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Ground validation of GPM Day-1 IMERG and TMPA Version-7 products over different rainfall regimes in India

Theoretical and Applied Climatology (2022)Cite this article

Abstract

This study presents a comprehensive evaluation of multi-satellite precipitation estimates against ground rain gauge data over three different climatic regions of India. In this study, performance evaluation of Integrated Multi-satellitE Retrievals for GPM (IMERG) a next-generation rainfall mission for observing global precipitation characteristics has been carried out. The IMERG was also inter-compared with the TRMM Multi-satellite Precipitation Analysis (TMPA) product for using contingency table and statistical methods. The dependences of the two satellite rainfall products were examined, with special focus on the reliance of product performance at different rainfall intensities over three different rainfall regime area of India (Upper Mahanadi Basin, districts of Himachal Pradesh (NW Himalaya) and regions of Rajasthan (Thar Desert)). The analysis was carried out on daily and monthly scales. Results indicated that both the satellite precipitation products (SPPs) IMERG and TMPA precipitation products overestimate the daily precipitation. Both the SPPs show good correlation at daily and monthly precipitation estimations, and the performance of SPPs is better in Thar desert area, but poor in the mountainous region. The results also revealed that IMERG precipitation shows better detection capability of daily rainfall compared to TMPA precipitation estimates for most of the rainfall events. In general, IMERG and TMPA overestimated rainfall depths for all rainfall events. This study suggests that there is a need for emendation in precipitation estimation algorithm and validation against rain gauge precipitation to capture the rain events more accurately in the study area.

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References

  • Adler RF, Huffman GJ, Chang A, Ferraro R, Xie PP, Janowiak J, Gruber A (2003) The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present). J Hydrometeorol 4(6):1147–1167

    Article  Google Scholar 

  • AghaKouchak A, Behrangi A, Sorooshian S, Hsu K, Amitai E (2011) Evaluation of satellite-retrieved extreme precipitation rates across the central United States J Geophys Res 116:D02115. https://doi.org/10.1029/2010JD014741

  • Asong ZE, Razavi S, Wheater HS, Wong JS (2017) Evaluation of integrated multisatellite retrievals for GPM (IMERG) over Southern Canada against ground precipitation observations: A preliminary assessment. J Hydrometeorol 18(4):1033–1050. https://doi.org/10.1175/JHM-D-16-0187.1

    Article  Google Scholar 

  • Behrangi A, Andreadis K, Fisher JB, Turk FJ, Granger S, Painter T, Das N (2014) Satellite-based precipitation estimation and its application for streamflow prediction over mountainous western US basins. J Appl Meteorol Climatol 53(12):2823–2842

    Article  Google Scholar 

  • Beria H, Nanda T, Bisht DS, Chatterjee C (2017) Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale. Hydrol Earth Syst Sci 21(12):6117

    Article  Google Scholar 

  • Bharti V, Singh C (2015) Evaluation of error in TRMM 3B42V7 precipitation estimates over the Himalayan region. J Geophys Res Atmos 120(24):12458–12473

    Article  Google Scholar 

  • Chen C, Chen Q, Duan Z, Zhang J, Mo K, Li Z, Tang G (2018) Multiscale comparative evaluation of the GPM IMERG v5 and TRMM 3B42 v7 precipitation products from 2015 to 2017 over a climate transition area of China. Remote Sensing 10(6):944

    Article  Google Scholar 

  • Gupta HV, Sorooshian S, Yapo PO (1999) Status of automatic calibration for hydrologic models: Comparison with multilevel expert calibration. J Hydrol Eng 4(2):135–143

    Article  Google Scholar 

  • He Z, Yang L, Tian F, Ni G, Hou A, Lu H (2017) Intercomparisons of rainfall estimates from TRMM and GPM Multisatellite Products over the Upper Mekong River Basin. J Hydrometeorol 18(2):413–430. https://doi.org/10.1175/JHM-D-16-0198.1

