Editorial Type:
Article
Article Type:
Research Article

Verification of Tropical Cyclone–Related Satellite Precipitation Estimates in Mainland China

Zifeng Yu Shanghai Typhoon Institute, and Laboratory of Typhoon Forecast Technique, China Meteorological Administration, Shanghai, China

Search for other papers by Zifeng Yu in
Current site
Google Scholar
PubMed Close
,
Hui Yu Shanghai Typhoon Institute, and Laboratory of Typhoon Forecast Technique, China Meteorological Administration, Shanghai, China

Search for other papers by Hui Yu in
Current site
Google Scholar
PubMed Close
,
Peiyan Chen Shanghai Typhoon Institute, and Laboratory of Typhoon Forecast Technique, China Meteorological Administration, Shanghai, China

Search for other papers by Peiyan Chen in
Current site
Google Scholar
PubMed Close
,
Chuanhai Qian National Meteorological Center, China Meteorological Administration, Beijing, China

Search for other papers by Chuanhai Qian in
Current site
Google Scholar
PubMed Close
, and
Caijun Yue Shanghai Typhoon Institute, and Laboratory of Typhoon Forecast Technique, China Meteorological Administration, Shanghai, China

Search for other papers by Caijun Yue in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Nov 2009
DOI:
https://doi.org/10.1175/2009JAMC2143.1
Page(s):
2227–2241
Restricted access

Abstract

To evaluate the abilities of satellite retrievals in reflecting precipitation features related to tropical cyclones (TCs) affecting mainland China, four years of 6- and 24-h precipitation retrievals from three datasets, namely the Tropical Rainfall Measuring Mission satellite algorithm 3B42, version 6 (3B42), Climate Prediction Center morphed (CMORPH) product, and one based on the Geostationary Meteorological Satellite-5 infrared brightness temperature (GMS5-TBB), are compared statistically with direct measurements from surface gauge rainfall data during the periods affected by TCs. The GMS5-TBB dataset was set up by a method of considering the GMS5-TBB characteristics, hourly precipitation intensity, and horizontal distribution for landfalling TCs. The results show that in a general sense, all three satellite-retrieved rainfall datasets give quite reasonable 6- and 24-h rainfall distributions, with skill decreasing with the increase in both latitude and rainfall amount. The 3B42 has a little bit better skill than CMORPH, which is likely related to the fact that the 3B42 product has a rain gauge adjustment and CMORPH does not. Further analyses show that both 3B42 and CMORPH considerably underestimate the moderate and heavy rainfall and overestimate the very light precipitation. The overestimation of the GMS5-TBB data for the light rain is larger than that for 3B42 and CMORPH, probably due to the fact that the GMS5-TBB method considers stratiform and convective rainfall separately with a fixed stratiform rain rate of 2 mm h−1. For the heavy rainfall events, the GMS5-TBB data perform much better than the 3B42 and CMORPH data with an almost halved bias, owing to the fact that the GMS5-TBB method adopted the adjustment of the convective rain rate by considering TBB characteristics of landfalling TCs and using hourly gauge rainfall in the setup process. Since the heavy rainfall events associated with landfalling TCs are of the most concern, the compared GMS5-TBB data could be useful as an operational/research reference.

Corresponding author address: Zifeng Yu, Shanghai Typhoon Institute, 166 Puxi Road, Xujiahui, Shanghai 200030, China. Email: yuzf@mail.typhoon.gov.cn

