DOE/SC-ARM-TR-070

> ARM Mobile Facility Surface Meteorology (MET) Handbook
>
> October 2008
>
> M.T. Ritsche
>
> Work supported by the U.S. Department of Energy,
>
> Office of Science, Office of Biological and Environmental Research

# Contents {#contents .Heading-Front}

[1. General Overview 1](#general-overview)

[2. Contacts 1](#contacts)

[3. Deployment Locations and History
2](#deployment-locations-and-history)

[4. Near-Real-Time Data Plots 2](#near-real-time-data-plots)

[5. Data Description and Examples 2](#data-description-and-examples)

[6. Data Quality 5](#data-quality)

[7. Instrument Details 6](#instrument-details)

**Tables**

[1. Locations and Sensors 2](#__RefHeading___Toc164237670)

# General Overview

The ARM Mobile Facility Surface Meteorology station (AMF MET) uses
mainly conventional *in situ* sensors to obtain 1-minute statistics of
surface wind speed, wind direction, air temperature, relative humidity,
barometric pressure, and rain-rate. Additional sensors may be added to
or removed from the base set of sensors depending upon the deployment
location, climate regime or programmatic needs. Additionally, sensor
types may change depending upon the climate regime of the deployment.
These changes/additions are noted in the Deployment Locations and
History section.

# Contacts

## Mentor

Michael Ritsche\
Argonne National Laboratory\
9700 South Cass Avenue\
Argonne, IL 60439\
Phone: 630-252-1554\
Fax: 630-252-5498\
E-mail: <mtritsche@anl.gov>

## Instrument Developer

> **Data Logger**\
> Campbell Scientific Inc.
>
> 815 W. 1800 N.
>
> Logan, UT 84321
>
> Phone: 801-753-2342
>
> Fax: 801-750-9540
>
> Web page: [http://www.campbellsci.com](http://www.campbellsci.com/)
>
> **Wind Monitor & Aspirated Radiation Shield**\
> R. M. Young Company
>
> 2801 Aero Park Drive
>
> Traverse City, MI 49686
>
> Phone: 231-946-3980
>
> Fax: 231-946-4772
>
> Web page: <http://www.youngusa.com/>
>
> **Temperature-Relative Humidity Probe, Digital Barometer & Present
> Weather Detector**\
> Vaisala\
> 100 Commerce Way\
> Woburn, MA 01801-1068\
> Phone: 617-933-4500\
> Fax: 617-933-8029
>
> Web page: [http://www.vaisala.com](http://www.vaisala.com/)
>
> **Rain Gauge**\
> Optical Scientific, Inc.\
> 205 Perry Parkway, Suite 14\
> Gaithsburg, MD 20877-2141\
> Phone: 301-948-6070\
> Fax: 301-948-4674

# Deployment Locations and History 

[]{#__RefHeading___Toc164237670 .anchor}**Table 1: Locations and
Sensors**

+----------------+--------+--------+----------------------------------+
| # Locatio      | *      | **End  | **Sensors**                      |
| n {#location . | *Start | Date** |                                  |
| Heading-Front} | Date** |        |                                  |
+----------------+--------+--------+----------------------------------+
| Pt. Reyes, Ca  | 02/0   | 09/1   | HMP-45D T/RH probe, 05106 Wind   |
|                | 1/2005 | 5/2005 | Monitor, PTB-220 Barometer, 815  |
|                |        |        | and 115 Optical Rain Gauge       |
+----------------+--------+--------+----------------------------------+
| Niamey, Niger  | 01/0   | 01/0   | HMP-45D T/RH probe, 05106 Wind   |
|                | 5/2006 | 7/2007 | Monitor, PTB-220 Barometer, 815  |
|                |        |        | and 115 Optical Rain Gauge,      |
|                |        |        | PWD-22 Present Weather Detector  |
+----------------+--------+--------+----------------------------------+
| Niger          | 01/0   | 12/0   | HMP-45D T/RH probe, 05106 Wind   |
| Ancillary Site | 5/2006 | 8/2006 | Monitor, PTB-220 Barometer, 815  |
| (Banizoumbou,  |        |        | and 115 Optical Rain Gauge       |
| Niger)         |        |        |                                  |
+----------------+--------+--------+----------------------------------+
| Heselbach,     | 04/0   |        | HMP-45D T/RH probe, 05106 Wond   |
| Germany        | 2/2007 |        | Monitor, PTB-220 Barometer, 815  |
|                |        |        | and 115 Optical Rain Gauge,      |
|                |        |        | PWD-22 Present Weather Detector  |
+----------------+--------+--------+----------------------------------+
| Shouxian,      | 05/1   |        | HMP-45D T/RH probe, 05106 Wind   |
| China          | 9/2008 |        | Monitor, PTB-220 Barometer, 815  |
|                |        |        | and 115 Optical Rain Gauge,      |
|                |        |        | PWD-22 Present Weather Detector  |
+----------------+--------+--------+----------------------------------+
| HFE Ancillary  | 05/2   |        | HMP-45D T/RH probe, 05106 Wind   |
| site           | 7/2008 |        | Monitor, PTB-220 Barometer, 815  |
|                |        |        | and 115 Optical Rain Gauge       |
| (Taihu, China) |        |        |                                  |
+----------------+--------+--------+----------------------------------+

