Climate models consistently project a significant drying in the Caribbean during climate change, and between 2013–2016 the region experienced the worst multi-year drought in the historical period. Although dynamical mechanisms have been proposed to explain drought in the Caribbean, it is unknown the contributions from mass convergence and advection to precipitation-evaporation (P-E) anomalies during drought. Here we analyze the dynamics of contemporaneous droughts in the Caribbean by decomposing the contributions of mass convergence and advection to P-E using observational and simulated data. We find that droughts arise from an anomalous subsidence over the southeastern Caribbean and northeastern South America. Although the contributions from mass convergence and advection vary across the region, it is mass convergence that is the main driver of drought in our study area. A similar dynamical pattern is observed in simulated droughts using the Community Earth System Model (CESM) Large Ensemble (LENS).

The atmospheric Green’s function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.’ To better study this method, this paper presents a protocol for creating atmospheric Green’s functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere-only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming vs. cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green’s function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation.

The atmospheric Green’s function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.” To better study this method, this paper presents a protocol for creating atmospheric Green’s functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere-only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming vs. cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green’s function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation.

Strengthened land‐atmosphere coupling in the northeastern United States (NEUS), accompanied by a positive soil moisture‐rainfall feedback, may lead to more drought. Coupling between the land and atmosphere emerges when low soil moisture values limit surface latent heat flux, or evapotranspiration, so that a majority of absorbed solar radiation is emitted from the surface as sensible heat. In this study, the Weather Research and Forecasting model was run with four prescribed soil moisture levels across 7 years to elucidate the strength of land‐atmosphere coupling under potential, future soil moisture states in the NEUS. Under drier conditions, land‐atmosphere coupling strengthens, and a positive soil moisture‐precipitation feedback develops in all years despite differences in the amount of moisture advected into the study domain. As snowpack decreases and evaporative demand increases, soil conditions may become drier in future summers over the NEUS, resulting in the more frequent development of drought.