Coupled Model Intercomparison Project Phase Research Articles

Fractional change of scattering and absorbing aerosols contributes to Northern Hemisphere Hadley circulation expansion

The relative amount of scattering and absorbing aerosols is essential in determining the aerosol radiative and climate effects. Using reanalysis datasets and climate simulations, here, we show that changes in the relative amount of scattering and absorbing aerosols in the Northern Hemisphere (NH) high latitudes, manifested as long-term decreasing trends in aerosol single-scattering albedo (SSA), have played an important role in driving the widening and weakening trends of the NH Hadley circulation (HC) since the early 1980s. Decreasing SSA in the NH middle and high latitudes can notably warm the troposphere there, thus reducing the equator-to-pole temperature gradient, increasing static stability in mid-latitude regions, and leading to the widening and weakening trends of NH HC. Further analysis of the Coupled Model Intercomparison Project Phase 6 (CMIP6) aerosol forcing–only simulations also supports the importance of SSA trends in perturbing NH HC through the above mechanism.

The Summer North Atlantic Oscillation, Arctic sea ice, and Arctic jet Rossby wave forcing

We use Coupled Model Intercomparison Project Phase 6 (CMIP6) coupled and Atmospheric Model Intercomparison Project (AMIP) climate models, dynamical analyses, and observations to investigate interactions between summer Arctic sea ice concentration (SIC) variations and the Summer North Atlantic Oscillation (SNAO). Observations suggest that SIC-SNAO relationships mainly come from the East Siberian to Arctic Canada (ESAC) region where a weak atmospheric jet stream exists in summer. Twelve CMIP6 models with the most realistic atmospheric climatologies over the North Atlantic and Europe agree well with reanalyses on relationships between SIC and Northern Hemisphere atmospheric circulation. CMIP6 model data indicate that ESAC SIC influences the SNAO with a lead time of several weeks. However, AMIP simulations do not reproduce the observed atmospheric circulation when observed sea ice is prescribed. Rossby wave analyses do though support observed ESAC SIC influences on the SNAO. We conclude that ESAC Arctic SIC modestly influences the SNAO, and such investigations require the use of coupled models.

Future changes in rainfall variability for the mainland Indochina southwest monsoon

Researching future changes in rainfall variability is critical for mitigating the possible effects of global warming, especially in areas where vulnerability is high, such as Indochina. While changes in mean and extreme rainfall have received a great deal of attention, rainfall variability has been poorly researched, despite its importance. We endeavored to determine the anticipated changes in rainfall variability during the mainland Indochina southwest monsoon (MSWM) by utilizing data derived from 5 ensemble models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Employing band pass filtering techniques on daily rainfall data, we discerned variability across an expansive spectrum of temporal scales. Our research indicates that, in the event of global warming, the variability in MSWM rainfall is expected to increase by approximately 10-25% throughout the whole region. Notably, this increased unpredictability appears uniformly throughout a wide range of time intervals. Changes in average rainfall significantly aid in explaining the majority of the intermodal variance in the predicted MSWM rainfall variability. To gain further insight into this phenomenon, we examined the effects of elevated atmospheric moisture content through the estimation of modifications resulting from idealized local thermodynamic enhancement. We showed that increased atmospheric moisture, as suggested by the Clausius-Clapeyron relation, accounts for most of the predicted changes in rainfall variability at all time scales.

