Sea ice concentration#Microwave radiometry

{{short description|Area of sea ice relative to the total area at a given point in the ocean}}

Sea ice concentration is a useful variable for climate

scientists and nautical navigators. It is defined as the area of

sea ice relative to the total at a given point in the ocean.

This article will deal primarily with its determination from remote sensing measurements.

Significance

Sea ice concentration helps determine a number of other important climate

variables. Since the albedo of ice is much higher than that of water,

ice concentration will regulate insolation in the polar oceans.

When combined with ice thickness, it determines

several other important fluxes between the air and sea,

such as salt and fresh-water fluxes between the polar oceans

(see for instance bottom water) as well as

heat transfer between the atmosphere.

Maps of sea ice concentration can be used to determine

Sea ice area and

Sea ice extent, both of which are important

markers of climate change.

Ice concentration charts are also used by navigators to determine

potentially passable regions—see icebreaker.

Methods

=In situ=

Measurements from ships and aircraft are based on simply calculating

the relative area of ice versus water visible within the scene.

This can be done using photographs or by eye.

In situ measurements are used to validate remote sensing

measurements.

=SAR and visible=

Both synthetic aperture radar and visible sensors (such as Landsat)

are normally high enough resolution that each pixel is simply classified

as a distinct surface type, i.e. water versus ice. The concentration can then be

determined by counting the number of ice pixels in a given area which

is useful for validating concentration estimates from lower resolution

instruments such as microwave radiometers. Since SAR images are normally

monochrome and the backscatter of ice can vary quite considerably,

classification is normally done based on texture using groups of

pixels—see pattern recognition.

Visible sensors have the disadvantage of being quite weather sensitive—images are obscured by clouds—while SAR sensors, especially in the

higher resolution modes, have a limited coverage and must be pointed.

This is why the tool of choice for determining ice concentration is

often a passive microwave sensor.

{{cite book

| title=Microwave Remote Sensing, Active and Passive

| editor=F. T. Ulaby

| editor2=R. K. Moore

| editor3=A. K. Fung

| date=1986

| publisher=Addison Wesley

| location=London, England}}

{{cite book

| title=Microwave Remote Sensing of Sea Ice

| editor=W. B. Tucker

| editor2=D. K. Prerovich

| editor3=A. J. Gow

| editor4=W. F. Weeks

| editor5=M. R. Drinkwater

| publisher=American Geophysical Union}}

=Microwave radiometry=

File:Oldest Arctic Sea Ice is Disappearing.png

All warm bodies emit electro-magnetic radiation: see thermal radiation.

Since different objects will emit differently at different frequencies,

we can often determine what type of object we are looking at based on its emitted

radiation—see spectroscopy. This principle underlies all passive

microwave sensors and most passive infrared sensors. Passive is used in the

sense that the sensor only measures radiation that has been emitted by other

objects but does not emit any of its own.

(A SAR sensor, by contrast, is active.) SSMR and SSMI radiometers were flown on the Nimbus program and DMSP series of satellites.

Because clouds are translucent in the microwave regime, especially

at lower frequencies, microwave radiometers are quite weather insensitive.

Since most microwave radiometers operate along a polar orbit with

a broad, sweeping scan, full ice maps of the polar regions where

the swaths are largely overlapping can usually be obtained within one day.

This frequency and reliability comes at the cost of a poor resolution:

the angular field of view of an antenna is directly

proportional to the wavelength

and inversely proportional to the effective aperture area.

Thus we need a large deflector dish to compensate for a low frequency

Most ice concentration algorithms based on microwave radiometry

are predicated on the dual observation that: 1. different surface types

have different, strongly clustered, microwave signatures and

2. the radiometric signature at the instrument head is a linear

combination of that of the different surface types, with the weights

taking on the values of the relative concentrations.

If we form a vector space from each of the instrument channels

in which all but one of the signatures of the different surface types

are linearly independent, then it is straightforward to solve for

the relative concentrations:

: $\vec T_b = \vec T_{b0} + \sum_{i=1}^n(\vec T_{bi} - \vec T_{b0})C_i$

where $\vec T_b$ is the radiometric signature at the

instrument head (normally measured as a brightness temperature),

$\vec T_{b0}$ is the signature of the nominal

background surface type (normally water),

$\vec T_{bi}$ is the signature of the ith

surface type while C_i are the relative

concentrations.

{{cite journal

| author=D. A. Rothrock| author2=D. R. Thomas| author3=A. S. Thorndike, AS| name-list-style=amp

| date=1988

| journal=Journal of Geophysical Research

| title=Principal Component Analysis of Satellite Passive Microwave Data Over Sea Ice

| volume=93

| number=C3

| pages=2321–2332

|bibcode = 1988JGR....93.2321R |doi = 10.1029/JC093iC03p02321 }}

{{cite tech report

| title=L-Band Radiometry for Sea-Ice Applications

| institution=Institute of Environmental Physics, University of Bremen

| date=2009

| number=ESA/ESTEC Contract N. 21130/08/NL/EL

}}

{{cite journal

| author=P. Mills| author2=G. Heygster| name-list-style=amp

| date=2010

| journal=IEEE Transactions on Geoscience and Remote Sensing

| title=Retrieving sea ice concentration from SMOS

| number=2

| volume=8

| pages=283–287

| doi = 10.1109/LGRS.2010.2064157

| s2cid=21337433| url=http://peteysoft.users.sourceforge.net/smos_concentration_ieee.pdf

}}

Every operational ice concentration algorithm is predicated on this

principle or a slight variation.

The NASA team algorithm, for instance, works by taking the

difference of two channels and dividing by their sum.

This makes the retrieval slightly nonlinear, but with

the advantage that the influence of temperature is mitigated.

This is because brightness temperature varies roughly linearly

with physical temperature when all other things are equal—see emissivity—and because the sea ice emissivity at different microwave

channels is strongly correlated.

As the equation suggests, concentrations of multiple ice

types can potentially be detected, with NASA team distinguishing between

first-year and multi-year ice (see image above).

{{cite journal

| date=1997

| journal=Remote Sensing of Environment

| title=Passive microwave algorithms for sea ice concentration: A comparison of two techniques

| volume=60

| issue=3| pages=357–384

| doi=10.1016/S0034-4257(96)00220-9| bibcode=1997RSEnv..60..357C}}

{{cite journal

| author=T. Markus| author2=D. J. Cavalieri| name-list-style=amp

| title=An Enhancement of the NASA Team Sea Ice Algorithm

| journal=IEEE Transactions on Geoscience and Remote Sensing

| volume=38

| number=3

| pages=1387–1398

| date=2000

|bibcode = 2000ITGRS..38.1387M |doi = 10.1109/36.843033 | url=https://zenodo.org/record/1232177}}

Accuracies of sea ice concentration derived from passive microwave sensors may be expected to be on the order of 5\% (absolute).

{{cite journal

| date=2006

| journal=Remote Sensing of Environment

| title=Improved retrieval of sea ice total concentration from spaceborne passive microwave observations using numerical weather prediction model fields: An intercomparison of nine algorithms

| volume=104

| issue=4| pages=374–392

| doi=10.1016/j.rse.2006.05.013| bibcode=2006RSEnv.104..374A}}

{{cite journal

| date=2009

| journal=Journal of the Remote Sensing Society of Japan

| volume=29

| number=1

| pages=226–235

| title=AMSR-E Geolocation and Validation of Sea Ice Concentrations Based on 89 GHz data

}}

A number of factors act to reduce the accuracy of the retrievals, the most obvious being variations in the microwave signatures produced by a given surface type.

For sea ice, the presence of snow, variations in salt and moisture content, the presence of melt ponds as well as variations in surface temperature will all produce strong variations in the microwave signature of a given ice type. New and thin ice in particular will often have a microwave signature closer to that of open water. This is normally because of its high salt content, not because of radiation being transmitted from the water through the ice—see sea ice emissivity modelling.

The presence of waves and surface roughness will change the signature over open water. Adverse weather conditions, clouds and humidity in particular, will also tend to reduce the accuracy of retrievals.

References

External links

[http://www.iup.uni-bremen.de/iuppage/psa/2001/amsrop.html High-resolution sea ice concentration charts] derived from AMSR-E 89 GHz channel
[http://www.arctic.io/satellite The Arctic ice sheet] True color satellite map with daily updates.

Category:Sea ice

Category:Remote sensing

Category:Radiometry

Sea ice concentration#Microwave radiometry

Significance

Methods

=In situ=

=SAR and visible=

=Microwave radiometry=

See also

References

External links