 10 50 2 125

Total 6 0 11 0 4 2 3 32 0 2 0 17 217 2 640

46: Cooperating and Assisting Agencies Not Listed Above:

OKANOGAN COUNTY SHERIFF'S OFFICE, WSP, OKANOGAN COUNTY FIRE

DISTRICT #6

Approval Information

47: Prepared by:

JAMES MUNROE, SITL (T)

48: Approved by:

STEVE HART, IC

49: Sent to:NWCC by: JAM

Date: 09/12/2003 Time: 1830

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USDA Forest Service RMRS-GTR-119. 2003. 125

Appendix T. GeoMAC Site Hierarchy and 

Options

This web-based fire application was developed by the Geospatial Multi-Agency 

Coordination Group of the U.S. Geological Survey. A flow chart is presented below. Further 

details are given in the Data Retrieval section of the report and in Appendix O.

About GeoMAC

Wildland fire maps

functions

locator

thermal avhrr

zoom

zoom in

thermal modis

layer/legend back

sit report fires

hyperlink

non-active sit fires

print

RAWS weather

reload

cities

full extent

road shields

zoom out

roads

pan

states

identify

water bodies

lat/long

rivers

shaded relief

help

urban outer face

Wildland fire information map

(conterminous US)

What is GeoMAC

How it works

The need for GeoMAC

The development team

Contact information

GeoMAC

Welcome Page
126 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix U. Summary of Responses to RAWS 

Survey

Survey questions were primarily concerned with data use, sampling protocols, importance 

of data, and data type elements. Responses were processed by simply tabulating results for 

fixed questions and parts of questions and then summarized. A total of 44 responses were 

received, evenly divided between NWS/WFO and federal and state land management users.

Survey question 1. What do you use RAWS for ?

incident management

fuels management

prescribed burning

research

hydrology

avalanche management

water quality or stream levels

air quality monitoring

resource management

public awareness/communication

weather prediction/forecasting

legal

other(?)

RAWS data were used for multiple purposes by all respondents. Of the above choices weather prediction/forecasting was the primary category accounting for 71% of use followed by incident management, prescribed burning (both roughly 40%), and fuels management. RAWS 

data were also used to support basic research, hydrology, public awareness/communication, 

resource management, and air quality monitoring by respondents. The category ‘other’ included general weather monitoring and summaries, and spot forecasts. Virtually all NWS 

respondents use RAWS data for weather prediction/forecasting; five do not use RAWS data at 

all nor are they involved in issuing fire weather forecasts.

Survey question 2. What type of weather data or NFDRS output do you use ?

fire danger rating indices/components (e.g. IC, BI, ERC, SC)

wind speed

wind direction

relative humidity

air temperature

rainfall/precipitation

fuel temperature

fuel moisture

peak wind gust

direction of peak wind gust

solar radiation

other (?)

NFDRS indices and components are used by 45% of NWS/WFO’s, the remainder did not 

use any NFDRS output. Twenty percent of land management responses indicated no NFDRS 

output use; the remainder did use NFDRS indices and components. Wind speed and direction, relative humidity, air temperature, precipitation, and fuel moisture were elements used by 

about 83% of all respondents. Fuel temperature and direction of peak wind gust were used by 
USDA Forest Service RMRS-GTR-119. 2003. 127

only about one-third of respondents. The other category included max/min air temperature, 

max/min RH, and KBDI.

Survey question 3. What data frequency do you use ?

daily

hourly

instantaneous/real time

event specific

minute

Almost 88% of all respondents use hourly and daily (daily = the 13:00 hr observation) observations; the real time and event specific categories accounted for the remaining responses. 

Almost all respondents indicated using data at multiple frequencies.

Survey question 4. What spatial resolution (area) do you use the data for and 

what do you need ?

GACC

agency region

national forest area

weather/climate zone

a specific location

Ninety percent of NWS/WFO respondents use the RAWS data set for a specific location 

and/or weather/climate zone. Sixty-eight percent of land management responses indicated 

use of RAWS data for agency regions and national forest areas; 21% for GACC use, weather/

climate zone, or a specific location; 11% did not respond to this question. These results are not 

very surprising given the different mandates driving these agencies and their different areas 

of interest and concern.

Survey question 5. For what decision(s) or judgment(s) are the data used for 

(briefly describe in your own words).

The majority of land management agency respondents use the RAWS data set for fire business applications (calculating NFDRS indices and components), determining staffing levels, 

incident management, informing the public (adjective fire danger ratings). Respondents from 

the NWS also use RAWS data for fire weather forecasting, public weather forecasts, red flag 

and fire weather watches, severe weather warnings, point forecasts, and forecast verification. 

The difference in use by these two groups was split along agency lines

Survey question 6. What potential impact of the data use do you see on your 

decision/judgment ? and Why ? (please briefly describe).

Given the answers to this question it was interpreted by respondents either as: describe 

the impact upon decision making resulting from lack of RAWS data or as: describe the importance of the RAWS data for your primary use of the data set. With respect to the former, 

answers range from: I cannot live without RAWS data – too many critical decisions are based 

on historical and current weather conditions to If you don’t have ground-truth data how can 

you make an intelligent decision? The importance of RAWS data was critical for calculating 

NFDRS indices and components, area fire weather and spot/point forecasts, fire fighter safety, 

resource management, staffing, and monitoring weather during prescribed burns or an incident. This was true for both the NWS and land management agency personnel.
128 USDA Forest Service RMRS-GTR-119. 2003. 

Survey question 7. Do you have any geographic areas or topographic 

settings where weather sampling/stations overlap or areas where there is not 

enough coverage ? If either or both, where ?

