(Version
2.01)
interpolated and documented by
Kenji Matsuura and Cort J. Willmott
(with support from IGES and NASA)
For additional information concerning this archive,
please contact us at:
Center for Climatic Research
Department of
(302) 831-2294
or
kenjisan@udel.edu
Archive (Version 2.01) created June, 2009
Station data, monthly-mean air temperature (T, oC), were compiled from several updated sources including a recent version of the Global Historical Climatology Network (GHCN2), Peterson and Vose, 1997); the Atmospheric Environment Service/Environment Canada; the State Hydrometeorological Institute, St. Petersburg, Russia; Greenland—from the GC-Net (Steffen et al., 1996); the Automatic Weather Station Project (courtesy of Charles R. Stearns at the University of Wisconsin-Madison); the Global Synoptic Climatology Network (Dataset 9290c, courtesy of National Climatic Data Center); and the Global Surface Summary of Day (GSOD) (NCDC) .
For stations and months with GHCN2 observations, the GHCN2 observations were used as “our” T values, because of GHCN2 quality-control measures. When and where GHCN2 observations were unavailable, other station records often were merged to create a composite monthly station-record series. During this process, station records that had the same geographical coordinates were interleaved or blended to create a single, station time series for that location. For some data sets, monthly values were compiled from hourly or daily values first. If there were two or more station observations for a given month, the median of these values was taken as T for that month. When there was only one station observation for a month, it was taken as T for that month. This was done to make use of all available data. Observations from stations which had different geographical coordinates were assumed to belong to different station records, although sometimes parts of nearby station records were extremely similar. The resultant number of stations available during this archive period ranges from about 1,600 to about 12,200.
For the background climatology, two station climatologies were merged. The first was calculated at those of our air-temperature time-series stations which had at least ten years of observations for each month. The second was the monthly station T climatology of Legates and Willmott (1990). Only those Legates and Willmott stations which were not collocated with our own 1960-1990 station climatology were included in the background climatology for CAI.
Traditional interpolation was accomplished with a spherical version of Shepard’s algorithm, which employs an enhanced distance-weighting method (Shepard, 1968; Willmott et al., 1985). Our traditional interpolations of estimated sea-level Ts, within our DEM-assisted procedure, as well as our interpolations of deviations from climatology, within CAI, were made in this way. The number of nearby stations that influence a grid-node estimate, however, was increased to an average of 20, from an average of 7 in earlier applications. This resulted in smaller cross-validation errors (see below) and visually more realistic air-temperature fields. A more robust neighbor finding algorithm, based on spherical distance, also was used.
Incorporating elevational influences, through an average air-temperature lapse rate, can increase the accuracy of spatially interpolating average air temperature (Willmott and Matsuura, 1995). DEM-assisted interpolation of average-monthly air temperature, therefore, was employed. Briefly, each average-monthly station air temperature was first “brought down” to sea level (warmed) at an average environmental lapse rate (6.0 deg C/km). Traditional interpolation then was performed on the adjusted-to-sea-level average-monthly station air temperatures. Finally, the gridded sea-level air temperatures were brought up to the DEM-grid height (cooled); once again, at the average environmental lapse rate.
Using a relatively high-resolution climatology also can increase the accuracy of spatially interpolated time series of monthly climate variables. Employing CAI (Willmott and Robeson, 1995), a monthly T at each time-series station was differenced from a climatologically averaged T for that month which was available at or was interpolated to the time-series station location. Traditional interpolation then was performed on the station differences to obtain a gridded difference field. Finally, the gridded difference field was added to the interpolated (DEM-assisted) estimates of the climatology at the same set of grid points.
To indicate (roughly) the spatial interpolation errors, station-by-station cross validation was employed (Willmott and Matsuura, 1995). One station was removed at a time, and the air temperature was then interpolated to the removed station location from the surrounding nearby stations. The difference between the real station value and the interpolated value is a local estimate of interpolation error. After each station cross validation was made, the removed station was put back into the network. To reduce network biases on cross-validation results, absolute values of the errors at the stations were interpolated to the same spatial resolution as the air temperature field.
|
air_temp2009.tar.gz: |
Monthly-mean air temperatures for the years 1900-2008 interpolated to a 0.5 by 0.5 degree grid resolution (centered on 0.25 degree). The format of each record is: |
|
Field |
Columns |
Variable |
Fortran Format |
|
1 |
1 - 8 |
Longitude (decimal degrees) |
F8.3 |
|
2 |
9 - 16 |
Latitude (decimal degrees) |
F8.3 |
|
3-14 |
17 - 112 |
Monthly Air Temperature (oC, Jan-Dec) |
12F8.1 |
|
air_temp_cv2009.tar.gz: |
Cross-validation errors (absolute values) associated with air temperatures for the years 1900-2008 interpolated to a 0.5 by 0.5 degree grid resolution. The format of each record is: |
|
Field |
Columns |
Variable |
Fortran Format |
|
1 |
1 - 8 |
Longitude (decimal degrees) |
F8.3 |
|
2 |
9 - 16 |
Latitude (decimal degrees) |
F8.3 |
|
3-14 |
17 - 112 |
Cross-validation errors (absolute values) of Monthly Temperature (oC, Jan-Dec) |
12F8.1 |
Peterson, T.C. and R.S. Vose (1997).
An overview of the Global Historical Climatology Network
temperature database. Bulletin of
the American Meteorological Society, 78, 2837-2849.
Shepard, D. (1968). A two-dimensional interpolation function
for irregularly-spaced data. Proceedings,
1968 ACM National Conference, 517-523.
Steffen, K., J.E. Box, and W. Abdalati
(1996).
Willmott, C.J. and K. Matsuura
(1995). Smart interpolation of annually averaged air
temperature in the
Willmott, C.J. and S.M. Robeson (1995). Climatologically aided interpolation (CAI) of terrestrial air
temperature. International
Journal of Climatology, 15(2), 221-229.
Willmott,
C.J., C.M. Rowe and W.D. Philpot (1985). Small-scale climate maps: a
sensitivity analysis of some common assumptions associated with grid-point
interpolation and contouring. American
Cartographer, 12, 5-16.