Large Ensemble Experiments Research Articles

Evaluation of tropical cyclone genesis frequency in FGOALS-g3 large ensemble: mean state and interannual variability

The tropical cyclone genesis frequency (TCGF) is an essential metric for gauging the performance of climate models. Previous evaluations on CMIP family models usually employ one realization for each model and show their diversities in performance. The single model initial condition large ensemble experiments provide a unique opportunity to quantify how internal variability may affect the model evaluation skill. Here, taking the TCGF in the Western North Pacific (WNP) as an example, we use two genesis potential indices as proxies to evaluate the performance of the FGOALS-g3 large ensemble simulation with 110 members. We show that while internal variability does not have a significant influence on the TCGF mean state evaluation, the TCGF-ENSO (El Niño–Southern Oscillation) relationship is significantly modulated by the decadal scale internal variability. For mean state simulation, the FGOALS-g3 large ensembles show reasonable performance in the simulation of TCGF spatial pattern but have differences compared with ERA5 in magnitude. Physical process analysis indicates that compared with ERA5, nearly all dynamic terms are more unfavorable for tropical cyclogenesis due to the cold sea surface temperature anomalies in the midlatitude, while the thermodynamic terms are more conducive to more TCs. For interannual variability, the ENSO-TCGF connection is significantly modulated by the tropical Pacific decadal variability (TPDV) mode by influencing the vertical wind shear in the WNP. Particularly, the model simulation skill depends on the choice of genesis potential indices. Our finding highlights the importance of considering decadal-scale internal variability in the evaluation of interannual ENSO-TCGF variability.

On the association of Pacific Decadal Oscillation with the interdecadal variability in Asian-Pacific Oscillation

The Asian-Pacific Oscillation (APO), featuring a seesaw pattern in the upper-tropospheric temperatures between Asia and the North Pacific, plays profound roles in the Northern Hemispheric climate anomalies. So, its variability and associated physical mechanisms are of great interest. Although progress has been achieved for the APO variability at the interannual time scale, the understanding of its interdecadal variability remains relatively poor. Based on the twentieth-century reanalysis and the simulations of the preindustrial control, Pacific pacemaker, and large ensemble experiments, this study reports a salient contribution of the Pacific Decadal Oscillation (PDO) to the interdecadal variability of the APO during summer, featured as a warm (cold) PDO phase accompanying a negative (positive) APO polarity. During the warm PDO phase, the sea surface temperature (SST) warming over the eastern Pacific is conducive to local ascending anomalies, which teleconnect with descending anomalies over the Tibetan Plateau through zonal vertical circulations. The anomalous ascent (descent) over the eastern Pacific (Tibetan Plateau) tends to strengthen (weaken) the atmospheric heating, beneficial for a warming (cooling) of the troposphere in situ. In addition, the PDO-related meridional SST gradient anomalies favor a southward shift of the subtropical jet stream, weakening the South Asian high and the North Pacific trough in the upper troposphere, which corresponds to the atmospheric situation of a negative APO phase. Quantitative analysis from the large ensemble simulations indicates that the PDO may contribute to approximately 48% of recent APO interdecadal variation from the negative phase to the positive phase in the late 1990s.

Role of the Indian Ocean basin mode in driving the interdecadal variations of summer precipitation over the East Asian monsoon boundary zone

