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Multivariate Adaptive Constructed Analogs (MACA) CMIP5 Statistically Downscaled Data for Coterminous USA
NOTICE: Given the large size of the MACAv2METDATA dataset, and a known issue with the data server being used to host it, initial load times may take a very long time and / or time out. Subsequent requests should be faster due to caching, but the cache clears periodically and the dataset must be rescanned prior to access. We are working on a fix for this issue. In the mean time, please use the dataset with care and make sureyou've reviewed the GDP scalability guidelines. https://my.usgs.gov/confluence/display/GeoDataPortal/Geo+Data+Portal+Scalability+Guidelines --- This archive contains daily downscaled meteorological and hydrological projections for the Conterminous United States at 1/24-deg resolution utilizing the Multivariate Adaptive Constructed Analogs (MACA, Abatzoglou, 2012) statistical downscaling method with the METDATA (Abatzoglou,2013) training dataset. The downscaled meteorological variables are maximum/minimum temperature(tasmax/tasmin), maximum/minimum relative humidity (rhsmax/rhsmin)precipitation amount(pr), downward shortwave solar radiation(rsds), eastward wind(uas), northward wind(vas), and specific humidity(huss). The downscaling is based on the 365-day model outputs from different global climate models (GCMs) from Phase 5 of the Coupled Model Inter-comparison Project (CMIP3) utlizing the historical (1950-2005) and future RCP4.5/8.5(2006-2099) scenarios. Leap days have been added to the dataset from the average values between Feb 28 and Mar 1 in order to aid modellers. See: http://maca.northwestknowledge.net/ for more information.
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CCMP Winds, Atlas FLK v1.1 Derived Surface Winds (Level 3.5a), Global, 0.25 Degree, 1987-2011, 5-Day Averages
공공데이터포털
This dataset is derived under the Cross-Calibrated Multi-Platform (CCMP) project and contains a value-added 5-day mean ocean surface wind and pseudostress to approximate a satellite-only climatological data record. The CCMP datasets combine cross-calibrated satellite winds obtained from Remote Sensing Systems (REMSS) using a Variational Analysis Method (VAM) to produce a high-resolution (0.25 degree) gridded analysis. The CCMP data set includes cross-calibrated satellite winds derived from SSM/I, SSMIS, AMSR-E, TRMM TMI, QuikSCAT, SeaWinds, WindSat and other satellite instruments as they become available from REMSS. ftp://podaac-ftp.jpl.nasa.gov/allData/ccmp/L3.5a/docs/ccmp_users_guide.pdf Atlas, R., R. N. Hoffman, J. Ardizzone, S. M. Leidner, J. C. Jusem, D. K. Smith, D. Gombos, 2011: A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bull. Amer. Meteor. Soc., 92, 157-174. doi: 10.1175/2010BAMS2946.1
CCMP Winds, Atlas FLK v1.1 Derived Surface Winds (Level 3.5a), Global, 0.25 Degree, 1987-2011, Monthly
공공데이터포털
This dataset is derived under the Cross-Calibrated Multi-Platform (CCMP) project and contains a value-added monthly mean ocean surface wind and pseudostress to approximate a satellite-only climatological data record. The CCMP datasets combine cross-calibrated satellite winds obtained from Remote Sensing Systems (REMSS) using a Variational Analysis Method (VAM) to produce a high-resolution (0.25 degree) gridded analysis. The CCMP data set includes cross-calibrated satellite winds derived from SSM/I, SSMIS, AMSR-E, TRMM TMI, QuikSCAT, SeaWinds, WindSat and other satellite instruments as they become available from REMSS. ftp://podaac-ftp.jpl.nasa.gov/allData/ccmp/L3.5a/docs/ccmp_users_guide.pdf Atlas, R., R. N. Hoffman, J. Ardizzone, S. M. Leidner, J. C. Jusem, D. K. Smith, D. Gombos, 2011: A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bull. Amer. Meteor. Soc., 92, 157-174. doi: 10.1175/2010BAMS2946.1
CCMP Winds, Atlas FLK v1.1 Derived Surface Winds (Level 3.5a), Global, 0.25 Degree, 1987-2011, 5-Day Averages, Lon+/-180
공공데이터포털
This dataset is derived under the Cross-Calibrated Multi-Platform (CCMP) project and contains a value-added 5-day mean ocean surface wind and pseudostress to approximate a satellite-only climatological data record. The CCMP datasets combine cross-calibrated satellite winds obtained from Remote Sensing Systems (REMSS) using a Variational Analysis Method (VAM) to produce a high-resolution (0.25 degree) gridded analysis. The CCMP data set includes cross-calibrated satellite winds derived from SSM/I, SSMIS, AMSR-E, TRMM TMI, QuikSCAT, SeaWinds, WindSat and other satellite instruments as they become available from REMSS. ftp://podaac-ftp.jpl.nasa.gov/allData/ccmp/L3.5a/docs/ccmp_users_guide.pdf Atlas, R., R. N. Hoffman, J. Ardizzone, S. M. Leidner, J. C. Jusem, D. K. Smith, D. Gombos, 2011: A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bull. Amer. Meteor. Soc., 92, 157-174. doi: 10.1175/2010BAMS2946.1
CLPX NCAR Data Analysis and Numerical Modeling, Version 1
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This data set consists of three-dimensional meteorological analyses for the entire cold season 2002-2003 for the three CLPX Meteorological Study Areas (MSAs) in northern Colorado (North Park, Fraser and Rabbit Ears) using high-resolution (500 m horizontal grid spacing).
