5.1: Introduction

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere—Hadley cell, Ferrell cell and Polar cell—and which determines the location of subtropical dry zones and midlatitude jet streams (Figure 5.1). These circulation cells are expected to shift poleward during warmer periods,1 ,2 ,3 ,4 which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources.5 ,6


Figure 5.1


(top) Plan and (bottom) cross-section schematic view representations of the general circulation of the atmosphere. Three main circulations exist between the equator and poles due to solar heating and Earth’s rotation: 1) Hadley cell – Low-latitude air moves toward the equator. Due to solar heating, air near the equator rises vertically and moves poleward in the upper atmosphere. 2) Ferrel cell – A midlatitude mean atmospheric circulation cell. In this cell, the air flows poleward and eastward near the surface and equatorward and westward at higher levels. 3) Polar cell – Air rises, diverges, and travels toward the poles. Once over the poles, the air sinks, forming the polar highs. At the surface, air diverges outward from the polar highs. Surface winds in the polar cell are easterly (polar easterlies). A high pressure band is located at about 30° N/S latitude, leading to dry/hot weather due to descending air motion (subtropical dry zones are indicated in orange in the schematic views). Expanding tropics (indicted by orange arrows) are associated with a poleward shift of the subtropical dry zones. A low pressure band is found at 50°–60° N/S, with rainy and stormy weather in relation to the polar jet stream bands of strong westerly wind in the upper levels of the atmosphere. (Figure source: adapted from NWS 2016177 ).

In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere–ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

On intraseasonal to interannual time scales, the climate of the United States is strongly affected by modes of atmospheric circulation variability like the North Atlantic Oscillation (NAO)/Northern Annular Mode (NAM), North Pacific Oscillation (NPO), and Pacific/North American Pattern (PNA).7 ,8 ,9 These modes are closely linked to other atmospheric circulation phenomena like blocking and quasi-stationary wave patterns and jet streams that can lead to weather and climate extremes.10 On an interannual time scale, coupled atmosphere–ocean phenomena like El Niño–Southern Oscillation (ENSO) have a prominent effect.11 On longer time scales, U.S. climate anomalies are linked to slow variations of sea surface temperature related to the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO).12 ,13 ,14

These modes of variability can affect the local-to-regional climate response to external forcing in various ways. The climate response may be altered by the forced response of these existing, recurring modes of variability.15 Further, the structure and strength of regional temperature and precipitation impacts of these recurring modes of variability may be modified due to a change in the background climate.16 Modes of internal variability of the climate system also contribute to observed decadal and multidecadal temperature and precipitation trends on local to regional scales, masking possible systematic changes due to an anthropogenic influence.17 However, there are still large uncertainties in our understanding of the impact of human-induced climate change on atmospheric circulation.4 ,18 Furthermore, the confidence in any specific projected change in ENSO variability in the 21st century remains low.19

5.2: Modes of Variability: Past and Projected Changes

5.2.1 Width of the Tropics and Global Circulation

Evidence continues to mount for an expansion of the tropics over the past several decades, with a poleward expansion of the Hadley cell and an associated poleward shift of the subtropical dry zones and storm tracks in each hemisphere.5 ,20 ,21 ,22 ,23 ,24 ,25 ,26 ,27 ,28 ,29 The rate of expansion is uncertain and depends on the metrics and data sources that are used. Recent estimates of the widening of the global tropics for the period 1979–2009 range between 1° and 3° latitude (between about 70 and 200 miles) in each hemisphere, an average trend of between approximately 0.5° and 1.0° per decade.26 While the roles of increasing greenhouse gases in both hemispheres,4 ,30 stratospheric ozone depletion in the Southern Hemisphere,31 and anthropogenic aerosols in the Northern Hemisphere32 ,33 have been implicated as contributors to the observed expansion, there is uncertainty in the relative contributions of natural and anthropogenic factors, and natural variability may currently be dominating.23 ,34 ,35

Most of the previous work on tropical expansion to date has focused on zonally averaged changes. There are only a few recent studies that diagnose regional characteristics of tropical expansion. The findings depend on analysis methods and datasets. For example, a northward expansion of the tropics in most regions of the Northern Hemisphere, including the Eastern Pacific with impact on drying in the American Southwest, is found based on diagnosing outgoing longwave radiation.36 However, other studies do not find a significant poleward expansion of the tropics over the Eastern Pacific and North America.37 ,38 Thus, while some studies associate the observed drying of the U.S. Southwest with the poleward expansion of the tropics,5 ,39 regional impacts of the observed zonally averaged changes in the width of the tropics are not understood.

Due to human-induced greenhouse gas increases, the Hadley cell is likely to widen in the future, with an accompanying poleward shift in the subtropical dry zones, midlatitude jets, and storm tracks.2 ,4 ,5 ,40 ,41 ,42 ,43 Large uncertainties remain in projected changes in non-zonal to regional circulation components and related changes in precipitation patterns.18 ,40 ,44 ,45 Uncertainties in projected changes in midlatitude jets are also related to the projected rate of arctic amplification and variations in the stratospheric polar vortex. Both factors could shift the midlatitude jet equatorward, especially in the North Atlantic region.46 ,47 ,48 ,49

5.2.2 El Niño–Southern Oscillation

El Niño–Southern Oscillation (ENSO) is a main source of climate variability, with a two- to seven-year timescale, originating from coupled ocean–atmosphere interactions in the tropical Pacific. Major ENSO events affect weather patterns over many parts of the globe through atmospheric teleconnections. ENSO strongly affects precipitation and temperature in the United States with impacts being most pronounced during the cold season (Figure 5.2).11 ,50 ,51 ,52 ,53 A cooling trend of the tropical Pacific Ocean that resembles La Niña conditions contributed to drying in southwestern North America from 1979 to 200654 and is found to explain most of the decrease in heavy daily precipitation events in the southern United States from 1979 to 2013.55


Figure 5.2


El Niño- and La Niña-related winter features over North America. Shown are typical January to March weather anomalies and atmospheric circulation during moderate to strong El Niño and La Niña conditions: (top) During El Niño, there is a tendency for a strong jet stream and storm track across the southern part of the United States. The southern tier of Alaska and the U.S. Pacific Northwest tend to be warmer than average, whereas the southern tier of United States tends to be cooler and wetter than average. (bottom) During La Niña, there is a tendency of a very wave-like jet stream flow over the United States and Canada, with colder and stormier than average conditions across the North and warmer and less stormy conditions across the South. (Figure source: adapted from Lindsey 2016178 ).

El Niño teleconnections are modulated by the location of maximum anomalous tropical Pacific sea surface temperatures (SST). Eastern Pacific (EP) El Niño events affect winter temperatures primarily over the Great Lakes, Northeast, and Southwest, while Central Pacific (CP) events influence temperatures primarily over the northwestern and southeastern United States.56 The CP El Niño also enhances the drying effect, but weakens the wetting effect, typically produced by traditional EP El Niño events on U.S. winter precipitation.57 It is not clear whether observed decadal-scale modulations of ENSO properties, including an increase in ENSO amplitude58 and an increase in frequency of CP El Niño events,59 ,60 are due to internal variability or anthropogenic forcing. Uncertainties in both the diagnosed distinct U.S. climate effects of EP and CP events and causes for the decadal scale changes result from the limited sample size of observed ENSO events in each category61 ,62 and the relatively short record of the comprehensive observations (since late 1970s) that would allow the investigation of ENSO-related coupled atmosphere–ocean feedbacks.19 Furthermore, unforced global climate model simulations show that decadal to centennial modulations of ENSO can be generated without any change in external forcing.63 A model study based on large, single-model ensembles of atmospheric and coupled atmosphere–ocean models finds that external radiative forcing resulted in an atmospheric teleconnection pattern that is independent of ENSO-like variations during the 1979–2014 period and is characterized by a hemisphere-scale increasing trend in heights.53

The representation of ENSO in climate models has improved from CMIP3 to CMIP5 models, especially in relation to ENSO amplitude.64 ,65 However, CMIP5 models still cannot capture the seasonal timing of ENSO events.66 Furthermore, they still exhibit errors in simulating key atmospheric feedbacks, and the improvement in ENSO amplitudes might therefore result from error compensations.64  Limited observational records and the nonstationarity of tropical Pacific teleconnections to North America on multidecadal time scales pose challenges for evaluating teleconnections between ENSO and U.S. climate in coupled atmosphere–ocean models.61 ,67 For a given SST forcing, however, the atmospheric component of CMIP5 models simulate the sign of the precipitation change over the southern section of North America.68

Climate projections suggest that ENSO will remain a primary mode of natural climate variability in the 21st century.19 Climate models do not agree, however, on projected changes in the intensity or spatial pattern of ENSO.19 This uncertainty is related to a model dependence of simulated changes in the zonal gradient of tropical Pacific sea surface temperature in a warming climate.19 Model studies suggest an eastward shift of ENSO-induced teleconnection patterns due to greenhouse gas-induced climate change.69 ,70 ,71 ,72 However, the impact of such a shift on ENSO-induced climate anomalies in the United States is not well understood.72 ,73

In summary, there is high confidence that, in the 21st century, ENSO will remain a main source of climate variability over the United States on seasonal to interannual timescales. There is low confidence for a specific projected change in ENSO variability.

