Skip to main content
Log in

Comparisons of Gauge, TMPA and IMERG Products for Monsoon and Tropical Cyclone Precipitation in Southern China

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM) Mission (IMERG) products are compared against 447 quality-controlled rain gauges in southern China (SC) during summer (May to August) for the period 2014–2016. The differences of TMPA and IMERG in measuring the monsoon and tropical cyclone (TC) precipitation, considering the mean spatial patterns, and rainfall intensities are evaluated quantitatively. Statistical analysis shows that IMERG has much higher correlations of precipitation frequency (PF) with gauge observations for monsoon and TC precipitation. However, both satellite-based products show much poorer capability in estimating conditional rainfall and PF for TC precipitation, especially for estimating large conditional rainfall in TC systems. The capability of capturing the precipitation events at different rainfall intensities decreases with the increase of rainfall threshold for both monsoon and TC precipitation. Generally, IMERG exhibits a superior ability to detect precipitation at different rainfall intensities than TMPA. In depicting the diurnal cycles, IMERG shows a much better performance in estimating rainfall and PF for monsoon precipitation than TMPA by revealing the comparable diurnal amplitudes to the rain gauges, whereas TMPA fails to accurately estimate the early morning rainfall and PF. As a successor to TMPA, IMERG is a reliable source of precipitation estimates for future studies on precipitation meteorology.

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
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Alexander, L. V., Zhang, X., Peterson, T. C., Caesar, J., Gleason, B., Klein Tank, A. M. G., et al. (2006). Global observed changes in daily climate extremes of temperature and precipitation. Journal of Geophysical Research, 111(D5), D05109.

    Article  Google Scholar 

  • Asong, Z., Razavi, S., Wheater, H., & Wong, J. (2017). Evaluation of integrated multisatellite retrievals for GPM (IMERG) over Southern Canada against ground precipitation observations: a preliminary assessment. Journal of Hydrometeorology, 18(4), 1033–1050.

    Article  Google Scholar 

  • Chen, Y., Ebert, E. E., Walsh, K. J., & Davidson, N. E. (2013). Evaluation of TMPA 3B42 daily precipitation estimates of tropical cyclone rainfall over Australia. Journal of Geophysical Research, 118(21), 11966–11978.

    Google Scholar 

  • Chen, F., & Fu, Y. (2015). Contribution of tropical cyclone rainfall at categories to total precipitation over the Western North Pacific from 1998 to 2007. Science China Earth Sciences, 58(11), 2015–2025.

    Article  Google Scholar 

  • Chen, G., Sha, W., & Iwasaki, T. (2009). Diurnal variation of precipitation over southeastern China: spatial distribution and its seasonality. Journal of Geophysical Research, 114(D13), D13103.

    Article  Google Scholar 

  • Dai, A., Lin, X., & Hsu, K.-L. (2007). The frequency, intensity, and diurnal cycle of precipitation in surface and satellite observations over low-and mid-latitudes. Climate Dynamics, 29(7–8), 727–744.

    Article  Google Scholar 

  • Dee, D. P., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S., et al. (2011). The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553–597.

    Article  Google Scholar 

  • Deng, X., Tie, X., Wu, D., Zhou, X., Bi, X., Tan, H., et al. (2008). Long-term trend of visibility and its characterizations in the Pearl River Delta (PRD) region. China Atmospheric Environment, 42(7), 1424–1435. https://doi.org/10.1016/j.atmosenv.2007.11.025.

    Article  Google Scholar 

  • Ebert, E. E., Janowiak, J. E., & Kidd, C. (2007). Comparison of near-real-time precipitation estimates from satellite observations and numerical models. Bulletin of the American Meteorological Society, 88(1), 47–64.

    Article  Google Scholar 

  • Fengjin, X., & Ziniu, X. (2010). Characteristics of tropical cyclones in China and their impacts analysis. Natural Hazards, 54(3), 827–837.

    Article  Google Scholar 

  • Fischer, E., & Knutti, R. (2014). Detection of spatially aggregated changes in temperature and precipitation extremes. Geophysical Research Letters, 41(2), 547–554.

    Article  Google Scholar 

  • Fu, Y., Chen, F., Liu, G., Yang, Y., Yuan, R., Li, R., et al. (2016). Recent trends of summer convective and stratiform precipitation in mid-eastern China. Scientific Reports, 5, 6.

    Google Scholar 

  • Hong, Y., Hsu, K.-L., Moradkhani, H., & Sorooshian, S. (2006). Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response. Water Resources Research, 42(8), W08421.

