In brief
Rain gauges record precipitation at various sub-hourly intervals, which are commonly aggregated into standard clock-hour bins for hydrological analysis. When intense convective bursts cross interval boundaries, fixed-window aggregation splits the peak volume across consecutive hours, artificially lowering the recorded maximum intensity. By conducting controlled coarsening experiments across systematically varied phase offsets, this study isolates the sampling bias caused purely by observation cadence and window timing. The results show how recording frequency governs the apparent magnitude of hourly extremes independently of physical meteorological variability.
Contribution
A controlled coarsening framework across systematic phase offsets that decouples recording cadence and window-alignment artifacts from true physical precipitation variability in hourly extreme diagnostics and fixed-duration maxima (AMS60).
Key finding
Fixed-interval clock-hour binning consistently attenuates peak hourly intensities when storm bursts are split across reporting boundaries. Quantifying this cadence-induced bias across phase offsets provides empirical bounds for sampling adjustment factors and clarifies observational uncertainties in sub-daily hydrological risk assessment.
Models and data
Distinctive research elements
Models and methods
- Controlled coarsening experiment
- Phase-offset sensitivity analysis
- Sampling adjustment factor evaluation
Data and evaluation
- Sub-hourly rain-gauge networks
- AVAMET weather station network
- High-resolution precipitation archives
The mechanism of cadence and window-boundary splitting
In short-duration, high-intensity precipitation events, rainfall volume is heavily concentrated over minutes rather than evenly spread over an hour. When gauge observations are binned into standard clock-hour windows (e.g., 10:00 to 11:00), the timing of the event relative to that boundary determines how the burst is recorded. An identical 60-minute storm can yield vastly different peak intensities depending solely on whether it falls neatly within a single bin or spans across two adjacent intervals. This window-splitting effect attenuates observed maxima and distorts statistical extreme-value metrics without any underlying physical change in rainfall intensity.
Controlled coarsening across systematic phase offsets
To isolate sampling artifacts from atmospheric variation, the study employs a controlled coarsening protocol applied to high-resolution sub-hourly gauge records. By advancing the aggregation window in discrete steps across the full cycle of phase offsets, the experiment measures the exact variability in annual maximum series (such as AMS60) and extreme thresholds attributable solely to reporting cadence. This benchmark establishes the mathematical and empirical relationship between native temporal resolution, arbitrary bin start times, and historical adjustment factors.
Implications for hydrological design and hazard screening
The findings emphasize that differences in extreme precipitation estimates across datasets often stem from heterogeneous temporal support rather than genuine regional climate differences. For flood risk screening, urban drainage infrastructure sizing, and the calibration of intensity-duration-frequency (IDF) curves, accounting for cadence bias prevents systematic underestimation of peak design storms. Furthermore, these benchmarks clarify the observational limits against which satellite products and atmospheric reanalyses can be reliably validated.
Cite this work
BibTeX
@article{semper2026reporting,
title = {How reporting cadence shapes hourly precipitation extremes},
author = {Marc Semper and Manuel Curado and Jose F. Vicent and Leandro Tortosa},
journal = {Journal of Hydrology},
year = {2026},
eid = {136555},
doi = {10.1016/j.jhydrol.2026.136555}
}Always check the publisher record for final volume, issue and page information before citing.