All figures used in the journal article are in netCDF format. This dataset is associated with the following publication: Sims, A., K. Alapaty , and S. Raman. Sensitivities of Summertime Mesoscale Circulations in the Coastal Carolinas to Modifications of the Kain–Fritsch Cumulus Parameterization. Monthly Weather Review. American Meteorological Society, Boston, MA, USA, 145(11): 4381-4399, (2017).

Data for all tables and figures are in netCDF format. This dataset is associated with the following publication: Glotfelty, T., K. Alapaty, J. He, P. Hawbecker, X. Song, and G. Zhang. The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI): Development, Evaluation, and Initial Application. Monthly Weather Review. American Meteorological Society, Boston, MA, USA, 147(5): 1491-1511, (2019).

Data for all tables and figures are in netCDF format. This dataset is associated with the following publication: Glotfelty, T., K. Alapaty, J. He, P. Hawbecker, X. Song, and G. Zhang. The Weather Research and Forecasting Model with Aerosol–Cloud Interactions (WRF-ACI): Development, Evaluation, and Initial Application. Monthly Weather Review. American Meteorological Society, Boston, MA, USA, 147(5): 1491-1511, (2019).

This archive contains daily surface meteorological (METDATA) data for the Continental United States at 4-km (1/24-deg) resolution. The meteorological variables are maximum/minimum temperature, precipitation amount and duration, maximum/minimum relative humidity,downward shortwave solar radiation, wind speed and direction, and specific humidity. The method utilized here combines desirable spatial attributes of gridded climate data from PRISM and desirable temporal attributes of regional-scale reanalysis and daily gauge-based precipitation from NLDAS-2 to derive a spatially and temporally complete high resolution gridded dataset of surface meteorological variables for the continental US for 1979-present. Validation of this data suggests that it can serve as a suitable surrogate for landscape-scale ecological modeling across vast unmonitored areas of the US. For more information visit: http://metdata.northwestknowledge.net/

This archive contains daily surface meteorological (METDATA) data for the Continental United States at 4-km (1/24-deg) resolution. The meteorological variables are maximum/minimum temperature, precipitation amount and duration, maximum/minimum relative humidity,downward shortwave solar radiation, wind speed and direction, and specific humidity. The method utilized here combines desirable spatial attributes of gridded climate data from PRISM and desirable temporal attributes of regional-scale reanalysis and daily gauge-based precipitation from NLDAS-2 to derive a spatially and temporally complete high resolution gridded dataset of surface meteorological variables for the continental US for 1979-present. Validation of this data suggests that it can serve as a suitable surrogate for landscape-scale ecological modeling across vast unmonitored areas of the US. For more information visit: http://metdata.northwestknowledge.net/

Excel file containing diurnal ensemble statistics of 2-m temperature, 2-m mixing ratio and 10-m wind speed. This Excel file contains figures for Figure 2 in the paper and worksheets containing all statistics for the 14 members of the ensemble and a base simulation. This dataset is associated with the following publication: Gilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259–12,280, (2015).

,[ NOTE – 2022/05/06: this dataset is superseded by an updated version https://doi.org/10.15482/USDA.ADC/1526433 ] The dataset contains 15-minute mean weather data from the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU) research weather station, Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) for all days in 2016. The data are from sensors deployed at standard heights over grass that is irrigated and mowed during the growing season to reference evapotranspiration standards. Sensors are duplicated at each height, and data from a duplicate sensor may be used to fill gaps in data from the primary sensor using appropriate regression relationships. Gap filling may also be accomplished using sensors deployed at one of the four large weighing lysimeters immediately west of the weather station. The primary paper describes details of the sensors used and methods of testing, calibration and use. The weather data include air temperature (C) and relative humidity (%), wind speed (m/s), solar irradiance (W m-2) and precipitation. Because the large (3 m by 3 m surface area) weighing lysimeters are better rain gages than are tipping bucket gages, the 15-minute precipitation data are derived for each lysimeter from changes in lysimeter mass. The land slope is <1% and flat. The mean annual precipitation is ~470 mm, the 20-year pan evaporation record indicates ~2,600 mm Class A pan evaporation per year, and winds are typically from the South and Southwest. The climate is semi-arid with ~70% (350 mm) of the annual precipitation occurring from May to September, during which period the pan evaporation averages ~1520 mm.,,

A zipped and tarred file which contains netCDF files needed to replicate all tables and figures shown in the referenced journal article. This dataset is associated with the following publication: Mallard, M., T. Spero, and S. Taylor. Examining WRF’s Sensitivity to Contemporary Land-Use Datasets across the Contiguous United States Using Dynamical Downscaling. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY. American Meteorological Society, Boston, MA, USA, 57(11): 2561-2583, (2018).