The High-resolution Urban Meteorology for Impacts Dataset - HUMID

We have explicitly included representation of spatial meteorological variability over urban areas in the contiguous United States (CONUS) as compared to other observation-only gridded meteorology products by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather.

Further, we include in situ meteorological observations such as local mesonets to bias correct the HRLDAS output, creating a model-observation fusion product. The data spans 1 January 1981 to 31 December 2018, covering all of CONUS at 1 km grid spacing. The dataset includes daily maximum, minimum, and mean values for a variety of temperature estimates such as 2 m temperature, skin temperature, urban temperatures, as well as specific humidity and surface energy budget terms.