Guide of SEA ICE

Sea Ice Remote Sensing
The AMSR-E will be used to study the Earth's hydrological cycle and will retrieve precipitation, soil moisture, snow cover, sea surface temperature, oceanic water vapor, cloud water, near surface wind speed, and sea ice parameters.
The sea ice parameters to be retrieved from AMSR-E include sea ice concentration, sea ice temperature, and snow depth on sea ice.
The sea ice concentration products will be generated using two algorithms: the enhanced NASA Team (NT2) algorithm (Markus and Cavalieri, 2000) and the AMSR Bootstrap algorithm (ABA).
In the Arctic, the NT2 algorithm will be used to obtain the standard sea ice concentration, whereas in the Antarctic, the ABA algorithm will provide the standard product.
In addition, the (ABA-NT2) and the (NT2-ABA) ice concentration differences will be provided for the Arctic and Antarctic, respectively.
Sea ice temperature is a by-product of the ABA algorithm and the sea ice snow depth will be obtained from an algorithm described by Markus and Cavalieri (1998).
A pre-launch Arctic campaign called Meltpond2000 (Cavalieri, 2000) took place from June 25 through July 6, 2000 with the objective of quantifying the errors incurred by the AMSR-E sea ice algorithms resulting from the presence of melt ponds.


SEA ICE

Sea Ice Remote Sensing
Our group conducts basic research primarily through the utilization of satellite passive microwave radiometry.
the study of the long-term variability of the polar sea ice cover and its relationship to climate change the study of air-sea-ice interactions at polar latitudes the development and validation of sea ice algorithms .

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info: SEA ICE


Photo by depts.washington.edu

CSM Sea Ice Model (CSIM)
It is driven by the heat, momentum, and freshwater fluxes provided at the upper and lower ice boundaries by the atmospheric and oceanic model components, respectively.
CSIM, in turn, provides the appropriate boundary fluxes required by the atmosphere and ocean in the presence of ice.
The most notable additions to this code are the inclusion of lower resolution grid domains (the x3 and x3p), and the ability to use sea ice concentration climatology datasets to integrate the system in climatology mode.

Benefits



RealClimate » Arctic Sea Ice decline in the 21st CenturyDéclin de la banquise de l’Arctique au 21ème siècle
Headlines read 'Experts warn North Pole will be 'ice free' by 2040', 'The Big Melt: Loss of Sea Ice Snowballs ', and 'Arctic Clear for Summer Sailing by 2040: Models Predict Rapid Decline of Sea Ice ''.
In our paper (with co-author Bruno Tremblay), we examined the September Arctic sea ice cover in the 20th and 21st centuries in climate models, and found occasional decades of very rapid retreat.
Figure 1 : (a) Northern Hemisphere sea ice extent in September from one integration of the Community Climate System Model version 3 (CCSM3) with observations from the satellite era shown in red.
The three lower panels show the September ice concentration (ice floes are separated by open water) in three select decades.
It is common practice to run climate models multiple times with slight variations to the initial conditions.
An ensemble of runs offers an opportunity to evaluate rare events too, such as extreme sea ice decay.
We were in search of evidence for 'tipping points ', which several authors have speculated might exist in sea ice.
RealClimate places sea ice in the category of systems with 'known unknowns' with regard to tipping points.

SEA ICE: