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Soil moisture feedbacks that initiate, enhance, or suppress convection initiation and precipitation are important components of regional hydroclimatology. However, soil moisture feedbacks and the processes through which they operate are notoriously challenging to observe and study outside of model environments. In this study, we combine a climatological assessment of event frequency-based measurements of soil moisture-precipitation coupling in the central United States with a process-based analysis of the mechanisms by which wet- and dry-soil feedbacks may operate in the region. We use the Thunderstorm Observation by Radar algorithm to identify the location of convection initiation, circumventing the issue of using precipitation accumulation as a proxy for convection initiation. Results show substantial spatial variability in the climatological sign and strength of soil moisture-precipitation coupling in the central United States, including regions that exhibit signs of both wet- and dry-soil feedbacks. Within the regions with the strongest feedback signals, we find consistently strong coupling between soil moisture and the partitioning of surface heat flux, and strong coupling between surface heat flux—particularly sensible heat flux—and diurnal change in planetary boundary layer height. In all three regions assessed, the process-based metrics confirmed the potential of wet- and/or dry-soil feedbacks leading to convection initiation 

Abstract Pluvial floods generated by tropical cyclones (TCs) are one of the major concerns for coastal communities. Choosing Houston as an example, we demonstrate that there will be significantly elevated risk of TC rainfall and flood in the future warming world by coupling downscaled TCs from Model Intercomparison Project Phase 6 models with physical hydrological models. We find that slower TC translation speed, more frequent stalling, greater TC frequency, and increased rain rate are major contributors to increased TC rainfall risk and flood risk. The TC flood risk increases more than the rainfall. Smaller watersheds with a high degree of urbanization are particularly vulnerable to future changes in TC floods in a warming world. 

Abstract Predicting future streamflow change is essential for water resources management and understanding the impacts of projected climate and land use changes on water availability. The Budyko framework is a useful and computationally efficient tool to model streamflow at larger spatial scales. This study predicts future streamflow changes in 889 watersheds in the contiguous United States based on projected climate and land use changes from 2040 to 2069. The temporal variability of surface water balance controls, represented by the Budykoωparameter, was modeled using multiple linear regression, random forest (RF), and gradient boosting. Results show that RF is the optimal model and can explain >85% of the variance in most watersheds. Relative cumulative moisture surplus, forest coverage, crop land and urban land are the most important variables of the time‐varyingωin most watersheds. There are statistically significant increases in mean annual precipitation, potential evapotranspiration, andωin 2040–2069, as compared to 1950–2005. This leads to a statistically significant decrease in the runoff ratio (Q/P). Streamflow is projected to decrease in the central, southwestern, and southeastern United States and increase in the northeast. These projections of water availability which are based on future climate and land use change scenarios can inform water resources management and adaptation strategies. 

Abstract Soil moisture feedbacks that initiate, enhance, or suppress convection initiation and precipitation are important components of regional hydroclimatology. However, soil moisture feedbacks and the processes through which they operate are notoriously challenging to observe and study outside of model environments. In this study, we combine a climatological assessment of event frequency‐based measurements of soil moisture‐precipitation coupling in the central United States with a process‐based analysis of the mechanisms by which wet‐ and dry‐soil feedbacks may operate in the region. We use the Thunderstorm Observation by Radar algorithm to identify the location of convection initiation, circumventing the issue of using precipitation accumulation as a proxy for convection initiation. Results show substantial spatial variability in the climatological sign and strength of soil moisture‐precipitation coupling in the central United States, including regions that exhibit signs of both wet‐ and dry‐soil feedbacks. Within the regions with the strongest feedback signals, we find consistently strong coupling between soil moisture and the partitioning of surface heat flux, and strong coupling between surface heat flux—particularly sensible heat flux—and diurnal change in planetary boundary layer height. In all three regions assessed, the process‐based metrics confirmed the potential of wet‐ and/or dry‐soil feedbacks leading to convection initiation. 

Abstract Understanding the dominant drivers of hydrological change is essential for water resources management. Watersheds in the United States are experiencing different types of changes (e.g., wet gets wetter and dry gets drier); however, few studies have analyzed what drivers are responsible for these changes, and how the dominant drivers vary over time and as a function of the climate/water regime and land cover. This study uses a time‐varying Budyko framework to quantify the relative importance of precipitation, potential evapotranspiration, and other factors (e.g., climate seasonality, agricultural drainage, and urbanization) in 889 watersheds in the contiguous United States from 1950 to 2009. Results show that watersheds that are getting wetter are primarily due to increases in precipitation. However, watersheds in dry climates that are getting drier are primarily due to other factors, while watersheds in wet climates that are getting drier are primarily due to precipitation. The drivers causing statistically significant streamflow trends vary depending on dominant land‐use types. Temporally, the increasing effects of other factors are more pronounced after the 1980s in the Midwest. The dominant drivers of streamflow in the United States are time‐varying instead of constant. This is consistent with non‐stationary patterns of streamflow. The time‐varying drivers provide information on the processes that are increasingly important and require the most attention in water resources management.