Evaluating Detection Skills of Satellite Rainfall Estimates over Desert Locust Recession Regions

Tufa Dinku International Research Institute for Climate and Society, The Earth Institute at Columbia University, Palisades, New York

Search for other papers by Tufa Dinku in
Current site
Google Scholar
PubMed
Close
,
Pietro Ceccato International Research Institute for Climate and Society, The Earth Institute at Columbia University, Palisades, New York

Search for other papers by Pietro Ceccato in
Current site
Google Scholar
PubMed
Close
,
Keith Cressman Desert Locust Information Service, United Nations Food and Agriculture Organization, Rome, Italy

Search for other papers by Keith Cressman in
Current site
Google Scholar
PubMed
Close
, and
Stephen J. Connor International Research Institute for Climate and Society, The Earth Institute at Columbia University, Palisades, New York

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

Abstract

This paper evaluates rainfall detection capabilities of seven satellite rainfall estimates over the desert locust recession regions of the world. The region of interest covers the arid and semiarid region from northwestern Africa to northwestern India. The evaluated satellite rainfall products are the African rainfall climatology (ARC), rainfall estimation algorithm (RFE), Tropical Rainfall Measuring Mission 3B42 and its real-time version (3B42RT), NOAA/Climate Prediction Center morphing technique (CMORPH), and two versions of the Global Satellite Mapping of Precipitation moving vector with Kalman filter (GSMaP-MVK and GSMaP-MVK+). The reference data were obtained from the Desert Locust Information Service of the United Nations Food and Agriculture Organization (FAO). The FAO data are qualitative information collated by desert locust survey teams from different countries during field campaigns. Such data can only be used to assess the rainfall detection capabilities of the satellite products. The validation region is divided into four subregions and validations statistics are computed for each region. The probability of detection varies from 70% for the relatively wet part of the validation region to less than 20% for the driest part. The main weakness of the satellite products is overestimation of rainfall occurrences. The false-alarm ratio was as high as 84% for the driest part and as high as 57% for the wetter region. The satellite products still exhibit positive detection skill for all of the subregions. A comparison of the different products shows that no single product stands out as having the best or the worst overall performance.

Corresponding author address: Tufa Dinku, IRI, The Earth Institute at Columbia University, 61 Route 9W, Monell Bldg., Palisades, NY 10964. Email: tufa@iri.columbia.edu

This article included in the International Precipitation Working Group (IPWG) special collection.

Abstract

This paper evaluates rainfall detection capabilities of seven satellite rainfall estimates over the desert locust recession regions of the world. The region of interest covers the arid and semiarid region from northwestern Africa to northwestern India. The evaluated satellite rainfall products are the African rainfall climatology (ARC), rainfall estimation algorithm (RFE), Tropical Rainfall Measuring Mission 3B42 and its real-time version (3B42RT), NOAA/Climate Prediction Center morphing technique (CMORPH), and two versions of the Global Satellite Mapping of Precipitation moving vector with Kalman filter (GSMaP-MVK and GSMaP-MVK+). The reference data were obtained from the Desert Locust Information Service of the United Nations Food and Agriculture Organization (FAO). The FAO data are qualitative information collated by desert locust survey teams from different countries during field campaigns. Such data can only be used to assess the rainfall detection capabilities of the satellite products. The validation region is divided into four subregions and validations statistics are computed for each region. The probability of detection varies from 70% for the relatively wet part of the validation region to less than 20% for the driest part. The main weakness of the satellite products is overestimation of rainfall occurrences. The false-alarm ratio was as high as 84% for the driest part and as high as 57% for the wetter region. The satellite products still exhibit positive detection skill for all of the subregions. A comparison of the different products shows that no single product stands out as having the best or the worst overall performance.

Corresponding author address: Tufa Dinku, IRI, The Earth Institute at Columbia University, 61 Route 9W, Monell Bldg., Palisades, NY 10964. Email: tufa@iri.columbia.edu

This article included in the International Precipitation Working Group (IPWG) special collection.

Save
  • Ceccato, P., K. Cressman, A. Giannini, and S. Trzaska, 2007: The desert locust upsurge in West Africa (2003–2005): Information on The Desert Locust Early Warning System, and the prospects for seasonal climate forecasting. Int. J. Pest Manage., 53 (1) 713.

    • Search Google Scholar
    • Export Citation
  • Dinku, T., P. Ceccato, E. Grover-Kopec, M. Lemma, S. H. Connor, and C. F. Ropelewski, 2007: Validation of satellite rainfall products over East Africa’s complex topography. Int. J. Remote Sens., 28 , 15031526.

