Evaluation of Error in IMERG Precipitation Estimates under Different Topographic Conditions and Temporal Scales over Mexico

This study evaluates the precipitation product of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) over the Mexican region during the period between April 2014 and October 2015 using three different time scales for cumulative precipitation (hourly, daily and seasonal). Also, the IMERG data have been analyzed as a function of elevation given the rain gauges from the automatic meteorological stations network, located within the area of study, which are used as a reference. In the present study, continuous and categorical statistics are used to evaluate IMERG. It was found that IMERG showed better performance at the daily and seasonal time scale resolutions. While hourly precipitation estimates reached a mean correlation coefficient of 0.35, the daily and seasonal precipitation estimates achieved correlations over 0.51. In addition, the IMERG precipitation product was able to reproduce the diurnal and daily cycles of the average precipitation with a trend towards overestimating rain gauges. However, extreme precipitation events were highly underestimated, as shown by relative biases of −61% and −46% for the hourly and daily precipitation analysis, respectively. It was also found that IMERG tends to improve precipitation detection and to decrease magnitude errors over the higher terrain elevations of Mexico.

[1]  Enrique R. Vivoni,et al.  An anomaly in the occurrence of the month of maximum precipitation distribution in northwest Mexico , 2010 .

[2]  松山 洋.  「Statistical Methods in the Atmospheric Sciences(2nd edition), International Geophysics Series 91」, Daniel S. Wilks著, Academic Press, 2005年11月, 648頁, $94.95, ISBN978-0-12-751966-1(本だな) , 2010 .

[3]  L. Qiao,et al.  Performance assessment of the successive Version 6 and Version 7 TMPA products over the climate-transitional zone in the southern Great Plains, USA , 2014 .

[4]  Yudong Tian,et al.  Performance of IMERG as a Function of Spatiotemporal Scale. , 2017, Journal of hydrometeorology.

[5]  Xi Li,et al.  Evaluation of IMERG and TRMM 3B43 Monthly Precipitation Products over Mainland China , 2016, Remote. Sens..

[6]  Yang Hong,et al.  Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China , 2016 .

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

[8]  Ali Tokay,et al.  A Novel Approach to Identify Sources of Errors in IMERG for GPM Ground Validation , 2016 .

[9]  Bin Wang,et al.  Diurnal Precipitation Regimes in the Global Tropics , 2008 .

[10]  W. Cleveland.  Robust Locally Weighted Regression and Smoothing Scatterplots , 1979 .

[11]  Vidhi Bharti,et al.  Evaluation of error in TRMM 3B42V7 precipitation estimates over the Himalayan region , 2015 .

[12]  Dennis P. Lettenmaier,et al.  Toward a unified view of the American monsoon systems , 2006 .

[13]  Takuji Kubota,et al.  Improvement of TMI Rain Retrievals in Mountainous Areas , 2013 .

[14]  Ahmad Al-Dousari,et al.  Site-specific precipitation estimate from TRMM data using bilinear weighted interpolation technique : An example from Kuwait , 2008 .

[15]  Di Long,et al.  Similarity and Error Intercomparison of the GPM and Its Predecessor-TRMM Multisatellite Precipitation Analysis Using the Best Available Hourly Gauge Network over the Tibetan Plateau , 2016, Remote. Sens..

[16]  Zhong Liu,et al.  Comparison of versions 6 and 7 3-hourly TRMM multi-satellite precipitation analysis (TMPA) research products , 2015 .

[17]  Guosheng Liu,et al.  A Parameterization of the Probability of Snow–Rain Transition , 2015 .

[18]  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..

[19]  Marco Casaioli,et al.  A multiscale approach for precipitation verification applied to the FORALPS case studies , 2008 .

[20]  A. Speranza,et al.  Sensitivity of Precipitation Forecast Skill Scores to Bilinear Interpolation and a Simple Nearest-Neighbor Average Method on High-Resolution Verification Grids , 2003 .

[21]  Y. Hong,et al.  Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over Mainland China at multiple spatiotemporal scales , 2015 .

[22]  Jose Leopoldo Guevara. Miranda.  Precipitation estimation over Mexico applying PERSIANN system and gauge data , 2002 .

[23]  G. Huffman,et al.  Integrated Multi-satellitE Retrievals for GPM (IMERG) Technical Documentation , 2015 .

[24]  Hidde Leijnse,et al.  First-year evaluation of GPM rainfall over the Netherlands : IMERG day 1 final run (V03D) , 2016 .