Planck Institute Earth System Model Research Articles

Acceleration of the Hydrological Cycle under Global Warming for the Poyang Lake Basin in Southeast China: An Age-Weighted Regional Water Tagging Approach

Abstract Global warming is assumed to accelerate the global water cycle. However, quantification of the acceleration and regional analyses remain open. Accordingly, in this study, we address the fundamental hydrological question: Is the water cycle regionally accelerating/decelerating under global warming? For our investigation, we have implemented the age-weighted regional water tagging approach into the Weather Research and Forecasting (WRF) Model, namely, WRF-age, to follow the atmospheric water pathways and to derive atmospheric water residence times defined as the age of tagged water since its source. We apply a three-dimensional online budget analysis of the total, tagged, and aged atmospheric water into WRF-age to provide a prognostic equation of the atmospheric water residence times and to derive atmospheric water transit times defined as the age of tagged water since its source originating from a particular physical or dynamical process. The newly developed, physics-based WRF-age model is used to regionally downscale the reanalysis of ERA-Interim and the Max Planck Institute Earth System Model (MPI-ESM) representative concentration pathway 8.5 scenario exemplarily for an East Asian monsoon region, i.e., the Poyang Lake basin (the tagged water source area), for historical (1980–89) and future (2040–49) times. In the warmer (+1.9°C for temperature and +2% for evaporation) and drier (−21% for precipitation) future, the residence time for the tagged water vapor will regionally decrease by 1.8 h (from 14.3 h) due to enhanced local evaporation contributions, but the transit time for the tagged precipitation will increase by 1.8 h (from 12.9 h) partly due to slower fallout of precipitating moisture components. Significance Statement Global warming is assumed to accelerate the global water cycle. However, quantification of the acceleration and regional analyses remain open. This study presents the newly developed WRF-age model that allows us to follow the atmospheric water pathways, to derive atmospheric water residence times and atmospheric water transit times. We exemplarily show for an East Asian monsoon region that global warming leads to regionally decreased residence time for the tagged water vapor in the atmosphere due to enhanced local contributions, but increased transit time for the tagged precipitation over the land surface that is partly attributed to slower fallout of precipitating moisture components in the atmosphere. These findings reveal the physical mechanisms behind dry-getting-drier at regional scales.

Arctic climate response to European radiative forcing: a deep learning study on circulation pattern changes

Abstract. Heterogeneous radiative forcing in mid-latitudes, such as that exerted by aerosols, has been found to affect the Arctic climate, though the mechanisms remain debated. In this study, we leverage deep learning (DL) techniques to explore the complex response of the Arctic climate system to local radiative forcing over Europe. We conducted sensitivity experiments using the Max Planck Institute Earth System Model (MPI-ESM1.2) coupled with atmosphere–ocean–land-surface components. Large-scale circulation patterns can mediate the impact of the forcing on Arctic climate dynamics. We employed a DL-based clustering approach to classify large-scale atmospheric circulation patterns. To enhance the analysis of how these patterns impact the Arctic climate, the poleward moist static energy transport (PMSET) associated with the atmospheric circulation patterns was incorporated as an additional similarity metric in the clustering process. Furthermore, we developed a novel method to analyze the circulation patterns' contributions to various climatic parameter anomalies. Our findings indicate that the negative radiative forcing over Europe alters existing circulation patterns and their occurrence frequency without introducing new ones. Specifically, our analysis revealed that while the regional radiative forcing alters the occurrence frequencies of the circulation patterns, these changes are not the primary drivers of the forcing's impact on the Arctic parameters. Instead, it is the shifts in the mean spatial characteristics of the atmospheric circulation patterns, induced by the forcing, that predominantly determine the effects on the Arctic climate. Our methodology facilitates the uncovering of complex, nonlinear interactions within the climate system, capturing nuances that are often obscured in broader seasonal anomaly analyses. This approach enables a deeper understanding of the dynamics driving observed climatic anomalies and their links to specific atmospheric circulation patterns.

