Cold‐Air Pooling and Temperature‐Elevation Mapping in a Colorado Watershed

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Abstract
Near‐surface air temperature grids are important environmental model forcings. In narrow mountain valleys, most gridded products are too coarse to resolve variability across slopes, so regional studies often map temperature across terrain following locally determined lapse rates. However, lapse rate approaches are complicated by patterns such as cold‐air pooling (CAP), which decouples the valley floor from upper slopes. We used a network of temperature sensors distributed across Colorado's East River watershed to characterize local CAP using empirical orthogonal function decomposition and a topographic algorithm. We then compared three approaches to map observed temperatures across terrain: a two‐station lapse rate, a lapse rate fit to a dense station network, and a CAP‐aware scheme which treated upper slopes separately from the valley floor. The CAP‐aware scheme reduced pooled root mean square error (RMSE) in predicted daily‐minimum temperatures () to 0.9°C, compared to 5.6°C and 1.6°C for the other two approaches, and an application with only a few local weather stations retained skill despite low sensor density (1.1°C). When used to construct 800 m grids, the CAP‐aware approach reduced pooled RMSE compared to PRISM (1.1°C vs. 3.8°C), even when only a few stations were used (1.9°C). When the best and worst performing approaches were mapped to a 100 m grid to force a regional hydrologic model, early summer cumulative basin snow water equivalent differed by 111% between runs, indicating strong sensitivity to melt season temperature input. Finally, analysis across Colorado state suggests CAP effects are widespread among SNOTEL observations.

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