Next Article in Journal
Reconciling the Discrepancy of Post-Volcanic Cooling Estimated from Tree-Ring Reconstructions and Model Simulations over the Tibetan Plateau
Previous Article in Journal
Evaluation of A Regional Climate Model for the Eastern Nile Basin: Terrestrial and Atmospheric Water Balance
Open AccessArticle

Precipitation Atlas for Germany (GePrA)

Environmental Meteorology, Albert-Ludwigs-University of Freiburg, Werthmannstrasse 10, D-79085 Freiburg, Germany
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(12), 737; https://doi.org/10.3390/atmos10120737
Received: 25 October 2019 / Revised: 14 November 2019 / Accepted: 20 November 2019 / Published: 23 November 2019
(This article belongs to the Section Meteorology)
A new approach for modeling daily precipitation (RR) at very high spatial resolution (25 m × 25 m) was introduced. It was used to develop the Precipitation Atlas for Germany (GePrA). GePrA is based on 2357 RR time series measured in the period 1981–2018. It provides monthly percentiles (p) of the large-scale RR patterns which were mapped by a thin plate spline interpolation (TPS). A least-squares boosting (LSBoost) approach and orographic predictor variables (PV) were applied to integrate the small-scale precipitation variability in GePrA. Then, a Weibull distribution (Wei) was fitted to RRp. It was found that the mean monthly sum of RR ( R R ¯ s u m ) is highest in July (84 mm) and lowest in April (49 mm). A great dependency of RR on the elevation (ε) was found and quantified. Model validation at 425 stations showed a mean coefficient of determination (R2) of 0.80 and a mean absolute error (MAE) of less than 10 mm in all months. The high spatial resolution, including the effects of the local orography, make GePrA a valuable tool for various applications. Since GePrA does not only describe R R ¯ s u m , but also the entire monthly precipitation distributions, the results of this study enable the seasonal differentiation between dry and wet period at small scales. View Full-Text
Keywords: Weibull distribution; least-squares boosting; annual cycle; thin plate spline interpolation Weibull distribution; least-squares boosting; annual cycle; thin plate spline interpolation
Show Figures

Figure 1

MDPI and ACS Style

Jung, C.; Schindler, D. Precipitation Atlas for Germany (GePrA). Atmosphere 2019, 10, 737.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop