Using temporal changes in drought indices to generate probabilistic drought intensification forecasts

Jason A. Otkin, Martha C. Anderson, Christopher Hain, Mark Svoboda

Research output: Contribution to journalArticlepeer-review

52 Scopus citations

Abstract

In this study, the potential utility of using rapid temporal changes in drought indices to provide early warning of an elevated risk for drought development over subseasonal time scales is assessed. Standardized change anomalies were computed each week during the 2000-13 growing seasons for drought indices depicting anomalies in evapotranspiration, precipitation, and soil moisture. A rapid change index (RCI) that encapsulates the accumulated magnitude of rapid changes in the weekly anomalies was computed each week for each drought index, and then a simple statistical method was used to convert the RCI values into drought intensification probabilities depicting the likelihood that drought severity as analyzed by theU.S. Drought Monitor (USDM) wouldworsen in subsequent weeks. Local and regional case study analyses revealed that elevated drought intensification probabilities often occur several weeks prior to changes in the USDM and in topsoil moisture and crop condition datasets compiled by the NationalAgricultural Statistics Service. Statistical analyses showed that theRCI-derived probabilities are most reliable and skillful over the central and eastern United States in regionsmost susceptible to rapid drought development. Taken together, these results suggest that tools used to identify areas experiencing rapid changes in drought indices may be useful components of future drought early warning systems.

Original languageEnglish (US)
Pages (from-to)88-105
Number of pages18
JournalJournal of Hydrometeorology
Volume16
Issue number1
DOIs
StatePublished - 2015
Externally publishedYes

Keywords

  • Agriculture
  • Drought
  • Land surface model
  • Probability forecasts/models/distribution

ASJC Scopus subject areas

  • Atmospheric Science

Fingerprint

Dive into the research topics of 'Using temporal changes in drought indices to generate probabilistic drought intensification forecasts'. Together they form a unique fingerprint.

Cite this