Improving interpolation of daily precipitation for hydrologic modelling: spatial patterns of preferred interpolators

摘要: Detailed hydrologic models require high-resolution spatial and temporal data. This study aims at improving the interpolation of daily precipitation for models. Different parameterizations (1) inverse distance weighted (IDW) (2) A local regression (LWR) method in which elevation is explanatory variable distance, difference aspect are weighting factors, were tested a hilly setting eastern Mediterranean, using 16 years The preferred IDW was better than LWR scheme 27 out 31 validation gauges (VGs) according to criteria aimed minimizing absolute bias mean error (MAE) estimations. choice exponent found be more important whether or not use as data most cases. rank interpolators specific VG stable characteristic if sufficient number rainy days averaged. pattern exponents revealed. Large (3) effective closer coast line whereas small mountain crest. variability consistent with previous studies that showed smaller correlation distances Mediterranean hills, attributed mainly relatively warm sea-surface temperature resulting cellular convection coastward. These results suggest spatially variable, physically based parameterization function can improve precipitation. Copyright © 2009 John Wiley & Sons, Ltd.