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Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community Atmosphere Model

Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community... The past four decades have seen an increase of terrestrial hot extremes during summer in the northern extratropics, accompa- nied by the Northern Hemisphere (NH) sea surface temperature (SST) warming (mainly over 10°–70°N, 0°–360°) and CO concentration rising. This study aims to understand possible causes for the increasing hot extremes, which are defined on a daily basis. We conduct a series of numerical experiments using the Community Atmosphere Model version 5 model for two periods, 1979–1995 and 2002–2018. The experiment by changing the C O concentration only with the climatological SST shows less increase of hot extremes days than that observed, whereas that by changing the NH SST (over 10°–70°N, 0°–360°) with constant C O concentration strengthens the hot extremes change over mid-latitudes. The experiment with both SST and CO concentration changes shows hot extremes change closer to the observation compared to the single-change experi- ments, as well as more similar simulations of atmospheric circulations and feedbacks from cloud and radiative processes. Also discussed are roles of natural variability (e.g., Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation) and other factors (e.g., Arctic sea ice and tropical SST). Keywords Hot extremes · Sea surface temperature · Greenhouse warming · Community Atmosphere Model · Climate change · Natural variability 1 Introduction the northern extratropics have been frequently observed, such as the ones in Europe in 2003 (Schär and Jendritzky Although the increase of the global mean temperature has 2004), Russia in 2010 (Coumou and Rahmstorf 2012), slowed down since the late 1990s (Kosaka and Xie 2013), United States in 2011 (Luo and Zhang 2012), and China terrestrial hot extremes characterized by extreme high sur- in 2013 and 2015 (Sun et al. 2016; Ma et al. 2017). These face air temperature (SAT) have become more frequent in hot extremes resulted in severe damages to ecosystems and recent decades (Perkins-Kirkpatrick and Lewis 2020). Since human society, including forest fires, decreasing agricultural the twenty-first century, severe summer hot extremes over production, and loss of human life (e.g., Ciais et al. 2005; Coumou and Rahmstorf 2012). Indeed, some hot extremes were concomitant with droughts due to strong anti-correla- Communicated by Jin-Ho Yoon. tion between temperature and precipitation during summer over the extratropics (Coumou et al. 2018). Due to disastrous * Siyu Zhao impacts of hot extremes and accompanying droughts, there siyu_zhao@atmos.ucla.edu is an urgent need for better understanding the dynamics and Department of Atmospheric and Oceanic Sciences, physics linked to these extremes. University of California, Los Angeles, Los Angeles, CA, Hot extremes are usually linked to large-scale circulation USA anomalies driving subsidence of air mass (Röthlisberger and School of Civil and Environmental Engineering, Georgia Martius 2019; Tian et al. 2020), cloud changes that mod- Institute of Technology, Atlanta, GA, USA ulate the surface radiation (Jaeger and Seneviratne 2011; School of Earth and Atmospheric Sciences, Georgia Institute Sousa et al. 2018; Tian et al. 2020), and/or enhanced warm of Technology, Atlanta, GA, USA air advection (Sousa et al. 2018). For example, a circum- Shandong Climate Center, Shandong Province global teleconnection (CGT) pattern, characterized by a Meteorological Bureau, Jinan, Shandong, China Korean MeteorologicalSociety Vol.:(0123456789) 1 3 S. Zhao et al. zonal wavenumber-5 structure from an empirical orthogonal on atmospheric circulation change (Shaw and Voigt 2015). function (EOF) analysis, results from internal atmospheric This tug of war on circulations highlights the importance of dynamics and provides the major source of climate variabil- understanding the effect of CO concentration and SST on ity and predictability in northern mid-latitudes, especially hot extremes, which are closely tied to circulations. for U.S. hot extremes (Teng et al. 2013). Ding and Wang Based on previous studies that applied the AGCM to (2005) suggested that the maintenance of the CGT pattern examine the roles of atmospheric composition and SST depends on interactions between the CGT (i.e., Rossby wave in atmospheric circulations, our study adopts a similar train patterns) and Indian summer monsoon (related to the approach to understand their individual and combined effects west-central Asian high). Such CGT pattern was also identi- on terrestrial hot extremes during boreal summer over the e fi d through a self-organizing map (SOM) analysis and tends northern extratropics. We conduct numerical experiments to be linked to the increasing hot extremes over the Northern using CAM version 5 (CAM5) model to investigate how Hemisphere (NH) (Lee et al. 2017).observed CO change and observed SST change influence These proximate drivers can be connected to atmos- the change of hot extremes in recent decades. pheric chemical composition and sea surface temperature (SST) (e.g., Lenderink et al. 2007; Trenberth et al. 2015; Xie et al. 2015; Horton et al. 2016; Baker et al. 2018). For 2 Data and Methodology example, the decadal change of the daytime, nighttime, and compound hot extremes over China is attributed to effects of 2.1 Data anthropogenic forcing, such as those related to greenhouse gas concentrations and anthropogenic aerosol emissions (Su Daily mean observed geopotential height, wind, total-cloud and Dong 2019). The change in global SAT from 1970 to cover, and surface downward shortwave and longwave 2000s is associated with anthropogenic forcing, in combina- radiations (hereafter SW and LW, respectively) are from tion with the effect of surface–atmosphere interactions and the European Centre for Medium Range Weather Forecasts large-scale circulation changes (Tian et al. 2020). Further- Reanalysis 5 (ERA5) on 2.5° × 2.5° spatial grids (Coper- more, the increase of summer hot extremes over the NH land nicus Climate Change Service 2017). Daily mean 2-m air is linked to the Atlantic Multidecadal Oscillation (AMO) (or temperatures is from ERA5 with a resolution of 1.0° and an AMO-like SST pattern) (Johnson et al. 2018; Gao et al. from the National Centers for Environmental Prediction 2019), but the Atlantic SST forced trend in daily maximum (NCEP)–National Center for Atmospheric Research (NCAR) SAT (over land) during 1979–2012 is much weaker in mag- reanalysis with a Gaussian grid (Kalnay et al. 1996). The nitude than that observed (Johnson et al. 2018). SST effects ERA5 and NCEP–NCAR data cover the boreal summer on hot extremes (or global SAT) have also been documented (June–August) for the period of 1979–2018 and 1950–2018, in other studies (e.g., Kosaka and Xie 2013; Watanabe et al. respectively. The monthly mean SST and sea ice concentra- 2014; Dai et al. 2015; Stolpe et al. 2017; Dai and Bloecker tion (SIC) come from the Hadley Centre Sea Ice and Sea 2019). Surface Temperature datasets (HadISST) on 1.0° × 1.0° spa- Many studies have applied an atmospheric general cir- tial grids for the period of 1950–2018 (Rayner et al. 2003). culation model (AGCM) to understand roles of atmos- pheric composition (e.g., CO concentration) and SST in 2.2 Observed Hot Extremes the change of atmospheric circulations. For example, Deser and Phillips (2009) applied the Community Atmosphere At each grid point over the northern extratropics (20°–80°N, Model version 3 (CAM3) model to examine the relative 0°–360°; over land), we define an anomalous hot day when th roles of direct atmospheric radiative forcing (e.g., changes the daily 2-m temperature at the grid point is above 90 per- in well-mixed greenhouse gases) and observed SST change centile for that calendar day over the period of 1979–2018 in global atmospheric circulation trends during boreal winter (Zhao et al. 2017, 2020). Such classifications are performed for 1950–2000. Their results showed that atmospheric radia- for all days and the total number of days of hot extremes tive changes slightly contribute to circulation trends over the in summer is computed for each year. We also use another Atlantic–Eurasian sector in the NH, while the SST change method to define anomalous hot days by comparing the daily largely contributes to the intensification of the Aleutian low. 2-m temperature anomaly (deviation from long-term daily In addition, some studies compared circulation responses to climatology) with the 1.5 standard deviation in daily temper- quadrupled atmospheric CO concentration and to 4 K SST ature for that calendar day. The composite anomalies for an warming using Atmospheric Model Intercomparison Project early/late period (which will be defined later) are calculated (AMIP) runs (e.g., Grise and Polvani 2014; Shaw and Voigt by subtracting the summer climatology from the average 2015, 2016). For example, during summer, CO concentra- of the annual data over that period, with the Student’s t test tion rising and SST warming can result in opposite effects applied to examine the significance. Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… 2.3 CAM5 Experiments3 Results To investigate the individual and combined effects of CO 3.1 Decadal Change of Hot Extremes concentration and SST on hot extremes, we apply the NCAR CAM5 model (Neale et al. 2012), with a grid of 1.9° × 2.5° Figure 1a shows the linear trend of the total number of days (gx1v6) for atmosphere (ocean) and 30 vertical levels in (using the ERA5 dataset and the definition of exceeding the th the atmosphere. The control experiment is forced with the 90 percentile) of hot extremes over the northern extratrop- climatological SST and C O concentration (Table 1). Other ics during the period of 1979 − 2018. The linear trend has the factors (e.g., SIC) that may contribute to hot extremes are largest magnitudes over v fi e key regions: Europe (35°–60°N, set as climatology. The model has been validated by com- 10 W°–50°E), northern Africa–western Asia (20°–35°N, paring the climatological SAT over land in the Control Exp 18 W°–65°E), eastern Asia (20°–60°N, 95°–135°E), west- with that observed. Three sets of sensitivity experiments are ern North America (20°–45°N, 95°–125°W), and Green- conducted with each set including an “early” run, a “tran- land (60°–80°N, 15°–70°W). Such a trend bears a strong sition” run, and a “late” run. The transition run is forced resemblance to the observed trend in daily maximum SAT with the climatological SST and CO concentration. The in Johnson et al. (2018). The domain-averaged anomalies of early and late runs are forced with different combinations hot extremes days and SAT (over land) have a positive trend of SST and CO , similar to the setting in Deser and Phillips (significant at the 0.01 level), with the positive anomaly of (2009). For example, in the FULL Exp, the SST for the early hot extremes days from 2002 (Fig. 1b). The increase of the and late runs is the SST climatology plus monthly mean extremes is not sensitive to either the definition of extremes NH SST anomaly (10°–70°N, 0°–360°) averaged for early or dataset applied. Hence, the ERA5 dataset and the defini- th (1979–1995) and late (2002–2018) periods, respectively; tion of exceeding the 90 percentile are used in the follow- and the C O for the early and late runs is the averaged C O ing analyses. The early period and late period are defined as 2 2 concentration in the early and late periods, respectively. 1979–1995 and 2002–2018, respectively, with a transition To be comparable to the observation, the early and late period during 1996 − 2001. There are more hot extremes in runs are integrated forward for 22 years with the first 5 years the late period and this difference is statistically significant discarded as spin-up, and the transition run is integrated at the 0.05 level over the five key regions (Fig.  2a). forward for 11 years with the first 5 years discarded (Fer - nando et al. 2016). Thus, each set of sensitivity experiments includes 40 members, with 17 ensembles in early runs (cor-3.2 Role of  CO Change responding to the 17 years in the early period), 17 in late runs (for the late period), and 6 in the transition run (for the First, we conduct the CAM5 experiment by changing the transition period). The definition of hot extremes in each set CO only with climatological SST (CO Exp). The spatial 2 2 of sensitivity experiments is similar to that observed, i.e., distribution of the extremes is either spatially shifted over th by comparing the daily SAT with 90 percentile for that the eastern Asia and western North America or insignificant calendar day among all members (total of 40 in each set). over Europe, northern Africa–western Asia, and Greenland The composite anomaly for an early (late) run in each set is (Fig. 2b). The domain averaged anomaly of hot extremes calculated by subtracting its 40-member average from the days in the CO Exp is obviously smaller than that observed average of the 17 ensembles of the early (late) run in that set. for the northern extratropics and five key regions (Fig.  3a), Table 1 List of main CAM5 Experiments Runs Ensembles SST CO experiments. There are three sets of the sensitivity Control Exp \ 17 Clm Clm experiments. Each experiment CO Exp Early 17 Clm Early includes an early run, a Transition 6 Clm Clm transition run, and a late run. “Clm” denotes climatology of Late 17 Clm Late 1979 − 2018 NH-SST Exp Early 17 Clm + NH SST anomaly (early) Clm Transition 6 Clm Clm Late 17 Clm + NH SST anomaly (late) Clm FULL Exp Early 17 Clm + NH SST anomaly (early) Early Transition 6 Clm Clm Late 17 Clm + NH SST anomaly (late) Late Korean MeteorologicalSociety 1 3 S. Zhao et al. Fig. 1 a Linear trend of the total number of days of hot extremes (shading; days per year) for the period of 1979 − 2018. Black boxes indicate the five key regions. b The domain averaged (20°–80°N, 0°–360°; over land) anomaly of the total number of days of hot extremes th defined by 90 percentile using ERA5 dataset, 1.5 standard deviation using ERA5 dataset, th and 90 percentile using NCEP–NCAR dataset, and the domain averaged (over land) summer mean SAT (°C) using ERA5 from 1979 to 2018. c Difference in summer mean SST (°C) between the late and early periods in the observation. Stippling in a and c indicates regions significant at the 5% level according to the Student’s t-test consistent with the smaller magnitude of the anomaly in the et al. (2017). This result indicates the dominant role of the spatial map. CGT pattern in the summertime temperature variability over We further examine dynamic and thermodynamic fac- the northern extratropics. Observed synoptic eddy kinetic tors associated with hot extremes. In the observation, the energy (EKE; Zhao et al. 2020) based on 2.5–6-day band- summer mean flow shows a positive geopotential height pass-filtered daily winds shows a reduction over mid- and anomaly at 300 hPa, with high-pressure centers over the high-latitudes (Fig. 4a; contours), indicating a weakening eastern Europe, mid-latitude eastern Asia, eastern Siberia, of fast-moving Rossby waves (Coumou et al. 2015, 2018). west coast of North America, and Greenland (Fig. 4a; shad- The relationship between eddy and mean flows, i.e., high ing). The hemispheric-scale circulation anomaly with the pressure anomaly versus low EKE anomaly, can be under- zonal wavenumber-5 structure bears some similarity with stood via a non-modal instability analysis (Zhao et al. 2018, the CGT pattern identified in Teng et al. (2013) and Lee 2020; Zhao and Deng 2020; Mak et al. 2021). Figures 5a and Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… Fig. 2 a Difference in the total number of days of hot extremes (shading; days) between the late and early periods in the observation. b–d Same as in a, but between the late and early run in three sets of CAM5 experiments. Stippling indicates regions significant at the 5% level according to the Student’s t-test. Black boxes indicate the five key regions 6a show observed anomalies of total-cloud cover, SW and The total-cloud cover and surface downward radiations LW, which can act as feedbacks to circulation changes. anomalies are also small in magnitude. The large differ - In the CO Exp, the magnitude of geopotential height ence between the observation and C O Exp can be also 2 2 anomaly