Validation of AMSR-E Polar Ocean Products Using a Combination of Observations and Modeling

PI: James A. Maslanik
Institution: University of Colorado
CCAR
CB431
Boulder, CO 80309
Phone: (303)492-8974
FAX: (303)492-8974
Email: james.maslanik@colorado.edu
WWW: http://just-ice.colorado.edu/AMSR.html


Co-investigators:
- John Heinrichs, Fort Hays State University
- Thorsten Markus; NASA/GSFC
- Julienne Stroeve; University of Colorado
- Matthew Sturm; U. S. Corps of Engineers Cold Regions Research and Eng. Lab.


EOS Team: AMSR-E

NASA EOS-PSO funding through FY02: $223,552

ABSTRACT

Variations in sea ice cover in the polar regions are sensitive indicators of climatic change, and significantly affect human and animal activities and habitat. In recognition of this, the polar oceans have been monitored using a series of passive microwave imaging systems since 1974. These systems have provided some of the longest, most consistent, and widely used data sets for sea ice and snow cover monitoring. With the launch of the Advanced Microwave Scanning Radiometer (AMSR) onboard the Aqua platform, these time series will be continued and enhanced by the additional spectral channels, enhanced resolution, and improved instrument performance offered by AMSR. Revised algorithms and new products have been proposed by the AMSR Instrument Science Team, in conjunction with a validation plan to assess algorithm performance for the generation of Level 3 sea ice-related products. This validation plan relies primarily on intercomparison of satellite products with data acquired from relatively high-altitude aircraft flights, and is essentially a continuation of past validation efforts. While these efforts have been fruitful, key aspects such as the effects on algorithms of atmospheric conditions, snow properties, surface roughness, melt processes, and evolution of ice growth in newly-formed open water areas are not sufficiently well understood or documented. In addition, the validation of sea ice temperature and snow depth on sea ice requires collection of additional data and analyses using alternative methods. To address these elements of product validation, we intend to complement and enhance the planned Science Team efforts by combining additional detailed, in situ data collection with radiance modeling to validate products under a wide variety of weather and surface conditions. Our work will include surface data collection at scales relevant for remote sensing validation, detailed mapping of surface and atmospheric conditions using Unpiloted Airborne Vehicles (UAVs), and use of radiative transfer modeling to assess algorithm performance in the polar regions for the following standard products: sea ice concentration, sea ice temperature, and snow depth on sea ice. The resulting error assessment and statistics will address new product applications such as data assimilation, climate model evaluation, and model boundary conditions that require greater understanding of the magnitudes and physical sources of errors. The data and results will also provide input needed for algorithm adjustments and enhancements to optimize the AMSR products.