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Aguilera, R, Gershunov A, Benmarhnia T.  2019.  Atmospheric rivers impact California's coastal water quality via extreme precipitation. Science of the Total Environment. 671:488-494.   10.1016/j.scitotenv.2019.03.318   AbstractWebsite

Precipitation in California is projected to become more volatile: less frequent but more extreme as global warming pushes midlatitude frontal cyclones further poleward while bolstering the atmospheric rivers (ARs), which tend to produce the region's extreme rainfall. Pollutant accumulation and delivery to coastal waters can be expected to increase, as lengthening dry spells will be increasingly punctuated by more extreme precipitation events. Coastal pollution exposes human populations to high levels of fecal bacteria and associated pathogens, which can cause a variety of health impacts. Consequently, studying the impact of atmospheric rivers as the mechanism generating pulses of water pollution in coastal areas is relevant for public health and in the context of climate change. We aimed to quantify the links between precipitation events and water quality in order to explore meteorological causes as first steps toward effective early warning systems for the benefit of population health in California and beyond. We used historical gridded daily precipitation and weekly multiple fecal bacteria indicators at similar to 500 monitoring locations in California's coastal waters to identify weekly associations between precipitation and water quality during 2003-09 using canonical correlation analysis to account for the nested/clustered nature of longitudinal data. We then quantified, using a recently published catalog of atmospheric rivers, the proportion of coastal pollution events attributable to ARs. Association between precipitation and fecal bacteria was strongest in Southern California. Over two-thirds of coastal water pollution spikes exceeding one standard deviation were associated with ARs. This work highlights the importance of skillful AR landfall predictions in reducing vulnerability to extreme weather improving resilience of human populations in a varying and changing climate. Quantifying the impacts of ARs on waterborne diseases is important for planning effective preventive strategies for public health. (C) 2019 Elsevier B.V. All rights reserved.

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.

Guirguis, K, Gershunov A, Cayan DR, Pierce DW.  2018.  Heat wave probability in the changing climate of the Southwest US. Climate Dynamics. 50:3853-3864.   10.1007/s00382-017-3850-3   AbstractWebsite

Analyses of observed non-Gaussian daily minimum and maximum temperature probability distribution functions (PDFs) in the Southwest US highlight the importance of variance and warm tail length in determining future heat wave probability. Even if no PDF shape change occurs with climate change, locations with shorter warm tails and/or smaller variance will see a greater increase in heat wave probability, defined as exceedances above the historical 95th percentile threshold, than will long tailed/larger variance distributions. Projections from ten downscaled CMIP5 models show important geospatial differences in the amount of warming expected for a location. However, changes in heat wave probability do not directly follow changes in background warming. Projected changes in heat wave probability are largely explained by a rigid shift of the daily temperature distribution. In some locations where there is more warming, future heat wave probability is buffered somewhat by longer warm tails. In other parts of the Southwest where there is less warming, heat wave probability is relatively enhanced because of shorter tailed PDFs. Effects of PDF shape changes are generally small by comparison to those from a rigid shift, and fall within the range of uncertainty among models in the amount of warming expected by the end of the century.

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.

Guirguis, K, Gershunov A, Cayan DR.  2015.  Interannual variability in associations between seasonal climate, weather, and extremes: wintertime temperature over the Southwestern United States. Environmental Research Letters. 10   10.1088/1748-9326/10/12/124023   AbstractWebsite

Temperature variability in the Southwest US is investigated using skew-normal probability distribution functions (SN PDFs) fitted to observed wintertime daily maximum temperature records. These PDFs vary significantly between years, with important geographical differences in the relationship between the central tendency and tails, revealing differing linkages between weather and climate. The warmest and coldest extremes do not necessarily follow the distribution center. In some regions one tail of the distribution shows more variability than does the other. For example, in California the cold tail is more variable while the warm tail remains relatively stable, so warm years are associated with fewer cold extremes but not necessarily more warm extremes. The opposite relationship is seen in the Great Plains. Changes in temperature PDFs are conditioned by different phases of El Nino-La Nina (ENSO) and the Pacific decadal oscillation (PDO). In the Southern Great Plains, La Nina and/or negative PDO are associated with generally warmer conditions. However, in terms of extremes, while the warm tails become thicker and longer, the cool tails are not impacted-extremely warm days become more frequent but extremely cool days are not less frequent. In contrast, in coastal California, La Nina or negative PDO bring generally cooler conditions with more/stronger cold extremes but the warm extreme probability is not significantly affected. These results could have implications for global warming. If a rigid shift of the whole range occurs, then warm years are not necessarily a good analogue for a warmer climate. If global warming instead brings regional changes more aligned with a preferred state of dominant climate variability modes, then we may see asymmetric changes in the tails of local temperature PDFs.