# Near-Real-Time Data Plots

Near-real-time data plots can be found at the following locations:

-   <http://www.arm.gov/sites/site_inst.php?loc=fkb&facility=M>

# Data Description and Examples

## Data File Contents

### Primary Variables and Expected Uncertainty

-   [Point Reyes, California, Primary
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/pointreyes_primaryvariables.pdf)

-   [Niamey, Niger, Primary
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/niamey_primaryvariables.pdf)

-   [Niger Ancillary Site (Banizoumbou, Niger), Primary
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/nigerancillary_primaryvariables.pdf)

-   [Heselbach, Germany, Primary
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/heselbach_primaryvariables.pdf)

#### Definition of Uncertainty

This definition should probably be included in a Definitions web page,
and only linked to from here.

We define uncertainty as the range of probable maximum deviation of a
measured value from the true value within a 95% confidence interval.
Given a bias (mean) error *B* and uncorrelated random errors
characterized by a variance , the root-mean-square error (RMSE) is
defined as the vector sum of these,

$$\text{RMSE} = \left( B^{2} + s^{2} \right)^{\frac{1}{2}}$$

(*B* may be generalized to be the sum of the various contributors to the
bias and *^2^* the sum of the variances of the contributors to the
random errors). To determine the 95% confidence interval we use the
Student's *t* distribution: *t*~n;0.025~ ≈ 2, assuming the RMSE was
computed for a reasonably large ensemble. Then the *uncertainty* is
calculated as twice the RMSE.

### Secondary/Underlying Variables

This section is not applicable to this instrument.

### Diagnostic Variables

-   [Point Reyes, California, Diagnostic
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/pointreyes_diagnosticvariables.pdf)

-   [Niamey, Niger, Diagnostic
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/niamey_diagnosticvariables.pdf)

-   [Niger Ancillary Site (Banizoumbou, Niger), Diagnostic
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/nigerancillary_diagnosticvariables.pdf)

-   [Heselbach, Germany, Diagnostic
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/heselbach_diagnosticvariables.pdf)

### Data Quality Flags

-   [Point Reyes, California, Quality Control
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/pointreyes_qualitycontrolvariables.pdf)

-   [Niamey, Niger, Quality Control
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/naimey_qualitycontrolvariables.pdf)

-   [Niger Ancillary Site (Banizoumbou, Niger), Quality Control
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/nigerancillary_qualitycontrolvariables.pdf)

```{=html}
<!-- -->
```
-   [Heselbach, Germany, Quality Control
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/heselbach_qualitycontrolvariables.pdf)

### Dimension Variables

-   [Point Reyes, California, Dimension
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/pointreyes_dimensionvariables.pdf)

-   [Niamey, Niger, Dimension
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/niamey_dimensionvariables.pdf)

-   [Niger Ancillary Site (Banizoumbou, Niger), Dimension
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/nigerancillary_dimensionvariables.pdf)

```{=html}
<!-- -->
```
-   [Heselbach, Germany, Dimension
    Variables](http://www.arm.gov/publications/tech_reports/handbooks/amfinstrumentdocs/heselbach_dimensionvariables.pdf)

## Annotated Examples

This section is not applicable to this instrument.