The answers to this question indicated an interpretation of: Is there any overlap of RAWS 

coverage in your area? Answers were almost all: no overlap in coverage, pretty good coverage, 

or adequate to there are gaps in my area/not enough coverage – we need more stations (authors quotation marks). The latter were mostly from areas in the mid-west continental United 

States, North-East, and East. One respondent indicated both conditions (FS Southern Region) 

and only two described overlapping station coverage; the last were two WFO areas located in 

North Carolina.

Survey question 8. Updating/upgrading RAWS data collection and NFDRS 

output protocols:

Background given as part of the question: Many users of RAWS data demand that they 

need a specific record like the 10-minute average wind speed or the instantaneous temperature, etc. as recorded only once per hour prior to transmission time. This has lead to disproportional competition for transmission times close to the top of the hour. Others have been asking 

for hourly averages or hourly maximums/minimums (of air temp. and/or relative humidity) as 

more representative of the actual weather. The current RAWS data output protocols are based 

on what was possible in the past when data could only be collected manually. With modern 

communication new data protocols are now possible – transmission more than once an hour 

and higher rates. It is true that our fire danger rating indices and components (IC, BI, ERC 

etc. – generated once per day for 13:00 LST) are currently based on the existing RAWS data 

collection protocols and any changes would require testing of the effects on these indices and 

possible minor adjustments. However the indices may be improved with such changes. Please 

provide your thoughts, support or disagreements on the subject of changing data collection and 

NFDRS output protocols to take advantage of modern capabilities. (Please feel free to use any 

additional space).

This is a loaded question and we thought it would elicit some strong response; it did not. 

Only three out of all the respondents (about 9%) emphatically advocated leaving the sampling 

protocol and overall procedures as is. All other responses indicated a desire for change: real 

time data access, NFDRS output more than once per day, higher transmission frequencies 

(more than once per hour), and better data access were the most frequently expressed thoughts. 

We were not clear what was exactly meant by better data access as no details were given. Some 

RAWS have real time data access capability via telephone and can also alert local dispatch 

centers if critical thresholds are exceeded. Calculation and application of NFDRS more than 

once per day would have to be tested rigorously and higher transmission frequencies are already part of the strategic plan set forth by the RSFWSU and NFDRS output calculation more 

than once per day has been discussed by the FDWT.

Survey question 9. Are there other users (non federal or state) of your RAWS 

data that you know of ? And how is the data being used ?

Almost 30% of respondents thought there was non-governmental data use but could give 

no specifics, 30% indicated only that local States Departments of Environmental Quality or 

Forestry used the data, 20% did not know of any other users, only 4% provided specifics of 

non-governmental use, and 16% did not respond. Non-governmental agency use included 
USDA Forest Service RMRS-GTR-119. 2003. 129

State and National Nature Conservancies, local fire departments, and the Province of Ontario 

(Canada) for hydrological purposes.

Survey question 10. Are RAWS and/or WIMS operations (maintenance, data 

entry and QA/QC) part of your position description? If so could you provide 

us with the wording as set out in your PD?

Almost without exception an explicit description of RAWS/WIMS related duties were not 

included in respondents Position Descriptions (87%). Four respondents replied yes but only 

one could give specifics as to exact wording (see Appendices K and M). Those who are involved in the RAWS program and/or perform WIMS duties have stated (to the authors) that 

such descriptions are usually vague; phrases such as ...weather related duties... are more 

common than not. This question was included to provide support for our recommendation to 

include explicit wording in Position Descriptions of those personnel involved in the RAWS 

and fire weather program regardless of agency affiliation.

Survey question 11. Summary RAWS Matrix: Please fill in based on your 

input above, indicate potential or current use.

All meteorological data elements were generally rated of high importance by all respondents. However, NWS/WFO personnel tended to rate NFDRS products of lower importance 

(or not at all) than land management agency respondents. The difference in response to this 

part of the matrix was quite striking – a 50/50 split, although in response to question 2 some 

personnel from WFO’s indicated that NFDRS output is looked at and evaluated. This is probably the result of two different missions. The NWS is tasked with issuing fire weather forecasts for use by land management agencies involved in generating NFDRS output for direct 

fire business applications. Desired data sampling frequency ranged across the spectrum; from 

on demand to daily (daily meaning the traditional 13:00 hour observation) and from the traditional 10 minute RAWS average to hourly averages.
130 USDA Forest Service RMRS-GTR-119. 2003. 

Comment(s):

Function: No response from anyone

Decision: No response from anyone

Below are given the authors summary of results for this matrix 

Parameter Importance a, Comment(s): sampling frequencyb

Temperature High on demand, hourly, daily

Relative Humidity High on demand, hourly, daily

Wind Speed High on demand, 10 min avg., hourly, daily

Wind direction High on demand, 10 min avg., hourly, daily

Fuel stick Temp Overall H on demand, 10 min avg., hourly, daily

Fuel Moisture High on demand, 10 min avg., hourly, daily

Pressure High on demand, 10 min avg., hourly, daily

Precipitation High on demand, 10 min avg., hourly, daily, 

 w/3 ,6, 12, 24 hour totals

Solar Radiation High but some do not use it at all

Soil Moisture M to H but usually not part of RAWS suite

Haines index overall M 

KBDI overall H on demand, 10 min avg., hourly, daily

Ventilation index M to H but still exptl. and some are unfamiliar

 with its meaning

NFDRS

Fosberg L to M but not widely used or even known

Burn index generally H on demand, 10 min avg., hourly, daily

Ignition component generally H on demand, 10 min avg., hourly, daily

Energy release component generally H on demand, 10 min avg., hourly, daily

Spread component generally H but not very widely used

Adjective rating generally H

Other Canadian fire Used somewhat in Alaska and Maine 

danger system – applicable to those fuel types a

 importance: H: very; M: somewhat; L: low. 