Evaluating Wheat Cultivation Potential in Ethiopia Under the Current and Future Climate Change Scenarios

Land suitability analyses are crucial for identifying sustainable areas for agricultural crops and developing appropriate land use strategies. Thus, the present study aims to analyze the current and future land suitability for wheat (Triticum aestivum L.) cultivation in Ethiopia. Twelve variables including soil properties, climate variables, and topographic characteristics were used in the evaluation of land suitability. Statistical methods such as Rotated Empirical Orthogonal Functions (REOF), Coefficient of Variation (CV), correlation, and parametric and non-parametric trend analyses were used to analyze the spatiotemporal variability in current and future climate data and identified significant patterns of variability. For future projections of land suitability and climate, this study employed climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) framework, downscaled using regional climate model version 4.7 (RegCM4.7) under two different Shared Socioeconomic Pathway (SSP) climate scenarios: SSP1 (a lower emission scenario) and SSP5 (a higher emission scenario). Under the current condition, during March, April, and May (MAM), 53.4% of the country was suitable for wheat cultivation while 44.4% was not suitable. In 2050, non-suitable areas for wheat cultivation are expected to increase by 1% and 6.9% during MAM under SSP1 and SSP5 climate scenarios, respectively. Our findings highlight that areas currently suitable for wheat may face challenges in the future due to altered temperature and precipitation patterns, potentially leading to shifts in suitable areas or reduced productivity. This study also found that the suitability of land for wheat cultivation was determined by rainfall amount, temperature, soil type, soil pH, soil organic carbon content, soil nitrogen content, and elevation. This research underscores the critical importance of integrating spatiotemporal climate variability with future projections to comprehensively assess wheat suitability. By elucidating the implications of climate change on wheat cultivation, this study lays the groundwork for developing effective adaptation strategies and actionable recommendations to enhance management practices. The findings support the county’s commitment to refining agricultural land use strategies, increasing wheat production through suitability predictions, and advancing self-sufficiency in wheat production. Additionally, these insights can empower Ethiopia’s agricultural extension services to guide farmers in cultivating wheat in areas identified as highly and moderately suitable, thereby bolstering production in a changing climate.

Extremes of Temperature and Precipitation Under CMIP6 Scenarios Projections Over Central Hokkaido, Japan

ABSTRACTClimate extreme events are intensifying globally, posing increasing risks across various sectors. Understanding climate extremes' spatiotemporal patterns and responses to climate change is crucial for effective management, especially on a regional scale. This study examines temperature and precipitation extremes, as well as compound dry‐hot events (CDHEs), in the Ishikari River basin (IRB) of Northeastern Japan, an area of significant socioeconomic importance. We focus on spatiotemporal analysis under multiple scenarios of temperature/precipitation extremes and CDHEs based on statistical downscaled datasets from the Coupled Model Intercomparison Project Phase 6. Results indicate that IRB underwent increased trends of extreme hot periods, extreme droughts, and heavy rainfalls during 1985–2014, which are significantly affected by the North Pacific Oscillation and Southern Oscillation Index. Future projections show that warming temperatures and less rainfall shift asymmetrical impacts on temperature and precipitation extremes, expecting increased warm spells and CDHEs but increased wet durations and less heavy rainfalls. Emission scenarios analysis suggests low‐emission scenarios (SSP1‐2.6) could mitigate their exacerbations, especially for CDHEs (decreased by 139%). Moreover, spatial‐pattern analysis reveals regional heterogeneity in temperature and precipitation extremes, with northern mountainous regions more susceptible to thermal extremes and southern plain regions (e.g., Sapporo city) experiencing prolonged drought and CDHEs. This study provides valuable insights into climate risk management and adaptation strategies.

Improved simulation of compound drought and heat extremes in eastern China through CWRF downscaling

Abstract Given their profound socio-economic impact and increasing occurrence, compound drought and heat extremes (CDHEs) have become a focal point of widespread concern. Studies have attempted to reproduce and predict these extremes using general circulation models (GCMs); however, the performance of these models in capturing compound events remains controversial. This study presents an improved simulation of CDHE trends over eastern China by using the regional Climate-Weather Research and Forecasting model (CWRF) to downscale the projections of two GCMs that participated in the Coupled Model Intercomparison Project Phase 6. The results show that CWRF downscaling significantly improved the underestimation of CDHE trends in GCM historical simulations, aligning better with observed trends. Moreover, the improvements of CWRF downscaling in simulating CDHEs are more pronounced than those for univariate events, i.e. extreme drought and extreme heat events. This enhancement largely results from CWRF’s better representation of land-atmosphere interaction processes, as indicated by the more realistic spatial distributions and intensities of the land-atmosphere coupling strength index. Under the SSP245 and SSP585 scenario, CWRF downscaling again predicts a more rapid increase in regional mean CDHE frequency compared to GCMs, with values nearing or exceeding 0.4 by the mid-21st century, suggesting a significant future threat to the study region. This study highlights the important role of land-atmosphere interactions in shaping CDHEs and the efficacy of regional climate models to reduce uncertainty in compound event simulations.

