#  **ICE HAZARD TEAM REPORT**

## CEOS/IGOS DISASTER MANAGEMENT SUPPORT PROJECT

### Executive Summary

This purpose of this report is to identify requirements and review the
current and projected utility of Earth Observation (EO) space technology
as applied to the detection, mapping and management of ice hazards. This
study was developed under the auspices of the Disaster Management
Support Project (DMSP) as part of the Integrated Global Observing
Strategy (IGOS) of the Committee on Earth Observation Satellites (CEOS).
This document was prepared by an international working group composed of
representatives with experience in remote sensing as applied in the
production of operational ice guidance products and services.

It is well known that sea ice and icebergs pose a serious hazard to
shipping and other maritime activities in the polar regions. The role of
EOS data in operational ice monitoring is well documented and has grown
in importance over the years. EOS data from visible/infrared sensors are
readably available to all ice services but are useful only under
cloud-free conditions. Passive microwave sensors can penetrate cloud
cover but their effectiveness in ice monitoring is limited by coarse
resolution. Active microwave sensors such as SAR's are ideal for ice
mapping because of their high resolution, all-weather, wide swath ice
detection capability. Investigations have also shown that these data are
also valuable in their ability to quantify other ice parameters such as
ice type (stage of development), ice topography and presence of open
water or thin ice openings within the sea ice pack. Sea ice guidance
products derived in real-time from these data are used operationally to
ensure safety of navigation of non-ice strengthened vessels, maximize
time and fuel savings of icebreaker lead convoys and protect life and
property associated with human activities on the ice. In contrast, the
utility of EOS observations for iceberg detection is considered limited
using presently available sensors. Space-borne SAR sensors can be
effective in depicting the location and size of icebergs but only under
low surface wind speed conditions.

In the future, new and updated EOS sensors provide great promise for
improving the applications of sea ice mapping and iceberg detection.
Data from multi-spectral visible/infrared radiometers and scatterometers
can be used to generate automated sea ice maps. SAR satellites with
right/left looking beam steering, multiple polarization modes and
enhanced downlink capabilities will provide more valuable data in a
shorter period of time to the end user. The coincident collection of EOS
data from multiple instruments "fused" with ancillary environmental data
can be used to resolve ambiguities and eliminate biases in conventional,
single sensor algorithms. Data policies must exist for easy and rapid
access to EOS data for ice hazard detection and monitoring. Lastly,
collaborative efforts are needed between all the national ice services
to ensure that EOS data are shared, that ice products are issued in
standard formats and most importantly that customers are educated on the
strengths, weaknesses and value of EOS data and Ice Hazard products.

**Introduction**

#### Sixteen nations, including Canada, China, Denmark, Estonia, Finland, Germany, Iceland, Japan, Latvia, Lithuania, Netherlands, Norway, Poland, the Russian Federation, Sweden and the United States operate national ice services that support shipping and other maritime activities in ice encumbered waters. From 1920 to the early 1950's, "in-situ" visual ice observations from coastal stations, transiting ships and aircraft patrols represented the primary source of data on sea ice conditions and the location of icebergs. The paucity of information made available by these collection methods and the serious hazard posed by glacial ice to vessel operations gained international recognition and notoriety with the sinking of the TITANTIC on April 14, 1912. As a result of this accident, the USCG International Ice Patrol (IIP) was formed to provide iceberg detection and warning services to vessels operating in the North Atlantic shipping lanes. Similarly, interest in many nations to develop more accurate methods for the detection, monitoring and forecasting of sea ice did not occur until there were significant incidents that threatened the safety of navigation and life and property at sea.

####  In 1951, operating under the code name *Operation Bluejay,* 30 ships of a 33 U.S. Navy vessel convoy were severely damaged while attempting to navigate along the west coast of Greenland to establish a Distant Early Warning station and air base at Thule, Greenland (McDowell, 1990). In 1952, as a direct result of this accident, the U.S. Navy established a formal sea ice program. Outside Russia, most national ice services at this time were fledgling programs that needed to collect information to build their knowledge on sea ice characteristics and behavior. Beginning in the early 1960's, this capability to collect data was enhanced when the Canadian Ice Service (CIS) introduced the use of search radars on ice reconnaissance aircraft (Bertoia et al, 1998). These radars provided, for the first time, a long-range, cloud independent capability to detect ice. Unfortunately, these early instruments were forward-looking, non-imaging sweep radars that were useful only in the accurate measurement of range and bearing to the ice edge. 

#### Due to limited range and expense, aerial reconnaissance was typically flown only in support of specific vessel operations. Knowledge on the overall extent, thickness and behavior of the polar ice cover in both hemispheres was viewed as incomplete thus posing a continual hazard to vessel operations. It was during the 1960's that sea ice detection and monitoring entered a new era of remote sensing with the launch weather satellites by the United States. The usefulness of "pictures" taken by vidicon cameras for gross ice mapping was recognized immediately after the launch of the first TIROS research and development satellite in 1960 (Wark and Popham, 1962). By the early 1970's, improvements in satellite technology allowed for the real-time use of these data for operational ice mapping. NOAA-2 (launched in October, 1972) carried a dual channel Very High Resolution Radiometer (VHRR) that provided visual and thermal imagery via direct global and local read-out. The NASA research satellite, NIMBUS-5 (launched in December, 1972) included an Electrically Scanning Microwave Radiometer (ESMR) that provided coarse resolution, all-weather, passive microwave data. These data, coupled with traditional data sources, allowed the U.S. National Ice Center (NIC) to initiate their weekly global ice mapping program of all Arctic and Antarctic seas. 

#### In the early 1970's, improvements in radar technology resulted in the deployment and use of real aperture Side‑Looking Airborne Radars (SLAR) on patrol aircraft. Several national ice services used these SLAR data to extend the range of aircraft providing traditional visual observations and to complement the visual, thermal and passive microwave imagery received from satellites. In June 1978, the benefits of merging rapid advancements in radar technology and satellites were seen in the launch of the NASA research satellite, SEASAT. SEASAT was the first satellite dedicated to use active microwave sensors for ocean observation. Although limited to only 105 days in orbit, SEASAT provided high resolution images which confirmed that a space-borne Synthetic Aperture Radar (SAR) can be a powerful tool in ice detection and mapping (Teleki et al, 1979). 

#### Today, Earth Observation Satellites (EOS) are used almost exclusively to provide operational information on the extent, coverage and thickness of sea/lake ice. In demonstration projects, EOS data are now being used to detect, forecast and assess the damage of destructive river ice break-up and ice jams. Additionally, EOS data are being used for research purposes by the U.S. Coast Guard (USCG) International Ice Patrol (IIP) to detect and map icebergs in the North Atlantic.

### 

### General Application Description

#### 

#### The requirement for the detection, mitigation and management of the potential hazard posed by ice originated with early 19^th^ and 20^th^ century polar exploration. Vessel expeditions attempting to find and exploit the Northwest Passage, the Russian Northern Sea Route or the resources found in or beneath the frozen waters of the Arctic and Antarctic were often damaged, beset or destroyed by sea ice. Today, the operational detection of sea ice, icebergs and river/lake ice is vital to ensuring the safety of vessel operations and the commercial viability of associated industries such as marine transportation, fishing, oil exploration and tourism. National governments are also interested in these data to support components of national defense and scientific research programs. Local interest is typically centered on the effect a heavy ice cover has on local economies. For example, native and indigenous people often use unstable shorefast ice as platforms for marine mammal hunts. Additionally, severe ice conditions like those observed along the U.S. east coast (e.g. Chesapeake Bay) in the winter of 1976-77 (Foster, 1982) can cause a disruption of maritime fuel oil deliveries, the closure of fishing areas and extensive infrastructure damage such as loss of coastal navigational aides and docking facilities. 

