REASoN Multi-Resolution Snow Products for the

Hydrologic Sciences

University of California, Santa BarbaraUniversity of California, Merced

• Long term commitment for snow remote sensing products– Mandate to work with applications community

UC Merced team

• Roger Bales– 4 yrs with Regional Earth Science Applications Center

(RESAC)

• Bob Rice, research scientist• Programmer• Grad student for modeling & analysis

Data access via www

http://hydis.hwr.arizona.edu/resac

1995-2001 on CD

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

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

Applications planAim: connect the snow remote sensing products w/

applications in water resourcesApproach:– 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

Sierra Nevada 1998 SCA animation

Red: cloudsBlack: no snowGreyscale: SCA

R. Davis, CRREL

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 usinghypsometric 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

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

Rio Grande SCA & SWE: average for March

1995 1998 1999 2000 2001 20021996 1997

SCA

SWE

National Operational Hydrological Remote Sensing Center (NOHRSC)

• AVHRR(Advanced Very High Resolution Radiometer) -Available since 1986-1-km resolution-fractional snowcover-blended SWE product

MODIS(Moderate Resolution Imaging

Spectroradiometer) snow cover, western U.S.

Image Color Legend:

white snow

pink cloud

grey no data / night

green snow/cloud free land

blue water

-Available since 2000/2001-1-km spatial resolution-36 bands, 0.620-14.385 m-Binary mapping

Western Snow Conference- 2005

Workshop (3hrs.)

Objectives• Introduce project• Generate interest• Initiate dialogue between research and apps

communitiesOverriding Objective • generating a demand and usefulness for RS

products

*User prospective on Remote Sensing • (DWR rep 10 min?)