over the northern extratropics is underestimated seen in domain averaged fields (Fig.  3). The magnitude (Fig.  4b), accompanied by a misrepresentation of total- of the domain averaged variables (blue bars) is generally cloud cover, SW and LW anomalies, especially over the smaller than that in the observation for the northern extra- five key regions (Figs.  5b  and 6b). For example, over tropics and five key regions. The reason for the difference Europe, the magnitude of upper-level geopotential height is probably because the SST is set as climatology in the and synoptic EKE anomalies is much smaller compared CO Exp. As we know, the majority of excess heat in the to that in the observation. The weak high pressure and Earth system due to rising greenhouse gases (e.g., C O ) strong synoptic activity (characterized by positive synoptic concentration ends up in oceans (e.g., von Schuckmann EKE anomaly) lead to more frequent maritime air masses et al. 2020). movement, creating a wet and cool condition over Europe. Korean MeteorologicalSociety 1 3 S. Zhao et al. Fig. 3 a Observed and simulated anomalies of total number of days cant level according to the Student’s t-test is denoted by error bars. of hot extremes (days) averaged over the northern extratropics and nEX, northern extratropics; EU, Europe; nAF–wAS, northern Africa– five key regions (over land). b–f Same as in a, but for geopotential western Asia; eAS, eastern Asia; wNA, western North America; GL, 2 –2 height at 300 hPa (m), synoptic EKE at 300 hPa (m s ), total-cloud Greenland –2 –2 cover, SW (W m ), and LW (W m ), respectively. The 5% signifi- extremes anomaly in the NH-SST Exp is much closer to 3.3 Role of the NH SST Change the observed pattern. The domain averaged hot extremes anomaly in the NH-SST Exp is also closer to the observa- In this section, we investigate the role of SST in hot tion (Fig. 3a). It is also noted that the hot extremes anomaly extremes. Figure  1c shows that the largest SST anomaly over mid-latitudes (e.g., Europe, eastern Asia, and western (difference between the late and early periods) occurs over North America) is better simulated compared to that over the NH (10°–70°N, 0°–360°), especially for 15°–50°N and high-latitudes (e.g., Greenland). 40°–65°N over the Pacific and Atlantic, respectively. It is Furthermore, the NH-SST Exp generally well simu- interesting to note that the early period (1979–1995) cor- lates the mean and eddy flows over mid-latitudes, despite responds to the positive and negative phases of the Pacific some discrepancies over the Pacific–North American sec- Decadal Oscillation (PDO) and AMO, respectively, while tor (Fig. 4c). In particular, the high pressure and low EKE the late period (2002–2018) is associated with the oppo- anomalies over Europe and eastern Asia are well captured site phases. Moreover, the role of SST over this region (i.e., by the model. Varying degrees of accuracy are shown for 10°–70°N, 0°–360°) in hot extremes is not as known as that clouds and surface downward radiations (Figs. 5c and 6c). over the entire Pacific or Atlantic (e.g., Johnson et al. 2018) For example, the negative anomaly of the total-cloud over and tropics (e.g., Kosaka and Xie 2013). Thus, we focus on the eastern Asia and western North America, and positive the impact of the NH SST on the hot extremes. anomaly over the northern Africa–western Asia are well We conduct an experiment by changing SST over simulated, but the large magnitude of negative anomaly 10°–70°N, 0°–360° with constant CO concentration (NH- over Europe is underestimated (Fig. 5c). As SW is linked to SST Exp). The NH-SST Exp exhibits a positive hot extremes total-cloud cover, similar representation could be found for anomaly over northern mid-latitudes (20°–60°N) (Fig. 2c), SW. The observed positive LW anomaly over the northern especially over four key regions (except for Greenland). Africa–western Asia is also well captured by the NH-SST Compared to the result in the C O Exp, the pattern of hot Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… Fig. 4 a Difference in geopoten- tial height (shading; m) and 2 –2 synoptic EKE (contours; m s ) anomalies at 300 hPa between the late and early periods in the observation. b–d Same as in a, but between the late and early run in three sets of the CAM5 simulations. Red solid and blue dashed lines represent the 2 –2 positive (1.5 and 4.0 m  s ) and negative values (–1.5 and –4.0 2 –2 m  s ), respectively Exp. For the domain averaged variables, their signs are gen- extratropics. This result indicates the effectiveness of the erally same as those in the observation despite their magni- decomposition of the total contribution into CO change and tudes are smaller (Fig. 3). These results suggest that the NH SST change. Compared to Johnson et al. (2018) that applies SST (mainly over 10°–70°N) is able to trigger hot extremes a coupled GCM with nudged SST, the FULL Exp with the anomaly similar to that observed, as well as a good represen- combined SST and C O changes shows a more similar pat- tation of dynamic and thermodynamic factors. tern to the observed hot extremes change over the northern Africa–western Asia and Greenland. Such similarity is likely 3.4 Combined Eec ff ts of the NH SST and  CO to be reflected by prescribing the observed SST change over the NH oceans (where the largest SST anomaly occurs) in The experiment with both NH SST and C O concentra- the AGCM. tion changes (FULL Exp) shows a more similar pattern of Consistent with the result of the hot extremes, the geo- hot extremes change compared to that of the single-change potential height anomaly is well simulated in the FULL experiments, especially over high-latitudes (e.g., Greenland) Exp (except for Greenland), as well as the synoptic EKE (Fig. 2d). Figure 3a shows that the domain averaged anomaly anomaly (Fig. 4d). The circulation anomaly over the Aleu- of hot extremes days in the FULL Exp (5.5 ± 2.7 days) is tian Islands is well represented due to the incorporation of very close to that observed (5.2 ± 2.4 days) over the northern the CO change. Over Europe, eastern Asia, and western Korean MeteorologicalSociety 1 3 S. Zhao et al. Fig. 5 a–d Same as in Fig. 4, but for total-cloud cover (shad- –2 ing) and SW (contours; W m ). Red solid and blue dashed lines represent the positive (4 and –2 10 W  m ) and negative values –2 (–4 and –10 W  m ), respec- tively North America, the observed positive SW anomaly is linked show that the combined effects of the NH SST and CO can to negative total-cloud cover anomaly (Figs. 5a and 6a), due lead to more hot extremes in recent decades, similar to those to cloud albedo effect (NASA Facts 1999). The negative observed. If it were not for the oceans’ capacity to store the total-cloud cover and positive SW anomalies over these three excess heat due to the rising CO concentration, the positive key regions are well captured by the FULL Exp (Fig. 5d). trend in hot extremes days would be substantially reduced In addition, the observed positive total-cloud cover anomaly (i.e., the results in the CO Exp). over the northern Africa–western Asia and Green land leads to the large LW anomaly, due to cloud greenhouse effect 3.5 Role of other Possible Factors (NASA Facts 1999). The large magnitude of LW anomaly over the northern Africa–western Asia could largely explain The aforementioned analyses suggest that SST over the the hot extremes change there and such LW anomaly is well NH (especially 10°–70°N) plays a significant role in hot simulated by the FULL Exp (Fig. 6a, d). For the domain extremes under global warming. To further understand averaged variables, both signs and magnitudes are very simi- individual roles of the North Pacific and North Atlantic, we lar to those in the observation (Fig. 3), further confirming conduct two experiments by changing SST over the North effectiveness of the decomposition of the total contribution Pacific (10°–70°N, 110°E–100°W) and the North Atlan- into CO change and NH SST change. Overall, our results tic (10°–70°N, 80 W°–360°), respectively (Table 2). The Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… Fig. 6 a–d Same as in Fig. 4, –2 but for LW (shading; W m ) result shows that neither basin solely can