NSF award 2621863 · University of California-Los Angeles

EAGER: Understanding Wildfire Smoke Transport though Satellite Observations, Machine Learning, and Numerical Modeling

Final report due

28 November 2028

in 772 days · The award ends on 31 July 2028.

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Dates this award owes

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Decide about an extension2 Apr 2028in 532 days
award ending 2028-07-31 · Research.gov
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Extension request16 Jun 2028in 607 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Jul 2028in 642 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Nov 2028in 772 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Nov 2028in 772 days
award ending 2028-07-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Nov 2028in 772 days
award ending 2028-07-31 · 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 31 July 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 November 2028.

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Award card

Award number: 2621863
Period of support: 15 Aug 2026 – 31 Jul 2028
Amount: $337,405
Awardee: University of California-Los Angeles, LOS Angeles, CA
Program: ESH-Earth System Hazards, Physical & Dynamic Meteorology
Directorate: GEO

Abstract

The transport of wildfire smoke is dependent on atmospheric factors, topography and the characteristics of the fire itself. Current numerical forecast models struggle with smoke because the fire can flare up or subside on short time scales and the atmospheric conditions that guide the smoke are on small spatial scales. This project involves the development of a new, observation-based framework using machine learning…

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