#### Specific user requirements for ice information can often be quite diverse depending on the user application or the capabilities of a vessel. For example, non-ice strengthened vessels require timely ice edge and iceberg limit information in order to plan their routes to avoid all known ice. For example, highly vulnerable crab and fishing ships operate directly adjacent to the rapidly changing ice edge in the Bering Sea during the volatile winter weather months. In contrast, vessels with hull strengthening and some degree of ice capability require information detailing ice concentration distribution and associated ice thickness. This information can be used to exploit the ice cover by planning routes more effectively. Even the most capable icebreakers use information on openings in the ice (e.g. leads and polynyas) to choose the path of least resistance in order to achieve greatest fuel economy. Additionally, submarines operating under the ice require ice opening and ice thickness information to assist in surfacing within the ice and in the successful transit of shallow ice-covered waterways. 

#### In the polar regions, sea ice varies both spatially and temporally due to the high variability in the environmental processes that form, advect and decay the ice. All international ice service organizations produce ice analyses describing current sea ice conditions. The production of these analyses is dependent almost exclusively on the availability and use of EOS data. Although an accurate spatial depiction of ice conditions is important to the mariner, temporal accuracy is generally of much greater importance. Ideally, vessels at sea prefer to receive high-resolution satellite images that are 3-6 hours old and have been interpreted to provide the necessary information to avoid or exploit the ice. Sea ice parameters required by users at sea include the location of the ice edge, concentration distribution, stage of development, floe size, amount of pressure ridging or topography, location and orientation of ice openings, degree of ice compaction and divergence and stage of decay during the summer melt season. Additionally, information on the location and size of icebergs is essential in waters located near or downstream of ice shelves and glaciers. 

Mitigation and preparedness for hazards posed by ice requires not only
accurate ice analyses (describing current ice conditions) but also short
(less than 72 hour) and long-term (168 hour to monthly/seasonal) ice
forecasts. Most national ice services have developed and are using
coupled ice/ocean/atmospheric models to predict short-term changes the
movement, formation and ablation of ice and icebergs. Long-term monthly
and seasonal forecasts are important to mission planning particularly
the prediction of the opening and closing of well-known navigational
chokepoints (e.g Bering strait, north slope of Alaska east to Prudoe Bay
and various locations along the Russian Northern Sea Route).
Additionally, to effectively describe the sea ice cover, nations with
Arctic interests have developed a set of common terminology to describe
the nature of sea ice and its behavior. This compendium of
internationally accepted ice terminology and symbology was adopted by
the World Meteorological Organization (WMO) in 1968. This terminology
was compiled into a volume including illustrative sea ice and iceberg
photographs and was issued as a publication entitled *WMO Sea-ice
Nomenclature* (Publication No. 259) in 1970. This publication remains
the accepted terminology and symbology for sea ice mapping and the
identification of icebergs today.

**Specific Application Description**

#### 

#### a) [Hazard Type]{.underline}: Sea Ice/Lake Ice Cover

####  [User Level]{.underline}: International, Regional, National, State

[Disaster Mgmt Category]{.underline}: Mitigation/Preparedness
(surveillance, detection, warning)

[Operational Status]{.underline}: Operational over all ice-covered seas

The majority of national ice services presently produce sea ice/lake ice
guidance products in a digital workstation environment using data from
polar orbiting satellites, ship/shore station reports, drifting buoys,
meteorological guidance products, ice model predictions and on a limited
basis, aerial ice reconnaissance flights. Among the presently available
operational data sources, satellite imagery now constitutes the largest
percentage of information received and integrated into global ice
analysis products. Traditional data collection methods, such as visual
aerial ice reconnaissance, require extensive pre-planning, are limited
in geographic scope and are generally not cost effective. Real-time
satellite data in the visible, infrared and microwave bands of the
spectrum are now used extensively, and are an essential requirement for
ice services to ensure safety of navigation and protect life and
property in ice-covered seas and lakes.

Today's commonly used optical, thermal, passive microwave and active
radar satellite systems possess characteristic strengths and weaknesses
with respect to spatial resolution, detection capability and
classification accuracy of the sea and lake ice cover. Additionally, the
orbit of the satellite directly effects the geographical coverage and
revisit time. Meteorological satellites fall into two categories:
Geostationary Environmental Satellites (GOES) and Polar Environmental
Satellites (POES). Orbiting at an altitude of 35,800 km and at the same
rate as the earth, GOES provide superior temporal resolution with images
available every 15-30 minutes. Thus, visible and infrared imagery from
GOES (GOES-8, GOES-10, METEOSAT and GMS) are used by several national
ice services to monitor ice in lower latitude seas and lakes. Unlike the
polar regions, these lower latitudes do not suffer from persistent
illumination problems that can restrict the use of visible imagery. In
North American areas, this is important because the GOES 8/10 Imager
instrument consists of a visible and infrared channel that have spatial
resolutions of 1 km and 4 km, respectively. The latter does not provide
data of sufficient spatial resolution to do detailed ice mapping.

In terms of geographic coverage in the polar regions, POES is the
preferred source for visible and infrared data for ice monitoring. The
National Oceanic Atmospheric Administration (NOAA) and Defense
Meteorological Satellite Program (DMSP) POES operate at an altitude of
approximately 830 km and provide coverage every 102 minutes. With
multiple satellites operating at any one time, many images are available
each day in the polar regions. With five or six (NOAA-15) spectral
channels and a 1.1 km spatial resolution (at nadir), visible and
infrared imagery from the Advanced Very High Resolution Radiometer
(AVHRR) is an effective tool for ice mapping. AVHRR imagery can be used
to accurately estimate the location of the ice edge, ice concentration,
ice stage of development and physical surface temperature (Emery et al,
1991, 1994; Massom and Comiso, 1994). In contrast, the DMSP Operational
Linescan System (OLS) provides visible and thermal data from only two
spectral channels but at improved 0.55 km spatial resolution that is
consistent across the width of the swath. Additionally, the OLS visible
channel often produces images with better sea ice and water contrast
than either AVHRR channels 1 or 2. This effect occurs because the broad
spectral wavelength of the OLS suppresses optically thin clouds when
compared to surface features (Isaacs and Barnes, 1987). Creating
bispectral composite AVHRR images based on the difference between the
visible and near-infrared channels (Lee et al,1993) can generate a
similar but improved effect.

Unfortunately, arithmetic image manipulation functions are limited in
their effectiveness when extensive, heavy cloud cover is present.
Climatologically, cloud cover may be present over 80% of the time over
the Arctic ice pack and the Marginal Ice Zone (MIZ) during the important
summer shipping months (Benner et al, 1992). Visible and infrared data
also require considerable expertise in manual image interpretation
techniques that use texture, tone, shape and persistence to separate ice
from clouds and water. Additionally, due to the fact that thermal
contrasts between water and ice are not as large as reflectance (albedo)
differences, infrared imagery generally requires image enhancement.

Passive microwave sensors are not limited by clouds or illumination
because the measured brightness temperature (Tb) is a function that
depends more directly upon the geophysical parameters of the sea ice
(Comiso, 1983; Cavalieri et al., 1984; Kwok et al., 1992 Kwok and
Cunnigham, 1994 and Fung, 1994). The Special Sensor Microwave Imager
(SSM/I), a multi-channel microwave radiometer onboard the DMSP
satellites, can be used to generate global ice concentration and first
year/multiyear ice classification products (Cavalieri, 1994; Kwok et
al., 1996). Many national ice services employ algorithms using some
combination of the 19 and 37 GHz channels to produce 25 km gridded
mosaic ice maps. These products assist in the general delineation of the
ice edge and inner pack concentrations in cloud-covered areas.
Unfortunately, the coarse resolution precludes detailed analyses and
great care must be taken to account for contamination errors induced by
surface meltwater and coastlines.

Similar to passive microwave, Synthetic Aperture Radar (SAR) satellite
systems (Canadian RADARSAT; European ERS-2; Japanese JERS (recently
failed) and Russian ALMAZ) are not effected by clouds or darkness. SAR
instruments use active microwave pulses to collect high spatial
resolution (10-100 meter) data over varying swaths at fixed or
selectable incidence angles. ERS-2 is presently being used by several
European ice services to routinely map and monitor ice in portions of
the Baltic Sea/Bay of Bothnia. In general though, the ERS is limited in
its effectiveness to do large-scale ice mapping because the single
frequency/single polarization SAR has a fixed incidence angle and
relatively narrow SCANSAR swath width (100km). In comparison, RADARSAT's
C-band SAR has a steerable beam (thus variable incidence angle) and a
SCANSAR mode that provides data with a 100 m spatial resolution and a
500 km wide swath. These characteristics back-up the claim that RADARSAT
is the world's first radar satellite specifically designed to maximize
its usefulness for sea ice monitoring.

