Publications

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2019
Guzman-Morales, J, Gershunov A.  2019.  Climate change suppresses Santa Ana winds of Southern California and sharpens their seasonality. Geophysical Research Letters. 46:2772-2780.   10.1029/2018gl080261   AbstractWebsite

We downscale Santa Ana winds (SAWs) from eight global climate models (GCMs) and validate key aspects of their climatology over the historical period. We then assess SAW evolution and behavior through the 21st century, paying special attention to changes in their extreme occurrences. All GCMs project decreases in SAW activity, starting in the early 21st century, which are commensurate with decreases in the southwestward pressure gradient force that drives these winds. The trend is most pronounced in the early and late SAW season: fall and spring. It is mainly determined by changes in the frequency of SAW events, less so by changes in their intensity. The peak of the SAW season (November-December-January) is least affected by anthropogenic climate change in GCM projections. Plain Language Summary Dry and gusty Santa Ana winds (SAWs) drive the most catastrophic wildfires in Southern California. Their sensitivity to the changing climate has been a matter of uncertainty and debate. We have assessed the response of SAW activity to global warming and describe these results in detail here. The overall decrease in SAW activity robustly projected by downscaled global climate models is strongest in the early and late seasons-fall and spring. SAWs are expected to decrease least at the peak of their season approximately December. Importantly, decreased SAW activity in the future climate is driven mainly by decreased frequency rather than the peak intensity of these winds. These results, together with what we know from recent literature about how precipitation is projected to change in this region, suggest a later wildfire season in the future.

2018
Guirguis, K, Gershunov A, Clemesha RES, Shulgina T, Subramanian AC, Ralph FM.  2018.  Circulation drivers of atmospheric rivers at the North American West Coast. Geophysical Research Letters. 45:12576-12584.   10.1029/2018gl079249   AbstractWebsite

Atmospheric rivers (ARs) are mechanisms of strong moisture transport capable of bringing heavy precipitation to the West Coast of North America, which drives water resources and can lead to large-scale flooding. Understanding links between climate variability and landfalling ARs is critical for improving forecasts on timescales needed for water resource management. We examined 69years of landfalling ARs along western North America using reanalysis and a long-term AR catalog to identify circulation drivers of AR landfalls. This analysis reveals that AR activity along the West Coast is largely associated with a handful of influential modes of atmospheric variability. Interaction between these modes creates favorable or unfavorable atmospheric states for landfalling ARs at different locations, effectively steering moisture plumes up and down the coast from Mexico to British Columbia. Seasonal persistence of certain modes helps explain interannual variability of landfalling ARs, including recent California drought years and the wet winter of 2016/2017. Plain Language Summary Understanding links between large-scale climate variability and landfalling ARs is important for improving subseasonal-to-seasonal (S2S) predictability of water resources in the western United States. We have analyzed a seven-decade-long catalog of ARs impacting western North America to quantify synoptic influence on AR activity. Our results identify dominant circulation patterns associated with landfalling ARs and show how seasonal variation in the prevalence of certain circulation features modulates the frequency of AR landfalls at different latitudes in a given year. AR variability played an important role in the recent California drought as well as the wet winter of 2016/2017, and we show how this variability was associated with the relative frequency of favorable versus unfavorable atmospheric states. Our findings also reveal that the bulk of AR landfalls along the West Coast is associated with only a handful of influential circulation features, which has implications for S2S predictability.

Shields, CA, Rutz JJ, Leung LY, Ralph FM, Wehner M, Kawzenuk B, Lora JM, McClenny E, Osborne T, Payne AE, Ullrich P, Gershunov A, Goldenson N, Guan B, Qian Y, Ramos AM, Sarangi C, Sellars S, Gorodetskaya I, Kashinath K, Kurlin V, Mahoney K, Muszynski G, Pierce R, Subramanian AC, Tome R, Waliser D, Walton D, Wick G, Wilson A, Lavers D, Prabhat, Collow A, Krishnan H, Magnusdottir G, Nguyen P.  2018.  Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design. Geoscientific Model Development. 11:2455-2474.   10.5194/gmd-11-2455-2018   AbstractWebsite

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month "proof-of-concept" trial run designed to illustrate the utility and feasibility of the ARTMIP project.