Cavanaugh, NR, Gershunov A, Panorska AK, Kozubowski TJ.  2015.  The probability distribution of intense daily precipitation. Geophysical Research Letters. 42:1560-1567.   10.1002/2015gl063238   AbstractWebsite

The probability tail structure of over 22,000 weather stations globally is examined in order to identify the physically and mathematically consistent distribution type for modeling the probability of intense daily precipitation and extremes. Results indicate that when aggregating data annually, most locations are to be considered heavy tailed with statistical significance. When aggregating data by season, it becomes evident that the thickness of the probability tail is related to the variability in precipitation causing events and thus that the fundamental cause of precipitation volatility is weather diversity. These results have both theoretical and practical implications for the modeling of high-frequency climate variability worldwide.

Guirguis, K, Gershunov A, Tardy A, Basu R.  2014.  The impact of recent heat waves on human health in California. Journal of Applied Meteorology and Climatology. 53:3-19.   10.1175/jamc-d-13-0130.1   AbstractWebsite

This study examines the health impacts of recent heat waves statewide and for six subregions of California: the north and south coasts, the Central Valley, the Mojave Desert, southern deserts, and northern forests. By using canonical correlation analysis applied to daily maximum temperatures and morbidity data in the form of unscheduled hospitalizations from 1999 to 2009, 19 heat waves spanning 3-15 days in duration that had a significant impact on health were identified. On average, hospital admissions were found to increase by 7% on the peak heat-wave day, with a significant impact seen for several disease categories, including cardiovascular disease, respiratory disease, dehydration, acute renal failure, heat illness, and mental health. Statewide, there were 11 000 excess hospitalizations that were due to extreme heat over the period, yet the majority of impactful events were not accompanied by a heat advisory or warning from the National Weather Service. On a regional basis, the strongest health impacts are seen in the Central Valley and the north and south coasts. The north coast contributes disproportionately to the statewide health impact during heat waves, with a 10.5% increase in daily morbidity at heat-wave peak as compared with 8.1% for the Central Valley and 5.6% for the south coast. The temperature threshold at which an impact is seen varies by subregion and timing within the season. These results suggest that heat-warning criteria should consider local percentile thresholds to account for acclimation to local climatological conditions as well as the seasonal timing of a forecast heat wave.

Rodo, X, Pascual M, Doblas-Reyes FJ, Gershunov A, Stone DA, Giorgi F, Hudson PJ, Kinter J, Rodriguez-Arias MA, Stenseth NC, Alonso D, Garcia-Serrano J, Dobson AP.  2013.  Climate change and infectious diseases: Can we meet the needs for better prediction? Climatic Change. 118:625-640.   10.1007/s10584-013-0744-1   AbstractWebsite

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.

Macias, D, Landry MR, Gershunov A, Miller AJ, Franks PJS.  2012.  Climatic control of upwelling variability along the western North American coast. Plos One. 7   10.1371/journal.pone.0030436   AbstractWebsite

The high biological production of the California Current System (CCS) results from the seasonal development of equatorward alongshore winds that drive coastal upwelling. While several climatic fluctuation patterns influence the dynamics and biological productivity of the CCS, including the El Nino-Southern Oscillation (ENSO), the Pacific Decadal Oscillation index (PDO) and the North Pacific Gyre Oscillation (NPGO), the mechanisms of interaction between climatic oscillations and the CCS upwelling dynamics have remained obscure. Here, we use Singular Spectral Analysis (SSA) to reveal, for the first time, low-frequency concordance between the time series of climatic indices and upwelling intensity along the coast of western North America. Based on energy distributions in annual, semiannual and low-frequency signals, we can divide the coast into three distinct regions. While the annual upwelling signal dominates the energy spectrum elsewhere, low-frequency variability is maximal in the regions south of 33 degrees N. Non-structured variability associated with storms and turbulent mixing is enhanced at northerly locations. We found that the low-frequency signal is significantly correlated with different climatic indices such as PDO, NPGO and ENSO with the correlation patterns being latitude-dependent. We also analyzed the correlations between this upwelling variability and sea surface temperature (SST) and sea level pressure (SLP) throughout the North Pacific to visualize and interpret the large-scale teleconnection dynamics in the atmosphere that drive the low-frequency coastal winds. These results provide new insights into the underlying mechanisms connecting climatic patterns with upwelling dynamics, which could enhance our prediction and forecast capabilities of the effects of future oceanographic and climatic variability in the CCS.

