Max 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.

Modelling the bottom-up effects of climate change on primary production in the Gulf of St. Lawrence and eastern Scotian Shelf

The Gulf of St. Lawrence (GSL), along with the St. Lawrence Estuary, is the largest estuarine system in North America. It is a biologically productive sea and an important fishing ground in Canada. The objectives of this study are to determine how climate changes will affect primary production in the GSL and on the eastern Scotian Shelf, and to determine the drivers of the changes. We use a regional ocean model forced with downscaled output of the Max-Planck Institute Earth System Model to study the changes in net primary production under the climate change scenario of Representative Concentration Pathway 8.5 (RCP8.5). Results reveal a projected 13.4% decrease in annual primary production across the GSL system over the next 70 years. This decline primarily stems from reduced nutrient concentrations in the upper layer, despite the increase in nutrients supplied by rivers. Enhanced freshwater influx and ocean surface warming contribute to heightened stratification, that in turn reduce the vertical nutrient fluxes from deeper layers. This mechanism affects the upwelling of nutrient-rich water at the head of the Laurentian Channel in the Lower St. Lawrence Estuary, leading to a 22% reduction in the vertical nitrate flux in the future. Additionally, nutrient concentrations in the water masses entering the GSL at the Strait of Belle Isle and at Cabot Strait are also reduced. Due to declining sea-ice concentration, the phytoplankton bloom is expected to occur between 9 and 23 days earlier under a warmer climate, and last for up to 24 days longer, depending on the GSL subregions, compared to the historical period (2001-2020). Biological productivity at higher trophic levels, and thus fisheries productivity, could be negatively impacted under the RCP8.5 climate change scenario.

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.

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.

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.

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 MPI-ESM Sea Level Projections to Its Ocean Spatial Resolution

Abstract The dependence of future regional sea level changes on ocean model resolution is investigated based on Max Planck Institute Earth System Model (MPI-ESM) simulations with varying spatial resolution, ranging from low resolution (LR), high resolution (HR), to eddy-rich (ER) resolution. Each run was driven by the shared socioeconomic pathway (SSP) 5-8.5 (fossil-fueled development) forcing. For each run the dynamic sea level (DSL) changes are evaluated by comparing the time mean of the SSP5-8.5 climate change scenario for the years 2080–99 to the time mean of the historical simulation for the years 1995–2014. Respective results indicate that each run reproduces previously identified large-scale DSL change patterns. However, substantial sensitivity of the projected DSL changes can be found on a regional to local scale with respect to model resolution. In comparison to models with parameterized eddies (HR and LR), enhanced sea level changes are found in the North Atlantic subtropical region, the Kuroshio region, and the Arctic Ocean in the model version capturing mesoscale processes (ER). Smaller yet still significant sea level changes can be found in the Southern Ocean and the North Atlantic subpolar region. These sea level changes are associated with changes in the regional circulation. Our study suggests that low-resolution sea level projections should be interpreted with care in regions where major differences are revealed here, particularly in eddy active regions such as the Kuroshio, Antarctic Circumpolar Current, Gulf Stream, and East Australian Current. Significance Statement Sea level change is expected to be more realistic when mesoscale processes are explicitly resolved in climate models. However, century-long simulations with eddy-resolving models are computationally expensive. Therefore, current sea level projections are based on climate models in which ocean eddies are parameterized. The representation of sea level by these models considerably differs from actual observations, particularly in the eddy-rich regions such as the Southern Ocean and the western boundary currents, implying erroneous ocean circulation that affects the sea level projections. Taking this into account, we review the sea level change pattern in a climate model with featuring an eddy-rich ocean model and compare the results to state-of-the-art coarser-resolution versions of the same model. We found substantial DSL differences in the global ocean between the different resolutions. Relatively small-scale ocean eddies can hence have profound large-scale effects on the projected sea level which may affect our understanding of future sea level change as well as the planning of future investments to adapt to climate change around the world.

Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model

Abstract. The global carbon budget (GCB) – including fluxes of CO2 between the atmosphere, land, and ocean and its atmospheric growth rate – show large interannual to decadal variations. Reconstructing and predicting the variable GCB is essential for tracing the fate of carbon and understanding the global carbon cycle in a changing climate. We use a novel approach to reconstruct and predict the variations in GCB in the next few years based on our decadal prediction system enhanced with an interactive carbon cycle. By assimilating physical atmospheric and oceanic data products into the Max Planck Institute Earth System Model (MPI-ESM), we are able to reproduce the annual mean historical GCB variations from 1970–2018, with high correlations of 0.75, 0.75, and 0.97 for atmospheric CO2 growth, air–land CO2 fluxes, and air–sea CO2 fluxes, respectively, relative to the assessments from the Global Carbon Project (GCP). Such a fully coupled decadal prediction system, with an interactive carbon cycle, enables the representation of the GCB within a closed Earth system and therefore provides an additional line of evidence for the ongoing assessments of the anthropogenic GCB. Retrospective predictions initialized from the simulation in which physical atmospheric and oceanic data products are assimilated show high confidence in predicting the following year's GCB. The predictive skill is up to 5 years for the air–sea CO2 fluxes, and 2 years for the air–land CO2 fluxes and atmospheric carbon growth rate. This is the first study investigating the GCB variations and predictions with an emission-driven prediction system. Such a system also enables the reconstruction of the past and prediction of the evolution of near-future atmospheric CO2 concentration changes. The Earth system predictions in this study provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.

Skillful decadal prediction of German Bight storm activity

Abstract. We evaluate the prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcast system for German Bight storm activity (GBSA) on a multiannual to decadal scale. We define GBSA every year via the most extreme 3-hourly geostrophic wind speeds, which are derived from mean sea-level pressure (MSLP) data. Our 64-member ensemble of annually initialized hindcast simulations spans the time period 1960–2018. For this period, we compare deterministically and probabilistically predicted winter MSLP anomalies and annual GBSA with a lead time of up to 10 years against observations. The model produces poor deterministic predictions of GBSA and winter MSLP anomalies for individual years but fair predictions for longer averaging periods. A similar but smaller skill difference between short and long averaging periods also emerges for probabilistic predictions of high storm activity. At long averaging periods (longer than 5 years), the model is more skillful than persistence- and climatology-based predictions. For short aggregation periods (4 years and less), probabilistic predictions are more skillful than persistence but insignificantly differ from climatological predictions. We therefore conclude that, for the German Bight, probabilistic decadal predictions (based on a large ensemble) of high storm activity are skillful for averaging periods longer than 5 years. Notably, a differentiation between low, moderate, and high storm activity is necessary to expose this skill.

Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2

Abstract. We assess the land surface model JSBACHv4 (Jena Scheme for Biosphere Atmosphere Coupling in Hamburg version 4), which was recently developed at the Max Planck Institute for Meteorology as part of the effort to build the new Icosahedral Nonhydrostatic (ICON) Earth system model (ESM), ICON-ESM. We assess JSBACHv4 in simulations coupled with ICON-A, the atmosphere model of ICON-ESM, hosting JSBACHv4 as land component to provide the surface boundary conditions. The assessment is based on a comparison of simulated albedo, land surface temperature (LST), leaf area index (LAI), terrestrial water storage (TWS), fraction of absorbed photosynthetic active radiation (FAPAR), net primary production (NPP), and water use efficiency (WUE) with corresponding observational data. JSBACHv4 is the successor of JSBACHv3; therefore, another purpose of this study is to document how this step in model development has changed model biases. This is achieved by also assessing, in parallel, the results of coupled land–atmosphere simulations with the preceding model ECHAM6 hosting JSBACHv3. Large albedo biases appear in both models over ice sheets and in central Asia. The temperate to boreal warm bias observed in simulations with JSBACHv3 largely remained in JSBACHv4, despite the very good agreement with observed LST in the global mean. For the assessment of changes in land water storage, a novel procedure is suggested to compare the gravitational data from the Gravity Recovery And Climate Experiment (GRACE) satellites to simulated TWS. It turns out that the agreement of the changes in the seasonal cycle of TWS is sensitive to the representation of precipitation in the atmosphere model. The LAI is generally too high, which is partly caused by too high soil moisture and also by the parameterization of the phenology itself. The pattern of WUE is, for both models, largely as observed. In India, WUE is too high, probably because JSBACH does not incorporate irrigation in our simulations. WUE differences between the two models can be traced back to differences in precipitation patterns in the two coupled land–atmosphere simulations. For both models, most NPP biases can be associated with biases in water stress, LAI, and FAPAR. In particular, the NPP bias of the Eurasian steppes has switched from positive in JSBACHv3 to negative in JSBACHv4. This difference is mainly caused by weaker precipitation and lower FAPAR of ICON-A–JSBACHv4 in July, which is most probably caused by a feedback loop between too little soil moisture, evaporation, and clouds. While the size and patterns of biases in albedo and LST are largely similar between the two model versions, they are less well correlated for precipitation- and vegetation-related variables like FAPAR. Overall, the biases found in the different assessment variables are either already known from the previous implementation in the Max Planck Institute Earth System Model (MPI-ESM) or have changed because of the coupling with the new atmospheric component ICON-A. Accordingly, this study demonstrates the technically successful completion of the re-implementation of JSBACH into ICON-ESM-V1. As discussed, there is a good perspective on mitigating the biases by an improved representation of the processes.