RADARSAT's wide swath provides the high repeat imaging capability that
can image every point on the earth's surface north of 65N latitude at
least once every day. North of 45N, the entire globe can be covered in 3
days or less. Three Command Data Acquisition (CDA) stations (Fairbanks,
Alaska; Gatineau, Canada; and Tromso, Norway) provide near complete
Arctic coverage. Arctic images are typically quick-look processed and
transferred via dedicated communications lines or Internet to national
ice centers within three hours of acquisition. No SAR imagery are
routinely integrated into ice analyses of the Antarctic seas because of
tape recorder limitations and data delivery delays associated with
communications to/from the McMurdo ground receiving station.

The Russian OKEAN-01 polar orbiting satellite series is unique for ice
mapping because it carries three intermediate resolution instruments
that have the capability of simultaneously collecting passive microwave,
Real Aperture Radar (RAR) and optical imagery. The passive microwave
instrument (36 GHz horizontal), X-band RAR and single channel
(0.8-1.1um) optical sensor provides imagery with 15km, 1.2km and 1.0km
spatial resolution, respectively. Ice maps produced using simultaneously
acquired passive and active microwave OKEAN data have compared favorably
to concurrent SSM/I and AVHRR ice classifications in several case
studies of northern Russian seas (Belchansky G. et al, 2000).

#### b) [Hazard Type]{.underline}: Icebergs

####  [User Level]{.underline}: International, Regional, National

[Disaster Mgmt Category]{.underline}: Mitigation/Preparedness
(surveillance, detection, warning)

[Operational Status]{.underline}: Operational in North Atlantic and
Antarctic

Icebergs are masses of freshwater ice that have broken off or calved
from the edges of glaciers whose termini make contact with the sea or
that have resulted from the fragmentation of larger icebergs already
afloat (Loset et al, 1993.) The rate of production of icebergs is highly
variable, being influenced by glacier velocity, degree of crevassing,
ocean waves, swell and tidal variations, temperature and sea ice extent
( Lost et al, 1993; Vinje, 1989). Maximum production tends to occur in
the summer when sea ice extent is at a minimum, temperature (and the
glaciers) are at the warmest and wave action is most intense (Vinje,
1989). Icebergs are classified on the basis of size and shape. The WMO
(1970) system defines three size classes (icebergs, bergy bits and
growlers) and six shape classes (tabular, dome, sloping, pinnacled,
weathered and glacier). Presently, operational data collection by the
International Ice Patrol is limited to visual observations and SLAR data
from planned aerial reconnaissance flights and opportunistic ship
reports. Attempts have been made to include EOS data to give synoptic
views of large areas. Unfortunately, until recently, the utility of
satellite observations (visible, infrared and passive microwave) were
considered limited due to an inability to penetrate cloud cover and
darkness, inadequate spatial resolution and/or poor revisit times.
Research activities are presently evaluating the effectiveness of
space-borne SAR's to detect icebergs.

Active microwave systems provide two-dimensional images of variations in
backscatter that are difficult to interpret when compared to
visible/infrared imagery. First, imaging radars are subject to speckle
noise. This noise can be reduced by spatial averaging of the image
resulting in a higher signal/noise ratio but at the expense of spatial
resolution (Rees, 1990). High speckle noise can inhibit the
effectiveness of detecting small icebergs and often results in a
significant number of false alarms (Willis et al, 1996). Backscatter
differences are the result of surface and volume scattering of the
target (in this case, an iceberg) and surrounding medium (sea water or
sea ice). High wind speeds and resulting rough seas can mask the signal
from an iceberg (Steffen et al, 1992a). In calmer conditions, icebergs
often give a bright target return with neighboring radar "shadow" that
can be used to estimate iceberg volume or size (Larsen et al, 1978).

Iceberg detection algorithms using the ERS-1 SAR (C-band, VV polarized
and 23 degree fixed incidence angle) demonstrated that 100 meter data
could be used to detect Arctic and North Atlantic icebergs with great
success under "optimal conditions" (Willis et al, 1996). Optimal
conditions are those with speeds below 5 meters/sec and no sea ice or
land within the image. At 100 meter spatial resolution, ERS-1 imagery
detected 100% of large icebergs (120-200m width), 90% of medium size
icebergs (60-120m width) and approximately 40% of small icebergs (15-60m
width) (Willis et al, 1996). It was noted however that the SAR's iceberg
detection capabilities decreased significantly with increasing wind
speeds. Willis et al (1996) stated that iceberg detection using
space-borne SAR's would be most effective with the following preferred
radar parameters: as high frequency instrument as possible, horizontal
polarization and large incidence angles. With this knowledge, the IIP
and CIS are presently conducting research evaluating the utility of
Radarsat SAR data for iceberg detection. Radarsat operates a C-band
instrument, HH polarization, wide swath widths (up to 500km), variable
incidence angles (20-60 degrees) and almost daily coverage in the high
latitudes.

As described above, iceberg detection using EOS data is heavily
dependent on iceberg size and surrounding environmental conditions. In
the southern hemisphere, large tabular icebergs routinely calve from the
numerous ice shelves in the Antarctic. Due to the enormous numbers of
icebergs in this region and the absence of "in-situ" ground truth
information, only very large icebergs (typically exceeding 10 nautical
miles along the long axis) are detected and routinely mapped. In most
cases, these icebergs are presently detected and tracked using AVHRR and
OLS visible/infrared imagery. Large iceberg calving events are typically
detected by the significant changes in the ice shelf boundaries. Once
within the sea ice pack, albedo similarities between icebergs and sea
ice make detection and tracking difficult. Under certain conditions,
visible and infrared imagery do show characteristic iceberg signatures.
These signatures include leeward open water areas resulting from when
iceberg movements are at a different velocity or direction than that of
the surrounding sea ice and surface temperature differences
distinguishing the thicker bergs (up to 250m in freeboard) from the
surrounding sea ice pack. The former effect is based upon the findings
that larger icebergs with deep keel drafts are driven primarily by ocean
currents (Gustajtis, 1979) vice surface winds for sea ice.

#### c) [Hazard Type]{.underline}: Shorefast, Lake and River Ice Break-up

####  [User Level]{.underline}: International, Regional, National 

[Disaster Mgmt Category]{.underline}: Mitigation/Preparedness/Relief
(surveillance, detection,

> Warning and damage assessment)

[Operational Status]{.underline}: Research with demonstration status in
select Arctic coastal

> areas.

#### As described in the previous sea/lake ice section, data from EO satellites are critical for sea ice/lake ice hazard monitoring. Shorefast ice is defined as sea/freshwater ice that is attached to the coastline. River ice is a type of shorefast ice that forms in many estuarine systems in the polar regions. Human activities, such as Great Lakes ice fishing and whale hunts by Alaskan indigenous people, use the stable lake or shorefast ice as a "platform" to conduct these endeavors. Unpredicted break-up of these ice types can threaten the safety of lives and property. In contrast, river ice break-up poses a hazard but typically only to vessels operating in the river. River break-up is usually an event of short duration but characterized by hazardous destructive forces. Human settlements are typically threatened only by associated flooding resulting from ice jams. 

