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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.

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.

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.

Guirguis, K, Gershunov A, Schwartz R, Bennett S.  2011.  Recent warm and cold daily winter temperature extremes in the Northern Hemisphere. Geophysical Research Letters. 38   10.1029/2011gl048762   AbstractWebsite

The winters of 2009-2010 and 2010-2011 brought frigid temperatures to parts of Europe, Russia, and the U. S. We analyzed regional and Northern Hemispheric (NH) daily temperature extremes for these two consecutive winters in the historical context of the past 63 years. While some parts clearly experienced very cold temperatures, the NH was not anomalously cold. Extreme warm events were much more prevalent in both magnitude and spatial extent. Importantly, the persistent negative state of the North Atlantic Oscillation (NAO) explained the bulk of the observed cold anomalies, however the warm extremes were anomalous even accounting for the NAO and also considering the states of the Pacific Decadal Oscillation (PDO) and El Nino Southern Oscillation (ENSO). These winters' widespread and intense warm extremes together with a continuing hemispheric decline in cold snap activity was a pattern fully consistent with a continuation of the warming trend observed in recent decades. Citation: Guirguis, K., A. Gershunov, R. Schwartz, and S. Bennett (2011), Recent warm and cold daily winter temperature extremes in the Northern Hemisphere, Geophys. Res. Lett., 38, L17701, doi:10.1029/2011GL048762.

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).

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.

Alfaro, EJ, Gershunov A, Cayan D.  2006.  Prediction of summer maximum and minimum temperature over the central and western United States: The roles of soil moisture and sea surface temperature. Journal of Climate. 19:1407-1421.   10.1175/jcli3665.1   AbstractWebsite

A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June-August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90 degrees W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950-2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly. skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.

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.

Biondi, F, Gershunov A, Cayan DR.  2001.  North Pacific decadal climate variability since 1661. Journal of Climate. 14:5-10.   10.1175/1520-0442(2001)014<0005:npdcvs>;2   AbstractWebsite

Climate in the North Pacific and North American sectors has experienced interdecadal shifts during the twentieth century. A network of recently developed tree-ring chronologies for Southern and Baja California extends the instrumental record and reveals decadal-scale variability back to 1661. The Pacific decadal oscillation (PDO) is closely matched by the dominant mode of tree-ring variability that provides a preliminary view of multiannual climate fluctuations spanning the past four centuries. The reconstructed PDO index features a prominent bidecadal oscillation, whose amplitude weakened in the late 1700s to mid-1800s. A comparison with proxy records of ENSO suggests that the greatest decadal-scale oscillations in Pacific climate between 1706 and 1977 occurred around 1750, 1905, and 1947.

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   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.

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   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.  Interdecadal modulation of ENSO teleconnections. Bulletin of the American Meteorological Society. 79:2715-2725.   10.1175/1520-0477(1998)079<2715:imoet>;2   AbstractWebsite

Seasonal climate anomalies over North America exhibit rather large variability between years characterized by the same ENSO phase. This lack of consistency reduces potential statistically based ENSO-related climate predictability. The authors show that the North Pacific oscillation (NPO) exerts a modulating effect on ENSO teleconnections. Sea lever pressure (SLP) data over the North Pacific, North America, and the North Atlantic and daily rainfall records in the contiguous United States are used to demonstrate that typical ENSO signals tend to be stronger and more stable during preferred phases of the NPO. Typical El Nino patterns (e.g., low pressure over the northeastern Pacific, dry northwest, and wet southwest, etc.) are strong and consistent only during the high phase of the NPO, which is associated with an anomalously cold northwestern Pacific. The generally reversed SLP and precipitation patterns during La Nina winters are consistent only during the low NPO phase. Climatic anomalies tend to be weak and spatially incoherent during low NPO-El Nino and high NPO-La Nina winters. These results suggest that confidence in ENSO-based long-range climate forecasts for North America should reflect interdecadal climatic anomalies in the North Pacific.