    Article  Google Scholar 

  • Hogan RJ, Ferro CA, Jolliffe IT, Stephenson DB (2010) Equitability revisited: why the “equitable threat score” is not equitable. Weather Forecast 25(2):710–726

    Article  Google Scholar 

  • Hong Y, Hsu KL, Sorooshian S, Gao X (2004) Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. J Appl Meteorol 43(12):1834–1853

    Article  Google Scholar 

  • Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Stocker EF (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8(1):38–55

    Article  Google Scholar 

  • Huffman GJ, Bolvin DT, Braithwaite D, Hsu K, Joyce R, Xie P, Yoo SH (2015) NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG). Algorithm Theoretical Basis Document (ATBD) Version 4:26

  • Indu J, Kumar DN (2014) Evaluation of TRMM PR sampling error over a subtropical basin using bootstrap technique. IEEE Trans Geosci Remote Sens 52(11):6870–6881

    Article  Google Scholar 

  • Indu J, Kumar DN (2016) Rainfall screening methodology using TRMM data over a river basin. Hydrol Sci J 61(14):2540–2551

    Article  Google Scholar 

  • Jamandre CA, Narisma GT (2013) Spatio-temporal validation of satellite-based rainfall estimates in the Philippines. Atmos Res 122:599–608

    Article  Google Scholar 

  • Jhajharia D, Kumar R, Dabral PP, Singh VP, Choudhary RR, Dinpashoh Y (2015) Reference evapotranspiration under changing climate over the Thar Desert in India. Meteorol Appl 22(3):425–435

    Article  Google Scholar 

  • Joyce RJ, Janowiak JE, Arkin PA, Xie P (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeorol 5(3):487–503

    Article  Google Scholar 

  • Khandelwal DD, Gupta AK, Chauhan V (2015) Observations of rainfall in Garhwal Himalaya, India during 2008–2013 and its correlation with TRMM data. Curr Sci 108(6):1146

    Google Scholar 

  • Khodadoust Siuki S, Saghafian B, Moazami S (2017) Comprehensive evaluation of 3-hourly TRMM and half-hourly GPM-IMERG satellite precipitation products. Int J Remote Sens 38(2):558–571

    Article  Google Scholar 

  • Kim K, Park J, Baik J, Choi M (2017) Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-East Asia. Atmos Res 187:95–105

    Article  Google Scholar 

  • Kneis D, Chatterjee C, Singh R (2014) Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi). Hydrol Earth Syst Sci Discuss 11(1):1169–1201

    Google Scholar 

  • Kubota T, Shige S, Hashizume H, Aonashi K, Takahashi N, Seto S, Kachi M (2007) Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: Production and validation. IEEE Trans Geosci Remote Sens 45(7):2259–2275

    Article  Google Scholar 

  • Kumar D, Gautam AK, Palmate SS, Pandey A, Suryavanshi S, Rathore N, Sharma N (2017) Evaluation of TRMM multi-satellite precipitation analysis (TMPA) against terrestrial measurement over a humid sub-tropical basin, India. Theor Appl Climatol 129(3):783–799

    Article  Google Scholar 

  • Liu Z (2015) Comparison of precipitation estimates between Version 7 3-hourly TRMM Multi-Satellite Precipitation Analysis (TMPA) near-real-time and research products. Atmos Res 153:119–133

    Article  Google Scholar 

  • Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900

    Article  Google Scholar 

  • Nanda T, Sahoo B, Beria H, Chatterjee C (2016) A wavelet-based non-linear autoregressive with exogenous inputs (WNARX) dynamic neural network model for real-time flood forecasting using satellite-based rainfall products. J Hydrol 539:57–73

    Article  Google Scholar 

  • Nasrollahi N, Hsu K, Sorooshian S (2013) An artificial neural network model to reduce false alarms in satellite precipitation products using MODIS and CloudSat observations. J Hydrometeorol 14(6):1872–1883

    Article  Google Scholar 

  • Nijssen B, Lettenmaier D (2004) Effect of precipitation sampling error on simulated hydrological fluxes and states: Anticipating the Global Precipitation Measurement satellites. J Geophys Res 109:D02103. https://doi.org/10.1029/2003JD003497