Hydrological response to climate change in Baro basin, Ethiopia, using representative concentration pathway scenarios

Droughts and floods are common in the Baro basin and climate change may exacerbate them. This study aimed to investigate the hydrological response to climate change’s impact in the Baro River basin. Four climate models namely, Hadley Centre Global Environmental Model, version 2 (HadGEM2-ES), Max Planck Institute Earth System Model—Low Resolution (MPI-ESM-LR), Coupled Model Version 5, Medium Resolution (CM5A-MR) and European Community Earth System Model (EC-Earth) dynamically downscaled outputs were obtained from Africa coordinated regional downscaling experiment program. The four climate models were evaluated using a suite of statistical measures such as bias, Root Mean Squared Error, and Coefficient of Variation. The bias of the simulated rainfall varies between − 4.20% and − 25.39% suggesting underestimation. The performance of the models differs subject to the performance measures used for evaluation. Before being used in the climate impact analysis, the climate model data was heavily skewed and needed correction. In terms of bias, HadGEM2-ES performed the worst while EC-Earth performed the best. MPI-ESM-LR was the worst performer in terms of RMSE and CM5A-MR was the best. Changes in the hydrological response to climate change were compared to the baseline scenario (1971–2000) under the Representative Concentration Pathway Scenarios (RCP 4.5) for the medium term (2041–2070). The GCM predictions for the RCP 4.5 scenarios suggested that, in the medium period (2041–2070) the maximum temperature in the Baro River basin will probably rise by 2.1 °C for MPI-ESM-LR and 2.49 °C for CM5A-MR, while the minimum temperature would likely climb by 1.7 °C to EC-Earth and 2.8 °C for HadGEM2-ES. Annual rainfall is expected to fall by 7.02% for CM5A-MR and 17.01% for HadGEM2-ES, while annual evapotranspiration potential is likely to rise. Except from March to May CM5A-MR consistently generated the greatest amount of streamflow change, while MPI-ESM-LR consistently generated the highest magnitude of streamflow change. The annual streamflow reduction is consistent with the annual precipitation reduction and increased annual potential evapotranspiration. Generally, climate change is predicted to have a significant impact on the hydrological response in the Baro River basin under the RCP 4.5 scenario.

Increasing aerosol direct effect despite declining global emissions in MPI-ESM1.2

Abstract. Anthropogenic aerosol particles partially mask global warming driven by greenhouse gases, both directly by reflecting sunlight back to space and indirectly by increasing cloud reflectivity. In recent decades, emissions of anthropogenic aerosols have declined globally and at the same time shifted from the North American and European regions, foremost to Southeast Asia. Using simulations with the Max Planck Institute Earth System Model version 1.2 (MPI-ESM1.2), we find that the direct effect of aerosols has continued to increase despite declining emissions. Concurrently, the indirect effect has diminished in approximate proportion to the emissions. In this model, which employs parameterized aerosol effects with constant regional direct effect efficiency, the enhanced efficiency of aerosol radiative forcing in emissions is associated with less cloud masking, longer atmospheric residence times, and differences in aerosol optical properties.

Contribution of internal variability to the Mongolian Plateau summer precipitation trends in MPI-ESM large-ensemble model

Summer precipitation over the Mongolian Plateau (MP) has experienced a consistent decline in recent decades. While the influence of atmospheric wave train on this reduction in precipitation has been recognized in prior studies, this study delves deeper into the physical mechanisms and quantifies the contributions of the internal atmosphere and oceanic variations to the diminishing precipitation utilizing a comprehensive 100-member ensemble simulations from the Max Planck Institute Earth System Model (MPI-ESM). Results show that the ensemble-mean precipitation in MP exhibits a positive trend and cannot explain the observed results. The precipitation trends vary significantly among individual ensemble members, highlighting the pivotal role of internal variability. The leading EOF mode of precipitation trends among ensemble members exhibits uniform variations. Further investigations reveal that the internal summer precipitation in MP is affected by the internal atmospheric circulation, the remote influence of the North Atlantic Dipole sea surface temperature (SST) anomalies, and Pacific Decadal Oscillation-like SST patterns. An eastward-propagating Rossby wave originating from the North Atlantic dipole SST anomalies provides the anomalous large-scale circulation that influences summer precipitation. The PDO contributes to reinforcing the anticyclonic anomaly over the MP. Additionally, the uncertainty of precipitation trends in MPI-ESM can be reduced by 13% through removing the internal atmospheric wave train-related precipitation variation, while oceanic factors only contribute about 7% uncertainty of precipitation variations. Our insights enhance the understanding of the physical drivers behind summer precipitation variability in the MP and effectively quantify the uncertainties stemming from internal variability.

