Work

Interpolation techniques for climate variables

Year: 1999

Type: report

Abstract: This paper examines statistical approaches for interpolating climatic data over large regions, providing a brief introduction to interpolation techniques for climate variables of use in agricultural research, as well as general recommendations for future research to assess interpolation techniques. Three approaches—1) inverse distance weighted averaging (IDWA), 2) thin plate smoothing splines and 3) co-kriging—were evaluated for a 20,000 km2 square area covering the state of Jalisco, Mexico. Taking into account valued error prediction, data assumptions, and computational simplicity, we recommend use of thin-plate smoothing splines for interpolating climate variables.

Source: Socio-Environmental Systems Modeling

Authors: A.D. Hartkamp, Kirsten M. de Beurs, Alfred Stein, James W. C. White

Language: English

Topic: Soil Geostatistics and Mapping

Subfield: Soil Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Climate action

Open Access status: green

OpenAlex ID: W1526395435

Cites: 35

Cited by: 242

Related to: 10