Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of dollars in flood damage. Because they transport latent energy towards the poles, they are crucial to maintaining the climate system’s energy balance. Although ARs are characterized by long, narrow filaments of water vapor, there is no first-principles definition of ARs grounded in geophysical fluid dynamics. Therefore, AR identification is currently performed by a large array of expert-defined, threshold-based algorithms. The variety of algorithms has introduced uncertainty in the projected future behavior of ARs, with consequences for understanding the future behavior of floods and drought. We propose an upper bound to constrain future AR projections using the dynamics of the large-scale atmospheric circulation.
While existing studies assess ARs’ contribution to net latent heat transport (LHT), we calculate the relationship between ARs and transient eddy LHT. Using a framework of diffusive heat transport, we decompose eddy LHT into moist, poleward and dry, equatorward components. In a multimodel ensemble of high-resolution climate simulations, we demonstrate that moist, poleward eddy LHT is a physics-based upper bound for AR-induced heat transport. We use this upper bound to constrain summer and winter changes in AR frequency, intensity, and precipitation.