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    • USGS Dynamical Downscaled Regional Climate

    Metadata Updated: June 15, 2024

    We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968 to 1999), common periods of the future (2040 to 2069), and two simulations continuously cover 2010 to 2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968 to 1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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    Dates

    Metadata Created Date June 1, 2023
    Metadata Updated Date June 15, 2024

    Metadata Source

    Harvested from DOI EDI

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date June 1, 2023
    Metadata Updated Date June 15, 2024
    Publisher Climate Adaptation Science Centers
    Maintainer
    @Id http://datainventory.doi.gov/id/dataset/348fd0f6aa54cb2be45c7453f498456e
    Identifier 54dd5daee4b08de9379b38c7
    Data Last Modified 2014-06-22T14:09:40
    Category geospatial
    Category Tag 16E15F51 D96E 4051 9124 75665Abdc6Ff "Ecosystem Vulnerability","Atmospheric, Earth and Ocean Sciences","Water"
    Public Access Level public
    Bureau Code 010:00
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://datainventory.doi.gov/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Harvest Object Id 017e2261-408e-4159-8884-5bd306b4a402
    Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
    Harvest Source Title DOI EDI
    Metadata Type geospatial
    Old Spatial -115.49382019,25.1519031525,-88.9157333374,44.6625442505
    Source Datajson Identifier True
    Source Hash c7aefee0d514b1b3367cf4f484f5b43b6fb8cc39e48776adb8b1bc92c52b2eed
    Source Schema Version 1.1
    Spatial {"type": "Polygon", "coordinates": -115.49382019, 25.1519031525, -115.49382019, 44.6625442505, -88.9157333374, 44.6625442505, -88.9157333374, 25.1519031525, -115.49382019, 25.1519031525}

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