On interannual to decadal time scales, the climate mode with many of the strongest societal impacts is the El Niño–Southern Oscillation (ENSO). However, quantifying ENSO's changes in a warming climate remains a formidable challenge, due to both the noise arising from internal variability and the complexity of air-sea feedbacks in the tropical Pacific Ocean. In this work, we use large (≥30-member) ensembles of climate simulations to show that anthropogenic climate change can produce systematic increases in ENSO teleconnection strength over many land regions, driving increased interannual variability in regional temperature extremes and wildfire frequency. As the spatial character of this intensification exhibits strong land-ocean contrasts, a causal role for land-atmosphere feedbacks is suggested. The identified increase in variance occurs in multiple model ensembles, independent of changes in sea surface temperature variance. This suggests that in addition to changes in the overall likelihoods of heat and wildfire extremes, the variability in these events may also be a robust feature of future climate.
- Intensity increases in temperature and wildfire extremes driven by ENSO in a warming climate are identified in climate model large ensembles
- The intensification occurs mainly over land regions and is influenced by precipitation
- Land-atmosphere feedbacks are likely to play a key role in the projected amplification
Plain Language Summary
Changes in climate variability strongly affect the overall impacts of climate change. In this work, increases in the intensity of heat waves and wildfire driven by El Niño/La Niña in a business-as-usual climate scenario are identified in recently produced climate simulations spanning the 20th and 21st centuries. The intensification in temperature extremes occurs mainly over land regions and independently of changes in eastern Pacific sea surface temperature variability. It is argued that land atmosphere feedbacks are likely to play a key role in the simulated amplification, with relevance to impacts such as heat waves and wildfire frequency.
El Niño events are characterized by an anomalous and widespread warming of central and eastern tropical Pacific Ocean sea surface temperature (SST) of up to several degrees. Along with its cool counterpart La Niña, El Niño has long been known to be associated with a planetary-scale redistribution of heat, precipitation, and winds (McPhaden et al., 2006; Rasmusson & Carpenter, 1983; Ropelewski & Halpert, 1987), now collectively known as the El Niño–Southern Oscillation (ENSO). The ENSO influence was first identified in early 20th century Indian monsoon variability (Walker, 1923) and over time has become recognized for its broad and profound socioeconomic and ecological consequences, which include impacts on crop yields, famine, heating, and cooling demands of homes and buildings, fire risks (Barbero et al., 2015; Westerling & Swetjnam, 2003), corals (Glynn & Weerdt, 1991), and extreme weather (Bell et al., 1999).
The exceptional severity of recent climate extremes has heightened our interest in understanding ENSO's future (Figure S1 in the supporting information). For example, from mid-2009 through mid-2010, intense drought and heat wave conditions spanned the Amazon Basin (Figure S1 left column, Lewis et al., 2011). While the period accompanied a moderate El Niño, which is known to increase temperature and decrease precipitation in the region (Ropelewski & Halpert, 1987), observed anomalies were considerably greater than those expected based on historical El Niño events during the 20th century (Marengo et al., 2011). Similarly, from mid-2010 through mid-2011, a severe drought and heat wave impacted the southern tier of the United States, coincident with a strong and prolonged La Niña event (Figure S1, right column). At the same time, in the northern United States and southern Canada, anomalies of opposite sign prevailed, with unusually cool and wet conditions, including once in multicentury flooding events in Manitoba, Canada (Burn & Whitfield, 2015). While climate anomalies in North America of similar general character are common during La Niña, the intensity of these anomalies was again highly unusual. A wide range of processes can potentially alter observed anomalies during any individual event, and therefore, these episodes do not provide a definitive basis for attributing changes in the strength of ENSO or its teleconnections, a challenge that relates to both the evaluation of events in nature (e.g., Seager et al., 2014; Yeh et al., 2018) and models (Deser et al., 2017; Guilyardi et al., 2016). They do, however, raise questions regarding the role a warming climate may have had on both these and even more recent ENSO-related extremes in California (Swain et al., 2018; Williams et al., 2015, 2018; Yoon, Wang, Gillies, Hipps, et al., 2015) and other regions (Herrera & Ault, 2017; Wang, Huang, et al., 2015; Williams et al., 2014).
