Climatology and Interannual Variability of Quasi-Global Intense Precipitation Using Satellite Observations

Martina Ricko SGT Inc., Greenbelt, Maryland

Search for other papers by Martina Ricko in
Current site
Google Scholar
PubMed
Close
,
Robert F. Adler Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

Search for other papers by Robert F. Adler in
Current site
Google Scholar
PubMed
Close
, and
George J. Huffman NASA Goddard Space Flight Center, Greenbelt, Maryland

Search for other papers by George J. Huffman in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Climatology and variations of recent mean and intense precipitation over a near-global (50°S–50°N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998–2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value (e.g., 25 and 50 mm day−1). All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation ≥ 25 mm day−1, defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Niño–Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.

Corresponding author address: Martina Ricko, SGT Inc., 7701 Greenbelt Rd., Suite 400, Greenbelt, MD 20770. E-mail: mricko@sgt-inc.com

Abstract

Climatology and variations of recent mean and intense precipitation over a near-global (50°S–50°N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998–2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value (e.g., 25 and 50 mm day−1). All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation ≥ 25 mm day−1, defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Niño–Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.

Corresponding author address: Martina Ricko, SGT Inc., 7701 Greenbelt Rd., Suite 400, Greenbelt, MD 20770. E-mail: mricko@sgt-inc.com
Save
  • Adler, R. F., and Coauthors, 2003: The Version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, doi:10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Adler, R. F., G. Gu, J.-J. Wang, G. J. Huffman, S. Curtis, and D. Bolvin, 2008: Relationships between global precipitation and surface temperature on interannual and longer timescales (1979–2006). J. Geophys. Res., 113, D22104, doi:10.1029/2008JD010536.

    • Search Google Scholar
    • Export Citation
  • Adler, R. F., J.-J. Wang, G. Gu, and G. J. Huffman, 2009: A ten-year tropical rainfall climatology based on a composite of TRMM products. J. Meteor. Soc. Japan, 87A, 281293, doi:10.2151/jmsj.87A.281.

    • Search Google Scholar
    • Export Citation
  • Allan, R. P., and B. J. Soden, 2008: Atmospheric warming and the amplification of precipitation extremes. Science, 321, 14811484, doi:10.1126/science.1160787.

    • Search Google Scholar
    • Export Citation
  • Arkin, P., J. Turk, and B. Ebert, 2005: Pilot Evaluation of High Resolution Precipitation Products (PEHRPP): A contribution to GPM planning. The 5th Global Precipitation Measurement (GPM) Int. Planning Workshop, Tokyo, Japan, Japan Aerospace Exploration Agency. [Available online at http://www.eorc.jaxa.jp/GPM/ws5/en/materials/6.8.3_abstract_Arkin.pdf.]

  • Benestad, R. E., 2013: Association between trends in daily rainfall percentiles and the global mean temperature. J. Geophys. Res. Atmos., 118, 10 80210 810, doi:10.1002/jgrd.50814.

    • Search Google Scholar
    • Export Citation
  • Benestad, R. E., D. Nychka, and L. O. Mearns, 2012: Spatially and temporally consistent prediction of heavy precipitation from mean values. Nat. Climate Change, 2, 544547, doi:10.1038/nclimate1497.

    • Search Google Scholar
    • Export Citation
  • Cavalcanti, I. F. A., 2012: Large scale and synoptic features associated with extreme precipitation over South America: A review and case studies for the first decade of the 21st century. Atmos. Res., 118, 2740, doi:10.1016/j.atmosres.2012.06.012.

    • Search Google Scholar
    • Export Citation
  • Curtis, S., A. Salahuddin, R. F. Adler, G. J. Huffman, G. Gu, and Y. Hong, 2007: Precipitation extremes estimated by GPCP and TRMM: ENSO relationships. J. Hydrometeor., 8, 678689, doi:10.1175/JHM601.1.

    • Search Google Scholar
    • Export Citation
  • Dai, A., 2011: Drought under global warming: A review. Wiley Interdiscip. Rev.: Climate Change, 2, 4565, doi:10.1002/wcc.81.

