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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.

Extratropical windstorms are amongst the highest rated perils for the European continent. Extreme wind speeds of these synoptic scale systems occur primarily in the winter season and often cause damage to buildings, forests and infrastructure, and thus can have large socio-economic impacts.In our studies of extratropical windstorms in the CMIP6 model ensemble, we found remarkable trends of opposite sign in the wind speed during the historical period. More specifically, we found a continuous increase in the surface wind speed in the early historical period between 1850 and 1920, and an even stronger decrease thereafter until the present.In a case study with one of the models (MPI-ESM) we found that the trends in the wind speed relate to a trend of opposite sign in the roughness length, thus the wind speed increases in eras with a decrease in the surface roughness (and tree fraction) and vice versa. While this relationship is expected and physically reasonable, it appears that the interaction of surface parameters with the atmosphere was different in CMIP5 climate models, as there is no comparable reaction of surface wind speeds to the trends in surface parameters (e.g. tree fraction).Since the historical era serves as the reference for any derived climate change signal, these trends might affect the amplitude of the changes in a future climate and the derived conclusions. Also, state of the art climate change signals regarding storminess might need to be reconsidered with this newly represented land-atmosphere interaction in the models.We further explore this phenomenon by eliminating the influence of the roughness on the wind speed and investigate the effect that this correction has on the appearance of climate change signals of extratropical windstorms.

The atmospheric CO2 concentration increased by about 20 ppm from 6000 BCE to the pre-industrial period (1850 CE). Several hypotheses have been proposed to explain mechanisms of this CO2 growth based on either ocean or land carbon sources. Here, we apply the Earth system model MPI-ESM-LR for two transient simulations of climate and carbon cycle dynamics during this period. In the first simulation, atmospheric CO2 is prescribed following ice-core CO2 data. In response to the growing atmospheric CO2 concentration, land carbon storage increases until 2000 BCE, stagnates afterwards, and decreases from 1 CE, while the ocean continuously takes CO2 out of the atmosphere after 4000 BCE. This leads to a missing source of 166 Pg of carbon in the ocean–land–atmosphere system by the end of the simulation. In the second experiment, we applied a CO2 nudging technique using surface alkalinity forcing to follow the reconstructed CO2 concentration while keeping the carbon cycle interactive. In that case the ocean is a source of CO2 from 6000 to 2000 BCE due to a decrease in the surface ocean alkalinity. In the prescribed CO2 simulation, surface alkalinity declines as well. However, it is not sufficient to turn the ocean into a CO2 source. The carbonate ion concentration in the deep Atlantic decreases in both the prescribed and the interactive CO2 simulations, while the magnitude of the decrease in the prescribed CO2 experiment is underestimated in comparison with available proxies. As the land serves as a carbon sink until 2000 BCE due to natural carbon cycle processes in both experiments, the missing source of carbon for land and atmosphere can only be attributed to the ocean. Within our model framework, an additional mechanism, such as surface alkalinity decrease, for example due to unaccounted for carbonate accumulation processes on shelves, is required for consistency with ice-core CO2 data. Consequently, our simulations support the hypothesis that the ocean was a source of CO2 until the late Holocene when anthropogenic CO2 sources started to affect atmospheric CO2 .

Reconstructions of the global mean annual temperature evolution during the Holocene yield conflicting results. One temperature reconstruction shows global cooling during the late Holocene. The other reconstruction reveals global warming. Here we show that both a global warming mode and a cooling mode emerge when performing a spatio-temporal analysis of annual temperature variability during the Holocene using data from a transient climate model simulation. The warming mode is most pronounced in the tropics. The simulated cooling mode is determined by changes in the seasonal cycle of Arctic sea-ice that are forced by orbital variations and volcanic eruptions. The warming mode dominates in the mid-Holocene, whereas the cooling mode takes over in the late Holocene. The weighted sum of the two modes yields the simulated global temperature trend evolution. Our findings have strong implications for the interpretation of proxy data and the selection of proxy locations to compute global mean temperatures., Proxy reconstructions show a decreasing trend from the Middle to Late Holocene, which conflicts with model results showing an increasing trend. Statistical analysis of model output shows that these conflicting results originate from two distinct modes of variability, which dominate at different regions and times.

ICON‐A is the new icosahedral nonhydrostatic (ICON) atmospheric general circulation model in a configuration using the Max Planck Institute physics package, which originates from the ECHAM6 general circulation model, and has been adapted to account for the changed dynamical core framework. The coupling scheme between dynamics and physics employs a sequential updating by dynamics and physics, and a fixed sequence of the physical processes similar to ECHAM6. To allow a meaningful initial comparison between ICON‐A and the established ECHAM6‐LR model, a setup with similar, low resolution in terms of number of grid points and levels is chosen. The ICON‐A model is tuned on the base of the Atmospheric Model Intercomparison Project (AMIP) experiment aiming primarily at a well balanced top‐of atmosphere energy budget to make the model suitable for coupled climate and Earth system modeling. The tuning addresses first the moisture and cloud distribution to achieve the top‐of‐atmosphere energy balance, followed by the tuning of the parameterized dynamic drag aiming at reduced wind errors in the troposphere. The resulting version of ICON‐A has overall biases, which are comparable to those of ECHAM6. Problematic specific biases remain in the vertical distribution of clouds and in the stratospheric circulation, where the winter vortices are too weak. Biases in precipitable water and tropospheric temperature are, however, reduced compared to the ECHAM6. ICON‐A will serve as the basis of further development and as the atmosphere component to the coupled model, ICON‐Earth system model (ESM).