The Role of the Aleutian Low in the Relationship between Spring Pacific Meridional Mode and Following ENSO

Abstract The spring Pacific meridional mode (PMM) is an important precursor of El Niño–Southern Oscillation (ENSO). However, recent studies reported that only about half of the spring PMM events were followed by ENSO events. This study examines the role of internal climate variability in modulating the impact of PMM on ENSO using 100-member ensemble simulations of the Max Planck Institute Earth System Model (MPI-ESM). The relationship between spring PMM and following winter ENSO shows a large spread among the 100 members. The variation of spring Aleutian low (AL) intensity is identified to be an important factor modulating the PMM–ENSO relation. The spring AL affects the PMM–ENSO relationship by modifying PMM-generated low-level zonal wind anomalies over the tropical western Pacific. The strengthening of the spring AL is accompanied by westerly wind anomalies over the midlatitude northwestern Pacific, leading to sea surface temperature (SST) cooling there via an enhancement of upward surface heat flux. This results in increased meridional SST gradient and leads to northerly wind anomalies over the subtropical northwestern Pacific, which turn to surface westerly wind anomalies after reaching the equatorial western Pacific due to the conservation of potential vorticity. Thus, the low-level westerly (easterly) wind anomalies over the tropical western Pacific associated with the positive (negative) spring PMM were strengthened (weakened), which further contributes to an enhanced (a weakened) PMM–ENSO relation. The mechanism for the modulation of the AL on the spring PMM–ENSO relationship is verified by a set of AGCM simulations. This study suggests that the condition of the spring AL should be considered when predicting ENSO on the basis of the PMM. Significance Statement Spring Pacific meridional mode (PMM) is a predictor of ENSO, but not all spring PMM events are accompanied by the occurrence of ENSO events. This study aims to explore the influence of internal climate variability on the relationship between spring PMM and following ENSO. It is revealed that the Aleutian low exerts a crucial modulation on the spring PMM–ENSO relationship. The underlying physical mechanisms for the impact of the Aleutian low on the relationship between spring PMM and ENSO are further examined. The results of this study have important implications for improving the prediction of ENSO.

Decadal Predictability of Seasonal Temperature Distributions

AbstractDecadal predictions focus regularly on the predictability of single values, like means or extremes. In this study we investigate the prediction skill of the full underlying surface temperature distributions on global and European scales. We investigate initialized hindcast simulations of the Max Planck Institute Earth system model decadal prediction system and compare the distribution of seasonal daily temperatures with estimates of the climatology and uninitialized historical simulations. In the analysis we show that the initialized prediction system has advantages in particular in the North Atlantic area and allow so to make reliable predictions for the whole temperature spectrum for two to 10 years ahead. We also demonstrate that the capability of initialized climate predictions to predict the temperature distribution depends on the season.

