U.S. Climate Divisions
History of the U.S. Climate Divisional Database
For many years the Climate Divisional Database was the only long-term temporally and spatially complete database from which to generate historical climate analyses (1895 to the present) for the contiguous United States (CONUS). It was originally developed for climate-division, statewide, regional, national, and population-weighted monitoring of drought, temperature, precipitation, and heating/cooling degree day values. Since the database was at the divisional spatial scale, it naturally lent itself to agricultural and hydrological applications.
There are 344 climate divisions in the CONUS. For each climate division, monthly station temperature and precipitation values are computed from the daily observations. The divisional values are weighted by area to compute statewide values and the statewide values are weighted by area to compute regional values. (Karl and Koss, 1984).
Traditional Climate Divisional Database
Traditionally, climate division values have been computed using the monthly values for all of the Cooperative Observer Network (COOP) stations in each division are averaged to compute divisional monthly temperature and precipitation averages/totals. This is valid for values computed from 1931 to the present. For the 1895-1930 period, statewide values were computed directly from stations within each state. Divisional values for this early period were computed using a regression technique against the statewide values (Guttman and Quayle, 1996). These values make up the traditional climate division database (TCDD).
Gridded Divisional Database
The GHCN-D 5km gridded divisional dataset (GrDD) is based on a similar station inventory as the TCDD however, new methodologies are used to compute temperature, precipitation, and drought for United States climate divisions. These new methodologies include the transition to a grid-based calculation, the inclusion of many more stations from the pre-1930s, and the use of NCDC's modern array of quality control algorithms. These are expected to improve the data coverage and the quality of the dataset, while maintaining the current product stream.
The GrDD is designed to address the following general issues inherent in the TCDD:
- For the TCDD, each divisional value from 1931-present is simply the arithmetic average of the station data within it, a computational practice that results in a bias when a division is spatially undersampled in a month (e.g., because some stations did not report) or is climatologically inhomogeneous in general (e.g., due to large variations in topography).
- For the TCDD, all divisional values before 1931 stem from state averages published by the U.S. Department of Agriculture (USDA) rather than from actual station observations, producing an artificial discontinuity in both the mean and variance for 1895-1930 (Guttman and Quayle, 1996).
- In the TCDD, many divisions experienced a systematic change in average station location and elevation during the 20th Century, resulting in spurious historical trends in some regions (Keim et al., 2003; Keim et al., 2005; Allard et al., 2009).
- Finally, none of the TCDD's station-based temperature records contain adjustments for historical changes in observation time, station location, or temperature instrumentation, inhomogeneities which further bias temporal trends (Peterson et al., 1998).
The GrDD's initial (and more straightforward) improvement is to the underlying network, which now includes additional station records and contemporary bias adjustments (i.e., those used in the U.S. Historical Climatology Network version 2; Menne et al., 2009).
The second (and far more extensive) improvement is to the computational methodology, which now addresses topographic and network variability via climatologically aided interpolation (Willmott and Robeson, 1995). The outcome of these improvements is a new divisional dataset that maintains the strengths of its predecessor while providing more robust estimates of areal averages and long-term trends.
The NCDC's Climate Monitoring Branch plans to transition from the TCDD to the more modern GrDD by 2014. While this transition will not disrupt the current product stream, some variances in temperature and precipitation values may be observed throughout the data record. For example, in general, climate divisions with extensive topography above the average station elevation will be reflected as cooler climatology. A preliminary assessment of the major impacts of this transition can be found in Fenimore, et. al, 2011.
A visualization toolkit was created to help users examine snapshots of both datasets for the comparison period (i.e., through December 2009). The tool allows the user to select criteria which are of interest and investigate the comparisons themselves. Parameters included in the toolkit are temperature, precipitation, and a variety of drought indices. Changes in monthly, seasonal and annual variability can be examined through the use of the interactive time series plots. In addition, slope (trend) values by decade and 30-year period may also be added to the output plots. This allows the user to take a closer look at the behavior of the data at a variety of smaller time scales throughout the record.
- 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.