Atmospheric rivers (ARs) are well-known producers of precipitation along the U.S. West Coast. Depending on their intensity, orientation, and location of landfall, some ARs penetrate inland and cause heavy rainfall and flooding hundreds of miles from the coast. Climate change is projected to potentially alter a variety of AR characteristics and impacts. This study examines potential future changes in moisture transport and precipitation intensity, type, and distribution for a high-impact landfalling AR event in the U.S. Pacific Northwest using an ensemble of high-resolution numerical simulations produced under projected future thermodynamic changes. Results indicate increased total precipitation in all future simulations, although there is considerable model spread in both domain-averaged and localized inland precipitation totals. Notable precipitation enhancements across inland locations such as Idaho’s Sawtooth Mountain Range are present in four out of six future simulations. The most marked inland precipitation increases are shown to occur by way of stronger and deeper moisture transport that more effectively crosses Oregon’s Coastal and Cascade mountain ranges, essentially “spilling over” into the Snake River Valley and fueling orographic precipitation in the Sawtooth Mountains. Moisture transport enhancements are shown to have both thermodynamic and dynamic contributions, with both enhanced absolute environmental moisture and localized lower- and midlevel dynamics contributing to amplified inland moisture penetration. Precipitation that fell as snow in the present-day simulation becomes rain in the future simulations for many mid- and high-elevation locations, suggesting potential for enhanced flood risk for these regions in future climate instances of similar events.
Seasonal forecasts of summer continental United States (CONUS) rainfall have relatively low skill, partly due to a lack of consensus about its sources of predictability. The East Asian monsoon (EAM) can excite a cross-Pacific Rossby wave train, also known as the Asia-North America (ANA) teleconnection. In this study, we analyze the ANA teleconnection in observations and model simulations from the Community Atmospheric Model, version 5 (CAM5), comparing experiments with prescribed climatological SSTs and prescribed observed SSTs. Observations indicate a statistically significant relationship between a strong EAM and increased probability of positive precipitation anomalies over the U.S. west coast and the Plains-Midwest. The ANA teleconnection and CONUS rainfall patterns are improved in the CAM5 experiment with prescribed observed SSTs, suggesting that SST variability is necessary to simulate this teleconnection over CONUS. We find distinct ANA patterns between ENSO phases, with the La Niña-related patterns in CAM5_obsSST disagreeing with observations.Using linear steady-state quasi-geostrophic theory, we conclude that incorrect EAM forcing location greatly contributed to CAM5 biases, and jet stream disparities explained the ENSOrelated biases. Finally, we compared EAM forcing experiments with different mean states using a simple dry nonlinear atmospheric general circulation model. Overall, the ANA pattern over CONUS and its modulation by ENSO forcing are well described by dry dynamics on seasonalto-interannual timescales, including the constructive (destructive) interference between El Niño (La Niña) modulation and the ANA patterns over CONUS.
Warm-season precipitation in the U.S. “Corn Belt,” the Great Plains, and the Midwest greatly influences agricultural production and is subject to high interannual and intraseasonal variability. Unfortunately, current seasonal and subseasonal forecasts for summer precipitation have relatively low skill. Therefore, there are ongoing efforts to understand hydroclimate variability targeted at improving predictions, particularly through its primary transporter of moisture: the Great Plains low-level jet (LLJ). This study uses the Community Climate System Model, version 4 (CCSM4), July forecasts, made as part of the North American Multi-Model Ensemble (NMME), to assess skill in reproducing the monthly Great Plains LLJ and associated precipitation. Generally, the CCSM4 forecasts capture the climatological jet but have problems representing the observed variability beyond two weeks. In addition, there are predictors associated with the large-scale variability identified through linear regression analysis, shifts in kernel density estimators, and case study analysis that suggest potential for improving confidence in forecasts. In this study, a strengthened Caribbean LLJ, negative Pacific–North American (PNA) teleconnection, El Niño, and a negative Atlantic multidecadal oscillation each have a relatively strong and consistent relationship with a strengthened Great Plains LLJ. The circulation predictors, the Caribbean LLJ and PNA, present the greatest “forecast of opportunity” for considering and assigning confidence in monthly forecasts.
Understanding summertime continental U.S. (CONUS) hydroclimate predictability on the subseasonal-to-seasonal (S2S) timescale has been challenging, and relationships between tropical remote forcing and mid-latitude circulation are difficult to assess due to the overall weak signals of the summer season (Trenberth et al., 1998;S. Zhou et al., 2012). Many studies suggest that Asian summer monsoon (ASM) variability on the seasonal-to-interannual timescale, especially over the West North Pacific (WNPM) and/or East Asian Monsoon (EAM) region, can influence CONUS hydroclimate via a quasi-stationary Rossby wave response (
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