Publications

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Book Chapter
Gershunov, A, Douville H.  2008.  Extensive summer hot and cold spells under current and possible future climatic conditions: Europe and North America. Climate extremes and society. ( Diaz HF, Murnane RJ, Eds.).:20., Cambridge: Cambridge University Press Abstract
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Panorska, AK, Gershunov A, Kozubowski TJ.  2007.  From diversity to volatility: probability of daily precipitation extremes. Nonlinear Dynamics in Geosciences. ( Tsonis AA, Elsner JB, Eds.).:465-484.: Springer New York   10.1007/978-0-387-34918-3_26   Abstract

A sensible stochastic model is required to correctly estimate the risk associated with daily precipitation extremes. The same requirement holds for studying high-frequency precipitation extremes in the context of climate variability and change. Results derived from probability theory were used to develop an efficient automated scheme to distinguish between heavy and exponential precipitation probability density function (PDF) tails in hundreds of daily station records spanning five decades over the North American continent. These results suggest that, at a vast majority of the stations, daily extreme precipitation probabilities do not decay exponentially, but more closely follow a power law. This means that statistical distributions traditionally used to model daily rainfall (e.g. exponential, Weibull, Gamma, lognormal) generally underestimate the probabilities of extremes. The degree of this distortion, i.e. volatility, depends on regional and seasonal climatic peculiarities. By examining geographical and seasonal patterns in extreme precipitation behavior, the authors show that the degree of volatility is determined regionally by the diversity in precipitation-producing mechanisms, or storm type diversity. Exponential tails are geographically limited to regions where precipitation falls almost exclusively from similar meteorological systems and where light probability tails are observed in all seasons. Topography plays an important role in flattening or fattening PDF tails by limiting the spatial extent of certain systems while orographically altering their precipitation amounts. Results presented here represent the first logical step towards choosing appropriate PDFs at various locations by specifying their regionally relevant family. Heavy tailed models are generally superior to those from the exponential family and can lead to more realistic estimates of extreme event probabilities, return periods, n-year events, and design limits. The correct choice of PDF is essential to safe engineering design, hazard assessment and other applications, as well as for fostering further investigations of hydrologic weather extremes and climate.

Journal Article
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.

Ralph, FM, Wilson AM, Shulgina T, Kawzenuk B, Sellars S, Rutz JJ, Lamjiri MA, Barnes EA, Gershunov A, Guan B, Nardi KM, Osborne T, Wick GA.  2019.  ARTMIP-early start comparison of atmospheric river detection tools: how many atmospheric rivers hit northern California's Russian River watershed? Climate Dynamics. 52:4973-4994.   10.1007/s00382-018-4427-5   AbstractWebsite

Many atmospheric river detection tools (ARDTs) have now been developed. However, their relative performance is not well documented. This paper compares a diverse set of ARDTs by applying them to a single location where a unique 12-year-long time-series from an atmospheric river observatory at Bodega Bay, California is available. The study quantifies the sensitivity of the diagnosed number, duration, and intensity of ARs at this location to the choice of ARDT, and to the choice of reanalysis data set. The ARDTs compared here represent a range of methods that vary in their use of different variables, fixed vs. percentile-based thresholds, geometric shape requirements, Eulerian vs. Lagrangian approaches, and reanalyses. The ARDTs were evaluated first using the datasets documented in their initial publication, which found an average annual count of 19 +/- 7. Applying the ARDTs to the same reanalysis dataset yields an average annual count of 19 +/- 4. Applying a single ARDT to three reanalyses of varying grid sizes (0.5 degrees, 1.0 degrees-2.5 degrees) showed little sensitivity to the choice of reanalysis. While the annual average AR event count varied by about a factor of two (10-25 per year) depending on the ARDT, average AR duration and maximum intensity varied by less than +/- 10%, i.e., 24 +/- 2h duration; 458 +/- 44kg m(-1) s(-1) maximum IVT. ARDTs that use a much higher threshold for integrated vapor transport were compared separately, and yielded just 1-2 ARs annually on average. Generally, ARDTs that include either more stringent geometric criteria or higher thresholds identified the fewest AR events.

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.

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.

