About $1.31M to the University of Alabama Tuscaloosa — 155 days from award date to start, using AI to unravel how marine heatwaves drive hurricane intensification
An award using AI to unravel the flood hazard created when marine heatwaves and hurricane intensification combine. The award date is 2026-07-30 while the start is 2027-01-01, a gap of 155 days, far longer than the median of 19 days across the records this site holds as of 2026-09-01.
Grant overview (primary data)
- Award amount$1,309,231
- RecipientUniversity of Alabama Tuscaloosa (Alabama)
- ProgramAI and Geosciences
- Period2027-01-01 〜 2029-12-31
- FunderU.S. National Science Foundation (NSF) / NSF
Key points
- Uses AI to unravel the flood hazard created when marine heatwaves and hurricane intensification combine.
- The award date is 2026-07-30 and the start is 2027-01-01, a gap of 155 days.
- Across the 120 NSF awards this site holds as of 2026-09-01, the gap has a median of 19 days and a mean of 32, so this one is far longer.
- Within the same 120, six records place the start before the award date and one places them on the same day.
- All data, models and software are to be made openly available, over a three-year period.
- The gap from award date to start runs a median of 19 days and a mean of 32, while this one runs 155, and six records start before the award date.
1A gap of 155 days between decision and start
The award date is 2026-07-30 and the start is 2027-01-01, 155 days apart. Among the 120 NSF awards this site holds as of 2026-09-01, the gap between award date and start has a median of 19 days and a mean of 32. This one runs far longer.
Within those same 120, the largest gap is 186 days and the smallest is minus 148. A negative value means the start date is placed before the award date, which happens on six records. On one record the two fall on the same day. In these records the day funding is decided and the day research begins are treated as separate things.
2Looking at where two phenomena overlap
What the research addresses is where marine heatwaves and rapid hurricane intensification coincide. The abstract notes that tropical cyclones can strengthen rapidly over unusually warm water, and that such fast changes leave coastal communities less time to prepare.
A hazard that neither phenomenon shows alone appears when they overlap. Beyond improving forecast accuracy, the subject is how to grasp the combination of two events. Among the stated outcomes is providing actionable risk information to decision-makers.
3Openness is built in
The abstract states that all data, models and software will be made openly available, and that graduate students and a postdoctoral researcher will be trained in AI and coastal hazard science.
Among the 120 NSF awards this site holds as of 2026-09-01, the obligated amount matches the estimated total on 86, and this award is one of them. The period runs three years, from 2027-01-01 to 2029-12-31. A plan beginning nearly half a year after funding is decided is a reminder to keep clear, when reading dates in the record, which of the two a date refers to.
Why it matters
In hazard assessment the overlap is harder to read than any single event. Research treating the combination of a persistently warm ocean and an arriving storm bears directly on the practical question of securing time to prepare. Working with award dates means allowing for a gap of up to nearly half a year between decision and start.
FAQ
Why the 155-day gap?
Can a start precede the award date?
Will the results be public?
Sources (primary)
Source: NSF Award Search (U.S. National Science Foundation, public domain). Amounts are the obligated amount. For privacy, we do not handle principal investigator names.
- NSF Award (original, official)
- NSF Award ID: 2616172