Role of the warm Arctic cold Eurasian-like pattern on the near future warming rate of East Asian surface temperature

Abstract Internal climate variability (ICV) plays an important role in either accelerating or slowing down the rate of surface temperature warming in East Asia in the near future. To examine the influence of ICV on East Asian surface temperature in the near future, we mainly analyzed the data sets obtained from Max Planck Institute Grand Ensemble model simulations under the Representative Concentration Pathway 8.5 scenario. It is found that the ICV associated with the so-called Warm Arctic-Cold Eurasian (WACE)-like pattern contributes to the near-future warming rate of East Asian surface temperature. Similar results are also obtained from large ensemble model simulations participating in the Coupled Model Intercomparison Project Phase 6 under the Shared Socioeconomic Pathways 5-8.5 scenario. This implies that the near-term warming rate in East Asia could vary depending on how the climate model simulates the WACE-like pattern, indicating that the ability to accurately simulate ICV in climate models is crucial for future climate mitigation and adaptation policies.

Global record-breaking recurrence rates indicate more widespread and intense surface air temperature and precipitation extremes.

We analyzed the evolution of extreme annual surface air temperature and rainfall on Earth, based on the recurrence rate of record-breaking events, and found the highest recurrence rates for record-high annual temperatures in the tropics, as opposed to the polar regions with the fastest warming. Both recurrence rates and the global surface area fraction with daily mean surface air temperatures exceeding 30° and 40°C provide further evidence for extremely hot years becoming more common and widespread. A similar analysis for precipitation highlighted some regions with more record-high annual total precipitation and others with record-low annual precipitation typically associated with drought. A multimodel ensemble of 306 runs with global climate models [Coupled Model Intercomparison Project phase 6 (CMIP) Shared Socioeconomic Pathways 2-45 (SSP2-45)] reproduced the statistics of record-breaking high temperatures, but there were some differences for the reanalysis precipitation record-breaking recurrence rates. The global climate model simulations suggested a slightly altered geographical pattern for record-breaking annual precipitation recurrence rates.

Processes Driving the Intermodel Spread of the Southern Hemisphere Hadley Circulation Expansion in CMIP6 Models

AbstractThe Hadley circulation (HC) has been expanding poleward in recent decades. The Coupled Model Intercomparison Project Phase 6 (CMIP6) models predict that the expansion will accelerate in the future, more so in the Southern Hemisphere (SH). However, the extent of the expansion varies widely among the models. We investigate the mechanisms driving the intermodel spread in SH HC expansion predictions. The intermodel spread is obtained by an empirical orthogonal function analysis on the SH HC trend patterns of 16 CMIP6 model simulations using the historical and shared socioeconomic pathway 5–8.5 scenarios. The leading mode, showing a mean meridional stream function anomaly at the poleward SH HC extent, explains 49.73% of the variance and significantly correlates (r = 0.94) with the SH HC expansion. By analyzing the extended Kuo‐Eliassen equation, we find that the intermodel difference in the representation of diabatic heating is responsible for about 14% of the intermodel spread. The meridional eddy momentum and heat fluxes contribute to about 21% and 18% of the intermodel spread, respectively. The models simulating a relatively large SH HC expansion tend to show increased precipitation in the Southern Pacific Convergence Zone, reduced baroclinic instability in the subtropics, and an enhanced poleward shift of jet stream in the midlatitudes. This suggests that the uncertainty in the HC projection may be constrained by reducing the bias in the trend of the mean fields.

