Data Product: Recent and Past Conditions, Climate
Data Source: gridMET
Organization: University of California, Merced
Spatial Extent: contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: gridMET (aka METDATA): The gridMET gridded surface meteorological dataset covers the continental US from 1979-present mapping surface weather variables at a ~4-km spatial grain. This dataset is updated by 2:30 pm PST daily with data for the previous day (i.e. 1-day lag).
Link: gridMET webpage
Data Website: See Download tab on gridMET page
Data Methods:
Drought Indices: Computations of drought indices (PDSI,Z,SPI,SPEI,EDDI)
Fire Danger Indices: Fire danger indices are computed using the National Fire Danger Rating System (NFDRS) methods using fuel model G (dense conifer forests) as a standard for examining fire danger across broad geographic regions.
Data Citation: Abatzoglou, J. T. (2013), Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol., 33: 121–131.
https://doi.org/10.1002/joc.3413
Data Product: Recent and Past Conditions, Hydrology (Western USA)
Data Source: VIC-UCLA-WUSA
Organization: UCLA Land Surface Hydrology Group
Spatial Extent: Western US
Spatial Resolution: 1/16-deg (10.8-km, 6.4-mile)
Description: VIC-UCLA (Western US): The Variable Infiltration Capacity (VIC) hydrology model (v. 5.0.1) is used to simulate soil moisture, snow water equivalent, and runoff for the period 1920-present using meteorological forcings from weather stations data (1920-present) disseminated through
ACIS and interpolated to 1/16-deg grid resolution.
Recent percentiles for soil moisture and snow water equivalent are computed using the years 1920-2010 as a historical baseline. This data set is updated by 3 pm daily with data for the previous day (i.e. 1-day lag).
Link: VIC Documentation
Data Websites:
Data Citation:
-
Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415–14428, doi:10.1029/94JD00483.
Data Product: Recent and Past Conditions, Hydrology (Contiguous USA)
Data Source: VIC-UCLA-CONUS
Organization: UCLA Land Surface Hydrology Group
Spatial Extent: Contiguous US
Spatial Resolution: 1/2-deg (43-km, 25-mile)
Description: VIC-UCLA (Contiguous US): The Variable Infiltration Capacity (VIC) hydrology model (v. 5.0.1) is used to simulate soil moisture, snow water equivalent, and runoff
for the period 1916-present using meteorological forcings from weather stations data (1916-present) disseminated through
ACIS and interpolated to 1/2-deg grid resolution.
Recent percentiles for soil moisture and snow water equivalent are computed using the years 1916-2010 as a historical baseline. This data set is updated once a month for the last 30 days.
Link: VIC Documentation
Data Website:
Data Citation:
-
Wood, A.W. 2008, The University of Washington Surface Water Monitor: An experimental platform for national hydrologic assessment and prediction, in Proceedings of the AMS 22nd Conference on Hydrology, New Orleans, LA, January 20-24, 2008.
-
Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415–14428, doi:10.1029/94JD00483.
Data Product: Recent and Past Conditions, Agriculture
Data Source: gridMET
Organization: University of California, Merced
Spatial Extent: contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: gridMET (aka METDATA): The gridMET gridded surface meteorological dataset covers the continental US from 1979-present mapping surface weather variables at a ~4-km spatial grain. This dataset is updated by 2:30 pm PST daily with data for the previous day (i.e. 1-day lag).
Link: gridMET webpage
Data Website: See Download tab on gridMET page
Data Methods:
Drought Indices: Computations of drought indices (PDSI,Z,SPI,SPEI,EDDI)
Fire Danger Indices: Fire danger indices are computed using the National Fire Danger Rating System (NFDRS) methods using fuel model G (dense conifer forests) as a standard for examining fire danger across broad geographic regions.
Data Citation: Abatzoglou, J. T. (2013), Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol., 33: 121–131.
https://doi.org/10.1002/joc.3413
Data Product: Recent and Past Conditions, Fire
Data Source: gridMET
Organization: University of California, Merced
Spatial Extent: contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: gridMET (aka METDATA): The gridMET gridded surface meteorological dataset covers the continental US from 1979-present mapping surface weather variables at a ~4-km spatial grain. This dataset is updated by 2:30 pm PST daily with data for the previous day (i.e. 1-day lag).
Link: gridMET webpage
Data Website: See Download tab on gridMET page
Data Methods:
Drought Indices: Computations of drought indices (PDSI,Z,SPI,SPEI,EDDI)
Fire Danger Indices: Fire danger indices are computed using the National Fire Danger Rating System (NFDRS) methods using fuel model G (dense conifer forests) as a standard for examining fire danger across broad geographic regions.