In addition to differences in projected 21st century ENSO strength across models, a major difficulty in assessing future ENSO-related risks is accounting for its large internal variability. The observational record exhibits events with considerable individual character and prolonged intervals of either highly variable or quiescent activity both in the tropical Pacific Ocean (Capotondi et al., 2015; Newman et al., 2011) and remotely teleconnected regions (Deser et al., 2017; Yeh et al., 2018). As a result, it is often unclear whether contrasts between different regional climate extremes arise at random or whether they are part of systematic shifts. This ambiguity affects the interpretation of both the observational record and model simulations (Bellenger et al., 2014; Stevenson, 2012; Stevenson et al., 2012; Wittenberg, 2009; Yeh et al., 2009). In climate models, the role of internal variability can be assessed by using a so-called “large ensemble” (LE) of simulations (e.g., Kay et al., 2015). By generating multiple simulations differing only in the fine details of their initialized states, an ensemble average can be generated to estimate the climate system's “forced” response. This, in turn, can be removed from individual members, both to isolate their internal variability and its changes under transient climate change.
In this paper, we examine changes in the regressions of regional climate against ENSO-related SST anomalies between historical and late 21st century climate in a business as usual climate scenario. Recently produced LEs of climate simulations are used, with the goal of identifying systematic shifts in the regressions due to warming of the background climate. The methods and data used are described in section 2, key results using the Community Earth System Model (CESM) are presented in section 3, and robust features across other model ensembles are discussed in section 4. A synthesis discussion and concluding remarks are given in section 5.
2 Methods and Data
Here we analyze the recently constructed CESM LE (CESM LENS, Kay et al., 2015). This ensemble is generated by using a common set of external forcings (e.g., evolving solar radiation, volcanic and anthropogenic aerosols, greenhouse gases, and land cover conditions) and a single model, initialized for multiple ensemble members with conditions that differ only slightly in their initial atmospheric states. Individual members of these simulations exhibit internal fluctuations (i.e., weather) that diverge within a few days, thereby providing a broad statistical sampling of coupled internal variability through the course of the 20th and 21st centuries.
In addition to reporting standard meteorological outputs, the CESM's land component, the Community Land Model, contains an interactive wildfire scheme, which allows for the simulation of wildfire probability (FP) and fractional area burned (FA; Lawrence et al., 2012) subject to the influence of near-surface meteorology and soil moisture in a manner consistent with commonly used bulk parameterizations for wildfire (Abatzoglou & Williams, 2016; Jolly et al., 2015). CESM's wildfire scheme offers the advantage of explicitly representing fuel load and coupled wildfire feedbacks (Yoon, Wang, Gillies, Kravitz, et al., 2015). The Community Land Model wildfire scheme applies statistical relationships between fire season length and burned area, combined with interactions with fuel abundance and moisture, to simulate fire activity. As the focus here is on interannual variability, such relationships are reasonably sampled in the observed wildfire record (Yoon, Wang, Gillies, Hipps, et al., 2015). CESM simulations of variability in fire and its underlying drivers have been found to agree favorably with observations (Chikamoto et al., 2015; Yoon, Wang, Gillies, Kravitz, et al., 2015), though the wide separation of scales between global climate and wildfire remains a significant modeling challenge. As FP and FA are strongly correlated in space and time, only FP is shown in the discussion below; however, statements regarding changes in wildfire variance generally are valid for both metrics.
The large number of members in this ensemble (40) and the long time period simulated (1920–2100) allow for a more complete statistical assessment of forced transient changes in ENSO than do small ensembles or multimodel ensembles, in which contrasts between members due to model structural differences are difficult to distinguish from internal variability (Stevenson et al., 2012). An additional motivation for using the ensemble is that the CESM is among the most skillful climate models in reproducing observed ENSO behavior in the Pacific Ocean and its associated remote teleconnections (Cai et al., 2014, Figures S2 and S3).
Additional analysis of a recently produced 30-member LE from GFDL using the coupled ESM developed at the Geophysical Fluid Dynamics Laboratory (ESM 2M, Dunne et al., 2013) is also conducted. It consists of the 1-degree version of the MOM4p1 ocean model coupled to 2-degree configurations of the AM2 atmospheric and LM3 land models. An assessment of simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5, Taylor et al., 2012) is also conducted. These simulations include contributions from 20 modeling groups from around the world including contributions from CESM and ESM 2M, with a broad range of skill in reproducing present-day climate.
Teleconnections are computed by regressing July to June climate averages against SST anomalies in the Niño3.4 region (5°N:5°S, 170 W:120 W) for the same period to maximize coherence with ENSO's seasonality. The linear regression model is fitted using the least squares approach. By design, linear regression removes the linear influence of changes in ENSO SST variance, which vary greatly across models and are not well constrained by observations (e.g., Bellenger et al., 2014), from its remote effects. Prior to computing these regressions, the forced climate change component of both Niño3.4 SST and other fields is estimated, by averaging all available ensemble members, and is subtracted from each individual member.