Abstract. Based on long-term observational and reanalysis datasets from 1901 through 2014, this study investigates the characteristics and physical causes of the interdecadal variations in the summer precipitation over the East Asian monsoon boundary zone (EAMBZ), which is a peculiar domain defined from the perspective of the interplay between climatic systems (i.e., mid-latitude westerly and East Asian summer monsoon). Observational evidence reveals that, similarly to previous studies, the EAMBZ precipitation featured prominent interdecadal fluctuations, e.g., with dry summers during the periods preceding 1927, 1939–1945, 1968–1982, and 1998–2010 and wet summers during the periods of 1928–1938, 1946–1967, and 2011 onwards. Further analyses identify that, amongst the major interdecadal oceanic forcings (e.g., Atlantic multidecadal oscillation and Pacific decadal oscillation), the Indian Ocean basin mode (IOBM) is a significant oceanic forcing responsible for the interdecadal variations of the EAMBZ precipitation, playing an independent and critical modulation role. When the cold phase of the IOBM occurs, an anomalous cyclonic circulation is excited around the northeast corner of the tropical Indian Ocean, which further induces a north-low–south-high meridional seesaw pattern over the Northeast China–subtropical western Pacific (SWP) sector. Such seesaw pattern is conducive to the enhanced EAMBZ precipitation by linking favorable environments for the transportation of water vapor from the SWP and the convergence over the EAMBZ at interdecadal timescales. For this reason, a physical–empirical model for the EAMBZ precipitation is developed in terms of the IOBM cooling. Despite the fact that the extreme summer EAMBZ precipitation cannot be captured by this model, it can still well capture its interdecadal fluctuations and reflect their steady relationship. The key physical pathway connecting the IOBM cooling with the interdecadal variations of the summer EAMBZ precipitation is supported by the numerical results based on the large ensemble experiment and the Indian Ocean pacemaker experiment. Our findings may provide new insights into the understanding of the causes of the interdecadal variations in the summer EAMBZ precipitation, which may favor the long-term policy decision-making for the local hydrometeorological planning.

What Controls the December Precipitation Deficit over the Southern Tibetan Plateau and the Northern Indian Continent?

Abstract Winter precipitation is critical for glacier growth, snow accumulation, and terrestrial storage on the Tibetan Plateau (TP). However, less attention has been paid to the changes in winter precipitation on the TP. In this study, based on the newly developed high-accuracy precipitation dataset, our diagnosis illustrated a distinct precipitation deficit over the southern TP and northern Indian continent (STNI) in December. Together with the ERA5 reanalysis, CESM1.1 large ensemble experiments, and pacemaker experiments, the dynamic diagnosis revealed that the precipitation deficit was attributed to the decrease in dynamic effects. In particular, the enhanced descending motion, accompanied by the strengthened anticyclone and regional meridional circulation over the STNI, resulted in the precipitation deficit. The changes in circulation system related to the precipitation deficit could be attributed to the Pacific and Indian sea surface temperature (SST) variability. With the negative interdecadal Pacific oscillation (IPO), there were circumglobal alternative geopotential height anomalies and an anomalous anticyclone over the southern TP, and descending motion around the STNI associated with the enhanced Walker circulation over the Indo-Pacific, which exhibited a similar pattern to the precipitation deficit over the STNI in the observations. In addition, the synergistic effect of Pacific and Indian SST variability can improve the simulated precipitation deficit over the STNI relative to the Pacific SST variability alone. These results imply a contribution of the tropical SST variability to the precipitation trends over the STNI in early winter and provide an insight into the understanding of climate warming on the winter climate over the TP.

Quantifying the uncertainty in the Eurasian ice-sheet geometry at the Penultimate Glacial Maximum (Marine Isotope Stage 6)

Abstract. The North Sea Last Interglacial sea level is sensitive to the fingerprint of mass loss from polar ice sheets. However, the signal is complicated by the influence of glacial isostatic adjustment driven by Penultimate Glacial Period ice-sheet changes, and yet these ice-sheet geometries remain significantly uncertain. Here, we produce new reconstructions of the Eurasian ice sheet during the Penultimate Glacial Maximum (PGM) by employing large ensemble experiments from a simple ice-sheet model that depends solely on basal shear stress, ice extent, and topography. To explore the range of uncertainty in possible ice geometries, we use a parameterised shear-stress map as input that has been developed to incorporate bedrock characteristics and the influence of ice-sheet basal processes. We perform Bayesian uncertainty quantification, utilising Gaussian process emulation, to calibrate against global ice-sheet reconstructions of the Last Deglaciation and rule out combinations of input parameters that produce unrealistic ice sheets. The refined parameter space is then applied to the PGM to create an ensemble of constrained 3D Eurasian ice-sheet geometries. Our reconstructed PGM Eurasian ice-sheet volume is 48±8 m sea-level equivalent (SLE). We find that the Barents–Kara Sea region displays both the largest mean volume and volume uncertainty of 24±8 m SLE while the British–Irish sector volume of 1.7±0.2 m SLE is the smallest. Our new workflow may be applied to other locations and periods where ice-sheet histories have limited empirical data.