b

 e.g. daily 13:00 10-minute average, hourly instantaneous record, on demand 5-minute average, daily min/max, 

etc.
USDA Forest Service RMRS-GTR-119. 2003. 131

Air Resource Specialists, Inc of Fort Collins CO (ARS) prepared a Meteorological Station 

Instrument Specification Survey for the U.S.Forest Service. The objective of the survey was to 

provide a wide-ranging summary and comparison of sensors available for RAWS fire weather 

use.The survey provides field technicians and project scientists with current information for instrument selection. 

The survey also included a Technical Reference section listing all the above, the primary 

manufacturers, and contact information. Tables for each sensor type from each manufacturer 

are included; an electronic copy of the survey is also attached on CD-ROM. The sensors 

that were given priority (along with primary requirements) were:

• Wind Speed: able to measure horizontal component of wind

• Wind Direction: able to measure horizontal component of wind

• Ambient Air Temperature: suitable for outdoor use

• Relative Humidity: suitable for outdoor use

• Precipitation: liquid and solid precipitation

• Barometric Pressure: suitable for outdoor use

• Solar Radiation: suitable for outdoor use

• Other sensors listed (along with primary requirements) were:

• Fuel Moisture: suitable for outdoor use, able to measure fuel temperature and provide

 data instantaneously

• Fuel Temperature: suitable for outdoor use

• Soil Moisture: suitable for outdoor use, able to take electronic measurements below

 surface and report data instantaneously

• Soil Temperature: suitable for outdoor use, able to measure temperature below the

 surface

Quality of those instruments surveyed ranged from research quality to low-cost home-use 

sensors. Usually only one home-grade sensor was chosen as representative for each sensor 

type. The RAWS project criteria for instrument selection was primarily the instrument’s longterm durability in remote and often in extreme environments. Other criteria were based on the 

National Wildfire Coordinating Group (NWCG) standards and EPA Prevention of Significant 

Deterioration Monitoring (PSD) standards.

Data was collected through Internet sources, from vendors and manufacturers, scientific 

journals, the EPA, the American Society for Testing and Materials (ASTM International), the 

International Organization for Standardization (ISO 9000), National Institute for Standards 

and Technology (NIST) and others. The instrument survey was conducted between January 

and April 2002. Data was then transferred into Microsoft Excel database tables. Specifications 

are listed just as the vendor reported them in many cases.

The following parameters were used to compare the sensors surveyed. An explanation/key 

of the parameters follows the list.

• Manufacturer / Distributor: lists the manufacturer or vendor surveyed.

• Model Number and Name: instrument identification as supplied by the manufacturer

 or vendor and the name of whom to contact for more information.

• Remarks: additional features and considerations for identifying sensor.

Appendix V. Summary of Meteorological 

Station Instrument Specification Survey
132 USDA Forest Service RMRS-GTR-119. 2003. 

• Certifications: listed if met requirements of EPA Prevention of Significant Deterioration

 Monitoring (PSD); National Fire Danger Rating System (NFDRS); National Weather

 Service (NWS); Nuclear Regulatory Certification (NRC); and military certification

 operational requirements.

• Integral: indicates whether or not the sensor must be purchased as part of a combined

 unit of sensors.

• Method of Measurement: the approach of the sensor used to take the measurements. For

each sensor there may be alternative instrument designs for measuring the same variable.

• Range of Operation: a certain state of environmental conditions within which the 

 sensor is capable of responding accurately.

• Accuracy: the degree of the sensor’s response to the known or true value.

• Resolution: the smallest change in conditions the instrument can detect.

• Starting Threshold: the lowest wind speed required for accurate anemometer readings.

 For wind vanes, the wind speed must be great enough to move the vane from 10 ̊ off

 axis to within 5 ̊ off axis.

• Time Constant: The time required for the instrument to respond to 63% of the true 

 environmental value.

• Power Requirement: all sensors, except Solar Radiation sensors, require electrical 

 power. This is listed for volts and for watts. If a heater is available the power 

 consumption of the heater is reported under the parameter of Heater Power 

 Consumption or Heater Power Requirements.

• Output Signal: the available options of electrical signals that transfer measured data

 to the data logger.

• Regular Maintenance Interval and Long Term Stability: the ruggedness of the 

 instrument. The Regular Maintenance Interval is recommended by the manufacturer 

 to be the time intervals between maintenance other than the regular calibration 

 intervals. Barometric Pressure uses the Long-Term Stability parameter to show the 

 accuracy maintained over prolonged periods of operation.

• Sensor Materials: construction material(s).

• Dimensions: measurements appropriate for the sensor such as height, length, diameter 

 and orifice diameter as reported by manufacturer. Operational Dimensions allow 

 planning for the placement of the instrument.

• Weight: the reported weight of the instrument by the manufacturer.

• Cost / Spring 2002: the cost of the sensor as of spring 2002. If the sensor is integrated 

 with another sensor, the cost listed covers entire unit.

• Comments: any information that could not be placed in previous cells.

In addition to the above, other unique sensor properties were used to compare sensors on 

an individual basis.

Sensor Properties

• Wind Speed sensors:

1. The Distant Constant is the length of an air column needed to pass the sensor to 

 respond exponentially to 63% of a sudden step change in wind speed.

