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Skillful subseasonal prediction of extreme heat and precipitation greatly benefits multiple sectors, including water management, public health, and agriculture, in mitigating the impact of extreme events. A statistical model is developed to predict the weekly frequency of extreme warm days and 14-day standardized precipitation index (SPI) during boreal summer in the United States. We use a leading principal component of U.S. soil moisture and an index based on the North Pacific sea surface temperature (SST) as predictors. The model outperforms the NCEP Climate Forecast System, version 2 (CFSv2), at weeks 3–4 in the eastern United States. It is found that the North Pacific SST anomalies persist for several weeks and are associated with a persistent wave train pattern, which leads to increased occurrences of blocking and extreme temperature over the eastern United States. Extreme dry soil moisture conditions persist into week 4 and are associated with an increase in sensible heat flux and a decrease in latent heat flux, which may help to maintain the overlying anticyclone. The clear-sky conditions associated with blocking anticyclones further decrease soil moisture and increase the frequency of extreme warm days. This skillful statistical model has the potential to aid in irrigation scheduling, crop planning, and reservoir operation and to provide mitigation of impacts from extreme heat events. [ABSTRACT FROM AUTHOR]

A hybrid dynamical–statistical model is pursued for prediction of Atlantic seasonal hurricane activity driven by output of the North American Multimodel Ensemble (NMME). This is an updated version of a proven multiple linear regression method conditioned on forecast vertical wind shear from the Climate Forecast System and observed sea surface temperatures (SSTs). The method pursued for prediction utilizes August–October (ASO) Main Development Region (MDR; 10–20°N, 20–80°W) vertical wind shear and observed North Atlantic (NATL; 55–65°N, 30–60°W) SST averaged over the 3 months preceding the forecast in conjunction with the full hurricane climatology. NMME forecasts improve upon representations relative to individual members. The NMME multi-model mean better reproduces vertical wind shear distributions over the MDR and captures the observed relationships between SST and vertical wind shear with hurricane trend and interannual variability despite occasionally poor reproductions by individual members. Cross-validation reveals the multi-model average of the hybrid model outputs from the individual NMME members yields forecast errors 10–30% less than the individual members, while correlations with observed hurricane-related activity typically improve. The NMME methodology is shown to be competitive with official outlooks from Colorado State University and the National Oceanic and Atmospheric Administration over recent years. [ABSTRACT FROM AUTHOR]

Two 1-km Weather Research and Forecasting model simulations of the rapid intensification (RI) periods of hurricanes Ike (2008) and Earl (2010), under low and high wind shear respectively, are performed to evaluate mechanisms linked to the initiation and maintenance of RI. Despite similar simulated intensification time series, the exhibited hydrometeor characteristics differ between the two cases since Ike possesses less asymmetry and less vigorous convection than Earl. An objective method to quantitatively estimate the radius of maximum wind (RMW) with respect to height is introduced for quantifying the primary circulation character of each storm, permitting analysis of where heating is most efficient for driving warm core growth and subsequent intensification. Following eye development in each, diabatic heating remains embedded within the RMW. Earl's RI onset coincides with an absolute maximum in diabatic heating occurring within the RMW, while Ike possesses relatively less diabatic heating inside the RMW throughout and lacks an absolute peak associated with RI. The majority of diabatic heating within the RMW of both cases occurs at subfreezing temperatures, indicative of the importance of clouds associated with ice processes in these RI simulations. Earl's diabatic heating peak is tied to a maximum in convective burst activity residing within the RMW. Earl's preference for more sparse but intense convection is associated with increased sea surface temperatures, surface heat fluxes, moisture convergence, and near-surface equivalent potential temperature relative to the broader, weaker convective character in Ike. [ABSTRACT FROM AUTHOR]