Pan‐Arctic distribution modeling reveals climate‐change‐driven poleward shifts of major gelatinous zooplankton species

AbstractAnthropogenic activities, including climate change, are hypothesized to cause increases in gelatinous zooplankton population sizes and blooms. In the most rapidly changing ecosystem, the Arctic Ocean, this hypothesis has not yet been verified, and gelatinous zooplankton is commonly excluded from large‐scale modeling studies. Our modeling study is based on an extensive biogeographic dataset, aggregating from four open‐source databases (Ocean Biodiversity Information System, Global Biodiversity Information Facility, Jellyfish Database Initiative, and PANGAEA). It includes data on eight of the most reported gelatinous zooplankton taxa of the pan‐Arctic region (Aglantha digitale, Sminthea arctica, Periphylla periphylla, Cyanea capillata, Oikopleura vanhoeffeni, Fritillaria borealis, Mertensia ovum, and Beroe spp.). By coupling three‐dimensional species distribution models with oceanographic components from the Max Planck Institute Earth System Model (MPI‐ESM1.2), run for historical (1950–2014) and future (2050–2099) periods under the shared socioeconomic pathway SSP370 scenario forcing, we identified species with expanding or contracting habitat ranges in response to climate change. Our projections indicated a general tendency for gelatinous zooplankton distributions to shift, with varying degrees of suitable habitat expansion (largest for the scyphozoan C. capillata ~ +180%) or contraction (largest for the hydrozoan Sm. arctica ~ −15%). Seven of the eight species modeled, which—similar to the majority of gelatinous taxa occurring in the Arctic Ocean—predominantly represented arcto‐boreal and boreal taxa, are projected to shift to northern latitudes. Hence, profound impacts on the Arctic marine environment and associated ecosystem services can be expected.

Improving seasonal predictions of German Bight storm activity

Abstract. Extratropical storms are one of the major coastal hazards along the coastline of the German Bight, the southeastern part of the North Sea, and a major driver of coastal protection efforts. However, the predictability of these regional extreme events on a seasonal scale is still limited. We therefore improve the seasonal prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) large-ensemble decadal hindcast system for German Bight storm activity (GBSA) in winter. We define GBSA as the 95th percentiles of three-hourly geostrophic wind speeds in winter, which we derive from mean sea-level pressure (MSLP) data. The hindcast system consists of an ensemble of 64 members, which are initialized annually in November and cover the winters of 1960/61–2017/18. We consider both deterministic and probabilistic predictions of GBSA, for both of which the full ensemble produces poor predictions in the first winter. To improve the skill, we observe the state of two physical predictors of GBSA, namely 70 hPa temperature anomalies in September, as well as 500 hPa geopotential height anomalies in November, in areas where these two predictors are correlated with winter GBSA. We translate the state of these predictors into a first guess of GBSA and remove ensemble members with a GBSA prediction too far away from this first guess. The resulting subselected ensemble exhibits a significantly improved skill in both deterministic and probabilistic predictions of winter GBSA. We also show how this skill increase is associated with better predictability of large-scale atmospheric patterns.

Effects of idealized land cover and land management changes on the atmospheric water cycle

Abstract. Land cover and land management changes (LCLMCs) play an important role in achieving low-end warming scenarios through land-based mitigation. However, their effects on moisture fluxes and recycling remain uncertain, although they have important implications for the future viability of such strategies. Here, we analyse the impact of idealized LCLMC scenarios on atmospheric moisture transport in three different Earth system model (ESMs): the Community Earth System Model (CESM), the Max Planck Institute Earth System Model (MPI-ESM), and the European Consortium Earth System Model (EC-EARTH). The LCLMC scenarios comprise of a full cropland world, a fully afforested world, and a cropland world with unlimited irrigation expansion. The effects of these LCLMC in the different ESMs are analysed for precipitation, evaporation, and vertically integrated moisture flux convergence to understand the LCLMC-induced changes in the atmospheric moisture cycle. Then, a moisture tracking algorithm is applied to assess the effects of LCLMC on moisture recycling at the local (grid cell level) and the global scale (continental moisture recycling). By applying a moisture tracking algorithm on fully coupled ESM simulations we are able to quantify the complete effects of LCLMC on moisture recycling (including circulation changes), which are generally not considered in moisture recycling studies. Our results indicate that cropland expansion is generally causing a drying and reduced local moisture recycling, while afforestation and irrigation expansion generally cause wetting and increased local moisture recycling. However, the strength of this effect varies across ESMs and shows a large dependency on the dominant driver. Some ESMs show a dominance of large-scale atmospheric circulation changes while other ESMs show a dominance of local to regional changes in the atmospheric water cycle only within the vicinity of the LCLMC. Overall, these results corroborate that LCLMC can induce substantial effects on the atmospheric water cycle and moisture recycling, both through local effects and changes in atmospheric circulation. However, more research is needed to constrain the uncertainty of these effects within ESMs to better inform future land-based mitigation strategies.