Abstract

To evaluate the abilities of satellite retrievals in reflecting precipitation features related to tropical cyclones (TCs) affecting mainland China, four years of 6- and 24-h precipitation retrievals from three datasets, namely the Tropical Rainfall Measuring Mission satellite algorithm 3B42, version 6 (3B42), Climate Prediction Center morphed (CMORPH) product, and one based on the Geostationary Meteorological Satellite-5 infrared brightness temperature (GMS5-TBB), are compared statistically with direct measurements from surface gauge rainfall data during the periods affected by TCs. The GMS5-TBB dataset was set up by a method of considering the GMS5-TBB characteristics, hourly precipitation intensity, and horizontal distribution for landfalling TCs. The results show that in a general sense, all three satellite-retrieved rainfall datasets give quite reasonable 6- and 24-h rainfall distributions, with skill decreasing with the increase in both latitude and rainfall amount. The 3B42 has a little bit better skill than CMORPH, which is likely related to the fact that the 3B42 product has a rain gauge adjustment and CMORPH does not. Further analyses show that both 3B42 and CMORPH considerably underestimate the moderate and heavy rainfall and overestimate the very light precipitation. The overestimation of the GMS5-TBB data for the light rain is larger than that for 3B42 and CMORPH, probably due to the fact that the GMS5-TBB method considers stratiform and convective rainfall separately with a fixed stratiform rain rate of 2 mm h−1. For the heavy rainfall events, the GMS5-TBB data perform much better than the 3B42 and CMORPH data with an almost halved bias, owing to the fact that the GMS5-TBB method adopted the adjustment of the convective rain rate by considering TBB characteristics of landfalling TCs and using hourly gauge rainfall in the setup process. Since the heavy rainfall events associated with landfalling TCs are of the most concern, the compared GMS5-TBB data could be useful as an operational/research reference.

Corresponding author address: Zifeng Yu, Shanghai Typhoon Institute, 166 Puxi Road, Xujiahui, Shanghai 200030, China. Email: yuzf@mail.typhoon.gov.cn

Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Adler, R. F., and A. J. Negri, 1988: A satellite infrared technique to estimate tropical convective and stratiform rainfall. J. Appl. Meteor., 27 , 31–51.

    • Search Google Scholar
    • Export Citation

  • Bell, T. L., and P. K. Kundu, 2003: Comparing satellite rainfall estimates with rain gauge data: Optimal strategies suggested by a spectral model. J. Geophys. Res., 108 , 4121. doi:10.1029/2002JD002641.

    • Search Google Scholar
    • Export Citation

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

  • Chen, S. S., J. A. Knaff, and F. D. Marks Jr., 2006: Effects of vertical wind shear and storm motion on tropical cyclone rainfall asymmetries deduced from TRMM. Mon. Wea. Rev., 134 , 3190–3208.

    • Search Google Scholar
    • Export Citation

  • Chokngamwong, R., and L. S. Chiu, 2008: Thailand daily rainfall and comparison with TRMM products. J. Hydrometeor., 9 , 256–266.

  • Demirtas, M., and Coauthors, 2005: The developmental testbed center verification system. Sixth WRF Users’ Workshop Paper, 3.23. [Available online at http://www.mmm.ucar.edu/wrf/users/workshops/WS2005/abstracts/Session3/23-DEMIRTAS.pdf].

    • Search Google Scholar
    • Export Citation

  • Ding, W., Q. Wan, and Y. Duan, 2005: 3D-Var assimilation of TRMM rain rate and its impact on the Typhoon Dujuan (0313) forecast (in Chinese). Chinese J. Atmos. Sci., 29 , 600–608.

    • Search Google Scholar
    • Export Citation

  • Donaldson, R. J., R. M. Dyer, and M. J. Kraus, 1975: An objective evaluator of techniques for predicting severe weather events. Preprints, Ninth Conf. on Severe Local Storms, Norman, OK, Amer. Meteor. Soc., 321–326.

    • Search Google Scholar
    • Export Citation

  • Ensor, L. A., and S. M. Robeson, 2008: Statistical characteristics of daily precipitation: Comparisons of gridded and point datasets. J. Appl. Meteor. Climatol., 47 , 2468–2476.

    • Search Google Scholar
    • Export Citation

  • Ferraro, R. R., 1997: SSM/I derived global rainfall estimates for climatological applications. J. Geophys. Res., 102 , 16715–16735.

  • Ferraro, R. R., F. Weng, N. C. Grody, and L. Zhao, 2000: Precipitation characteristics over land from the NOAA-15 AMSU sensor. Geophys. Res. Lett., 27 , 2669–2672.

    • Search Google Scholar
    • Export Citation

  • Goldenberg, S. B., R. A. Houze, and D. D. Churchill, 1990: Convective and stratiform components of a winter monsoon cloud cluster determined from geosynchronous infrared satellite data. J. Meteor. Soc. Japan, 68 , 37–62.

