Skip to main content
  1. ScienceBase Catalog
  2. Geo Data Portal Catalog
  3. Waterdata Catalog
  4. TopoWx: Topoclimatic Daily Air Temperature Dataset for the Conterminous United States

TopoWx: Topoclimatic Daily Air Temperature Dataset for the Conterminous United States

Dates

Metadata Creation Date
2015-09-10 07:35
Citation Creation Date
2015-07-20
Citation Publication Date
2015-09-08

Summary

The TopoWx ('Topography Weather') dataset contains historical 30-arcsec resolution (~800-m) interpolations of daily minimum and maximum topoclimatic air temperature for the conterminous U.S. Using both DEM-based variables and MODIS land skin temperature as predictors of air temperature, interpolation procedures include moving window regression kriging and geographically weighted regression. To avoid artificial climate trends, all input station data are homogenized using the GHCN/USHCN Pairwise Homogenization Algorithm (http://www.ncdc.noaa.gov/oa/climate/research/ushcn/#phas). The interpolation model is open source and information on obtaining model code can be found at http://www.ntsg.umt.edu/project/TopoWx. The following data are [...]

Contacts

Point of Contact :
Jared Oyler, Jared Oyler
Publisher :
Center for Integrated Data Analytics

Attached Files

Click on title to download individual files attached to this item.

61b387fdd34e3bd218628e74.xml
Original ISO Metadata
View 		39.85 KB application/vnd.iso.19115+xml
Extension: topowx.zip
topowx.tif 43.42 MB
topowx.tif-ColorRamp.SLD 2.19 KB
Extension: topowx_normals.zip
topowx_normals.tif 43.42 MB
topowx_normals.tif-ColorRamp.SLD 2.19 KB

Map

Map Preview

Spatial Services

ScienceBase WMS

ScienceBase WCS

Communities

  • Geo Data Portal Catalog

Tags

Provenance

Additional Information

Identifiers

Type Scheme Key
File Identifier file identifier 61b387fdd34e3bd218628e74

NetCDF OPeNDAP Service Extension

boundingBox
minY24.124999896840485
minX-125.00000055343521
maxY51.19999978854319
maxX-66.67500078682558
summaryThe TopoWx ('Topography Weather') dataset contains historical 30-arcsec resolution (~800-m) interpolations of daily minimum and maximum topoclimatic air temperature for the conterminous U.S. Using both DEM-based variables and MODIS land skin temperature as predictors of air temperature, interpolation procedures include moving window regression kriging and geographically weighted regression. To avoid artificial climate trends, all input station data are homogenized using the GHCN/USHCN Pairwise Homogenization Algorithm (http://www.ncdc.noaa.gov/oa/climate/research/ushcn/#phas). The interpolation model is open source and information on obtaining model code can be found at http://www.ntsg.umt.edu/project/TopoWx. The following data are available in this archive: 1948-2014 daily minimum and maximum temperature, and 1981-2010 monthly normals for minimum and maximum temperature with corresponding uncertainty (kriging prediction error). Ongoing annual updates will regenerate the entire dataset incorporating both new observations and model enhancements. This will result in a continuously improved dataset. However, different versions of TopoWx will be incompatible. For instance, data from the original 1948-2012 version should not be mixed with data from the new 1948-2014 version.
titleTopoWx: Topoclimatic Daily Air Temperature Dataset for the Conterminous United States
urlhttps://cida.usgs.gov/thredds/dodsC/topowx
variables
nametmax
unitsC
nametmin
unitsC
namelon
unitsdegrees_east
namelat
unitsdegrees_north
nametime
unitsdays since 1948-1-1 0:0:0

NetCDF OPeNDAP Service Extension

boundingBox
minY24.124999896840485
minX-125.00000055343521
maxY51.19999978854319
maxX-66.67500078682558
summaryThe TopoWx ('Topography Weather') dataset contains historical 30-arcsec resolution (~800-m) interpolations of daily minimum and maximum topoclimatic air temperature for the conterminous U.S. Using both DEM-based variables and MODIS land skin temperature as predictors of air temperature, interpolation procedures include moving window regression kriging and geographically weighted regression. To avoid artificial climate trends, all input station data are homogenized using the GHCN/USHCN Pairwise Homogenization Algorithm (http://www.ncdc.noaa.gov/oa/climate/research/ushcn/#phas). The interpolation model is open source and information on obtaining model code can be found at http://www.ntsg.umt.edu/project/TopoWx. The following data are available in this archive: 1948-2014 daily minimum and maximum temperature, and 1981-2010 monthly normals for minimum and maximum temperature with corresponding uncertainty (kriging prediction error). Ongoing annual updates will regenerate the entire dataset incorporating both new observations and model enhancements. This will result in a continuously improved dataset. However, different versions of TopoWx will be incompatible. For instance, data from the original 1948-2012 version should not be mixed with data from the new 1948-2014 version.
titleInterpolated 1981-2010 Monthly Normals for Topoclimatic Temperature
urlhttps://cida.usgs.gov/thredds/dodsC/topowx_normals

Raster Extension

files
nametopowx.tif
contentTypeimage/geotiff
pathOnDisk__disk__ee/01/ac/ee01ac08eeab2ddef9c197ecb9b4eeabd7da6b43
size45531608
dateUploadedFri Dec 10 10:02:05 MST 2021
nametopowx.tif-ColorRamp.SLD
contentTypeapplication/sld+xml
pathOnDisk__disk__06/b2/4f/06b24f7f0132284ca9fada96d1a66b34fc2a48ea
imageWidth580
imageHeight435
size2247
dateUploadedFri Dec 10 10:02:05 MST 2021
nametopowx
rasterTypeGeoTIFF

Raster Extension

files
nametopowx_normals.tif
contentTypeimage/geotiff
pathOnDisk__disk__94/84/3d/94843dcf628e9eb566f6557b71eab5199ebd36f5
size45528678
dateUploadedFri Dec 10 10:02:19 MST 2021
nametopowx_normals.tif-ColorRamp.SLD
contentTypeapplication/sld+xml
pathOnDisk__disk__10/b3/53/10b353d8ee25764465aa431783535d7bf0c95808
imageWidth580
imageHeight435
size2247
dateUploadedFri Dec 10 10:02:19 MST 2021
nametopowx_normals
rasterTypeGeoTIFF

Item Actions

Use Item

Process feature with Geo Data Portal

View Item as ...

JSON ATOM ISO XML

Save Item as ...

JSON FGDC MODS XML ISO XML

View Item...

Metrics