Multi time-scale evaluation of high-resolution satellite-based precipitation products over northeast of Austria

Abstract Over the years, combinations of different methods that use multi-satellites and multi-sensors have been developed for estimating global precipitation. Recently, studies that have evaluated Integrated Multi-satellite Retrievals for GPM (IMERG) Final-Run (FR) version V-03D and other precipitation products have indicated better performance for IMERG-FR compared to other similar products in different climate regimes. This study comprehensively evaluates the two GPM-IMERG products, specifically IMERG-FR and IMERG-Real-Time (RT) late-run, against a dense station network (62 stations) in northeast Austria from mid-March 2015 to the end of January 2016 using different time-scales. Both products are examined against station data in capturing the occurrence and statistical characteristics of precipitation intensity. With regard to probability density functions (PDFs), the satellite precipitation estimate (SPE) products have detected more heavy and extreme precipitation events than the ground measurements. Both precipitation products at all time-scales, except for IMERG-RT 12-hourly and daily precipitation, capture less occurrence of precipitation than the station dataset for light precipitation. This partially explains the under-detection of precipitation events. For all time-scales, both IMERG products' CDFs (Cumulative Distribution Function) are well above that of the stations' precipitation. For lower precipitation levels, IMERG-RT is slightly below the IMERG-FR whereas IMERG-RT is above IMERG-FR at higher precipitation levels. Furthermore, for entire spectrum precipitation rates (P ≥ 0.1 mm), 1, 3, 6-hourly, IMERG-FR did not show a clear improvement of the Bias over IMERG-RT, while for 12-hourly and daily precipitation estimates, the bias in IMERG-FR has improved compared to IMERG-RT. In addition, IMERG-FR shows a considerable improvement in RMSE as compared to IMERG-RT. IMERG-FR, however, systematically underestimates moderate to extreme precipitation and overestimates light precipitation for all time scales against rain-gauges in northeast Austria. When comparing the bias, RMSE, and correlation coefficients, IMERG-FR has outperformed IMERG-RT particularly for 6-hourly, 12-hourly, and daily precipitation. Despite the general low probability of detection (POD) and threat score (TS) and the high false alarm ratio (FAR) within specified precipitation thresholds, the contingency table shows relatively acceptable values of the POD, TS and FAR for precipitation without classification.

[1]  C. Collier.  On the propagation of uncertainty in weather radar estimates of rainfall through hydrological models , 2009 .

[2]  Zhong Liu,et al.  Comparison of Integrated Multisatellite Retrievals for GPM (IMERG) and TRMM Multisatellite Precipitation Analysis (TMPA) Monthly Precipitation Products: Initial Results , 2016 .

[3]  F. Rubel,et al.  The climate of the European Alps: Shift of very high resolution Köppen-Geiger climate zones 1800–2100 , 2017 .

[4]  D. S. Pai,et al.  A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region , 2018 .

[5]  Nasrin Nasrollahi,et al.  False Alarm in Satellite Precipitation Data , 2015 .

[6]  Reinhard Böhm,et al.  Multi-methodical realisation of Austrian climate maps for 1971–2000 , 2011 .

[7]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[8]  Tarendra Lakhankar,et al.  Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal , 2013, Remote. Sens..

[9]  J. Gourley,et al.  The Influence of Surface and Precipitation Characteristics on TRMM Microwave Imager Rainfall Retrieval Uncertainty , 2015 .

[10]  Y. Hong,et al.  Multi-scale evaluation of high-resolution multi-sensor blended global precipitation products over the Yangtze River , 2013 .

[11]  A. Hou,et al.  The Global Precipitation Measurement Mission , 2014 .

[12]  Daniel Vila,et al.  Precipitation comparison for the CFSR, MERRA, TRMM3B42 and Combined Scheme datasets in Bolivia , 2015 .

[13]  David L. Toll,et al.  Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimates over Continental South America , 2009 .

[14]  Filipe Aires,et al.  A Tool to Estimate Land‐Surface Emissivities at Microwave frequencies (TELSEM) for use in numerical weather prediction , 2011 .

[15]  Thomas R. Karl,et al.  Trends in high-frequency climate variability in the twentieth century , 1995, Nature.