  • Dai, A., I. Y. Fung, and A. D. Del Genio, 1997: Surface observed global land precipitation variations during 1900–88. J. Climate, 10, 29432962, doi:10.1175/1520-0442(1997)010<2943:SOGLPV>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Easterling, D. R., J. L. Evans, P. Y. Groisman, T. R. Karl, K. E. Kunkel, and P. Ambenje, 2000: Observed variability and trends in extreme climate events: A brief review. Bull. Amer. Meteor. Soc., 81, 417425, doi:10.1175/1520-0477(2000)081<0417:OVATIE>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ebert, E. E., J. Janowiak, and C. Kidd, 2007: Comparison of near-real-time precipitation estimates from satellite observations and numerical models. Bull. Amer. Meteor. Soc., 88, 4764, doi:10.1175/BAMS-88-1-47.

    • Search Google Scholar
    • Export Citation
  • Grimm, A. M., 2011: Interannual climate variability in South America: Impacts on seasonal precipitation, extreme events, and possible effects of climate change. Stochastic Environ. Res. Risk Assess., 25, 537554, doi:10.1007/s00477-010-0420-1.

    • Search Google Scholar
    • Export Citation
  • Grimm, A. M., and R. G. Tedeschi, 2009: ENSO and extreme rainfall events in South America. J. Climate, 22, 15891609, doi:10.1175/2008JCLI2429.1.

    • Search Google Scholar
    • Export Citation
  • Grimm, A. M., and J. P. J. Saboia, 2015: Interdecadal variability of the South American precipitation in the monsoon season. J. Climate, 28, 755775, doi:10.1175/JCLI-D-14-00046.1.

    • Search Google Scholar
    • Export Citation
  • Grimm, A. M., N. C. Laureanti, R. B. Rodakoviski, and C. B. Gama, 2016: Interdecadal variability and extreme precipitation events in South America during the monsoon season. Climate Res., 68, 277294, doi:10.3354/cr01375.

    • Search Google Scholar
    • Export Citation
  • Gu, G., R. F. Adler, G. J. Huffman, and S. Curtis, 2007: Tropical rainfall variability on interannual-to-interdecadal and longer time scales derived from the GPCP monthly product. J. Climate, 20, 40334046, doi:10.1175/JCLI4227.1.

    • Search Google Scholar
    • Export Citation
  • Gustafsson, M., D. Rayner, and D. Chen, 2010: Extreme rainfall events in southern Sweden: Where does the moisture come from? Tellus, 62A, 605616, doi:10.1111/j.1600-0870.2010.00456.x.

    • Search Google Scholar
    • Export Citation
  • Held, I. M., and B. J. Soden, 2006: Robust responses of the hydrological cycle to global warming. J. Climate, 19, 56865699, doi:10.1175/JCLI3990.1.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., and D. T. Bolvin, 2015: Real-time TRMM Multi-satellite Precipitation Analysis data set documentation. NASA Tech. Doc., 48 pp. [Available online at ftp://trmmopen.gsfc.nasa.gov/pub/merged/V7Documents/3B4XRT_doc_V7.pdf.]

  • Huffman, G. J., R. F. Adler, M. Morrissey, D. Bolvin, S. Curtis, R. Joyce, B. McGavock, and J. Susskind, 2001: Global precipitation at one-degree daily resolution from multisatellite observations. J. Hydrometeor., 2, 3650, doi:10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2.

    • 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, 3855, doi:10.1175/JHM560.1.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., R. F. Adler, D. T. Bolvin, and G. Gu, 2009: Improving the global precipitation record: GPCP Version 2.1. Geophys. Res. Lett., 36, L17808, doi:10.1029/2009GL040000.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., R. F. Adler, D. T. Bolvin, and E. J. Nelkin, 2010: The TRMM Multi-Satellite Precipitation Analysis (TMPA). Satellite Rainfall Applications for Surface Hydrology, F. Hossain and M. Gebremichael, Eds., Springer Verlag, 3–22.

  • IPCC, 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.

  • Karl, T. R., N. Nicholls, and A. Ghazi, 1999: CLIVAR/GCOS/WMO workshop on indices and indicators for climate extremes: Workshop summary. Climatic Change, 42, 37, doi:10.1023/A:1005491526870.

    • Search Google Scholar
    • Export Citation
  • Kharin, V., F. W. Zwiers, X. Zhang, and G. C. Hergerl, 2007: Changes in temperature and precipitation extremes in IPCC ensemble of coupled model simulations. J. Climate, 20, 14191444, doi:10.1175/JCLI4066.1.

