Skip to main content
Log in

Assessment of Real Time, Multi-Satellite Precipitation Products under Diverse Climatic and Topographic Conditions

  • Original Article
  • Published:
Asia-Pacific Journal of Atmospheric Sciences Aims and scope Submit manuscript

Abstract

A preliminary assessment of real-time multi-satellite precipitation products, Global Precipitation Measurement (GPM) IMERG real time (IMRT), TMPA 3B42 real time (TMPA), PERSIANN (PERS) and CMORPH (CMOR) was carried out in Pakistan on entire study area basis and by dividing the study area in to five regions. It is extended from 61o to 77o East and 23.5 o to 37 o North, with varied climatic and topographic conditions. In south coastline along the Arabian Sea, plateaus, deserts and plain areas in the center and in north snow caped mountains. A set of evaluating (continuous) statistical indices, correlation coefficient (CC), bias (Bias), root mean square error (RMSE) and detective (categorical) statistical indices, probability of detection (POD), false alarm ratio (FAR), critical success index (CSI) were applied to evaluate the satellite products against rain gauge data at daily time scales. However CC values were computed at monthly time scale and comparison between average annual values of satellite data and gauge values was also conducted. At annual basis significant resemblance was observed between spatial distribution of satellite and gauge data. At monthly time scale satellite products showed correlation in the range of 0.7 to 0.9 against reference data at major portion of the study area. But at daily time scale a weak correlation from 0.2 to 0.45, higher values of bias and RMSE in hilly terrains with highest average annual rainfall and the adjacent foot hill areas as compared to the plain areas, lower values of POD, CSI and higher values of FAR were observed. An inter comparison among the used satellite products revealed that overall performance of IMRT was better in the study area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Adler, R.F., Negri, A.J.: A satellite infrared technique to estimate tropical convective and stratiform rainfall. J. Appl. Meteorol. 27(1), 30–51 (1988)

    Google Scholar 

  • Aghakouchak, A., Nasrollahi, N., Habib, E.: Accounting for uncertainties of the TRMM satellite estimates. Remote Sens. 1, 606–619 (2009)

    Google Scholar 

  • Ali AF, Cunde X, Anjum MN, Adnan M, Nawaz Z, Ijaz MW, Sajid M, Farid HU Evaluation and comparison of TRMM multi-satellite precipitation products with reference to rain gauge observations in Hunza River Basin, Karakoram Range, Northern Pakistan. Sustainability 9:1954 (2017)

  • Anjum, M.N., Ding, Y., Shangguan, D., Tahir, A.A., Iqbal, M., Adnan, M.: Comparison of two successive versions 6 and 7 of TMPA satellite precipitation products with rain gauge data over swat watershed, Hindukush Mountains. Pakistan. Atmos. Sci. Let. 17(4), 270–279 (2016)

    Google Scholar 

  • Anjum, M.N., Ding, Y., Shangguan, D., et al.: Performance evaluation of latest integrated multi-satellite retrievals for global precipitation measurement (IMERG) over the northern highlands of Pakistan. Atmos. Res. 205, 134–146 (2018)

    Google Scholar 

  • Blacutt, L., Herdies, D., Goncalves, L., Vila, D., Andrade, M.: Precipitation comparison for the CFSR, MERRA, TRMM3B42 and combined scheme datasets in Bolivia. Atmos. Res. 163, 117–131 (2015)

    Google Scholar 

  • Boushaki, F.I., Hsu, K., Sorooshian, S., Park, G., Mahani, S., Shi, W.: Bias adjustment of satellite precipitation estimation using ground-based measurement: a case study evaluation over the southwestern United States. J. Hydrometeorol. 10, 1231–1242 (2009)

    Google Scholar 

  • Bowman, K.P.: Comparison of TRMM precipitation retrievals with rain gauge data from ocean buoys. J. Clim. 18(1), 178–190 (2005)

    Google Scholar 

  • Cheema, M.J.M., Bastiaanssen, W.G.: Local calibration of remotely sensed rainfall from the TRMM satellite for different periods and spatial scales in the Indus Basin. Inter. J. Remote Sens. 33(8), 2603–2627 (2012)

