Task 224

Improving NOAA/NWS River Forecast Center Decision Support with NASA Satellite and Land Information System Products

Principal Investigator(s):

S. Yatheendradas


C. Peters-Lidard

Last Updated:

October 26, 2012 15:25:50

Description of Problem

The overarching goal is to demonstrate improved accuracy in runoff, stream flow, and flood monitoring and simulation that result from the combination of NASA infrastructure of snow data (MODIS) and model (LIS), with operational NOAA National Weather Service (NWS) River Forecast System (NWSRFS) Decision Support Tools (DST). The objectives are to engineer and integrate NASA satellite- and model-derived land surface products, through the Land Information System (LIS), into NWSRFS DST component models. The specific science question we investigated is whether adjusting modeled snow area with MODIS estimates improves modeled streamflow.

Scientific Objectives and Approach

This work leveraged ongoing NASA/NOAA collaborative research toward the integration of LIS and NWSRFS components (called LIS-RFS), mainly the Sacramento Soil Moisture Accounting (SAC-SMA) and SNOW17 models. With inputs from NOAA/NWS/OHD, NASA/GSFC continuously evaluated the system at successive software integration levels and benchmarked the Distributed Model Intercomparison Project II (DMIP2) Western snow basins in a retrospective simulation mode focusing on the assimilation of NASA remotely sensed MODIS snow covered fraction product. We also note possible snow masking effect under vegetation canopy present in almost any satellite snow product and so compare against assimilating the Snow Data Assimilation System (SNODAS) analysis product that is apparently free from this effect. SNODAS assimilates observations from satellite, airborne passive gamma-ray sensors and ground stations into a physically based, spatially-distributed energy- and mass-balance snow model forced by downscaled output from Numerical Weather Prediction models and gridded precipitation.


The project is in the final stages with a publication being written up that is expected to be submit soon. Preliminary analysis indicates no significant improvement in streamflow from adjusting modeled snow area with MODIS data, and we are conducting final detailed investigations into different aspects of the streamflow response. Adjusting modeled snow area with SNODAS data also shows similar conclusions, seemingly indicating in overall a minor information content in snow area extent for streamflow improvement as against other snow variables like SWE (Snow Water Equivalent).

Task Figures

Fig. 1 – Preliminary analysis for a sample Water Year 2004 for the DMIP2 Western snow-dominated uncalibrated Carson basin: Bottom row subplots show means and standard deviations against streamflow of improvements of assimilation against control for the discharge residuals (i.e., simulated-observed). Top row is basin SWE for different cases: SNODAS, Control, NWS operational MOD code, and finally assimilations where melt-time under canopy snow is considered by disabling assimilation below observed fractional snow area values of 100% and 50% respectively. Middle row is similar to top row but for streamflow, and gaged observations instead of SNODAS. Bottom row early melt season discharge residual improvements (shown only for the 100% case) seem to be positive for months when SWE generally increases.