Impact of groundwater representation on heat events in regional climate simulations over Europe

Abstract. The representation of groundwater is simplified in most regional climate models (RCMs), potentially leading to biases in the simulations. This study introduces a unique dataset from the regional Terrestrial Systems Modelling Platform (TSMP) driven by the Max Planck Institute Earth System Model at Low Resolution (MPI-ESM-LR) boundary conditions in the context of dynamical downscaling of global climate models (GCMs) for climate change studies. TSMP explicitly simulates full 3D soil and groundwater dynamics together with overland flow, including complete water and energy cycles from the bedrock to the top of the atmosphere. By comparing the statistics of heat events, i.e., a series of consecutive days with a near-surface temperature exceeding the 90th percentile of the reference period, from TSMP and those from GCM–RCM simulations with simplified groundwater dynamics from the COordinated Regional Climate Downscaling EXperiment (CORDEX) for the European domain, we aim to improve the understanding of how groundwater representation affects heat events in Europe. The analysis was carried out using RCM outputs for the summer seasons of 1976–2005 relative to the reference period of 1961–1990. While our results show that TSMP simulates heat events consistently with the CORDEX ensemble, there are some systematic differences that we attribute to the more realistic representation of groundwater in TSMP. Compared to the CORDEX ensemble, TSMP simulates fewer hot days (i.e., days with a near-surface temperature exceeding the 90th percentile of the reference period) and lower interannual variability and decadal change in the number of hot days on average over Europe. TSMP systematically simulates fewer heat waves (i.e., heat events lasting 6 d or more) compared to the CORDEX ensemble; moreover, they are shorter and less intense. The Iberian Peninsula is particularly sensitive with respect to groundwater. Therefore, incorporating an explicit 3D groundwater representation in RCMs may be a key in reducing biases in simulated duration, intensity, and frequency of heat waves in Europe. The results highlight the importance of hydrological processes for the long-term regional climate simulations and provide indications of possible potential implications for climate change projections.

Projections and patterns of heat-related mortality impacts from climate change in Southeast Asia

This study aims to investigate the impact of climate change on heat-related mortality in Southeast Asia in the future. The ensemble mean from five General Circulation Models (GCMs) including the Flexible Global Ocean-Atmosphere-Land System Model: Grid-Point Version 3 (FGOALS-g3), Max Planck Institute Earth System Model Version 1.2 (MPI-ESM1-2-LR), EC-Earth3, The Meteorological Research Institute Earth System Model Version 2.0 (MRI-ESM2-0), and Geophysical Fluid Dynamics Laboratory Earth System Model Version 4 (GFDL-ESM4) was used to project severe temperatures and heat indices in Southeast Asia under the Coupled Model Intercomparison Projects Phase 6 (CMIP6). This data was used to correlate with mortality data from the Global Burden of Disease database to quantify heat-related mortality in the region. The ensemble mean results show a reasonable level of accuracy in capturing temperature patterns in the Southeast Asian region with an R2 of 0.96, root mean square error (RMSE) of 0.84 and a standard deviation of residual (SDR) of 0.02. When compared to the baseline (1990–2019), temperature extreme indices are rising across all climatic scenarios, with a substantial increase in the SSP3–7.0 and SSP5–8.5 scenarios, ranging from 10% to 50% over the regions, with the heat index predicted to peak in the middle of the century. The two low-emission scenarios, SSP1-2.6 and SSP2-4.5, on the other hand, anticipate more moderate increases, indicating a potentially less severe impact on the region. As a result, under high-emission scenarios, there is expected to be a significant increase in heat-related mortality across Southeast Asia. The expected impact is estimated to affect between 200 and 300 people per 100,000 people from 2030 to 2079, accordingly. Our results highlight the critical need to address health-related impacts of climate change in this region.

