Assessing the Potential of Enhanced Resolution Gridded Passive Microwave Brightness Temperatures for Retrieval of Sea Ice Parameters

A new enhanced resolution gridded passive microwave brightness temperature (TB) product is used to estimate sea ice concentration and motion. The effective resolution of the TBs is found to be roughly twice that of the standard 25 km resolution, though the gridded resolution of the distributed product is higher. Enhanced resolution sea ice concentrations from the Bootstrap algorithm show more detail in the sea ice, including relatively small open water regions within the ice pack. Sea ice motion estimates from the enhanced resolution TBs using a maximum cross-correlation method show a smoother motion circulation pattern; in comparison to buoys, RMS errors are 15–20% lower than motion estimates from the standard resolution fields and the magnitude of the bias is smaller as well. The enhanced resolution product includes other potentially beneficial characteristics, including twice-daily grids based on local time of day and a complete timeseries of data from nearly all multi-channel passive microwave radiometers since 1978. These enhanced resolution TBs are potential new source for long-term records of sea ice concentration, motion, age, melt, as well as salinity and ocean-atmosphere fluxes.

[1]  David G. Long,et al.  Optimum Image Formation for Spaceborne Microwave Radiometer Products , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[2]  J. Turner,et al.  Positive Trend in the Antarctic Sea Ice Cover and Associated Changes in Surface Temperature. , 2017, Journal of climate.

[3]  B. Ramsay,et al.  Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/hyp.6720 Enhancements to, and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS) † , 2022 .

[4]  K. Ohshima,et al.  Estimation of Sea Ice Production in the Bering Sea From AMSR‐E and AMSR2 Data, With Special Emphasis on the Anadyr Polynya , 2020 .

[5]  W. Emery,et al.  An objective method for computing advective surface velocities from sequential infrared satellite images , 1986 .

[6]  W. Meier,et al.  An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC) , 2020 .

[7]  Thorsten Markus,et al.  An enhancement of the NASA Team sea ice algorithm , 2000, IEEE Trans. Geosci. Remote. Sens..

[8]  J. Comiso,et al.  Trends in the sea ice cover using enhanced and compatible AMSR‐E, SSM/I, and SMMR data , 2008 .

[9]  S. Kern,et al.  Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions , 2020 .

[10]  David G. Long,et al.  Image reconstruction and enhanced resolution imaging from irregular samples , 2001, IEEE Trans. Geosci. Remote. Sens..

[11]  Sohey Nihashi,et al.  Sea-Ice Production in Antarctic Coastal Polynyas Estimated From AMSR2 Data and Its Validation Using AMSR-E and SSM/I-SSMIS Data , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[12]  L. Kaleschke,et al.  Sea ice remote sensing using AMSR‐E 89‐GHz channels , 2008 .

[13]  C. L. Parkinson,et al.  A 40-y record reveals gradual Antarctic sea ice increases followed by decreases at rates far exceeding the rates seen in the Arctic , 2019, Proceedings of the National Academy of Sciences.

[14]  W. Campbell,et al.  Determination of sea ice parameters with the NIMBUS 7 SMMR , 1984 .

[15]  Niels Martin Schmidt,et al.  Key indicators of Arctic climate change: 1971–2017 , 2019, Environmental Research Letters.