    • Search Google Scholar
    • Export Citation

  • Gottschalck, J., J. Meng, M. Rodell, and P. Houser, 2005: Analysis of multiple precipitation products and preliminary assessment of their impact on Global Land Data Assimilation System (GLDAS) land surface states. J. Hydrometeor., 6 , 573–598.

    • Search Google Scholar
    • Export Citation

  • He, H., M. Cheng, and F. Zhou, 2006: 3D structure of rain and cloud hydrometeors for Typhoon Kujira (0302) (in Chinese). Chinese J. Atmos. Sci., 30 , 491–503.

    • Search Google Scholar
    • Export Citation

  • Hou, A. Y., and S. Q. Zhang, 2007: Assimilation of precipitation information using column model physics as a weak constraint. J. Atmos. Sci., 64 , 3865–3878.

    • Search Google Scholar
    • Export Citation

  • Hou, A. Y., S. Q. Zhang, A. M. da Silva, W. S. Olson, C. D. Kummerow, and J. Simpson, 2001: Improving global analysis and short-range forecast using rainfall and moisture observations derived from TRMM and SSM/I passive microwave sensors. Bull. Amer. Meteor. Soc., 82 , 659–679.

    • Search Google Scholar
    • Export Citation

  • Hou, A. Y., S. Q. Zhang, and O. Reale, 2004: Variational continuous assimilation of TMI and SSM/I rain rates: Impact on GEOS-3 on hurricane analyses and forecasts. Mon. Wea. Rev., 132 , 2094–2109.

    • Search Google Scholar
    • Export Citation

  • Huffman, G. J., R. F. Adler, B. Rudolf, U. Schneider, and P. R. Keehn, 1995: Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model precipitation information. J. Climate, 8 , 1284–1295.

    • Search Google Scholar
    • Export Citation

  • Huffman, G. J., and Coauthors, 1997: The Global Precipitation Climatology Project (GPCP) combined precipitation dataset. Bull. Amer. Meteor. Soc., 78 , 5–20.

    • Search Google Scholar
    • Export Citation

  • Huffman, G. J., and Coauthors, 2007: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J. Hydrometeor., 8 , 38–55.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Kikuchi, K., and B. Wang, 2008: Diurnal precipitation regimes in the global Tropics. J. Climate, 21 , 2680–2696.

  • Kummerow, C., W. Barnes, T. Kozu, J. Shiue, and J. Simpson, 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15 , 809–817.

    • Search Google Scholar
    • Export Citation

  • Kummerow, C., and Coauthors, 2001: Evolution of the Goddard Profiling Algorithm (GPROF) for rainfall estimation from passive microwave sensors. J. Appl. Meteor., 40 , 1801–1820.

    • Search Google Scholar
    • Export Citation

  • Li, J., L. Wang, and F. Zhou, 1993: Convective and stratiform cloud rainfall estimation from geostationary satellite data. Adv. Atmos. Sci., 10 , 475–480.

    • Search Google Scholar
    • Export Citation

  • Lonfat, M., F. D. Marks Jr., and S. S. Chen, 2004: Precipitation distribution in tropical cyclones using the Tropical Rainfall Measuring Mission (TRMM) microwave imager: A global perspective. Mon. Wea. Rev., 132 , 1645–1660.

    • Search Google Scholar
    • Export Citation

  • Morrissey, M. L., and J. S. Greene, 1993: Comparison of two satellite-based rainfall algorithms using Pacific atoll raingage data. J. Appl. Meteor., 32 , 411–425.

    • Search Google Scholar
    • Export Citation

  • Nesbitt, S. W., and E. J. Zipser, 2003: The diurnal cycle of rainfall and convective intensity according to three years of TRMM measurements. J. Climate, 16 , 1456–1475.

    • Search Google Scholar
    • Export Citation

  • Nicholson, S. E., and Coauthors, 2003a: Validation of TRMM and other rainfall estimates with a high-density gauge dataset for West Africa. Part I: Validation of GPCC rainfall product and pre-TRMM satellite and blended products. J. Appl. Meteor., 42 , 1337–1354.

    • Search Google Scholar
    • Export Citation

  • Nicholson, S. E., and Coauthors, 2003b: Validation of TRMM and other rainfall estimates with a high-density gauge dataset for West Africa. Part II: Validation of TRMM rainfall products. J. Appl. Meteor., 42 , 1355–1368.