    Google Scholar 

  • Chen, F., Li, X.: Evaluation of IMERG and TRMM 3B43 monthly precipitation products over mainland China. Remote Sens. 8(6), 472 (2016)

    Google Scholar 

  • Ciach, G., Krajewski, W.F.: On the estimation of radar rainfall error variance. Adv. Water Resour. 22(6), 585–595 (1999)

    Google Scholar 

  • Derin, Y., Yilmaz, K.K.: Evaluation of multiple satellite based precipitation products over complex topography. J. Hydrometeorol. 15, 1498–1516 (2014)

    Google Scholar 

  • Dinku, T., Ceccato, P., Grover-Kopec, E., et al.: Validation of satellite rainfall products over East Africa’s complex topography. Int. J. Remote Sens. 28(7), 1503–1526 (2007)

    Google Scholar 

  • Ferraro, R., et al.: A screening methodology for passive microwave precipitation retrieval algorithms. J. Atmos. Sci. 55, 1583–1600 (1998)

    Google Scholar 

  • Franchito, S.H., Rao, V.B., Vasques, A.C., et al.: Validation of TRMM precipitation radar monthly rainfall estimates over Brazil. J. Geophys. Res. 114, (2009)

  • Gao, Y.C., Liu, M.F.: Evaluation of high-resolution satellite precipitation products using rain gauge observations over the Tibetan plateau. Hydrol. Earth Syst. Sci. 17(2), 837–849 (2013)

    Google Scholar 

  • Gebremichael, M., Anagnostou, E.N., Bitew, M.M.: Critical steps for continuing advancement of satellite rainfall applications for surface hydrology in the Nile river basin. J. Am. Water Resour. Assoc. 46, 361–366 (2010)

    Google Scholar 

  • Habib, E., Larson, B.F., Graschel, J.: Validation of NEXRAD multisensory precipitation estimates using an experimental dense rain gauge network in South Louisiana. J. Hydrol. 373(3–4), 463–478 (2009)

    Google Scholar 

  • Hong, Y., Hsu, K.L., Sorooshian, S., et al.: Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. J. Appl. Meteorol. 43, 1834–1852 (2004)

    Google Scholar 

  • Hong, Y., Hsu, K.L., Moradkhani, H., Sorooshian, S.: Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response. Water Resour. Res. 42, (2006)

  • Hossain, F., Anagnostoub, E.N., Bagtzoglou, A.C.: On Latin hypercube sampling for efficient uncertainty estimation of satellite rainfall observations in flood prediction. Comput. Geosci. 32, 776–792 (2006)

    Google Scholar 

  • Huffman, G.J., Adler, R.F., Bolvin, D.T., et al.: The TRMM multi-satellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J. Hydrometeorol. 8, 38–55 (2007)

    Google Scholar 

  • Hussain, Y., Sathe, F., Hussain, M.B., Martinez, H.E.: Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan. Theor. Appl. Climatol. 131, 1–14 (2017)

    Google Scholar 

  • Iqbal, M.F., Athar, H.: Validation of satellite based precipitation over diverse topography of Pakistan. Atmos. Res. 201, 247–260 (2018)

    Google Scholar 

  • Joyce, R.J., Janowiak, J.E., Arkin, P.A., et al.: CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J. Hydrometeorol. 5, 487–503 (2004)

    Google Scholar 

  • Khan, S.I., Hong, Y., Gourley, J.J., et al.: Evaluation of three high-resolution satellite precipitation estimates: potential for monsoon monitoring over Pakistan. Adv. Space Res. 54, 670–684 (2014)

    Google Scholar 

  • Kidd, C., Huffman, G.: Global precipitation measurement. Meteorol. Appl. 18, 334–353 (2011)

    Google Scholar 

  • Kidd, C., Levizzani, V.: Status of satellite precipitation retrievals. Hydrol. Earth Syst. Sci. 15, 1109–1116 (2011)

