SBIR/STTR Research Award

Extending the Analog Ensemble Method for Satellite Observations

Award identifier 738b47cc59af9c5a04427426d284f09d84adef1764014041129e67a5bc4c5effAwarding agency Department of Defense · Army

Award amount

$196,994

Program and phase

STTR · Phase I

Award year

2024

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Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
CREARE LLC
Proposal award date
2024-03-01
Contract end date
2024-09-01
UEI
JDKYAKDT4TT6
Solicitation number
23.B
Topic code
A23B-T020

Research abstract

The army needs probabilistic weather forecasts for effective mission planning and preparation. Current DoD weather capabilities use deterministic numerical weather prediction (NWP) models to forecast weather. This means the model may not predict rain when thereÆs a 30% chance of rain, for example. The most common variant of the Analog Ensemble (AnEn) method can provide forecast probabilities using historic NWP modelĀ runs (existing DoD capabilities) and in-situ observations. However, for remote or denied regions, in-situ observations are not available, and satellite observations need to be used instead. As such, the AnEn methods must be adapted to use satellite observations. Creare and our Pennsylvania State University collaborators propose to develop AnEn-Sat, a software framework for producing probabilistic weather forecasts from deterministic NWP model runs and satellite observations.

Technology keywords

Not reported

Agency intelligence

Department of Defense

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