## User Notes and Known Problems

**Induced Voltage on Wind Speed Cable Caused Offsets In Wind Speed
Data**

The marine model of the RM Young wind sensor needs twisted pair shielded
cable. The manufacturer did not originally supply the pigtail with
twisted pair shielded cable. Use of twisted pair shielded cable for the
rest of the cable run to the logger was also not specified. This caused
an induced voltage in the wind speed line from the wind direction
excitation. The induced voltage varied from sensor to sensor and
probably changed anytime the cable was replaced or parts of the wind
sensor were repaired or replaced. The induced voltage has been seen to
vary from 0.15 m/s to as much as 1.08 m/s. To complicate matters until
2006 or 2007 depending upon site, the calibration coefficients of the
wind monitors included an offset.

All deployments up to and including the Niamey deployment were affected.
The METRAD ancillary site deployed during in Banizoumbou was affected by
both the calibration offset and the induced voltage offset at different
times. This was due to an original error of not including the offset,
but then later correcting it and adding it back in. The program in the
datalogger collects the calibration information once a day. Users can
investigate the NETCDF header information to ascertain what, if any,
calibration offset has been applied to the data.

The following is a plot of the wind speed and direction data showing the
induced offset caused by the excitation voltage of the wind direction at
TWP C3. This offset does NOT include any calibration coefficient offset.

![](media/image1.png){width="5.868055555555555in"
height="3.689583333333333in"}

**Incorrectly Listed Units for Vapor Pressure in Data Object Design**

The Data Object Design incorrectly listed the units of hPa for Vapor
Pressure. When the new collection system was installed at each site (see
Table 1) the units were actually reported in kPa.

**Naming Convention of the Wind Monitor During the Pt. Reyes
Deployment**

The program was adapted from the TWP AMF MET system. These surface
meteorology systems have two wind monitors. Therefore, the naming
convention of the two wind monitors (upper and lower) was kept during
this deployment. All wind variables that are preceded with an "up" are
where the data from the single wind monitor were stored. All wind
variables that are preceded with a "lo" were filled with --9999
indicating that the data are missing. In subsequent deployments the
program was changed to reflect that there is only one wind sensor.

## Frequently Asked Questions

This section is not applicable to this instrument.

# Data Quality

## Data Quality Health and Status

Data Quality Health and Status (DQ HandS)
[http://dq.arm.gov](http://dq.arm.gov/)

NCVweb - for interactive data plotting using
<http://dq.arm.gov/ncvweb/ncvweb.cgi>

## Data Reviews by Instrument Mentor

The Instrument Mentor (Michael Ritsche) performs a number of tasks to
assure the quality of AMFMET data. Data quality control procedures for
this system are considered **mature**.

-   **QC frequency**: Weekly

-   **QC delay**: Real-time; weekly

-   **QC type**: Min/max/delta flags; graphical plots; mentor reviews

-   **Inputs**: Collected data

-   **Outputs**: Monthly Mentor Reports, DQR, BCR, ECO, PIF, DQPR (as
    needed)

-   **Reference**: None

Standard AMF MET data are subject to several levels of quality control
and quality assurance. When the data are collected each variable has
various automated QC checks that look for values outside defined
max/min/delta. Any variable outside these parameters are flagged in the
QC variable. The mentor receives weekly reports, called Data Quality
Assessment Reports (DQAR) from the DQ Office and reviews them for
problems. Any problems listed in the weekly DQAR's are checked and spot
checks are also performed to verify the DQAR's are accurate.

## Data Assessments by Site Scientist/Data Quality Office

The ARM Data Quality Office uses the Data Quality Assessment (DQA)
system to inform the ARM Site Operators, Site Scientists, and Instrument
Team members of instrument and data flow problems as well as general
data quality observations. The routine assessment reports are performed
on the most recently collected ARM data, and used with the Data Quality
Problem reports tool to initiate and track the problem resolution
process. Weekly reports are sent to the mentor describing errors
noticed, quality flags that were tripped, and any other issues that the
DQ office feel might affect data quality.