Gershunov, A, Cayan DR, Iacobellis SF.  2009.  The great 2006 heat wave over California and Nevada: Signal of an increasing trend. Journal of Climate. 22:6181-6203.   10.1175/2009jcli2465.1   AbstractWebsite

Most of the great California-Nevada heat waves can be classified into primarily daytime or nighttime events depending on whether atmospheric conditions are dry or humid. A rash of nighttime-accentuated events in the last decade was punctuated by an unusually intense case in July 2006, which was the largest heat wave on record (1948-2006). Generally, there is a positive trend in heat wave activity over the entire region that is expressed most strongly and clearly in nighttime rather than daytime temperature extremes. This trend in nighttime heat wave activity has intensified markedly since the 1980s and especially since 2000. The two most recent nighttime heat waves were also strongly expressed in extreme daytime temperatures. Circulations associated with great regional heat waves advect hot air into the region. This air can be dry or moist, depending on whether a moisture source is available, causing heat waves to be expressed preferentially during day or night. A remote moisture source centered within a marine region west of Baja California has been increasing in prominence because of gradual sea surface warming and a related increase in atmospheric humidity. Adding to the very strong synoptic dynamics during the 2006 heat wave were a prolonged stream of moisture from this southwestern source and, despite the heightened humidity, an environment in which afternoon convection was suppressed, keeping cloudiness low and daytime temperatures high. The relative contributions of these factors and possible relations to global warming are discussed.

Ben Ari, T, Gershunov A, Gage KL, Snall T, Ettestad P, Kausrud KL, Stenseth NC.  2008.  Human plague in the USA: the importance of regional and local climate. Biology Letters. 4:737-740.   10.1098/rsbl.2008.0363   AbstractWebsite

A 56-year time series of human plague cases (Yersinia pestis) in the western United States was used to explore the effects of climatic patterns on plague levels. We found that the Pacific Decadal Oscillation (PDO), together with previous plague levels and above-normal temperatures, explained much of the plague variability. We propose that the PDO's impact on plague is conveyed via its effect on precipitation and temperature and the effect of precipitation and temperature on plague hosts and vectors: warmer and wetter climate leading to increased plague activity and thus an increased number of human cases. Our analysis furthermore provides insights into the consistency of plague mechanisms at larger scales.

Favre, A, Gershunov A.  2006.  Extra-tropical cyclonic/anticyclonic activity in North-Eastern Pacific and air temperature extremes in Western North America. Climate Dynamics. 26:617-629.   10.1007/s00382-005-0101-9   AbstractWebsite

Synoptic extra-tropical cyclone and anticyclone trajectories have been constructed from mean daily sea level pressure (SLP) data using a new automated scheme. Frequency, intensity and trajectory characteristics of these transients have been summarized to form indices describing wintertime cyclonic and anticyclonic activity over the North-Eastern Pacific (east of 170 degrees W) during 1950-2001. During this period, the strength of anticyclones gradually diminished and their frequency became more variable, while cyclones intensified in a discrete shift with deeper lows and further southerly trajectories occurring since the mid-1970s. These changes in synoptic transients translate into anomalously low seasonal mean SLP in the Aleutian Low, a low-level circulation anomaly consistent with the positive phase of the North Pacific Decadal Oscillation, with positive sea surface temperature (SST) anomalies along the west coast of North America and negative in the central North Pacific Ocean. A link between cyclonic/anticyclonic activity and tropical SST anomalies also exists, but this link only becomes significant after the mid-1970s, a period that coincides with more southerly cyclone trajectories. Southward excursions of mid-latitude cyclones during El Ni (n) over tildeo/positive NPO winters accomplish the northward advection of tropical air and discourage the southward penetration of polar air masses associated with transient anticyclones. Naturally, these changes in cyclonic/anticyclonic activity directly impact surface air temperatures, especially at night. We document these profound impacts on observed wintertime minimum temperatures over Western North America.