5.2.3 Extra-tropical Modes of Variability and Phenomena


The North Atlantic Oscillation (NAO), the leading recurring mode of variability in the extratropical North Atlantic region, describes an opposing pattern of sea level pressure between the Atlantic subtropical high and the Iceland/Arctic low. Variations in the NAO are accompanied by changes in the location and intensity of the Atlantic midlatitude storm track and blocking activity that affect climate over the North Atlantic and surrounding continents. A negative NAO phase is related to anomalously cold conditions and an enhanced number of cold outbreaks in the eastern United States, while a strong positive phase of the NAO tends to be associated with above-normal temperatures in this region.7 ,74 The positive phase of the NAO is associated with increased precipitation frequency and positive daily rainfall anomalies, including extreme daily precipitation anomalies in the northeastern United States.75 ,76

The Northern Annular Mode/Arctic Oscillation (NAM/AO) is closely related to the NAO. It describes a similar out-of-phase pressure variation between mid- and high latitudes but on a hemispheric rather than regional scale.77 ,78 The time series of the NAO and NAM/AO are highly correlated, with persistent NAO and NAM/AO events being indistinguishable.79 ,80

The wintertime NAO/NAM index exhibits pronounced variability on multidecadal time scales, with an increase from the 1960s to the 1990s, a shift to a more negative phase since the 1990s due to a series of winters like 2009–2010 and 2010–2011 (which had exceptionally low index values), and a return to more positive values after 2011.30 Decadal scale temperature trends in the eastern United States, including occurrences of cold outbreaks during recent years, are linked to these changes in the NAO/NAM.81 ,82 ,83 ,84

The NAO’s influence on the ocean occurs through changes in heat content, gyre circulations, mixed layer depth, salinity, high-latitude deep water formation, and sea ice cover.7 ,85 Climate model simulations show that multidecadal variations in the NAO induce multidecadal variations in the strength of the Atlantic Meridional Overturning Circulation (AMOC) and poleward ocean heat transport in the Atlantic, extending to the Arctic, with potential impacts on recent arctic sea ice loss and Northern Hemisphere warming.85 However, other model simulations suggest that the NAO and recent changes in Northern Hemisphere climate were affected by recent variations in the AMOC,86 for which enhanced freshwater discharge from the Greenland Ice Sheet (GrIS) may have been a contributing cause.87

Climate models are widely analyzed for their ability to simulate the spatial patterns of the NAO/NAM and their relationship to temperature and precipitation anomalies over the United States.9 ,65 ,88 Climate models reproduce the broad spatial and temporal features of the NAO, although there are large differences among the individual models in the location of the NAO centers of action and their average magnitude. These differences affect the agreement between observed and simulated climate anomalies related to the NAO.9 ,65 Climate models tend to have a NAM pattern that is more annular than observed,65 ,88 resulting in a strong bias in the Pacific center of the NAM. As a result, temperature anomalies over the northwestern United States associated with the NAM in most models are of opposite sign compared to observation.88 Biases in the model representation of NAO/NAM features are linked to limited abilities of general circulation models to reproduce dynamical processes, including atmospheric blocking,89 troposphere–stratosphere coupling,90 and climatological stationary waves.90 ,91

The CMIP5 models on average simulate a progressive shift of the NAO/NAM towards the positive phase due to human-induced climate change.92 However, the spread between model simulations is larger than the projected multimodel increase,19 and there are uncertainties related to future scenarios.9  Furthermore, it is found that shifts between preferred periods of positive and negative NAO phase will continue to occur similar to those observed in the past.19 ,93 There is no consensus on the location of changes of NAO centers among the global climate models under future warming scenarios.9 Uncertainties in future projections of the NAO/NAM in some seasons are linked to model spread in projected future arctic warming46 ,47 (Ch. 11: Arctic Changes) and to how models resolve stratospheric processes.19 ,94

In summary, while it is likely that the NAO/NAM index will become slightly more positive (on average) due to increases in GHGs, there is low confidence in temperature and precipitation changes over the United States related to such variations in the NAO/NAM.


The North Pacific Oscillation (NPO) is a recurring mode of variability in the extratropical North Pacific region and is characterized by a north-south seesaw in sea level pressure. Effects of NPO on U.S. hydroclimate and marginal ice zone extent in the arctic seas have been reported.8

The NPO is linked to tropical sea surface temperature variability. Specifically, NPO contributes to the excitation of ENSO events via the “Seasonal Footprinting Mechanism”.95 ,96 In turn, warm events in the central tropical Pacific Ocean are suggested to force an NPO-like circulation pattern.97 There is low confidence in future projections of the NPO due to the small number of modeling studies as well as the finding that many climate models do not properly simulate the observed linkages between the NPO and tropical sea surface temperature variability.19 ,98


The Pacific/North American (PNA) pattern is the leading recurring mode of internal atmospheric variability over the North Pacific and the North American continent, especially during the cold season. It describes a quadripole pattern of mid-tropospheric height anomalies, with anomalies of similar sign located over the subtropical northeastern Pacific and northwestern North America and of the opposite sign centered over the Gulf of Alaska and the southeastern United States. The PNA pattern is associated with strong fluctuations in the strength and location of the East Asian jet stream. The positive phase of the PNA pattern is associated with above average temperatures over the western and northwestern United States, and below average temperatures across the south-central and southeastern United States, including an enhanced occurrence of extreme cold temperatures.9 ,99 ,100 Significant negative correlation between the PNA and winter precipitation over the Ohio River Valley has been documented.9 ,99 ,101 The PNA is related to ENSO events102 and also serves as a bridge linking ENSO and NAO variability.103

Climate models are able to reasonably represent the atmospheric circulation and climate anomalies associated with the PNA pattern. However, individual models exhibit differences compared to the observed relationship, due to displacements of the simulated PNA centers of action and offsets in their magnitudes.9 Climate models do not show consistent location changes of the PNA centers due to increases in GHGs.9 ,72 Therefore, there is low confidence for projected changes in the PNA and the association with temperature and precipitation variations over the United States.


Anomalous atmospheric flow patterns in the extratropics that remain in place for an extended period of time (for example, blocking and quasi-stationary Rossby waves)—and thus affect a region with similar weather conditions like rain or clear sky for several days to weeks—can lead to flooding, drought, heat waves, and cold waves.10 ,104 ,105 Specifically, blocking describes large-scale, persistent high pressure systems that interrupt the typical westerly flow, while planetary waves (Rossby waves) describe large-scale meandering of the atmospheric jet stream.

A persistent pattern of high pressure in the circulation off the West Coast of the United States has been associated with the recent multiyear California drought106 ,107 ,108 (Ch. 8: Droughts, Floods, and Wildfire). Blocking in the Alaskan region, which is enhanced during La Niña winters (Figure 5.2),109 is associated with higher temperatures in western Alaska but shift to lower mean and extreme surface temperatures from the Yukon southward to the southern Plains.110 The anomalously cold winters of 2009–2010 and 2010–2011 in the United States are linked to the blocked (or negative) phase of the NAO.111 Stationary Rossby wave patterns may have contributed to the North American temperature extremes during summers like 2011.112 It has been suggested that arctic amplification has already led to weakened westerly winds and hence more slowly moving and amplified wave patterns and enhanced occurrence of blocking113 ,114 (Ch. 11: Arctic Changes). While some studies suggest an observed increase in the metrics of these persistent circulation patterns,113 ,115 other studies suggest that observed changes are small compared to atmospheric internal variability.116 ,117 ,118

A decrease of blocking frequency with climate change is found in CMIP3, CMIP5, and higher-resolution models.19 ,119 ,120 Climate models robustly project a change in Northern Hemisphere winter quasi-stationary wave fields that are linked to a wetting of the North American West Coast,45 ,121 ,122 due to a strengthening of the zonal mean westerlies in the subtropical upper troposphere. However, CMIP5 models still underestimate observed blocking activity in the North Atlantic sector while they tend to overestimate activity in the North Pacific, although with a large intermodel spread.19 Most climate models also exhibit biases in the representation of relevant stationary waves.44

In summary, there is low confidence in projected changes in atmospheric blocking and wintertime quasi-stationary waves. Therefore, our confidence is low on the association between observed and projected changes in weather and climate extremes over the United States and variations in these persistent atmospheric circulation patterns.

Modes of Variability on Decadal to Multidecadal Time Scales


The Pacific Decadal Oscillation (PDO) was first introduced by Mantua et al. 1997123 as the leading empirical orthogonal function of North Pacific (20°–70°N) monthly averaged sea surface temperature anomalies.14 Interdecadal Pacific Oscillation (IPO) refers to the same phenomenon and is based on Pacific-wide sea surface temperatures. PDO/IPO lacks a characteristic timescale and represents a combination of physical processes that span the tropics and extratropics, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions.14 Consequently, PDO-related variations in temperature and precipitation in the United States are very similar to (and indeed may be caused by) variations associated with ENSO and the strength of the Aleutian low (North Pacific Index, NPI), as shown in Figure 5.3. A PDO-related temperature variation in Alaska is also apparent.124 ,125


Figure 5.3


Cold season relationship between climate indices and U.S. precipitation and temperature anomalies determined from U.S. climate division data,179

for the years 1901–2014. November–March mean U.S. precipitation anomalies correlated with (a) the Pacific Decadal Oscillation (PDO) index, (b) the El Niño–Southern Oscillation (ENSO) index, and (c) the North Pacific Index (NPI). November–March U.S. temperature anomalies correlated with (d) the PDO index, (e) the ENSO index, and (f) the NPI. United States temperature and precipitation related to the Pacific Decadal Oscillation are very similar to (and indeed may be caused by) variations associated with ENSO and the Aleutian low strength (North Pacific Index). (Figure source: Newman et al. 201614 ; © American Meteorological Society, used with permission).