## Value-Added Procedures and Quality Measurement Experiments

Many of the scientific needs of the ARM Program are met through the
analysis and processing of existing data products into "value-added"
products or VAPs. Despite extensive instrumentation deployed at the ARM
CART sites, there will always be quantities of interest that are either
impractical or impossible to measure directly or routinely. Physical
models using ARM instrument data as inputs are implemented as VAPs and
can help fill some of the unmet measurement needs of the program.
Conversely, ARM produces some VAPs not in order to fill unmet
measurement needs, but instead to improve the quality of existing
measurements. In addition, when more than one measurement is available,
ARM also produces "best estimate" VAPs. A special class of VAP called a
Quality Measurement Experiment (QME) does not output geophysical
parameters of scientific interest. Rather, a QME adds value to the input
datastreams by providing for continuous assessment of the quality of the
input data based on internal consistency checks, comparisons between
independent similar measurements, or comparisons between measurement
with modeled results, and so forth. For more information, see the [VAPs
and QMEs](http://www.arm.gov/data/vaps_all.php) web page.

# Instrument Details

## Detailed Description

### List of Components

**Wind speed and direction sensors**: A propeller anemometer and wind
vane, R. M. Young Model 05106 Wind Monitor.

**Temperature and relative humidity sensor**: Platinum RTD and RH,
Vaisala Model HMP45D Temperature and Relative Humidity Probe.

**Barometric pressure sensor**: Digital barometer, Vaisala Model PTB220.

**Precipitation**: Optical precipitation gauge, Optical Scientific, Inc.
Model ORG-115-DA MiniOrg or ORG-815-DA MiniOrg.

**Data logger**: Campbell Scientific, Inc. Model CR23X.

### System Configuration and Measurement Methods

The AMF MET sensors are mounted on a 3-meter mast, except for the
optical rain gauge.

The wind monitor propeller anemometer produces a magnetically controlled
AC output whose frequencies are proportional to the wind speed. The Wind
Monitor direction vane drives a potentiometer, which is part of a
resistance bridge.

The Wind Monitors is mounted on a cross-arm at a height of 3 m.

The T-RH probe 4-lead, platinum resistance thermometer is part of a
resistance bridge. The Vaisala RH circuitry produces a voltage that is
proportional to the capacitance of a water vapor absorbing, thin polymer
film. The T-RH probe is mounted in a naturally aspirated R. M. Young
Model 41002 Gill Multi-plate Radiation Shield at a height of 2 m.

The barometric pressure sensor uses a silicon capacitive pressure sensor
and is housed in an enclosure along with the data logger.

The optical precipitation gauge detects scintillation of an infrared
beam caused by liquid water in the path. It is located near the tower.
The following equations are used to convert the voltage signal to a
rainrate.

For the ORG-815:

Rainrate (mm/hr) = (25\*(V^1.87^) -- 0.15

For the ORG-115:

Rainrate (mm/hr) = (20\*(V^2^) -- 0.05

The CR23X data logger measures each input once per second except for
barometric pressure, which is measured once per minute, and logs 1-min
averaged data. Vapor pressure is computed from the air temperature and
relative humidity. The data logger produces 1-min averages, minimums,
maximums, and standard deviations of wind speed, air temperature,
relative humidity, and rain rate. It also produces 1‑min vector-averaged
wind speed and direction, a 1-min standard deviation of the wind
direction computed by an algorithm, 1-min averages and standard
deviations of vapor pressure, and a reading of the barometric pressure,
logger panel temperature, and the internal supply voltage.

### Specifications

**Wind speed at 3 m**: Precision: 0.01 m/s; Uncertainty: +/-2%.

**Wind direction at 3 m**: Precision: 0.1 deg; Uncertainty: +/-5 deg.

**Air temperature at 2 m**: Precision: 0.01 C; Uncertainty: a function
of wind speed.

**Relative humidity at 2 m**: Precision: 0.1% RH; Uncertainty: +/-2.06%
RH (0% to 90% RH), +/-3.04% RH (90% to 100% RH).

**Barometric pressure at 1 m**: Precision: 0.01 hPa; Uncertainty:
+/-0.15 hPa.

**Precipitation**: Precision: 0.1 mm/hr; Uncertainty: +/-0.1 mm/hr.

**Overall Uncertainties for Primary Quantities Measured**

All AMF MET uncertainty analyses are based on manufacturer's
specifications. Manufacturers specify accuracies in several ways. Some
give absolute range of error; some give uncertainties as defined above,
while others give rms errors.