capture the hot conduct the experiment by changing SST over the tropics extremes change over mid-latitudes (Fig. 7a, b). For com- (20°S–20°N, 0°–360°) (Table 2). Figure 7d shows that the pleteness, we further investigate the impact of the Arctic sea increasing hot extremes over the northern Africa–western ice loss, which was found to be important for hot extremes Asia, western North America (lower latitudes), eastern Asia, over Europe (Zhang et al. 2020). From 1979 to 2018, there and Greenland are well captured by the model, while the was a significant downward trend in the Arctic sea ice and magnitude of such change over the last two regions is much such trend is linked to Arctic amplification (Coumou et al. smaller than that in the observation. Overall, the additional 2018). We conduct the experiment by changing the SIC only experiments suggest that the hot extremes change simulated (Table 2). The result shows that the SIC forcing well cap- by changing North Pacific (or Atlantic) or Arctic SIC is not tures the increasing hot extremes over Europe but misrepre- as significant as that in the observation, while tropical SST sents changes over other key regions (Fig. 7c). In addition, is also an important factor for the hot extremes change. the influence of the tropical SST on northern extratropical As mentioned in previous sections, we focus on and pre- SAT has been documented (e.g., Kosaka and Xie 2013). We scribe the SST anomaly over the NH (especially 10°–70°N) Korean MeteorologicalSociety 1 3 S. Zhao et al. Table 2 List of five additional CAM5 experiments. Each experiment includes an early run, a transition run, and a late run. “Clm” denotes clima- tology of 1979 − 2018 and 1950 − 2018 for the first four experiments and the fifth experiment, respectively Experiments Runs Ensembles SST SIC CO North_Pacific-SST Exp Early 17 Clm + North Pacific SST anomaly (early) Clm Clm Transition 6 Clm Clm Clm Late 17 Clm + North Pacific SST anomaly (late) Clm Clm North_Atlantic-SST Exp Early 17 Clm + North Atlantic SST anomaly (early) Clm Clm Transition 6 Clm Clm Clm Late 17 Clm + North Atlantic SST anomaly (late) Clm Clm SIC Exp Early 17 Clm Clm + SIC anomaly (early) Clm Transition 6 Clm Clm Clm Late 17 Clm Clm + SIC anomaly (late) Clm Tropical-SST Exp Early 17 Clm + tropical SST anomaly (early) Clm Clm Transition 6 Clm Clm Clm Late 17 Clm + tropical SST anomaly (late) Clm Clm NH-SST Exp (1950–2018) Early 30 Clm + NH SST anomaly (early, 1950–1979) Clm Clm Transition 9 Clm Clm Clm Late 30 Clm + NH SST anomaly Clm Clm (late, 1989–2018) Fig. 7 a–d Difference in the total number of days of hot extremes (shading; days) between the late and early run in four sets of additional CAM5 experiments (for the period of 1979–2018). Stippling indicates regions significant at the 5% level according to the Student’s t-test. Black boxes indicate the five key regions Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… because 1) the largest SST anomaly (i.e., difference between the observation, especially less hot extremes during the late the late and early periods) occurs over this region (Fig. 1a) period over the northern Africa–western Asia and eastern and 2) the role of SST over this region is not as known as Asia (Fig. 8b). Without the influence of the phase change of that over the entire Pacific or Atlantic (e.g., Johnson et al. oceanic modes, the increasing hot extremes over these two 2018) and tropics (e.g., Kosaka and Xie 2013). Despite the keys regions is not shown for the analysis with the longer significant role of the NH SST warming, the source for the period. This result indicates that the increasing hot extremes SST warming is still unclear. Previous studies have sug- over these two regions (shown in Fig. 2a, c) are probably gested that the change in SST is related to both anthropo- associated with the certain time period (i.e., 1979–2018) and genic forcing (e.g., C O concentration rising) and natural the influence of the phase change of oceanic modes during variability (Meehl et al. 2009, 2013; Chan and Wu 2015; this period. For other key regions, both anthropogenic forc- Hua et al. 2018; Liguori et al. 2020). In the current study- ing (warming trend) and natural variability (phase change of ing period (1979–2018), the early period corresponds to the PDO and AMO) play a role in the increasing hot extremes. positive and negative phases of the PDO and AMO, respec- tively, while the late period is linked to the opposite phases. It is uncertain whether the hot extremes change is caused by 4 Concluding Remarks the phase change of the oceanic modes or the warming trend of SST (due to anthropogenic forcing). This study investigates possible causes for the increasing To better estimate the effect of anthropogenic forcing hot extremes over the northern extratropics during summer. (i.e., warming trend) versus natural variability (i.e., phase The past four decades have seen an increase of hot extremes, change of PDO and AMO), we analyze observational data accompanied by the NH SST warming and CO concentra- and conduct an experiment for a longer period (1950–2018). tion rising. Through a series of modeling experiments with The early and late periods are defined as 1950–1979 and the CAM5 model, we show that the increase of hot extremes 1989–2018, respectively, with a transition period dur- is largely due to these two factors. However, the rising CO ing 1980 − 1988. Note that the period of 1950–1979 or concentration alone cannot trigger the observed change of 1989–2018 is not associated with a single phase of those hot extremes days, as well as mean and eddy flows, clouds, oceanic modes (e.g., PDO and AMO) and thus we may and surface downward radiations, due to the lack of SST better understand the role of anthropogenic forcing (i.e., adjustment. Due to the oceans’ capacity to store a large warming trend). In the observation, in contrast to Fig. 2a, amount of heat in the Earth system, the incorporation of there are less hot extremes in the late period (1989–2018) the NH SST change strengthens terrestrial warming over over the northern Africa–western Asia and eastern Asia the northern extratropics, as shown by capturing anoma- (Fig.  8a). Then, we conduct an experiment by changing lies of hot extremes days and those dynamic and thermody- SST over 10°–70°N, 0°–360° for 1950–1979 and 1989–2018 namic factors. Specifically, over Europe, eastern Asia, and (Table 2). The hot extremes pattern for the NH-SST Exp western North America, the experiment with both NH SST with the longer period shares some similarities with that in and CO concentration changes (FULL Exp) well simulates Fig. 8 a Difference in the total number of days of hot extremes (shading; days) between the late (1989–2018) and early (1950–1979) period in the observation (using NCEP– NCAR reanalysis data) for the period of 1950–2018. b Same as in a, but between the late and early run in CAM5 NH-SST experiments (for the period of 1950–2018). Stippling indicates regions significant at the 5% level according to the Student’s t-test. Black boxes indicate the five key regions Korean MeteorologicalSociety 1 3 S. Zhao et al. the article's Creative Commons licence and your intended use is not SW radiation, which is modulated by total-cloud cover and permitted by statutory regulation or exceeds the permitted use, you will eddy-mean flows. Over the northern Africa–western Asia need to obtain permission directly from the copyright holder. To view a and Greenland, the FULL Exp faithfully captures LW radia- copy of this licence, visit http://cr eativ ecommons. or g/licen ses/ b y/4.0/ . tion, which is responsible for the increasing hot extremes over these two regions. Finally, our study discusses potential roles of natural variability (e.g., PDO and AMO) and other possible factors (e.g., Arctic sea ice and tropical SST). References One caveat of the current study is that the modeling set- ting in the CAM5 experiments cannot really disentangle Baker, H.S., et al.: Higher C O concentrations increase extreme event risk in a 1.5 °C world. Nat. Clim. 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Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community Atmosphere Model

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Abstract