The PDO does not show a long-term trend either in SST reconstructions or in the ensemble mean of historical CMIP3 and CMIP5 simulations.14 Emerging science suggests that externally forced natural and anthropogenic factors have contributed to the observed PDO-like variability. For example, a model study finds that the observed PDO phase is affected by large volcanic events and the variability in incoming solar radiation.126 Aerosols from anthropogenic sources could change the temporal variability of the North Pacific SST through modifications of the atmospheric circulation.127 ,128 Furthermore, some studies show that periods with near-zero warming trends of global mean temperature and periods of accelerated temperatures could result from the interplay between internally generated PDO/IPO-like temperature variations in the tropical Pacific Ocean and greenhouse gas-induced ocean warming.129 ,130

Future changes in the spatial and temporal characteristics of PDO/IPO are uncertain. Based on CMIP3 models, one study finds that most of these models do not exhibit significant changes,98 while another study points out that the PDO/IPO becomes weaker and more frequent by the end of the 21st century in some models.131 Furthermore, future changes in ENSO variability, which strongly contributes to the PDO/IPO,132 are also uncertain (Section 5.2.2). Therefore, there is low confidence in projected future changes in the PDO/IPO.


The North Atlantic Ocean region exhibits coherent multidecadal variability that exerts measurable impacts on regional climate for variables such as U.S. precipitation12 ,133 ,134 ,135 and Atlantic hurricane activity.13 ,136 ,137 ,138 ,139 ,140 This observed Atlantic multidecadal variability, or AMV, is generally understood to be driven by a combination of internal and external factors.12 ,141 ,142 ,143 ,144 ,145 ,146 ,147 ,148 The AMV manifests in SST variability and patterns as well as synoptic-scale variability of atmospheric conditions. The internal part of the observed AMV is often referred to as the Atlantic Multidecadal Oscillation (AMO) and is putatively driven by changes in the strength of the Atlantic Meridional Overturning Circulation (AMOC).142 ,143 ,149 ,150 It is important to understand the distinction between the AMO, which is often assumed to be natural (because of its putative relationship with natural AMOC variability), and AMV, which simply represents the observed multidecadal variability as a whole.

The relationship between observed AMV and the AMOC has recently been called into question and arguments have been made that AMV can occur in the absence of the AMOC via stochastic forcing of the ocean by coherent atmospheric circulation variability, but this is presently a topic of debate.151 ,152 ,153 ,154 Despite the ongoing debates, it is generally acknowledged that observed AMV, as a whole, represents a complex conflation of natural internal variability of the AMOC, natural red-noise stochastic forcing of the ocean by the atmosphere,146 natural external variability from volcanic events155 ,156 and mineral aerosols,157 and anthropogenic forcing from greenhouse gases and pollution aerosols.158 ,159 ,160 ,161

As also discussed in Chapter 9: Extreme Storms (in the context of Atlantic hurricanes), determining the relative contributions of each mechanism to the observed multidecadal variability in the Atlantic is presently an active area of research and debate, and no consensus has yet been reached.146 ,161 ,162 ,163 ,164 ,165 ,166 Still, despite the level of disagreement about the relative magnitude of human influences (particularly whether natural or anthropogenic factors are dominating), there is broad agreement in the literature of the past decade or so that human factors have had a measurable impact on the observed AMV. Furthermore, the AMO, as measured by indices constructed from environmental data (e.g., Enfield et al. 200112 ), is generally based on detrended SST data and is then, by construction, segregated from the century-scale linear SST trends that are likely forced by increasing greenhouse gas concentrations. In particular, removal of a linear trend is not expected to account for all of the variability forced by changes in sulfate aerosol concentrations that have occurred over the past century. In this case, increasing sulfate aerosols are argued to cause cooling of Atlantic SST, thus offsetting the warming caused by increasing greenhouse gas concentration. After the Clean Air Act and Amendments of the 1970s, however, a steady reduction of sulfate aerosols is argued to have caused SST warming that compounds the warming from the ongoing increases in greenhouse gas concentrations.160 ,161 This combination of greenhouse gas and sulfate aerosol forcing, by itself, can lead to Atlantic multidecadal SST variability that would not be removed by removing a linear trend.155

In summary, it is unclear what the statistically derived AMO indices represent, and it is not readily supportable to treat AMO index variability as tacitly representing natural variability, nor is it clear that the observed AMV is truly oscillatory in nature.167 There is a physical basis for treating the AMOC as oscillatory (via thermohaline circulation arguments),168 but there is no expectation of true oscillatory behavior in the hypothesized external forcing agents for the remaining variability. Detrending the SST data used to construct the AMO indices may partially remove the century-scale trends forced by increasing greenhouse gas concentrations, but it is not adequate for removing multidecadal variability forced by aerosol concentration variability. There is evidence that natural AMOC variability has been occurring for hundreds of years,149 ,169 ,170 ,171 ,172 and this has apparently played some role in the observed AMV as a whole, but a growing body of evidence shows that external factors, both natural and anthropogenic, have played a substantial additional role in the past century.

5.3: Quantifying the Role of Internal Variability on Past and Future U.S. Climate Trends

The role of internal variability in masking trends is substantially increased on regional and local scales relative to the global scale, and in the extratropics relative to the tropics (Ch. 4: Projections). Approaches have been developed to better quantify the externally forced and internally driven contributions to observed and future climate trends and variability and further separate these contributions into thermodynamically and dynamically driven factors.17 Specifically, large “initial condition” climate model ensembles with 30 ensemble members and more93 ,173 ,174 and long control runs175 have been shown to be useful tools to characterize uncertainties in climate change projections at local/regional scales.

North American temperature and precipitation trends on timescales of up to a few decades are strongly affected by intrinsic atmospheric circulation variability.17 ,173 For example, it is estimated that internal circulation trends account for approximately one-third of the observed wintertime warming over North America during the past 50 years. In a few areas, such as the central Rocky Mountains and far western Alaska, internal dynamics have offset the warming trend by 10%–30%.17 Natural climate variability superimposed upon forced climate change will result in a large range of possible trends for surface air temperature and precipitation in the United States over the next 50 years (Figure 5.4).173


Figure 5.4


(left) Total 2010–2060 winter trends decomposed into (center) internal and (right) forced components for two contrasting CCSM3 ensemble members (runs 29 and 6) for (a) surface air temperature [color shading; °F/(51 years)] and sea level pressure (SLP; contours) and (b) precipitation [color shading; inches per day/(51 years)] and SLP (contours). SLP contour interval is 1 hPa/(51 years), with solid (dashed) contours for positive (negative) values; the zero contour is thickened. The same climate model (CCSM3) simulates a large range of possible trends in North American climate over the 2010–2060 period because of the influence of internal climate variability superposed upon forced climate trends. (Figure source: adapted from Deser et al. 2014;173 © American Meteorological Society, used with permission).

Climate models are evaluated with respect to their proper simulation of internal decadal variability. Comparing observed and simulated variability estimates at timescales longer than 10 years suggest that models tend to overestimate the internal variability in the northern extratropics, including over the continental United States, but underestimate it over much of the tropics and subtropical ocean regions.93 ,176 Such biases affect signal-to-noise estimates of regional scale climate change response and thus assessment of internally driven contributions to regional/local trends.


