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Improving Seasonal Drought Predictions in the Western USA: Developing and Evaluating an Ensemble Snow Modeling Framework in the Community Hydrologic Prediction System (CHPS)

NIDIS Supported Research
NIDIS-Supported Research
Main Summary

The predictability of hydrologic drought depends in large part on land-surface memory; in particular, the capability to simulate the seasonal evolution of snow and soil moisture. The skill of seasonal drought predictions in the western USA is therefore intimately linked to the validity of hydrologic and land-surface models that are used to produce the predictions. The goal of this research is to improve predictions of hydrologic drought in the western USA; specifically to both improve model representations of snow processes and quantify uncertainty in snow simulations. This research focuses on snow because a large amount of predictability in seasonal streamflow in the western USA is derived from knowledge of the accumulated snowpack.

Research Snapshot

Principal Investigator(s)
Martyn Clark, National Center for Atmospheric Research
Project Funding
Modeling, Analysis, Predictions, and Projections (MAPP) FY 2011
Focus Areas (DEWS Components)
Related Topics

Key regions

Research Scope