Next Article in Journal
Correction: Mõttus, M. et al. Measurement of Diurnal Variation in Needle PRI and Shoot Photosynthesis in a Boreal Forest. Remote Sens. 2018, 10, 1019
Next Article in Special Issue
Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan
Previous Article in Journal
Crustal Deformation Prior to the 2017 Jiuzhaigou, Northeastern Tibetan Plateau (China), Ms 7.0 Earthquake Derived from GPS Observations
Previous Article in Special Issue
Evaluation and Hydrological Utility of the Latest GPM IMERG V5 and GSMaP V7 Precipitation Products over the Tibetan Plateau
Article Menu
Issue 12 (December) cover image

Export Article

Open AccessArticle
Remote Sens. 2018, 10(12), 2029;

Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany

Department of Geography, LMU Munich, Luisenstraße 37, 80333 Munich, Germany
Author to whom correspondence should be addressed.
Received: 15 October 2018 / Revised: 2 December 2018 / Accepted: 2 December 2018 / Published: 13 December 2018
(This article belongs to the Special Issue Remote Sensing of Precipitation)
Full-Text   |   PDF [27994 KB, uploaded 13 December 2018]   |  


Precipitation measurements provide crucial information for hydrometeorological applications. In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources. This study examines the performance of NASA’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG, GPM) satellite precipitation dataset in capturing the spatio-temporal variability of weather events compared to the German weather radar dataset RADOLAN RW. Besides quantity, also timing of rainfall is of very high importance when modeling or monitoring the hydrologic cycle. Therefore, detection metrics are evaluated along with standard statistical measures to test both datasets. Using indices like “probability of detection” allows a binary evaluation showing the basic categorical accordance of the radar and satellite data. Furthermore, a pixel-by-pixel comparison is performed to assess the ability to represent the spatial variability of rainfall and precipitation quantity. All calculations are additionally carried out for seasonal subsets of the data to assess potentially different behavior due to differences in precipitation schemes. The results indicate significant differences between the datasets. Overall, GPM IMERG overestimates the quantity of precipitation compared to RADOLAN, especially in the winter season. Moreover, shortcomings in detection performance arise in this season with significant erroneously-detected, yet also missed precipitation events compared to the weather radar data. Additionally, along secondary mountain ranges and the Alps, topographically-induced precipitation is not represented in GPM data, which generally shows a lack of spatial variability in rainfall and snowfall estimates due to lower resolution. View Full-Text
Keywords: precipitation; weather; radar; GPM; RADOLAN; QPE precipitation; weather; radar; GPM; RADOLAN; QPE

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Ramsauer, T.; Weiß, T.; Marzahn, P. Comparison of the GPM IMERG Final Precipitation Product to RADOLAN Weather Radar Data over the Topographically and Climatically Diverse Germany. Remote Sens. 2018, 10, 2029.

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.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top