1. REASoN Multi-Resolution Snow Products for the Hydrologic Sciences University of California, Santa Barbara University of California, Merced Long term commitment for snow remote sensing products –Mandate to work with applications community

2. UC Merced team Roger Bales –4 yrs with Regional Earth Science Applications Center (RESAC) Bob Rice, research scientist Programmer Grad student for modeling & analysis

3. Data access via www http://hydis.hwr.arizona.edu/resac 1995-2001 on CD

4. RESAC output & outcomes –fractional SCA product for Colorado & Rio Grande basins 1995-2002 –blended SWE product: interpolated SNOTEL & AVHRR SCA –near-real-time product delivered via map server & archived product via CD –SWE volume estimates evaluated by SRP (AZ), CO, NM –SWE assimilation into PRMS for upper Salt & upper Rio Grande (in progress) –formal user workshop to introduce & evaluate products; multiple stakeholder meetings

5. Expected REASoN outcomes –create new demands for RS snow products within water resources community –demonstrate usefulness of RS products in various ways to applications community –demonstrate improved ways of using RS products for hydrologic forecasts & water resources decisions –enhance dialog between research & applications communities on the topic of snow RS products

6. Applications plan Aim: connect the snow remote sensing products w/ applications in water resources Approach: –cooperative efforts w/ research community –specify & analyze snow products –develop & implement strategies to use the products for both model input & model evaluation –working directly w/ applications community –develop approaches to use & evaluate products in existing Decision Support Systems –assimilate products into available snowmelt runoff models to do hindcasts (USGS, Scripps, LLNL, LBL…) –use products to make forecasts of basin-scale runoff

7. Sierra Nevada 1998 SCA animation Red: clouds Black: no snow Greyscale: SCA R. Davis, CRREL

8. 1 2 3 4 5 AVHRR bands Geographic mask Thermal mask Masked fractional snow covered area map Composite cloud mask Build Cloud Masks using several spectral- based tests Snow map algorithm output: mixed clouds, high reflective bare ground, & sub-pixel snow cover Execute sub-pixel snow cover algorithm: AVTREE using bands 1,2,3 (reflectance) as input Build thermal mask Application of cloud, thermal & geographic masks to raw AVTREE output Scene evaluation: degree of cloud cover Coverage over study basins Topography Ground measured snow water equivalent Total snow water equivalent map Interpolate using hypsometric method Combine sub-pixel SCA and ground-based interpolated SWE to produce total basin water maps Execute atmospheric corrections, conversion to engineering units using AVREF AVHRR (HRPT FORMAT) pre-processed at UCSB [NOAA-12,14,16] Snow cover mapping process Georegister image using GEOREG script. x

9. Product design studies (forward and backward) SCA map cloud mask aggregating subsetting canopy corrections SWE/SCA blending NOHRSC products ground data SNOTEL Snowcourse Modeling (PRMS..) applications community evaluation MODIS 500m resolution Fractional snow cover AVHRR

10. Rio Grande SCA & SWE: average for March 19951998199920002001200219961997 SCA SWE

11. National Operational Hydrological Remote Sensing Center (NOHRSC) AVHRR(Advanced Very High Resolution Radiometer) -Available since 1986 -1-km resolution -fractional snowcover -blended SWE product

12. MODIS (Moderate Resolution Imaging Spectroradiometer) snow cover, western U.S. Image Color Legend: whitesnow pinkcloud greyno data / night greensnow/cloud free land bluewater -Available since 2000/2001 -1-km spatial resolution -36 bands, 0.620-14.385 m -Binary mapping

13. Western Snow Conference- 2005 Workshop (3hrs.) Objectives Introduce project Generate interest Initiate dialogue between research and apps communities Overriding Objective generating a demand and usefulness for RS products *User prospective on Remote Sensing (DWR rep 10 min?)