Guirguis, K, Gershunov A, Shulgina T, Clemesha RES, Ralph FM.  2019.  Atmospheric rivers impacting Northern California and their modulation by a variable climate. Climate Dynamics. 52:6569-6583.   10.1007/s00382-018-4532-5   AbstractWebsite

Understanding the role of climate variability in modulating the behavior of land-falling atmospheric rivers (ARs) is important for seasonal and subseasonal predictability for water resource management and flood control. We examine daily activity of ARs targeting the Northern California coast over six decades using observations of synoptic-scale circulation, high-resolution precipitation, and a long-term AR detection catalog to quantify distinct types of land-falling ARs categorized by their circulation features. We demonstrate how dramatically different atmospheric states evolve into landfalling ARs along distinct pathways that are modulated by interannual (El Nino/Southern Oscillation (ENSO)and the Pacific Decadal Oscillation) and subseasonal (Arctic Oscillation, Pacific North American Pattern, Western Pacific Oscillation, and the Eastern Pacific Oscillation) modes of large-scale climate variability. Different configurations of climate variability modes are shown to favor ARs having different characteristics in terms of synoptic evolution, integrated vapor transport and landfall orientation resulting in different patterns of precipitation over the landscape. In particular, our results show that while ENSO plays an important role in modulating the synoptic evolution of ARs and their orientation at landfall, subseasonal regional climate modes, which also influence landfall orientation as well as the position of the storm track, appear to be more influential than ENSO in modulating precipitation variability in California. This could have implications for seasonal to subseasonal (S2S) forecasting. Finally, we examine AR activity over the most recent and highly anomalous winter 2016-2017 and show how the unprecedented wet conditions in Northern California were at least partly due to the persistence of ARs characterized by a southward storm track and southerly orientation, which represent the type of ARs associated with heavy rainfall in California, and which are associated with the negative phase of subseasonal regional teleconnection patterns.

Gershunov, A, Guirguis K.  2012.  California heat waves in the present and future. Geophysical Research Letters. 39   10.1029/2012gl052979   AbstractWebsite

Current and projected heat waves are examined over California and its sub-regions in observations and downscaled global climate model (GCM) simulations. California heat wave activity falls into two distinct types: (1) typically dry daytime heat waves and (2) humid nighttime-accentuated events (Type I and Type II, respectively). The four GCMs considered project Type II heat waves to intensify more with climate change than the historically characteristic Type I events, although both types are projected to increase. This trend is already clearly observed and simulated to various degrees over all sub-regions of California. Part of the intensification in heat wave activity is due directly to mean warming. However, when one considers non-stationarity in daily temperature variance, desert heat waves are expected to become progressively and relatively less intense while coastal heat waves are projected to intensify even relative to the background warming. This result generally holds for both types of heat waves across models. Given the high coastal population density and low acclimatization to heat, especially humid heat, this trend bodes ill for coastal communities, jeopardizing public health and stressing energy resources. Citation: Gershunov, A., and K. Guirguis (2012), California heat waves in the present and future, Geophys. Res. Lett., 39, L18710, doi:10.1029/2012GL052979.

Clemesha, RES, Guirguis K, Gershunov A, Small IJ, Tardy A.  2018.  California heat waves: their spatial evolution, variation, and coastal modulation by low clouds. Climate Dynamics. 50:4285-4301.   10.1007/s00382-017-3875-7   AbstractWebsite

We examine the spatial and temporal evolution of heat waves through California and consider one of the key modulating factors of summertime coastal climate-coastal low cloudiness (CLC). Heat waves are defined relative to daytime maximum temperature (T-max) anomalies after removing local seasonality and capture unseasonably warm events during May-September. California is home to several diverse climate regions and characteristics of extreme heat events are also variable throughout these regions. Heat wave events tend to be shorter, but more anomalously intense along the coast. Heat waves typically impact both coastal and inland regions, although there is more propensity towards coastally trapped events. Most heat waves with a strong impact across regions start at the coast, proceed inland, and weaken at the coast before letting up inland. Typically, the beginning of coastal heat waves are associated with a loss of CLC, followed by a strong rebound of CLC starting close to the peak in heat wave intensity. The degree to which an inland heat wave is expressed at the coast is associated with the presence of these low clouds. Inland heat waves that have very little expression at the coast tend to have CLC present and an elevated inversion base height compared with other heat waves.

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.

Westerling, AL, Gershunov A, Brown TJ, Cayan DR, Dettinger MD.  2003.  Climate and wildfire in the western United States. Bulletin of the American Meteorological Society. 84:595-+.   10.1175/bams-84-5-595   AbstractWebsite

A 21-yr gridded monthly fire-starts and acres-burned dataset from U.S. Forest Service, Bureau of Land Management, National Park Service, and Bureau of Indian Affairs fire reports recreates the seasonality and interannual variability of wildfire in the western United States. Despite pervasive human influence in western fire regimes, it is striking how strongly these data reveal a fire season responding to variations in climate. Correlating anomalous wildfire frequency and extent with the Palmer Drought Severity Index illustrates the importance of prior and accumulated precipitation anomalies for future wildfire season severity. This link to antecedent seasons' moisture conditions varies widely with differences in predominant fuel type. Furthermore, these data demonstrate that the relationship between wildfire season severity and observed moisture anomalies from antecedent seasons is strong enough to forecast fire season severity at lead times of one season to a year in advance.

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.

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.

Lavers, DA, Ralph FM, Waliser DE, Gershunov A, Dettinger MD.  2015.  Climate change intensification of horizontal water vapor transport in CMIP5. Geophysical Research Letters. 42:5617-5625.   10.1002/2015gl064672   AbstractWebsite

Global warming of the Earth's atmosphere is hypothesized to lead to an intensification of the global water cycle. To determine associated hydrological changes, most previous research has used precipitation. This study, however, investigates projected changes to global atmospheric water vapor transport (integrated vapor transport (IVT)), the key link between water source and sink regions. Using 22 global circulation models from the Climate Model Intercomparison Project Phase 5, we evaluate, globally, the mean, standard deviation, and the 95th percentiles of IVT from the historical simulations (1979-2005) and two emissions scenarios (2073-2099). Considering the more extreme emissions, multimodel mean IVT increases by 30-40% in the North Pacific and North Atlantic storm tracks and in the equatorial Pacific Ocean trade winds. An acceleration of the high-latitude IVT is also shown. Analysis of low-altitude moisture and winds suggests that these changes are mainly due to higher atmospheric water vapor content.

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.

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.

White, WB, Gershunov A, Annis J.  2008.  Climatic influences on Midwest drought during the twentieth century. Journal of Climate. 21:517-531.   10.1175/2007jcli1465.1   AbstractWebsite

The Dustbowl Era drought in the 1930s was the principal Midwest drought of the twentieth century, occurring primarily in late spring-summer [April-August (AMJJA)] when > 70% of annual rainfall normally occurred. Another major Midwest drought occurred in the 1950s but primarily in fall-early winter [September-December (SOND)] when normal rainfall was similar to 1/2 as much. Optimized canonical correlation analysis (CCA) is applied to forecast AMJJA and SOND Midwest rainfall variability in cross-validated fashion from antecedent DJF and JJA sea surface temperature (SST) variability in the surrounding oceans. These CCA models simulate (i. e., hindcast, not forecast) the Dustbowl Era drought of the 1930s and four of seven secondary AMJJA droughts (>= 3-yr duration) during the twentieth century, and the principal Midwest drought of the 1950s and one of three secondary SOND droughts. Diagnosing the model canonical correlations finds the superposition of tropical Pacific cool phases of the quasi-decadal oscillation (QDO) and interdecadal oscillation (IDO) responsible for secondary droughts in AMJJA when ENSO was weak and finds the eastern equatorial Pacific cool phase of the ENSO responsible for secondary droughts during SOND when ENSO was strong. These explain why secondary droughts in AMJJA occurred more often (nearly every decade) and were of longer duration than secondary droughts in SOND when decadal drought tendencies were usually interrupted by ENSO. These diagnostics also find the AMJJA Dustbowl Era drought in the 1930s and the principal SOND drought in the 1950s driven primarily by different phases (i. e., in quadrature) of the pentadecadal signal in the Pacific decadal oscillation (PDO).

