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Four-kilometer long-term regional hydroclimate reanalysis over the conterminous United States (CONUS)

| DOI: 10.5065/ZYY0-Y036

CONUS404 is a unique, high-resolution hydro-climate dataset appropriate for forcing hydrological models and conducting meteorological analysis over the conterminous United States. CONUS404, so named because it covers the CONterminous United States for over 40 years at 4 km resolution, was produced by the Weather Research and Forecasting (WRF) model simulations run by NCAR as part of a collaboration with the USGS Water Mission Area. The CONUS404 includes 42 years of data (water years 1980-2021) and the spatial domain extends beyond the CONUS into Canada and Mexico, thereby capturing transboundary river basins and covering all contributing areas for CONUS surface waters.

The CONUS404 dataset, produced using WRF version, is the successor to the CONUS1 dataset in ds612.0 (Liu, et al., 2017) with improved representation of weather and climate conditions in the central United States due to the addition of a shallow groundwater module and several other improvements in the NOAH-Multiparameterization land surface model. It also uses a more up-to-date and higher-resolution reanalysis dataset (ERA5) as input and covers a longer period than CONUS1.


In addition to the RDA dataset citation, authors are required to include the following citations in publications that base outcomes on this dataset:

1. Rasmussen, R.M., F. Chen, C.H. Liu, K. Ikeda, A. Prein, J. Kim, T. Schneider, A. Dai, D. Gochis, A. Dugger, Y. Zhang, A. Jaye, J. Dudhia, C. He, M. Harrold, L. Xue, S. Chen, A. Newman, E. Dougherty, R. Abolafia-Rozenzweig, N. Lybarger, R. Viger, D. Lesmes, K. Skalak, J. Brakebill, D. Cline, K. Dunne, K. Rasmussen, G. Miguez-Macho, 2023: CONUS404: The NCAR-USGS 4-km long-term regional hydroclimate reanalysis over the CONUS. Bull. Amer. Meteor. Soc., under revision.

2. Rasmussen, R.M., Chen, F., Liu, C., Ikeda, K., Prein, A., Kim, J., Schneider, T., Dai, A., Gochis, D., Dugger, A., Zhang, Y., Jaye, A., Dudhia, J., He, C., Harrold, M., Xue, L., Chen, S., Newman, A., Dougherty, E., Abolafia-Rozenzweig, R., Lybarger, N., R. Viger, Dunne, K., Rasmussen, K., Miguez-Macho, G., 2023, Four-kilometer long-term regional hydroclimate reanalysis over the conterminous United States (CONUS), 1979-2020: U.S. Geological Survey data release,

Temporal Range:
1979-10-01 00:00 +0000 to 2022-09-30 23:00 +0000 (Entire dataset) Period details by dataset product
Air Temperature Runoff
Vertical Levels:
See the detailed metadata for level information.
Data Types:
Spatial Coverage:
Longitude Range: Westernmost=137.873W Easternmost=58.463W
Latitude Range: Southernmost=17.631N Northernmost=56.704N Detailed coverage information
Data Contributors:
U.S. Geological Survey, U.S. Department of the Interior
Hydrometeorological Applications Program, Research Application Laboratory, National Center for Atmospheric Research, University Corporation for Atmospheric Research
Related Resources:
Liu, C., K. Ikeda, R. Rasmussen, M. Barlage, A. Newman, A. Prein, F. Chen, L. Chen, M. Clark, A. Dai, J. Dudhia, T. Eidhammer, D. Gochis, E. Gutman, S. Kurkute, Y. Li, G. Thompson, and D. Yates, 2017: Continental-Scale Convection-Permitting Modeling of the Current and Future Climate of North America Climate Dynamics, 49, 71-95 (DOI: 10.1007/s00382-016-3327-9).

Total Volume:
815.86 TB (Entire dataset) Volume details by dataset product
Data Formats:
Related RDA Datasets:
High Resolution WRF Simulations of the Current and Future Climate of North America
CONUS (Continental U.S.) II High Resolution Present and Future Climate Simulation
More Details:
View a more detailed summary of the data, including specific date ranges and locations by parameter
Metadata Record:
Data License:
Citation counts are compiled through information provided by publicly-accessible APIs according to the guidelines developed through the project. If journals do not provide citation information to these publicly-accessible services, then this citation information will not be included in RDA citation counts. Additionally citations that include dataset DOIs are the only types included in these counts, so legacy citations without DOIs, references found in publication acknowledgements, or references to a related publication that describes a dataset will not be included in these counts.