Exploring the Future Rainfall Characteristics over India from Large Ensemble Global Warming Experiments

We investigated rainfall patterns over India for the period from 1951 to 2010 and predicted changes for the next century (2051–2100) with an assumed 4K warming from large ensemble experiments (190 members). We focused on rainfall patterns during two periods of present-day climate (1951–1980 and 1981–2010) and their projected changes for the near and far future (2051–2080 and 2081–2110). Our analysis found that the northeastern region of India and some southern regions received higher rainfall during the period of 1951–2010, which is consistent with daily observations from the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE). In the warming climate, rainfall events in India are predicted to carry more precipitation, with the northeast and southern regions experiencing stronger rainfall events. The frequency and intensity of these events (with more than 20 mm of rainfall per day, on average) are also expected to increase. Overall, our study suggests that water-related disasters such as flooding and landslides could be much worse in India in the future due to climate warming.

Influence of internal variability on future changes in extreme wind speed over North America

Internal variability plays an important role in the projection of climate and extreme climate changes at regional scales. Here, we use large ensemble experiments from two different climate models [the Canadian Earth System Model Large Ensemble (CanESM2-LE) with 50 members and the Community Earth System Model Large Ensemble (CESM1-LE) with 40 members to investigate the influence of internal variability on the projection of extreme wind speed (extreme WS) in the future (2081–2100) relative to the present climatology (1986–2005) over North America. Generally, the spatial patterns of future changes in extreme WS across members in both ensembles exhibit quite large diversity for the whole year and winter, while consistent changes among members are found in summer. This indicates that the influence of internal variability on the future changes in extreme WS is higher in winter than summer. With enough members, the forced responses allow direct comparisons to demonstrate the model uncertainty. Increases in wintertime extreme WS at high latitudes and around the Hudson Bay, as well as decreases over the west-central USA and along the southwest coast of the domain, are largely influenced by the external forcing with small model uncertainty. Regions within the 40°–60°N latitudinal band of the domain are projected to experience external forced decrease in extreme WS in summer with high model consistency. Results from high-resolution of dynamical downscaling large ensemble simulations (CanRCM4-LE) are comparable with those of its driving models (CanESM2-LE) and can provide detailed information in regions with sea–land contrast and complex topography, which is of great vital for the local policy maker.

Quantifying the Human Influence on the Intensity of Extreme 1- and 5-Day Precipitation Amounts at Global, Continental, and Regional Scales

Abstract This study provides a comprehensive analysis of the human contribution to the observed intensification of precipitation extremes at different spatial scales. We consider the annual maxima of the logarithm of 1-day (Rx1day) and 5-day (Rx5day) precipitation amounts for 1950–2014 over the global land area, four continents, and several regions, and compare observed changes with expected responses to external forcings as simulated by CanESM2 in a large-ensemble experiment and by multiple models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). We use a novel detection and attribution analysis method that is applied directly to station data in the areas considered without prior processing such as gridding, spatial or temporal dimension reduction, or transformation to unitless indices and uses climate models only to obtain estimates of the space–time pattern of extreme precipitation response to external forcing. The influence of anthropogenic forcings on extreme precipitation is detected over the global land area, three continental regions (the western Northern Hemisphere, western Eurasia, and eastern Eurasia), and many smaller IPCC regions, including central North America, East Asia, east-central Asia, eastern Europe, eastern North America, northern Europe, and western Siberia for Rx1day, and central North America, eastern Europe, eastern North America, northern Europe, the Russian Arctic region, and western Siberia for Rx5day. Consistent results are obtained using forcing response estimates from either CanESM2 or CMIP6. Anthropogenic influence is estimated to have substantially decreased the approximate waiting time between extreme annual maximum events in regions where anthropogenic influence has been detected, which has important implications for infrastructure design and climate change adaptation policy. Significance Statement All previous detection and attribution studies of observed changes in extreme precipitation (i) use station data that has been heavily processed via gridding, transformation, and spatial and temporal averaging or other dimension reduction approaches, as well as using climate models to estimate the responses to external forcing, and (ii) also use models to estimate the unforced natural variability of extreme precipitation. Both aspects reduce user confidence in detection and attribution results. This study uses station data directly and avoids difficult to verify model-based estimates of the unforced variability of precipitation extremes. Results confirm findings from previous studies, and extend them to a number of subcontinental regions, thus substantially increasing confidence in detection and attribution findings precipitation.