    Google Scholar 

  • Kidd, C., Kniveton, D.R., Todd, M.C., et al.: Satellite rainfall estimation using combined passive microwave and infrared algorithms. J. Hydrometeorol. 4, 1088–1104 (2003)

    Google Scholar 

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

    Google Scholar 

  • Kummerow, C., Olson, W.S., Giglio, L.: A simplified scheme for obtaining precipitation and vertical hydrometeor profiles from passive microwave sensors. Geosci. Remote Sens. 34(5), 1213–1232 (1996)

    Google Scholar 

  • Lensky, I.M., Rosenfeld, D.: A night-rain delineation algorithm for infrared satellite data based on microphysical considerations. J. Appl. Meteorol. 42, 1218–1226 (2003)

    Google Scholar 

  • Li, J., Heap, A.D.: A review of spatial interpolation methods for environmental scientists, geosci. Austral, Canberra (2008)

    Google Scholar 

  • Liu, Z.: Comparison of integrated multisatellite retrievals for GPM (IMERG) and TRMM multisatellite precipitation analysis (TMPA) monthly precipitation products: initial results. J. Hydrometeorol. 17(3), 777–790 (2015)

    Google Scholar 

  • Ma, L., Zhang, T., Frauenfeld, O., Ye, B., Yang, D., Qin, D.: Evaluation of precipitation from the ERA-40, NCEP-1, and NCEP-2 Reanalysis and CMAP-1, CMAP-2, and GPCP-2 with ground-based measurements in China. J. Geophys. Res. (2009)

  • Maggioni, V., Meyers, P.C., Robinson, M.D.: A review of merged high-resolution satellite precipitation product accuracy during the tropical rainfall measuring Mission (TRMM). Era. J. Hydrometeor. 17(4), 1101–1117 (2016)

    Google Scholar 

  • Michaelides, S., Levizzani, V., Anagnostou, E.N., et al.: Precipitation: measurement, remote sensing, climatology and modeling. Atmos. Res. 94, 512–533 (2009)

    Google Scholar 

  • Michele, D.S., Marzano, F.S., Mugnai, A., et al.: Physically-based statistical integration of TRMM microwave measurements for precipitation profiling. Radio Sci. 38, 8072–8088 (2003)

    Google Scholar 

  • Moazami, S., Golian, S., Kavianpour, M.R., et al.: Uncertainty analysis of bias from satellite rainfall estimates using coupla method. Atmos. Res. 137, 145–166 (2014a)

    Google Scholar 

  • Moazami, S., Golian, S., Hong, Y., et al.: Comprehensive evaluation of four high-resolution satellite precipitation products under diverse climate conditions in Iran. Hydrol. Sci. J. 61(2), 420–440 (2014b)

    Google Scholar 

  • Moazami, S., Golian, S., Hong, Y., Sheng, C. and Kavianpour, M.R. Comprehensive evaluation of four high‐resolution satellite precipitation products under diverse climate conditions in Iran. Hydrological Sciences Journal, 61( 2), 420– 440 (2016)

  • Muller, M.F., Thompson, S.E.: Bias adjustment of satellite rainfall data through stochastic modeling: methods development and application to Nepal. Adv. Water Res. 60(2013), 121–134 (2013)

    Google Scholar 

  • Nespor, V., Sevruk, B.: Estimation of wind-induced error of rainfall gauge measurements using a numerical simulation. J. Atmos. Ocean. Technol. 16(4), 450–464 (1999)

    Google Scholar 

  • Panegrossi, G., Dietrich, S., Marzano, F.S., et al.: Use of cloud model microphysics for passive microwave-based precipitation retrieval: significance of consistency between model and measurement manifolds. J. Atmos. Sci. 55, 1644–1673 (1998)

    Google Scholar 

  • Prakash, S., Mitra, A.K., Momin, I.M., Pai, D.S., Rajagopal, E.N., Basu, S.: Comparison of TMPA-3B42 versions 6 and 7 precipitation products with gauge based data over India for the south-west monsoon period. J. Hydrometeorol. 16(1), 346–362 (2015a)