#### Visible and infrared EOS data are effective in providing general information on the location of shorefast boundaries. The shear zone caused by moving pack ice adjacent the fixed shorefast ice is often quite distinct in AVHRR/OLS imagery. Thickness information must however be obtained from "in-situ" measurements (ice cores) or estimated by freezing degree day (air temperature) models. Space-borne SAR systems are the preferred data source to mitigate and assess the effects of this ice hazard. SAR imagery is high resolution and not effected by clouds and darkness. Thus, these data are ideal for characterizing and monitoring the shorefast, lake and river ice. Unfortunately, what is really needed is a better understanding of the environmental processes that cause the break-up of this ice. Research highlighting case studies that couple EOS data with "in-situ" meteorological/oceanographic observations are needed to enhance the preparedness and capabilities of ice services to issue accurate forecasts. The NOAA Alaskan Demonstration Project is presently making high resolution Radarsat SAR-based products coincident ancillary environmental data available to state regulatory agencies (Alaska River Forecast Office) responsible for monitoring ice break-up in the Yukon River system (Lunsford, 1998). 

**Products and Services**

a\) [National Ice Information Services]{.underline}

A detailed description of all sixteen national ice services (Appendix B)
can be found in WMO publication No. 574 "*Sea Ice Services in the
World".* This publication is available from the WMO/IOC Global Digital
Sea Ice Data bank website (http://www.aari.nw.ru/gdsidb_2.html). In
general, national sea ice services provide a diverse suite of digital
and analog ice guidance products in support of mission planning,
operations and research in the ice-covered seas in the northern and
southern hemispheres. In the United States, this service is extended to
the Great Lakes. Routine ice guidance products include regional and
local-scale ice analyses, annotated satellite imagery, short and
long-term ice forecasts, legacy ice information, ice climatologies and
iceberg reports. Ice analyses typically document the date and time of
data used in each analyses in a metadata narrative. Ice product formats
include a) paper charts, b) simple electronic charts in GIF or Adobe
Acrobat (.gif, .pdf) formats and c) Geographic Information System (GIS)
compatible (e.g. ESRI ARC/INFO .e00 export format) coverages.
International standards for archival include the WMO digital standard
for Sea Ice in GRIDed (SIGRID, SIGRID-2) formats. Almost all ice
analysis charts are labeled using the World Meteorological Organization
(WMO) international sea ice symbology. Additionally, many international
organizations also provide services available via special request. These
services include Optimum Track Ship Routing (OTSR) recommendations,
pre-sail ship briefings, aerial ice reconnaissance and ship rider
support.

Information on North Atlantic icebergs is provided daily by the USCG
IIP. This support focuses specifically on identifying the southern limit
of icebergs in the North Atlantic/Grand Banks region of Newfoundland.
During the iceberg season (Feb-Aug), the IIP distributes information on
the southern extent of all known icebergs every 12 hours. Size and time
of sighting for all reported icebergs are routinely entered into an
iceberg forecast model. Initialized daily with surface wind and ocean
current information, the Berg Analysis Prediction Systems (BAPS) model
is used to predict iceberg drift and estimated rates of deterioration.
Model output is critical in predicting movement and longevity of
icebergs in North Atlantic shipping lanes.

b\) [User Types]{.underline}

The table below lists the specific ice hazard applications and
subsequent user communities that have been identified for EOS data and
resulting ice guidance products.

##### 

+------------------+------------------+-------------------+-----------+
| #                | ##### User Level | ##### Category    | #         |
| #### Application |                  |                   | #### Acti |
|                  |                  |                   | on Status |
+------------------+------------------+-------------------+-----------+
| ##### Sea and    | ##### Internat   | ##### Mitigat     | ##### Op  |
| Lake Ice Detecti | ional, National, | ion, Preparedness | erational |
| on for Avoidance |  Regional, State |                   |           |
+------------------+------------------+-------------------+-----------+
| ##### Se         | ##### Internat   | ##### Mitigat     | ##### Op  |
| a and Lake Ice C | ional, National, | ion, Preparedness | erational |
| haracterization  |  Regional, State |                   |           |
| for Exploitation |                  |                   |           |
+------------------+------------------+-------------------+-----------+
| #####            | ##### Interna    | #####             | ##### Op  |
| Beset Vessel in  | tional, National | Mitigation, Prepa | erational |
| Sea and Lake Ice |                  | redness, Response |           |
+------------------+------------------+-------------------+-----------+
| #####            | ##### Interna    | ##### Mitigat     | ##### Ope |
|  Iceberg Detecti | tional, National | ion, Preparedness | rational, |
| on for Avoidance |                  |                   |  Research |
+------------------+------------------+-------------------+-----------+
| ##### Landf      | ##               | ##### Mitigati    | #         |
| ast, Lake and Ri | ### State, Local | on, Preparedness, | #### Demo |
| ver Ice Break-up |                  |  Response, Relief | nstration |
|                  |                  |                   |  Research |
+------------------+------------------+-------------------+-----------+

##### 

##### 

##### Sea Ice Detection for Avoidance

The majority of users interested in real-time EOS data and operational
sea ice products have the basic requirement to avoid sea ice. National
governments that have military or government research vessels operating
near or in ice-covered waters are users of these data. Knowledge of the
exact position of an ice edge is critical to a submarine patrolling
underwater but navigating with a periscope. When under the ice,
submarines need information on pressure ridging and associated keel
depths. Non-ice strengthened government research vessels conducting
ocean surveys will in most cases attempt to totally avoid the ice.
Similarly, federal and state interest also exists in non-reinforced
vessels that are part of the marine transportation, fishing, oil
exploration and tourism industries.

##### Sea Ice Characterization for Exploitation

Knowledge on the characteristics of the sea ice cover is important to
both the operational and scientific research communities. National
interest lies in the operation of military vessels (e.g. submarines),
Government owned icebreakers (e.g. Canada, Finland, Germany, Japan,
Russia, Sweden) and ice strengthened research vessels. Icebreaker led
convoys want to know the optimum track through ice to maximize time and
fuel savings. Many commercial industries have ice-strengthened cargo
vessels with the same need for information to exploit the ice cover. For
example, along Russia's Northern Sea Route Norilsk-class cargo vessels
are capable of maintaining continuous progress through one meter of
first-year ice but must avoid areas of high ice concentration under
pressure or those dominated by thicker multiyear ice (Brigham, 1991).
Although not used specifically for exploitation purposes, other users of
sea ice extent and coverage information include the international
scientific community interested in long-term climate monitoring. Climate
models suggest that the Arctic environment is particularly sensitive to
global climate change and that sea ice (extent and thickness) is the one
geophysical variable that is most sensitive to climate variability
(Wadhams, 1994). Accurate and complete EOS-derived records of sea ice
are recognized as being extremely important to scientific research
(Parkinson et al, 1987).

###### Beset Vessels in Sea Ice

Sea ice information intended to assist in the freeing of beset vessels
typically receives international and national attention. Vessels that
become beset in ice are typically icebreakers or ice-strengthened
research vessels operating in the high Arctic or Antarctic ice packs. In
the fall of 1983, for example, 15 cargo vessels and several icebreakers
that were part of a Russian convoy transiting the Northern Sea Route
were beset for weeks in the Chukchi Sea (Brigham, 1991). To assist these
vessels in distress, national ice services are often called upon to
assist their own vessels and those of other countries that become stuck
in the ice. In 1997, the National Ice Center ordered Radarsat SAR
imagery to assist the Argentine icebreaker, the ALMIRANTE IRIZAR that
was stuck in the ice of the Weddell Sea near Antarctica.

##### Iceberg Detection for Avoidance

The basic premise and mission of the IIP is to provide information on
icebergs to protect vessels by ensuring safety of navigation in the
North Atlantic. The IIP was formed by international mandate and is
jointly funded by many countries with marine shipping interests.
Specific national interest in icebergs is more elevated in those
countries whose waters are more populated by icebergs. These countries
include Canada (Baffin Bay, Newfoundland areas), Denmark (East and West
Greenland waters), Russia (Barents Sea) and the United States (IIP area
and Prince William Sound, Alaska). The increasing demand for
hydrocarbons and other earth resources have stimulated interest and
activity in many of these polar seas. Icebergs of all sizes pose a
hazard to shipping, oil exploration and extraction activities. Other
users of iceberg information include the international scientific
community interested in long-term climate monitoring. Rates of iceberg
production and distribution characteristics have been suggested as
indicators of variations in the global climate since the polar regions
are particularly susceptible to the effects of climate change (Brown et
al, 1982).