Data Citation: Abatzoglou, J. T. (2013), Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol., 33: 121–131.
https://doi.org/10.1002/joc.3413
Data Product: Forecasted Future Conditions, Weather
Data Source: Downscaled CFSv2 Forecasts (CFSv2-gridMET)
Organization: University of California, Merced
Spatial Extent: Contiguous USA
Spatial Resolution: 1/24-degree (4-km, 2.5-mile)
Description: 48 downscaled weather forecasts for the next 28-days are assembled by first collecting the raw forecast model outputs from
NOAA NCEP's Climate Forecast System (CFSv2) operational forecast model:
Last 3 days of CFSv2 forecasts for the next 30 days
4 CFSv2 forecast initialization per day (every 6 hours)
4 CFSv2 ensembles per initialization
These 48 forecasts are then downscaled by calculating anomalies from the 1981–2010 base period from CFS, interpolating these anomalies to the gridMET mesh, and applying them to the climatological values in gridMET for the corresponding period.
This is how the 48 downscaled CFSv2 forecasts for the next 28-days are made.
This dataset is updated by 12 pm daily.
Link: Not available.
Data Website:
Data Citation:
Abatzoglou, J. T., McEvoy, D. J., Nauslar, N. J., Hegewisch, K. C., & Huntington, J. L. (2023). Downscaled subseasonal fire danger forecast skill across the contiguous United States. Atmospheric Science Letters, e1165.
https://doi.org/10.1002/asl.1165
Data Product: Forecasted Future Conditions, Hydrology
Data Source: VIC-CFSv2-gridMET (VIC v. 5.0.1, MetSim v.)
Organization: UW Hydro | Computational Hydrology, University of Washington
Spatial Extent: Pacific Northwest
Spatial Resolution: 1/16-deg (5.4-km, 3.4-mile)
Description: VIC-CFSv2-gridMET: The Variable Infiltration Capacity (VIC) hydrology model (v. 5.0.1) is used to simulate soil moisture, snow water equivalent, and runoff for the next 90 days using meteorological forcings from the CFSv2-gridMET bias-corrected weather forecasts. Elevation, soil and vegetation parameters for the VIC model were provided by the UW Hydro Columbia River Climate Change study (http://hydro.washington.edu/CRCC). The forecasts are initialized using the hydrologic states from VIC-gridMET. Each ensemble member (n=16) of CFSv2-gridMET is then used to force the VIC hydrologic model, and the hydrologic forecasts are then averaged to produce percentiles (with respect to the 1981-2010 baseline period). Forecasts are prepared for the next four weeks, presented in increments of either each week separately or aggregated across multiple weeks. This data set is updated by 6 pm daily with forecasts for the next four weeks.
Link: VIC Documentation
Data Website: THREDDS Catalog
Data Citation:
-
Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415–14428, doi:10.1029/94JD00483.
- Hamman, J. J., B. Nijssen, T. J. Bohn, D. R. Gergel, and Y. Mao, 2018: The Variable Infiltration Capacity Model, Version 5 (VIC-5): Infrastructure improvements for new applications and reproducibility. Geoscientific Model Development, in review.
Data Product: Forecasted Future Conditions, Climate
Data Source: BCSD-NMME, version 2012
Organization: University of California, Merced
Spatial Extent: Contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: Seasonal climate forecasts for the next seven months downscaled from 7 models of the North American Multi-Model Ensemble (NMME) to a ~4-km spatial grain across the contiguous US for compatibility with the gridMET data. This dataset is updated by the third week of each month with forecasts initialized on the 9th of each month for the next 7 months of data.
Link: BCSD-NMME website
Data Website: THREDDS Catalog
Data Citation: Barbero, R., Abatzoglou, J.T. Hegewisch,K.C. (2017) "Evaluation of statistical downscaling of North American Multi-Model Ensemble forecasts over the Western United States". Weather and Forecasting, February 2017..DOI: 10.1175/WAF-D-16-0117.1.
Data Product: Forecasted Future Conditions, Hydrology
Data Source: VIC-NMME-gridMET (VIC v. 5.0.1, MetSim v.)
Organization: UW Hydro | Computational Hydrology, University of Washington
Spatial Extent: Pacific Northwest
Spatial Resolution: 1/16-deg (5.4-km, 3.4-mile)
Description: VIC-NMME-gridMET: The Variable Infiltration Capacity (VIC) hydrology model (v. 5.0.1) is used to simulate soil moisture, snow water equivalent, and runoff for the next 7 months using meteorological forcings from climate model forecasts from the North American Multi-Model Ensemble (NMME) project. The monthly forecasts are bias corrected to the gridMET climate dataset and temporally disaggregated to daily data forcings.