  • Adam, O., T. Schneider, and N. Harnik, 2014: Role of changes in mean temperatures versus temperature gradients in the recent widening of the Hadley circulation. Journal of Climate, 27, 7450–7461, doi:10.1175/JCLI-D-14-00140.1.
  • Alexander, M. A., D. J. Vimont, P. Chang, and J. D. Scott, 2010: The impact of extratropical atmospheric variability on ENSO: Testing the seasonal footprinting mechanism using coupled model experiments. Journal of Climate, 23, 2885–2901, doi:10.1175/2010jcli3205.1.
  • Allen, R. J., J. R. Norris, and M. Kovilakam, 2014: Influence of anthropogenic aerosols and the Pacific Decadal Oscillation on tropical belt width. Nature Geoscience, 7, 270–274, doi:10.1038/ngeo2091.
  • Allen, R. J., S. C. Sherwood, J. R. Norris, and C. S. Zender, 2012: Recent Northern Hemisphere tropical expansion primarily driven by black carbon and tropospheric ozone. Nature, 485, 350–354, doi:10.1038/nature11097.
  • Archambault, H. M., L. F. Bosart, D. Keyser, and A. R. Aiyyer, 2008: Influence of large-scale flow regimes on cool-season precipitation in the northeastern United States. Monthly Weather Review, 136, 2945–2963, doi:10.1175/2007MWR2308.1.
  • Barnes, E. A., 2013: Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes. Geophysical Research Letters, 40, 4734–4739, doi:10.1002/grl.50880.
  • Barnes, E. A., E. Dunn-Sigouin, G. Masato, and T. Woollings, 2014: Exploring recent trends in Northern Hemisphere blocking. Geophysical Research Letters, 41, 638–644, doi:10.1002/2013GL058745.
  • Barnes, E. A., and L. M. Polvani, 2015: CMIP5 projections of Arctic amplification, of the North American/North Atlantic circulation, and of their relationship. Journal of Climate, 28, 5254–5271, doi:10.1175/JCLI-D-14-00589.1.
  • Barnes, E. A., and L. Polvani, 2013: Response of the midlatitude jets, and of their variability, to increased greenhouse gases in the CMIP5 models. Journal of Climate, 26, 7117–7135, doi:10.1175/JCLI-D-12-00536.1.
  • Bellenger, H., E. Guilyardi, J. Leloup, M. Lengaigne, and J. Vialard, 2014: ENSO representation in climate models: From CMIP3 to CMIP5. Climate Dynamics, 42, 1999–2018, doi:10.1007/s00382-013-1783-z.
  • Bindoff, N. L., P. A. Stott, K. M. AchutaRao, M. R. Allen, N. Gillett, D. Gutzler, K. Hansingo, G. Hegerl, Y. Hu, S. Jain, I. I. Mokhov, J. Overland, J. Perlwitz, R. Sebbari, and X. Zhang, 2013: Detection and attribution of climate change: From global to regional. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley, Eds., Cambridge University Press, 867–952. URL
  • Birner, T., S. M. Davis, and Dian J. Seidel, 2014: The changing width of Earth’s tropical belt. Physcis Today, 67, 38–44, doi:10.1063/PT.3.2620.
  • Boo, K.-O., B. B. B. Booth, Y.-H. Byun, J. Lee, C. Cho, S. Shim, and K.-T. Kim, 2015: Influence of aerosols in multidecadal SST variability simulations over the North Pacific. Journal of Geophysical Research Atmospheres, 120, 517–531, doi:10.1002/2014JD021933.
  • Booth, B. B. B., N. J. Dunstone, P. R. Halloran, T. Andrews, and N. Bellouin, 2012: Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability. Nature, 484, 228–232, doi:10.1038/nature10946.
  • Brandefelt, J., and H. Körnich, 2008: Northern Hemisphere stationary waves in future climate projections. Journal of Climate, 21, 6341–6353, doi:10.1175/2008JCLI2373.1.
  • Brönnimann, S., A. M. Fischer, E. Rozanov, P. Poli, G. P. Compo, and P. D. Sardeshmukh, 2015: Southward shift of the northern tropical belt from 1945 to 1980. Nature Geoscience, 8, 969–974, doi:10.1038/ngeo2568.
  • Canty, T., N. R. Mascioli, M. D. Smarte, and R. J. Salawitch, 2013: An empirical model of global climate – Part 1: A critical evaluation of volcanic cooling. Atmospheric Chemistry and Physics, 13, 3997–4031, doi:10.5194/acp-13-3997-2013.
  • Capotondi, A., A. T. Wittenberg, M. Newman, E. D. Lorenzo, J.-Y. Yu, P. Braconnot, J. Cole, B. Dewitte, B. Giese, E. Guilyardi, F.-F. Jin, K. Karnauskas, B. Kirtman, T. Lee, N. Schneider, Y. Xue, and S.-W. Yeh, 2015: Understanding ENSO diversity. Bulletin of the American Meteorological Society, 96 (12), 921–938, doi:10.1175/BAMS-D-13-00117.1.
  • Caron, L.-P., M. Boudreault, and C. L. Bruyère, 2015: Changes in large-scale controls of Atlantic tropical cyclone activity with the phases of the Atlantic Multidecadal Oscillation. Climate Dynamics, 44, 1801–1821, doi:10.1007/s00382-014-2186-5.
  • Carrera, M. L., R. W. Higgins, and V. E. Kousky, 2004: Downstream weather impacts associated with atmospheric blocking over the northeast Pacific. Journal of Climate, 17, 4823–4839, doi:10.1175/JCLI-3237.1.
  • Carslaw, K. S., L. A. Lee, C. L. Reddington, K. J. Pringle, A. Rap, P. M. Forster, G. W. Mann, D. V. Spracklen, M. T. Woodhouse, L. A. Regayre, and J. R. Pierce, 2013: Large contribution of natural aerosols to uncertainty in indirect forcing. Nature, 503, 67–71, doi:10.1038/nature12674.
  • Cattiaux, J., and C. Cassou, 2013: Opposite CMIP3/CMIP5 trends in the wintertime Northern Annular Mode explained by combined local sea ice and remote tropical influences. Geophysical Research Letters, 40, 3682–3687, doi:10.1002/grl.50643.
  • Chen, S., K. Wei, W. Chen, and L. Song, 2014: Regional changes in the annual mean Hadley circulation in recent decades. Journal of Geophysical Research Atmospheres, 119, 7815–7832, doi:10.1002/2014JD021540.
  • Christensen, J. H., K. Krishna Kumar, E. Aldrian, S.-I. An, I. F. A. Cavalcanti, M. de Castro, W. Dong, P. Goswami, A. Hall, J. K. Kanyanga, A. Kitoh, J. Kossin, N.-C. Lau, J. Renwick, D. B. Stephenson, S.-P. Xie, and T. Zhou, 2013: Climate phenomena and their relevance for future regional climate change. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley, Eds., Cambridge University Press, 1217–1308. URL
  • Chylek, P., C. K. Folland, H. A. Dijkstra, G. Lesins, and M. K. Dubey, 2011: Ice-core data evidence for a prominent near 20 year time-scale of the Atlantic Multidecadal Oscillation. Geophysical Research Letters, 38, L13704, doi:10.1029/2011GL047501.
  • Chylek, P., and G. Lesins, 2008: Multidecadal variability of Atlantic hurricane activity: 1851–2007. Journal of Geophysical Research, 113, D22106, doi:10.1029/2008JD010036.
  • Clement, A., K. Bellomo, L. N. Murphy, M. A. Cane, T. Mauritsen, G. Rädel, and B. Stevens, 2015: The Atlantic Multidecadal Oscillation without a role for ocean circulation. Science, 350, 320–324, doi:10.1126/science.aab3980.
  • Clement, A., M. A. Cane, L. N. Murphy, K. Bellomo, T. Mauritsen, and B. Stevens, 2016: Response to Comment on “The Atlantic Multidecadal Oscillation without a role for ocean circulation.” Science, 352, 1527–1527, doi:10.1126/science.aaf2575.
  • Coats, S., J. E. Smerdon, B. I. Cook, and R. Seager, 2013: Stationarity of the tropical pacific teleconnection to North America in CMIP5/PMIP3 model simulations. Geophysical Research Letters, 40, 4927–4932, doi:10.1002/grl.50938.
  • Cohen, J., and M. Barlow, 2005: The NAO, the AO, and global warming: How closely related? Journal of Climate, 18, 4498–4513, doi:10.1175/jcli3530.1.
  • Coleman, J. S. M., and J. C. Rogers, 2003: Ohio River valley winter moisture conditions associated with the Pacific–North American teleconnection pattern. Journal of Climate, 16, 969–981, doi:10.1175/1520-0442(2003)016<0969:ORVWMC>2.0.CO;2.
  • Collins, M., R. Knutti, J. Arblaster, J.-L. Dufresne, T. Fichefet, P. Friedlingstein, X. Gao, W. J. Gutowski, T. Johns, G. Krinner, M. Shongwe, C. Tebaldi, A. J. Weaver, and M. Wehner, 2013: Long-term climate change: Projections, commitments and irreversibility. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley, Eds., Cambridge University Press, 1029–1136. URL
  • Davini, P., and C. Cagnazzo, 2014: On the misinterpretation of the North Atlantic Oscillation in CMIP5 models. Climate Dynamics, 43, 1497–1511, doi:10.1007/s00382-013-1970-y.
  • Davis, N. A., and T. Birner, 2013: Seasonal to multidecadal variability of the width of the tropical belt. Journal of Geophysical Research Atmospheres, 118, 7773–7787, doi:10.1002/jgrd.50610.
  • Delworth, L. T., and E. M. Mann, 2000: Observed and simulated multidecadal variability in the Northern Hemisphere. Climate Dynamics, 16, 661–676, doi:10.1007/s003820000075.
  • Delworth, T. L., F. Zeng, G. A. Vecchi, X. Yang, L. Zhang, and R. Zhang, 2016: The North Atlantic Oscillation as a driver of rapid climate change in the Northern Hemisphere. Nature Geoscience, 9, 509–512, doi:10.1038/ngeo2738.
  • Delworth, T. L., F. Zeng, L. Zhang, R. Zhang, G. A. Vecchi, and X. Yang, 2017: The central role of ocean dynamics in connecting the North Atlantic Oscillation to the extratropical component of the Atlantic Multidecadal Oscillation. Journal of Climate, 30, 3789–3805, doi:10.1175/jcli-d-16-0358.1.
  • Deser, C., 2000: On the teleconnectivity of the “Arctic Oscillation.” Geophysical Research Letters, 27, 779–782, doi:10.1029/1999GL010945.
  • Deser, C., A. Phillips, V. Bourdette, and H. Teng, 2012: Uncertainty in climate change projections: The role of internal variability. Climate Dynamics, 38, 527–546, doi:10.1007/s00382-010-0977-x.
  • Deser, C., A. S. Phillips, M. A. Alexander, and B. V. Smoliak, 2014: Projecting North American climate over the next 50 years: Uncertainty due to internal variability. Journal of Climate, 27, 2271–2296, doi:10.1175/JCLI-D-13-00451.1.
  • Deser, C., I. R. Simpson, K. A. McKinnon, and A. S. Phillips, 2017: The Northern Hemisphere extratropical atmospheric circulation response to ENSO: How well do we know it and how do we evaluate models accordingly? Journal of Climate, 30, 5059–5082, doi:10.1175/jcli-d-16-0844.1.
  • Deser, C., L. Terray, and A. S. Phillips, 2016: Forced and internal components of winter air temperature trends over North America during the past 50 years: Mechanisms and implications. Journal of Climate, 29, 2237–2258, doi:10.1175/JCLI-D-15-0304.1.
  • Di Lorenzo, E., K. M. Cobb, J. C. Furtado, N. Schneider, B. T. Anderson, A. Bracco, M. A. Alexander, and D. J. Vimont, 2010: Central Pacific El Niño and decadal climate change in the North Pacific Ocean. Nature Geoscience, 3, 762–765, doi:10.1038/ngeo984.
  • Dima, M., and G. Lohmann, 2007: A hemispheric mechanism for the Atlantic Multidecadal Oscillation. Journal of Climate, 20, 2706–2719, doi:10.1175/jcli4174.1.
  • Dunstone, N. J., D. M. Smith, B. B. B. Booth, L. Hermanson, and R. Eade, 2013: Anthropogenic aerosol forcing of Atlantic tropical storms. Nature Geoscience, 6, 534–539, doi:10.1038/ngeo1854.
  • Durkee, J. D., J. D. Frye, C. M. Fuhrmann, M. C. Lacke, H. G. Jeong, and T. L. Mote, 2008: Effects of the North Atlantic Oscillation on precipitation-type frequency and distribution in the eastern United States. Theoretical and Applied Climatology, 94, 51–65, doi:10.1007/s00704-007-0345-x.
  • Enfield, D. B., A. M. Mestas-Nuñez, and P. J. Trimble, 2001: The Atlantic Multidecadal Oscillation and its relation to rainfall and river flows in the continental U.S. Geophysical Research Letters, 28, 2077–2080, doi:10.1029/2000GL012745.
  • Evan, A. T., 2012: Atlantic hurricane activity following two major volcanic eruptions. Journal of Geophysical Research, 117, D06101, doi:10.1029/2011JD016716.
  • Evan, A. T., D. J. Vimont, A. K. Heidinger, J. P. Kossin, and R. Bennartz, 2009: The role of aerosols in the evolution of tropical North Atlantic Ocean temperature anomalies. Science, 324, 778–781, doi:10.1126/science.1167404.
  • Feldstein, S. B., and C. Franzke, 2006: Are the North Atlantic Oscillation and the Northern Annular Mode distinguishable? Journal of the Atmospheric Sciences, 63, 2915–2930, doi:10.1175/JAS3798.1.
  • Feng, S., Q. Hu, and R. J. Oglesby, 2011: Influence of Atlantic sea surface temperatures on persistent drought in North America. Climate Dynamics, 37, 569–586, doi:10.1007/s00382-010-0835-x.
  • Feng, S., and Q. Fu, 2013: Expansion of global drylands under a warming climate. Atmospheric Chemistry and Physics, 13, 10081–10094, doi:10.5194/acp-13-10081-2013.
  • Flato, G., J. Marotzke, B. Abiodun, P. Braconnot, S. C. Chou, W. Collins, P. Cox, F. Driouech, S. Emori, V. Eyring, C. Forest, P. Gleckler, E. Guilyardi, C. Jakob, V. Kattsov, C. Reason, and M. Rummukainen, 2013: Evaluation of climate models. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley, Eds., Cambridge University Press, 741–866. URL
  • Francis, J. A., S. J. Vavrus, and J. Cohen, 2017: Amplified Arctic warming and mid-latitude weather:  Emerging connections. Wiley Interdesciplinary Review: Climate Change, 8, e474, doi:10.1002/wcc.474.
  • Francis, J. A., and S. J. Vavrus, 2012: Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophysical Research Letters, 39, L06801, doi:10.1029/2012GL051000.
  • Frankcombe, L. M., A. von der Heydt, and H. A. Dijkstra, 2010: North Atlantic multidecadal climate variability: An investigation of dominant time scales and processes. Journal of Climate, 23, 3626–3638, doi:10.1175/2010jcli3471.1.
  • Frierson, D. M. W., J. Lu, and G. Chen, 2007: Width of the Hadley cell in simple and comprehensive general circulation models. Geophysical Research Letters, 34, L18804, doi:10.1029/2007GL031115.
  • Furtado, J. C., E. D. Lorenzo, N. Schneider, and N. A. Bond, 2011: North Pacific decadal variability and climate change in the IPCC AR4 models. Journal of Climate, 24, 3049–3067, doi:10.1175/2010JCLI3584.1.
  • Garfinkel, C. I., D. W. Waugh, and L. M. Polvani, 2015: Recent Hadley cell expansion: The role of internal atmospheric variability in reconciling modeled and observed trends. Geophysical Research Letters, 42, 10,824–10,831, doi:10.1002/2015GL066942.
  • Garfinkel, C. I., M. M. Hurwitz, D. W. Waugh, and A. H. Butler, 2013: Are the teleconnections of Central Pacific and Eastern Pacific El Niño distinct in boreal wintertime? Climate Dynamics, 41, 1835–1852, doi:10.1007/s00382-012-1570-2.
  • Gillett, N. P., and J. C. Fyfe, 2013: Annular mode changes in the CMIP5 simulations. Geophysical Research Letters, 40, 1189–1193, doi:10.1002/grl.50249.
  • Goldenberg, S. B., C. W. Landsea, A. M. Mestas-Nuñez, and W. M. Gray, 2001: The recent increase in Atlantic hurricane activity: Causes and implications. Science, 293, 474–479, doi:10.1126/science.1060040.
  • Gong, H., L. Wang, W. Chen, X. Chen, and D. Nath, 2017: Biases of the wintertime Arctic Oscillation in CMIP5 models. Environmental Research Letters, 12, 014001, doi:10.1088/1748-9326/12/1/014001.
  • Gray, S. T., L. J. Graumlich, J. L. Betancourt, and G. T. Pederson, 2004: A tree-ring based reconstruction of the Atlantic Multidecadal Oscillation since 1567 A.D. Geophysical Research Letters, 31, L12205, doi:10.1029/2004GL019932.
  • Gray, W. M., J. D. Sheaffer, and C. W. Landsea, 1997: Climate trends associated with multidecadal variability of Atlantic hurricane activity. H.F. Diaz and R.S. Pulwarty, Eds., Springer, 15–53.
  • Grotjahn, R., R. Black, R. Leung, M. F. Wehner, M. Barlow, M. Bosilovich, A. Gershunov, W. J. Gutowski, J. R. Gyakum, R. W. Katz, Y.-Y. Lee, Y.-K. Lim, and 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, doi:10.1007/s00382-015-2638-6.
  • Guirguis, K., A. Gershunov, R. Schwartz, and S. Bennett, 2011: Recent warm and cold daily winter temperature extremes in the Northern Hemisphere. Geophysical Research Letters, 38, L17701, doi:10.1029/2011GL048762.
  • Haarsma, R. J., and F. Selten, 2012: Anthropogenic changes in the Walker circulation and their impact on the extra-tropical planetary wave structure in the Northern Hemisphere. Climate Dynamics, 39, 1781–1799, doi:10.1007/s00382-012-1308-1.
  • Halpert, M. S., and C. F. Ropelewski, 1992: Surface temperature patterns associated with the Southern Oscillation. Journal of Climate, 5, 577–593, doi:10.1175/1520-0442(1992)005<0577:STPAWT>2.0.CO;2.
