Downscaling daily air-temperature measurements in the Netherlands
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ORIGINAL PAPER
Downscaling daily air-temperature measurements in the Netherlands Marieke Dirksen1,2,3
· Wouter H. Knap2 · Gert-Jan Steeneveld3 · Albert A. M. Holtslag3 · Albert M. G. Klein Tank3
Received: 30 April 2019 / Accepted: 3 July 2020 © The Author(s) 2020
Abstract High-resolution, regularly gridded air-temperature maps are frequently used in climatology, hydrology, and ecology. Within the Netherlands, 34 official automatic weather stations (AWSs) are operated by the National Met Service according to World Meteorological Organization (WMO) standards. Although the measurements are of high quality, the spatial density of the AWSs is not sufficient to reconstruct the temperature on a 1-km-resolution grid. Therefore, a new methodology for daily temperature reconstruction from 1990 to 2017 is proposed, using linear regression and multiple adaptive regression splines. The daily 34 AWS measurements are interpolated using eight different predictors: diurnal temperature range, population density, elevation, albedo, solar irradiance, roughness, precipitation, and vegetation index. Results are cross-validated for the AWS locations and compared with independent citizen weather observations. The RMSE of the reference method ordinary kriging amounts to 2.6 ◦ C whereas using the new methods the RMSE drops below 1.0 ◦ C. Especially for cities, a substantial improvement of the predictions is found. Independent predictions are on average 0.3 ◦ C less biased than ordinary kriging at 40 high-quality citizen measurement sites. With this new method, we have improved the representation of local temperature variations within the Netherlands. The temperature maps presented here can have applications in urban heat island studies, local trend analysis, and model evaluation.
1 Introduction High-resolution, regularly gridded temperature maps are essential for the construction of climatologies (Newman et al. 2015; Mohr and Tveito 2008; van den Hurk et al. 2006). Several scientific fields use these maps, examples are: the calculation of evapotranspiration (Enku and Melesse 2014; Lofgren et al. 2011; Hiemstra and Sluiter 2011), ecological relationships with bird and plant species occurrence (Vasseur et al. 2014), and the timing of pollen release (van Vliet et al. 2002). On the larger scale, homogenized gridded time series have been constructed to study temperature changes (van der Schrier et al. 2011). For example, the central Netherlands has warmed approximately
Marieke Dirksen
[email protected] 1
Technical University of Delft (TUD), Delft, Netherlands
2
The Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands
3
Wageningen University and Research (WUR), Wageningen, Netherlands
1 ◦ C over the twentieth century (van Oldenborgh and Van Ulden 2003). These authors have used data from the automatic weather stations (AWSs) to estimate a regional representation of the warming trends. Western Europe has been warming much faster than climate models projected (van Oldenborgh et al. 2009). The resolution of cli
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