Alfaro, EJ, Pierce DW, Steinemann AC, Gershunov A.  2005.  Relationships between the irrigation-pumping electrical loads and the local climate in Climate Division 9, Idaho. Journal of Applied Meteorology. 44:1972-1978.   10.1175/jam2315.1   AbstractWebsite

The electrical load from irrigation pumps is an important part of the overall electricity demand in many agricultural areas of the U.S. west. The date the pumps turn on and the total electrical load they present over the summer varies from year to year, partly because of climate fluctuations. Predicting this variability would be useful to electricity producers that supply the region. This work presents a contingency analysis and linear regression scheme for forecasting summertime irrigation pump loads in southeastern Idaho. The basis of the predictability is the persistence of spring soil moisture conditions into summer, and the effect it has on summer temperatures. There is a strong contemporaneous relationship between soil moisture and temperature in the summer and total summer pump electrical loads so that a reasonable prediction of summer pump electrical loads based on spring soil moisture conditions can be obtained in the region. If one assumes that decision makers will take appropriate actions based on the forecast output, the net economic benefit of forecast information is approximately $2.5 million per year, making this prediction problem an important seasonal summer forecasting issue with significant economic implications.

Gershunov, A, Cayan DR.  2003.  Heavy daily precipitation frequency over the contiguous United States: Sources of climatic variability and seasonal predictability. Journal of Climate. 16:2752-2765.   10.1175/1520-0442(2003)016<2752:hdpfot>;2   AbstractWebsite

By matching large-scale patterns in climate fields with patterns in observed station precipitation, this work explores seasonal predictability of precipitation in the contiguous United States for all seasons. Although it is shown that total seasonal precipitation and frequencies of less-than-extreme daily precipitation events can be predicted with much higher skill, the focus of this study is on frequencies of daily precipitation above the seasonal 90th percentile (P90), a variable whose skillful prediction is more challenging. Frequency of heavy daily precipitation is shown to respond to ENSO as well as to non-ENSO interannual and interdecadal variability in the North Pacific. Specification skill achieved by a statistical model based on contemporaneous SST forcing with and without an explicit dynamical atmosphere is compared and contrasted. Statistical models relating the SST forcing patterns directly to observed station precipitation are shown to perform consistently better in all seasons than hybrid (dynamical-statistical) models where the SST forcing is first translated to atmospheric circulation via three separate general circulation models and the dynamically computed circulation anomalies are statistically related to observed precipitation. Skill is summarized for all seasons, but in detail for January-February-March, when it is shown that predictable patterns are spatially robust regardless of the approach used. Predictably, much of the skill is due to ENSO. While the U. S. average skill is modest, regional skill levels can be quite high. It is also found that non-ENSO-related skill is significant, especially for the extreme Southwest and that this is due mostly to non-ENSO interannual and decadal variability in the North Pacific SST forcing. Although useful specification skill is achieved by both approaches, hybrid predictability is not pursued further in this effort. Rather, prognostic analysis is carried out with the purely statistical approach to analyze P90 predictability based on antecedent SST forcing. Skill at various lead times is investigated and it is shown that significant regional skill can be achieved at lead times of several months even in the absence of strong ENSO forcing.

Gershunov, A, Barnett TP, Cayan DR, Tubbs T, Goddard L.  2000.  Predicting and downscaling ENSO impacts on intraseasonal precipitation statistics in California: The 1997/98 event. Journal of Hydrometeorology. 1:201-210.   10.1175/1525-7541(2000)001<0201:padeio>;2   AbstractWebsite

Three long-range forecasting methods have been evaluated for prediction and downscaling of seasonal and intraseasonal precipitation statistics in California. Full-statistical, hybrid-dynamical-statistical and full-dynamical approaches have been used to forecast Fl Nino-Southern Oscillation (ENSO)-related total precipitation, daily precipitation frequency, and average intensity anomalies during the January-March season. For El Nino winters, the hybrid approach emerges as the best performer, while La Nina forecasting skill is poor. The full-statistical forecasting method features reasonable forecasting skill for both La Nina and El Nino winters. The performance of the full-dynamical approach could not be evaluated as rigorously as that of the other two forecasting schemes. Although the full-dynamical forecasting approach is expected to outperform simpler forecasting schemes in the long run, evidence is presented to conclude that, at present, the full-dynamical forecasting approach is the least viable of the three, at least in California. The authors suggest that operational forecasting of any intraseasonal temperature, precipitation, or streamflow statistic derivable from the available-records is possible now for ENSO-extreme years.