The atmospheric CO2 concentration increased by about 20 ppm from 6000 BCE to pre-industrial (1850 CE). Several hypotheses have been proposed to explain mechanisms of this CO2 growth based on either ocean or land carbon sources. Here, we apply the Earth System model MPI-ESM-LR for two transient simulations of climate and carbon cycle dynamics during this period. In the 1st simulation, atmospheric CO2 is prescribed following ice-core CO2 data. In response to the growing atmospheric CO2 concentration, land carbon storage increases until 2000 BCE, stagnates afterwards, and decreases from 1 CE, while the ocean continuously takes CO2 out of atmosphere after 4000 BCE. This leads to a missing source of 166 Pg of carbon in the ocean-land-atmosphere system by the end of the simulation. In the 2nd experiment, we applied a CO2-nudging technique using surface alkalinity forcing to follow the reconstructed CO2 concentration while keeping the carbon cycle interactive. In that case the ocean is a source of CO2 from 6000 to 2000 BCE due to a decrease in the surface ocean alkalinity. In the prescribed CO2 simulation, surface alkalinity declines as well. However, it is not sufficient to turn the ocean into a CO2 source. The carbonate ion concentration in the deep Atlantic decreases in both the prescribed and the interactive CO2 simulations, while the magnitude of the decrease in the prescribed CO2 experiment is underestimated in comparison with available proxies. As the land serves as a carbon sink until 2000 BCE due to natural carbon cycle processes in both experiments, the missing source of carbon for land and atmosphere can only be attributed to the ocean. Within our model framework, an additional mechanism, such as surface alkalinity decrease, for example due to unaccounted carbonate accumulation processes on shelves, is required for consistency with ice-core CO2 data. Consequently, our simulations support the hypothesis that the ocean was a source of CO2 until the late Holocene when anthropogenic CO2 sources started to affect atmospheric CO2.

International audience; the accumulation of magma within the Monti Sabatini Volcanic District (MSVD), italy, coupled with the extensional tectonics of the region, pose both volcanic and tectonic hazards to the city of Rome, located 20 km to the southeast. We combine 40 Ar/ 39 Ar geochronology of volcanic deposits and a geomorphologic/stratigraphic/paleomagnetic study of fluvial terraces to determine the recurrence interval and the time elapsed since the last eruption of the MSVD. Moreover, we provide a date for the youngest known eruption of the MSVD and assess the timing of the most recent volcanic phase. Results of this study show: (i) The most recent eruptive phase occurred between 100 ka and 70 ka; (ii) the anomalously high elevation of the MIS 5 terrace indicates that it was concurrent with 50 m of uplift in the volcanic area; (iii) the time since the last eruption (70 ka) exceeds the average recurrence interval (39 ky) in the last 300 ky, as well as the longest previous dormancy (50 ky) in that time span. (iv) the current duration of dormancy is similar to the timespan separating the major explosive phase that occurred 590-450 ka. The magnitude and patterns of deformation of a volcanic field provide constraints on the magmatic processes operating beneath a volcano. A recent geomorphological study 1 reconstructed a series of paleo-surfaces along a 40-km-long stretch of the Tiber River Valley north of Rome, between Magliano Sabina and Monterotondo, located at the eastern margin of the Monti Sabatini Volcanic District (MSVD) (Fig. 1a). These paleo-surfaces are interpreted as fluvial terraces formed through the interplay between regional uplift and glacio-eustasy (e.g. 2) during a regressive phase that formed the hydrographic network of the Paleo-Tiber River since the end of the Santernian (1.78-1.5 Ma; lower Calabrian) 3. The reconstructed rates of uplift during the last 1.8 Ma recognized two major pulses: 0.86 through 0.5 Ma, and 0.25 Ma through the present time 1. The coincidence of the uplift pulses with the ages of the main volcanic phases 1 are interpreted as mainly driven by uprising magma bodies from a metasomatized mantle source of the Roman Magmatic Province (e.g. 4-6). This "magmatic" uplift overlaps a smaller isostatic component on the Tyrrhenian Sea Margin of central Italy. In the present study, we further refine the chronostratigraphy of the paleo-surfaces in the area previously investigated, providing five new 40 Ar/ 39 Ar age determinations on volcanic products intercalated within the

A major link between climate and humans in tropical northern Africa, and the Sahel in particular, is land use and associated land cover change, mainly where subsistence farming prevails. Here we assess possible feedbacks between the type of land use and harvest intensity and climate by analysing a series of idealized GCM experiments using the Max Planck Institute Earth System Model (MPI-ESM). The baseline for these experiments is a simulation forced by the RCP8.5 (radiation concentration pathway) scenario, which includes strong greenhouse gas emissions and anthropogenic land cover changes. The anthropogenic land cover changes in the RCP8.5 scenario include a mixture of pasture and agriculture. In subsequent simulations, we replace the entire area affected by anthropogenic land cover change in the region between the Sahara in the north and the Guinean Coast in the south (4 to 20\\degree N) with either pasture or agriculture. In a second set-up we vary the amount of harvest in the case of agriculture. The RCP8.5 baseline simulation reveals strong changes in the area mean agriculture and monsoon rainfall. In comparison with these changes, any variation of the type of land use in the study area leads to very small, mostly insignificantly small, additional differences in mean temperature and annual precipitation change in this region. These findings are only based on the specific set-up of our experiments, which only focuses on variations in the kind of land use, and not the increase in land use, over the 21st century, nor whether land use is considered at all. Within the uncertainty of the representation of land use in current ESMs, our study suggests marginal feedback between land use changes and climate changes triggered by strong greenhouse gas emissions. Hence as a good approximation, climate can be considered as an external forcing: models investigating land-use–conflict dynamics can run offline by prescribing seasonal or mean values of climate as a boundary condition for climate.

Recent advances in the representation of soil carbon decomposition (Goll et al., 2015) and carbon-nitrogen interactions (Parida, 2011; Goll et al., 2012) implemented previously into separate versions of the land surface scheme JSBACH are here combined in a single version which is set to be used in the upcoming 6th phase of coupled model intercomparison project (CMIP6) (Eyring et al., 2016). Here we demonstrate that the new version of JSBACH is able to reproduce the spatial variability in the reactive nitrogen loss pathways as derived from a compilation of δ15N data (r=.63, RMSE=.26, Taylor score=.81). The inclusion of carbon-nitrogen interactions leads to a moderate reduction (−10 %) of the carbon-concentration feedback (βL) and has a negligible effect on the sensitivity of the land carbon cycle to warming (γL) compared to the same version of the model without carbon-nitrogen interactions in idealized simulations (1 % increase in atmospheric carbon dioxide per yr). In line with evidence from elevated carbon dioxide manipulation experiments (Shi et al., 2015; Liang et al., 2016), pronounced nitrogen scarcity is alleviated by (1) the accumulation of nitrogen due to enhanced nitrogen inputs by biological nitrogen fixation and reduced losses by leaching and volatilization as well as the (2) enhanced turnover of organic nitrogen. The strengths of the land carbon feedbacks of the recent version of JSBACH, with βL=0.61 Pg ppm−1 and γL=−27.5 Pg °C−1, are 34 % and 53 % less than the averages of CMIP5 models (Arora et al., 2013), although the CMIP5 version of JSBACH simulated βL and γL which are 59 % and 42 % higher than multi-model average. These changes are primarily due to the new decomposition model, stressing the importance of getting the basics right (here: the decomposition of soil carbon) before increasing the complexity of the model (here: carbon-nitrogen interactions).

[1] The new Max-Planck-Institute Earth System Model (MPI-ESM) is used in the Coupled Model Intercomparison Project phase 5 (CMIP5) in a series of climate change experiments for either idealized CO2-only forcing or forcings based on observations and the Representative Concentration Pathway (RCP) scenarios. The paper gives an overview of the model configurations, experiments related forcings, and initialization procedures and presents results for the simulated changes in climate and carbon cycle. It is found that the climate feedback depends on the global warming and possibly the forcing history. The global warming from climatological 1850 conditions to 2080–2100 ranges from 1.5°C under the RCP2.6 scenario to 4.4°C under the RCP8.5 scenario. Over this range, the patterns of temperature and precipitation change are nearly independent of the global warming. The model shows a tendency to reduce the ocean heat uptake efficiency toward a warmer climate, and hence acceleration in warming in the later years. The precipitation sensitivity can be as high as 2.5% K−1 if the CO2 concentration is constant, or as small as 1.6% K−1, if the CO2 concentration is increasing. The oceanic uptake of anthropogenic carbon increases over time in all scenarios, being smallest in the experiment forced by RCP2.6 and largest in that for RCP8.5. The land also serves as a net carbon sink in all scenarios, predominantly in boreal regions. The strong tropical carbon sources found in the RCP2.6 and RCP8.5 experiments are almost absent in the RCP4.5 experiment, which can be explained by reforestation in the RCP4.5 scenario.

[1] The purpose of this paper is to give a rather comprehensive description of the models for natural and anthropogenically driven changes in biogeography as implemented in the land component JSBACH of the Max Planck Institute Earth system model (MPI-ESM). The model for natural land cover change (DYNVEG) features two types of competition: between the classes of grasses and woody types (trees, shrubs) controlled by disturbances (fire, windthrow) and within those vegetation classes between different plant functional types based on relative net primary productivity advantages. As part of this model, the distribution of land unhospitable to vegetation (hot and cold deserts) is determined dynamically from plant productivity under the prevailing climate conditions. The model for anthropogenic land cover change implements the land use transition approach by Hurtt et al. (2006). Our implementation is based on the assumption that historically pastures have been preferentially established on former grasslands (“pasture rule”). We demonstrate that due to the pasture rule, deforestation reduces global forest area between 1850 and 2005 by 15% less than without. Because of the pasture rule the land cover distribution depends on the full history of land use transitions. This has implications for the dynamics of natural land cover change because assumptions must be made on how agriculturalists react to a changing natural vegetation in their environment. A separate model representing this process has been developed so that natural and anthropogenic land cover change can be simulated consistently. Certain aspects of our model implementation are illustrated by selected results from the recent CMIP5 simulations.

The present paper addresses the origin of natural variability arising internally from the climate system of the global carbon cycle at centennial time scales. The investigation is based on the Max Planck Institute for Meteorology, Coupled Model Intercomparison Project Phase 5 (MPI-MCMIP5) preindustrial control simulations with the MPI Earth System Model in low resolution (MPI-ESM-LR) supplemented by additional simulations conducted for further analysis. The simulations show a distinct low-frequency component in the global terrestrial carbon content that induces atmospheric CO2 variations on centennial time scales of up to 3 ppm. The main drivers for these variations are low-frequency fluctuations in net primary production (NPP) of the land biosphere. The signal arises from small regions scattered across the whole globe with a pronounced source in North America. The main reason for the global NPP fluctuations is found in climatic changes leading to long-term variations in leaf area index, which largely determines the strength of photosynthetic carbon assimilation. The underlying climatic changes encompass several spatial diverse climatic alterations. For the particular case of North America, the carbon storage changes are (besides NPP) also dependent on soil respiration. This second mechanism is strongly connected to low-frequency variations in incoming shortwave radiation at the surface. ©2013. American Geophysical Union. All Rights Reserved.

[1] In recent generation Earth system models (ESMs), land-surface grid cells are represented as tiles covered by different plant functional types such as trees or grasses. Here, we present an evaluation of the vegetation-cover module of the ESM developed at the Max Planck Institute for Meteorology in Hamburg, Germany (MPI-ESM) for present-day conditions. The vegetation continuous fields (VCF) product that is based on satellite observations in 2001 is used to evaluate the fractional distributions of woody vegetation cover and bare ground. The model performance is quantified using two metrics: a square of the Pearson correlation coefficient, r2, and the root-mean-square error (RMSE). On a global scale, r2 and RMSE of modeled tree cover are equal to 0.61 and 0.19, respectively, which we consider as satisfactory values. The model simulates tree cover and bare ground with r2 higher for the Northern Hemisphere (0.66) than for the Southern Hemisphere (0.48–0.50). We complement this analysis with an evaluation of the simulated land-surface albedo using the difference in net surface radiation. On a global scale, the correlation between modeled and observed albedos is high during all seasons, whereas the main disagreement occurs in spring in the high northern latitudes. This discrepancy can be attributed to a high sensitivity of the land-surface albedo to the simulated snow cover and snow-masking effect of trees. By contrast, the tropics are characterized by very high correlation and relatively low RMSE (5.4–6.5 W/m2) during all seasons. The presented approach could be applied for an evaluation of vegetation cover and land-surface albedo simulated by different ESMs.

The scientific understanding of the Earth's climate system, including the central question of how the climate system is likely to respond to human-induced perturbations, is comprehensively captured in GCMs and Earth System Models(ESM). Diagnosing the simulated climate response, and comparing responses across different models, is crucially dependent on transparent assumptions of how the GCM/ESM has been driven – especially because the implementation can involve subjective decisions and may differ between modelling groups performing the same experiment. This paper outlines the climate forcings and setup of the Met Office Hadley Centre ESM, HadGEM2-ES for the CMIP5 set of centennial experiments. We document the prescribed greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the HadGEM2-ES historical and future experiments following the Representative Concentration Pathways. In addition, we provide details of how HadGEM2-ES ensemble members were initialised from the control run and how the palaeoclimate and AMIP experiments, as well as the "emission-driven" RCP experiments were performed.

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. So-called Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models to identify common signals and understand model similarities and differences without being hindered by ad-hoc differences in model set-up or experimental boundary conditions. The activity known as the Coupled Model Intercomparison Project (CMIP) has thus grown significantly in scope and as it enters its 6th phase, CMIP6, the design and documentation of individual simulations has been devolved to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilise climate or avoid dangerous climate change. For over a decade C4MIP has coordinated coupled climate-carbon cycle simulations and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has formed this experimental design the simulations also fit into the wider CMIP activity and conform to some common standards such as documentation and diagnostic requests and are designed to complement the CMIP core experiments known as the DECK. C4MIP has 3 key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation; (2) idealised coupled and partially-coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components; (3) future scenario simulations to project how the Earth System will respond over the 21st century and beyond to anthropogenic activity. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set-up and run the simulations. Particular attention is paid to boundary conditions and input data required, and also the output diagnostics requested. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.

Photosynthetic capacity and its relationship to leaf nitrogen content are two of the most sensitive parameters of terrestrial biosphere models (TBM) whose representation in global-scale simulations has been severely hampered by a lack of systematic analyses using a sufficiently broad database. Here, we use data of qualitative traits, climate and soil to subdivide the terrestrial vegetation into functional types (PFT), and then assimilate observations of carboxylation capacity, V max (723 data points), and maximum photosynthesis rates, A max (776 data points), into the C 3 photosynthesis model proposed by Farquhar et al. to constrain the relationship of V 25 max (V max normalised to 25 °C) to leaf nitrogen content per unit leaf area for each PFT. In a second step, the resulting functions are used to predict V 25 max per PFT from easily measurable values of leaf nitrogen content in natural vegetation (1966 data points). Mean values of V 25 max thus obtained are implemented into a TBM (BETHY within the coupled climate-vegetation model ECHAM5/JSBACH) and modelled gross primary production (GPP) is compared with independent observations on stand scale. Apart from providing parameter ranges per PFT constrained from much more comprehensive data, the results of this analysis enable several major improvements on previous parameterisations. (1) The range of mean V 25 max between PFTs is dominated by differences of photosynthetic nitrogen use efficiency (NUE, defined as V 25 max divided by leaf nitrogen content), while within each PFT, the scatter of V 25 max values is dominated by the high variability of leaf nitrogen content. (2) We find a systematic depression of NUE on certain tropical soils that are known to be deficient in phosphorous. (3) V 25 max of tropical trees derived by this study is substantially lower than earlier estimates currently used in TBMs, with an obvious effect on modelled GPP and surface temperature. (4) The root-mean-squared difference between modelled and observed GPP is substantially reduced.

The aim of this study was to develop an advanced parameterization of the snow-free land surface albedo for climate modelling describing the temporal variation of surface albedo as a function of vegetation phenology on a monthly time scale. To estimate the effect of vegetation phenology on snow-free land surface albedo, remotely sensed data products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra platform measured during 2001 to 2004 are used. The snow-free surface albedo variability is determined by the optical contrast between the vegetation canopy and the underlying soil surface. The MODIS products of the white-sky albedo for total shortwave broad bands and the fraction of absorbed photosynthetically active radiation (FPAR) are analysed to separate the vegetation canopy albedo from the underlying soil albedo. Global maps of pure soil albedo and pure vegetation albedo are derived on a 0.5° regular latitude/longitude grid, re-sampling the high-resolution information from remote sensing-measured pixel level to the model grid scale and filling up gaps from the satellite data. These global maps show that in the northern and mid-latitudes soils are mostly darker than vegetation, whereas in the lower latitudes, especially in semi-deserts, soil albedo is mostly higher than vegetation albedo. The separated soil and vegetation albedo can be applied to compute the annual surface albedo cycle from monthly varying leaf area index. This parameterization is especially designed for the land surface scheme of the regional climate model REMO and the global climate model ECHAM5, but can easily be integrated into the land surface schemes of other regional and global climate models.

The increase of atmospheric CO2 concentrations due to anthropogenic activities is substantially damped by the ocean, whose CO2 uptake is determined by the state of the ocean, which in turn is influenced by climate change. We investigate the mechanisms of the ocean’s carbon uptake within the feedback loop of atmospheric CO2 concentration, climate change and atmosphere/ocean CO2 flux. We evaluate two transient simulations from 1860 until 2100, performed with a version of the Max Planck Institute Earth System Model (MPI-ESM) with the carbon cycle included. In both experiments observed anthropogenic CO2 emissions were prescribed until 2000, followed by the emissions according to the IPCC Scenario A2. In one simulation the radiative forcing of changing atmospheric CO2 is taken into account (coupled), in the other it is suppressed (uncoupled). In both simulations, the oceanic carbon uptake increases from 1 GT C/year in 1960 to 4.5 GT C/year in 2070. Afterwards, this trend weakens in the coupled simulation, leading to a reduced uptake rate of 10% in 2100 compared to the uncoupled simulation. This includes a partial offset due to higher atmospheric CO2 concentrations in the coupled simulation owing to reduced carbon uptake by the terrestrial biosphere. The difference of the oceanic carbon uptake between both simulations is primarily due to partial pressure difference and secondary to solubility changes. These contributions are widely offset by changes of gas transfer velocity due to sea ice melting and wind changes. The major differences appear in the Southern Ocean (−45%) and in the North Atlantic (−30%), related to reduced vertical mixing and North Atlantic meridional overturning circulation, respectively. In the polar areas, sea ice melting induces additional CO2 uptake (+20%).

Global warming caused by anthropogenic CO2 emissions is expected to reduce the capability of the ocean and the land biosphere to take up carbon. This will enlarge the fraction of the CO2 emissions remaining in the atmosphere, which in turn will reinforce future climate change. Recent model studies agree in the existence of such a positive climate–carbon cycle feedback, but the estimates of its amplitude differ by an order of magnitude, which considerably increases the uncertainty in future climate projections. Therefore we discuss, in how far a particular process or component of the carbon cycle can be identified, that potentially contributes most to the positive feedback. The discussion is based on simulations with a carbon cycle model, which is embedded in the atmosphere/ocean general circulation model ECHAM5/MPI-OM. Two simulations covering the period 1860–2100 are conducted to determine the impact of global warming on the carbon cycle. Forced by historical and future carbon dioxide emissions (following the scenario A2 of the Intergovernmental Panel on Climate Change), they reveal a noticeable positive climate–carbon cycle feedback, which is mainly driven by the tropical land biosphere. The oceans contribute much less to the positive feedback and the temperate/boreal terrestrial biosphere induces a minor negative feedback. The contrasting behavior of the tropical and temperate/boreal land biosphere is mostly attributed to opposite trends in their net primary productivity (NPP) under global warming conditions. As these findings depend on the model employed they are compared with results derived from other climate–carbon cycle models, which participated in the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP).

International audience; The quantification of sources and sinks of carbon from land use and land cover changes (LULCC) is uncertain. We investigated how the parametrization of LULCC and of organic matter decomposition, as well as initial land cover, affects the historical and future carbon fluxes in an Earth System Model (ESM). Using the land component of the Max Planck Institute ESM, we found that the historical (1750-2010) LULCC flux varied up to 25% depending on the fraction of biomass which enters the atmosphere directly due to burning or is used in short-lived products. The uncertainty in the decadal LULCC fluxes of the recent past due to the parametrization of decomposition and direct emissions was 0.6 Pg C yr −1 , which is 3 times larger than the uncertainty previously attributed to model and method in general. Preindustrial natural land cover had a larger effect on decadal LULCC fluxes than the aforementioned parameter sensitivity (1.0 Pg C yr −1). Regional differences between reconstructed and dynamically computed land covers, in particular, at low latitudes, led to differences in historical LULCC emissions of 84-114 Pg C, globally. This effect is larger than the effects of forest regrowth, shifting cultivation, or climate feedbacks and comparable to the effect of differences among studies in the terminology of LULCC. In general, we find that the practice of calibrating the net land carbon balance to provide realistic boundary conditions for the climate component of an ESM hampers the applicability of the land component outside its primary field of application.

Dynamic Global Vegetation Models (DGVM) are an essential part of current state-of-the-art Earth System Models. In recent years, the complexity of DGVM has increased by incorporating new important processes, like e.g. nutrient cycling and land cover dynamics while biogeophysical processes, like surface radiation have been not much further developed. Canopy radiation models are however very important for the estimation of absorption and reflected fluxes and are essential for a proper estimation of surface carbon, energy and water fluxes. The present study provides an overview about current implementations of canopy radiation schemes in a couple of state-of-the-art DGVMs and evaluates their accuracy in simulating canopy absorption and reflection for a variety of different surface conditions. Systematic deviations in surface albedo and fraction of absorbed photosynthetic active radiation (faPAR) are identified and potential impacts are assessed. The results show clear deviations for both, absorbed and reflected, surface solar radiation fluxes. FaPAR is typically underestimated which results in an underestimation of Gross Primary Productivity (GPP) for the investigated cases. The deviation can be as large as 25% in extreme cases. Deviations in surface albedo range between −0.15 ≤ Δ α ≤ 0.36 with slight positive bias in the order of Δ α ≈ 0.04. Potential radiative forcing caused by albedo deviations is estimated as −1.25 ≤ RF ≤ −0.8 [W m−2] caused by a neglecting the diurnal cycle of surface albedo. The present study is the first one that provides an evaluation of canopy RT schemes in different currently used DGVMs together with an assessment of the potential impact of the identified deviations. The paper illustrates that there is a general need to improve the canopy radiation schemes in DGVMs and provides different perspectives for their improvement.

Climatic Change, 109 (3-4), ISSN:0165-0009, ISSN:1573-1480

[1] Anthropogenic land cover change (ALCC) influences global mean temperatures via counteracting effects: CO2 emissions contribute to global warming, while biogeophysical effects, in particular the increase in surface albedo, often impose a cooling influence. Previous studies of idealized, large-scale deforestation found that albedo cooling dominates over CO2 warming in boreal regions, indicating that boreal reforestation is not an effective mitigation tool. Here we show the importance of past land use decisions in influencing the mitigation potential of reforestation on these lands. In our simulations, CO2 warming dominates over albedo cooling because past land use decisions resulted in the use of the most productive land with larger carbon stocks and less snow than on average. As a result past land use decisions extended CO2 dominance to most agriculturally important regions in the world, suggesting that in most places reversion of past land cover change could contribute to climate change mitigation. While the relative magnitude of CO2 and albedo effects remains uncertain, the historical land use pattern is found to be biased towards stronger CO2 and weaker albedo effects as compared to idealized large-scale deforestation.

Thum, T., et al. (2011), 'Soil carbon model alternatives for ECHAM5/JSBACH climate model: Evaluation and impacts on global carbon cycle estimates', Journal of Geophysical Research, Vol. 116, G02028, published 29 June 2011. The version of record is available at doi:10.1029/2010JG001612 © 2011 American Geophysical Union.

We investigate the relative importance of climate change (CC) and anthropogenic land cover change (ALCC) for the dust emissions and burden changes between the late nineteenth century and today. For this purpose, the climate-aerosol model ECHAM6-HAM2 is complemented by a new scheme to derive potential dust sources at runtime using the vegetation cover provided by the land component JSBACH of ECHAM6. Dust emissions are computed online using information from the ECHAM6 atmospheric component. This allows us to account for changes in land cover and climate interactively and to distinguish between emissions from natural and agricultural dust sources. For today's climate we find that nearly 10% of dust particles are emitted from agricultural areas. According to our simulations, global annual dust emissions have increased by 25% between the late nineteenth century and today (e. g., from 729 Tg/a to 912 Tg/a). Globally, CC and ALCC (e. g., agricultural expansion) have both contributed to this change (56% and 40%, respectively). There are however large regional differences. For example, change in dust emissions in Africa are clearly dominated by CC. Global dust burden have increased by 24.5% since the late nineteenth century, which results in a clear-sky radiative forcing at top of the atmosphere of similar to 0.14W/m(2). Based on these findings, we recommend that both climate changes and anthropogenic land cover changes should be considered when investigating long-term changes in dust emissions.

[1] Anthropogenic land cover change (ALCC) is one of the few climate forcings with still unknown sign of their climate response. Major uncertainty results from the often counteracting temperature responses to biogeochemical as compared to biogeophysical effects. Here, we separate the strength of these two effects for ALCC during the last millennium. We add unprecedented detail by (i) using a coupled atmosphere/ocean general circulation model (GCM), and (ii) applying a high-detail reconstruction of historical ALCC. We find that biogeophysical effects have a slight cooling influence on global mean temperature (−0.03 K in the 20th century), while biogeochemical effects lead to strong warming (0.16–0.18 K). During the industrial era, both effects cause significant changes in certain regions; only few regions, however, experience biogeophysical cooling strong enough to dominate the overall temperature response. This study therefore suggests that the climate response to historical ALCC, both globally and in most regions, is dominated by the rise in CO2 caused by ALCC emissions.

[1] The large AD 1258 eruption had a stratospheric sulfate load approximately ten times greater than the 1991 Pinatubo eruption. Yet surface cooling was not substantially larger than for Pinatubo (∼0.4 K). We apply a comprehensive Earth System Model to demonstrate that the size of the aerosol particles needs to be included in simulations, especially to explain the climate response to large eruptions. The temperature response weakens because increased density of particles increases collision rate and therefore aerosol growth. Only aerosol particle sizes substantially larger than observed after the Pinatubo eruption yield temperature changes consistent with terrestrial Northern Hemisphere summer temperature reconstructions. These results challenge an oft-held assumption of volcanic impacts not only with respect to the immediate or longer-term temperature response, but also any ecosystem response, including extinctions.

[1] Transient simulations are performed over the entire last millennium with a general circulation model that couples the atmosphere, ocean, and the land surface with a closed carbon cycle. This setup applies a high-detail reconstruction of anthropogenic land cover change (ALCC) as the only forcing to the climate system with two goals: (1) to isolate the effects of ALCC on the carbon cycle and the climate independently of any other natural and anthropogenic disturbance and (2) to assess the importance of preindustrial human activities. With ALCC as only forcing, the terrestrial biosphere experiences a net loss of 96 Gt C over the last millennium, leading to an increase of atmospheric CO2 by 20 ppm. The biosphere-atmosphere coupling thereby leads to a restoration of 37% and 48% of the primary emissions over the industrial (A.D. 1850–2000) and the preindustrial period (A.D. 800–1850), respectively. Because of the stronger coupling flux over the preindustrial period, only 21% of the 53 Gt C preindustrial emissions remain airborne. Despite the low airborne fraction, atmospheric CO2 rises above natural variability by late medieval times. This suggests that human influence on CO2 began prior to industrialization. Global mean temperatures, however, are not significantly altered until the strong population growth in the industrial period. Furthermore, we investigate the effects of historic events such as epidemics and warfare on the carbon budget. We find that only long-lasting events such as the Mongol invasion lead to carbon sequestration. The reason for this limited carbon sequestration is indirect emissions from past ALCC that compensate carbon uptake in regrowing vegetation for several decades. Drops in ice core CO2 are thus unlikely to be attributable to human action. Our results indicate that climate-carbon cycle studies for present and future centuries, which usually start from an equilibrium state around 1850, start from a significantly disturbed state of the carbon cycle.

Uncertainty in climate sensitivity is a fundamental problem for projections of the future climate. Equilibrium climate sensitivity is defined as the asymptotic response of global-mean surface air temperature to a doubling of the atmospheric CO2 concentration from the preindustrial level (approximate to 280 ppm). In spite of various efforts to estimate its value, climate sensitivity is still not well constrained. Here we show that the probability of high climate sensitivity is higher than previously thought because uncertainty in historical radiative forcing has not been sufficiently considered. The greater the uncertainty that is considered for radiative forcing, the more difficult it is to rule out high climat sensitivity, although low climate sensitivity (

[1] We determine both the impact of atmosphere-ocean and atmosphere-vegetation feedback, and their synergy on northern latitude climate in response to the orbitally-induced changes in mid-Holocene insolation. For this purpose, we present results of eight simulations using the general circulation model ECHAM5-MPIOM including the land surface scheme JSBACH with a dynamic vegetation module. The experimental set-up allows us to apply a factor-separation technique to isolate the contribution of dynamic Earth system components (atmosphere, atmosphere-ocean, atmosphere-vegetation, atmosphere-ocean-vegetation) to the total climate change signal. Moreover, in order to keep the definition of seasons consistent with insolation forcing, we define the seasons on an astronomical basis. Our results reveal that north of 40°N atmosphere-vegetation feedback (maximum in spring of 0.08°C) and synergistic effects (maximum in winter of 0.25°C) are weaker than in previous studies. The most important modification of the orbital forcing is related to the atmosphere-ocean component (maximum in autumn of 0.78°C).

[1] In two sensitivity experiments using the Earth System Model of the Max Planck Institute for Meteorology (MPI-ESM), the vegetation cover of the ice-free land surface has been set worldwide to either forest or grassland in order to quantify the quasi-equilibrium response of the atmosphere and ocean components to extreme land surface boundary conditions. After 400 years of model integration, the global mean annual surface temperature increased by 0.7°K and declined by 0.6°K in the forest and grassland simulations, respectively, as compared to the control simulation. Thereafter, the geographic distribution of vegetation has been allowed to respond interactively to climate. After subsequent 500 years of interactive climate-vegetation dynamics, both forest and grassland simulations converged to essentially the same climate state as in the control simulation. This convergence suggests an absence of multiple climate-forest states in the current version of the MPI-ESM.

Previous modelling studies have shown that the response of the ocean and the vegetation to mid-Holocene insolation feeds back on the climate. There is less consensus, however, on the relative magnitude of the two feedbacks and the strength of the synergy between them. This discrepancy may arise partly from the statistical uncertainty caused by internal climate variability as the common analysis period is only about a century. Therefore, we have performed an ensemble of centennial-scale simulations using the general circulation model ECHAM5/JSBACH-MPIOM. The direct atmospheric response and the weak atmosphere-vegetation feedback are statistically robust. The synergy is always weak and it changes sign between the ensemble members. The simulations, including a dynamic ocean, show a large variability at sea-ice margins. This variability leads to a sampling error which affects the magnitude of the diagnosed feedbacks. Citation: Otto, J., T. Raddatz, and M. Claussen (2009), Climate variability-induced uncertainty in mid-Holocene atmosphere-ocean-vegetation feedbacks, Geophys. Res. Lett., 36, L23710, doi:10.1029/2009GL041457.

[1] We calculate the radiative forcing (RF) from surface albedo changes over the last millennium applying a recently published, population-based reconstruction of anthropogenic land cover change (ALCC). This study thus allows for the first time to assess anthropogenic effects on climate during the pre-industrial era at high spatial and temporal detail. We find that the RF is small throughout the pre-industrial period on the global scale (negative with a magnitude less than 0.05 W/m2) and not strong enough to explain the cooling reconstructed from climate proxies between A.D. 1000 and 1900. For the regional scale, however, our results suggest an early anthropogenic impact on climate: Already in A.D. 800, the surface energy balance was altered by ALCC at a strength comparable to present-day greenhouse gas forcing, e.g., −2.0 W/m2 are derived for parts of India for that time. Several other regions exhibit a distinct variability of RF as a result of major epidemics and warfare, with RF changes in the order of 0.1 W/m2 within just one century.