Changing El Niño–Southern Oscillation in a warming climate

Originating in the equatorial Pacific, the El Niño–Southern Oscillation (ENSO) has highly consequential global impacts, motivating the need to understand its responses to anthropogenic warming. In this Review, we synthesize advances in observed and projected changes of multiple aspects of ENSO, including the processes behind such changes. As in previous syntheses, there is an inter-model consensus of an increase in future ENSO rainfall variability. Now, however, it is apparent that models that best capture key ENSO dynamics also tend to project an increase in future ENSO sea surface temperature variability and, thereby, ENSO magnitude under greenhouse warming, as well as an eastward shift and intensification of ENSO-related atmospheric teleconnections — the Pacific–North American and Pacific–South American patterns. Such projected changes are consistent with palaeoclimate evidence of stronger ENSO variability since the 1950s compared with past centuries. The increase in ENSO variability, though underpinned by increased equatorial Pacific upper-ocean stratification, is strongly influenced by internal variability, raising issues about its quantifiability and detectability. Yet, ongoing coordinated community efforts and computational advances are enabling long-simulation, large-ensemble experiments and high-resolution modelling, offering encouraging prospects for alleviating model biases, incorporating fundamental dynamical processes and reducing uncertainties in projections. The El Niño–Southern Oscillation (ENSO) has global climatic implications, necessitating understanding of its observed and projected changes. This Review brings together knowledge of ENSO in a warming climate, revealing projected increases in ENSO magnitude, as well as ENSO-related rainfall and sea surface temperature variability.

Detecting Climate Signals Using Explainable AI With Single‐Forcing Large Ensembles

AbstractIt remains difficult to disentangle the relative influences of aerosols and greenhouse gases on regional surface temperature trends in the context of global climate change. To address this issue, we use a new collection of initial‐condition large ensembles from the Community Earth System Model version 1 that are prescribed with different combinations of industrial aerosol and greenhouse gas forcing. To compare the climate response to these external forcings, we adopt an artificial neural network (ANN) architecture from previous work that predicts the year by training on maps of near‐surface temperature. We then utilize layer‐wise relevance propagation (LRP) to visualize the regional temperature signals that are important for the ANN's prediction in each climate model experiment. To mask noise when extracting only the most robust climate patterns from LRP, we introduce a simple uncertainty metric that can be adopted to other explainable artificial intelligence (AI) problems. We find that the North Atlantic, Southern Ocean, and Southeast Asia are key regions of importance for the neural network to make its prediction, especially prior to the early‐21st century. Notably, we also find that the ANN predictions based on maps of observations correlate higher to the actual year after training on the large ensemble experiment with industrial aerosols held fixed to 1920 levels. This work illustrates the sensitivity of regional temperature signals to changes in aerosol forcing in historical simulations. By using explainable AI methods, we have the opportunity to improve our understanding of (non)linear combinations of anthropogenic forcings in state‐of‐the‐art global climate models.