Elevation, soil and vegetation parameters for the VIC model were provided by the UW Hydro Columbia River Climate Change study (http://hydro.washington.edu/CRCC). The forecasts are initialized using the hydrologic states from VIC-gridMET. The daily-disaggregated NMME forecast ensemble-mean is then used to force the VIC hydrologic model. Percentiles of hydrologic variables are then created with respect to the 1981-2010 baseline period. Forecasts are prepared for the next 7 months. This data set is updated by the third week of each month with forecasts initialized on the 9th of each month for the next 7 months of data.
Link: VIC Documentation
Data Website: THREDDS Catalog
Data Citation:
-
Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415–14428, doi:10.1029/94JD00483.
- Hamman, J. J., B. Nijssen, T. J. Bohn, D. R. Gergel, and Y. Mao, 2018: The Variable Infiltration Capacity Model, Version 5 (VIC-5): Infrastructure improvements for new applications and reproducibility. Geoscientific Model Development, in review.
Data Product: Projected Future Conditions, Climate
Data Source: MACAv2-METDATA, version 2
Organization: University of California, Merced
Spatial Extent: Contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: Projections from 20 climate models and 2 scenarios (RCP 4.5 and 8.5) were downscaled to a ~4-km resolution across the US for compatibility with the gridMET data.
Link: MACA Info Page
Data Website: MACA Website
Data Citation:
Abatzoglou J.T. and Brown T.J. A comparison of statistical downscaling methods suited for wildfire applications, International Journal of Climatology (2012), 32, 772-780.
https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.2312
Data Product: Projected Future Conditions, Hydrology
Data Source: VIC forced by MACAv2-LIVNEH, VIC (v4.1.2 ), MACA (v2), Livneh (V13 US, v14 BC Canada)
Organization: University of Washington
Spatial Extent: Western USA, USA
Spatial Resolution: 1/16-deg (6-km, 3.7-mile)
Description: Hydrology projections from 10 global climate models (GCMs) and 2 scenarios were simulated using the Variable Infiltration Capacity(VIC v 4.1.1.2) hydrology model, forced with the downscaled MACAv2-Livneh data 1950-2005(historic) and 2006-2100 (future) to 1/16th degree to produce metrics such as snow water equivalent, soil moisture, runoff and evaporation. The climate data was downscaled using gridded historical observations of meteorology from Livneh (v13 for USA and v14 for British Columbia, Canada). In the VIC model, the upper layers of the soil are from 0 - 140 cm beneath the surface.
Link: Integrated Scenarios Website
Data Website: Integrated Scenarios Website
Data Citation:
- Mote, P., Abatzoglou, J., Lettenmaier, D., Turner, D., Rupp, D., Bachelet, D., Conklin, D. (2017) “Final report for Integrated Scenarios of climate, hydrology, and vegetation for the Northwest”.
- Mote, Philip W., John T. Abatzoglou, Dennis P. Lettenmaier, Dave P. Turner, David E. Rupp, Dominique Bachelet, and David R. Conklin. Integrated Scenarios of Climate, Hydrology, and Vegetation for the Northwest, Final Report. Corvallis, Oregon: Pacific Northwest Climate Impacts Research Consortium, College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, 2014.
Data Product: Projected Future Conditions, Hydrology
Data Source: MWBM: CMIP5 MACAv2-METDATA Monthly Water Balance Model Projections 1950-2099 for the Contiguous United States
Organization: Northern Rocky Mountain Science Center
Spatial Extent: Continuous USA, USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: Hydrology projections from 20 global climate models (GCMs) and 2 scenarios were simulated using a monthly water-balance model (MWBM) to simulate components of the water balance (snow storage, soil storage, runoff, actual and potential evapotranspiration and water deficit) for the period 1950-2099 under RCP4.5 and RCP8.5 for the Contiguous United States. They used the statistically downscaled MACAv2-METDATA temperature and precipitation data from 20 General Circulation Models (GCMs) from the Climate Model Intercomparison Program Phase 5 (CMIP5) as input to the water balance model. This MACAv2-METDATA dataset was downscaled using gridded historical observations of meteorology from gridMET. This hydrology dataset supports the
USGS National Climate Change Viewer.