  • Ning S, Wang J, Jin J, Ishidaira H (2016) Assessment of the latest GPM-era high-resolution satellite precipitation products by comparison with observation gauge data over the Chinese Mainland. Water 8(11):481

    Article  Google Scholar 

  • Prakash S, Mitra AK, Pai DS (2015) Comparing two high-resolution gauge-adjusted multisatellite rainfall products over India for the southwest monsoon period. Meteorol Appl 22(3):679–688

    Article  Google Scholar 

  • Prakash S, Mitra AK, Momin IM, Pai DS, Rajagopal EN, Basu S (2015) Comparison of TMPA-3B42 versions 6 and 7 precipitation products with gauge-based data over India for the southwest monsoon period. J Hydrometeorol 16(1):346–362

    Article  Google Scholar 

  • Prakash S, Mitra AK, Pai DS, AghaKouchak A (2016) From TRMM to GPM: how well can heavy rainfall be detected from space? Adv Water Resour 88:1–7

    Article  Google Scholar 

  • Prakash S, Mitra AK, AghaKouchak A, Liu Z, Norouzi H, Pai DS (2018) A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region. J Hydrol 556:865–876

    Article  Google Scholar 

  • Salio P, Hobouchian MP, Skabar YG, Vila D (2015) Evaluation of high-resolution satellite precipitation estimates over southern South America using a dense rain gauge network. Atmos Res 163:146–161

    Article  Google Scholar 

  • Sapiano MRP, Arkin PA (2009) An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data. J Hydrometeorol 10(1):149–166

    Article  Google Scholar 

  • Satgé F, Bonnet MP, Gosset M, Molina J, Lima WHY, Zolá RP, Garnier J (2016) Assessment of satellite rainfall products over the Andean plateau. Atmos Res 167:1–14

    Article  Google Scholar 

  • Sharifi E, Steinacker R, Saghafian B (2016) Assessment of GPM-IMERG and other precipitation products against gauge data under different topographic and climatic conditions in Iran: preliminary results. Remote Sensing 8(2):135

    Article  Google Scholar 

  • Sharifi E, Steinacker R, Saghafian B (2018) Multi time-scale evaluation of high-resolution satellite-based precipitation products over northeast of Austria. Atmos Res 206:46–63

    Article  Google Scholar 

  • Shige S, Kida S, Ashiwake H, Kubota T, Aonashi K (2013) Improvement of TMI rain retrievals in mountainous areas. J Appl Meteorol Climatol 52(1):242–254

    Article  Google Scholar 

  • Sorooshian S, Hsu KL, Gao X, Gupta HV, Imam B, Braithwaite D (2000) Evaluation of PERSIANN system satellite–based estimates of tropical rainfall. Bull Am Meteor Soc 81(9):2035–2046

    Article  Google Scholar 

  • Su F, Hong Y, Lettenmaier DP (2008) Evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) and its utility in hydrologic prediction in the La Plata Basin. J Hydrometeorol 9(4):622–640

    Article  Google Scholar 

  • Tan ML, Duan Z (2017) Assessment of GPM and TRMM precipitation products over Singapore. Remote Sensing 9(7):720

    Article  Google Scholar 

  • Tan ML, Santo H (2018) Comparison of GPM IMERG, TMPA 3B42 and PERSIANN-CDR satellite precipitation products over Malaysia. Atmos Res 202:63–76

    Article  Google Scholar 

  • Tan ML, Ibrahim AL, Duan Z, Cracknell AP, Chaplot V (2015) Evaluation of six high-resolution satellite and ground-based precipitation products over Malaysia. Remote Sensing 7(2):1504–1528

    Article  Google Scholar 

  • Tan J, Petersen WA, Tokay A (2016) A novel approach to identify sources of errors in IMERG for GPM ground validation. J Hydrometeorol 17(9):2477–2491