    Article  Google Scholar 

  • Huffman, G. J., Adler, R. F., Bolvin, D. T., & Nelkin, E. J. (2010). The TRMM multi-satellite precipitation analysis (TMPA). In Satellite rainfall applications for surface hydrology (pp. 3–22). Heidelberg: Springer.

    Book  Google Scholar 

  • Huffman, G. J., Bolvin, D. T., Braithwaite, D., Hsu, K., Joyce, R., Xie, P., et al. (2014). NASA global precipitation measurement (GPM) integrated multi-satellite retrievals for GPM (IMERG). Algorithm Theoretical Basis Document (ATBD), NASA/GSFC, Greenbelt, MD, USA.

  • Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G., et al. (2007). The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1), 38–55.

    Article  Google Scholar 

  • Iguchi, T., Kozu, T., Kwiatkowski, J., Meneghini, R., Awaka, J., Okamoto, K., et al. (2009). Uncertainties in the Rain Profiling Algorithm for the TRMM Precipitation Radar (1. Precipitation Radar (PR), Precipitation Measurements from Space). Journal of the Meteorological Society of Japan, 87(3), 1–30.

    Article  Google Scholar 

  • Jiang, Z., Zhang, D.-L., Xia, R., & Qian, T. (2017). Diurnal Variations of Presummer Rainfall over Southern China. Journal of Climate, 30(2), 755–773.

    Article  Google Scholar 

  • Kidd, C., & Levizzani, V. (2011). Status of satellite precipitation retrievals. Hydrology and Earth System Sciences, 15(4), 1109–1116.

    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. Atmospheric Research, 187, 95–105.

    Article  Google Scholar 

  • Li, J., Yu, R., & Zhou, T. (2008). Seasonal variation of the diurnal cycle of rainfall in southern contiguous China. Journal of Climate, 21(22), 6036–6043.

    Article  Google Scholar 

  • Liu, P., & Fu, Y. (2010). Climatic characteristics of summer convective and stratiform precipitation in southern China based on measurements by TRMM precipitation radar. Chinese J Atmos Sci, 34, 802–814.

    Google Scholar 

  • Liu, R., Liu, S. C., Cicerone, R. J., Shiu, C.-J., Li, J., Wang, J., et al. (2015). Trends of extreme precipitation in eastern China and their possible causes. Advances in Atmospheric Sciences, 32(8), 1027.

    Article  Google Scholar 

  • Liu, C., Zipser, E. J. (2008). Diurnal cycles of precipitation, clouds, and lightning in the tropics from 9 years of TRMM observations. Geophysical Research Letters, 35(4), L04819. https://doi.org/10.1029/2007GL032437.

    Google Scholar 

  • Luo, Y., Wang, H., Zhang, R., Qian, W., & Luo, Z. (2013). Comparison of rainfall characteristics and convective properties of monsoon precipitation systems over South China and the Yangtze and Huai River Basin. Journal of Climate, 26(1), 110–132.

    Article  Google Scholar 

  • Manz, B., Páez-Bimos, S., Horna, N., Buytaert, W., Ochoa-Tocachi, B., Lavado-Casimiro, W., et al. (2017). Comparative ground validation of IMERG and TMPA at variable spatio-temporal scales in the tropical andes. Journal of Hydrometeorology, 18, 2469–2489.

    Article  Google Scholar 

  • Mehran, A., & AghaKouchak, A. (2013). Capabilities of satellite precipitation datasets to estimate heavy precipitation rates at different temporal accumulations. Hydrological Processes, 28(4), 2262–2270. https://doi.org/10.1002/hyp.9779.

    Article  Google Scholar 

  • Mei, Y., Nikolopoulos, E. I., Anagnostou, E. N., & Borga, M. (2016). Evaluating satellite precipitation error propagation in runoff simulations of mountainous basins. Journal of Hydrometeorology, 17(5), 1407–1423.

    Article  Google Scholar 

  • Min, S.-K., Zhang, X., Zwiers, F. W., & Hegerl, G. C. (2011). Human contribution to more-intense precipitation extremes. Nature, 470(7334), 378–381.

    Article  Google Scholar 

  • Nijssen, B., & Lettenmaier, D. P. (2004). Effect of precipitation sampling error on simulated hydrological fluxes and states: anticipating the Global Precipitation Measurement satellites. Journal of Geophysical Research, 109(D2), D02103.

    Article  Google Scholar 

  • Oki, T., & Kanae, S. (2006). Global hydrological cycles and world water resources. Science, 313(5790), 1068–1072.

    Article  Google Scholar 

  • Oliveira, R., Maggioni, V., Vila, D., & Morales, C. (2016). Characteristics and diurnal cycle of GPM rainfall estimates over the central amazon region. Remote Sensing, 8(7), 544.