    • Search Google Scholar
    • Export Citation

  • Pu, Z., W-K. Tao, S. Braun, J. Simpson, Y. Jia, J. Halverson, W. Olson, and A. Hou, 2002: The impact of TRMM data on mesoscale numerical simulation of Supertyphoon Paka. Mon. Wea. Rev., 130 , 2448–2458.

    • Search Google Scholar
    • Export Citation

  • Ruane, A. C., and J. O. Roads, 2007: 6-hour to 1-year variance of five global precipitation sets. Earth Interactions, 11. [Available online at http://EarthInteractions.org].

    • Search Google Scholar
    • Export Citation

  • Schaefer, J. T., 1990: The critical success index as an indicator of warning skill. Wea. Forecasting, 5 , 570–575.

  • Serra, Y. L., and M. J. McPhaden, 2003: Multiple time- and space-scale comparisons of ATLAS rain gauge measurements with TRMM satellite precipitation measurements. J. Appl. Meteor., 42 , 1045–1059.

    • Search Google Scholar
    • Export Citation

  • Simpson, J., R. F. Adler, and G. R. North, 1988: A proposed Tropical Rainfall Measuring Mission (TRMM) satellite. Bull. Amer. Meteor. Soc., 69 , 278–295.

    • Search Google Scholar
    • Export Citation

  • Sorooshian, S., K. Hsu, X. Gao, H. V. Gupta, B. Imam, and D. Braithwaite, 2000: Evaluation of PERSIANN system satellite–based estimates of tropical rainfall. Bull. Amer. Meteor. Soc., 81 , 2035–2046.

    • Search Google Scholar
    • Export Citation

  • Wang, X., C. Tang, X. Liu, and Q. Xia, 2007a: Cloud characters of typhoon SAOMAI on the TRMM satellite data (in Chinese). Meteor. Disaster Reduct. Res., 30 , 7–11.

    • Search Google Scholar
    • Export Citation

  • Wang, Y., L. Zhou, and K. Hamilton, 2007b: Effect of convective entrainment/detrainment on simulation of tropical precipitation diurnal cycle. Mon. Wea. Rev., 135 , 567–585.

    • Search Google Scholar
    • Export Citation

  • Xie, P., and P. A. Arkin, 1995: An intercomparison of gauge observations and satellite estimates of monthly precipitation. J. Appl. Meteor., 34 , 1143–1160.

    • Search Google Scholar
    • Export Citation

  • Yang, D., B. E. Goodison, J. R. Metcalfe, V. S. Golubev, R. Bates, T. Pangburn, and C. L. Hanson, 1998: Accuracy of NWS 8” standard nonrecording precipitation gauge: Results and application of WMO intercomparison. J. Atmos. Oceanic Technol., 15 , 54–68.

    • Search Google Scholar
    • Export Citation

  • Yang, S., and E. A. Smith, 2006: Mechanisms for diurnal variability of global tropical rainfall observed from TRMM. J. Climate, 19 , 5190–5226.

    • Search Google Scholar
    • Export Citation

  • Yue, C., P. Chen, X. Lei, and Y. Yang, 2006a: A preliminary study on method of Quantitative Precipitation Estimation (QPE) for landfall typhoon (in Chinese). Sci. Meteor. Sin., 26 , 17–23.

    • Search Google Scholar
    • Export Citation

  • Yue, C., P. Chen, X. Lei, and Y. Yang, 2006b: Preliminary study of short-term quantitative precipitation forecast method for landfalling typhoon (in Chinese). Sci. Meteor. Sin., 34 , 7–11.

    • Search Google Scholar
    • Export Citation

  • Zhang, Q., M. Tu, S. Ma, Z. Yang, and Y. Luo, 2007: Quality assessment of the observational data of automatic precipitation stations in China (in Chinese). J. Appl. Meteor. Sci., 18 , 365–372.

    • Search Google Scholar
    • Export Citation

  • Zhou, L., and Y. Wang, 2006: Tropical Rainfall Measuring Mission observation and regional model study of precipitation diurnal cycle in the New Guinean region. J. Geophys. Res., 111 , D17104. doi:10.1029/2006JD007243.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 659 135 19
PDF Downloads 397 129 10