Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation
Why this work is in the frame
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Bibliographic record
Abstract
One of the most important impacts of a future warmer climate is the projected increase in the frequency and intensity of extreme \nrainfall events. This increasing trend in extreme rainfall is seen in both the observational record and climate model projections. However, a \nthorough review of the recent scientific literature paints a complex picture in which the intensification of rainfall extremes depends on a \nmultitude of factors. While some projected rainfall indices follow the Clausius-Clapeyron relationship scaling of an ∼7% increase in \nrainfall per 1°C of warming, there is substantial evidence that this scaling depends on rainfall extremes frequency, with longer return \nperiod events seeing larger increases, leading to super Clausius-Clapeyron scaling in some cases. The intensification of extreme rainfall \nevents is now well documented at the daily scale but is less clear at the subdaily scale. In recent years, climate model simulations at a finer \nspatial and temporal resolution, including convection-permitting models, have provided more reliable projections of subdaily rainfall. \nRecent analyses indicate that rainfall scaling may also increase as a function of duration, such that shorter-duration, longer return period \nevents will likely see the largest rainfall increases in a warmer climate. This has broad implications on the design and the use of rainfall \nintensity–duration–frequency (IDF) curves, for which both an overall increase in magnitude and a steepening can now be predicted. This \npaper also presents an overview of measures that have been adopted by various governing bodies to adapt IDF curves to the changing \nclimate. Current measures vary from multiplying historical design rainfall by a simple constant percentage to modulating correction factors \nbased on return periods and to scaling them to the Clausius-Clapeyron relationship based on projected temperature increases. All of these \ncurrent measures fail to recognize a possible super Clausius-Clapeyron scaling of extreme rainfall and, perhaps more importantly, the \nincreasing scaling toward shorter-duration rainfall and the most extreme rainfall events that will significantly impact stormwater runoff in \ncities and in small rural catchments. This paper discusses the remaining scientific gaps and offers technical recommendations for practi- \ntioners on how to adapt IDF curves to improve climate resilience
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it