Ensemble modeling of the hydrological impacts of climate change: a case study of the Baro River Sub-basin, Ethiopia

ABSTRACT Given the Baro River basin's high climatic variability and frequent flooding, climate change is expected to exacerbate the existing issues in the region. Three best-performing climate models from Coupled Model Intercomparison Project phase 6 (CMIP6) were used to examine the potential impact of climate change on the hydrology of the Baro River Basin. The ensemble of the climate models were bias-corrected for the climate change analysis and a calibrated and validated Soil and Water Assessment Tool (SWAT) model was used to examine the impact of the climate changes under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) in the future (2031–2060). The climate change scenarios projected an increase in precipitation and temperature under all scenarios. Consequently, annual increase in surface runoff, water yield, and potential evapotranspiration (PET) was reported by 30.33% (44.67%), 6% (18.1%,), and 4.49% (6.63%) and decline in groundwater by 13.17% (2.64%) under shared socioeconomic pathway, SSP2-4.5 (SSP5-8.5), respectively. The rise in temperature and PET could be responsible for the decline in groundwater, while the projected increase in precipitation is expected to enhance surface runoff, perhaps leading to flooding. This requires an improved water management policy that involves all sectors and takes into account the equity for different users.

Assessing Alterations of Rainfall Variability Under Climate Change in Zengwen Reservoir Watershed, Southern Taiwan

This study aims to detect changes in rainfall variability caused by climate change for various scenarios in the CMIP6 (Coupled Model Intercomparison Project Phase 6) multi-model ensemble. Projected changes in rainfall unevenness in terms of different timescale indices using three categories, namely WD50 (number of wettest days for half annual rainfall), SI (seasonality index), and DWR (ratio of dry-season to wet-season rainfall) are analyzed in Zengwen Reservoir watershed, southern Taiwan over near future (2021–2040) and midterm future (2041–2060) relative to the baseline period (1995–2014) under SSP2-4.5 and SSP5-8.5 scenarios. The projected rainfall for both baseline and future periods is derived from 25 GCMs (global climate models). The results indicate that noticeably deteriorated rainfall unevenness is projected in the Zengwen Reservoir watershed over future periods, which include decreased WD50, increased SI, and decreased DWR. Though there were noticeable differences in the rainfall projections by the different GCMs, the overall consensus reveals that uncertainties in future rainfall should not be ignored. In addition, WD50 has the greatest deviated relative change in mean, which implies that the short-timescale rainfall unevenness index is easily affected by climate change in the study area. Distributional changes in rainfall unevenness determined by simultaneously considering alterations in relative changes in mean and standard deviation indicated that there was no single dominant category. However, the top two categories, with summed frequencies exceeding 0.5, characterize different properties of rainfall unevenness indices. The top two categories of WD50 and SI commonly have decreased mean and increased mean, respectively, but nearly equal frequencies of the top two categories in DWR exhibit opposite variations. The proposed rainfall unevenness change detection approach provides a better understanding of the impacts of climate change on rainfall unevenness, which is useful for preparing adaptive mitigation measures for coping with disasters induced by climate change.

Influence of Model Resolution on Wind Energy Simulations over Tibetan Plateau Using CMIP6 HighResMIP