Gershunov, A, Michaelsen J.  1996.  Climatic-scale space-time variability of tropical precipitation. Journal of Geophysical Research-Atmospheres. 101:26297-26307.   10.1029/96jd01382   AbstractWebsite

More than 15 years of monthly microwave sounding unit rainfall data over the tropical oceans are analyzed to illustrate rainfall variability on various timescales and delineate its spatial patterns. The annual and semiannual components of the seasonal cycle are modeled with first and second annual harmonics at every 2.5 degrees x 2.5 degrees grid square. Regions of highest rainfall variability tend to be characterized by a powerful annual cycle. The semiannual cycle is generally a trivial component of the seasonal cycle, except in some regions where either the mean climatological precipitation is low or where the total seasonal cycle is weak. An interesting exception, in this respect, is a band of the southeastern tropical Pacific extending immediately to the south of the eastern equatorial Pacific cold tongue. Regions of highest climatological mean rainfall are characterized by weak seasonality but strong nonseasonal variability. After seasonality is described and removed from the data, nonseasonal variability is considered via principal component analysis in the time domain. The two dominant modes together describe precipitation variability associated with the El Nino-Southern Oscillation: they outline the evolution of warm- and cold-event precipitation anomalies and contrast the intense 1982-1983 warm event with the moderate events of 1986-1987 and 1992-1993. These two modes display oscillations with predominantly quasi-biennial and similar to 5-year periods. Another coherent mode summarizes intraseasonal variability which, although inadequately resolved by the monthly average rainfall data, displays typical signs of the 40- to 50-day oscillation. All coherent modes, despite having much of their energy concentrated around rather different frequencies, show signs of interaction.

Gershunov, A, Roca R.  2004.  Coupling of latent heat flux and the greenhouse effect by large-scale tropical/subtropical dynamics diagnosed in a set of observations and model simulations. Climate Dynamics. 22:205-222.   10.1007/s00382-003-0376-7   AbstractWebsite

Coupled variability of the greenhouse effect (GH) and latent heat flux (LHF) over the tropical - subtropical oceans is described, summarized and compared in observations and a coupled ocean-atmosphere general circulation model (CGCM). Coupled seasonal and interannual modes account for much of the total variability in both GH and LHF. In both observations and model, seasonal coupled variability is locally 180degrees out-of-phase throughout the tropics. Moisture is brought into convergent/convective regions from remote source areas located partly in the opposite, non-convective hemisphere. On interannual time scales, the tropical Pacific GH in the ENSO region of largest interannual variance is 180degrees out of phase with local LHF in observations but in phase in the model. A local source of moisture is thus present in the model on interannual time scales while in observations, moisture is mostly advected from remote source regions. The latent cooling and radiative heating of the surface as manifested in the interplay of LHF and GH is an important determinant of the current climate. Moreover, the hydrodynamic processes involved in the GH-LHF interplay determine in large part the climate response to external perturbations mainly through influencing the water vapor feedback but also through their intimate connection to the hydrological cycle. The diagnostic process proposed here can be performed on other CGCMs. Similarly, it should be repeated using a number of observational latent heat flux datasets to account for the variability in the different satellite retrievals. A realistic CGCM could be used to further study these coupled dynamics in natural and anthropogenically altered climate conditions.

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.

Gershunov, A.  1998.  ENSO influence on intraseasonal extreme rainfall and temperature frequencies in the contiguous United States: Implications for long-range predictability. Journal of Climate. 11:3192-3203.   10.1175/1520-0442(1998)011<3192:eioier>2.0.co;2   AbstractWebsite

Potential ENSO-related predictability of wintertime daily extreme precipitation and temperature frequencies is investigated. This is done empirically using six decades of daily data at 168 stations distributed over the contiguous United States. ENSO sensitivity in the extreme ranges of intraseasonal precipitation and temperature probability density functions is demonstrated via a compositing technique. Potential predictability of extremes is then investigated with a simple statistical model. Given a perfect forecast of ENSO, the frequency of intraseasonal extremes is specified as the average frequency of occurrence during similar-phased ENSO winters on record. Specification skill is assessed as the cross-validated proportion of local variance explained by this method. The skill depends on varying ENSO sensitivity in different geographic regions and quantile ranges and on consistency or variability from one like-phased ENSO event to another. ENSO sensitivity also varies according to the intensity of the tropical forcing; however, not always in the expected sense. Good predictability is likely for variables and in regions displaying a strong and consistent ENSO signal. This is found in some coherent regions of the United States for various combinations of frequency variable and ENSO phase. ENSO-based predictability of heavy and extreme precipitation frequency is potentially good along the Gulf Coast, central plains, Southwest, and in the Ohio River valley for El Nino winters and in the Southwest and Florida for La Nina winters. Not all large magnitude signals translate into significant specification skill. Extreme precipitation frequency in the Southwest is a good example of this. Extreme warm temperature frequency (EWF) is potentially predictable in the southern and eastern United States during Fl Nino winters and in the Midwest during the strongest events. La Nina winters exhibit potentially very good EWF predictability in a Large area of the southern United States centered on Texas. Despite showing coherent ENSO patterns, extreme cold temperature frequency (ECF) signals are mostly weak and inconsistent, especially during strong ENSO events. Curiously, specification skill improves in the northern United States, along the West Coast and in the southeast during weaker El Nino winters. An improvement in potential ECF predictability is also observed in the Midwest during weaker La Nina winters.

Gershunov, A, Barnett TP.  1998.  ENSO influence on intraseasonal extreme rainfall and temperature frequencies in the contiguous United States: Observations and model results. Journal of Climate. 11:1575-1586.   10.1175/1520-0442(1998)011<1575:eioier>2.0.co;2   AbstractWebsite

The signature of ENSO in the wintertime frequencies of heavy precipitation and temperature extremes is derived from both observations and atmospheric general circulation model output for the contiguous United States. ENSO signals in the frequency of occurrence of heavy rainfall are found in the Southeast, Gulf Coast, central Rockies, and the general area of the Mississippi-Ohio River valleys. Strong, nonlinear signals in extreme warm temperature frequencies are found in the southern and eastern United States. Extreme cold temperature frequencies are found to be less sensitive to ENSO forcing than extreme warm temperature frequencies. Observed ENSO signals in extreme temperature frequencies are not simply manifestations of shifts in mean seasonal temperature. These signals in the wintertime frequency of extreme rainfall and temperature events appear strong enough to be useful in long-range regional statistical prediction. Comparisons of observational and model results show that the model climate is sensitive to ENSO on continental scales and provide some encouragement to modeling studies of intraseasonal sensitivity to low-frequency climatic forcing. However, large regional disagreements exist in all variables. Continental-scale El Nino signatures in intraseasonal temperature variability are not correctly modeled. Modeled signals in extreme temperature event frequencies are much more directly related to shifts in seasonal mean temperature than they are in nature.

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.

White, WB, Gershunov A, Annis JL, McKeon G, Syktus J.  2004.  Forecasting Australian drought using southern, hemisphere modes of sea-surface temperature variability. International Journal of Climatology. 24:1911-1927.   10.1002/joc.1091   AbstractWebsite

Drought of 3 to 7 years' duration has devastated the flora, fauna, and regional economies in rangeland grazing districts over eastern and central Australia every 15 to 25 years throughout the 20th century, in some cases degrading the land beyond recover. Recently, these drought and degradation episodes have been associated with a global interdecadal oscillation (IDO) of period 15 to 25 years. This IDO signal brought cooler sea-surface temperatures (SSTs) to the western extra-tropical South Pacific Ocean in association with reduced onshore transport of moisture over eastern/central Australia during the summer monsoon. Here, we utilize optimized canonical correlation analysis (CCA) to forecase principal components of summer precipitation (PCP) anomalies over Australia from the persistence of principal components that dominate spring SST anomalies across the Southern Hemisphere. These summer PCP forecasts are cross-validated with the CCA forecast model for each year independent of that year's variability. Resulting cross-validated forecasts are best over Queensland, correlating with those observed at >0.40 from 1890 through to 2001, significant at >99% confidence level. More importantly, 6 of 10 drought episodes (but only three of seven degradation episodes) observed in eastern/central Australia during the 20th century are forecast. Copyright (C) 2004 Royal Meteorological Society.