The past four decades have seen an increase of terrestrial hot extremes during summer in the northern extratropics, accompa- nied by the Northern Hemisphere (NH) sea surface temperature (SST) warming (mainly over 10°–70°N, 0°–360°) and CO concentration rising. This study aims to understand possible causes for the increasing hot extremes, which are defined on a daily basis. We conduct a series of numerical experiments using the Community Atmosphere Model version 5 model for two periods, 1979–1995 and 2002–2018. The experiment by changing the C O concentration only with the climatological SST shows less increase of hot extremes days than that observed, whereas that by changing the NH SST (over 10°–70°N, 0°–360°) with constant C O concentration strengthens the hot extremes change over mid-latitudes. The experiment with both SST and CO concentration changes shows hot extremes change closer to the observation compared to the single-change experi- ments, as well as more similar simulations of atmospheric circulations and feedbacks from cloud and radiative processes. Also discussed are roles of natural variability (e.g., Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation) and other factors (e.g., Arctic sea ice and tropical SST). Keywords Hot extremes · Sea surface temperature · Greenhouse warming · Community Atmosphere Model · Climate change · Natural variability 1 Introduction the northern extratropics have been frequently observed, such as the ones in Europe in 2003 (Schär and Jendritzky Although the increase of the global mean temperature has 2004), Russia in 2010 (Coumou and Rahmstorf 2012), slowed down since the late 1990s (Kosaka and Xie 2013), United States in 2011 (Luo and Zhang 2012), and China terrestrial hot extremes characterized by extreme high sur- in 2013 and 2015 (Sun et al. 2016; Ma et al. 2017). These face air temperature (SAT) have become more frequent in hot extremes resulted in severe damages to ecosystems and recent decades (Perkins-Kirkpatrick and Lewis 2020). Since human society, including forest fires, decreasing agricultural the twenty-first century, severe summer hot extremes over production, and loss of human life (e.g., Ciais et al. 2005; Coumou and Rahmstorf 2012). Indeed, some hot extremes were concomitant with droughts due to strong anti-correla- Communicated by Jin-Ho Yoon. tion between temperature and precipitation during summer over the extratropics (Coumou et al. 2018). Due to disastrous * Siyu Zhao impacts of hot extremes and accompanying droughts, there siyu_zhao@atmos.ucla.edu is an urgent need for better understanding the dynamics and Department of Atmospheric and Oceanic Sciences, physics linked to these extremes. University of California, Los Angeles, Los Angeles, CA, Hot extremes are usually linked to large-scale circulation USA anomalies driving subsidence of air mass (Röthlisberger and School of Civil and Environmental Engineering, Georgia Martius 2019; Tian et al. 2020), cloud changes that mod- Institute of Technology, Atlanta, GA, USA ulate the surface radiation (Jaeger and Seneviratne 2011; School of Earth and Atmospheric Sciences, Georgia Institute Sousa et al. 2018; Tian et al. 2020), and/or enhanced warm of Technology, Atlanta, GA, USA air advection (Sousa et al. 2018). For example, a circum- Shandong Climate Center, Shandong Province global teleconnection (CGT) pattern, characterized by a Meteorological Bureau, Jinan, Shandong, China Korean MeteorologicalSociety Vol.:(0123456789) 1 3 S. Zhao et al. zonal wavenumber-5 structure from an empirical orthogonal on atmospheric circulation change (Shaw and Voigt 2015). function (EOF) analysis, results from internal atmospheric This tug of war on circulations highlights the importance of dynamics and provides the major source of climate variabil- understanding the effect of CO concentration and SST on ity and predictability in northern mid-latitudes, especially hot extremes, which are closely tied to circulations. for U.S. hot extremes (Teng et al. 2013). Ding and Wang Based on previous studies that applied the AGCM to (2005) suggested that the maintenance of the CGT pattern examine the roles of atmospheric composition and SST depends on interactions between the CGT (i.e., Rossby wave in atmospheric circulations, our study adopts a similar train patterns) and Indian summer monsoon (related to the approach to understand their individual and combined effects west-central Asian high). Such CGT pattern was also identi- on terrestrial hot extremes during boreal summer over the e fi d through a self-organizing map (SOM) analysis and tends northern extratropics. We conduct numerical experiments to be linked to the increasing hot extremes over the Northern using CAM version 5 (CAM5) model to investigate how Hemisphere (NH) (Lee et al. 2017).observed CO change and observed SST change influence These proximate drivers can be connected to atmos- the change of hot extremes in recent decades. pheric chemical composition and sea surface temperature (SST) (e.g., Lenderink et al. 2007; Trenberth et al. 2015; Xie et al. 2015; Horton et al. 2016; Baker et al. 2018). For 2 Data and Methodology example, the decadal change of the daytime, nighttime, and compound hot extremes over China is attributed to effects of 2.1 Data anthropogenic forcing, such as those related to greenhouse gas concentrations and anthropogenic aerosol emissions (Su Daily mean observed geopotential height, wind, total-cloud and Dong 2019). The change in global SAT from 1970 to cover, and surface downward shortwave and longwave 2000s is associated with anthropogenic forcing, in combina- radiations (hereafter SW and LW, respectively) are from tion with the effect of surface–atmosphere interactions and the European Centre for Medium Range Weather Forecasts large-scale circulation changes (Tian et al. 2020). Further- Reanalysis 5 (ERA5) on 2.5° × 2.5° spatial grids (Coper- more, the increase of summer hot extremes over the NH land nicus Climate Change Service 2017). Daily mean 2-m air is linked to the Atlantic Multidecadal Oscillation (AMO) (or temperatures is from ERA5 with a resolution of 1.0° and an AMO-like SST pattern) (Johnson et al. 2018; Gao et al. from the National Centers for Environmental Prediction 2019), but the Atlantic SST forced trend in daily maximum (NCEP)–National Center for Atmospheric Research (NCAR) SAT (over land) during 1979–2012 is much weaker in mag- reanalysis with a Gaussian grid (Kalnay et al. 1996). The nitude than that observed (Johnson et al. 2018). SST effects ERA5 and NCEP–NCAR data cover the boreal summer on hot extremes (or global SAT) have also been documented (June–August) for the period of 1979–2018 and 1950–2018, in other studies (e.g., Kosaka and Xie 2013; Watanabe et al. respectively. The monthly mean SST and sea ice concentra- 2014; Dai et al. 2015; Stolpe et al. 2017; Dai and Bloecker tion (SIC) come from the Hadley Centre Sea Ice and Sea 2019). Surface Temperature datasets (HadISST) on 1.0° × 1.0° spa- Many studies have applied an atmospheric general cir- tial grids for the period of 1950–2018 (Rayner et al. 2003). culation model (AGCM) to understand roles of atmos- pheric composition (e.g., CO concentration) and SST in 2.2 Observed Hot Extremes the change of atmospheric circulations. For example, Deser and Phillips (2009) applied the Community Atmosphere At each grid point over the northern extratropics (20°–80°N, Model version 3 (CAM3) model to examine the relative 0°–360°; over land), we define an anomalous hot day when th roles of direct atmospheric radiative forcing (e.g., changes the daily 2-m temperature at the grid point is above 90 per- in well-mixed greenhouse gases) and observed SST change centile for that calendar day over the period of 1979–2018 in global atmospheric circulation trends during boreal winter (Zhao et al. 2017, 2020). Such classifications are performed for 1950–2000. Their results showed that atmospheric radia- for all days and the total number of days of hot extremes tive changes slightly contribute to circulation trends over the in summer is computed for each year. We also use another Atlantic–Eurasian sector in the NH, while the SST change method to define anomalous hot days by comparing the daily largely contributes to the intensification of the Aleutian low. 2-m temperature anomaly (deviation from long-term daily In addition, some studies compared circulation responses to climatology) with the 1.5 standard deviation in daily temper- quadrupled atmospheric CO concentration and to 4 K SST ature for that calendar day. The composite anomalies for an warming using Atmospheric Model Intercomparison Project early/late period (which will be defined later) are calculated (AMIP) runs (e.g., Grise and Polvani 2014; Shaw and Voigt by subtracting the summer climatology from the average 2015, 2016). For example, during summer, CO concentra- of the annual data over that period, with the Student’s t test tion rising and SST warming can result in opposite effects applied to examine the significance. Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… 2.3 CAM5 Experiments3 Results To investigate the individual and combined effects of CO 3.1 Decadal Change of Hot Extremes concentration and SST on hot extremes, we apply the NCAR CAM5 model (Neale et al. 2012), with a grid of 1.9° × 2.5° Figure 1a shows the linear trend of the total number of days (gx1v6) for atmosphere (ocean) and 30 vertical levels in (using the ERA5 dataset and the definition of exceeding the th the atmosphere. The control experiment is forced with the 90 percentile) of hot extremes over the northern extratrop- climatological SST and C O concentration (Table 1). Other ics during the period of 1979 − 2018. The linear trend has the factors (e.g., SIC) that may contribute to hot extremes are largest magnitudes over v fi e key regions: Europe (35°–60°N, set as climatology. The model has been validated by com- 10 W°–50°E), northern Africa–western Asia (20°–35°N, paring the climatological SAT over land in the Control Exp 18 W°–65°E), eastern Asia (20°–60°N, 95°–135°E), west- with that observed. Three sets of sensitivity experiments are ern North America (20°–45°N, 95°–125°W), and Green- conducted with each set including an “early” run, a “tran- land (60°–80°N, 15°–70°W). Such a trend bears a strong sition” run, and a “late” run. The transition run is forced resemblance to the observed trend in daily maximum SAT with the climatological SST and CO concentration. The in Johnson et al. (2018). The domain-averaged anomalies of early and late runs are forced with different combinations hot extremes days and SAT (over land) have a positive trend of SST and CO , similar to the setting in Deser and Phillips (significant at the 0.01 level), with the positive anomaly of (2009). For example, in the FULL Exp, the SST for the early hot extremes days from 2002 (Fig. 1b). The increase of the and late runs is the SST climatology plus monthly mean extremes is not sensitive to either the definition of extremes NH SST anomaly (10°–70°N, 0°–360°) averaged for early or dataset applied. Hence, the ERA5 dataset and the defini- th (1979–1995) and late (2002–2018) periods, respectively; tion of exceeding the 90 percentile are used in the follow- and the C O for the early and late runs is the averaged C O ing analyses. The early period and late period are defined as 2 2 concentration in the early and late periods, respectively. 1979–1995 and 2002–2018, respectively, with a transition To be comparable to the observation, the early and late period during 1996 − 2001. There are more hot extremes in runs are integrated forward for 22 years with the first 5 years the late period and this difference is statistically significant discarded as spin-up, and the transition run is integrated at the 0.05 level over the five key regions (Fig.  2a). forward for 11 years with the first 5 years discarded (Fer - nando et al. 2016). Thus, each set of sensitivity experiments includes 40 members, with 17 ensembles in early runs (cor-3.2 Role of  CO Change responding to the 17 years in the early period), 17 in late runs (for the late period), and 6 in the transition run (for the First, we conduct the CAM5 experiment by changing the transition period). The definition of hot extremes in each set CO only with climatological SST (CO Exp). The spatial 2 2 of sensitivity experiments is similar to that observed, i.e., distribution of the extremes is either spatially shifted over th by comparing the daily SAT with 90 percentile for that the eastern Asia and western North America or insignificant calendar day among all members (total of 40 in each set). over Europe, northern Africa–western Asia, and Greenland The composite anomaly for an early (late) run in each set is (Fig. 2b). The domain averaged anomaly of hot extremes calculated by subtracting its 40-member average from the days in the CO Exp is obviously smaller than that observed average of the 17 ensembles of the early (late) run in that set. for the northern extratropics and five key regions (Fig.  3a), Table 1 List of main CAM5 Experiments Runs Ensembles SST CO experiments. There are three sets of the sensitivity Control Exp \ 17 Clm Clm experiments. Each experiment CO Exp Early 17 Clm Early includes an early run, a Transition 6 Clm Clm transition run, and a late run. “Clm” denotes climatology of Late 17 Clm Late 1979 − 2018 NH-SST Exp Early 17 Clm + NH SST anomaly (early) Clm Transition 6 Clm Clm Late 17 Clm + NH SST anomaly (late) Clm FULL Exp Early 17 Clm + NH SST anomaly (early) Early Transition 6 Clm Clm Late 17 Clm + NH SST anomaly (late) Late Korean MeteorologicalSociety 1 3 S. Zhao et al. Fig. 1 a Linear trend of the total number of days of hot extremes (shading; days per year) for the period of 1979 − 2018. Black boxes indicate the five key regions. b The domain averaged (20°–80°N, 0°–360°; over land) anomaly of the total number of days of hot extremes th defined by 90 percentile using ERA5 dataset, 1.5 standard deviation using ERA5 dataset, th and 90 percentile using NCEP–NCAR dataset, and the domain averaged (over land) summer mean SAT (°C) using ERA5 from 1979 to 2018. c Difference in summer mean SST (°C) between the late and early periods in the observation. Stippling in a and c indicates regions significant at the 5% level according to the Student’s t-test consistent with the smaller magnitude of the anomaly in the et al. (2017). This result indicates the dominant role of the spatial map. CGT pattern in the summertime temperature variability over We further examine dynamic and thermodynamic fac- the northern extratropics. Observed synoptic eddy kinetic tors associated with hot extremes. In the observation, the energy (EKE; Zhao et al. 2020) based on 2.5–6-day band- summer mean flow shows a positive geopotential height pass-filtered daily winds shows a reduction over mid- and anomaly at 300 hPa, with high-pressure centers over the high-latitudes (Fig. 4a; contours), indicating a weakening eastern Europe, mid-latitude eastern Asia, eastern Siberia, of fast-moving Rossby waves (Coumou et al. 2015, 2018). west coast of North America, and Greenland (Fig. 4a; shad- The relationship between eddy and mean flows, i.e., high ing). The hemispheric-scale circulation anomaly with the pressure anomaly versus low EKE anomaly, can be under- zonal wavenumber-5 structure bears some similarity with stood via a non-modal instability analysis (Zhao et al. 2018, the CGT pattern identified in Teng et al. (2013) and Lee 2020; Zhao and Deng 2020; Mak et al. 2021). Figures 5a and Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… Fig. 2 a Difference in the total number of days of hot extremes (shading; days) between the late and early periods in the observation. b–d Same as in a, but between the late and early run in three sets of CAM5 experiments. Stippling indicates regions significant at the 5% level according to the Student’s t-test. Black boxes indicate the five key regions 6a show observed anomalies of total-cloud cover, SW and The total-cloud cover and surface downward radiations LW, which can act as feedbacks to circulation changes. anomalies are also small in magnitude. The large differ - In the CO Exp, the magnitude of geopotential height ence between the observation and C O Exp can be also 2 2 anomaly over the northern extratropics is underestimated seen in domain averaged fields (Fig.  3). The magnitude (Fig.  4b), accompanied by a misrepresentation of total- of the domain averaged