Prediction of snow water equivalent from remote sensing and a land surface model
 
Collaborators on this project include Marc Stieglitz and Judith Curry (Georgia Tech.), Dorothy Hall (NASA), and Nicole Smith (Harvard).
For creation of the PASR product, snow depth observations were used with the NSIPP model to reconstruct how much snow must have fallen to create the observed snow depth. In a similar manner, snow water equivalent available for spring runoff can be predicted by assimilating measurements of snow cover and other remote sensing observations into the NSIPP catchment-based land surface model. This project is in the development phase where various data assimilation methods are being tested against ground-based measurements in Alaska.