Late Holocene glacier and climate fluctuations in the Mackenzie and Selwyn mountain ranges, northwestern Canada

Abstract. Over the last century, northwestern Canada experienced some of the highest rates of tropospheric warming globally, which caused glaciers in the region to rapidly retreat. Our study seeks to extend the record of glacier fluctuations and assess climate drivers prior to the instrumental record in the Mackenzie and Selwyn mountains of northwestern Canada. We collected 27 10Be surface exposure ages across nine cirque and valley glacier moraines to constrain the timing of their emplacement. Cirque and valley glaciers in this region reached their greatest Holocene extents in the latter half of the Little Ice Age (1600–1850 CE). Four erratic boulders, 10–250 m distal from late Holocene moraines, yielded 10Be exposure ages of 10.9–11.6 ka, demonstrating that by ca. 11 ka, alpine glaciers were no more extensive than during the last several hundred years. Estimated temperature change obtained through reconstruction of equilibrium line altitudes shows that since ca. 1850 CE, mean annual temperatures have risen 0.2–2.3 ∘C. We use our glacier chronology and the Open Global Glacier Model (OGGM) to estimate that from 1000 CE, glaciers in this region reached a maximum total volume of 34–38 km3 between 1765 and 1855 CE and had lost nearly half their ice volume by 2019 CE. OGGM was unable to produce modeled glacier lengths that match the timing or magnitude of the maximum glacier extent indicated by the 10Be chronology. However, when applied to the entire Mackenzie and Selwyn mountain region, past millennium OGGM simulations using the Max Planck Institute Earth System Model (MPI-ESM) and the Community Climate System Model 4 (CCSM4) yield late Holocene glacier volume change temporally consistent with our moraine and remote sensing record, while the Meteorological Research Institute Earth System Model 2 (MRI-ESM2) and the Model for Interdisciplinary Research on Climate (MIROC) fail to produce modeled glacier change consistent with our glacier chronology. Finally, OGGM forced by future climate projections under varying greenhouse gas emission scenarios predicts 85 % to over 97 % glacier volume loss by the end of the 21st century. The loss of glaciers from this region will have profound impacts on local ecosystems and communities that rely on meltwater from glacierized catchments.

Performance of regional climate model RegCM4 with a hydrostatic or non‐hydrostatic dynamic core at simulating precipitation extremes in China

AbstractIn this study, we investigated the performance of RegCM4 with a hydrostatic or non‐hydrostatic dynamic core and different land surface models at simulating the mean and extreme precipitation during 1991–1999 in China and the Beijing–Tianjin–Hebei urban agglomeration (JJJ) in northern China. The resolutions were 12 km with the whole of China included and 3 km nested over the JJJ region. The observed daily precipitation data comprised the CN05.1 data set from China Meteorological Administration. First, RegCM4 with a hydrostatic dynamic core forced by the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR) that participated in CMIP6 was used to simulate the east Asia area at a resolution of 12 km. Next, the RegCM4 results with 12 km resolution forced RegCM4 with a non‐hydrostatic dynamic core (RegCM4‐NH) to run over the JJJ region with a 3 km convection‐permitting scale through one‐way nesting. The results showed that RegCM4 with a hydrostatic and non‐hydrostatic core could obtain more detailed seasonal and annual precipitation in China and the JJJ region relative to MPI‐ESM1.2‐HR although their performance varied over different regions. RegCM4 with the community land surface model 4.5 (CLM4.5) generally performed better at simulating the mean and extreme precipitation over the four subregions of China than that with the Biosphere–Atmosphere Transfer Scheme because of more detailed descriptions of land surface processes of CLM4.5. RegCM4‐NH with convection‐permitting resolution improved the simulations of heavy precipitation extremes over JJJ compared with RegCM4 with a hydrostatic core and resolution of 12 km. In addition, RegCM4‐NH with CLM4.5 performed better at simulating heavy precipitation extremes over JJJ compared with all other simulations, with higher correlation coefficients and larger relative root mean squared errors.

