The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States.

ABSTRACT: Many current gridded surface meteorological datasets are inadequate for quantifying near-surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981-2018 over the CONUS at daily te

SUBMITTER: Newman AJ 

PROVIDER: S-EPMC11618800 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature