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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.

OrtizBevia, MJ, Perez-Gonzalez I, Alvarez-Garcia FJ, Gershunov A.  2010.  Nonlinear estimation of El Nino impact on the North Atlantic winter. Journal of Geophysical Research-Atmospheres. 115   10.1029/2009jd013387   AbstractWebsite

The differences in the teleconnections forced by different El Nino events (Ninos) can be partly explained by the intrinsic nonlinearity of the atmospheric response. In the present study, we segregate the responses of the North Atlantic to strong from those to moderate Ninos and compare nonlinear and linear estimates. El Nino forcing is represented by the tropical Pacific sea surface temperature anomalies, and the North Atlantic atmospheric response is represented by sea level pressure anomalies in the region. To gain insight into the evolution of El Nino teleconnections in a future climate, linear and nonlinear analyses are carried out on the corresponding data fields in the control and scenario simulations of a climate model experiment. This experiment presents, in its control version, realistic teleconnections. In the observational analysis, the nonlinear method performs only slightly better than the linear one. However, in the analysis of the interannual variability by a long control experiment of a realistic climate simulation, the nonlinear estimate improves significantly with respect to the linear one. The analysis of the corresponding scenario experiment points to an intensification of the (negative) surface pressure anomalies associated with the Ninos in the west European sector in a future climate. This feature is related to the important stratospheric anomalies in the same region, revealed by previous studies.

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.