##### Shorefast, Lake and River Ice Break-up

Users of these data are almost always state agencies and local
communities. River ice break-up (like the Yukon River in Alaska) are
monitored at the state level but can be elevated to federal agencies
(e.g. USCG) when navigation aides for the waterways are destroyed.
Fishing and hunting expeditions by local communities need information on
shorefast and lake ice break-up. The user class in this hazard may also
transition when individuals do become stranded on drifting ice. Local
governments in many northern communities (like the North Slope Bureau in
Pt. Barrow, Alaska) can provide the required coordination and resources
for search and rescue efforts (ARCUS, 1999). Without these local
resources, state or federal agencies may be called on to assist.

[c) End User Requirements]{.underline}

#### As previously described, the operational detection of sea ice, icebergs and river/lake ice is vital to ensuring the safety of vessel operations and the commercial viability of the growing number of industries with activities in the polar regions. End user requirements for ice hazard information are quite diverse mainly due to the variability of applications. Spatial and temporal resolution of EOS data and associated ice guidance products are importance to vessels that wish to avoid or exploit the ice. SAR imagery with its high resolution, wide swath, frequent revisit and all-weather capabilities is now the data of choice for many ice hazard users. Ice parameters of most frequent interest to vessels at sea include the location and size of icebergs, the location of the sea ice edge, concentration distribution, stage of development, floe size and location and orientation of openings in the sea ice pack. Other developing applications require information on the extent of landfast, ice motion, amount of sea ice pressure ridging or topography, degree of ice compaction and the stage of decay during the summer melt season. 

#### Generally, a ship's captain prefers to receive detailed, tactical-scale graphics or interpreted imagery rather than raw satellite images. This preference is based on the fact that expert ice analysts are found at the various national ice centers and generally not aboard ships. The greatest challenge to most national ice centers is to process the EOS data, interpret it and deliver an ice hazard product to the customer within 3-12 hours of acquisition. Additionally, most users desire short-term ice forecasts detailing expected changes in the ice over the next 24-72 hours. 

#### Specific requirements for ice hazard parameters detailing present day thresholds and future objectives are listed in the table below. 

#### 

+----------------------+----------------------+-----------------------+
| ####  Parameters     | ####  Threshold      | ####  Objective       |
+----------------------+----------------------+-----------------------+
| ##                   | 100 meters           | 50 meters             |
| ## Ice Edge Accuracy |                      |                       |
+----------------------+----------------------+-----------------------+
| #### Ice Co          | \< 10%               | \< 5%                 |
| ncentration Accuracy |                      |                       |
|                      | 1/10 to 10/10        | 0 to 100 % (includes  |
| #### Ice             |                      | less than 1/10^th^ of |
|  Concentration Range |                      | ice                   |
+----------------------+----------------------+-----------------------+
| Ice Age (probability | 70%                  | 90%                   |
| of typing correctly) |                      |                       |
|                      | Distinguish          | Distinguish new,      |
| Ice Age Range        | first-year from      | young, first-yea and  |
|                      | multiyear ice        | multiyear ice         |
+----------------------+----------------------+-----------------------+
| ####                 | 1.  km/day           | 0.05 km/day           |
|  Ice Motion Accuracy |                      |                       |
|                      | 0-50 km/day          | 0-50 km/day           |
| #                    |                      |                       |
| ### Ice Motion Range |                      |                       |
+----------------------+----------------------+-----------------------+
| #### Timeliness      | 3-6 hours            | \< 3 hours            |
+----------------------+----------------------+-----------------------+
| ###                  | 24 hours             | 6 hours               |
| # Sampling Frequency |                      |                       |
+----------------------+----------------------+-----------------------+
| ####                 | [Poleward of 34^0^   | [Poleward of 34^0^    |
|  Geographic Coverage | north and south of   | north and south of    |
|                      | 50^0^                | 50^0^                 |
|                      | south]{.underline}   | south]{.underline}    |
+----------------------+----------------------+-----------------------+

d\) [Observational Requirements]{.underline}

For each ice hazard application, EOS data needs have been identified.
These requirements are listed in the table below.

+------------------+--------+------------+--------+-------+-----------+
| Application      | S      | Spatial    | Te     | Ta    | Delivery  |
|                  | patial | Coverage   | mporal | sking | Time      |
|                  | Reso   | (swath     | Reso   | Time  |           |
|                  | lution | width)     | lution |       |           |
+------------------+--------+------------+--------+-------+-----------+
| ##### Sea and    | 100m   | 500km      | daily  | 7     | \< 3      |
| Lake Ice Detecti |        |            |        | 2-168 | hours     |
| on for Avoidance |        |            |        | hours |           |
+------------------+--------+------------+--------+-------+-----------+
| ##### Se         | 50m    | 300km      | daily  | 7     | \< 3      |
| a and Lake Ice C |        |            |        | 2-168 | hours     |
| haracterization  |        |            |        | hours |           |
| for Exploitation |        |            |        |       |           |
+------------------+--------+------------+--------+-------+-----------+
| #####            | 30m    | 150km      | 2x     | 24-72 | \< 3      |
| Beset Vessel in  |        |            | /daily | hours | hours     |
| Sea and Lake Ice |        |            |        |       |           |
+------------------+--------+------------+--------+-------+-----------+
| #####            | 10m    | 300km      | daily  | 7     | \<3 hours |
|  Iceberg Detecti |        |            |        | 2-168 |           |
| on for Avoidance |        |            |        | hours |           |
+------------------+--------+------------+--------+-------+-----------+
| ##### Shoref     | 30m    | 150km      | 2x     | 24-72 | \< 3      |
| ast, Lake and Ri |        |            | /daily | hours | hours     |
| ver Ice Break-up |        |            |        |       |           |
+------------------+--------+------------+--------+-------+-----------+

**Assessment of Current and Planned Satellite Data**

Earth Observation Satellites that provide data presently being used
[operationally]{.underline} for Ice Hazard monitoring fall into three
major categories:

-   Passive microwave satellites (DMSP SSM/I, OKEAN RM08) providing data
    used to produce coarse resolution (15-25 km) ice concentration/ice
    type gridded products. The SSM/I 85 GHz channel is also used to
    produce ice motion product.

-   Visible/infrared satellites (TIROS AVHRR, DMSP OLS, various GOES
    Imager instruments) providing medium resolution (0.55-4.0 km) data.

-   Active microwave satellites with Synthetic Aperture RADAR (SAR)
    instruments (RADARSAT, ERS-2) providing all-weather, high resolution
    (10-100 m).

Note: The OKEAN RAR provides 1.2 km spatial resolution data.

### 

### Planned or recently launched Earth Observation Satellites representing new sources of data (or presently available data in a research or demonstration mode) that are suitable for Ice Hazard monitoring include:

-   Passive microwave satellites (DMSP SSM/IS, CORIOLIS).

-   Multi-spectral visible/infrared satellites (TERRA MODIS, ADEOS-2
    GLI).

-   Active microwave satellites with SAR instruments (ENVISAT ASAR,
    RADARSAT-2 SAR, ALOS PALSAR) and scatterometers (QuikSCAT SEAWINDS,
    ERS-2, METOP, ADEOS-2)

#### [Passive Microwave Satellites]{.underline}

#### The DMSP Block 5D-3/F-15 satellite carries an improved Special Sensor Microwave Imager with sounder (SSM/IS). As in previous instruments, SSM/IS measures radiances at 19, 22, 37 and 85 GHz. Most algorithms use the first three channels to extract ice concentration and ice type information. The sounder should provide coincident information on attenuation due to water vapor in atmosphere. Additionally, due to the higher spatial resolution (12.5 km) of the 85 GHz channel, some work has demonstrated that sequential SSM/I images can be used to generate ice motion estimates (Kwok et al, 1998). The useful of the 85 GHz channel is limited by weather. 

CORIOLIS (United States), planned for launch in 2002 by the U.S. Navy is
a passive microwave instrument with 5 bands (6.2, 10.7, 18.7, 23.8 and
37 GHz).

