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Sherbakov, T, Malig B, Guirguis K, Gershunov A, Basu R.  2018.  Ambient temperature and added heat wave effects on hospitalizations in California from 1999 to 2009. Environmental Research. 160:83-90.   10.1016/j.envres.2017.08.052   AbstractWebsite

Investigators have examined how heat waves or incremental changes in temperature affect health outcomes, but few have examined both simultaneously. We utilized distributed lag nonlinear models (DLNM) to explore temperature associations and evaluate possible added heat wave effects on hospitalizations in 16 climate zones throughout California from May through October 1999-2009. We define heat waves as a period when daily mean temperatures were above the zone- and month-specific 95th percentile for at least two consecutive days. DLNMs were used to estimate climate zone-specific non-linear temperature and heat wave effects, which were then combined using random effects meta-analysis to produce an overall estimate for each. With higher temperatures, admissions for acute renal failure, appendicitis, dehydration, ischemic stroke, mental health, noninfectious enteritis, and primary diabetes were significantly increased, with added effects from heat waves observed for acute renal failure and dehydration. Higher temperatures also predicted statistically significant decreases in hypertension admissions, respiratory admissions, and respiratory diseases with secondary diagnoses of diabetes, though heat waves independently predicted an added increase in risk for both respiratory types. Our findings provide evidence that both heat wave and temperature exposures can exert effects independently.

Gershunov, A, Shulgina T, Ralph MF, Lavers DA, Rutz JJ.  2017.  Assessing the climate-scale variability of atmospheric rivers affecting western North America. Geophysical Research Letters.   10.1002/2017GL074175   Abstract

A new method for automatic detection of atmospheric rivers (ARs) is developed and applied to an atmospheric reanalysis, yielding an extensive catalog of ARs land-falling along the west coast of North America during 1948–2017. This catalog provides a large array of variables that can be used to examine AR cases and their climate-scale variability in exceptional detail. The new record of AR activity, as presented, validated and examined here, provides a perspective on the seasonal cycle and the interannual-interdecadal variability of AR activity affecting the hydroclimate of western North America. Importantly, AR intensity does not exactly follow the climatological pattern of AR frequency. Strong links to hydroclimate are demonstrated using a high-resolution precipitation data set. We describe the seasonal progression of AR activity and diagnose linkages with climate variability expressed in Pacific sea surface temperatures, revealing links to Pacific decadal variability, recent regional anomalies, as well as a generally rising trend in land-falling AR activity. The latter trend is consistent with a long-term increase in vapor transport from the warming North Pacific onto the North American continent. The new catalog provides unprecedented opportunities to study the climate-scale behavior and predictability of ARs affecting western North America.

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.