TY - BK AU - Hartkamp, A.D. AU - De Beurs, K. AU - Stein, A. AU - White,J.W. TI - Interpolation techniques for climate variables T2 - CIMMYT NRG-GIS Series PY - 1999/// CY - Mexico PB - CIMMYT, KW - Agriculture KW - AGROVOC KW - Climatic factors KW - Statistical methods N1 - Open Access N2 - 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 2,000 km2 square area covering the state of Jalisco, México. Taking into account valued error prediction, data assumptions, and computational simplicity, we recommend use of thin-plate smoothing splines for interpolating climate variables UR - http://hdl.handle.net/10883/988 ER -