##### Multi-spectral Visible/Infrared Satellites

TERRA (United States), launched in December, 1999 by NASA (as par of the
Earth Observation System (EOS) program), carries the Moderate Resolution
Imaging Spectrometer (MODIS) instrument. MODIS gathers high-quality data
in 36 channels covering the visible, shortwave and longwave infrared
bands (0.4-14 um). Taking advantage of the high radiometric resolution,
NASA's MODIS Instrument Science team has developed the ICEMAP algorithm
to produce an automated daily global sea ice extent map (by swath) at a
1 km spatial resolution (Riggs et al, 1999). The ICEMAP algorithm is
based on the normalized difference between surface reflectance in the
visible band and a shortwave-infrared band. Sea ice will also be mapped
using emitted longwave thermal radiation. The Ice Surface Temperature
(IST) algorithm is calculated using a split window technique method
developed with AVHRR data (Key et al, 1997). Daytime gridded sea ice
products will be produced using the ICEMAP/IST techniques while
night-time products will be produced using only the IST technique. Data
are presently being produced in the research mode with plans for
operational use by national ice centers in late 2000/early 2001.

ADEOS-2 (Japan), planned for a mid-2001 launch by NASDA, will carry a
multi-spectral Global Imager (GLI) instrument. The GLI, like MODIS, will
have 36 channels that can be exploited to produce an automated sea ice
product.

##### Active Microwave Satellites

a)  Synthetic Aperture Radar Satellites --

ENVISAT (Europe), planned for a mid-2001 launch by ESA, will carry an
Advanced Synthetic Aperture Radar (ASAR) instrument. ASAR is a C-band,
dual polarized instrument with beam steering (15-45^0^ incidence angle)
that allows collection of data in several different modes. Data
collected in the standard mode will have a 100 km swath and 30 m spatial
resolution, while the wide mode will have a swath of 405 km and 100 m
spatial resolution. The later mode is ideal for sea ice monitoring. It
is also believed that alternating polarization will give improved ice
edge/water discrimination over earlier single polarization SAR's
(ERS-1/2 VV polarization; Radarsat-1 HH polarization). Cross
polarization data are expected to be particularly useful in estimating
topography and ice type discrimination (ESA, 1998).

RADARSAT-2 (Canada), planned for mid-2003 launch by CSA, will carry an
advance C-band SAR characterized by quad polarization, beam steering in
right and left directions, an increased downlink capability and a fine
resolution (3 meter) mode in addition to all the same operating modes as
Radarsat-1.

ALOS (Japan), planned for a mid-2003 launch by NASDA, will carry a
Phased Array type L-band SAR (PALSAR) with a cross-track pointing
capability from 18-550 incidence angle and a ScanSAR mode with a 350 km
swath and 100 m spatial resolution. ALOS will depend on two Data Relay
Transmission Satellites (DRTS) and x-band downlink to ground stations
for real-time data delivery to operational users.

b\) Scatterometer Satellites -

QuikSCAT (United States), launched in June of 1999 by NASA, carries the
SEAWINDS scatterometer. SEAWINDS is a specialized Ku band (13.4 GHZ)
microwave radar that was designed to measure ocean-surface winds but can
also be used to monitor ice over its 1,800 km swath. Using data from the
NASA Scatterometer (NSCAT) mission, Long and Drinkwater (1999) have
demonstrated that ice images with spatial resolutions of 8-10 km can be
created using the Scatterometer Image Reconstruction with Filtering
(SIRF) algorithm. Although the nominal resolution of the QuikSCAT
SEAWINDS sensor is 30x50 km it is believed that similar resolution
images can be created from QuikSCAT data.

ERS-2 (Europe), launched in 1995 by ESA, carries a scatterometer that
like QuikSCAT can be exploited to map sea ice. Research and development
by the Norwegian Meteorological Institute for the proposed EUMETSAT
Ocean and Sea Ice Application Facility (O&SI SAF) is using the ERS-2
scatterometer data to map sea ice on a demonstration basis (Breivik et
al, 1999). These data are combined with AVHRR and SSM/I data to produce
ice maps with 10 km spatial resolution. METOP (Europe), planned for
launch in 2003, will carry an advanced C-band Advanced Scatterometer
(ASCAT).

ADEOS-2 (Japan), planned for a mid-2001 launch by NASDA, will carry
SEAWINDS-2 a Ku band scatterometer that also can be used to generate ice
all-weather, moderate resolution ice images. Like QuikSCAT, these data
would serve as complimentary data sets to the coarser resolution passive
microwave and high resolution SAR data to produce more accurate
global-scale ice maps ideal for mission planning and climate research.

**Future Improvements to Consider**

As previously described, EOS data play an important and critical role in
the mature application of operational sea ice mapping. The role of EOS
data in iceberg detection and monitoring remains in the research and
evaluation phase. Improvements can be divided into four categories:
methodology, science, technology and data/product management.

[Methodology]{.underline}:

-   International Collaboration - there is a need for increased
    cooperation with other national ice services. The International Ice
    Chart Working Group (IICWG) was formed and had its 1^st^ meeting in
    October, 1999 in Copenhagen, Denmark. This group will focus on
    improving the exchange of satellite data and products and initiating
    cooperative training activities.

-   Access to EOS Data -- new and updated mechanisms to improve access
    to satellite data should include satellite acquisition tools (and
    policies) that shorten time to order data and rapid payload planning
    for future satellites.

-   Data Fusion Techniques -- recent studies indicate that substantial
    improvements in the quality of ice information derived from
    algorithms using EOS data can be achieved by using ancillary data
    and data fusion techniques. For example, Steffen et al, (1992b),
    stated that data assimilation and artificial intelligence (AI)
    methods offer the greatest promise for resolving ambiguities in
    passive microwave ice algorithms.

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-   Standard Product Formats - all national ice centers should produce
    standard digital formatted products (ice analysis graphics;
    annotated (interpreted) imagery and ice forecasts) that are
    user-friendly and GIS-compatible. This standardization effort should
    be directed at *operational customers* and separate from
    WMO-approved data archival formats (SIGRID-1/2 and CONTOUR-2). FGDC
    SDTS and IHO S-57 formats show promise but have gained little
    acceptance by the user community. Additionally, common digital
    coastlines are important for seamless exchange of information
    between national ice centers.

[Science]{.underline}:

-   EOS Data Algorithms -- new or improved sea ice/iceberg detection and
    sea ice classification algorithms. Possibilities include an "expert"
    or AI system that classifies SAR data into ice types, SSM/I hybrid
    algorithms that account for natural variations in brightness
    temperatures associated with regional inhomogeneities of sea ice,
    SSM/I 85 GHz ice motion products, an ice/no ice cloud-masked
    visible/infrared product and an SAR-based iceberg detection
    algorithm.

-   Ice Forecasting Models -- develop and implement regional (higher
    resolution) coupled ice/ocean/atmosphere forecasting models to
    improve sea ice forecasts in the Marginal Ice Zone (MIZ) and iceberg
    drift and ablation rates.

[Technology]{.underline}:

-   New and Improved Satellite Sensors -- utilize data from new sensors
    such as multi-spectral radiometers and scatterometers. Improve ice
    mapping capabilities by taking advantage of improved sensors like
    SAR instruments with dual/quad polarization.

-   Satellites with Multiple Instrument Payloads - improve ice mapping
    capabilities through use of simultaneous data collection (e.g.
    ENVISAT ASAR and MERIS; ALOS AVNIR-2 and PALSAR; satellite with
    multiple frequency SAR (C and X bands).

-   Satellite Revisit Time -- design right/left looking beam steering
    capability and optimum orbits to maximize revisit time and
    geographic coverage in ice-covered seas.

-   Temporal Resolution of EOS Data -- improve delivery of processed
    imagery by requiring minimum real-time data processing and
    throughput standards at all participating ground stations. Consider
    use of onboard satellite data processors.

-   Electronic Charts -- improve utility of ice information by producing
    ice analyses in electronic chart formats that can be integrated into
    ship chart display systems.