**Data Acquisition Errors**

The Campbell Scientific, Inc CR23X datalogger A-D converter accuracy is
+/- 0.025% FSR for 0 -- 40C, +/- 0.05% FSR --25 to 50C, +/- 0.075% FSR
--40 to 80C. The clock accuracy is +/- 1 minute per month --25 to 50C,
+/- 2 minutes per month --40 to 80C. The LoggerNet software checks the
clock of the logger once per day and adjusts it if it off by more than 2
seconds. The computer continuously maintains time synchronization with a
GPS based time reference using the NTPD protocol. The GPS based
reference is local to each site.

**Wind Speed**

The propeller of the wind monitor is accurate to +/- 2%. The conversion
error is negligible. The schedule of routine maintenance and sensor
verification is designed to eliminate any long-term stability error. The
sensor threshold is specified as 1 m/s.

**Wind Direction**

The sensor accuracy is specified as +/-3 deg. The A-D conversion
accuracy is equivalent to 0.7 deg over a temperature range of 0 to 40C
for a period of one year. Sensor alignment to true north has been
estimated to be accurate within +/-3 deg. The uncertainty with 95%
confidence is, therefore, approximately +/-5 deg.

**Temperature**

The accuracy of the temperature measurement is specified as ± 0.4C.
Included in this accuracy are sensor interchangeability, bridge resistor
precision, and polynomial curve fitting errors. The long-term stability
is not known. The radiation error of the naturally aspirated multi-plate
radiation is specified as ± 0.4C root mean square (rms) at 3 m/s, ± 0.7C
rms at 2 m/s, and ± 1.5C rms at 1 m/s.

The uncertainty with 95% confidence of temperature sensors in naturally
aspirated radiation shields is approximately:

  -------------- --------------------------------------------------------
  ± 0.45 C       when the wind speed is 6 m/s or greater

  ± 0.89 C       when the wind speed is 3 m/s

  ± 1.46 C       when the wind speed is 2 m/s

  ± 3.07 C       when the wind speed is 1 m/s
  -------------- --------------------------------------------------------

**Relative Humidity**

The accuracy of the sensor is specified as ± 2% RH for 0 to 90% RH, and
± 3% RH for 90 to 100% RH. Errors considered in this accuracy are
calibration uncertainty, repeatability, hysteresis, temperature
dependence, and long-term stability over a period of one year. The A/D
conversion accuracy is equivalent to ± 0.5% RH.

The uncertainty with at least 95% confidence is, therefore,

  -----------------------------------------------------------------------
  ± 2.06 % RH, 0 to 90 % RH

  ± 3.04 % RH, 90 to 100 % RH
  -----------------------------------------------------------------------

**Barometric Pressure**

+-----------------------------------+-----------------------------------+
| # Error Sour                      | **Imprecision**                   |
| ce {#error-source .Heading-Front} |                                   |
+-----------------------------------+-----------------------------------+
| Linearity                         | +/- 0.10 hPa                      |
+-----------------------------------+-----------------------------------+
| Hysteresis                        | +/- 0.03 hPa                      |
+-----------------------------------+-----------------------------------+
| Repeatability                     | +/- 0.03 hPa                      |
+-----------------------------------+-----------------------------------+
| Calibration Uncertainty           | +/- 0.15 hPa                      |
+-----------------------------------+-----------------------------------+
| Temperature Dependence            | +/- 0.1 hPa                       |
+-----------------------------------+-----------------------------------+
| Long-term Stability               | +/- 0.1 hPa                       |
+-----------------------------------+-----------------------------------+
| Accuracy at +20 C                 | +/- 0.20 hPa                      |
+-----------------------------------+-----------------------------------+
| **Total Accuracy**                | **+/- 0.25 hpa**                  |
+-----------------------------------+-----------------------------------+

**Precipitation/Rainfall Rate**

The Optical raingauge has an uncertainty of +/-0.1 mm/hr. The ORG always
has a voltage level output. Programming allows the datalogger to
disregard voltage values less than the threshold recommended by the
manufacturer (85mV). Since the ORG is sampled at 1Hz and the data is
averaged to a minute it is possible that rain rates as small as 0.002
mm/hr can be reported (0.1mm/hr divided by 60 seconds).

