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JDI-Precipitation-Viewer
Helps visualize the Joint Deficit Index (JDI) of Precipitation
Launch Tool
Archive Version 1.4z
Published on 13 Jan 2014, unpublished on 13 Jan 2014 All versions
This tool is closed source.
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Abstract
Droughts are prolonged abnormalities of moisture deficits that vary widely across temporal and spatial scales. Many hydrometeorologic variables are used to monitor the status of a drought. However, because of the dependence structure between all affecting variables under various temporal windows, an integrated spatio-temporal analysis of droughts cannot be easily achieved. A copula-based drought analysis was performed by Kao et al. using long-term monthly precipitation dataset for the upper Midwest United States. The spatio-temporal dependence relationships between various drought variables were investigated, and their joint probability distribution was constructed by combining drought marginals and the dependence structure. A copula-based joint deficit index (JDI) was adopted for an objective (probability-based) description of the overall drought status and compared to the Palmer drought severity index results. Results from the copula-based JDI provide information for drought identification, and further allow a month-by-month assessment for future drought recovery.
Credits
Shih-Chieh Kao
References
Kao, S.-C., R.S. Govindaraju, and D. Niyogi (2009). "A spatio-temporal
drought analysis for the Midwestern US." In World Environmental and
Water Resources Congress 2009: Great Rivers, Kansas, May 17-21, pg.
4654-4663.
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