Raw model
sea ice concentration data was processed using a simple linear regression model and satellite derived ice extent to produce bias corrected predictions.
The results indicate that concurrent atmospheric circulation trends contribute to forcing winter and
summer sea ice concentration trends in many parts of the marginal ice zone during both periods.
It is therefore important to consider both loss
of sea ice concentration and sea ice thickness in evaluating the response of the atmosphere.
Semenov, V. A. & Latif, M. Nonlinear winter atmospheric circulation response to
Arctic sea ice concentration anomalies for different periods during 1966 — 2012.
Beitsch et al. (University of Hamburg); 4.7 ± 0.5; Statistical The estimate is based on AMSR -
E sea ice concentration data derived using the ARTIST sea ice (ASI) algorithm (Spreen et al., 2008; Kaleschke et al., 2001).
We also include a
September sea ice concentration map from Zhang and Lindsay's August SIO (mean concentration is a slightly different metric to the probability of sea ice extent).
Using
daily sea ice concentration data from the satellite record, he calculated changes in the dates of the beginning of the melt season in spring and the start of the fall freeze - up from 1979 to 2013.
A look at Arctic
sea ice concentration over the last 100 years (through 2013) using the latest NSIDC gridded 1850 - reconstruction from Walsh et al. [2016].
Yuan et al. (LDEO Columbia University), 5.08 (+ / - 0.51), Statistical The prediction is made by statistical models, which are capable to predict Arctic
sea ice concentrations at grid points 3 - month in advance with reasonable skills.
(a, b) Annual -
mean sea ice concentration in the CTL and SW experiments, and (c) SST anomalies during the last 50 years of the latter simulation.
Assuming the patterns in August — September are neutral, then our expectation is that sea ice decreases may yet approach the record minimum in 2007, the reason being the susceptibility of the predominantly first - year ice cover and the large areas of
reduced sea ice concentration evident in the late July AMSR - E image data.
All this cold water being released into the ocean has a significant impact on the formation of sea ice, resulting in higher rates of
sea ice concentration around Antarctica.
Wang, 5.7 (+ / - 0.47), Modeling (same as June) A projected September Arctic sea ice extent of 5.7 million km2 is based on a NCEP ensemble mean CFSv2 forecast initialized from the NCEP Climate Forecast System Reanalysis (CFSR) that assimilates
observed sea ice concentrations and other atmospheric and oceanic observations.
To be consistent with the validating sea ice extent index from NSIDC, if possible, please first compute the
average sea ice concentration for the month and then compute the extent as the sum of cell areas > 15 %.
On Januray 25, 2013, the calibrated brightness temperature data have been released to the public, and starting from 26 January 2013, we produce daily
sea ice concentration maps from the AMSR2 data.
NOAA@NSIDC is pleased to announce the release of Version 3 Revision 1 of the NOAA / NSIDC Climate Data Record of Passive
Microwave Sea Ice Concentration data product.
Sea ice concentration during the summer months — an important measure because summertime is when some subpopulations are forced to fast on land — also declined in all regions, by 1 percent to 9 percent per decade.
The
ASI sea ice concentration algorithm used here has been validated in several studies (Spreen et al. 2005, Spreen et al., 2008).
For all the ensemble members, we used one regression model using 27 years of past model data and NSIDC Merged SMMR and SSM /
I sea ice concentration data to estimate and correct for systematic model bias.
Petty (NASA - GSFC / UMD), 4.12 (± 0.30), Statistical Based on an analysis of
June sea ice concentration data provided by the NSIDC (NASA Team), I forecast a 2016 September Arctic sea ice extent of 4.12 + / - 0.30 million km2.