On the additivity of climate responses to the volcanic and solar forcing in the early 19th century

Abstract. The early 19th century was the coldest period over the past 500 years, when strong tropical volcanic events and a solar minimum coincided. The 1809 unidentified eruption and the 1815 Tambora eruption happened consecutively during the Dalton minimum of solar irradiance; however, the relative role of the two forcing (volcano and solar) agents is still unclear. In this study, we examine the responses from a set of early 19th century simulations with combined and separated volcanic and solar forcing agents, as suggested in the protocol for the past1000 experiment of the Paleoclimate Modelling Intercomparison Project – Phase 4 (PMIP4). From 20-member ensemble simulations with the Max Planck Institute Earth system model (MPI-ESM1.2-LR), we find that the volcano- and solar-induced surface cooling is additive in the global mean/large scale, regardless of combining or separating the forcing agents. The two solar reconstructions (SATIRE (Spectral and Total Irradiance REconstruction-Millennia model) and PMOD (Physikalisch-Meteorologisches Observatorium Davos)) contribute to a cooling before and after 1815 of ∼0.05 and ∼0.15 K monthly average near-surface air cooling, respectively, indicating a limited solar contribution to the early 19th century cold period. The volcanic events provide the main cooling contributions, inducing a surface cooling that peaks at ∼0.82 K for the 1809 event and ∼1.35 K for Tambora. After the Tambora eruption, the temperature in most regions increases toward climatology largely within 5 years, along with the reduction of volcanic forcing. In the northern extratropical oceans, the temperature increases slowly at a constant rate until 1830, which is related to the reduction of seasonality and the concurrent changes in Arctic sea-ice extent. The albedo feedback of Arctic sea ice is found to be the main contributor to the Arctic amplification of the cooling signal. Several non-additive responses to solar and volcanic forcing happen on regional scales. In the atmosphere, the stratospheric polar vortex tends to strengthen when combining both volcano and solar forcing, even though the two forcing agents separately induce opposite-sign changes in stratospheric temperatures and zonal winds. In the ocean, when combining the two forcings, additional surface cold water propagates to the northern extratropics from the additional solar cooling in the tropics, which results in regional cooling along the propagation. Overall, this study not only quantifies the surface responses from combinations of the volcano and solar forcing, but also highlights the components that cannot be simply added from the responses of the individual forcing agents, indicating that a relatively small forcing agent (such as solar in early 19th century) can impact the response from the large forcing (such as the 1815 Tambora eruption) when considering regional climates.

Quantifying the Contribution of Internal Atmospheric Drivers to Near-Term Projection Uncertainty in September Arctic Sea Ice

Abstract Arctic sea ice has undergone rapid loss in all months of the year in recent decades, especially in September. The September sea ice extent (SSIE) in the multimodel ensemble mean of climate models shows a large divergence from observations since the 2000s, which indicates the potential influence of internal variability on SSIE decadal variations. Reasons previously identified for the accelerated decrease in SSIE are largely related to the tendency toward a barotropic geopotential height rise in summer over the Arctic. We used a 40-member ensemble of simulation by the Community Earth System Model version 1 (CESM1) and a 100-member ensemble simulation by the Max Planck Institute Earth System Model (MPI-ESM) to reveal that the internal variability of the local atmosphere circulation change can contribute 12%–17% to the uncertainties in the projected SSIE changes during 2016–45 in both CESM-LE and MPI-ESM. The tropical Pacific Ocean may act as a remote driver for the sea ice melting but the coupling between them is more intense on decadal time scales than that on year-to-year scales. Our quantitative estimation of the contribution of the internal atmospheric circulation to SSIE during the next three decades may be underestimated due to models’ inability to capture the observed Rossby wave train originating from the tropical Pacific Ocean propagating into the Arctic. Further efforts toward investigating causes of the model limitations and quantifying the contribution of local and remote component to Arctic sea ice on different time scales may help to improve the future sea ice prediction.

Strong increase in thawing of subsea permafrost in the 22nd century caused by anthropogenic climate change

Abstract. Most earth system models (ESMs) neglect climate feedbacks arising from carbon release from thawing permafrost, especially from thawing of subsea permafrost (SSPF). To assess the fate of SSPF in the next 1000 years, we implemented SSPF into JSBACH, the land component of the Max Planck Institute Earth System Model (MPI-ESM). This is the first implementation of SSPF processes in an ESM component. We investigate three extended scenarios from the 6th phase of the Coupled Model Intercomparison Project (CMIP6). In the 21st century only small differences are found among the scenarios, but in the upper-end emission scenario SSP5–8.5 (shared socio-economic pathway), especially in the 22nd century, SSPF ice melting is more than 15 times faster than in the pre-industrial period. In this scenario about 35 % of total SSPF volume and 34 % of SSPF area are lost by the year 3000 due to climatic changes. In the more moderate scenarios, the melting rate maximally exceeds that of pre-industrial times by a factor of 4, and the climate change induced SSPF loss (volume and area) by the year 3000 does not exceed 14 %. Our results suggest that the rate of melting of SSPF ice is related to the length of the local open-water season and thus that the easily observable sea ice concentration may be used as a proxy for the change in SSPF.

Sea level changes mechanisms in the MPI-ESM under FAFMIP forcing conditions

Mechanistic causes for sea level (SL) change patterns are analyzed as they emerge from the Coupled Model Intercomparison Project Phase 6 (CMIP6) endorsed Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) coupled climate experiments imposing individual forcing anomalies in wind stress, heatflux and freshwater flux to the Max-Planck-Institute Earth System Model (MPI-ESM). It appears that the heat flux perturbations have the largest effect on the sea level. In contrast, the direct impact of momentum and freshwater flux anomalies on SL anomalies appear to be limited to some region e.g. the Southern Ocean, Arctic Ocean and to some extent the North Pacific and North Atlantic Ocean. We find that thermosteric changes dominate the total SL change over large parts of the global ocean, except north of 60 °N where halosteric changes prevail. An analysis of added and redistributed components of heat and freshwater further suggests that the added component dominates the thermosteric SL and the redistributed component dominates the halosteric SL. Due to feedback processes a superposition of all forcing components together leads to the simulated sea level changes in each individual experiment. As a result, large surface heat flux anomalies over the Atlantic lead to wind stress change outside of the Atlantic through teleconnections, which in turn appear to be the primary driving agent for changes of sea level outside of the Atlantic in all three experiments. The associated wind driven Sverdrup stream function implicates that outside of the Atlantic most of the feedback can be explained by changes in the Sverdrup circulation.

Policy-Making toward Integrated Water Resources Management of Zarrine River Basin via System Dynamics Approach under Climate Change Impact

In terms of having a comprehensive vision toward supplying the water requirements, a multi-criteria decision-making approach was employed on the Zarrine River Basin (ZRB) in the northwest of Iran. First, the climate change impacts were analyzed with the Long Ashton Research Station Weather Generator (LARS-WG) downscaling approach by using General Circulation Models (GCMs) including the European Consortium Earth System Model (EC-EARTH), Hadley Centre Global Environment Model version 2 (HADGEM2), Model for Interdisciplinary Research on Climate, version 5 (MIROC5), and Max Planck Institute Earth System Model (MPI-ESM), from Coupled Model Intercomparison Project 5 (CMIP5) under Representative Concentration Pathway (RCP4.5, RCP8.5) scenarios for 2021–2080. Afterward, the downscaled variables were utilized as inputs to the Artificial Neural Network (ANN) model to predict future runoff under the climate change impact. Finally, the system dynamics (SD) model was employed to simulate various scenarios for assessing water balance utilizing the Vensim software. The results of downscaling models suggested that the temperature of the basin will increase by 0.47 and 0.91 °C under RCPs4.5 and 8.5 by 2040, respectively. Additionally, the precipitation will decrease by 3.5 percent under RCP4.5 and 14 percent under RCP8.5, respectively. Moreover, simulation results revealed that the water demand in various sectors will be enormously increased. The contribution of the climate change impact on the future run-off was a seven percent decrease, on average, over the basin. The SD model, according to presented plausible scenarios including decreasing agriculture product and shifting irrigation efficiency, cloud-seeding, population control, and household consumption reduction, reducing meat and animal-husbandry production, and groundwater consumption control, resulted in a water balance equilibrium over five years. However, the performance of individual scenarios was not effective; instead, a combination of several scenarios led to effective performance in managing reduced runoff under climate change.

Exploring the Potential of Forecasting Fish Distributions in the North East Atlantic With a Dynamic Earth System Model, Exemplified by the Suitable Spawning Habitat of Blue Whiting

Local oceanographic variability strongly influences the spawning distribution of blue whiting (Micromesistius poutassou). Here, we explore the potential of using a dynamic Earth System Model (ESM) to forecast the suitable spawning habitat of blue whiting to assist management. Retrospective forecasts of temperature and salinity with the Max Planck Institute ESM (MPI-ESM) show significant skill within blue whiting’s spawning region and spawning depth (250–600 m) during the peak months of spawning. While persistence forecasts perform well at shorter lead times (≤2 years), retrospective forecasts with MPI-ESM are clearly more skilful than persistence in predicting salinity at longer lead times. Our results indicate that retrospective forecasts of the suitable spawning habitat of blue whiting based on predicted salinity outperform those based on calibrated species distribution models. In particular, we find high predictive skill for the suitable spawning habitat based on salinity predictions around one year ahead in the area of Rockall-Hatton Plateau. Our approach shows that retrospective forecasts with MPI-ESM show a better ability to differentiate between the presence and absence of suitable habitat over Rockall Plateau compared to persistence. Our study highlights that physical-biological forecasts based on ESMs could be crucial for developing distributional forecasts of marine organisms in the North East Atlantic.

Impact of Internal Climate Variability on the Relationship between Spring Northern Tropical Atlantic SST Anomalies and Succedent Winter ENSO: The Role of the North Pacific Oscillation

Abstract Previous studies suggested that spring sea surface temperature anomalies (SSTAs) in the northern tropical Atlantic (NTA) have a marked influence on the succedent winter El Niño–Southern Oscillation (ENSO). In this study, we examine the spring NTA SSTA–winter ENSO connection in a 50-member large-ensemble simulation conducted with the Canadian Centre for Climate Modelling and Analysis second-generation Canadian Earth System Model (CanESM2) and a 100-member ensemble simulation conducted with the Max Planck Institute Earth System Model (MPI-ESM). The observed out-of-phase relation of spring NTA SSTA with winter ENSO can be captured by the multimember ensemble means of the large-ensemble simulations from both models. However, the relation shows a large diversity among different ensemble members attributing to the internal climate variability. The preceding winter North Pacific Oscillation (NPO) is suggested to be an important source of the internal climate variability that modulates the spring NTA SSTA–ENSO connection. The modulation of the winter NPO on the subsequent spring NTA SSTA–winter ENSO relation is seen in both climate modeling and observational datasets. When winter NPO and spring NTA SSTA indices have the same (opposite) sign, the linkage between the spring NTA SSTA and the following winter ENSO tends to be weak (strong). The NPO modulates the spring NTA SSTA–winter ENSO relation mainly via changing the zonal wind anomalies over the tropical western-to-central Pacific induced by the spring NTA SSTA. In addition, our analysis indicates that winter NPO may have a marked effect on the predictability of winter ENSO based on the condition of spring NTA SSTA.

Circulation type analysis of regional hydrology: the added value in using CMIP6 over CMIP5 simulations as exemplified from the MPI-ESM-LR model

AbstractThis study addresses the applicability of general circulation models (GCMs) in studying the impact of climate change on hydrology. The statistical downscaling of precipitation based on circulation types (CTs) derived from the fuzzy, i.e., more than one CTs can occur in a given day, obliquely rotated principal component analysis is suggested as a robust methodology in using climate models to research the impact of climate change on hydrology. The methodology allows understanding of the mechanism of atmospheric circulation in the study region, and the physical relationship between atmospheric circulation and the regional hydrological cycle. The capability of climate simulations from the Max Planck Institute Earth System Model (MPI-ESM) GCM to reproduce the observed CTs in the target region is examined in light of the uncertainty of atmospheric GCMs when used for circulation typing. The results were discussed and it showed that, generally, the analyzed GCM can reproduce the underlying physics of atmospheric circulation in the study region, represented by the CTs, together with their dominant periods, probability of occurrence, and annual frequency of occurrence with modest biases. Generally, the Coupled Model Intercomparison Project 6 (CMIP6) simulation indicates some improvement for the CT-based analysis relative to the CMIP5 counterpart; however, this depends on the analyzed CT.