Link: WMBM Website
Data Website: USGS RegClim THREDDS server
Data Citation:
- Hostetler, S.W. and Alder, J.R., 2016. Implementation and evaluation of a monthly water balance model over the U.S. on an 800 m grid. Water Resources Research, 52, doi:10.1002/2016WR018665.
Data Product: Projected Future Conditions, Snow
Data Source: SnowClim, version 1
Organization: University of Idaho
Spatial Extent: Western USA
Spatial Resolution: 210-m
Description:
The SnowClim gridded snow dataset covers the western contiguous US at 210 m spatial resolution. The historical SnowClim dataset was created by forcing the SnowClim model with downscaled 4-hourly data from the Weather Research and Forecasting model (WRF; Rasmussen and Liu, 2017) that used initial and boundary conditions from ERA-Interim. The future SnowClim projections were created by forcing the SnowClim model with ERA-Interim data perturbed by average differences from a suite of nineteen climate models participating in the Fifth Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) between 1976–2005 and 2071–2100 under the high-warming RCP 8.5 scenario (Rasmussen and Liu, 2017). Data for the recent historical period represents conditions during the water year period Oct 1, 2000 to Sep 30, 2013. Data for the future period represents conditions during 2071-2100 under RCP8.5.
Link: SnowClim Info Page
Data Website: Dryad Downloads,
HydroShare Downloads.
Data Citation:
Lute, A. C., Abatzoglou, J., and Link, T.: SnowClim v1.0: high-resolution snow model and data for the western United States, Geosci. Model Dev., 15, 5045–5071,
https://doi.org/10.5194/gmd-15-5045-2022, 2022.
Data Product: Projected Future Conditions, Agriculture
Data Source: MACAv2-METDATA, version 2
Organization: University of California, Merced
Spatial Extent: Contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: Projections from 20 climate models and 2 scenarios (RCP 4.5 and 8.5) were downscaled to a ~4-km resolution across the US for compatibility with the gridMET data.
Link: MACA Info Page
Data Website: MACA Website
Data Citation:
Abatzoglou J.T. and Brown T.J. A comparison of statistical downscaling methods suited for wildfire applications, International Journal of Climatology (2012), 32, 772-780.
https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.2312
Data Product: Projected Future Conditions, Fire Danger
Data Source: MACAv2-METDATA, version 2
Organization: University of California, Merced
Spatial Extent: Contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: Projections from 20 climate models and 2 scenarios (RCP 4.5 and 8.5) were downscaled to a ~4-km resolution across the US for compatibility with the gridMET data.
Link: MACA Info Page
Data Website: MACA Website
Data Citation:
Abatzoglou J.T. and Brown T.J. A comparison of statistical downscaling methods suited for wildfire applications, International Journal of Climatology (2012), 32, 772-780.
https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.2312
Data Product: Projected Future Conditions, Very Large Fires
Data Source: Barbero et al. (2015)
Spatial Extent: Contiguous USA
Spatial Resolution: ~1/2-deg (60-km, 37.5-mile)
Description: Modeled very large fire (>5000ha) developed at sub-ecoregion scales for fire prone ecoregion across the continental US based on observed very large fire occurrences during 1984-2013. Climate projections were taken from aggregated MACAv2 data for 17 climate models and 1 scenario (RCP 8.5).
Link: https://www.fs.fed.us/pnw/pubs/journals/pnw_2015_barbero002.pdf
Data Citation:
Barbero R, Abatzoglou JT, Larkin NK, Kolden CA, Stocks B (2015). Climate change presents increased potential for very large fires in the contiguous United States.
Int J Wildland Fire 24(7):892–899.
Data Product: Projected Future Conditions, Area Burned
Data Source: MC2-MACAv2-PRISM-CMIP5
Organization: Conservation Biology Institute
Spatial Extent: Contiguous USA
Spatial Resolution: 1/24-deg (4-km, 2.5-mile)
Description: MC2-MACAv2-PRISM-CMIP5: Vegetation projections from 20 global climate models (GCMs) and 2 scenarios (RCP 4.5/8.5) were simulated using the MC2 dynamic global vegetation model, forced with the downscaled MACAv2-PRISM-CMIP5 data 1895-2014(historic) and 2015-2099 (future) to 1/24th degree. The climate data was downscaled using gridded historical observations of meteorology from PRISM. The MC2 model was run both with no fire suppression and with fire suppression.
Link: Integrated Scenarios Webpage
Data Website: MC2 Data Catalog
Data Citation:
- Bachelet, D., and D. Turner (editors). 2015. Global Vegetation Dynamics: Concepts and Applications in the MC1 Model. AGU Geophysical Monographs 214. 210pp.
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