Snowmelt runoff, eScience, and the end of stationarity How do we build the knowledge and information...

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Snowmelt runoff, eScience, and the end of stationarity How do we build the knowledge and information base to provide clean, safe water for people and for ecosystems in the face of social and climate change? Specifically for snowmelt runoff in the mountain West … How will we ensure reliable water supply while maintaining acceptable flood risks, improving water quality and creating sustainable habitat? 1

Transcript of Snowmelt runoff, eScience, and the end of stationarity How do we build the knowledge and information...

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Snowmelt runoff, eScience, and the end of stationarity

• How do we build the knowledge and information base to provide clean, safe water for people and for ecosystems in the face of social and climate change?

• Specifically for snowmelt runoff in the mountain West …– How will we ensure reliable water supply

while maintaining acceptable flood risks, improving water quality and creating sustainable habitat?

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Manual measurement of SWE (snow water equivalent)

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Automated measurement with snow pillow

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A changing western snowpack?

Less snow? Earlier melt?

Service, R. F., As the West goes dry, Science, 20 Feb 2004

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36 37 38 39 40 41 42

1500

2000

2500

3000

3500

latitude, deg

ele

vatio

n, m

< -1%/yr-1% to -0.25%/yr±0.25%/yr0.25% to 1%/yr

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Pure endmembers,01 Apr 2005

100% Snow

100% Vegetation

100% Rock/Soil

MODIS image

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Model structure for MODIS snow-covered area and albedo (38 images/day × 300 days)

Basinmask

Provenance

Watershedinfo

MODIScloud mask

(48 bits)

MODIS 7 land bands (112 bits)

MODIS quality flags

Topography

MODIS snow cover and grain

size

MODISview

angles

Solarzenith,

azimuth

Snowfraction

albedoRMSerror

Vegfraction

Soilfraction

Shadefraction

Open water

fraction

Quality flag

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Snow-covered area and albedo, 2004

Snow Covered Area

Albedo

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=

X X [1– ]

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The Data Author’s Perspective: from data creation to data curation

Collect

Store

Search

Retrieve

Analyze

Present

• No “standard” environmental science computing environment– commercial packages (ArcGIS, IDL,

MATLAB, …)

– public packages/models (MM5, MODTRAN, …)

– locally-developed codes (C, Fortran)

• How do we get these programs to– communicate

– cooperate

without rewriting?

• And what about the Cloud?– “graduated outsourcing”

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So what do I want so I can do better?

• Easy integration and data quality checks for a variety of datasets– Surface measurements and remote sensing images– which are stored at different places in different formats

• Easy integration of tools– SQL Server, MATLAB, IDL, my own low-level code, and

even code for which I don’t have source

• A Cloud that looks like my laptop/desktop• A good way to store/access/view multidimensional

data (which are sometimes sparse)• A nice, geographic UI to get to the data• Ability to format output for a variety of analysis

tools (e.g, GeoTIFF, OpenDAP)