    • Search Google Scholar
    • Export Citation
  • Kirschbaum, D., R. Adler, D. Adler, C. Peters-Lidard, and G. Huffman, 2012: Global distribution of extreme precipitation and high-impact landslides in 2010 relative to previous years. J. Hydrometeor., 13, 15361551, doi:10.1175/JHM-D-12-02.1.

    • Search Google Scholar
    • Export Citation
  • Lau, K.-M., and H.-T. Wu, 2011: Climatology and changes in tropical oceanic rainfall characteristics inferred from Tropical Rainfall Measuring Mission (TRMM) data (1998–2009). J. Geophys. Res., 116, D17111, doi:10.1029/2011JD015827.

    • Search Google Scholar
    • Export Citation
  • Lau, K.-M., H.-T. Wu, and K.-M. Kim, 2013: A canonical response of precipitation characteristics to global warming from CMIP5 models. Geophys. Res. Lett., 40, 31633169, doi:10.1002/grl.50420.

    • Search Google Scholar
    • Export Citation
  • Liu, C., and R. P. Allan, 2012: Multisatellite observed responses of precipitation and its extremes to interannual climate variability. J. Geophys. Res., 117, D03101, doi:10.1029/2011JD016568.

    • Search Google Scholar
    • Export Citation
  • Min, S.-K., X. Zhang, F. W. Zwiers, and G. C. Hegerl, 2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378381, doi:10.1038/nature09763.

    • Search Google Scholar
    • Export Citation
  • O’Gorman, P. A., 2012: Sensitivity of tropical precipitation extremes to climate change. Nat. Geosci., 5, 697700, doi:10.1038/ngeo1568.

    • Search Google Scholar
    • Export Citation
  • Peterson, T. C., C. Folland, G. Gruza, W. Hogg, A. Mokssit, and N. Plummer, 2001: Report on the activities of the Working Group on Climate Change Detection and related rapporteurs 1998–2001. WMO/TD-1071, 143 pp.

  • Sapiano, M. R. P., and P. A. Arkin, 2009: An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data. J. Hydrometeor., 10, 149166, doi:10.1175/2008JHM1052.1.

    • Search Google Scholar
    • Export Citation
  • Scheel, M. L. M., M. Rohrer, C. Huggel, D. S. Villar, E. Silvestre, and G. J. Huffman, 2011: 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., 15, 26492663, doi:10.5194/hess-15-2649-2011.

    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, A. Meyer-Christoffer, M. Ziese, and B. Rudolf, 2011: Global precipitation analysis products of the GPCC. Global Precipitation Climatology Centre (GPCC) Rep., 13 pp. [Available online at ftp://ftp.dwd.de/pub/data/gpcc/PDF/GPCC_intro_products_v2011.pdf.]

  • Shiu, C.-J., S. C. Liu, C. Fu, A. Dai, and Y. Sun, 2012: How much do precipitation extremes change in a warming climate? Geophys. Res. Lett., 39, L17707, doi:10.1029/2012GL052762.

    • Search Google Scholar
    • Export Citation
  • Su, F., Y. Hong, and D. P. Lettenmaier, 2008: Evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) and its utility in hydrologic prediction in the La Plata basin. J. Hydrometeor., 9, 622640, doi:10.1175/2007JHM944.1.

    • Search Google Scholar
    • Export Citation
  • Tian, Y., and Coauthors, 2009: Component analysis of errors in satellite-based precipitation estimates. J. Geophys. Res., 114, D24101, doi:10.1029/2009JD011949.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 12051217, doi:10.1175/BAMS-84-9-1205.

    • Search Google Scholar
    • Export Citation
  • Wang, J.-J., R. F. Adler, G. J. Huffman, and D. Bolvin, 2014: An updated TRMM composite climatology of tropical rainfall and its validation. J. Climate, 27, 273284, doi:10.1175/JCLI-D-13-00331.1.

    • Search Google Scholar
    • Export Citation
  • Wu, H., R. F. Adler, Y. Hong, Y. Tian, and F. Policelli, 2012: Evaluation of global flood detection using satellite-based rainfall and a hydrologic model. J. Hydrometeor., 13, 12681284, doi:10.1175/JHM-D-11-087.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1009 734 45
PDF Downloads 226 48 8