2. The Survival is the maximum wind gust that can be withstood by the instrument 

 without damage.

3. The Maximum Scan Rate for sonic anemometers is the maximum rate at which 

 the sensor can record accurate measurements.
USDA Forest Service RMRS-GTR-119. 2003. 133

• Wind Direction sensors:

1. The Dead Band is the magnitude that must be subtracted from 360∞ to correct for

 the gap between magnetic north and true north.

2. The Delay Distance parameter is the length of the column of air needed to pass 

 the sensor to return the vane to 50% of the initial 10% displacement angle.

3. The Damping Ratio relates the number of oscillations and the length of the 

 overshoot of the vane upon a shift in wind direction.

4. The Damped Natural Wavelength / Undamped Natural Wavelength is the free 

 oscillation of the wind vane after a directional change in wind. The wavelength is 

 either damped by the friction of the bearings, or undamped when only affected by 

 it’s own inertia.

• Precipitation sensors/gauges: precipitation type; either solid or liquid.

• Barometric Pressure sensors: Output Impedance is an indication of the amount of 

 impedance or resistance between the sensor transducer and the data logger over the 

 output terminals.

• Solar Radiation:

1. The Light Spectrum Waveband is the energy wavelength that the sensor is able to 

 detect.

2. The Sensitivity is the ratio of the magnitude of sensor signal per unit of irradiance.

• Fuel Temperature:

1. The Stick Size Available (related to fuel size) is the size of the dowel that the 

 temperature sensor is placed in.

2. The Temperature Storage Range is the highest and lowest temperatures that the 

 instrument can endure without damage.

3. The Interchangeability Error is the maximum amount of error between any two 

 sensors of the same make and model.
134 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix W. Super-RAWS Data Element List

Order Parameter Description Units Format

1 continuous accumulative precipitation ending at :15 inches xx.xx

2 10-minute average scalar wind speed from :05 to :15 mph xxx

3 10-minute average wind direction from :05 to :15 degrees xxx

4 single scan of 3 meter ambient air temperature at :15 F xxx

5 single scan of fuel temperature at :15 F xxx

6 10-minute average relative humidity from :05 to :15 % xxx

7 minimum data logger battery voltage DC Volts xx.x

8 single scan of barometric pressure at :15 inHg xx.xx

9 wind direction during peak wind speed for the hour degrees xxx

10 peak wind speed for the hour mph xxx

11 single scan of fuel moisture at :15 % xxx

12 single scan of solar radiation at :15 W/m2 xxxx

13 6-meter cup/vane scalar wind speed (hourly avg.) m/s xx.x

14 6-meter cup/vane vector wind speed (hourly avg.) m/s xx.xx

15 6-meter cup/vane wind direction (hourly avg.) degrees xxx

16 6-meter cup/vane standard deviation wind direction degrees xxx.x

17 6-meter cup/vane standard deviation of scalar wind speed m/s xxx.x

18 6-meter sonic scalar wind speed (hourly avg.) m/s xx.x

19 6-meter sonic vector wind speed (hourly avg.) m/s xx.xx

20 6-meter sonic wind direction (hourly avg.) degrees xxx

21 6-meter sonic standard deviation of wind direction degrees xxx.x

22 6-meter sonic standard deviation of scalar wind speed m/s xxx.x

23 15-meter sonic scalar wind speed (hourly avg.) m/s xx.x

24 15-meter sonic vector wind speed (hourly avg.) m/s xx.xx

25 15-meter sonic wind direction (hourly avg.) degrees xxx

26 15-meter sonic standard deviation of wind direction degrees xxx.x

27 15-meter sonic standard deviation of scalar wind speed m/s xxx.x

28 3-meter ambient air temperature (hourly avg.) C ±xx.x

29 3-15 meter delta air temperature (hourly avg.) C ±xx.x

30 standard deviation of 3-meter ambient air temperature C xx.x

31 3-meter relative humidity (hourly avg.) % xxx

32 standard deviation of 3-meter relative humidity % xx.x

33 barometric pressure (hourly avg.) mmHg xxx.x

34 standard deviation of barometric pressure mmHg xx.x

35 hourly average of solar radiation W/m2 xxxx

36 standard deviation of solar radiation W/m2 xx.x

37 hourly precipitation mm xxx.x

38 fuel temperature (hourly avg.) C ±xx.x

39 fuel moisture (hourly avg.) % xxx.x

40 duff moisture 1 (hourly avg.) % xxx.x

41 duff moisture 2 (hourly avg.) % xxx.x

42 soil moisture (hourly avg.) % xxx.x

43 soil temperature (hourly avg.) C ±xx.x

44 2.5 to 5 soil delta temperature (hourly avg.) C ±xx.x

45 leaf wetness (hourly avg.) % time wet xxx.x

46 calendar year 2002 xxxx

47 julian day xxx xxxx

48 Hour (GMT) xxxx xxxx

This is the data element list for the Super-RAWS, which is the experimental RAWS at 

Fernberg, MN.
USDA Forest Service RMRS-GTR-119. 2003. 135

Appendix X: Comparison of RAWS and SuperRAWS Data Sets

Presented here are the results of a comparison between the RAWS and super-RAWS data 

sets. Super-RAWS is the experimental RAWS at Fernberg, MN, discussed in the main text. 

This study compares traditionally collected RAWS data elements and the hourly averages of 

those same elements described in appendix W. Data elements compared were wind speed, 

wind direction, solar radiation, ambient temperature, and relative humidity. 

Figure X-1. Deviations of RAWS instantaneous measurements from actual hourly averages 

for solar radiation at the Fernberg site.
136 USDA Forest Service RMRS-GTR-119. 2003. 

