Global Extreme Drought / Flood Monitoring
Introduction and Methodology
The impacts of drought are associated with the costs and losses in areas of economic, social, or environmental areas directly or indirectly. Drought monitoring is essential to develop a good prediction system, mitigate losses caused by drought and to set up preparedness strategies. The APCC Global Drought Monitoring is based on the Standardized Precipitation Index (SPI; McKee et al. 1993) maps for the last 1-month, 3-month, 6-month and 12-month periods using monthly precipitation at 2.5°x2.5° resolution. SPI between -1.0 to -1.49 indicates moderate drought, -1.5 to -2.0 severe drought, and less than -2.0 extreme drought conditions. The SPI is estimated by transforming the observed rainfall distribution for the recent 30 yrs, usually fitted to a Gamma distribution, into a standardized normal distribution on an equal probability basis (see Sohn et al. 2012a, 2012b for more details).
In retrospect: Global drought/flood condition on serveral times scales
The Climate Anomaly Monitoring System (CAMS) and Outgoing Longwave Radiation (OLR) Precipitation Index (OPI) (CAMS OPI) (Janowiak and Xie 1999) is used for SPI computation. The CAMS OPI is precipitation analyses which merge observations from rain gauges with estimates from satellite algorithm to produce real-time monthly global precipitation.
The datasets are available at CAMS_OPI . Currently, the Colorado Climate Center, the Western Regional Climate Center (WRCC), the National Drought Mitigation Center (NCDC), and Beijing Climate Center (BCC) use the SPI to monitor ongoing drought conditions in the United States and China, respectively.
Note: The global drought assessment provided in this bulletin is subject to the limitations of the aforementioned data issue, data resolution, and also those arising from the methodology. It is advised that for detailed regional drought monitoring, relevant products issued by the national weather and climate centers may be referred; this product is intended to identify the very large scale anomalous rainfall deficit/surplus patterns around the globe.
Janowiak, J. E. and P. Xie, 1999: CAMS_OPI: a global satellite-raingauge merged product for real-time precipitation monitoring applications. J. Climate, 12, 3335-3342.
Mckee, T. B., N. J. Doesken, and J. Kleist, 1993: The relationship of drought frequency and duration to time scales. In Proceeding of 8th Conference on Applied Climatology, 17-22 January 1993, Anaheim, California, 179-184.
Sohn, S.-J., C.-Y. Tam, K. Ashok, and J.-B. Ahn, 2012a: Quantifying the reliability of precipitation datasets for monitoring large-scale East Asian precipitation variations. Int. J. Clim., DOI: 10.1002/joc.2380.
Sohn, S.-J., C.-Y. Tam, and J.-B. Ahn, 2012b: Development of a multimodel-based seasonal prediction system for extreme droughts and floods: a case study for South Korea. Int. J. Clim., DOI: 10.1002/joc.3464.