variables (blue bars) is generally cloud cover, SW and LW anomalies, especially over the smaller than that in the observation for the northern extra- five key regions (Figs.  5b  and 6b). For example, over tropics and five key regions. The reason for the difference Europe, the magnitude of upper-level geopotential height is probably because the SST is set as climatology in the and synoptic EKE anomalies is much smaller compared CO Exp. As we know, the majority of excess heat in the to that in the observation. The weak high pressure and Earth system due to rising greenhouse gases (e.g., C O ) strong synoptic activity (characterized by positive synoptic concentration ends up in oceans (e.g., von Schuckmann EKE anomaly) lead to more frequent maritime air masses et al. 2020). movement, creating a wet and cool condition over Europe. Korean MeteorologicalSociety 1 3 S. Zhao et al. Fig. 3 a Observed and simulated anomalies of total number of days cant level according to the Student’s t-test is denoted by error bars. of hot extremes (days) averaged over the northern extratropics and nEX, northern extratropics; EU, Europe; nAF–wAS, northern Africa– five key regions (over land). b–f Same as in a, but for geopotential western Asia; eAS, eastern Asia; wNA, western North America; GL, 2 –2 height at 300 hPa (m), synoptic EKE at 300 hPa (m s ), total-cloud Greenland –2 –2 cover, SW (W m ), and LW (W m ), respectively. The 5% signifi- extremes anomaly in the NH-SST Exp is much closer to 3.3 Role of the NH SST Change the observed pattern. The domain averaged hot extremes anomaly in the NH-SST Exp is also closer to the observa- In this section, we investigate the role of SST in hot tion (Fig. 3a). It is also noted that the hot extremes anomaly extremes. Figure  1c shows that the largest SST anomaly over mid-latitudes (e.g., Europe, eastern Asia, and western (difference between the late and early periods) occurs over North America) is better simulated compared to that over the NH (10°–70°N, 0°–360°), especially for 15°–50°N and high-latitudes (e.g., Greenland). 40°–65°N over the Pacific and Atlantic, respectively. It is Furthermore, the NH-SST Exp generally well simu- interesting to note that the early period (1979–1995) cor- lates the mean and eddy flows over mid-latitudes, despite responds to the positive and negative phases of the Pacific some discrepancies over the Pacific–North American sec- Decadal Oscillation (PDO) and AMO, respectively, while tor (Fig. 4c). In particular, the high pressure and low EKE the late period (2002–2018) is associated with the oppo- anomalies over Europe and eastern Asia are well captured site phases. Moreover, the role of SST over this region (i.e., by the model. Varying degrees of accuracy are shown for 10°–70°N, 0°–360°) in hot extremes is not as known as that clouds and surface downward radiations (Figs. 5c and 6c). over the entire Pacific or Atlantic (e.g., Johnson et al. 2018) For example, the negative anomaly of the total-cloud over and tropics (e.g., Kosaka and Xie 2013). Thus, we focus on the eastern Asia and western North America, and positive the impact of the NH SST on the hot extremes. anomaly over the northern Africa–western Asia are well We conduct an experiment by changing SST over simulated, but the large magnitude of negative anomaly 10°–70°N, 0°–360° with constant CO concentration (NH- over Europe is underestimated (Fig. 5c). As SW is linked to SST Exp). The NH-SST Exp exhibits a positive hot extremes total-cloud cover, similar representation could be found for anomaly over northern mid-latitudes (20°–60°N) (Fig. 2c), SW. The observed positive LW anomaly over the northern especially over four key regions (except for Greenland). Africa–western Asia is also well captured by the NH-SST Compared to the result in the C O Exp, the pattern of hot Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… Fig. 4 a Difference in geopoten- tial height (shading; m) and 2 –2 synoptic EKE (contours; m s ) anomalies at 300 hPa between the late and early periods in the observation. b–d Same as in a, but between the late and early run in three sets of the CAM5 simulations. Red solid and blue dashed lines represent the 2 –2 positive (1.5 and 4.0 m  s ) and negative values (–1.5 and –4.0 2 –2 m  s ), respectively Exp. For the domain averaged variables, their signs are gen- extratropics. This result indicates the effectiveness of the erally same as those in the observation despite their magni- decomposition of the total contribution into CO change and tudes are smaller (Fig. 3). These results suggest that the NH SST change. Compared to Johnson et al. (2018) that applies SST (mainly over 10°–70°N) is able to trigger hot extremes a coupled GCM with nudged SST, the FULL Exp with the anomaly similar to that observed, as well as a good represen- combined SST and C O changes shows a more similar pat- tation of dynamic and thermodynamic factors. tern to the observed hot extremes change over the northern Africa–western Asia and Greenland. Such similarity is likely 3.4 Combined Eec ff ts of the NH SST and  CO to be reflected by prescribing the observed SST change over the NH oceans (where the largest SST anomaly occurs) in The experiment with both NH SST and C O concentra- the AGCM. tion changes (FULL Exp) shows a more similar pattern of Consistent with the result of the hot extremes, the geo- hot extremes change compared to that of the single-change potential height anomaly is well simulated in the FULL experiments, especially over high-latitudes (e.g., Greenland) Exp (except for Greenland), as well as the synoptic EKE (Fig. 2d). Figure 3a shows that the domain averaged anomaly anomaly (Fig. 4d). The circulation anomaly over the Aleu- of hot extremes days in the FULL Exp (5.5 ± 2.7 days) is tian Islands is well represented due to the incorporation of very close to that observed (5.2 ± 2.4 days) over the northern the CO change. Over Europe, eastern Asia, and western Korean MeteorologicalSociety 1 3 S. Zhao et al. Fig. 5 a–d Same as in Fig. 4, but for total-cloud cover (shad- –2 ing) and SW (contours; W m ). Red solid and blue dashed lines represent the positive (4 and –2 10 W  m ) and negative values –2 (–4 and –10 W  m ), respec- tively North America, the observed positive SW anomaly is linked show that the combined effects of the NH SST and CO can to negative total-cloud cover anomaly (Figs. 5a and 6a), due lead to more hot extremes in recent decades, similar to those to cloud albedo effect (NASA Facts 1999). The negative observed. If it were not for the oceans’ capacity to store the total-cloud cover and positive SW anomalies over these three excess heat due to the rising CO concentration, the positive key regions are well captured by the FULL Exp (Fig. 5d). trend in hot extremes days would be substantially reduced In addition, the observed positive total-cloud cover anomaly (i.e., the results in the CO Exp). over the northern Africa–western Asia and Green land leads to the large LW anomaly, due to cloud greenhouse effect 3.5 Role of other Possible Factors (NASA Facts 1999). The large magnitude of LW anomaly over the northern Africa–western Asia could largely explain The aforementioned analyses suggest that SST over the the hot extremes change there and such LW anomaly is well NH (especially 10°–70°N) plays a significant role in hot simulated by the FULL Exp (Fig. 6a, d). For the domain extremes under global warming. To further understand averaged variables, both signs and magnitudes are very simi- individual roles of the North Pacific and North Atlantic, we lar to those in the observation (Fig. 3), further confirming conduct two experiments by changing SST over the North effectiveness of the decomposition of the total contribution Pacific (10°–70°N, 110°E–100°W) and the North Atlan- into CO change and NH SST change. Overall, our results tic (10°–70°N, 80 W°–360°), respectively (Table 2). The Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… Fig. 6 a–d Same as in Fig. 4, –2 but for LW (shading; W m ) result shows that neither basin solely can capture the hot conduct the experiment by changing SST over the tropics extremes change over mid-latitudes (Fig. 7a, b). For com- (20°S–20°N, 0°–360°) (Table 2). Figure 7d shows that the