Spatially Distributed, Physically Based Assimilation of Satellite, Airborne, Surface, and Atmospheric Model Data

Spatially Distributed, Physically Based Assimilation of Satellite, Airborne,

Surface, and Atmospheric Model Data

to Estimate Snow Water Equivalence over Large Regions

Don Cline1 and Tom Carroll1

To support routine streamflow forecasting in seasonally snow-covered regions, estimates of the areal

extent of snow cover (AESC) and snow water equivalence (SWE) must be provided to regional

forecasters in a timely manner. Historically, these estimates have been made by classifying remotely

sensed data into maps of snow cover, and by interpolating, using various methods, satellite-, air-

borne- and surface-based observations of snow water equivalence. These methods cannot readily

utilize other snowpack observations, such as snow depth, which is routinely observed at a large

number of sites, or snow albedo, which can be observed from remote sensing, or other hydrometeo-

rological observations that indirectly provide information relevant to snowpack conditions. A com-

prehensive mechanism is needed to translate available, diverse observations that are irregularly dis-

tributed in time into routine, timely estimates of SWE and AESC. To address this problem, the

National Operational Hydrologic Remote Sensing Center is currently developing an operational data

assimilation framework for spatially distributed, physically based snow modeling to take maximum

advantage of available operational satellite, airborne, surface, and atmospheric model data over large

regions. The system consists of four major components: 1) data ingestion, quality control, and man-

agement, 2) a physical snow modeling basis for data assimilation, 3) data assimilation procedures

and decision criteria, and 4) on-line validation. We will first provide an overview of our approach to

developing this snow information assimilation system. We will then discuss in detail the data used in

the assimilation scheme and describe several of the problems associated with using these data.

1 National Operational Hydrologic Remote Sensing Center, National Weather Service, 1735 Lake Drive West,

Chanhassen, Minnesota 55317, USA