Decadal phase shift of summertime Arctic dipole pattern and its nonlinear effect on sea ice extent

AbstractThe rapid decline in Arctic sea ice during recent decades has been attributed to the combined influence of global warming and internal climate variability. Herein, we elucidate the process by which the decrease in sea ice is accelerated in association with the decadal phase shift of the Arctic dipole (AD), using observational data and Community Earth System Model (CESM1) simulations. The influence of the AD on Arctic sea ice varied according to its phase; in the negative‐AD decades (1979–1998), atmospheric circulation during summers of positive phase AD acts to reduce the sea ice extent (SIE) in the Pacific sector but increases it in the Atlantic sector. In contrast, in the positive‐AD decades (after 1999), the same atmospheric circulation pattern reduces the SIE in both sectors, resulting in enhanced sea ice melting across the entire Arctic region. A similar nonlinear relationship between the AD phase and SIE change is also observed in CESM1 Pre‐Industrial simulations, which stem from altered background temperature conditions between periods, implying the significant role of internal variability, particularly over the Atlantic sector. However, contrary to the recently observed AD trend, CESM1 Large Ensemble experiments predicted a negative AD trend as global warming proceeded. This suggests that the recent positive AD phase may be naturally driven, but the current state of sea ice decline associated with AD could be altered in the near future because of enhanced global warming.

Snow on Arctic Sea Ice in a Warming Climate as Simulated in CESM.

Earth system models are valuable tools for understanding how the Arctic snow‐ice system and the feedbacks therein may respond to a warming climate. In this analysis, we investigate snow on Arctic sea ice to better understand how snow conditions may change under different forcing scenarios. First, we use in situ, airborne, and satellite observations to assess the realism of the Community Earth System Model (CESM) in simulating snow on Arctic sea ice. CESM versions one and two are evaluated, with V1 being the Large Ensemble experiment (CESM1‐LE) and V2 being configured with low‐ and high‐top atmospheric components. The assessment shows CESM2 underestimates snow depth and produces overly uniform snow distributions, whereas CESM1‐LE produces a highly variable, excessively‐thick snow cover. Observations indicate that snow in CESM2 accumulates too slowly in autumn, too quickly in winter‐spring, and melts too soon and rapidly in late spring. The 1950–2050 trends in annual mean snow depths are markedly smaller in CESM2 (−0.8 cm decade−1) than in CESM1‐LE (−3.6 cm decade−1) due to CESM2 having less snow overall. A perennial, thick sea‐ice cover, cool summers, and excessive summer snowfall facilitate a thicker, longer‐lasting snow cover in CESM1‐LE. Under the SSP5‐8.5 forcing scenario, CESM2 shows that, compared to present‐day, snow on Arctic sea ice will: (1) undergo enhanced, earlier spring melt, (2) accumulate less in summer‐autumn, (3) sublimate more, and (4) facilitate marginally more snow‐ice formation. CESM2 also reveals that summers with snow‐free ice can occur ∼30–60 years before an ice‐free central Arctic, which may promote faster sea‐ice melt.

Impact of air\u2013sea coupling on the probability of occurrence of heat waves in Japan

In extreme event attribution, which aims to answer whether and to what extent a particular extreme weather event can be attributed to global warming, the probability of an event is generally estimated through large ensemble simulations, using an atmospheric general circulation model (AGCM). In islands, such as Japan, it has been considered that surface air temperature (SAT) can be significantly affected by the surrounding sea surface temperature (SST), which mostly is affected by atmospheric circulation at mid- and high-latitudes. Therefore, the absence of SST responses to atmospheric variability in AGCMs impacts the estimation of the occurrence of extreme events, such as heat waves in Japan. In this study, we examined the impact of air–sea coupling on the probability of occurrence of severe heat waves that occurred in Japan in the summer of 2010 by analyzing the probability differences obtained from AGCM and coupled general circulation model (CGCM) large-ensemble experiments. The observed ocean temperature, salinity, and sea ice were assimilated in the 100-member CGCM experiments, as they were assigned as boundary conditions in the 100-member AGCM experiments. The SAT around Japan in the northern summer is largely related to the Bonin high, whose interannual variability is largely affected by the Silk Road and Pacific-Japan (PJ) pattern teleconnections in the real world. The SAT anomaly over Japan was related to the pressure variability due to the Silk Road and PJ patterns in the CGCM experiment. By contrast, the SAT over Japan simulated by AGCM was less sensitive to such pressure variability, and the SAT ensemble spread became narrower in AGCM. The results suggest that the probability of occurrence of the 2010 heat wave in Japan would tend to be underestimated by the AGCM ensemble compared to the CGCM ensemble, provided that the ensemble averages of the SAT anomalies were equal between CGCM and AGCM experiments. This study raised the issue of the absence of SST response to atmospheric variability in AGCMs, which can critically impact the estimation of extreme event probability, particularly in mid-latitude islands, such as Japan.

