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John M. Peters, Christopher J. Nowotarski, and Gretchen L. Mullendore

. (d) The CIR MEDSHR LOWCAPE run at 65 min. (e) The STR HISHR LOWCAPE run at 180 min. (f) The CIR HISHR LOWCAPE run at 180 min. Arrows denote the location of the analyzed storm. Fig . 4. As in Fig. 3 , but for the HICAPE runs. (a) The STR LOWSHR HICAPE run at 65 min. (b) The CIR LOWSHR HICAPE run at 65 min. (c) The STR MEDSHR HICAPE run at 180 min. (d) The CIR MEDSHR HICAPE run at 65 min. (e) The STR HISHR HICAPE run at 180 min. (f) The CIR HISHR HICAPE run at 180 min. Fig . 5. (a),(b) Plan views

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Shahrbanou Madadgar and Hamid Moradkhani

1. Introduction Accurate forecasting of hydrologic extreme events plays a significant role in developing appropriate policies to plan for available water resources. Although several studies have proposed promising methods to improve hydrologic forecasts, the observed effects of climate change on floods and droughts across different regions of the globe in recent decades highlights the need for more sophisticated methods in predicting extreme events ( Mishra and Singh 2010 ; Moradkhani et al

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Eric F. Wood, Siegfried D. Schubert, Andrew W. Wood, Christa D. Peters-Lidard, Kingtse C. Mo, Annarita Mariotti, and Roger S. Pulwarty

1. Introduction The National Integrated Drought Information System’s (NIDIS) Implementation Plan states that “[d]rought is among the most damaging and least understood of all natural hazards” ( NISDIS 2007 , p. ii; ). It is well understood among climatologists that drought is a naturally occurring phenomenon. Its slow onset; often long-duration, cumulative impacts; and widespread extent results in droughts being the costliest of natural disasters ( NCDC 2012 ; Below

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Richard Seager, Lisa Goddard, Jennifer Nakamura, Naomi Henderson, and Dong Eun Lee

them and any atmospheric response to prior land surface conditions. A comprehensive analysis and understanding of the 2010/11 TexMex drought, and its predictability, will inform decision making and disaster planning by allowing assessment of its likelihood, advance warning signs, and ability to predict ahead of time, or lack thereof. 2. Observational and model data The observed precipitation data are from the National Oceanic and Atmospheric Administration (NOAA)–National Centers for Environmental

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