US Climate Divisions Dataset Source and Information

Obtain data

NCEI Data Access page (select map interface to selected data and choose divisional). Data can be downloaded from NCEI in ascii format from the ftpsite It is updated at the beginning of the following month, usually between the 3rd and the 9th of the month.


  • Allard, J., B.D. Keim, J.E. Chassereau, D. Sathiaraj. 2009. Spuriously induced precipitation trends in the southeast United States. Theoretical and Applied Climatology. DOI: 10.1007/s00704-008-0021-9.
  • Guttman, N. V. and R. G. Quayle, 1996: A historical perspective of U.S. climate divisions. Bull. Amer. Meteor. Soc., 77, 293-303.
  • Karl, T.R., C.N. Williams, Jr., P.J. Young, and W.M. Wendland, 1986: A model to estimate the time of observation bias associated with monthly mean maximum, minimum, and mean temperature for the United States, J. Climate Appl. Meteor., 25, 145-160.
  • Karl T. R. and Koss W. J., 1984: Historical Climatology Series 4-3: Regional and National Monthly, Seasonal and Annual Temperature Weighted by Area, 1895-1983
  • Keim, B. D., A. Wilson, C. Wake, and T. G. Huntington, 2003: Are there spurious temperature trends in the United States Climate Division Database? Geophys. Res. Lett.,30, 1404, doi:10.1029/ 2002GL016295
  • Keim, B.D., M.R. Fischer, and A.M. Wilson, 2005: Are there spurious precipitation trends in the United States Climate Division database? Geophys. Res. Lett., 32, L04702, doi: 10.1029/2004GL021985.
  • Menne, M.J., C.N. Williams, and R.S. Vose, 2009: The United States Historical Climatology Network Monthly Temperature Data - Version 2. Bulletin of the American Meteorological Society, 90, 993-1107.
  • Peterson, T.C., T.R. Karl, P.F. Jamason, R. Knight, and D.R. Easterling, 1998: The first difference method: maximizing station density for the calculation of long-term global temperature change. J. Geophys. Res., Atmospheres, 103 (D20), 25967-25974.
  • Willmott, C.J. and S.M. Robeson, 1995. Climatologically aided interpolation (CAI) of terrestrial air temperature. International Journal of Climatology, 15(2), 221-229.
  • Vose, R.S., Applequist, S., Durre, I., Menne, M.J., Williams, C.N., Fenimore, C., Gleason, K., Arndt, D. 2014: Improved Historical Temperature and Precipitation Time Series For U.S. Climate Divisions Journal of Applied Meteorology and Climatology. DOI:

Description of plotted file produced at PSL

Format is here

Climate Divisions: Descriptions and Maps

Map of divisions(from NCEI)
Map of US with all divisions
Area weights of divisions from NCEI
GIS and related boundary description files


What stations go into each division?
We do not have a list here. You must refer to the references. Note that stations go into and out of the dataset each month as stations are created, move and go away. In addtion, data errors or similar collection problems may result in a particular station not being included in a month.
What is the Palmer Drought Index?
This is the monthly value (index) that is generated indicating the severity of a wet or dry spell. This index is based on the principles of a balance between moisture supply and demand. Man-made changes were not considered in this calculation. The index generally ranges from -6 to +6, with negative values denoting dry spells and positive values indicating wet spells. There are a few values in the magnitude of +7 or -7. PDSI values:
  0.0 to -0.5 = normal
 -0.5 to -1.0 = incipient drought;
 -1.0 to -2.0 = mild drought
 -2.0 to -3.0 = moderate drought
 -3.0 to -4.0 = severe  drought 
  >     - 4.0 = extreme drought. 
Similar adjectives are attached to positive values of wet spells. This is a meteorological drought index used to assess the severity of dry or wet spells of weather
Can you provide more dataset details?
Reprint of information on dataset from NCEI:




The major parameters in this file are sequential statewide, regional, and national monthly precipitation and monthly "time bias corrected" average temperature. The period of record is 1895 through the latest month available. This file is provided online and is updated monthly. The data in this file are used for historical perspectives in the CLIMATE VARIATIONS BULLETIN (Historical Climatology Series 4-7).

The monthly values for the most recent one to two years are based on preliminary data and will change when the final data are analyzed.