  • Hanna, E., T. E. Cropper, R. J. Hall, and J. Cappelen, 2016: Greenland blocking index 1851–2015: A regional climate change signal. International Journal of Climatology, 36, 4847–4861, doi:10.1002/joc.4673.
  • Hartmann, B., and G. Wendler, 2005: The significance of the 1976 Pacific climate shift in the climatology of Alaska. Journal of Climate, 18, 4824–4839, doi:10.1175/JCLI3532.1.
  • Hartmann, D. L., A. M. G. Klein Tank, M. Rusticucci, L. V. Alexander, S. Brönnimann, Y. Charabi, F. J. Dentener, E. J. Dlugokencky, D. R. Easterling, A. Kaplan, B. J. Soden, P. W. Thorne, M. Wild, and P. M. Zhai, 2013: Observations: Atmosphere and surface. T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley, Eds., Cambridge University Press, 159–254. URL
  • Hoerling, M. P., A. Kumar, and T. Xu, 2001: Robustness of the nonlinear climate response to ENSO’s extreme phases. Journal of Climate, 14, 1277–1293, doi:10.1175/1520-0442(2001)014<1277:ROTNCR>2.0.CO;2.
  • Hoerling, M., J. Eischeid, J. Perlwitz, X.-W. Quan, K. Wolter, and L. Cheng, 2016: Characterizing recent trends in U.S. heavy precipitation. Journal of Climate, 29, 2313–2332, doi:10.1175/jcli-d-15-0441.1.
  • Hoerling, M., J. Eischeid, and J. Perlwitz, 2010: Regional precipitation trends: Distinguishing natural variability from anthropogenic forcing. Journal of Climate, 23, 2131–2145, doi:10.1175/2009jcli3420.1.
  • Hoskins, B., and T. Woollings, 2015: Persistent extratropical regimes and climate extremes. Current Climate Change Reports, 1, 115–124, doi:10.1007/s40641-015-0020-8.
  • Hurrell, J. W., 1995: Decadal trends in the North Atlantic oscillation: Regional temperatures and precipitation. Science, 269, 676–679, doi:10.1126/science.269.5224.676.
  • Hurrell, J. W., and C. Deser, 2009: North Atlantic climate variability: The role of the North Atlantic oscillation. Journal of Marine Systems, 78, 28–41, doi:10.1016/j.jmarsys.2008.11.026.
  • Karnauskas, K. B., and C. C. Ummenhofer, 2014: On the dynamics of the Hadley circulation and subtropical drying. Climate Dynamics, 42, 2259–2269, doi:10.1007/s00382-014-2129-1.
  • Karpechko, A. Y., and E. Manzini, 2012: Stratospheric influence on tropospheric climate change in the Northern Hemisphere. Journal of Geophysical Research, 117, D05133, doi:10.1029/2011JD017036.
  • Kavvada, A., A. Ruiz-Barradas, and S. Nigam, 2013: AMO’s structure and climate footprint in observations and IPCC AR5 climate simulations. Climate Dynamics, 41, 1345–1364, doi:10.1007/s00382-013-1712-1.
  • Kennedy, D., T. Parker, T. Woollings, B. Harvey, and L. Shaffrey, 2016: The response of high-impact blocking weather systems to climate change. Geophysical Research Letters, 43, 7250–7258, doi:10.1002/2016GL069725.
  • Kiladis, G. N., and H. F. Diaz, 1989: Global climatic anomalies associated with extremes in the Southern Oscillation. Journal of Climate, 2, 1069–1090, doi:10.1175/1520-0442(1989)002<1069:GCAAWE>2.0.CO;2.
  • Knight, J. R., C. K. Folland, and A. A. Scaife, 2006: Climate impacts of the Atlantic Multidecadal Oscillation. Geophysical Research Letters, 33, L17706, doi:10.1029/2006GL026242.
  • Knudsen, M. F., B. H. Jacobsen, M.-S. Seidenkrantz, and J. Olsen, 2014: Evidence for external forcing of the Atlantic Multidecadal Oscillation since termination of the Little Ice Age. Nature Communications, 5, 3323, doi:10.1038/ncomms4323.
  • Knutson, T. R., F. Zeng, and A. T. Wittenberg, 2013: Multimodel assessment of regional surface temperature trends: CMIP3 and CMIP5 twentieth-century simulations. Journal of Climate, 26, 8709–8743, doi:10.1175/JCLI-D-12-00567.1.
  • Kossin, J. P., 2017: Hurricane intensification along U. S. coast suppressed during active hurricane periods. Nature, 541, 390–393, doi:10.1038/nature20783.
  • Kovilakam, M., and S. Mahajan, 2015: Black carbon aerosol-induced Northern Hemisphere tropical expansion. Geophysical Research Letters, 42, 4964–4972, doi:10.1002/2015GL064559.
  • Kug, J.-S., S.-I. An, Y.-G. Ham, and I.-S. Kang, 2010: Changes in El Niño and La Niña teleconnections over North Pacific–America in the global warming simulations. Theoretical and Applied Climatology, 100, 275–282, doi:10.1007/s00704-009-0183-0.
  • Landsea, C. W., R. A. Pielke Jr., A. M. Mestas-Nuñez, and J. A. Knaff, 1999: Atlantic basin hurricanes: Indices of climatic changes. Climatic Change, 42, 89–129, doi:10.1023/a:1005416332322.
  • Langenbrunner, B., and J. D. Neelin, 2013: Analyzing ENSO teleconnections in CMIP models as a measure of model fidelity in simulating precipitation. Journal of Climate, 26, 4431–4446, doi:10.1175/jcli-d-12-00542.1.
  • Lapp, S. L., J.-M. St. Jacques, E. M. Barrow, and D. J. Sauchyn, 2012: GCM projections for the Pacific Decadal Oscillation under greenhouse forcing for the early 21st century. International Journal of Climatology, 32, 1423–1442, doi:10.1002/joc.2364.
  • Leathers, D. J., B. Yarnal, and M. A. Palecki, 1991: The Pacific/North American teleconnection pattern and United States climate. Part I: Regional temperature and precipitation associations. Journal of Climate, 4, 517–528, doi:10.1175/1520-0442(1991)004<0517:TPATPA>2.0.CO;2.
  • Lee, T., and M. J. McPhaden, 2010: Increasing intensity of El Niño in the central-equatorial Pacific. Geophysical Research Letters, 37, L14603, doi:10.1029/2010GL044007.
  • Lee, Y.-Y., and R. X. Black, 2013: Boreal winter low-frequency variability in CMIP5 models. Journal of Geophysical Research Atmospheres, 118, 6891–6904, doi:10.1002/jgrd.50493.
  • Li, J., S.-P. Xie, E. R. Cook, G. Huang, R. D’Arrigo, F. Liu, J. Ma, and X.-T. Zheng, 2011: Interdecadal modulation of El Niño amplitude during the past millennium. Nature Climate Change, 1, 114–118, doi:10.1038/nclimate1086.
  • Li, Y., and N.-C. Lau, 2012: Impact of ENSO on the atmospheric variability over the North Atlantic in late winter—Role of transient eddies. Journal of Climate, 25, 320–342, doi:10.1175/JCLI-D-11-00037.1.
  • Lindsey, R., 2016: How El Niño and La Niña affect the winter jet stream and U.S. climate. Climate.gov. URL
  • Linkin, M. E., and S. Nigam, 2008: The North Pacific Oscillation–West Pacific teleconnection pattern: Mature-phase structure and winter impacts. Journal of Climate, 21, 1979–1997, doi:10.1175/2007JCLI2048.1.
  • Loikith, P. C., and A. J. Broccoli, 2012: Characteristics of observed atmospheric circulation patterns associated with temperature extremes over North America. Journal of Climate, 25, 7266–7281, doi:10.1175/JCLI-D-11-00709.1.
  • Lucas, C., B. Timbal, and H. Nguyen, 2014: The expanding tropics: A critical assessment of the observational and modeling studies. Wiley Interdisciplinary Reviews: Climate Change, 5, 89–112, doi:10.1002/wcc.251.
  • Lucas, C., and H. Nguyen, 2015: Regional characteristics of tropical expansion and the role of climate variability. Journal of Geophysical Research Atmospheres, 120, 6809–6824, doi:10.1002/2015JD023130.
  • Mann, M. E., B. A. Steinman, and S. K. Miller, 2014: On forced temperature changes, internal variability, and the AMO. Geophysical Research Letters, 41, 3211–3219, doi:10.1002/2014GL059233.
  • Mann, M. E., J. D. Woodruff, J. P. Donnelly, and Z. Zhang, 2009: Atlantic hurricanes and climate over the past 1,500 years. Nature, 460, 880–883, doi:10.1038/nature08219.
  • Mann, M. E., and K. A. Emanuel, 2006: Atlantic hurricane trends linked to climate change. Eos, Transactions, American Geophysical Union, 87, 233–244, doi:10.1029/2006EO240001.
  • Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C. Francis, 1997: A Pacific interdecadal climate oscillation with impacts on salmon production. Bulletin of the American Meteorological Society, 78, 1069–1080, doi:10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2.
  • Manzini, E. et al., 2014: Northern winter climate change: Assessment of uncertainty in CMIP5 projections related to stratosphere-troposphere coupling. Journal of Geophysical Research Atmospheres, 119, 7979–7998, doi:10.1002/2013JD021403.
