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The Modified Palmer Drought Severity Index Based on the NCEP North American Regional Reanalysis
Author(s) -
Kingtse C. Mo,
Muthuvel Chelliah
Publication year - 2006
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/jam2402.1
Subject(s) - environmental science , precipitation , evapotranspiration , water content , potential evaporation , surface runoff , snowmelt , climatology , moisture , snow , hydrology (agriculture) , atmospheric sciences , meteorology , geology , geography , ecology , geotechnical engineering , biology
A 32-km high-resolution modified Palmer drought severity index (MPDSI) based on the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (RR) from 1979 to 2004 is presented. The assumptions of Palmer, such as the water balance equation, the difference between observed precipitation and the climatologically expected precipitation over the maximum conditions, and the changes of the index as a function of the current index, are preserved. Many deficiencies of the original PDSI are eliminated by taking fields directly from the RR or by making better estimates. For example, fields such as potential evapotranspiration, evaporation, runoff, total soil moisture, and soil moisture change in a given month are obtained directly from the RR. The potential recharge is defined as the total soil moisture needed to reach the maximum total soil moisture at each grid point for each calendar month. The potential precipitation is defined as the maximum precipitation at each grid point for a given calendar month. The underground volumetric soil moisture includes both frozen and liquid form. Therefore, the contribution of snowmelt is taken into account inexplicitly. The questionable assumptions of two-layer soil model and the available soil moisture capacity are no longer needed. Overall, the MPDSI, when averaged over a large area and long time, often resembles the traditional PDSI based on the Palmer formula and the climate-division data. The MPDSI obeys Gaussian distribution, and so it can also be used to assess the potential for floods. Together with a consistent suite of soil moisture, surface energy, and atmospheric terms from the RR, the MPDSI can be used to monitor and diagnose drought and floods.

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