The statewide values are available for the 48 contiguous States and are computed from the divisional values weighted by area. The regional values are computed from the statewide values weighted by area (as defined by T.R. Karl and W.J. Koss, 1984: Historical Climatology Series 4-3: Regional and National Monthly, Seasonal and Annual Temperature Weighted by Area, 1895-1983). The states and area weights for each region are as follows:

Northeast Region: CT, 0.02752; DE, 0.01130; ME, 0.18251; MD, 0.05812; MA, 0.04537; NH, 0.05112; NJ, 0.04306; NY, 0.27242; PA, 0.24910; RI, 0.00667; VT, 0.05280

East North Central Region: IA, 0.22098; MI, 0.22854; MN, 0.33003; WI, 0.22045

Central Region: IL, 0.18169; IN, 0.11691; KY, 0.13013; MO, 0.22449; OH, 0.13279; TN, 0.13609; WV, 0.07790

Southeast Region: AL, 0.17576; FL, 0.19944; GA, 0.20051; NC, 0.17952; SC, 0.10576; VA, 0.13900

West North Central Region: MT, 0.31307; NE, 0.16432; ND, 0.15035; SD, 0.16393; WY, 0.20833

South Region: AR, 0.09335; KS, 0.14461; LA, 0.08530; MS, 0.08388; OK, 0.12291; TX, 0.46995

Southwest Region: AZ, 0.26819; CO, 0.24544; NM, 0.28645; UT, 0.19993

Northwest Region: ID, 0.33593; OR, 0.38990; WA, 0.27416

West Region: CA, 0.58943; NV, 0.41057

National (contiguous U.S.) values are computed from the regional values weighted by area. The regional weights are as follows:

Northeast, 0.06021 East North Central, 0.08428 Central, 0.10271 Southeast, 0.09715 West North Central, 0.15551 South, 0.18822 Southwest, 0.14053 Northwest, 0.08230 West, 0.08908

The values in this file may not agree with statewide, regional, and national values published in other NCEI publications due to: (1) differences in the way the regions are defined, (2) the temperature data are adjusted for time of observation bias, and (3) the most recent months are based on preliminary data.


Monthly averages within a climatic division have been calculated by giving equal weight to stations reporting both temperature and precipitation within a division. In the U.S., observers at cooperative stations often take one observation per day, and the ending time of the climatological day at any station can vary from station-to-station as well as year-to-year. Differences of the 24-hour period over which each observer reports his or her maximum and minimum temperature as well as the average temperature [(max + min)/2] affects the calculated monthly mean temperature. Karl, et al. (1986), describe the biases that this introduces. These potential biases were rectified by adjusting for these varying observation times. The model described by Karl, et al. (1986), was used to adjust the climate division averages such that all stations end their climatological day at midnight; i.e., climatological day coincides with calendar day. The time of observation was determined at each station within a climate division during January of the years 1931, 1941, 1951, 1965, 1975, and 1984 for the states of California, Colorado, Illinois, Indiana, New York, North Carolina, and Washington. The fraction of observers recording at various hours of the day was calculated and interpolated for intervening years (extrapolated for subsequent years). For these seven states, the ending time of observation was grouped into three categories: AM, PM, and MD. The AM category included observers who ended their climatological day between 3 AM and 11 AM; the PM category between noon and 9 PM; and the MD category between 10 PM and 2 AM; all local standard time. The fraction of observers in these categories was calculated, and it was assumed the 7 AM observation time best represented the AM category; the 5 PM observation time, the PM category; and midnight for the MD category. The reason for the simplification was to test if a faster method, requiring significantly less bookkeeping and keypunching, could not provide nearly as good results as calculating the fraction of observers at each of the 24 hours of the day.

The time of observation bias model was run by using the latitude and longitude of each of the centroids of the climate divisions. The output from the model was the time of observation bias, with respect to a midnight-to- midnight climatological day, for each of the possible ending hours of the climatological day. Each climate division's monthly average was then adjusted by weighting the bias at any given hour by the fraction of stations within the climate division observing at that hour, and subtracting the result for the reported monthly mean temperature.

Differences of the biases were small (< 0.3 Deg. F.) for those calculated by categorizing the ending time of observation into three categories compared to those obtained from calculating the fraction of stations with observation times at each of the 24 hours of the day. This is attributed to the preponderance of AM observation times falling between 6 AM and 9 AM, and PM observation times falling between 4 PM and 7 PM. As a result, by assuming 7 AM observation for all AM stations and 5 PM for all PM stations, a good estimate of the median bias is obtained for all AM or PM observations. Furthermore, nearly all the MD stations observed at midnight.

It should also be noted that the borders of the climate divisions in 1951 were not consistent with those defined in 1965. Due to the substantial additional effort it would have required locating each station within three or four climate divisions, as defined today, the change in the statewide percentage of AM, PM, and MD observation times was applied in equal proportions to all climate divisions prior to and including 1951.

Based on small differences between the two methods of estimating the time of observation bias, the simpler categorical procedure was used for all climate divisions. This should effectively eliminate most of the biases (over 2 Deg.F) in some climate divisions that have become part of the divisional averages. These biases affect both trends and actual estimates of divisional averages.

Reference: Karl, et al. (1986): "A model to estimate the time of observation bias associated with monthly mean maximum, minimum, and mean temperatures for the United States" (Thomas R. Karl, Claude N. Williams, Jr., and Pamela J. Young, National Climatic Data Center, and Wayne M. Wendland, Illinois State Water Survey, Journal of Climate and Applied Meteorology, January 1986, vol. 25, pp. 145-160, American Meteorological Society, Boston, MA).