Figure X-2. a & b: Deviations of reported RAWS 10-minute measurements from actual hourly averages 

for wind speed at the Fernberg site. c: Deviations of RAWS 10-minute as reported minus RAWS 10-

minute as measured.

c)
USDA Forest Service RMRS-GTR-119. 2003. 137

Figure X-3. Deviations of reported RAWS 10-minute measurements from actual hourly averages for wind direction at the Fernberg site.
138 USDA Forest Service RMRS-GTR-119. 2003. 

Figure X-4. Discrepancies in hourly averages of wind direction between the cup and the sonic 

anemometer at the Fernberg site.
USDA Forest Service RMRS-GTR-119. 2003. 139

Figure X-5. Deviations of RAWS instantaneous measurements from actual hourly averages for ambient temperature at the Fernberg site.
140 USDA Forest Service RMRS-GTR-119. 2003. 

Figure X-6. Deviations of reported RAWS 10-minute measurements from actual hourly averages 

for relative humidity at the Fernberg site.
USDA Forest Service RMRS-GTR-119. 2003. 141

Figure X-7. Discrepancies in hourly averages of wind speed between the cup and the sonic anemometer at the Fernberg site.
142 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix Y. Comparison of KCFast and WRCC 

Data Sets

The table below presents the results from a study comparing the KCFast and WRCC 

data sets (i.e., supposedly the same data) from four RAWS: Lake George, Cheeseman, and 

Redfeather in Colorado and Doyle in California. The figures below present the results from a 

study comparing the KCFast and WRCC data sets from two RAWS: Cheeseman in Colorado 

and Doyle in California.

Cheeseman Lake George Redfeather Doyle

Mean

Values

R2 = 0.85

S = 0.97

R2 = 0.94

S = 0.99

R2 = 0.90

S = 0.99

R2 = 0.86

Spread S = 1.08

Comp. Maximum

Value

R2 = 0.70

S = 0.96

R2 = 0.92

S = 1.00

R2 = 0.69

S = 0.99

R2 = 0.66

S = 1.04

Mean

Value

R2 = 0.98

S = 0.99

R2 = 0.99

S = 1.00

R2 = 0.99

S = 1.00

R2 = 0.99

Energy S = 1.01

Release

Comp. Maximum

Value

R2 = 0.95

S = 1.00

R2 = 0.99

S = 1.00

R2 = 0.98

S = 1.00

R2 = 0.98

S = 1.00

Mean

Value

R2 = 0.94

S = 0.98

R2 = 0.97

S = 0.99

R2 = 0.95

S = 1.00

R2 = 0.96

S = 1.04 Burning

Index Maximum

Value

R2 = 0.73

S = 0.99

R2 = 0.95

S = 0.97

R2 = 0.74

S = 0.99

R2 = 0.83

S = 1.03

Mean

Value

R2 = 0.93

S = 0.97

R2 = 0.97

S = 0.99

R2 = 0.94

S = 0.99

R2 = 0.95

S = 1.04 Ignition

Comp. Maximum

Value

R2 = 0.78

S = 0.99

R2 = 0.94

S = 0.99

R2 = 0.80

S = 1.00

R2 = 0.82

S = 1.01

Table Y-1. Correlation coefficients (R2) and regression slopes (S) between values of NFDRS indicies 

and components estimated from KCFast and WRCC data archives.
USDA Forest Service RMRS-GTR-119. 2003. 143

Figure Y-1. Temporal dynamics of the discrepancy (i.e., the arithmetic difference) between 1300-hour meteorological observations for the same data 

provided separately by WRCC and by KCFast for Cheeseman RAWS in 

Colorado.
144 USDA Forest Service RMRS-GTR-119. 2003. 

Figure Y-2. Comparison between 13:00-hour meteorological observations provided by WRCC and KCFast for Cheeseman RAWS in Colorado. Statistics 

include: r 2 = correlation coefficient, S = regression slope, and I = intercept.
USDA Forest Service RMRS-GTR-119. 2003. 145

Figure Y-3. Comparison between mean values of the Spread Component (SC) 

computed from meteorological data provided by WRCC and KCFast for Doyle 

RAWS in CA: (a) daily dynamics of the difference (in %) between the two estimates; (b) correlation between the two estimates (r 2

 = correlation coefficient, S

= regression slope).
146 USDA Forest Service RMRS-GTR-119. 2003. 

Figure Y-4. Comparison between maximum values of the Spread Component (SC) 

computed from meteorological data provided by WRCC and KCFast for Doyle 

RAWS in CA: (a) daily dynamics of the difference (in %) between the two estimates; (b) correlation between the two estimates (r 2

 = correlation coefficient, 

S = regression slope).
USDA Forest Service RMRS-GTR-119. 2003. 147

Figure Y-5. Comparison between maximum values of the Burning Index (BI) computed from 

meteorological data provided by WRCC and KCFast for Doyle RAWS in CA: (a) daily 

dynamics of the percent difference between the two estimates; (b) correlation between 

the two estimates (r 2 = correlation coefficient, S = regression slope).
148 USDA Forest Service RMRS-GTR-119. 2003. 

Appendix Z. RAWS Contacts at Regional and 

National Levels of USFS, NPS, and FWS

This Appendix contains a contact list for personnel at regional and national levels for USFS, 

NPS, and FWS. The e-version contains e-mail links via Lotus Notes. This list as of July 3, 2002.

