NSF award 2531008 · University of California-Los Angeles

CAIG: Deep Learning-based Stochastic Models for Large-Scale Atmospheric Variability and Extreme Events

Final report due

28 January 2029

in 833 days · The award ends on 30 September 2028.

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award ending 2028-09-30 · Research.gov
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Extension request16 Aug 2028in 668 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2028in 703 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2029in 833 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2029in 833 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2029in 833 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 30 September 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2029.

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Award card

Award number: 2531008
Period of support: 1 Oct 2025 – 30 Sep 2028
Amount: $798,840
Awardee: University of California-Los Angeles, LOS Angeles, CA
Program: GEO CI - GEO Cyberinfrastrctre
Directorate: GEO

Abstract

Extreme weather events—such as heat waves, cold snaps, wildfires, and heavy rainfall—pose increasing risks to society. These events are often driven by shifts in powerful atmospheric jet streams, which typically flow from west to east across the midlatitudes but can sometimes meander dramatically north or south. While recent advances in AI have shown promise in improving weather forecasts, many AI models still…

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