Projection of Future Heatwaves in the Pearl River Delta through CMIP6-WRF Dynamical Downscaling

Abstract Recent worldwide heatwaves have shattered temperature records in many regions. In this study, we applied a dynamical downscaling method on the high-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-1-2-HR) to obtain projections of the summer thermal environments and heatwaves in the Pearl River Delta (PRD) considering three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) in the middle and late twenty-first century. Results indicated that relative to the temperatures in the 2010s, the mean increases in the summer (June–September) daytime and nighttime temperatures in the 2040s will be 0.7°–0.8°C and 0.9°–1.1°C, respectively. In the 2090s, the mean difference will be 0.5°–3.1°C and 0.7°–3.4°C, respectively. SSP1-2.6 is the only scenario in which the temperatures in the 2090s are expected to be lower than those in the 2040s. When compared with those in the 2010s, hot extremes are expected to be more frequent, intense, extensive, and longer-lasting in the future in the SSP2-4.5 and SSP5-8.5 scenarios. In the 2010s, a heatwave occurred in the PRD lasted for 6 days on average, with a mean daily maximum temperature of 34.4°C. In the 2040s, the heatwave duration and intensity are expected to increase by 2–3 days and 0.2°–0.4°C in all three scenarios. In the 2090s, these values will become 23 days and 36.0°C in SSP5-8.5. Moreover, a 10-yr extreme high temperature in the 2010s is expected to occur at a monthly frequency from June to September in the 2090s. Significance Statement Pearl River Delta (PRD) has been experiencing record-shattering heatwaves in recent years. This study aims to investigate the future trends of summer heatwaves in the PRD by modeling three future scenarios including a sustainable scenario, an intermediate scenario, and a worst-case scenario. Except for the sustainable scenario, summer temperatures in the intermediate and worst-case scenarios will keep increasing, and heatwaves will become more frequent, intense, extensive, and longer-lasting. In the worst-case scenario, extreme heat events that occurred once in 10 years in the 2010s will shorten to once a month in the 2090s. A better understanding of heatwave trends will benefit implementing climate mitigation methods, urban planning, and improving social infrastructure.

The impact of horizontal resolution on the representation of atmospheric circulation types in Western Europe using the MPI‐ESM model

AbstractIn this study, the added value in using the sea level pressure field from the coupled higher‐resolution version of the Max Planck Institute Earth System Model (MPI‐ESM‐HR), compared to the lower‐resolution version (MPI‐ESM‐LR) for circulation typing, within the regional context of Western Europe was examined. The results show that the MPI‐ESM‐HR and the MPI‐ESM‐LR simulations can produce the classified circulation types (CTs) and their long‐term statistical characteristics as obtained from the ERA5 reanalysis. Overall, there are improvements in the composite maps, probability of occurrence and annual cycle of the simulated CTs in the MPI‐ESM‐HR compared to the MPI‐ESM‐LR. The model bias in simulating the structure of anticyclonic circulations over the Western European landmass was reduced by 14% under MPI‐ESM‐HR. Furthermore, under the shared socio‐economic pathways (SSP2‐4.5 and SSP5‐8.5) future emission scenarios, the historical CTs in the region of assessment were classified, suggesting that in Western Europe, the same historical CTs are present under future climate change scenarios. However, the frequency distribution and geographical structure of some of the CTs in Western Europe are projected to change by the MPI‐ESM model, especially under the higher future emission scenario.