[Data/Product Management]{.underline}:

-   Special EOS Data Policy -- request EOS data providers implement
    special data policies that allow for preferred and affordable access
    for national ice services and the production of ice hazard products.

-   Outreach Programs -- establish out reach programs to educate
    customers on EOS data types, products available and the potential
    uses of each. Communicate to end-users the strengths and weaknesses
    of EOS data and ice guidance products.

#### New and Improved Ice Guidance Products - survey customer requirements to develop and implement new ice hazard products such as maps indicating state of ice decay and color-coded ice warning charts based on ship classes.

#### Data/Product Dissemination -- improve efficiency of data networks through use of state of the art compression software.

**Summary and Conclusions**

It is well known that sea ice and icebergs pose a serious hazard to
shipping and other maritime activities in the polar regions. The role of
EOS data in operational ice monitoring is well documented and has grown
in importance over the years. EOS data from visible/infrared sensors are
readably available to all ice services but are useful only under
cloud-free conditions. Passive microwave sensors can penetrate cloud
cover but their effectiveness in ice monitoring is limited by coarse
resolution. Active microwave sensors such as SAR's are ideal for ice
mapping because of their high resolution, all-weather, wide swath ice
detection capability. Investigations have also shown that these data are
also valuable in their ability to quantify other ice parameters such as
ice type (stage of development), ice topography and presence of open
water or thin ice openings within the sea ice pack. Sea ice guidance
products derived in real-time from these data are used operationally to
ensure safety of navigation of non-ice strengthened vessels, maximize
time and fuel savings of icebreaker lead convoys and protect life and
property associated with human activities on the ice.

In the future, new and updated EOS sensors provide great promise for
improving the applications of sea ice mapping and iceberg detection.
Data from multi-spectral visible/infrared radiometers and scatterometers
can be used to generate automated sea ice maps. SAR satellites with
right/left looking beam steering, multiple polarization modes and
enhanced downlink capabilities will provide more valuable data in a
shorter period of time to the end user. The coincident collection of EOS
data from multiple instruments "fused" with ancillary environmental data
can be used to resolve ambiguities and eliminate biases in conventional,
single sensor algorithms. Data policies must exist for easy and rapid
access to EOS data for ice hazard detection and monitoring. Lastly,
collaborative efforts are needed between all the national ice services
to ensure that EOS data are shared, that ice products are issued in
standard formats and most importantly that customers are educated on the
strengths, weaknesses and value of EOS data and Ice Hazard products.

**References**

ARCUS, (1999), The Future of an Arctic Resource --Recommendations from
the Barrow Area Research Support Workshop. Arctic Research Consortium of
the United States (ARCUS), Fairbanks, AK.

Belchansky, G.I. and D.C. Douglas (2000), Classification Methods for
Monitoring Arctic Sea ice Using OKEAN Passive/Active Two Channel
Microwave Data. Remote Sensing of the Environment, 73:307-322.

Bertoia, C., J. Falkingham, F. Fetterer (1998), "Polar SAR for
Operational Ice Mapping" in Analysis of SAR Data of Polar Oceans. C.
Tsatsoulis and R. Kwok, Eds. Berlin and Heidelberg:Springer-Verlag.

Brigham, L. (1991), "Technical Developments and the Future of Soviet
Arctic Marine Transportation" in The Soviet Maritime Arctic. L.W.
Brigham, Ed. Naval Institute Press.

Brown, C.S., M.F. Meier and A. Post (1982), Calving Speed of Tidewater
Glaciers, with Application to the Columbia Glacier. U.S. Geological
Survey Professional Paper 1258-C, Washington DC Government Printing
Office.

Cavalieri, D.J., P. Gloerson and W.J. Campbell (1984), Determination of
Sea Ice Parameters with NIMBU-7 SMMR. J. Geophys. Res., 89:5355-5369.

Cavalieri, D.J. (1994), A Microwave Technique for Mapping Thin Ice. J.
Geophys. Res., 99(C6):12561-12572.

Comiso, J.C. (1983), Sea Ice Effective Emissivities from Satellite
Passive Microwave and Infrared Observations. J. Geophys. Res.
88(C12):7686-7704.

Emery,W.J., M. Radebaugh, C.W. Fowler, D.J Cavalieri and K. Steffen
(1991). A Comparison of Sea ice Parameters Computed from AVHRR, Landsat
imagery and Airborne Passive Microwave Radiometer. J. Geophys. Res.
96(C12):22075-22085.

Emery, W.J., C. Fowler and J.K. Maslanik (1994), Arctic Sea Ice
Concentrations from SSMI and AVHRR Data. J. Geophys. Res.
99(C9):18329-18342.

European Space Agency, (1998), ASAR Science and Applications, SP-1225,
ESA Publications Division, The Netherlands.

Foster, J. (1982), Ice Observations in the Chesapeake Bay 1977-1981.
Mariners Weather Log, NOAA/NESDIS/NODC, Vol 26, No. 2: 66-71.

#### Fung, A.K. (1994), Microwave Scattering and Emission Models and their Applications, Artech House, Boston MA.

Gustajtis, K.A. (1979), Iceberg population distribution study in the
Labrador Sea. C-Core Publication, July Data Report (79-8), Centre for
Cold Ocean Resources Engineering, Memorial University of Newfoundland,
St. John's Newfoundland.

Isaacs, R. G. and J.C. Barnes (1987), Intercomparison of cloud imagery
from DMSP OLS, NOAA AVHRR, GOES VISSR and Landsat MSS. J. Atmos Oceanic
Technol., 4, 647-667.

Key, J., J.B. Collins, C. Fowler and R.S. Stone (1997), High-latitude
surface temperature estimates from thermal satellite data. Rem. Sens. Of
Environ., 68(2):152-163.

Kwok, R., E. Rignot, B. Holt and R. Onstott (1992), Identification of
Sea Ice Types in Space Borne SAR Data. J. Geophys. Res.
97(C2):2391-2402.

Kwok, R. and G.F. Cunnigham (1994), Backscatter Characteristics of the
Winter Ice Cover in the Beaufort Sea. J. Geophys. Res. 99(C4):7787-7802.

Kwok, R., J.C. Comiso and G. F. Cunnigham (1996), Seasonal
Characteristics of the Perennial Ice Cover of the Beaufort Sea. J.
Geophys. Res. 101(C12):28417-28439.

Lee, T.F., S. Atwater and C. Samuels (1993), Sea Ice Edge Enhancement
using Polar-Orbiting Environmental Satellite Data. American
Meteorological Society Notes, Sept, p.369-377.

Larsen, R.W., R.A. Shuchman, R.F. Rawson and R.D. Worsford, (1978), The
use of SAR Systems for Iceberg Detection and Characterization. 12^th^
International Symposium on Remote Sensing on the Environment, Ann Arbor,
Michigan; 20-26 April, 1978, pp.1127-1147.

Loset S. and T. Carstens (1993), Production of icebergs and observed
extreme drift speeds in the Barents Sea. The 12^th^ Conference on Port
and Ocean Engineering under Arctic Conditions-POAC 93, Hamberg, Germany;
17-20 August 1993; pp.425-438.

Lunsford, A.C. (1998), "Use of SAR Data at the Alaska River Forecast
Center" in Proc. 14^th^ Int. Symp. On Ice in surface Waters, Clarkson
Univ., Potsdam, N.Y. pp. 25-30.

Massom, R. and J.C. Comiso (1994), The Classification of Arctic Sea Ice
Types and the Determination of Surface Temperature using AVHRR data. J.
Geophys. Res. 99(C3):5201-5218.

McDowell, J. (1990), The Other Cold War. Mariners Weather Log,
NOAA/NESDIS/ NODC, Vol 34, No. 1:3-7

Parkinson, C.L.,J.C. Comiso, H.J. Zwally, D. Cavalieri, P. Gloersen and
W.J. Campbell (1987), Arctic Sea Ice 1973-1976: Satellite Passive
Microwave Observations, Washington D.C.

Rees, W.G. (1990), Physical Principles of Remote Sensing. Cambridge:
Cambridge University Press.