The assessment of wind energy resources is critical for the transition from fossil fuel to renewable energy sources. Using the outputs from high-resolution global climate models (GCMs), such as the High Resolution Model Intercomparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6), has become one of the most important tools in wind energy research. This study evaluated the reliability of the 22 GCMs available in the HighResMIP-PRIMAVERA project by simulating the wind energy climatology and variability over the Tibetan Plateau (TP) with reference to observations and investigated the differences in performance of the GCMs between high-resolution (HR) and low-resolution (LR) simulations. The results show that most models performed relatively well in simulating the probability distribution of the observed wind speed over the TP, but nearly half of the models generally underestimated the wind speed, whereas the others tended to overestimated the wind speed. Compared with the wind speed, the GCMs showed larger biases in reproducing the wind power density (WPD) and other wind energy resources, whereas the biases in multi-model ensembles were relatively smaller than those in most individual models. With respect to interannual variability, both the HR and LR models failed to capture interannual variations in WPD over the TP. Furthermore, more than half of the HR GCMs had a reduced bias relative to the corresponding LR GCMs, indicating the good performance of most HR models in simulating wind energy resources over the TP in terms of spatial pattern and temporal variability. However, the overall performance of HR GCMs varied among models, which suggests that solely improving the horizontal resolution is not sufficient to completely solve the uncertainties and deficiencies in the simulation of wind energy over complex terrain.

Projecting dry-wet abrupt alternation across China from the perspective of soil moisture

Under a warmer climate, the enhancement of dry-wet abrupt alternation (DWAA) risk poses a great challenge for sustainable development. Here, we introduce a novel framework for DWAA detection based on our proposed soil moisture concentration index. By the end of this century, over humid southern China, the shift of soil moisture time series from anomalously wet to anomalously dry pattern, or the other way around, will be more abrupt. In addition, the proposed framework driven by Coupled Model Intercomparison Project Phase 6 simulations projects more widespread DWAA-affected areas over southwestern China, coastal regions of southeastern China, and the lower reaches of the Yangtze River, especially under a high emission scenario. The framework proposed in this study provides an efficient system for DWAA detection and prediction, and the findings of this study provide a reference for upgrading hydraulic infrastructure and mitigating future DWAA events.

Recent impact of reduced arctic sea-ice on the winter North Atlantic jet stream and its quantitative contributions compared to pre-industrial level

It has been a challenge to identify the impact of Arctic sea-ice loss on the intensity and position of the winter North Atlantic jet stream (NAJS) and the related mechanisms due to the uncertain effects of atmospheric internal variability. This study investigates the response of the winter NAJS to Arctic sea-ice loss and roughly estimates the contribution of internal variability in Arctic sea ice (ArcSIC) after the pre-industrial period, based on reanalysis dataset (referred to as observation here), the Coupled Model Inter-comparison Project phase 6 (CMIP6) and the Polar Amplification Model Inter-comparison Project (PAMIP). The results indicate that the majority of PAMIP models display robust but weak equatorward shift of the NAJS response to Arctic sea-ice loss, as well as robust NAJS-related circulation anomalies. Further analysis shows that the ability of models to reproduce observed NAJS response is primarily associated with tropospheric baroclinic wave activity and the troposphere–stratosphere coupling. Based on 20th-Century reanalysis data and CMIP6 historical simulations, we further estimate the relative contributions of external forcing and internal variability (including reduced ArcSIC) to NAJS latitude and speed variability. Compared to the pre-industrial period, the recent winter NAJS at 850 hPa has accelerated and shifted poleward. By calculating the ratio of the difference in NAJS speed (latitude) between the present-day and pre-industrial in CMIP6 multi-model ensemble mean to the difference in observation, this study approximately estimates that the external forcing contributes about 40 % of NAJS acceleration with minimal influence on its shift. The remaining acceleration and poleward shift are mainly attributed to internal variability. The difference between the present-day and pre-industrial PAMIP ensemble mean is considered as the “pure” forcing of Arctic sea-ice loss. Most models indicate that reduced ArcSIC tends to slow down the acceleration and poleward shift of winter NAJS, but show quantitively a wide range of uncertainty.