To estimate observed teleconnections for our 20th century baseline interval (1920–1980), ECMWF's 20th century reanalysis is used (Poli et al., 2016). ERA-20C is ECMWF's first atmospheric reanalysis of the 20th century, assimilating only observations of surface pressure and surface marine winds based on ISPD v3.2.6 and ICOADS v2.5.1 and surface marine winds from ICOADS v2.5.1. The ERA-20C horizontal resolution of approximately 125 km is on par with that of the CESM. The assimilation methodology is a 24-hr 4D-Var analysis with bias correction of surface pressure observations.
3 CESM Results
The 20th century (1920–1980) ENSO teleconnections in surface temperature in observations and CESM, and projected late 21st century changes (2040–2100) relative to the 20th century, are shown in Figure 1. These periods are chosen to maximize contrasts arising from climate change. Key features of the observed teleconnections for the 20th century include strong negative values (e.g., cooling during El Niño associated with increased clouds and precipitation; see also Figures S2, S7, and S8) over the southern tier of North America (Figure 1a, consistent for example with warming and decreased precipitation during La Niña such as was evident in 2010–2011) and strong positive values over Australia (Figure 1b) and South America (Figure 1c), where warming and reduced precipitation are characteristic of historical El Niño teleconnections (Ropelewski & Halpert, 1987, Figure S2A). The CESM 20th century teleconnections (Figures 1d–1f) reproduce many of the observed features and are strongly spatially correlated to observed teleconnections, though the ensemble mean teleconnections are somewhat weaker than observed in most regions. Such regional discrepancies in intensity between observations and the CESM may arise from the large uncertainty in teleconnections due to internal variability (e.g., Deser et al., 2017) and errors in both model physics and observations.
Future changes in the regressions (Figures 1g–1i) are characterized by a general intensification of 20th century patterns and suggest a broad-scale increase in ENSO's remote influence on surface temperature as the climate warms, particularly over land. In North America, the intensification is statistically significant across Mexico and the southern half of the United States. In Australia and South America, the intensification is pervasive and exhibits strong coherence with continental boundaries. The projection of significant teleconnection changes in regions where historical teleconnections are weak, such as in eastern Canada and southern South America, is also a notable aspect of ENSO's changes in a warming climate.
The projected 21st century increase in the regressed surface temperature response to ENSO is accompanied by regional mean state climate changes and likely contributes to projected changes in wildfire risk. ENSO's 20th century FP teleconnections are shown in Figures 2a–2c and are characterized negative values in northern Mexico and the southern tier of the United States, positive values across Australia with negligible values where forest extents are small (i.e., central Australia), and regionally contrasting signals in South America, where the meridional structure of precipitation is influenced by ENSO (e.g., Ropelewski & Halpert, 1987, Figure S2A). Given the strong ties between FP and surface temperature, aridity, and soil moisture, a spatial similarity between the TS (Figure 1) and FP teleconnections is generally expected; however, the spatial structure and dominant influences can vary regionally. Departures between 20th century Ts and Fp teleconnections are particularly evident in central South America, where negative Fp and positive Ts regressions coincide. Mean state changes in the CESM include warming, decreases in relative humidity, and increases in FP and FA (Figure S9). In North America, patterns of Fp teleconnection changes include an intensification of existing regions of influence in northern Mexico and the southwest United States, a reduction of influence in southern Mexico, and a spreading of negative teleconnections into the southern central and western U.S. regions. In Australia, the pattern of teleconnection changes is generally one of intensification of existing regions of influence, while in South America, the pattern of change is negatively correlated to existing teleconnections. A strong negative correlation exists between changes in FP teleconnections and those in precipitation, suggesting the potential for precipitation shifts to override temperature influences in South America (e.g., Figure 1i). This moderation of temperature teleconnections coincides with regions of large positive changes in precipitation teleconnections (Figure S7) and likely reflects the moderating influence of precipitation on temperature extremes (Trenberth & Shea, 2005). An important aspect of temperature and wildfire teleconnection changes is therefore suggested, whereby precipitation changes, where they are sufficiently strong, are likely to modulate the intensity of future teleconnections. While changes in total biomass may also influence wildfire activity, its trends in CESM in the regions covered in Figure 2 are generally negative (not shown) and therefore are not likely to be a main contributor to increases in wildfire variability.