Forest Service

RAWS Contacts

Name Phone e-maillinks, via Lotus Notes

BLM Remote Sensing Support Unit:

Buddy Adams 208-387-5475 buddy_adams@nifc.blm.gov

USFS National RAWS Coordinator:

Kolleen Shelley 208-476-8362 kshelley@fs.fed.us

Linnea Keating 208-476-8312 lkeating@fs.fed.us

USFS Regional RAWS Coordinators:

R01 - Bruce Thoricht 406-329-4875 bthoricht@fs.fed.us

R02 - Dave Clement 303-275-5791 dclement@fs.fed.us

R03 - Chuck Maxwell 505-842-3419 cmaxwell@fs.fed.us

R04 - Tenna Biggs 208-373-4179 tbiggs@fs.fed.us

R05 - Beth Little 530-226-2710 blittle@fs.fed.us

R06 - Neal Wurschmidt 541-416-6820 nwurschmidt@fs.fed.us

R08 - Eddy Holt 423-476-9700 eholt@fs.fed.us

R09 - Steve Marien 612-713-7300 stevemarien@fs.fed.us

R10 - Sharon Alden 907-356-5691 Sharon_Alden@blm.gov

NPS Fire Weather Program

Committee Membership

Name / Phone Address e-mail links, via Lotus Notes

Dick Bahr FMPC-NIFC Dick Bahr

208 387-5217 3833 S. Development Ave.

NIFC Coord. Boise, ID 83705-5354

Mike Warren FMPC-NIFC Mike Warren

208 387-52 3833 S. Development Ave.

NIFC Boise, ID 83705-5354

Marhsa Lutz Wrangel-St. Elias NP Marsha Lutz

907 822-5234 P.O. Box 439

Alaska Region Mile 105.5 Old Richardson Hwy

Copper Center, Ak 99573

Tim Stubbs Carlsbad Caverns NP Tim Stubbs

505 785-2232 x367 3225 National Parks Hwy

Intermountain Region Carlsbad, NM 88720

Doug Alexander Midwest Regional Office Doug Alexander

402 221-4994 1709 Jackson St.

Midwest Region Omaha, NE 68102

605 673-2061x1254 Temp> Jewell Cave NM
USDA Forest Service RMRS-GTR-119. 2003. 149

Don Boucher National Capitol Regional Office Don Boucher

202 619-7065 1100 Ohio Dr. SW

National Capital Region Room 357

Washington, DC 20242

Dave Bartlett New River Gorge NR Dave Bartlett

307 768-3191 P.O. Box 246

Northeast Region Glen Vern, WV 25846

Mike_Worthington Golden Gate NRA Mike Worthington

415 331-6374 1069 Ft. Cronkhite

Pacific West Region Sausalito, CA 94965

Dan Mapstone Natchez Trace Parkway Dan Mapstone

601 680-4029 2680 Natchez Trace Parkway

Southeast Region Tupelo, MS 38801

Michelle Hawley NIFC – RAWS Michelle Hawley

208 387-5475 3833 S. Development Ave.

Technical Spec. Boise, ID 83705-5354

FISH AND WILDLIFE SERVICE

REGIONAL RAWS COORDINATORS

Region Coordinator Phone

R01 Roddy Baumann 503-231-2075

R02 Jeff Whitney 505-248-6474

RAWS Tech / Field Coordinator Dean Ross 936-875-4786

R03 Meredith Weltmer 612-713-5445

R04 Lynn Howard 404-679-7190

R05 Allen Carter 757-986-3706

R06 Angie Braun 303-236-8145 ext 617

RAWS Tech / Field Coordinator Shannon Swanson 406-789-2305 ext 111

R07 Larry Vanderlinden 907-786-3654

National Coordinator Rod Bloms 208-387-5599
150 USDA Forest Service RMRS-GTR-119. 2003. 

A

ACC or GACC (Area Coordination Center or Geographic Area Coordination Center), 1, 5, 14,15, 

 27,29, 49, 53, 58, 65, Appendix A, B, I, N, U

Accuracy standards and protocols, 9-11, 35, 42, 43, Appendix I

AFFIRMS, 5, 6, 55

Anemometers, Appendix V

Archiving, data, 21-26, Appendix C, D, F, G, H

ASCADS (Automated Sorting Conversion and Distribution System), 21, 22, Appendix F

AT (Air temperature), 10, 55, 76

B

Barometric pressure sensors, Appendix V

BEHAVE, 55; see FARSITE

BI (Burn Index), Glossary, Appendix B

BP (Barometric pressure), 11

Boise Interagency Fire Center (BIFC/NIFC), 6-9, 14, 15, 21

Depot repair facility (RSFWSU), 14, 16, 27, 28

Direct Readout Ground Station (DRGS), (also see RAWS downlink), 8, 27, 28, 54

field support group, see RSFWSU (above)

C

CEFA (Climate, Ecosystem, and Fire Applications – research), 12, 56, Appendix A

CIRP (Cooperative Institute for Regional Prediction), 30, 56

Clouds, see also SOW (State of the Weather)

cover, 14

Communications, RAWS

satellite, 1, 8, 9, 21 - 26, 29, 30, 42 - 43, 45, 56, 58, 59, Appendix A, G, I, J, O

voice synthesizer, 29, Appendix B, I, J

Computer programs, 57, 59, 60

D

DAPS (Data Collection System (DCS) Automated Processing System), 43, 44, 56, Appendix F, I, P

