Publications

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2019
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.

2018
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.

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.

2017
Polade, SD, Gershunov A, Cayan DR, Dettinger MD, Pierce DW.  2017.  Precipitation in a warming world: Assessing projected hydro-climate changes in California and other Mediterranean climate regions. Scientific Reports. 7   10.1038/s41598-017-11285-y   AbstractWebsite

In most Mediterranean climate (MedClim) regions around the world, global climate models (GCMs) consistently project drier futures. In California, however, projections of changes in annual precipitation are inconsistent. Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over each of the five MedClm regions globally and helps disentangle their causes. MedClim regions, except California, are expected to dry via decreased frequency of winter precipitation. Frequencies of extreme precipitation, however, are projected to increase over the two MedClim regions of the Northern Hemisphere where projected warming is strongest. The increase in heavy and extreme precipitation is particularly robust over California, where it is only partially offset by projected decreases in low-medium intensity precipitation. Over the Mediterranean Basin, however, losses from decreasing frequency of low-medium-intensity precipitation are projected to dominate gains from intensifying projected extreme precipitation. MedClim regions are projected to become more sub-tropical, i.e. made dryer via pole-ward expanding subtropical subsidence. California's more nuanced hydrological future reflects a precarious balance between the expanding subtropical high from the south and the south-eastward extending Aleutian low from the north-west. These dynamical mechanisms and thermodynamic moistening of the warming atmosphere result in increased horizontal water vapor transport, bolstering extreme precipitation events.

2016
Guzman-Morales, J, Gershunov A, Theiss J, Li HQ, Cayan D.  2016.  Santa Ana Winds of Southern California: Their climatology, extremes, and behavior spanning six and a half decades. Geophysical Research Letters. 43:2827-2834.   10.1002/2016gl067887   AbstractWebsite

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region, but their climate-scale behavior is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis from 1948 to 2012. Model winds are validated with anemometer observations. SAWs exhibit an organized pattern with strongest easterly winds on westward facing downwind slopes and muted magnitudes at sea and over desert lowlands. We construct hourly local and regional SAW indices and analyze elements of their behavior on daily, annual, and multidecadal timescales. SAWs occurrences peak in winter, but some of the strongest winds have occurred in fall. Finally, we observe that SAW intensity is influenced by prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system.

Grotjahn, R, Black R, Leung R, Wehner MF, Barlow M, Bosilovich M, Gershunov A, Gutowski WJ, Gyakum JR, Katz RW, Lee YY, Lim YK, Prabhat.  2016.  North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends. Climate Dynamics. 46:1151-1184.   10.1007/s00382-015-2638-6   AbstractWebsite

The objective of this paper is to review statistical methods, dynamics, modeling efforts, and trends related to temperature extremes, with a focus upon extreme events of short duration that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). The statistics, dynamics, and modeling sections of this paper are written to be autonomous and so can be read separately. Methods to define extreme events statistics and to identify and connect LSMPs to extreme temperature events are presented. Recent advances in statistical techniques connect LSMPs to extreme temperatures through appropriately defined covariates that supplement more straightforward analyses. Various LSMPs, ranging from synoptic to planetary scale structures, are associated with extreme temperature events. Current knowledge about the synoptics and the dynamical mechanisms leading to the associated LSMPs is incomplete. Systematic studies of: the physics of LSMP life cycles, comprehensive model assessment of LSMP-extreme temperature event linkages, and LSMP properties are needed. Generally, climate models capture observed properties of heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreak frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Modeling studies have identified the impact of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs to more specifically understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated. The paper concludes with unresolved issues and research questions.