Finally, using output from the CESM, lead/lag relationships of ENSO teleconnections to Australian TS and FP and Californian precipitation and FP are summarized in Figure 3, both for historical (blue) and projected (red) climates. Changes in the mean state and histograms of the peak to trough regression range for each ensemble member are also shown. By the late 21st century, Australia has warmed by about 3.5 K (Figure 3a). Increases in ENSO-regressed variability in the 21st century (red) are evident and, on average, warming by the late 21st century contributes to an additional 30% in variance (~0.1 K/K−1) to typical interannual shifts in continent-mean temperature associated with ENSO relative to mid-20th century conditions (blue).
The peak in this effect is coherent with ENSO's maximum influence, with a lag of about a season. Histograms of peak-to-trough regressions show substantial future variance increases (inset in Figure 3a). In conjunction with the increase in temperature variance, an increase in FP in Australia is also simulated, itself lagging Niño3.4 SST by about 9 months (Figure 3b; a roughly 6-month lag from Australian TS), and histograms of future variance show substantial increases in year-to-year shifts (Figure 3b, inset).
In California, a region where increases in the surface temperature response to ENSO are small (e.g., Figure 1, in contrast to North America generally) and circulation changes in the lead up to El Niño play a key role in future teleconnection shifts (Wang et al., 2014; Wang, Simon, et al., 2015, Zhou et al., 2014), increased ENSO-regressed variance in precipitation is associated with late 21st century warming (Figure 3c, and consistent with recent findings of Swain et al., 2018). California precipitation is approximately in phase with Niño3.4 SST, with a peak lagged relationship at about a month. Histograms show substantial future increases in peak-to-trough variability. Associated with the increase in precipitation variance, an increase in FP variance of about 30% over 20th century variance is simulated. The increase is accompanied by a background increase in FP of about 4.7%. A highly significant shift in the ensemble distribution toward greater variability is also evident (Figure 3d).
4 Consistency Across Other Model Ensembles
Contrasts across model projections of Niño 3.4 SST constitute an important source of uncertainty in assessing the influence of warming on future ENSO behavior and interannual variance in general (Bellenger et al., 2014; Stevenson, 2012; Yeh et al., 2018). There is therefore a need to evaluate the robustness of CESM projections across models. Toward this end, we first use a recently generated LE using the Geophysical Fluid Dynamics Laboratory ESM 2M (Rodgers et al., 2015). As with the CESM, the ESM 2M is driven by a complete set of external forcings (e.g., evolving solar radiation, volcanic and anthropogenic aerosols, greenhouse gases, and land cover conditions) but extends instead from 1950 to 2100 and is composed of only 30 members. Other important differences in climate exist, such as the ESM 2M's projection of reduced Niño 3.4 SST variance in a warming climate, particularly in the 3- to 5-year time span (Figures S3b and S4b), as opposed to the CESM, which projects a substantial variance increase (Figures S4b and S5b). The differences in their projected variance are likely linked in part to biases in present-day simulation of ENSO (Graham et al., 2016; Phillips et al., 2014) and to projected changes in the background climate state (Cai et al., 2014, 2015; Collins et al., 2010; Zheng et al., 2016), with 21st century warming in tropical SST being greatest in the eastern Pacific Ocean in the CESM and the central-western Pacific Ocean in the ESM 2M. It is not known which change in ENSO variance is more likely (Bellenger et al., 2014; Stevenson, 2012; Stevenson et al., 2012). Despite these contrasts, future changes in tropical Pacific precipitation associated with ENSO have been shown to be more consistent across climate models (Cai et al., 2014, 2015; Power et al., 2013). Here we show that it is also true that changes in the temperature teleconnections are generally consistent across climate models in our focus regions and are comparable between the ESM 2M and CESM. Figure 4 shows ESM 2M's 20th century temperature teleconnections and their projected changes. Strong similarities are evident between ESM 2M and CESM, and these include strong pattern correlation between observed and simulated 20th century teleconnections, strong pattern correlations between present-day teleconnections and future changes, and the existence of strong land-sea contrasts in each. It is noteworthy that this general agreement in teleconnection changes occurs despite significant differences in projected changes in the mean atmospheric circulation (i.e., Walker circulation): CESM simulates a general weakening, whereas the GFDL LE shows an eastward displacement and slight strengthening in some regions (Figure S6).