Data, 9-26 (for sub-sections listed below)

archiving,

communication,

computer programs,

management,

quality control (monitoring)

processing,

retrieval,

storage,

summaries,

transmission (see data communication}

Data collection platform (DCP), RAWS, 10, 42, 55, Appendix I, N

Digital readout, see Appendix V for sub-sections listed below

anemometer

precipitation gauge

pyranometer

thermometer

wind vane

Dimensionality, 56

DOMSAT (Domestic satellite), 9, 27, 43, 56, Appendix I, O

Duff and duff bed, 34, Appendix W

E

Electrical (electronic) thermometers, Appendix V

Index
USDA Forest Service RMRS-GTR-119. 2003. 151

Electronics, RAWS system, 9,10

Electronics enclosure, 10

Equipment list, 10, 14-15 (for sub-sections listed below)

maintenance, manual stations,

maintenance, RAWS,

manual weather stations,

RAWS sensors, 10 and see BIFC/NIFC (above/RSFWSU)

ERC (Energy release component), 37, 39, 57, Appendix B, U

Exposure, instrument and sensor sitting, 10

F

FARSITE (Fire Area Simulator), 20, 57, 63, Appendix D

FCAMMS (Fire Consortia for Advanced Modeling of Meteorology and Smoke), 20, 27, 48, 49, 57, 

 Appendix A

FF+ or FFP (Fire Family Plus), 36, 37, 57

Fire & Aviation Management (F&AM) Helpdesk, 11, 19, 50

Fire danger indices, Appendix B

Fire-weather station, manual type, 4, 5, 18, 20

FM (Fuel moisture), 11, 57, Appendix B

FT (Fuel temperature), 10-12, 17, 33, 34, 57, Appendix B, I, U

Fuel model, 9, 20, 26, 57, Appendix B, C-2, E, I

Fuel moisture sticks, Appendix I, see also FM

G

GACC or ACC (Geographic Area Coordination Center or Area Coordination Center), see ACC or 

 GACC

GeoMAC (Geospatial Multi-Agency Coordination Group), 21, 26, 29, 58, Appendix A, O, T

GOES satellite (see satellite communication), see Communications, RAWS, satellite

H

Haines Index, 9, 58, 63, Appendix A, G, U

Hand-held anemometers, Appendix V

I

IC (Ignition component), 29, 37, 39, 58, Appendix B, C-1, U

Incident Report, Appendix S

IMET (Incident meteorologist), 1, 26, 58

Installation of equipment, 9-10

Instruments (sensors) (see individual listings for exposure, installation, maintenance, and operating 

 instructions)

desirable characteristics, Appendix V

K

KBDI (Keetch-Byram Drought Index), 52, 58, Appendix A, B, G, I, U

KCFast (Kansas City Fire Access Software), 24-25, Appendix A, C-1, D, Q, Y

L

LAL or LOI (Lightning activity level or Lightning occurrence index), 13, 14, 29, 36, 50, 58

Layout, weather station, 9-10

Location, station, see Exposure, instrument and station sitting

M

Maintenance, 14-16, also see BIFC/NIFC Depot repair facility

instrument (see individual instrument listings), tools and equipment

RAWS (see remote automatic weather stations, maintenance)

responsibility, 13, Appendix I, J, N

Management,

stations and network data, 20-26

Maximum air temperature, Appendix Q

Measurements and units (see also observations or operating instructions for individual instruments

 or weather elements), 10-12

Mesoscale weather modeling, see FCAMMS
152 USDA Forest Service RMRS-GTR-119. 2003. 

Metadata, 7-10, 13, 21-25, 28, 50, 53, 59, 62, Appendix H

Monitoring, RAWS, see Watchdog, Appendix I, J for sub-sections listed below

data,

performance,

N

National Environmental Satellite Data Information Service (NESDIS), 9, 22, 23, 29, 44, 59, 

 Appendix A, I

National Fire Danger Rating System (NFDRS) indices, 20, 34-42, Appendix B

NDVI (Normalized Difference Vegetation Index), see WFAS and Appendix G

NFDRS (National Fire Danger Rating System), 5 - 15, 20 -26, 33 -39, 44, 48, Appendix B

NICC (National Interagency Coordination Center), 30, 60, Appendix A, C-1, R

NIFC (National Interagency Fire Center), 6, 15, 25, 27, 50, 60, Appendix A, I, L

NIFMID (National Interagency Fire Management Integrated Database), 5-8, 16, 24-25, 29, 50, 60, 

 Appendix A, B, C-1, O

NITC (National Information Technology Center), 9, 25, 58, 60

NWCG (National Wildfire Coordinating Group), 7, 8, 11, 12, 17, 35, 57, 60, Appendix A, B

O

Observations (measurements) (see listings for individual instruments and data elements), 10-12

Observer responsibilities, Appendix I, L, K

Operating instructions (operation), see NWCG publication PMS 426-3 (2003), in references and 

 Appendix A for web site access

P

PD (Position Description), 51, 60, Appendix K, M

Pocket Card, Appendix E

Precipitation (PPT), 10, Appendix C-2

measurement, see Rain gauges

Predictive Service Meteorologist, see IMET

Preventive maintenance (see individual instrument listings and RAWS maintenance), 9-10, 14-15, 