## Theory of Operation

Each of the primary measurements of wind speed, wind direction, air
temperature, relative humidity, barometric pressure, and rate of
rainfall are intended to represent self-standing data streams that can
be used independently or in combinations. The theory of operation of
each of these sensors is similar to that for sensors typically used in
other conventional surface meteorological stations. Some details can be
found under *System Configuration and Measurement Methods* but further,
greatly detailed description of theory of operation is not considered
necessary for effective use of the data for these rather common types of
measurements. The instrument mentor or the manufacturers can be
contacted for further information.

## Calibration

### Theory

The AMF MET is not calibrated as a system. The sensors and the data
logger (which includes the A-D converter) are calibrated separately. All
systems are installed using components that have a current calibration.
Site personnel check the sensor and data logger calibrations in the
field by comparison to calibrated references. Any sensor or data logger
that fails a field check is returned to the manufacturer for
recalibration. The Wind Monitors are returned to the manufacturer for
recalibration after two years of use.

### Procedures

Wind speed calibration is checked by rotating the propeller shaft at a
series of fixed rpm's using an R. M. Young Model 18810 Anemometer Drive.
The reported wind speeds are compared to a table of expected values and
tolerances. If the reported wind speeds are outside the tolerances for
any rate of rotation, the sensor is replaced by one with a current
calibration.

Wind direction calibration checks are done by using a vane angle fixture
R. M. Young Model 18212 to position the vane at a series of angles. The
reported wind directions are compared to the expected values. If any
direction is in error by more than 5 degrees, one with a current
calibration replaces the sensor. Air temperature and relative humidity
calibrations are checked by comparison with a reference Vaisala Model
HMI31 Digital Relative Humidity and Temperature Meter and HMP35 Probe
and a YSI 4600 Precision Thermometer. If the reported temperature and
relative humidity vary by more than the sensor uncertainty from the
reference, one with a current calibration replaces the probe.

Barometric pressure calibration is checked by comparison with a
reference Vaisala PA-11 Barometer. If the reported pressure varies by
more than the sensor uncertainty from the reference, one with a current
calibration replaces the sensor.

The data loggers are sent back to the manufacturer every two years for
calibration checks on the internal clock, Analog to digital converters
and the internal multiplexers. Removed units are replaced by loggers
with a current calibration.

### History

## Operation and Maintenance

### User Manual

This section is not applicable to this instrument.

### Routine and Corrective Maintenance Documentation

See the following links:

-   <http://www.twppo.lanl.gov/internal/pages/operations_mobile_niger.html>

### Software Documentation

-   [http://science.arm.gov/tool/dod/showdod.php?Inst=AMF
    MET](http://science.arm.gov/tool/dod/showdod.php?Inst=smet).

### Additional Documentation

-   <http://www.twppo.lanl.gov/internal/pages/operations.html>.

## Glossary

Barometric pressure - Local station pressure measured at the station at
a height of 1 m.

Precipitation - All forms of water meteors.

Relative humidity - Percentage of saturated vapor pressure at the
specified temperature.

Vector-averaged wind speed - Wind speed computed as the vector sum of
the orthogonal u and v components that are computed for each one-second
sample of wind speed and direction. The wind directions reported by the
AMF are determined from the vector-averaged winds.

Wind Monitor - Trade name for R. M. Young propeller anemometer and wind
vane.

Also see the [ARM Glossary](http://www.arm.gov/about/glossary.stm).

## Acronyms

A-D: Analog to Digital converter

RH: Relative Humidity

SGP: Southern Great Plains

SMOS: Surface Meteorological Observation System

T-RH: Temperature-Relative Humidity

Also see the [ARM Acronyms and
Abbreviations](http://www.arm.gov/about/acronyms.stm).

## Citable References

None.