A new approach to satellite-based estimation of precipitation over snow cover

Abstract

Current satellite-based remote-sensing approaches are largely incapable of estimating precipitation over snow cover. This note reports a proof-of-concept study of a new satellite-based approach to the estimation of precipitation over snow-covered surfaces. The method is based on the principle that precipitation can be inferred from the changes in the snow water equivalent of the snowpack. Using satellite-based snow water equivalent measurements, we derived daily precipitation amounts for the northern hemisphere for three snow-accumulation seasons, and evaluated these against independent reference datasets. The new precipitation estimates captured realistic-looking storm events over largely un-instrumented regions. However, the data are noisy and, on a seasonal scale, the amount of precipitation is believed to be underestimated. Nevertheless, current uncertainty in snow measurements, albeit large (50–100%), is still lower than direct precipitation measurements over snow (100–140%) and therefore this approach is still useful. The method will become more feasible as the quality of remotely sensed snow measurements improves.

Acknowledgements

We thank Dr James Foster for helpful discussions and Dr Wade Crow for reviewing an earlier version of the paper and useful suggestions. We also want to thank two anonymous reviewers for their helpful comments. Computing resources were provided by the NASA Center for Climate Simulation.

Funding

This research was supported by the NASA Earth System Data Records Uncertainty Analysis Program (Martha E. Maiden) [grant number NNX11AO22G].