There is also general agreement between models on the character of 20th century precipitation teleconnections to these regions (Figure S8), though with greater spread than for temperature. However, large disagreement also exists regarding changes to precipitation teleconnections under warming. In regions where precipitation is sufficiently intense, changes in precipitation can also influence temperature teleconnections (e.g., Trenberth & Shea, 2005). As was identified for the CESM in Figure 1i, the ESM 2M exhibits some regions in northern South America that project weakened temperature teleconnections, and these are associated generally with the mitigating influence of changing precipitation teleconnections (Figures 4 and S8). Projections of changing precipitation teleconnections represent a significant source of uncertainty in regions where precipitation is sufficiently strong and differences in model projections are large (e.g., South America). However, in arid regions such as the southwestern United States and Australia, precipitation's mitigating influence is suggested to be small (consistent with Udall & Overpeck, 2017).
Lastly, the robustness of changes in teleconnections can be explored more generally in the multimodel CMIP5 archive (Taylor et al., 2012). As for the LEs, the multimodel mean teleconnections for the 20th century agree closely with observations (Figures S10A–S10C). Patterns of projected change also agree well in general with those from the CESM and ESM 2M, though the area of their statistical significance is generally less, both for the CMIP5 archive overall (Figures S10D–S10F) and a subset of the models with the best representation of ENSO (Figures S10G–S10I). The reduced area of significance arises in part from the relatively small number of ensemble members in these archives and their poorer and more diverse representation of ENSO patterns in the Pacific Ocean (Bellenger et al., 2014; Perry et al., 2017). Nonetheless, the models' mean patterns corroborate both the projection of increased variance, even in South America, and the presence of strong land-ocean contrasts in such patterns, again suggesting a role for land-atmosphere feedbacks.
5 Discussion and Conclusions
The intensification of ENSO temperature teleconnections to key land regions is shown here to be depicted broadly across the CESM and ESM 2M LEs and CMIP5 models. The southern tier of North America and Australia are identified as regions where amplified teleconnections are simulated with particular consistency across models. Less consistent are projected changes in South America, where both model disagreement and systematic bias in simulating precipitation and ENSO teleconnections remain problematic. The intensification of temperature teleconnections occurs despite strong intermodel contrasts in projections of Niño3.4 SST variance and mean-state dynamic and thermodynamic patterns in a warming climate. This finding contrasts with those of studies using only a single model and where changes in teleconnection variance are implicitly linked to increases in Niño 3.4 SST variance, which are highly uncertain. Changes in precipitation teleconnections are identified as being a potentially important influencing factor in some regions, particularly where base-state precipitation is high such as in the Amazon basin. In the CESM, changes in wildfire probability are found to mirror those in temperature. The teleconnection strengthening is particularly notable in that it contrasts with the projected weakening of the atmospheric circulation's response to ENSO in a warming climate, a feature common to most CMIP5-class models (Bellenger et al., 2014; Stevenson, 2012; Stevenson et al., 2012). This dynamical weakening, while evident in the CESM, is largely absent from the ESM 2M (Figure S6), suggesting an important distinction between ENSO's dynamic and thermodynamic changes. The strong land-ocean contrasts evident in both the mean state regressions and their future changes are suggestive of a role for land-atmosphere feedbacks in enhancing the surface temperature response in a manner similar to aridity increases in the mean state (Berg et al., 2016; Fasullo, 2010; Williams et al., 2018). It is also likely that regional circulation changes, both in the mean state and transient variability, may act to modulate the net intensity of teleconnection changes (Funk & Hoell, 2015; Wang et al., 2014; Wang, Simon, et al., 2015), hypotheses that will be explored further in follow-on work.
Changes in ENSO's remote influence in a warming climate estimated in the CESM and ESM 2M suggest that the impact of an El Niño/La Niña event of a given strength is enhanced by mean climate warming, with accompanying increases in the probability and severity of regional temperature extremes. The CESM suggests as well that related impacts such as wildfire frequency will increase as a result. The changes do not, however, provide a definitive estimation of changes in total variability, given the underlying uncertainties in changes in Niño3.4 SST variance. Identifying such changes in observations faces the considerable challenge of distinguishing internal variability from the response to warming. The findings here suggest an increased probability of enhanced future extremes, impacts, and related risks in a warming climate, even if ENSO-related SST variance remains unchanged or decreases slightly. Continued improvement of coupled models, particularly through the reduction of biases in ENSO and the mean states of the tropical oceans, is likely to further increase confidence in these findings, particularly in South America where the character of precipitation projections exhibits marked inconsistency across models.
This work was supported by NSF Award ID AGS-1243125 and DOE Award ID DE-SC0012711. The CESM and CMIP5 simulations are available on the Earth System Grid (https://esgf.llnl.gov). The ESM 2M simulations have been made available by Keith Rodgers of GFDL ([email protected]). The ECMWF 20th century reanalysis was obtained from https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era-20c.
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