Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets

Summary

This comprehensive review synthesises evidence on the performance of 63 gridded climate datasets (spanning ground-based observations, satellite imagery, and reanalysis products) used in hydrological modelling across North America and globally. Rather than identifying a single optimal dataset, the authors distil common selection principles from 29 recent intercomparison studies, establishing that dataset performance varies by region, terrain complexity, and underlying station density. The findings provide hydrological investigators with structured guidance for justifying climate forcing data choices in model applications.

UK applicability

UK hydrologists and agricultural water-resource planners may benefit from the review's framework for dataset evaluation, though recommendations were derived primarily from CONUS and continental datasets. UK-specific gridded climate products (such as those from the UK Met Office or national reanalysis) would require separate validation against the principles identified here, particularly given the UK's complex topography and maritime climate influences.

Key measures

Dataset characteristics (spatial resolution, temporal coverage, latency, accessibility); performance metrics from prior intercomparison studies; accuracy relative to station density and terrain complexity

Outcomes reported

The study compiled and evaluated 63 gridded climate datasets (ground-based, satellite, and reanalysis sources) across precipitation, temperature, humidity, wind speed, and solar radiation variables. It synthesised findings from 29 recent intercomparison studies to provide evidence-based recommendations for dataset selection in hydrological analyses.

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