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Schwartz, RE, Gershunov A, Iacobellis SF, Cayan DR.  2014.  North American west coast summer low cloudiness: Broadscale variability associated with sea surface temperature. Geophysical Research Letters. 41:3307-3314.   10.1002/2014gl059825   AbstractWebsite

Six decades of observations at 20 coastal airports, from Alaska to southern California, reveal coherent interannual to interdecadal variation of coastal low cloudiness (CLC) from summer to summer over this broad region. The leading mode of CLC variability represents coherent variation, accounting for nearly 40% of the total CLC variance spanning 1950-2012. This leading mode and the majority of individual airports exhibit decreased low cloudiness from the earlier to the later part of the record. Exploring climatic controls on CLC, we identify North Pacific Sea Surface Temperature anomalies, largely in the form of the Pacific Decadal Oscillation (PDO) as well correlated with, and evidently helping to organize, the coherent patterns of summer coastal cloud variability. Links from the PDO to summer CLC appear a few months in advance of the summer. These associations hold up consistently in interannual and interdecadal frequencies.

Semenza, JC, Caplan JS, Buescher G, Das T, Brinks MV, Gershunov A.  2012.  Climate change and microbiological water quality at California beaches. Ecohealth. 9:293-297.   10.1007/s10393-012-0779-1   AbstractWebsite

Daily microbiological water quality and precipitation data spanning 6 years were collected from monitoring stations at southern California beaches. Daily precipitation projected for the twenty-first century was derived from downscaled CNRM CM3 global climate model. A time series model of Enterococcus concentrations that was driven by precipitation, matched the general trend of empirical water quality data; there was a positive association between precipitation and microbiological water contamination (P < 0.001). Future projections of precipitation result in a decrease in predicted Enterococcus levels through the majority of the twenty-first century. Nevertheless, variability of storminess due to climate change calls for innovative adaptation and surveillance strategies.

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.

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.