The challenge of comparing pollen-based quantitative vegetation reconstructions with outputs from vegetation models – a European perspective

Abstract. We compare Holocene tree cover changes in Europe derived from a transient Earth system model simulation (Max Planck Institute Earth System Model – MPI-ESM1.2, including the land surface and dynamic vegetation model JSBACH) with high-spatial-resolution time slice simulations performed in the dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator) and pollen-based quantitative reconstructions of tree cover based on the REVEALS (Regional Estimates of Vegetation Abundance from Large Sites) model. The dynamic vegetation models and REVEALS agree with respect to the general temporal trends in tree cover for most parts of Europe, with a large tree cover during the mid-Holocene and a substantially smaller tree cover closer to the present time. However, the decrease in tree cover in REVEALS starts much earlier than in the models, indicating much earlier anthropogenic deforestation than the prescribed land use in the models. While LPJ-GUESS generally overestimates tree cover compared to the reconstructions, MPI-ESM indicates lower percentages of tree cover than REVEALS, particularly in central Europe and the British Isles. A comparison of the simulated climate with chironomid-based climate reconstructions reveals that model–data mismatches in tree cover are in most cases not driven by biases in the climate. Instead, sensitivity experiments indicate that the model results strongly depend on the tuning of the models regarding natural disturbance regimes (e.g. fire and wind throw). The frequency and strength of disturbances are – like most of the parameters in the vegetation models – static and calibrated to modern conditions. However, these parameter values may not be valid for past climate and vegetation states totally different from today's. In particular, the mid-Holocene natural forests were probably more stable and less sensitive to disturbances than present-day forests that are heavily altered by human interventions. Our analysis highlights the fact that such model settings are inappropriate for paleo-simulations and complicate model–data comparisons with additional challenges. Moreover, our study suggests that land use is the main driver of forest decline in Europe during the mid-Holocene and late Holocene.

Sensitivity of Arctic CH4 emissions to landscape wetness diminished by atmospheric feedbacks

Simulations using land surface models suggest future increases in Arctic methane emissions to be limited by the thaw-induced drying of permafrost landscapes. Here we use the Max Planck Institute Earth System Model to show that this constraint may be weaker than previously thought owing to compensatory atmospheric feedbacks. In two sets of extreme scenario simulations, a modification of the permafrost hydrology resulted in diverging hydroclimatic trajectories that, however, led to comparable methane fluxes. While a wet Arctic showed almost twice the wetland area compared with an increasingly dry Arctic, the latter featured greater substrate availability due to higher temperatures resulting from reduced evaporation, diminished cloudiness and more surface solar radiation. Given the limitations of present-day models and the potential model dependence of the atmospheric response, our results provide merely a qualitative estimation of these effects, but they suggest that atmospheric feedbacks play an important role in shaping future Arctic methane emissions.

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

Representation of soil hydrology in permafrost regions may explain large part of inter-model spread in simulated Arctic and subarctic climate

Abstract. The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone, with differences in model structure and parametrizations being one of the main sources of uncertainty. One particularly challenging aspect in modelling is the representation of terrestrial processes in permafrost-affected regions, which are often governed by spatial heterogeneity far below the resolution of the models' land surface components. Here, we use the Max Planck Institute (MPI) Earth System Model to investigate how different plausible assumptions for the representation of permafrost hydrology modulate land–atmosphere interactions and how the resulting feedbacks affect not only the regional and global climate, but also our ability to predict whether the high latitudes will become wetter or drier in a warmer future. Focusing on two idealized setups that induce comparatively “wet” or “dry” conditions in regions that are presently affected by permafrost, we find that the parameter settings determine the direction of the 21st-century trend in the simulated soil water content and result in substantial differences in the land–atmosphere exchange of energy and moisture. The latter leads to differences in the simulated cloud cover during spring and summer and thus in the planetary energy uptake. The respective effects are so pronounced that uncertainties in the representation of the Arctic hydrological cycle can help to explain a large fraction of the inter-model spread in regional surface temperatures and precipitation. Furthermore, they affect a range of components of the Earth system as far to the south as the tropics. With both setups being similarly plausible, our findings highlight the need for more observational constraints on the permafrost hydrology to reduce the inter-model spread in Arctic climate projections.