    • Search Google Scholar
    • Export Citation
  • FAO, 2007: Preparedness to Prevent Desert Locust Plagues in the Central Region: An Historical Review. FAO Desert Locust Technical Series, AGP/DL/TS/35, Food and Agriculture Organization, 129 pp.

    • Search Google Scholar
    • Export Citation
  • Herman, A., V. B. Kumar, P. A. Arkin, and J. V. Kousky, 1997: Objectively determined 10-day African rainfall estimates created for famine early warning. Int. J. Remote Sens., 18 , 21472159.

    • Search Google Scholar
    • Export Citation
  • Hielkema, J. U., and F. L. Sunders, 1994: Operational use of environmental satellite remote sensing and satellite communications technology for global food security and locust control by FAO: The ARTEMIS and DIANA system. Acta Astronaut., 32 , 603616.

    • 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.

    • 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 , 487503.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437471.

  • Love, T. B., V. Kumar, P. Xie, and W. Thiaw, 2004: A 20-year daily Africa precipitation climatology using satellite and gauge data. Preprints, 14th Conf. on Applied Climatology, Seattle, WA, Amer. Meteor. Soc., P5.4. [Available online at http://ams.confex.com/ams/pdfpapers/67484.pdf].

    • Search Google Scholar
    • Export Citation
  • Mahowald, N. M., and L. M. Kiehl, 2003: Mineral aerosol and cloud interactions. Geophys. Res. Lett., 30 , 1475. doi:10.1029/2002GL016762.

    • Search Google Scholar
    • Export Citation
  • McCollum, J. R., A. Gruber, and M. B. Ba, 2000: Discrepancy between gauges and satellite estimates of rainfall in equatorial Africa. J. Appl. Meteor., 39 , 666679.

    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., 2000: The nature of rainfall variability over Africa on time scales of decades to millennia. Global Planet. Change, 26 , 137158.

    • Search Google Scholar
    • Export Citation
  • Okamoto, K., T. Iguchi, N. Takahashi, T. Ushio, J. Awaka, S. Shige, and T. Kubota, 2007: High precision and high resolution global precipitation map from satellite data. Proc. Int. Symp. on Antennas and Propagation (ISAP), Niigata, Japan, 506–509.

    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., 2000: Suppression of rain and snow by urban and industrial air pollution. Science, 287 , 17931796.

  • Rosenfeld, D., 2006: Aerosols, clouds, and climate. Science, 312 , 13231324.

  • Rosenfeld, D., and Y. Mintz, 1988: Evaporation of rain falling from convective clouds as derived from radar measurements. J. Appl. Meteor., 27 , 209215.

    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., Y. Rudich, and R. Lahav, 2001: Desert dust suppressing precipitation: A possible desertification feedback loop. Proc. Natl. Acad. Sci. USA, 98 , 59755980.

    • Search Google Scholar
    • Export Citation
  • Schneider, U., T. Fuchs, A. Meyer-Christoffer, and B. Rudolf, cited. 2008: Global precipitation analysis products of the GPCC. [Available online at http://gpcc.dwd.de].

    • Search Google Scholar
    • Export Citation
  • Seto, S., T. Kubota, T. Iguchi, N. Takahashi, and T. Oki, 2009: An evaluation of over-land rain rate estimates by the GSMaP and GPROF algorithms: The role of lower-frequency channels. J. Meteor. Soc. Japan, 87A , 183202.

    • Search Google Scholar
    • Export Citation
  • Takemi, T., 1999: Evaporation of rain falling below a cloud base through a deep atmospheric layer over an arid region. J. Meteor. Soc. Japan, 77 , 387397.

    • Search Google Scholar
    • Export Citation
  • van Huis, A., K. Cressman, and J. I. Magor, 2007: Preventing desert locust plagues: Optimizing management interventions. Entomol. Exp. Appl., 122 , 191214.

    • Search Google Scholar
    • Export Citation
  • Wang, N-Y., R. Ferraro, C. Liu, D. Wolff, E. Zipser, and C. Kummerow, 2009: The TRMM 2A12 land precipitation product − status and future plans. J. Meteor. Soc. Japan, 87A , 237253.

    • Search Google Scholar
    • Export Citation
  • Xie, P., Y. Yarosh, T. Love, J. Janowiak, and P. A. Arkin, 2002: A real-time daily precipitation analysis over South Asia. Preprints, 16th Conf. on Hydrology, Orlando, FL, Amer. Meteor. Soc., 3.15. [Available online at http://ams.confex.com/ams/pdfpapers/27889.pdf].

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 821 392 18
PDF Downloads 436 100 10