We compare historical and end‐of‐century temperature and precipitation patterns over California from one dynamically downscaled simulation using the Weather Research and Forecast (WRF) model and two simulations statistically downscaled using Localized Constructed Analogs (LOCA). We uniquely separate causes of differences between dynamically and statistically based future climate projections into differences in historical climate (gridded observations versus regional climate model output) and differences in how these downscaling techniques explicitly handle future climate changes (numerical modeling versus analogs). In these methods, solutions between different downscaling techniques differ more in the future compared to the historical period. Changes projected by LOCA are insensitive to the choice of driving data. Only through dynamical downscaling can we simulate physically consistent regional springtime warming patterns across the Sierra Nevada, while the statistical simulations inherit an unphysical signal from their parent Global Climate Model (GCM) or gridded data. The results of our study clarify why these different techniques produce different outcomes and may also provide guidance on which downscaled products to use for certain impact analyses in California and perhaps other Mediterranean regimes.
This study focuses on quantifying future anthropogenic changes in surface runoff associated with extreme precipitation in California's Sierra Nevada. The method involves driving a land surface model with output from a high resolution regional atmospheric simulation of the most extreme atmospheric rivers (ARs). AR events were selected from an ensemble of global climate model simulations of historical and late 21st century climate under the “high‐emission” RCP8.5 scenario. Average precipitation during the future ARs increases by ~25% but a much lower proportion falls as snow. The resulting future runoff increase is dramatic—nearly 50%, reflecting both the precipitation increase and simultaneous conversion of snow to rain. The “double whammy” impact on runoff is largest in the 2,000–2,500 m elevation band, where the snowfall loss and precipitation increase are both especially large. This huge increase in runoff during the most extreme AR events could present major flood control challenges for the region.
Paper Summary InfographicPrecipitation extremes will likely intensify under climate change. However, much uncertainty surrounds intensification of high-magnitude events that are often inadequately resolved by global climate models. In this analysis, we develop a framework involving targeted dynamical downscaling of historical and future extreme precipitation events produced by a large ensemble of a global climate model. This framework is applied to extreme “atmospheric river” storms in California. We find a substantial (10 to 40%) increase in total accumulated precipitation, with the largest relative increases in valleys and mountain lee-side areas. We also report even higher and more spatially uniform increases in hourly maximum precipitation intensity, which exceed Clausius-Clapeyron expectations. Up to 85% of this increase arises from thermodynamically driven increases in water vapor, with a smaller contribution by increased zonal wind strength. These findings imply substantial challenges for water and flood management in California, given future increases in intense atmospheric river-induced precipitation extremes.
Paper Summary InfographicPayne, AE, ME Demory, LR Leung, AM Ramos, CA Shields, JJ Rutz, N Siler, G Villarini, A Hall, and FM Ralph. 2020. “
Responses and impacts of atmospheric rivers to climate change.” Nature Reviews Earth & Environment 1: 143–157.
Publisher's Version Abstract Atmospheric rivers (ARs) are characterized by intense moisture transport, which, on landfall, produce precipitation which can be both beneficial and destructive. ARs in California, for example, are known to have ended drought conditions but also to have caused substantial socio-economic damage from landslides and flooding linked to extreme precipitation. Understanding how AR characteristics will respond to a warming climate is, therefore, vital to the resilience of communities affected by them, such as the western USA, Europe, East Asia and South Africa. In this Review, we use a theoretical framework to synthesize understanding of the dynamic and thermodynamic responses of ARs to anthropogenic warming and connect them to observed and projected changes and impacts revealed by observations and complex models. Evidence suggests that increased atmospheric moisture (governed by Clausius–Clapeyron scaling) will enhance the intensity of AR-related precipitation — and related hydrological extremes — but with changes that are ultimately linked to topographic barriers. However, due to their dependency on both weather and climate-scale processes, which themselves are often poorly constrained, projections are uncertain. To build confidence and improve resilience, future work must focus efforts on characterizing the multiscale development of ARs and in obtaining observations from understudied regions, including the West Pacific, South Pacific and South Atlantic.
Atmospheric rivers (ARs) are responsible for a majority of extreme precipitation and flood events along the U.S. West Coast. To better understand the present‐day characteristics of AR‐related precipitation extremes, a selection of nine most intense historical AR events during 1980–2017 is simulated using a dynamical downscaling modeling framework based on the Weather Research and Forecasting Model. We find that the chosen framework and Weather Research and Forecasting Model configuration reproduces both large‐scale atmospheric features—including parent synoptic‐scale cyclones—as well as the filamentary corridors of integrated vapor transport associated with the ARs themselves. The accuracy of simulated extreme precipitation maxima, relative to in situ and interpolated gridded observations, improves notably with increasing model resolution, with improvements as large as 40–60% for fine scale (3 km) relative to coarse‐scale (27 km) simulations. A separate set of simulations using smoothed topography suggests that much of these gains stem from the improved representation of complex terrain. Additionally, using the 12 December 1995 storm in Northern California as an example, we demonstrate that only the highest‐resolution simulations resolve important fine‐scale features—such as localized orographically forced vertical motion and powerful near hurricane‐force boundary layer winds. Given the demonstrated ability of a targeted dynamical downscaling framework to capture both local extreme precipitation and key fine‐scale characteristics of the most intense ARs in the historical record, we argue that such a configuration may be highly conducive to understanding AR‐related extremes and associated changes in a warming climate.