A 40-year high-resolution gridded meteorological dataset derived from station observations in the Reynolds Creek Experimental Watershed

A 40-year gridded meteorological forcing dataset spanning the water years from 1 October 1983 to 30 September 2023 was compiled for the Reynolds Creek Experimental Watershed (RCEW) in southwest Idaho, USA. This Reynolds Creek Long-Term (RCLT) dataset consists of hourly, 10 m resolution grids of air temperature, vapor pressure, precipitation mass and phase, incoming shortwave and longwave radiation, visible and infrared snow albedo, and wind speed and direction. These variables were interpolated and calculated from hourly measurements from the dense meteorological station network within the mountainous 239 km2 RCEW, which contains elevations that span the historical winter rain-to-snow transition. The observations are foundational for many ecological and hydrological Land Surface Models (LSMs) used in research and operational applications. Additionally, an example use case is presented in which we show how the snow-dominated area of the basin has evolved over the data record. This 13 TB dataset, stored in cloud-optimized Zarr format, enables future model development, benchmarking, uncertainty analyses of existing models, independent validation of gridded atmospheric reanalysis datasets, and novel investigations of hydroclimatic variability across snow-dominated semi-arid environments. Data access is available via the following repository: https://doi.org/10.15482/USDA.ADC/30199954 (Hedrick et al., 2025).

Hedrick, A. R., Stairs, B., Williams, C. J., Meyer, J., McNamara, J. P., and Kormos, P.: A 40-year high-resolution gridded meteorological dataset derived from station observations in the Reynolds Creek Experimental Watershed, Earth Syst. Sci. Data, 18, 5531–5543, https://doi.org/10.5194/essd-18-5531-2026 , 2026.

https://doi.org/10.15482/USDA.ADC/30199954

The gridded dataset in its published form is at hourly temporal and 10 m spatial resolution, which was determined to be optimal for users requiring high resolution forcing data while also being suitable for disk storage. NetCDF files, though standard format for meteorological data, can become unwieldy when file sizes become too large, which is mitigated by the cloud-optimized Zarr format (Miles et al., 2023) that can be read by programming libraries in python, R, C, and Java. Nevertheless, users that desire a coarser spatiotemporal RCLT dataset have two options for decreasing resolution. The simplest approach would be to read the provided high resolution files, resample to desired resolution using mean or sum values across space and time, and save to a new NetCDF file. A slightly more accurate approach would be to install SMRF locally, create a model setup file at the desired spatial resolution, edit the configuration files to define the coarser temporal resolution, and run the distribution code. However, this approach will require detailed knowledge of the software and is not recommended for most users. An example SMRF configuration file for a single water year and all station data CSV files organised by water year are provided in the Supplementary Materials.

Accessing temporal and spatial slices of this 13 TB dataset is straightforward as it is stored as cloud-optimized Zarr-formatted files and hosted by the open-access Ag Data Commons data repository ( https://doi.org/10.15482/USDA.ADC/30199954 , Hedrick et al., 2025) maintained by the USDA National Agricultural Library ( https://agdatacommons.nal.usda.gov , last access: 22 July 2026). Users may download either the entire 40-year record or by individual water year (∼325 GB yr−1) through the linked Globus web interface. It is also recommended that users work with the dataset on a High-Performance Computing (HPC) or Cloud environment with parallel processing capabilities. An example jupyter notebook script for loading the Zarr-formatted data using the python Xarray package is provided in the repository. The coordinates are stored as projected coordinates in UTM Zone 11 using the WGS84 geodetic reference system. At 10 m spatial resolution, the model domain shape is 3010 (north–south) by 1602 (east–west) pixels. The time domain is 350 640 total time steps, resulting in 1.7 trillion total stored values per variable, or 20.3 trillion stored values across the entire dataset. A tagged release for the SMRF source code used to create this dataset is available at https://github.com/iSnobal/smrf/releases/tag/20250926 (last access: 22 July 2026; https://doi.org/10.5281/zenodo.21514687 , Meyer et al., 2025).