SBIR/STTR Research Award

Commercial Solutions for Weather Forecasting

Award identifier fd6c0829e047740e9513f6b260efeefb514a69dea445ae8a4357ed5e5b1dde91Awarding agency Department of Defense · Air Force

Award amount

$49,635

Program and phase

SBIR · Phase I

Award year

2019

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
Cook, Ashton Robinson
Proposal award date
2019-01-07
Contract end date
2020-01-07
UEI
CGDKNKXSMNJ3
Solicitation number
18.2
Topic code
AF182-001

Research abstract

Exploitation of weather and climatological information has historically provided significant (and at times decisive) advantages for Air Force and Department of Defense missions (e.g., WWII, 2003 Iraq, etc.) Current and short-term (0-7 day) and climatological (long-term average) weather information near the geographic locations of missions have often been the basis for these operations. However, a critical gap exists regarding extended-range forecast information for high-impact weather (occurring in the monthly to seasonal timeframe). This potentially valuable information can assist in extended-range mission planning while also mitigating impacts from severe and extreme weather. To address this need, WeatherDeep proposes to develop “L-model� as a flexible software platform for providing these types of extended-range forecasts. The L-model builds upon machine/deep learning concepts developed by Dr. Ashton Cook to provide forecasts of high-impact weather with potential lead times of 10-12 months. Initial products forecast tornadoes, damaging thunderstorm winds, and hail, although these products will be expanded to forecast additional perils impacting Air Force and Department of Defense missions (e.g., wildfires, tropical cyclones, dust storms, etc.)

Technology keywords

Not reported

Awards with the same topic code

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Agency intelligence

Department of Defense

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