    Article  Google Scholar 

  • Prakash, S., Mitra, A. K., Pai, D., & AghaKouchak, A. (2016). From TRMM to GPM: How well can heavy rainfall be detected from space? Advances in Water Resources, 88, 1–7.

    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 

  • Su, F., Hong, Y., & Lettenmaier, D. P. (2008). Evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) and its utility in hydrologic prediction in the La Plata Basin. Journal of Hydrometeorology, 9(4), 622–640.

    Article  Google Scholar 

  • Tang, G., Zeng, Z., Long, D., Guo, X., Yong, B., Zhang, W., et al. (2016). Statistical and hydrological comparisons between TRMM and GPM level-3 products over a midlatitude basin: Is day-1 IMERG a good successor for TMPA 3B42V7? Journal of Hydrometeorology, 17(1), 121–137.

    Article  Google Scholar 

  • Tapiador, F. J., Turk, F. J., Petersen, W., Hou, A. Y., García-Ortega, E., Machado, L. A., et al. (2012). Global precipitation measurement: methods, datasets and applications. Atmospheric Research, 104, 70–97.

    Article  Google Scholar 

  • Tian, Y., Peters-Lidard, C. D., Choudhury, B. J., & Garcia, M. (2007). Multitemporal analysis of TRMM-based satellite precipitation products for land data assimilation applications. Journal of Hydrometeorology, 8(6), 1165–1183. https://doi.org/10.1175/2007JHM859.1.

    Article  Google Scholar 

  • Tian, Y., Peters-Lidard, C. D., Eylander, J. B., Joyce, R. J., Huffman, G. J., Adler, R. F., et al. (2009). Component analysis of errors in satellite-based precipitation estimates. Journal of Geophysical Research, 114(D24), D24101.

    Article  Google Scholar 

  • Wang, Y., Wan, Q., Meng, W., & Liao, F. (2011). Long-term impacts of aerosols on precipitation and lightning over the Pearl River Delta megacity area in China. Atmospheric Chemistry and Physics (ACP) and Discussions (ACPD). https://doi.org/10.5194/acp-11-12421-2011.

    Google Scholar 

  • Wu, D., Tie, X., Li, C., Ying, Z., Kai-Hon Lau, A., Huang, J., et al. (2005). An extremely low visibility event over the Guangzhou region: a case study. Atmospheric Environment, 39(35), 6568–6577. https://doi.org/10.1016/j.atmosenv.2005.07.061.

    Article  Google Scholar 

  • Ying, M., Zhang, W., Yu, H., Lu, X., Feng, J., Fan, Y., et al. (2014). An overview of the China Meteorological Administration tropical cyclone database. Journal of Atmospheric and Oceanic Technology, 31(2), 287–301.

    Article  Google Scholar 

  • Yu, R., Li, J., Yuan, W., & Chen, H. (2010). Changes in characteristics of late-summer precipitation over eastern China in the past 40 years revealed by hourly precipitation data. Journal of Climate, 23(12), 3390–3396.

    Article  Google Scholar 

  • Yuan, W., Yu, R., Chen, H., Li, J., & Zhang, M. (2010). Subseasonal characteristics of diurnal variation in summer monsoon rainfall over central eastern China. Journal of Climate, 23(24), 6684–6695.

    Article  Google Scholar 

  • Zhang, Q., Liu, Q., & Wu, L. (2009). Tropical cyclone damages in China 1983–2006. Bulletin of the American Meteorological Society, 90(4), 489–495.

    Article  Google Scholar 

  • Zhou, T., Yu, R., Chen, H., Dai, A., & Pan, Y. (2008). Summer precipitation frequency, intensity, and diurnal cycle over China: a comparison of satellite data with rain gauge observations. Journal of Climate, 21(16), 3997–4010.

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to the NASA Goddard Space Flight Center’s Mesoscale Atmospheric Processes Laboratory and Precipitation Processing System (PPS) for providing the TMPA and IMERG data. The rain gauge data were provided by CMA. This work has been jointly supported by Natural Science Foundation of Anhui Province, China (Grant 1808085MD99), National Natural Science Foundation of China (Grant 41805023) and the Masters and Doctor Fund of Anhui Meteorological Bureau (Grant RC201701).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hao Huang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, F., Huang, H. Comparisons of Gauge, TMPA and IMERG Products for Monsoon and Tropical Cyclone Precipitation in Southern China. Pure Appl. Geophys. 176, 1767–1784 (2019). https://doi.org/10.1007/s00024-018-2038-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-018-2038-z

Keywords

Navigation