CNRM-CM5: Downscaled climate projections at 800m spatial resolution for north central United States based on the Multivariate Adaptive Constructed Analog (MACA) method
공공데이터포털
This dataset provides downscaled climate projections at 800m spatial resolution for nine ecologically-relevant climate variables for the north central US region between 35.5N-49N latitude and 88W-118W longitude from the National Centre of Meteorological Research (France) model, CNRM-CM5, simulations (r1i1p1) from two emissions scenarios (RCP 4.5 and 8.5), which are downscaled using the Multivariate Adaptive Constructed Analog (MACA) method. These projections are available as five different (approximately) 30-year climate normals between 1950 and 2099 as monthly values, except for Aridity Index which are annual values. The five periods for which these climate normals are provided are 1950-1979 and 1980-2005 in the historic, and 2011-2040, 2041-2070 and 2071-2099 in the future. The nine climate variables include aridity index (unitless), potential evapotranspiration (mm), precipitation (mm), relative humidity (%), downward solar radiation (W.m-2), maximum daily temperature (C), minimum daily temperature (C), average temperature (C), vapor pressure deficit (Pa). Most of these variables were directly available from the 4km MACAv2-METDATA archive at the monthly time frequency, while others such as aridity index, relative humidity, average temperature and vapor pressure deficits were calculated additionally. The climate normals for the different periods (mentioned above) were estimated at 4km spatial resolution and then spatially disaggregated to 800m spatial resolution using bilinear interpolation.
CLPX NCAR Data Analysis and Numerical Modeling, Version 1
공공데이터포털
This data set consists of three-dimensional meteorological analyses for the entire cold season 2002-2003 for the three CLPX Meteorological Study Areas (MSAs) in northern Colorado (North Park, Fraser and Rabbit Ears) using high-resolution (500 m horizontal grid spacing).
Multivariate Adaptive Constructed Analogs (MACA) Catchment Minimum Temperature data, 2006-2099
공공데이터포털
This tabular data set represents estimated monthly minimum temperature (in degrees Fahrenheit) over the period 2006-2099 compiled for NHDPlus version 2 data suite (NHDPlusv2) catchments. This dataset can be linked to the NHDPlusv2 by the unique identifier COMID. The source data is Multivariate Adaptive Constructed Analogs (MACA) (Abatzoglou & Brown, 2011). Summaries are provided for five regions corresponding to NHDPlus vector processing units (VPUs): VPU 02, VPU 03w, VPU 04, VPU 14, and VPU 17.
Multivariate Adaptive Constructed Analogs (MACA) Catchment Maximum Temperature data, 2006-2099
공공데이터포털
This tabular data set represents estimated monthly maximum temperature (in degrees Fahrenheit) over the period 2006-2099 compiled for NHDPlus version 2 data suite (NHDPlusv2) catchments. This dataset can be linked to the NHDPlusv2 by the unique identifier COMID. The source data is Multivariate Adaptive Constructed Analogs (MACA) (Abatzoglou & Brown, 2011). Summaries are provided for five regions corresponding to NHDPlus vector processing units (VPUs): VPU 02, VPU 03w, VPU 04, VPU 14, and VPU 17.