pleteness, we further investigate the impact of the Arctic sea increasing hot extremes over the northern Africa–western ice loss, which was found to be important for hot extremes Asia, western North America (lower latitudes), eastern Asia, over Europe (Zhang et al. 2020). From 1979 to 2018, there and Greenland are well captured by the model, while the was a significant downward trend in the Arctic sea ice and magnitude of such change over the last two regions is much such trend is linked to Arctic amplification (Coumou et al. smaller than that in the observation. Overall, the additional 2018). We conduct the experiment by changing the SIC only experiments suggest that the hot extremes change simulated (Table 2). The result shows that the SIC forcing well cap- by changing North Pacific (or Atlantic) or Arctic SIC is not tures the increasing hot extremes over Europe but misrepre- as significant as that in the observation, while tropical SST sents changes over other key regions (Fig. 7c). In addition, is also an important factor for the hot extremes change. the influence of the tropical SST on northern extratropical As mentioned in previous sections, we focus on and pre- SAT has been documented (e.g., Kosaka and Xie 2013). We scribe the SST anomaly over the NH (especially 10°–70°N) Korean MeteorologicalSociety 1 3 S. Zhao et al. Table 2 List of five additional CAM5 experiments. Each experiment includes an early run, a transition run, and a late run. “Clm” denotes clima- tology of 1979 − 2018 and 1950 − 2018 for the first four experiments and the fifth experiment, respectively Experiments Runs Ensembles SST SIC CO North_Pacific-SST Exp Early 17 Clm + North Pacific SST anomaly (early) Clm Clm Transition 6 Clm Clm Clm Late 17 Clm + North Pacific SST anomaly (late) Clm Clm North_Atlantic-SST Exp Early 17 Clm + North Atlantic SST anomaly (early) Clm Clm Transition 6 Clm Clm Clm Late 17 Clm + North Atlantic SST anomaly (late) Clm Clm SIC Exp Early 17 Clm Clm + SIC anomaly (early) Clm Transition 6 Clm Clm Clm Late 17 Clm Clm + SIC anomaly (late) Clm Tropical-SST Exp Early 17 Clm + tropical SST anomaly (early) Clm Clm Transition 6 Clm Clm Clm Late 17 Clm + tropical SST anomaly (late) Clm Clm NH-SST Exp (1950–2018) Early 30 Clm + NH SST anomaly (early, 1950–1979) Clm Clm Transition 9 Clm Clm Clm Late 30 Clm + NH SST anomaly Clm Clm (late, 1989–2018) Fig. 7 a–d Difference in the total number of days of hot extremes (shading; days) between the late and early run in four sets of additional CAM5 experiments (for the period of 1979–2018). Stippling indicates regions significant at the 5% level according to the Student’s t-test. Black boxes indicate the five key regions Korean MeteorologicalSociety 1 3 Understanding the Increasing Hot Extremes over the Northern Extratropics Using Community… because 1) the largest SST anomaly (i.e., difference between the observation, especially less hot extremes during the late the late and early periods) occurs over this region (Fig. 1a) period over the northern Africa–western Asia and eastern and 2) the role of SST over this region is not as known as Asia (Fig. 8b). Without the influence of the phase change of that over the entire Pacific or Atlantic (e.g., Johnson et al. oceanic modes, the increasing hot extremes over these two 2018) and tropics (e.g., Kosaka and Xie 2013). Despite the keys regions is not shown for the analysis with the longer significant role of the NH SST warming, the source for the period. This result indicates that the increasing hot extremes SST warming is still unclear. Previous studies have sug- over these two regions (shown in Fig. 2a, c) are probably gested that the change in SST is related to both anthropo- associated with the certain time period (i.e., 1979–2018) and genic forcing (e.g., C O concentration rising) and natural the influence of the phase change of oceanic modes during variability (Meehl et al. 2009, 2013; Chan and Wu 2015; this period. For other key regions, both anthropogenic forc- Hua et al. 2018; Liguori et al. 2020). In the current study- ing (warming trend) and natural variability (phase change of ing period (1979–2018), the early period corresponds to the PDO and AMO) play a role in the increasing hot extremes. positive and negative phases of the PDO and AMO, respec- tively, while the late period is linked to the opposite phases. It is uncertain whether the hot extremes change is caused by 4 Concluding Remarks the phase change of the oceanic modes or the warming trend of SST (due to anthropogenic forcing). This study investigates possible causes for the increasing To better estimate the effect of anthropogenic forcing hot extremes over the northern extratropics during summer. (i.e., warming trend) versus natural variability (i.e., phase The past four decades have seen an increase of hot extremes, change of PDO and AMO), we analyze observational data accompanied by the NH SST warming and CO concentra- and conduct an experiment for a longer period (1950–2018). tion rising. Through a series of modeling experiments with The early and late periods are defined as 1950–1979 and the CAM5 model, we show that the increase of hot extremes 1989–2018, respectively, with a transition period dur- is largely due to these two factors. However, the rising CO ing 1980 − 1988. Note that the period of 1950–1979 or concentration alone cannot trigger the observed change of 1989–2018 is not associated with a single phase of those hot extremes days, as well as mean and eddy flows, clouds, oceanic modes (e.g., PDO and AMO) and thus we may and surface downward radiations, due to the lack of SST better understand the role of anthropogenic forcing (i.e., adjustment. Due to the oceans’ capacity to store a large warming trend). In the observation, in contrast to Fig. 2a, amount of heat in the Earth system, the incorporation of there are less hot extremes in the late period (1989–2018) the NH SST change strengthens terrestrial warming over over the northern Africa–western Asia and eastern Asia the northern extratropics, as shown by capturing anoma- (Fig.  8a). Then, we conduct an experiment by changing lies of hot extremes days and those dynamic and thermody- SST over 10°–70°N, 0°–360° for 1950–1979 and 1989–2018 namic factors. Specifically, over Europe, eastern Asia, and (Table 2). The hot extremes pattern for the NH-SST Exp western North America, the experiment with both NH SST with the longer period shares some similarities with that in and CO concentration changes (FULL Exp) well simulates Fig. 8 a Difference in the total number of days of hot extremes (shading; days) between the late (1989–2018) and early (1950–1979) period in the observation (using NCEP– NCAR reanalysis data) for the period of 1950–2018. b Same as in a, but between the late and early run in CAM5 NH-SST experiments (for the period of 1950–2018). Stippling indicates regions significant at the 5% level according to the Student’s t-test. Black boxes indicate the five key regions Korean MeteorologicalSociety 1 3 S. Zhao et al. the article's Creative Commons licence and your intended use is not SW radiation, which is modulated by total-cloud cover and permitted by statutory regulation or exceeds the permitted use, you will eddy-mean flows. Over the northern Africa–western Asia need to obtain permission directly from the copyright holder. To view a and Greenland, the FULL Exp faithfully captures LW radia- copy of this licence, visit http://cr eativ ecommons. or g/licen ses/ b y/4.0/ . tion, which is responsible for the increasing hot extremes over these two regions. Finally, our study discusses potential roles of natural variability (e.g., PDO and AMO) and other possible factors (e.g., Arctic sea ice and tropical SST). References One caveat of the current study is that the modeling set- ting in the CAM5 experiments cannot really disentangle Baker, H.S., et al.: Higher C O concentrations increase extreme event risk in a 1.5 °C world. Nat. Clim. 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Journal

"Asia-Pacific Journal of Atmospheric Sciences"Springer Journals

Published: Oct 18, 2021

Keywords: Hot extremes; Sea surface temperature; Greenhouse warming; Community Atmosphere Model; Climate change; Natural variability

References