Global snow water storage; why should we be concerned with its estimation and how best should we measure it?

Richard Kelly
Goddard Earth Science and Technology Center,
University of Maryland Baltimore County, Baltimore, 21250
and
NASA Goddard Space Flight Center, Greenbelt, Maryland 21770

Snow is an important storage component of the hydrological cycle and its influence is evident both in terms of river basin runoff and climate change dynamics. In many parts of the world snow contributes a very high percentage of total annual water supply and the allocation of limited water resources has significant economic and policy consequences. Furthermore, snow is considered a renewable resource but in a changing climate system that is placing considerable pressures on regional water supplies, significant questions are emerging about how best to use this valuable water supply. It has been shown that snow cover can affect directly climate dynamics and so our ability to estimate global snow coverage and volumetric storage of water in seasonal and permanent snow packs impacts on our ability to monitor climate and climate change and to test climate model simulations. Thus, in a changing global environment, there are compelling reasons why we need to be able to map and monitor the distribution of snow storage through winter seasons and from year to year.

This presentation will show how the work of Alfred T.C. Chang has contributed to our understanding of snow storage measurements using indirect or remote sensing methods. Snow depth and mass have been measured historically using in situ ground surveys which are accurate at a very local scale but are not always representative at the regional scale. Al's experimental and modeling research in the 1970s and 1980s paved the way for our understanding of how to use microwave observations to estimate snow water equivalent at the regional and global scales. His research formed the basis of global snow storage estimates from satellite instruments and is currently the method used with state-of-the-art satellite microwave observations from the Advanced Microwave Scanning Radiometer – EOS. The estimates are more internally consistent than in situ measurements and can provide daily ‘snapshots' of snow storage around the world. While this is not the end of the story, as far as passive microwave estimation methods are concerned, Al's research provided an invaluable reference against which future approaches will be tested. Furthermore, the approach pioneered by Al forms the basis of more sophisticated methods and this presentation will illustrate different approaches currently under investigation and offer some observations on how best we can estimate snow storage globally in the future.

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