[1] Humans have substantially modified the Earth's land cover, especially by transforming natural ecosystems to agricultural areas. In preindustrial times, the expansion of agriculture was probably the dominant process by which humankind altered the Earth system, but little is known about its extent, timing, and spatial pattern. This study presents an approach to reconstruct spatially explicit changes in global agricultural areas (cropland and pasture) and the resulting changes in land cover over the last millennium. The reconstruction is based on published maps of agricultural areas for the last three centuries. For earlier times, a country-based method is developed that uses population data as a proxy for agricultural activity. With this approach, the extent of cropland and pasture is consistently estimated since AD 800. The resulting reconstruction of agricultural areas is combined with a map of potential vegetation to estimate the resulting historical changes in land cover. Uncertainties associated with this approach, in particular owing to technological progress in agriculture and uncertainties in population estimates, are quantified. About 5 million km2 of natural vegetation are found to be transformed to agriculture between AD 800 and 1700, slightly more to cropland (mainly at the expense of forested area) than to pasture (mainly at the expense of natural grasslands). Historical events such as the Black Death in Europe led to considerable dynamics in land cover change on a regional scale. The reconstruction can be used with global climate and ecosystem models to assess the impact of human activities on the Earth system in preindustrial times.

Eleven coupled climate–carbon cycle models used a common protocol to study the coupling between climate change and the carbon cycle. The models were forced by historical emissions and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 anthropogenic emissions of CO2 for the 1850–2100 time period. For each model, two simulations were performed in order to isolate the impact of climate change on the land and ocean carbon cycle, and therefore the climate feedback on the atmospheric CO2 concentration growth rate. There was unanimous agreement among the models that future climate change will reduce the efficiency of the earth system to absorb the anthropogenic carbon perturbation. A larger fraction of anthropogenic CO2 will stay airborne if climate change is accounted for. By the end of the twenty-first century, this additional CO2 varied between 20 and 200 ppm for the two extreme models, the majority of the models lying between 50 and 100 ppm. The higher CO2 levels led to an additional climate warming ranging between 0.1° and 1.5°C. All models simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models.

Based on a recent reconstruction of anthropogenic land cover change (ALCC), we derive the associated CO 2 emissions since 800 AD by two independent methods: a bookkeeping approach and a process model. The results are compared with the pre-industrial development of atmospheric CO 2 known from antarctic ice cores. Our results show that pre-industrial CO 2 emissions from ALCC have been relevant for the pre-industrial carbon cycle, although before 1750 AD their trace in atmospheric CO 2 is obscured by other processes of similar magnitude. After 1750 AD, the situation is different: the steep increase in atmospheric CO 2 until 1850 AD—this is before fossil fuel emissions rose to significant values—is to a substantial part explained by growing emissions from ALCC. DOI: 10.1111/j.1600-0889.2010.00479.x To access the supplementary material to this article please see Supplementary files in the column to the right (under Article Tools).

The sensitivity of the climate–biogeochemistry system to volcanic eruptions is investigated using the comprehensive Earth System Model developed at the Max Planck Institute for Meteorology. The model includes an interactive carbon cycle with modules for terrestrial biosphere as well as ocean biogeochemistry. The volcanic forcing is based on a recent reconstruction for the last 1200 yr. An ensemble of five simulations is performed and the averaged response of the system is analysed in particular for the largest eruption of the last millennium in the year 1258. After this eruption, the global annual mean temperature drops by 1 K and recovers slowly during 10 yr. Atmospheric CO 2 concentration declines during 4 yr after the eruption by ca. 2 ppmv to its minimum value and then starts to increase towards the pre-eruption level. This CO 2 decrease is explained mainly by reduced heterotrophic respiration on land in response to the surface cooling, which leads to increased carbon storage in soils, mostly in tropical and subtropical regions. The ocean acts as a weak carbon sink, which is primarily due to temperature-induced solubility. This sink saturates 2 yr after the eruption, earlier than the land uptake. DOI: 10.1111/j.1600-0889.2010.00471.x

The Max Planck Institute Grand Ensemble (MPI‐GE) is the largest ensemble of a single comprehensive climate model currently available, with 100 members for the historical simulations (1850–2005) and four forcing scenarios. It is currently the only large ensemble available that includes scenario representative concentration pathway (RCP) 2.6 and a 1% CO2 scenario. These advantages make MPI‐GE a powerful tool. We present an overview of MPI‐GE, its components, and detail the experiments completed. We demonstrate how to separate the forced response from internal variability in a large ensemble. This separation allows the quantification of both the forced signal under climate change and the internal variability to unprecedented precision. We then demonstrate multiple ways to evaluate MPI‐GE and put observations in the context of a large ensemble, including a novel approach for comparing model internal variability with estimated observed variability. Finally, we present four novel analyses, which can only be completed using a large ensemble. First, we address whether temperature and precipitation have a pathway dependence using the forcing scenarios. Second, the forced signal of the highly noisy atmospheric circulation is computed, and different drivers are identified to be important for the North Pacific and North Atlantic regions. Third, we use the ensemble dimension to investigate the time dependency of Atlantic Meridional Overturning Circulation variability changes under global warming. Last, sea level pressure is used as an example to demonstrate how MPI‐GE can be utilized to estimate the ensemble size needed for a given scientific problem and provide insights for future ensemble projects.

This work documents the ICON-Earth System Model (ICON-ESM V1.0), the first coupled model based on the ICON (ICOsahedral Non-hydrostatic) framework with its unstructured, isosahedral grid concept. T...