    Google Scholar 

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

    Google Scholar 

  • Prakash, S., Mitra, A.K., AghaKouchak, A., Pai, D.S.: Error characterization of TRMM multisatellite precipitation analysis (TMPA-3B42) products over India for different seasons. J. Hydrol. 529(P3), 1302–1312 (2015c)

    Google Scholar 

  • Prakash, S,. Mitra, A., and AghaKouchak, A.. A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region. Journal of Hydrology, 556, 865-876 (2016)

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

    Google Scholar 

  • Ringard, J., Becker, M., Seyler, F., Linguet, L.: Temporal and spatial assessment of four satellite rainfall estimates over French Guiana and North Brazil. Remote Sens. 7(12), 16441–16459 (2015)

    Google Scholar 

  • Salma, S., Rehman, S., Shah, M.A.: Rainfall trends in different climate zones of Pakistan. Pak. J. Meteorol. 9(17), 37–47 (2012)

    Google Scholar 

  • Scheel, M., Rohrer, M., Huggel, C., Villar, D., Silvestre, E., Huffman, G.: Evaluation of TRMM multi-satellite precipitation analysis (TMPA) performance in the Central Andes region and its dependency on spatial and temporal resolution. Hydrol. Earth Syst. Sci. Discuss. 15(8), 2649–2663 (2011)

    Google Scholar 

  • Sun, R., Yuan, H., Liu, X., Jiang, X.: Evaluation of the latest satellite-gauge precipitation products and their hydrologic applications over the Huaihe River basin. J. Hydrol. 536, 302–319 (2016)

    Google Scholar 

  • Tang, G., Yingzhao, M., Long, D., et al.: Evaluation of GPM Day-1 IMERG and TMPA Version-7 legacy products over mainland China at multiple spatiotemporal scales. J. Hydrol. 533(2016), 152–167 (2016)

    Google Scholar 

  • Tobin, K.J., Bennett, M.E.: Adjusting satellite precipitation data to facilitate hydrologic modeling. J. Hydrometeorol. 11, 966–978 (2010)

    Google Scholar 

  • Toté, C., Patricio, D., Boogaard, H., Van-der-Wijngaart, R., Tarnavsky, E., Funk, C.: Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique. Remote Sens. 7(2), 1758–1776 (2015)

    Google Scholar 

  • Ward, E., Buytaert, W., Peaver, L., Wheater, H.: Evaluation of precipitation products over complex mountainous terrain: a water resources perspective. Adv. Water Res. 34(10), 1222–1231 (2011)

    Google Scholar 

  • Yuan, F., Zhang, L., Win, K.W.W., Ren, L., Zhao, C., Zhu, Y., Jiang, S., Liu, Y.: Assessment of GPM and TRMM multi-satellite precipitation products in stream flow simulations in a data-sparse mountainous watershed in Myanmar. Remote Sens. 9(3), 302 (2017)

    Google Scholar 

  • Zambrano-Bigiarini, M., Nauditt, A., Birkel, C., Verbist, K., Ribbe, L.: Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile. Hydrol. Earth Syst. Sci. 21(2), 1295–1320 (2016)

    Google Scholar 

  • Zhao, T., Fu, C.: Comparison of products from ERA-40, NCEP-2, and CRU with station data for summer precipitation over China. Adv. Atmos. Sci. 23(4), 593–604 (2006)

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank Center of Excellence in Water Resource Engineering for support in conducting this study. The authors are also grateful to Pakistan Meteorological Department (PMD) for providing the rain gauge data used in the study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Muhammad Masood.

Additional information

Responsible Editor: Soon-Il An.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Masood, M., Shakir, A.S., Azhar, A.H. et al. Assessment of Real Time, Multi-Satellite Precipitation Products under Diverse Climatic and Topographic Conditions. Asia-Pacific J Atmos Sci 56, 577–591 (2020). https://doi.org/10.1007/s13143-019-00166-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13143-019-00166-1

Keywords

Navigation