    Article  Google Scholar 

  • Tang G, Ma Y, Long D, Zhong L, Hong Y (2016) Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over Mainland China at multiple spatiotemporal scales. J Hydrol 533:152–167

    Article  Google Scholar 

  • Thiemig V, Rojas R, Zambrano-Bigiarini M, De Roo A (2013) Hydrological evaluation of satellite-based rainfall estimates over the Volta and Baro-Akobo Basin. J Hydrol 499:324–338

    Article  Google Scholar 

  • Tian Y, Peters-Lidard CD, Eylander JB, Joyce RJ, Huffman GJ, Adler RF, Hsu K, Turk FJ, Garcia M, Zeng J (2009) Component analysis of errors in satellite-based precipitation estimates. J Geophys Res 114:D24101. https://doi.org/10.1029/2009JD011949

  • Wang XL, Lin A (2015) An algorithm for integrating satellite precipitation estimates with in situ precipitation data on a pentad time scale. J Geophys Res: Atmos 120(9):3728–3744

    Article  Google Scholar 

  • Wilks D (2011) Statistical methods in the atmospheric sciences (3rd edn) Amsterdam: Elsevier

  • Xu S, Shen Y, Du Z (2016) Tracing the source of the errors in hourly IMERG using a decomposition evaluation scheme. Atmosphere 7(12):161

    Article  Google Scholar 

  • Xu R, Tian F, Yang L, Hu H, Lu H, Hou A (2017) Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over southern Tibetan Plateau based on a high-density rain gauge network. J Geophys Res Atmos 122:910–924. https://doi.org/10.1002/2016JD025418

    Article  Google Scholar 

  • Yang Z, Hsu K, Sorooshian S, Xu X, Braithwaite D, Zhang Y, Verbist KMJ (2017) Merging high-resolution satellite-based precipitation fields and point-scale rain gauge measurements—A case study in Chile. J Geophys Res Atmos 122:5267–5284. https://doi.org/10.1002/2016JD026177

    Article  Google Scholar 

  • Yatagai A, Kamiguchi K, Arakawa O, Hamada A, Yasutomi N, Kitoh A (2012) APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull Am Meteor Soc 93(9):1401–1415

    Article  Google Scholar 

  • Yong B, Ren L-L, Hong Y, Wang J-H, Gourley JJ, Jiang S-H, Chen X, Wang W (2010) Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: A case study in Laohahe basin, China. Water Resour Res 46:W07542. https://doi.org/10.1029/2009WR008965

  • Zambrano-Bigiarini M, Nauditt A, Birkel C, Verbist K, Ribbe L (2017) Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile. Hydrol Earth Syst Sci 21(2):1295

    Article  Google Scholar 

  • Zhang X, Srinivasan R (2009) GIS-based spatial precipitation estimation: a comparison of geostatistical approaches1. JAWRA J Am Water Resour Assoc 45(4):894–906

    Article  Google Scholar 

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Acknowledgements

Authors are thankful to Data Centre, Raipur Chhattisgarh for providing ground rainfall data. We also thank NASA and JAXA for making TMPA and IMERG datasets freely available to the scientific community. First, author would like to acknowledge the Ministry of Human Resources Development, Government of India, New Delhi for providing fellowship for the Ph.D.

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  1. Amar Kant Gautam

    Present address: Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, India

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  1. Department of Water Resources Development & Management, Indian Institute of Technology Roorkee, Roorkee, India, 247667

    Amar Kant Gautam & Ashish Pandey

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Amar Kant Guatam conceived the original idea and was in-charge of the overall direction and planning; Prof. Ashish Pandey provided guidance in the formal analysis and during investigation of the research work. Amar Kant Gautam and Prof. Ashish Pandey carried out supervision review and editing of the manuscript.

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Gautam, A.K., Pandey, A. Ground validation of GPM Day-1 IMERG and TMPA Version-7 products over different rainfall regimes in India. Theor Appl Climatol (2022). https://doi.org/10.1007/s00704-022-04091-8

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