  • Mbengue, C., and T. Schneider, 2017: Storm-track shifts under climate change: Toward a mechanistic understanding using baroclinic mean available potential energy. Journal of the Atmospheric Sciences, 74, 93–110, doi:10.1175/jas-d-15-0267.1.
  • McAfee, S. A., 2014: Consistency and the lack thereof in Pacific Decadal Oscillation impacts on North American winter climate. Journal of Climate, 27, 7410–7431, doi:10.1175/JCLI-D-14-00143.1.
  • Meehl, G. A., A. Hu, B. D. Santer, and S.-P. Xie, 2016: Contribution of the Interdecadal Pacific Oscillation to twentieth-century global surface temperature trends. Nature Climate Change, 6, 1005–1008, doi:10.1038/nclimate3107.
  • Meehl, G. A., A. Hu, J. M. Arblaster, J. Fasullo, and K. E. Trenberth, 2013: Externally forced and internally generated decadal climate variability associated with the Interdecadal Pacific Oscillation. Journal of Climate, 26, 7298–7310, doi:10.1175/JCLI-D-12-00548.1.
  • Meehl, G. A., and H. Teng, 2007: Multi-model changes in El Niño teleconnections over North America in a future warmer climate. Climate Dynamics, 29, 779–790, doi:10.1007/s00382-007-0268-3.
  • Miles, M. W., D. V. Divine, T. Furevik, E. Jansen, M. Moros, and A. E. J. Ogilvie, 2014: A signal of persistent Atlantic multidecadal variability in Arctic sea ice. Geophysical Research Letters, 41, 463–469, doi:10.1002/2013GL058084.
  • Moore, G. W. K., J. Halfar, H. Majeed, W. Adey, and A. Kronz, 2017: Amplification of the Atlantic Multidecadal Oscillation associated with the onset of the industrial-era warming. Scientific Reports, 7, 40861, doi:10.1038/srep40861.
  • NWS, 2016: Global Circulations in NWS Jet Stream: An Online School for Weather. National Weather Service. URL
  • Newman, M., 2007: Interannual to decadal predictability of tropical and North Pacific sea surface temperatures. Journal of Climate, 20, 2333–2356, doi:10.1175/jcli4165.1.
  • Newman, M., M. A. Alexander, T. R. Ault, K. M. Cobb, C. Deser, E. D. Lorenzo, N. J. Mantua, A. J. Miller, S. Minobe, H. Nakamura, N. Schneider, D. J. Vimont, A. S. Phillips, J. D. Scott, and C. A. Smith, 2016: The Pacific Decadal Oscillation, revisited. Journal of Climate, 29, 4399–4427, doi:10.1175/JCLI-D-15-0508.1.
  • Nigam, S., 2003: Teleconnections. J.R. Holton, Ed., Academic Press, 2243–2269.
  • Ning, L., and R. S. Bradley, 2016: NAO and PNA influences on winter temperature and precipitation over the eastern United States in CMIP5 GCMs. Climate Dynamics, 46, 1257–1276, doi:10.1007/s00382-015-2643-9.
  • Norris, J. R., R. J. Allen, A. T. Evan, M. D. Zelinka, C. W. O’Dell, and S. A. Klein, 2016: Evidence for climate change in the satellite cloud record. Nature, 536, 72–75, doi:10.1038/nature18273.
  • Overland, J. E., and M. Wang, 2015: Increased variability in the early winter subarctic North American atmospheric circulation. Journal of Climate, 28, 7297–7305, doi:10.1175/jcli-d-15-0395.1.
  • Overland, J., J. A. Francis, R. Hall, E. Hanna, S.-J. Kim, and T. Vihma, 2015: The melting Arctic and midlatitude weather patterns: Are they connected? Journal of Climate, 28, 7917–7932, doi:10.1175/JCLI-D-14-00822.1.
  • Palmer, T. N., F. J. Doblas-Reyes, A. Weisheimer, and M. J. Rodwell, 2008: Toward seamless prediction: Calibration of climate change projections using seasonal forecasts. Bulletin of the American Meteorological Society, 89, 459–470, doi:10.1175/bams-89-4-459.
  • Peings, Y., and G. Magnusdottir, 2014: Forcing of the wintertime atmospheric circulation by the multidecadal fluctuations of the North Atlantic ocean. Environmental Research Letters, 9, 034018, doi:10.1088/1748-9326/9/3/034018.
  • Perlwitz, J., S. Pawson, R. L. Fogt, J. E. Nielsen, and W. D. Neff, 2008: Impact of stratospheric ozone hole recovery on Antarctic climate. Geophysical Research Letters, 35, L08714, doi:10.1029/2008GL033317.
  • Petoukhov, V., S. Rahmstorf, S. Petri, and H. J. Schellnhuber, 2013: Quasiresonant amplification of planetary waves and recent Northern Hemisphere weather extremes. Proceedings of the National Academy of Sciences, 110, 5336–5341, doi:10.1073/pnas.1222000110.
  • Prein, A. F., G. J. Holland, R. M. Rasmussen, M. P. Clark, and M. R. Tye, 2016: Running dry: The U.S. Southwest’s drift into a drier climate state. Geophysical Research Letters, 43, 1272–1279, doi:10.1002/2015GL066727.
  • Quan, X.-W., M. P. Hoerling, J. Perlwitz, H. F. Diaz, and T. Xu, 2014: How fast are the tropics expanding? Journal of Climate, 27, 1999–2013, doi:10.1175/JCLI-D-13-00287.1.
  • Reichler, T., 2016: Chapter 6 - Poleward expansion of the atmospheric circulation . T.M. Letcher, Ed., Elsevier, 79–104.
  • Renwick, J. A., and J. M. Wallace, 1996: Relationships between North Pacific wintertime blocking, El Niño, and the PNA pattern. Monthly Weather Review, 124, 2071–2076, doi:10.1175/1520-0493(1996)124<2071:RBNPWB>2.0.CO;2.
  • Ropelewski, C. F., and M. S. Halpert, 1987: Global and regional scale precipitation patterns associated with the El Niño/Southern Oscillation. Monthly Weather Review, 115, 1606–1626, doi:10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2.
  • Scaife, A. A., T. Spangehl, D. R. Fereday, U. Cubasch, U. Langematz, H. Akiyoshi, S. Bekki, P. Braesicke, N. Butchart, M. P. Chipperfield, A. Gettelman, S. C. Hardiman, M. Michou, E. Rozanov, and T. G. Shepherd, 2012: Climate change projections and stratosphere–troposphere interaction. Climate Dynamics, 38, 2089–2097, doi:10.1007/s00382-011-1080-7.
  • Scheff, J., and D. Frierson, 2012: Twenty-first-century multimodel subtropical precipitation declines are mostly midlatitude shifts. Journal of Climate, 25, 4330–4347, doi:10.1175/JCLI-D-11-00393.1.
  • Scheff, J., and D. M. W. Frierson, 2012: Robust future precipitation declines in CMIP5 largely reflect the poleward expansion of model subtropical dry zones. Geophysical Research Letters, 39, L18704, doi:10.1029/2012GL052910.
  • Schwendike, J., G. J. Berry, M. J. Reeder, C. Jakob, P. Govekar, and R. Wardle, 2015: Trends in the local Hadley and local Walker circulations. Journal of Geophysical Research Atmospheres, 120, 7599–7618, doi:10.1002/2014JD022652.
  • Screen, J. A., and I. Simmonds, 2013: Exploring links between Arctic amplification and mid-latitude weather. Geophysical Research Letters, 40, 959–964, doi:10.1002/grl.50174.
  • Seager, R., M. Hoerling, S. Schubert, H. Wang, B. Lyon, A. Kumar, J. Nakamura, and N. Henderson, 2015: Causes of the 2011–14 California drought. Journal of Climate, 28, 6997–7024, doi:10.1175/JCLI-D-14-00860.1.
  • Seager, R., N. Naik, and L. Vogel, 2012: Does global warming cause intensified interannual hydroclimate variability? Journal of Climate, 25, 3355–3372, doi:10.1175/JCLI-D-11-00363.1.
  • Seager, R., Y. Kushnir, M. Ting, M. Cane, N. Naik, and J. Miller, 2008: Would advance knowledge of 1930s SSTs have allowed prediction of the Dust Bowl drought? Journal of Climate, 21, 3261–3281, doi:10.1175/2007JCLI2134.1.
  • Seidel, D. J., Q. Fu, W. J. Randel, and T. J. Reichler, 2008: Widening of the tropical belt in a changing climate. Nature Geoscience, 1, 21–24, doi:10.1038/ngeo.2007.38.
  • Shaw, T. A., J. Perlwitz, and O. Weiner, 2014: Troposphere-stratosphere coupling: Links to North Atlantic weather and climate, including their representation in CMIP5 models. Journal of Geophysical Research Atmospheres, 119, 5864–5880, doi:10.1002/2013JD021191.
  • Sheffield, J. et al., 2013: North American climate in CMIP5 experiments. Part II: Evaluation of historical simulations of intraseasonal to decadal variability. Journal of Climate, 26, 9247–9290, doi:10.1175/jcli-d-12-00593.1.
  • Shepherd, T. G., 2014: Atmospheric circulation as a source of uncertainty in climate change projections. Nature Geoscience, 7, 703–708, doi:10.1038/ngeo2253.