 Appendix J

Pyranometers (and solar radiation), 10-12, 34-35

Instruments, Appendix V

R

Rain gauges (precipitation gauges), Appendix V

RAWS, see remote automatic weather stations

Red flag warning, 29, 33, 61, Appendix A, U

RH (Relative humidity), 10-12,

instruments or sensors, Appendix V

Remote automatic weather stations (RAWS),

antenna, 51, Appendix I

BLM Field Support Group, see RSFWSU

breakdown maintenance, see maintenance

classes, deployment, numbers, 17, 18, 19

communications, see Communications RAWS

configuration, 4, 9 – 11, 28, Appendix I

contracted services, 14, 15, Appendix I

data archiving, see Data

data collection platform, 9-26

data retrieval, 9-26, Appendix O

depot maintenance, 14-16, Appendix I

Direct Readout Ground Station (DRGS), 8, 27 - 29, 54

downlink, see communications

electronics, 10

equipment, 10

installation, 10

maintenance, 14-15, Appendix I, J

monitoring (Watchdog), 12, 21, 22, 53, 62, Appendix P
USDA Forest Service RMRS-GTR-119. 2003. 153

preventive (field) maintenance, see maintenance

portable RAWS, 16, 18, 27, 29, 46, 58

satellite (GOES) communications, see Communications RAWS, satellite

sensors, 10

sensor standards, see NWCG publication PMS 426-3 (2003), Appendix A for web site

solar panel, 51

transmitter, 8, 34, 43, Appendix I

tower, 10, 30, 39-42, Appendix I

voice synthesizer,17, 29, Appendix J, L

Responsibilities, personnel, Appendix I

RSFWSU (Remote Sensing Fire Weather Support Unit), 6, 14 - 17, 16, 27, 28, see also 

 BIFC/NIFC, Depot repair facility

S

Sampling protocols, 10-12, Appendix I

SC (Spread component), 37-39, 61, Appendix B, Y

Sensors, see instruments, and RAWS, 10, Appendix I

Sensor standards, RAWS, Appendix I, NWCG publication PMS 426-3 (2003)-Appendix A for 

 web site access

SIT (Situation Report, Interagency), Appendix R, S

Site selection standards, 10, Appendix I

Soil moisture measurement, 34, 39, Appendix G, P, U, V, W

Soil temperature, 34, 48, 52, Appendix P, V, W

Soil thermometers, Appendix V

SOW (State of the Weather), 4, 8, 11, 13, 14, 27, 36, 50, 61, Appendix B

SR (Solar Radiation), 10-12, 34, 35, 52, 61, Appendix P, V

Standards (RAWS), NWCG publication PMS 426-3 (2003)-Appendix A for web site access

T

Temperature, (see air, soil, and fuel temperature)

instruments, Appendix V for individual sensors

maximum and minimum, Appendix Q

Time (clock, WWV), 10, 15, 62

observations, 10-12

Tipping bucket rain gauge, Appendix V

Totalizing wind counter (wind odometer), 4

Tower, see RAWS/tower

Transmitter, RAWS, see communications/satellite

Twenty-foot standard height,

Adjustment of wind speed, see RAWS/tower

V

Vanes, wind (see wind vanes), Appendix V

W

Watchdog (alert system), see ASCADS, Appendix P

Weather modeling, see FCAMMS

Western Regional Climate Center (WRCC), 7, 22 – 24, Appendix H, Y

WFAS (Wildland Fire Assessment System), 7-9, 26, 53, 62, Appendix A, G

WFMI System (Wildland Fire Management Information System), 7, 9, 14, 21, 23, 25, 62

WD (Wind direction), 10-12

WIMS (Weather Information Management System), 6,12 - 17, 24 - 27, 29, Appendix C-1, C-2, O

WS (Windspeed), 10-12

adjustment to 20-foot standard height, 39-42

gusts, 10-11

instruments (see anemometers), Appendix V

Wind vane, Appendix V

WRCC (Western Regional Climate Center), 7, 8, 23-24, Appendix H
A Review of the Forest Service 

Remote Automated Weather 

Station (RAWS) Network

and

Appendix V: Instrument Specifi cation Survey

Air Resource Specialist, Inc. contract #: 53-82FT-7-03

RMRS-GTR-119

USDA Forest Service

Rocky Mountain Research Station
Federal Recycling Program Printed on Recycled Paper

RMRS

ROCKY MOUNTAIN RESEARCH STATION

The U.S. Department of Agriculture (USDA) prohibits discrimination 

in all its programs and activities on the basis of race, color, national 

origin, sex, religion, age, disability, political beliefs, sexual orientation, 

or marital or family status. (Not all prohibited bases apply to all 

programs.) Persons with disabilities who require alternative means for 

communication of program information (Braille, large print, audiotape, 

etc.) should contact USDA’s TARGET Center at (202) 720-2600 (voice 

and TDD).

To file a complaint of discrimination, write USDA, Director, Office 

of Civil Rights, Room 326 W, Whitten Building, 1400 Independence 

Avenue, SW, Washington, D.C. 20250-9410 or call (202) 720-5964 

(voice and TDD). USDA is an equal opportunity provider and employer.

The Rocky Mountain Research Station develops scientific 

information and technology to improve management, protection, 

and use of the forests and rangelands. Research is designed to 

meet the needs of the National Forest managers, Federal and 

State agencies, public and private organizations, academic 

institutions, industry, and individuals.

Studies accelerate solutions to problems involving 

ecosystems, range, forests, water, recreation, fire, resource 

inventory, land reclamation, community sustainability, forest 

engineering technology, multiple use economics, wildlife and fish 

habitat, and forest insects and diseases. Studies are conducted 

cooperatively, and applications may be found worldwide.

Research Locations

Flagstaff, Arizona Reno, Nevada

Fort Collins, Colorado* Albuquerque, New Mexico

Boise, Idaho Rapid City, South Dakota

Moscow, Idaho Logan, Utah

Bozeman, Montana Ogden, Utah

Missoula, Montana Provo, Utah

Lincoln, Nebraska Laramie, Wyoming

*Station Headquarters, Natural Resources Research Center, 

2150 Centre Avenue, Building A, Fort Collins, CO 80526.