Climatologically aided interpolation (CAI) of terrestrial air temperature

Climatologically aided interpolation (CAI) of terrestrial air temperature A new and relatively straightforward approach to interpolating and spatially averaging air temperature from weather‐station observations is introduced and evaluated using yearly station averages taken from the Jones et al. archive. All available terrestrial station records over the period from 1881 through to 1988 are examined. Called climatologically aided interpolation, or CAI, our procedure makes combined use of (i) a spatially high‐resolution air‐temperature climatology recently compiled by Legates and Willmott, as well as (ii) spatially interpolated yearly temperature deviations (evaluated at the stations) from the climatology. Spherically based inverse‐distance‐weighting and triangular‐decomposition interpolation algorithms are used to interpolate yearly station temperatures and temperature deviations to the nodes of a regular, spherical lattice. Interpolation errors are estimated using a cross‐validation methodology. Interpolation errors associated with CAI estimates of annual‐average air temperatures over the terrestrial surface are quite low. On average, CAI errors are of the order of 0.8°C, whereas interpolations made directly (and only) from the yearly station temperatures exhibit average errors between 1.3°C and 1.9°C. Although both the high‐resolution climatology and the interpolated temperature‐deviation fields explain non‐trivial portions of the space‐time variability in terrestrial air temperature, most of CAI's accuracy can be attributed to the spatial variability captured by the high‐resolution (Legates and Willmott's) climatology. Our results suggest that raw air‐temperature fields as well as temperature anomaly fields can be interpolated reliably. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Climatology Wiley

Climatologically aided interpolation (CAI) of terrestrial air temperature

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Publisher
Wiley
Copyright
Copyright © 1995 John Wiley & Sons, Ltd
ISSN
0899-8418
eISSN
1097-0088
DOI
10.1002/joc.3370150207
Publisher site
See Article on Publisher Site

Abstract

A new and relatively straightforward approach to interpolating and spatially averaging air temperature from weather‐station observations is introduced and evaluated using yearly station averages taken from the Jones et al. archive. All available terrestrial station records over the period from 1881 through to 1988 are examined. Called climatologically aided interpolation, or CAI, our procedure makes combined use of (i) a spatially high‐resolution air‐temperature climatology recently compiled by Legates and Willmott, as well as (ii) spatially interpolated yearly temperature deviations (evaluated at the stations) from the climatology. Spherically based inverse‐distance‐weighting and triangular‐decomposition interpolation algorithms are used to interpolate yearly station temperatures and temperature deviations to the nodes of a regular, spherical lattice. Interpolation errors are estimated using a cross‐validation methodology. Interpolation errors associated with CAI estimates of annual‐average air temperatures over the terrestrial surface are quite low. On average, CAI errors are of the order of 0.8°C, whereas interpolations made directly (and only) from the yearly station temperatures exhibit average errors between 1.3°C and 1.9°C. Although both the high‐resolution climatology and the interpolated temperature‐deviation fields explain non‐trivial portions of the space‐time variability in terrestrial air temperature, most of CAI's accuracy can be attributed to the spatial variability captured by the high‐resolution (Legates and Willmott's) climatology. Our results suggest that raw air‐temperature fields as well as temperature anomaly fields can be interpolated reliably.

Journal

International Journal of ClimatologyWiley

Published: Feb 1, 1995

References

  • A method for bivariate interpolation and smooth surface fitting for irregularly distributed data points
    Akima, Akima
  • The recent climatic record: what it can and cannot tell us
    Karl, Karl; Tarpley, Tarpley; Quayle, Quayle; Diaz, Diaz; Robinson, Robinson; Bradley, Bradley

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