The Shifting Distribution of Arctic Daily Temperatures Under Global Warming

AbstractWe examine daily surface air temperatures (SAT) in the Arctic under global warming, synthesizing changes in mean temperature, variability, seasonality, and extremes based on five Earth system model large ensembles from the Coupled Model Intercomparison Project Phase 6. Our analysis shows that the distribution of daily Arctic SAT changes substantially, with Arctic mean temperatures being distinguishable from pre‐industrial levels on 84% and 97% of days at 1.5 and 2°C of global warming, respectively, and on virtually every day at 3°C of global warming. This shift is primarily due to the rapid rise in average temperature resulting from Arctic amplification and is exacerbated by a decrease in the variability of daily Arctic SAT of approximately 8.5% per degree of global warming. The changes in mean temperature and variability are more pronounced in the cold seasons than in summer, resulting in a weakened and shifted seasonal cycle of Arctic SAT. Moreover, the intensity and frequency of warm and cold extreme events change to varying degrees. The hottest days warm slightly more, while the coldest days warm 4–5 times more than the global average temperature, making extreme cold events rare. Changes in local SAT vary regionally across the Arctic and are most significant in areas of sea‐ice loss. Our findings underscore the Arctic's amplified sensitivity to global warming and emphasize the urgent need to limit global warming to mitigate impacts on human and natural systems.

Identification of thresholds and key drivers on Water Use Efficiency in different maize ecoregions in Yellow River Basin of China

Identifying the constrains on water use efficiency (WUE) of crops along a wet-to-dry gradient is important due to irrigation water scarcity, as well as the increasing drought risk under climate change in China. This study coupled five high-resolution climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6) with the Decision Support System for Agrotechnology Transfer (DSSAT)-CERES-Maize model to quantify drought risk and the drivers affecting WUE in five major maize ecoregions of the Yellow River Basin (YRB) under three future scenarios (SSP126, SSP370, and SSP585) for both the historical baseline (1985-2014) and three future periods: 2021-2040 (2030s), 2041-2070 (2050s), and 2071-2100 (2080s). And a bias correction method was implemented for the crop model to analyze optimal WUE thresholds for maize across varying dry-wet gradients. The results indicated that future drought risk will likely persist in the YRB under all scenarios, but with regional differences in drought severity and frequency. The southwestern region (V) experienced the highest frequency of drought (62.50%-SSP126), while the northwestern region (III) exhibited the lowest frequency (33.00%-SSP585) in 2030s, and 83.30% of areas in the southwestern (V) showed significant wetting in the 2080s under SSP126. The bias-corrected CERES-Maize model effectively simulated crop yield and evapotranspiration (ET), resulting in an average reduction of 4.00% and 9.73% in normalized root mean square error (nRMSE) respectively. Distinct WUE thresholds ranging from 1.96 to 8.41 kg ha−1 mm-1 were observed across various scenarios-periods in the maize regions, mostly under slight and moderate dry/wet conditions. Notably, all SSP585 scenarios demonstrated a decrease in WUE thresholds compared to the baseline. Across all scenarios and periods, WUE was mainly driven by yield in the eastern regions (I and II) but by ET in the western regions (III, IV, and V). These findings suggest that regions experiencing varying degrees of drought severity should undergo differentiated management and optimization of agricultural practices to improve WUE under future climate scenarios.

Revisiting the inconsistent influence of El Niño-Southern Oscillation on the equatorial Atlantic

Abstract The impact of El Niño-Southern Oscillation (ENSO) on the equatorial Atlantic Zonal Mode (AZM) is investigated using two atmospheric reanalysis products and 44 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). While the impact of ENSO on equatorial Atlantic SST is inconsistent, as previously reported, there is a very robust influence of decaying ENSO events in boreal spring on the contemporaneous surface zonal winds over the equatorial Atlantic, with El Niño events associated with anomalous easterlies that cool the equatorial Atlantic. This dynamic impact is counteracted by a thermodynamic impact, in which El Niño events cause changes in surface heat fluxes that lead to warming over the tropical Atlantic. The thermodynamic influence is active throughout the lifecycle of the ENSO event, but the dynamic influence is highly seasonal with a pronounced peak in boreal spring. Thus, a quickly decaying El Niño event will lead to warming, while a slowly decaying event will lead to cooling in the equatorial Atlantic. The ENSO-AZM relation is further complicated by partially independent Atlantic variability, in particular that associated with the South Atlantic subtropical dipole (SASD). Prediction experiments with a simple linear regression model support the role of the SASD as an AZM precursor. Many CMIP6 models show skillful predictions of the June-July-August AZM based on SST indices in the preceding December-January-February, with correlations above 0.5. When predictions are restricted to ENSO years, even more models exceed this threshold, but skill in the reanalyses remains relatively low, possibly due to insufficient training data.

Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future

Northeast China plays a crucial role as a major grain-producing region, and attention to its land use and land cover changes (LUCC), especially farmland changes, are crucial to ensure food security and promote sustainable development. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data and a decision tree model, land types, especially those of paddy fields in Northeast China from 2000 to 2020, were extracted, and the spatiotemporal changes in paddy fields and their drivers were analyzed. The development trends of paddy fields under different future scenarios were explored alongside the Coupled Model Intercomparison Project Phase 6 (CMIP6) data. The findings revealed that the kappa coefficients of land use classification from 2000 to 2020 reached 0.761–0.825, with an overall accuracy of 80.5–87.3%. The proposed land classification method can be used for long-term paddy field monitoring in Northeast China. The LUCC in Northeast China is dominated by the expansion of paddy fields. The centroids of paddy fields gradually shifted toward the northeast by a distance of 292 km, with climate warming being the main reason for the shift. Under various climate scenarios, the temperature in Northeast China and its surrounding regions is projected to rise. Each scenario is anticipated to meet the temperature conditions necessary for the northeastward expansion of paddy fields. This study provides support for ensuring sustainable agricultural development in Northeast China.

Future shifts in climatic conditions promoting northward expansion of the Mediterranean climate in the circum-Mediterranean region.

In the upcoming decades, precipitation and temperature patterns are expected to shift in the Mediterranean basin due to global warming, potentially having an influence on the environment and the economy in the area. Using monthly precipitation and temperature data from 15 global climate models (GCMs) developed as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Mediterranean Climate Envelop (MCE), as defined by Daget's (1977) criteria, is projected under two climate change scenarios: SSP2-4.5 and SSP5-8.5, and for two future periods: 2050s and 2070s. According to the findings, the MCE is expected to expand by 3.51 and 4.93% in the 2050s under the SSP2-4.5 and SSP5-8.5 scenarios, respectively, in comparison to the current state. This expansion is expected to reach 5.28 and 9.87% for SSP2-4.5 and SSP5-8.5, respectively, in 2070s. For both situations and durations, MCE contraction would be minor, however, at less than 1%. More than 99% of the present MCE would stay stable proportionately. The northern Mediterranean region is mostly concerned by the MCE's expansion. The SSP2-4.5 scenario predicts that by the 2070s, expansion zones will occupy 674,183 km2, with 64% of the area located in Southern Europe and 36% in Western Asia. In SSP5-8.5 scenario, this area is expected to be significantly larger, estimated to be approximately 1,256,881 km2; 67% in Southern Europe and 33% in Western Asia.

Influence of SST‐Precipitation Relationship Over the Equatorial Western Pacific on Simulation of the Madden‐Julian Oscillation

AbstractCapabilities of 43 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the Madden‐Julian Oscillation (MJO) were compared in this study. Models with higher MJO simulation skills reproduce organized large‐scale convection more frequently over the equatorial western Pacific (EWP), suggesting that MJO simulations are tightly connected to organization of large‐scale precipitation over the EWP. MJO simulation skills are not significantly correlated with the mean sea surface temperature (SST) over the EWP, but tightly connected to SST threshold for convection there. The top simulations exhibit lower SST threshold and more realistic SST‐precipitation relationship over the EWP, suggesting that convection can be organized more efficiently and intensified more rapidly with the increasing SST in these simulations. Our results emphasize that reproducing the relationship between SST and large‐scale precipitation over the EWP is critical to MJO simulations.