Clemesha, RES, Gershunov A, Iacobellis SF, Williams AP, Cayan DR.  2016.  The northward march of summer low cloudiness along the California coast. Geophysical Research Letters. 43:1287-1295.   10.1002/2015gl067081   AbstractWebsite

A new satellite-derived low cloud retrieval reveals rich spatial texture and coherent space-time propagation in summertime California coastal low cloudiness (CLC). Throughout the region, CLC is greatest during May-September but has considerable monthly variability within this summer season. On average, June is cloudiest along the coast of southern California and northern Baja, Mexico, while July is cloudiest along northern California's coast. Over the course of the summer, the core of peak CLC migrates northward along coastal California, reaching its northernmost extent in late July/early August, then recedes while weakening. The timing and movement of the CLC climatological structure is related to the summer evolution of lower tropospheric stability and both its component parts, sea surface temperature and potential temperature at 700hPa. The roughly coincident seasonal timing of peak CLC with peak summertime temperatures translates into the strongest heat-modulating capacity of CLC along California's north coast.

2015
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.

2014
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.

2013
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.

2010
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.

2009
Favre, A, Gershunov A.  2009.  North Pacific cyclonic and anticyclonic transients in a global warming context: possible consequences for Western North American daily precipitation and temperature extremes. Climate Dynamics. 32:969-987.   10.1007/s00382-008-0417-3   AbstractWebsite

Trajectories of surface cyclones and anticyclones were constructed using an automated scheme by tracking local minima and maxima of mean daily sea level pressure data in the NCEP-NCAR reanalysis and the Centre National de Recherches M,t,orologiques coupled global climate Model (CNRM-CM3) SRES A2 integration. Mid-latitude lows and highs traveling in the North Pacific were tracked and daily frequencies were gridded. Transient activity in the CNRM-CM3 historical simulation (1950-1999) was validated against reanalysis. The GCM correctly reproduces winter trajectories as well as mean geographical distributions of cyclones and anticyclones over the North Pacific in spite of a general under-estimation of cyclones' frequency. On inter-annual time scales, frequencies of cyclones and anticyclones vary in accordance with the Aleutian Low (AL) strength. When the AL is stronger (weaker), cyclones are more (less) numerous over the central and eastern North Pacific, while anticyclones are significantly less (more) numerous over this region. The action of transient cyclones and anticyclones over the central and eastern North Pacific determines seasonal climate over the West Coast of North America, and specifically, winter weather over California. Relationships between winter cyclone/anticyclone behavior and daily precipitation/cold temperature extremes over Western North America (the West) were examined and yielded two simple indices summarizing North Pacific transient activity relevant to regional climates. These indices are strongly related to the observed inter-annual variability of daily precipitation and cold temperature extremes over the West as well as to large scale seasonally averaged near surface climate conditions (e.g., air temperature at 2 m and wind at 10 m). In fact, they represent the synoptic links that accomplish the teleconnections. Comparison of patterns derived from NCEP-NCAR and CNRM-CM3 revealed that the model reproduces links between cyclone/anticyclone frequencies over the Northeastern Pacific and extra-tropical climate conditions but is deficient in relation to tropical climate variability. The connections between these synoptic indices and Western weather are well reproduced by the model. Under advanced global warming conditions, that is, the last half of the century, the model predicts a significant reduction of cyclonic transients throughout the mid-latitude North Pacific with the exception of the far northern and northeastern domains. Anticyclonic transients respond somewhat more regionally but consistently to strong greenhouse forcing, with notably fewer anticyclones over the Okhotsk/Kamchatka sector and generally more anticyclones in the Northeastern Pacific. These modifications of synoptic weather result in regional feedbacks, that is, regional synoptic alterations of the anthropogenic warming signal around the North Pacific. In the eastern Pacific, for example, synoptic feedbacks, having to do especially with the northward shift of the eastern Pacific storm-track (responding, in turn, to a weaker equator-to-pole temperature gradient), are favorable to more anticyclonic conditions off the American mid-latitude west coast and more cyclonic conditions at higher latitudes. These circulation feedbacks further reduce the equator-to-pole temperature gradient by favoring high-latitude mean winter warming especially over a broad wedge of the Arctic north of the Bering Sea and moderating the warming along the mid-latitude west coast of north America while also reducing precipitation frequencies from California to Northern Mexio.

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.

2008
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).

2006
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.

2005
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.

2004
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.

1998
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.