The objective of this project is to maintain, enhance, validate and refine the current suite of Terra and Aqua MODIS snow and sea ice algorithms to provide consistent, systematic measurements for science research, modeling, and for development of climate-data records of snow cover and sea ice surface temperature (IST). An overall accuracy of >95% accuracy will be achieved for the snow-cover products. Specifically, we will:
- improve snow/cloud and sea ice/cloud discrimination;
- improve snow algorithm operation under conditions of low illumination and in dense forest cover;
- perform a rigorous analysis of errors;
- improve and validate the snow-albedo algorithm;
- evaluate and validate the Aqua MODIS snow products;
- develop a monthly sea ice product.
The investigators have developed, along with outside colleagues, MODIS snow and ice products that are being used with increasing frequency in the scientific and modeling communities. The Terra MODIS snow products have an overall accuracy of ~93%, and the sea ice IST product has an error of <1.3 K. The products are used by modelers (see support letter from the Air Force Weather Agency).
Why should NASA fund us to continue producing these products? The present team is intimately familiar with the myriad of issues associated with maintenance and accuracy of the products and understands the details involved in preparing and implementing the code. Furthermore, the National Polar-orbiting Operational Environment Satellite System (NPOESS) snow and sea ice algorithms are largely based on the MODIS algorithms, so a smooth transition and continuity of long-term data record is ensured if we continue to maintain and refine the MODIS products.
The focus of this work will be to reduce or eliminate known sources of error in the algorithms. We will test, refine and validate the existing snow-albedo algorithm (or replace it as necessary). Through selective use of tests from the MODIS cloud-mask, we will improve snow/cloud discrimination, the largest source of error.
We will continue working with the science and modeling communities and National Snow and Ice Data Center (NSIDC) personnel to further ensure that the products meet user needs, giving special attention given to:
- issues raised by the user community;
- impacts due to changes in sensor performance;
- effects that input-product refinements and changes may have on the continuity of the data set.
We expect to achieve a >95% overall accuracy in the MODIS snow-cover maps. The products will be suitable for answering a variety of scientific questions about the dynamic variability of snow and ice cover and the relationship to climate, and for modeling and data-assimilation. The products will also be suitable as vital components of CDRs of snow and sea ice.
