Validating daily climate interpolations over complex terrain in Austria

• Published in: Agricultural and forest meteorology Vol. 119; no. 1; pp. 87 - 107
• Main Authors: Hasenauer, Hubert, Merganicova, Katarina, Petritsch, Richard, Pietsch, Stephan A., Thornton, Peter E.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 30.10.2003; Oxford Elsevier; New York, NY
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agricultural and forest meteorology; Agronomy. Soil science and plant productions; Biological and medical sciences; Biometeorology; Climatology, meteorology; DAYMET; Ecosystem modeling; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Generalities. Techniques. Climatology. Meteorology. Climatic models of plant production; Precipitation; Temperature; Central Europe; Austria; Europe; Biometeorology; Ecosystem modeling; Temperature; Precipitation; DAYMET; Climate; Model study; Modeling; Weather; Interpolation; Complex terrain; Minimum temperature; Maximum temperature; Simulation model; Atmospheric precipitation; Solar radiation
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/S0168-1923(03)00114-X

Based on daily weather records of minimum and maximum air temperatures as well as precipitation from more than 250 stations between 1960 and 1998 across Austria we interpolate and validate daily climate interpolations using DAYMET. The current version of DAYMET interpolates on a systematic grid daily minimum and maximum temperature and precipitation from surrounding stations based on the principles of a weighted Gaussian filter. In addition, it calculates missing daily solar radiation (Srad) and humidity as it can be derived from temperature and precipitation data. In this study we calibrated DAYMET using the Austrian climate data base and developed a DAYMET point version, which allows us to interpolate daily weather for any location within the country, as it is needed to link existing field observations with missing weather data. We validated this procedure by using an independent data set of 23 stations located across the country. Our results can be summarized as follows: the sensitivity study using the full data set of about 3 million values of daily air temperature (minimum and maximum) as well as precipitation data indicated no regional or elevation related trends or biases. The only exception are daily precipitation predictions in very high altitudes (>1800 m), where model predictions diverge from observations probably due to an increase in the error of recording precipitation rates. The independent model validation using 23 stations consisting of minimum and maximum air temperature, precipitation, solar radiation observations as well as humidity data indicated no trends or bias. The mean error and the prediction interval, an indicator of the expected error range for future applications of the model, suggest no bias. Finally an assessment for two selected stations in Austria, Schmittenhöhe and Großenzersdorf, indicated a good coincidence between model predictions and observations using DAYMET.