[16]  U. Germann,et al.  REAL—Ensemble radar precipitation estimation for hydrology in a mountainous region , 2009 .

[17]  E. McDonald,et al.  Mapping Quaternary alluvial fans in the southwestern United States based on multiparameter surface roughness of lidar topographic data , 2014 .

[18]  S. Sorooshian,et al.  Evaluation of PERSIANN system satellite-based estimates of tropical rainfall , 2000 .

[19]  G. Huffman,et al.  Validation of IMERG precipitation in Africa. , 2017, Journal of hydrometeorology.

[20]  C. Ropelewski,et al.  Validation of satellite rainfall products over East Africa's complex topography , 2007 .

[21]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .

[22]  U. Foelsche,et al.  Validation and correction of rainfall data from the WegenerNet high density network in southeast Austria , 2018 .

[23]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[24]  Charles N. Long,et al.  Exploiting diurnal variations to evaluate the ISCCP-FD flux calculations and radiative-flux-analysis-processed surface observations from BSRN, ARM, and SURFRAD , 2010 .

[25]  T. Haiden,et al.  The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region , 2011 .

[26]  R. Moore,et al.  Rainfall and sampling uncertainties: A rain gauge perspective , 2008 .

[27]  Assefa M. Melesse,et al.  Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia , 2015, Remote. Sens..

[28]  Yudong Tian,et al.  Multitemporal Analysis of TRMM-Based Satellite Precipitation Products for Land Data Assimilation Applications , 2007 .

[29]  Yang Hong,et al.  Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: A case study in Laohahe basin, China , 2010 .

[30]  Xinhua Zhang,et al.  Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia , 2015, Remote. Sens..

[31]  R. Dickinson,et al.  Critical assessment of surface incident solar radiation observations collected by SURFRAD, USCRN and AmeriFlux networks from 1995 to 2011 , 2012 .

[32]  Martin Wild,et al.  Spatial representativeness of ground‐based solar radiation measurements—Extension to the full Meteosat disk , 2014 .

[33]  U. Germann,et al.  Radar precipitation measurement in a mountainous region , 2006 .

[34]  Guillaume Quantin,et al.  Evaluation of several rainfall products used for hydrological applications over West Africa using two high‐resolution gauge networks , 2013 .

[35]  N. Nicholls,et al.  Changes in Climate Extremes Over the Australian Region and New Zealand During the Twentieth Century , 1999 .

[36]  J. Janowiak,et al.  COMPARISON OF NEAR-REAL-TIME PRECIPITATION ESTIMATES FROM SATELLITE OBSERVATIONS AND NUMERICAL MODELS , 2007 .

[37]  K. Hennessy,et al.  Trends in total rainfall, heavy rain events and number of dry days in Australia, 1910–1990 , 1998 .

[38]  S. Simonovic.  Floods in a Changing Climate: Risk Management , 2013 .

[39]  Gottfried Kirchengast,et al.  Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria , 2017 .

[40]  Witold F. Krajewski,et al.  Product‐error‐driven generator of probable rainfall conditioned on WSR‐88D precipitation estimates , 2009 .

[41]  Ali Behrangi,et al.  What does CloudSat reveal about global land precipitation detection by other spaceborne sensors? , 2014 .

[42]  Jordi Moré,et al.  The representativeness problem of a station net applied to the verification of a precipitation forecast based on areas , 2007 .

[43]  Long Sang Chiu,et al.  Spatial and Temporal Analysis of Rain Gauge Data and TRMM Rainfall Retrievals in Hong Kong , 2008, Ann. GIS.

[44]  M. Ou,et al.  Characteristic Features of Warm-Type Rain Producing Heavy Rainfall over the Korean Peninsula Inferred from TRMM Measurements , 2013 .

[45]  Thomas R. Karl,et al.  Secular Trends of Precipitation Amount, Frequency, and Intensity in the United States , 1998 .

[46]  P. Xie,et al.  Performance of high‐resolution satellite precipitation products over China , 2010 .

[47]  P. Xie,et al.  An Intercomparison of Gauge Observations and Satellite Estimates of Monthly Precipitation , 1995 .

[48]  Ehsan Sharifi,et al.  Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results , 2016, Remote. Sens..