The role of internal climate variability in projecting Antarctica\u2019s contribution to future sea-level rise

Retreat of the Antarctic ice sheet (AIS) is likely to be a major contributor to future sea-level rise (SLR). Current projections of SLR due to ice-sheet mass loss remain highly uncertain. Better understanding of how ice sheets respond to future climate forcing and variability is essential for assessing long-term risk of SLR. However, predictability of future climate is limited by uncertainties from emission scenarios, model structural differences, and internal climate variability (ICV) that is inherently generated within the fully coupled climate system. Among those uncertainties, the impact of ICV on the AIS changes has not been explicitly assessed. Here we quantify the effects of ICV on the AIS evolutions by employing climate fields from two large-ensemble experiments using the Community Earth System Model to force a three-dimensional ice-sheet model. We find that ICV of climate fields among ensemble members leads to significantly different AIS responses, and that most of the effect is due to atmospheric variability compared to oceanic. Our results show that ICV can cause about 0.08 m differences of AIS contribution to SLR by 2100 compared to the ensemble-mean AIS contribution of 0.38–0.45 m. Moreover, using ensemble-mean climate forcing fields as the forcing in an ice-sheet model significantly delays retreat of the West AIS for up to 20 years and significantly underestimates the AIS contribution to SLR by 0.07–0.11 m in 2100 and up to 0.34 m in the 2250’s. This study highlights the need to take internal climate variability into account in assessing uncertainty associated with the AIS contribution in sea-level rise projections.

A Mechanism for the Arctic Sea Ice Spring Predictability Barrier

AbstractThe decline of Arctic sea ice extent has created a pressing need for accurate seasonal predictions of regional summer sea ice. Recent work has shown evidence for an Arctic sea ice spring predictability barrier, which may impose a sharp limit on regional forecasts initialized prior to spring. However, the physical mechanism for this barrier has remained elusive. In this work, we perform a daily sea ice mass (SIM) budget analysis in large ensemble experiments from two global climate models to investigate the mechanisms that underpin the spring predictability barrier. We find that predictability is limited in winter months by synoptically driven SIM export and negative feedbacks from sea ice growth. The spring barrier results from a sharp increase in predictability at melt onset, when ice‐albedo feedbacks act to enhance and persist the preexisting export‐generated mass anomaly. These results imply that ice thickness observations collected after melt onset are particularly critical for summer Arctic sea ice predictions.

Evaluation for Characteristics of Tropical Cyclone Induced Heavy Rainfall over the Sub-basins in The Central Hokkaido, Northern Japan by 5-km Large Ensemble Experiments

Previous studies have shown that the acceleration of global warming will increase the intensity of rainfall induced by tropical cyclones (TCs) (hereinafter referred to as “TC-induced rainfall”). TC-induced rainfall is affected by TC position and topography (slope shape and direction). Thus, TC-induced rainfall is expected to vary by sub-basin due to varying topographies. However, these relationships have not been explained, as historical TCs, which occurred several decades earlier, do not exhaustively encompass all TC positions that could potentially affect each basin. We used large ensemble regional climate model experiments with 5 km grid spacing, which enabled us to prepare a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins. We quantified the characteristics of TC-induced rainfall (rainfall volume, relationship between TC position and rainfall intensity, and contribution of TC intensity on rainfall) over four sub-basins in the Tokachi River basin, central Hokkaido, northern Japan. The results reveal differences in TC-induced rainfall characteristics between the sub-basins. In addition, the large ensemble data under a future climate scenario were used to evaluate future changes in the characteristics of TC-induced rainfall for each sub-basin.

