Publications

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2018
Vashishtha, D, Sieber W, Hailey B, Guirguis K, Gershunov A, Al-Delaimy WK.  2018.  Outpatient clinic visits during heat waves: findings from a large family medicine clinical database. Family Practice. 35:567-570.   10.1093/fampra/cmy013   AbstractWebsite

Introduction. The purpose of this study was to determine whether heat waves are associated with increased frequency of clinic visits for ICD-9 codes of illnesses traditionally associated with heat waves. Methods. During 4 years of family medicine clinic data between 2012 and 2016, we identified six heat wave events in San Diego County. For each heat wave event, we selected a control period in the same season that was twice as long. Scheduling a visit on a heat wave day (versus a non-heat wave day) was the primary predictor, and receiving a primary ICD-9 disease code related to heat waves was the outcome. Analyses were adjusted for age, gender, race/ethnicity and marital status. Results. Of the 5448 visits across the heat wave and control periods, 6.4% of visits (n = 346) were for heat wave-related diagnoses. Scheduling a visit on heat wave day was not associated with receiving a heat wave-related ICD code as compared with the control period (adjusted odds ratio: 1.35; 95% confidence interval: 0.86-1.36; P = 0.51). Discussion. We show that in a relatively large and demographically diverse population, patients who schedule appointments during heat waves are not being more frequently seen for diagnoses typically associated with heat waves in the acute setting. Given that heat waves are increasing in frequency due to climate change, there is an opportunity to increase utilization of primary care clinics during heat waves.

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.

2017
Clemesha, RES, Gershunov A, Iacobellis SF, Cayan DR.  2017.  Daily variability of California coastal low cloudiness: A balancing act between stability and subsidence. Geophysical Research Letters. 44:3330-3338.   10.1002/2017gl073075   AbstractWebsite

We examine mechanisms driving daily variability of summer coastal low cloudiness (CLC) along the California coast. Daily CLC is derived from a satellite record from 1996 to 2014. Atmospheric rather than oceanic processes are mostly responsible for daily fluctuations in vertical stability that dictate short-period variation in CLC structure. Daily CLC anomalies are most strongly correlated to lower tropospheric stability anomalies to the north. The spatially offset nature of the cloud-stability relationship is a result of the balancing act that affects low cloudiness wherein subsidence drives increased stability, which promotes cloudiness, but too much subsidence limits cloudiness. Lay explanations claim that high inland temperatures pull in CLC, but such a process presumably would have the high temperatures directly inland. Rather, we find that the spatially offset associations between CLC and atmospheric circulation result in positive correlations between CLC and inland surface temperature anomalies to the north.

2013
Polade, SD, Gershunov A, Cayan DR, Dettinger MD, Pierce DW.  2013.  Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models. Geophysical Research Letters. 40:2296-2301.   10.1002/grl.50491   AbstractWebsite

Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

2001
Gershunov, A, Schneider N, Barnett T.  2001.  Low-frequency modulation of the ENSO-Indian monsoon rainfall relationship: Signal or noise? Journal of Climate. 14:2486-2492.   10.1175/1520-0442(2001)014<2486:lfmote>2.0.co;2   AbstractWebsite

Running correlations between pairs of stochastic time series are typically characterized by low-frequency evolution. This simple result of sampling variability holds for climate time series but is not often recognized for being merely noise. As an example, this paper discusses the historical connection between El Nino-Southern Oscillation (ENSO) and average Indian rainfall (AIR). Decades of strong correlation (similar to -0.8) alternate with decades of insignificant correlation, and it is shown that this decadal modulation could be due solely to stochastic processes. In fact, the specific relationship between ENSO and AIR is significantly less variable on decadal timescales than should be expected from sampling variability alone.