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). These included remote effects of tropical sea surface temperatures, land use practices, and the potential feedbacks that abundant soil-related aerosols may have exerted on rainfall. An important role for random atmospheric internal variability has also been proposed ( Hoerling et al. 2009 ). However, since the 1930s, summer rainfall has shown less severe declines in the 1950s and 1970s, while the last two decades were noted mostly by abundant summer rainfall (e.g., Wang et al. 2009 ). Looking at
). These included remote effects of tropical sea surface temperatures, land use practices, and the potential feedbacks that abundant soil-related aerosols may have exerted on rainfall. An important role for random atmospheric internal variability has also been proposed ( Hoerling et al. 2009 ). However, since the 1930s, summer rainfall has shown less severe declines in the 1950s and 1970s, while the last two decades were noted mostly by abundant summer rainfall (e.g., Wang et al. 2009 ). Looking at
enhance the SST-forced anomalies. However, in the case of 2010/11, the combination of La Niña conditions and internal atmospheric variability led to a drought that was severe, much worse in terms of dryness and heat than that forecast ahead of time and at the very edge of the observed historical variability of climate. Acknowledgments This work was supported by NOAA Awards NA08OAR4320912 and NA10OAR4310137 (Global Decadal Hydroclimate Variability and Change) and NSF Award AGS-0804107. The authors
enhance the SST-forced anomalies. However, in the case of 2010/11, the combination of La Niña conditions and internal atmospheric variability led to a drought that was severe, much worse in terms of dryness and heat than that forecast ahead of time and at the very edge of the observed historical variability of climate. Acknowledgments This work was supported by NOAA Awards NA08OAR4320912 and NA10OAR4310137 (Global Decadal Hydroclimate Variability and Change) and NSF Award AGS-0804107. The authors
existed some large-scale factors that might enhance the probability of such an extreme event, they conducted climate model simulations that revealed a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade. This shift, most likely due to natural decadal variability, is such that the probability for a severe summer Great Plains drought may have increased fivefold in the last decade compared to the 1980s and 1990s. Wang et al. (2014) compared the roles played
existed some large-scale factors that might enhance the probability of such an extreme event, they conducted climate model simulations that revealed a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade. This shift, most likely due to natural decadal variability, is such that the probability for a severe summer Great Plains drought may have increased fivefold in the last decade compared to the 1980s and 1990s. Wang et al. (2014) compared the roles played
1. Introduction Throughout its history, the United States has experienced numerous droughts and heat waves, and these have caused extensive human suffering and enormous economic loss. The last few decades have seen significant advances in our understanding of large-scale controls on these droughts. In particular, it is now well known that certain spatial patterns of sea surface temperature (SST) are conducive to generating precipitation deficits or meteorological droughts over much of the
1. Introduction Throughout its history, the United States has experienced numerous droughts and heat waves, and these have caused extensive human suffering and enormous economic loss. The last few decades have seen significant advances in our understanding of large-scale controls on these droughts. In particular, it is now well known that certain spatial patterns of sea surface temperature (SST) are conducive to generating precipitation deficits or meteorological droughts over much of the
precipitation, results from L. Li et al. (2011) and W. Li et al. (2011) show that the North Atlantic subtropical high (NASH) has affected precipitation variation in the southeast, and that summer precipitation variability has been enhanced in the past few decades due in part to the NASH. The Atlantic multidecadal oscillation (AMO) may also affect summertime precipitation, leading to increased summer rainfall during warm phases of the AMO ( Hu et al. 2011 ). There is also evidence that tropical storms
precipitation, results from L. Li et al. (2011) and W. Li et al. (2011) show that the North Atlantic subtropical high (NASH) has affected precipitation variation in the southeast, and that summer precipitation variability has been enhanced in the past few decades due in part to the NASH. The Atlantic multidecadal oscillation (AMO) may also affect summertime precipitation, leading to increased summer rainfall during warm phases of the AMO ( Hu et al. 2011 ). There is also evidence that tropical storms
1. Introduction Drought is a natural phenomenon due to climate variability. However, with global warming and population growth, the resilience to drought is likely to decrease in the future. Unlike other meteorological hazards such as floods, tornados, and hurricanes, drought is a creeping phenomenon that can build up without warning and persist for many months ( Sheffield and Wood 2011 ). Once the water deficit of the climate system reaches a certain threshold, drought will affect agriculture
1. Introduction Drought is a natural phenomenon due to climate variability. However, with global warming and population growth, the resilience to drought is likely to decrease in the future. Unlike other meteorological hazards such as floods, tornados, and hurricanes, drought is a creeping phenomenon that can build up without warning and persist for many months ( Sheffield and Wood 2011 ). Once the water deficit of the climate system reaches a certain threshold, drought will affect agriculture
strong moisture variability over the past decade. Both points exhibit drought impacts in 2006 and 2011, while the Texas drought of 2009 did not extend into the central plains. In 2000, the ESI captures impacts of a flash drought that occurred over Oklahoma and is missed by the SM indices in the sampled area. This event is further explored in section 4d . Time traces from two points in Iowa (IA-N and IA-S, also sampled in Fig. 3 ) demonstrate variable ESI performance over the Corn Belt. At both
strong moisture variability over the past decade. Both points exhibit drought impacts in 2006 and 2011, while the Texas drought of 2009 did not extend into the central plains. In 2000, the ESI captures impacts of a flash drought that occurred over Oklahoma and is missed by the SM indices in the sampled area. This event is further explored in section 4d . Time traces from two points in Iowa (IA-N and IA-S, also sampled in Fig. 3 ) demonstrate variable ESI performance over the Corn Belt. At both
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
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
transported out of the grid cell is further routed through the river network to generate estimates of streamflow, using the distributed approach of Lohmann et al. (1998) . Satellite retrievals Microwave remote sensing measurements have a long legacy of providing estimates of near-surface soil moisture from a number of sensors ( Jackson 1993 ; Njoku and Entekhabi 1996 ) for several decades. They include the SMMR (1978–87); the SSM/I (since 1987); the Tropical Rainfall Measuring Mission (TRMM) Microwave
transported out of the grid cell is further routed through the river network to generate estimates of streamflow, using the distributed approach of Lohmann et al. (1998) . Satellite retrievals Microwave remote sensing measurements have a long legacy of providing estimates of near-surface soil moisture from a number of sensors ( Jackson 1993 ; Njoku and Entekhabi 1996 ) for several decades. They include the SMMR (1978–87); the SSM/I (since 1987); the Tropical Rainfall Measuring Mission (TRMM) Microwave