A Regime Perspective on the North Atlantic Eddy-Driven Jet Response to Sudden Stratospheric Warmings

AbstractChanges to the preferred states, or regime behavior, of the North Atlantic eddy-driven jet (EDJ) following a major sudden stratospheric warming (SSW) is examined using a large ensemble experiment from the Canadian Middle Atmosphere Model in which the stratosphere is nudged toward an SSW. In the 3 months following the SSW (January–March), the North Atlantic EDJ shifts equatorward by ~3°, on average; this arises from an increased occurrence of the EDJ’s south regime and reductions in its north and central regimes. Qualitatively similar behavior is shown in a reanalysis dataset. We show that under SSW conditions the south regime becomes more persistent and that this can explain the overall increase in the EDJ latitude decorrelation time scale. A cluster analysis reveals that, following the SSW, the south EDJ regime is characterized by weaker low-level baroclinicity and eddy heat fluxes in the North Atlantic Ocean. We hypothesize, therefore, that the increased persistence of the south regime is related to the weaker baroclinicity leading to slower growth rates of the unstable modes and hence a slower buildup of eddy heat flux, which has been shown to precede EDJ transitions. In the North Atlantic sector, the surface response to the SSW projects onto a negative North Atlantic Oscillation (NAO) pattern, with almost no change in the east Atlantic (EA) pattern. This behavior appears to be distinct from the modeled intrinsic variability in the EDJ, where the jet latitude index captures variations in both the NAO and EA patterns. The results offer new insight into the mechanisms for stratosphere–troposphere coupling following SSWs.

Projected Changes of Extremely Cool Summer Days over Northeastern Japan Simulated by 20 km-mesh Large Ensemble Experiment

Projected Changes of Extremely Cool Summer Days over Northeastern Japan Simulated by 20 km-mesh Large Ensemble Experiment

Potential Impacts of Anthropogenic Forcing on the Frequency of Tropical Depressions in the North Indian Ocean in 2018

Fourteen tropical depressions formed in the North Indian Ocean during 2018—the most active season since 1986 and the second most active season since 1980. Among the 14 tropical depressions during 2018, seven developed into cyclonic storms, with five intensifying into severe cyclonic storms—three of which became very severe cyclonic storms. The sea surface temperature anomaly associated with El Niño appears to have played a minor role in shaping this extreme event (i.e., the 14 tropical depressions in the North Indian Ocean). Using large ensemble experiments performed by the Community Earth System Model developed by the National Center for Atmospheric Research, we detected an important role potentially played by anthropogenic forcing in increasing the risk of the 14 tropical depressions in the North Indian Ocean that were observed in the active 2018 season. Moreover, the projection experiments suggest a rising frequency of tropical depressions in the second half of the 21st century.

Strong Influence of Aerosol Reductions on Future Heatwaves

AbstractUsing the Community Earth System Model Large Ensemble experiments, we investigate future heatwaves under the Representative Concentration Pathway 8.5 scenario, separating the relative roles of greenhouse gas increases and aerosol reductions. We show that there will be more severe heatwaves (in terms of intensity, duration, and frequency) due to mean warming, with minor contributions from future temperature variability changes. While these changes come primarily from greenhouse gas increases, aerosol reductions contribute significantly over the Northern Hemisphere. Furthermore, per degree of global warming, aerosol reductions induce a significantly stronger response in heatwave metrics relative to greenhouse gas increases. The stronger response to aerosols is associated with aerosol‐cloud interactions, which are still poorly understood and constrained in current climate models. This suggests that there may exist large uncertainties in future heatwave projections, highlighting the critical significance of reducing uncertainties in aerosol‐cloud interactions for reliable projection of climate extremes and effective risk management.