Dynamically Downscaled Hourly Future Weather Data for Energy Modeling
This dataset provides hourly future weather data for energy modeling applications. It is primarily based on the output of a regional climate model (RCM), i.e., the Weather Research and Forecasting (WRF) model version 3.3.1. The WRF simulations are driven by the output of a general circulation model (GCM), i.e., the Community Climate System Model version 4 (CCSM4).
The files are provided in EPW format, which can be read or translated by more than 25 building energy modeling programs (e.g., EnergyPlus, ESP-r, and IESVE), energy system modeling programs (e.g., System Advisor Model (SAM)), indoor air quality analysis programs (e.g., CONTAM), and hygrothermal analysis programs (e.g., WUFI). The dataset contains 13 weather variables: Dry-Bulb Temperature, Dew Point Temperature, Relative Humidity, Atmospheric Pressure, Horizontal Infrared Radiation Intensity from Sky, Global Horizontal Irradiation, Direct Normal Irradiation, Diffuse Horizontal Irradiation, Wind Speed, Wind Direction, Sky Cover, Albedo, and Liquid Precipitation Depth.
The weather data is available for two emissions scenarios, RCP4.5 and RCP8.5, and spans two 10-year time slices in the future, 2045 - 2054 and 2085 - 2094. This dataset offers a spatial resolution of 12 km by 12 km with extensive coverage across most of North America. Due to the enormous size of the entire dataset, in the first stage of its distribution, we provide 20 years of future weather data for the centroid of each Public Use Microdata Area (PUMA), excluding Hawaii. PUMAs are non-overlapping, statistical geographic areas that partition each state or equivalent entity into geographic areas containing no fewer than 100,000 people each. The 2,378 PUMAs as a whole cover the entirety of the U.S. A file named "PUMA information.csv" is included with the dataset, containing the PUMA number, PUMA name, latitude, longitude, elevation, and time zone of all PUMA centroids. Users can reference this file to find the PUMAs corresponding to their locations of interest.
Contact: Zhaoyun Zeng [email protected]