  • Simpson, I. R., R. Seager, M. Ting, and T. A. Shaw, 2016: Causes of change in Northern Hemisphere winter meridional winds and regional hydroclimate. Nature Climate Change, 6, 65–70, doi:10.1038/nclimate2783.
  • Simpson, I. R., T. A. Shaw, and R. Seager, 2014: A diagnosis of the seasonally and longitudinally varying midlatitude circulation response to global warming. Journal of the Atmospheric Sciences, 71, 2489–2515, doi:10.1175/JAS-D-13-0325.1.
  • Sobel, A. H., S. J. Camargo, T. M. Hall, C.-Y. Lee, M. K. Tippett, and A. A. Wing, 2016: Human influence on tropical cyclone intensity. Science, 353, 242–246, doi:10.1126/science.aaf6574.
  • Srivastava, A., and T. DelSole, 2017: Decadal predictability without ocean dynamics. Proceedings of the National Academy of Sciences, 114, 2177–2182, doi:10.1073/pnas.1614085114.
  • Stevens, B., 2015: Rethinking the lower bound on aerosol radiative forcing. Journal of Climate, 28, 4794–4819, doi:10.1175/jcli-d-14-00656.1.
  • Stevenson, S. L., 2012: Significant changes to ENSO strength and impacts in the twenty-first century: Results from CMIP5. Geophysical Research Letters, 39, L17703, doi:10.1029/2012GL052759.
  • Sun, Y., G. Ramstein, C. Contoux, and T. Zhou, 2013: A comparative study of large-scale atmospheric circulation in the context of a future scenario (RCP4.5) and past warmth (mid-Pliocene). Climate of the Past, 9, 1613–1627, doi:10.5194/cp-9-1613-2013.
  • Swain, D., M. Tsiang, M. Haughen, D. Singh, A. Charland, B. Rajarthan, and N. S. Diffenbaugh, 2014: The extraordinary California drought of 2013/14: Character, context and the role of climate change [in “Explaining Extreme Events of 2013 from a Climate Perspective”]. Bulletin of the American Meteorological Society, 95 (9), S3–S6, doi:10.1175/1520-0477-95.9.S1.1.
  • Teng, H., and G. Branstator, 2017: Causes of extreme ridges that induce California droughts. Journal of Climate, 30, 1477–1492, doi:10.1175/jcli-d-16-0524.1.
  • Terray, L., 2012: Evidence for multiple drivers of North Atlantic multi-decadal climate variability. Geophysical Research Letters, 39, L19712, doi:10.1029/2012GL053046.
  • Thompson, D. W. J., E. A. Barnes, C. Deser, W. E. Foust, and A. S. Phillips, 2015: Quantifying the role of internal climate variability in future climate trends. Journal of Climate, 28, 6443–6456, doi:10.1175/JCLI-D-14-00830.1.
  • Thompson, D. W. J., and J. M. Wallace, 1998: The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophysical Research Letters, 25, 1297–1300, doi:10.1029/98GL00950.
  • Thompson, D. W. J., and J. M. Wallace, 2000: Annular modes in the extratropical circulation. Part I: Month-to-month variability. Journal of Climate, 13, 1000–1016, doi:10.1175/1520-0442(2000)013<1000:AMITEC>2.0.CO;2.
  • Thompson, D. W. J., and J. M. Wallace, 2001: Regional climate impacts of the Northern Hemisphere annular mode. Science, 293, 85–89, doi:10.1126/science.1058958.
  • Ting, M., Y. Kushnir, R. Seager, and C. Li, 2009: Forced and internal twentieth-century SST trends in the North Atlantic. Journal of Climate, 22, 1469–1481, doi:10.1175/2008jcli2561.1.
  • Trenary, L., and T. DelSole, 2016: Does the Atlantic Multidecadal Oscillation get its predictability from the Atlantic Meridional Overturning Circulation? Journal of Climate, 29, 5267–5280, doi:10.1175/jcli-d-16-0030.1.
  • Tung, K.-K., and J. Zhou, 2013: Using data to attribute episodes of warming and cooling in instrumental records. Proceedings of the National Academy of Sciences, doi:10.1073/pnas.1212471110.
  • Vallis, G. K., P. Zurita-Gotor, C. Cairns, and J. Kidston, 2015: Response of the large-scale structure of the atmosphere to global warming. Quarterly Journal of the Royal Meteorological Society, 141, 1479–1501, doi:10.1002/qj.2456.
  • Vimont, D. J., J. M. Wallace, and D. S. Battisti, 2003: The seasonal footprinting mechanism in the Pacific: Implications for ENSO. Journal of Climate, 16, 2668–2675, doi:10.1175/1520-0442(2003)016<2668:tsfmit>2.0.co;2.
  • Vincze, M., and I. M. Jánosi, 2011: Is the Atlantic Multidecadal Oscillation (AMO) a statistical phantom? Nonlinear Processes in Geophysics, 18, 469–475, doi:10.5194/npg-18-469-2011.
  • Vose, R. S., S. Applequist, M. Squires, I. Durre, M. J. Menne, C. N. Williams, C. Fenimore, K. Gleason, and D. Arndt, 2014: Improved Historical Temperature and Precipitation Time Series for U.S. Climate Divisions. Journal of Applied Meteorology and Climatology, 53, 1232–1251, doi:10.1175/JAMC-D-13-0248.1.
  • Wang, H., S. Schubert, R. Koster, Y.-G. Ham, and M. Suarez, 2014: On the role of SST forcing in the 2011 and 2012 extreme U.S. heat and drought: A study in contrasts. Journal of Hydrometeorology, 15, 1255–1273, doi:10.1175/JHM-D-13-069.1.
  • Wang, T., O. H. Otterå, Y. Gao, and H. Wang, 2012: The response of the North Pacific Decadal Variability to strong tropical volcanic eruptions. Climate Dynamics, 39, 2917–2936, doi:10.1007/s00382-012-1373-5.
  • Waugh, D. W., C. I. Garfinkel, and L. M. Polvani, 2015: Drivers of the recent tropical expansion in the Southern Hemisphere: Changing SSTs or ozone depletion? Journal of Climate, 28, 6581–6586, doi:10.1175/JCLI-D-15-0138.1.
  • Wettstein, J. J., and C. Deser, 2014: Internal variability in projections of twenty-first-century Arctic sea ice loss: Role of the large-scale atmospheric circulation. Journal of Climate, 27, 527–550, doi:10.1175/JCLI-D-12-00839.1.
  • Whan, K., F. Zwiers, and J. Sillmann, 2016: The influence of atmospheric blocking on extreme winter minimum temperatures in North America. Journal of Climate, 29, 4361–4381, doi:10.1175/JCLI-D-15-0493.1.
  • Yang, Q., T. H. Dixon, P. G. Myers, J. Bonin, D. Chambers, and M. R. van den Broeke, 2016: Recent increases in Arctic freshwater flux affects Labrador Sea convection and Atlantic overturning circulation. Nature Communications, 7, 10525, doi:10.1038/ncomms10525.
  • Yeh, S.-W., J.-S. Kug, B. Dewitte, M.-H. Kwon, B. P. Kirtman, and F.-F. Jin, 2009: El Niño in a changing climate. Nature, 461, 511–514, doi:10.1038/nature08316.
  • Yeh, S.-W., W.-M. Kim, Y. H. Kim, B.-K. Moon, R. J. Park, and C.-K. Song, 2013: Changes in the variability of the North Pacific sea surface temperature caused by direct sulfate aerosol forcing in China in a coupled general circulation model. Journal of Geophysical Research Atmospheres, 118, 1261–1270, doi:10.1029/2012JD017947.
  • Yu, J.-Y., Y. Zou, S. T. Kim, and T. Lee, 2012: The changing impact of El Niño on US winter temperatures. Geophysical Research Letters, 39, L15702, doi:10.1029/2012GL052483.
  • Yu, J.-Y., and Y. Zou, 2013: The enhanced drying effect of Central-Pacific El Niño on US winter. Environmental Research Letters, 8, 014019, doi:10.1088/1748-9326/8/1/014019.
  • Zhang, R., R. Sutton, G. Danabasoglu, T. L. Delworth, W. M. Kim, J. Robson, and S. G. Yeager, 2016: Comment on “The Atlantic Multidecadal Oscillation without a role for ocean circulation.” Science, 352, 1527–1527, doi:10.1126/science.aaf1660.
  • Zhang, R., T. L. Delworth, R. Sutton, D. L. R. Hodson, K. W. Dixon, I. M. Held, Y. Kushnir, J. Marshall, Y. Ming, R. Msadek, J. Robson, A. J. Rosati, M. Ting, and G. A. Vecchi, 2013: Have aerosols caused the observed Atlantic multidecadal variability? Journal of the Atmospheric Sciences, 70, 1135–1144, doi:10.1175/jas-d-12-0331.1.
  • Zhang, R., and T. L. Delworth, 2009: A new method for attributing climate variations over the Atlantic Hurricane Basin’s main development region. Geophysical Research Letters, 36, L06701, doi:10.1029/2009GL037260.
  • Zhang, T., M. P. Hoerling, J. Perlwitz, and T. Xu, 2016: Forced atmospheric teleconnections during 1979–2014. Journal of Climate, 29, 2333–2357, doi:10.1175/jcli-d-15-0226.1.
  • Zhou, Z.-Q., S.-P. Xie, X.-T. Zheng, Q. Liu, and H. Wang, 2014: Global warming–induced changes in El Niño teleconnections over the North Pacific and North America. Journal of Climate, 27, 9050–9064, doi:10.1175/JCLI-D-14-00254.1.