Riggs, G.A., D.K Hall and S.A. Ackerman, (1999), Sea Ice Extent and
Classification using the MODIS Airborne Simulator (MAS). Rem. Sens. Of
Environ., 61:302-309.

Steffen, K., J. Heinrichs, J. Maslanik and J. Key (1992a), Sea Ice
Features and Type Identification in merged ERS-1 SAR and Landsat TM
Imagery. Proceeding of the 1^st^ ERS-1 Symposium-Space at the Service of
our Environment held in Cannes, France, 4-6 November 1992; pp.361-365.

Steffen, K., J. Key, D. Cavalieri, J. Comiso, P. Gloersen, K. St.
Germain and I. Rubinstein (1992b), "The Estimation of Geophysical
Parameters using Passive Microwave Algorithms" in Microwave Remote
Sensing of Sea Ice, Geophysical Monograph, F.D. Carsey, Ed., Washington
DC:AGU, vol.68, ch.1, pp.1-6.

Teleki, P.G., W.J Campbell, R.O. Ramsier and D. Ross (1979), "The
Offshore Environment: A Perspective from SEASAT-1 SAR Data", Proc.
11^th^ Annual Offshore Technology conference, Houston, Texas,
pp.215-220.

Vinje, T.E., (1989), Icebergs in the Barents Sea. In Proceedings of the
8^th^ International Offshore Mechanics and Arctic Engineering Conference
(OMAE) held in the Hague, Netherlands on 19-23 March 1989; pp.139-145.

Wark D.Q. and R. W. Popham (1962), First International Symposium on
Rocket and Satellite Meteorology. North Holland Publishing Co.,
Amsterdam, 415 p.

Wadhams, P. 1994, Sea ice Thickness Changes and their Relation to
climate, in Polar oceans and Their Role in Shaping the Global
Environment: The Nansen Centennial Volume. Geophysical Monograph 85,
pp.337-362, AGU, Washington.

World Meteorological Organization, (1970). Sea Ice Nomenclature. WMO
Geneva, Switzerland.

### Appendix A 

####### Ice Hazard Team Members

David Benner, National Ice Center USA Co-team leader

Bruce Ramsay Canadian Ice Service Canada Co-team leader

**Appendix B**

####### National Ice Services

**[Canada]{.underline}**

Canadian Ice Service -- Environment Canada

373 Sussex Drive, Block E - 3rd floor

Ottawa, Ontario

Canada K1A 0H3

telephone: (613) 996-1550 or toll-free in North America (800) 767-2885

telefax: (613) 947-9160

e-mail: cis.client@ec.gc.ca

Internet: http://www.cis.ec.gc.ca

## 

## **[China]{.underline}**

National Marine Environment Forecast Center, 8, Dahuisi Rd., Haidian
District

Beijing, 100081, China

Qingdao Marine Forecasting Observatory of SOA 22 Fushun Road,

Qingdao, 266033, China

Group of Sea Ice Management

C/o General Dispatch Office

China Offshore Oil Bohai Corporation

P.O. Box 501 Tanggu

Tianjin 300452 China

## **[Denmark]{.underline}**

Søværnets Operative Kommando

Istjenesten

Postboks 483

### DK-8100 Århus C DENMARK 

telephone: +45 89 43 30 99,

+45 89 43 32 53 (Ice-Breaking Service and Ice-reporting Service)

telefax: +45 89 43 32 30

telephone answering unit: + 45 89 32 44.

telex: 64527 SHIPPOS DK

e-mail: bk4@sok.dk (Attention.: Danish Ice Service)

Danmarks Meteorologiske Institut

Lyngbyvej 100

DK-2100 Copenhagen DENMARK

Iscentralen Narsarsuaq

3923 Narsarsuaq

GREENLAND

http://www.dmi.dk (DMI main page)

http://www.dmi.dk/vejr/gron/iskort.html

Internet: http://iserit.greennet.gl/isc/ice/

e-mail: isc@greennet.gl

## **[Estonia]{.underline}**

Estonian Meteorological and Hydrological Institute EMHI

Rävala 8

EE - 0001 Tallin, Estonia

telephone +372 6461561

telefax +372 6461577

e-mail: emhi@online.ee

## 

## **[Finland]{.underline}**

Finnish Institute of Marine Research

Finnish ice service

P.O. Box 304

FIN-00181 HELSINKI, FINLAND

telephone: +358 9 6857659

telefax: +358 9 6857638 or 6857639

call-fax: +358 60018668

e-mail: info@ice.fmi.fi

Internet: http://ice.fmi.fi

## 

## **[Germany]{.underline}**

BSH -- Eisdienst

Postfach 301220

20305 Hamburg, Germany

telephone: +49 40 3190 3290

telefax: +49 40 3190 5032

e-mail: ice@bsh.d400.de

Internet: http://www.bsh.de (in German/English)

## **[Iceland]{.underline}**

Icelandic Meteorological Office

Bustadavegur 9

IS-150 Reykjavik, Iceland

telephone: +354 560 0600

telefax: +354 552 8121

http://www.vedur.is

## **[Japan]{.underline}**

Maritime Meteorological Division

Climate and Marine Department

Japan Meteorological Agency

1-3-4 Ote-machi, Chiyoda-ku

Tokyo 100-8122, Japan

http://www.kishou.go.jp/
http://www.jodc.jhd.go.jp/inf/institute/jma/jma.html (In English)

## **[Latvia]{.underline}**

Latvian Hydrometeorological Agency

165, Maskavas Str.

LV- 1019 Riga, Latvia

#### **[Lithuania]{.underline}**

CMR

Taikos str. 26, 5802 Klaipeda,

Lithuania

tel. (+ 3706) 250324

fax (+ 3706) 250930

CMR@klaipeda.omnitel.net.

LHMS Klaipeda Department

Taikos str.26, 5802 Klaipeda,

Lithuania

telephone (+ 3706) 252247;

telefax (+ 3706)2 52247;

e-mail. khmo@klaipeda.aiva.lt

**[Netherlands]{.underline}**

Rijkswaterstaat / Riza

Information and Warning Centre

Postbox 17

8200 AA Lelystad NETHERLANDS

telephone: +31 320 298550, +31 320 298888

telefax: +31 320 298580

e-mail bc@riza.rws.minvenw.nl

**[Norway]{.underline}**

Vervarslinga for Nord-Norge

Postboks 2501

9002 Tromsoe, Norway

telephone: +47 77 68 40 44

telefax: +47 77 68 90 04

Internet: http://www.dnmi.no

## **[Poland]{.underline}**

Instytut Meteorologii i Gospodarki Wodnej, Oddzial Morski

Waszyngtona 42,

PL 81-342 GDYNIA, Poland

telephone: +48 58 6205221 (operator), +48 58 6201641 (ice team 06-14Z)

telefax: +48 58 6205493

e-mail: pga@stratus.imgw.gdynia.pl

Internet: http://www.imgw.gdynia.pl/

## **[Russia]{.underline}**

Arctic and Antarctic Research Institute

38 Bering Street

St.Petersburg, Russia, 199397

telephone.:+7(812)352-1520

telefax: +7(812)352-2688

e-mail: service@aari.nw.ru

Internet: http://www.aari.nw.ru

Internet: ftp://aari.nw.ru

## **[Sweden]{.underline}**

Swedish Meteorological and Hydrological Institute, SMHI.

Marine Service

S - 601 76 Norrkoping Sweden

telephone: +46 (0)11 495 8400

telefax: +46 (0)11 495 8403

e-mail: ice@smhi.se

Internet: http://www.smhi.se (main web-page)

Internet: ftp://ftp.smhi.se (ftp-server)

## **[United States]{.underline}**

Director

National Ice Center

4251 Suitland Road, FB4

Washington, DC 20395

ph. (301) 457-5303/-5300 (Fax)

e-mail: liaison@natice.noaa.gov

http://natice.noaa.gov

Commander

International Ice Patrol

1082 Shennecossett Road

Groton, CT 06340-6095

ph. (860) 441-2626/-2773 (Fax)

http://www.rdc.uscg.mil/iippages/home.html