Current Earth System Models Research Articles

Molecular Imaging Reveals Two Distinct Mixing States of PM2.5 Particles Sampled in a Typical Beijing Winter Pollution Case.

Mixing states of aerosol particles are crucial for understanding the role of aerosols in influencing air quality and climate. However, a fundamental understanding of the complex mixing states is still lacking because most traditional analysis techniques only reveal bulk chemical and physical properties with limited surface and 3-D information. In this research, 3-D molecular imaging enabled by ToF-SIMS was used to elucidate the mixing states of PM2.5 samples obtained from a typical Beijing winter haze event. In light pollution cases, a thin organic layer covers separated inorganic particles; while in serious pollution cases, ion exchange and an organic-inorganic mixing surface on large-area particles were observed. The new results provide key 3-D molecular information of mixing states, which is highly potential for reducing uncertainty and bias in representing aerosol-cloud interactions in current Earth System Models and improving the understanding of aerosols on air quality and human health.

Emergent Constraint for Future Decline in Arctic Phytoplankton Concentration

AbstractIn recent decades, the Arctic Ocean has experienced continuous warming and freshening, affecting biogeochemical factors such as nutrient supply, light availability, chlorophyll, and productivity. While Arctic marine productivity is projected to increase due to the expansion of the open ocean and increased chlorophyll concentration, uncertainties related to chlorophyll and nutrients may distract the fidelity of productivity in current Earth system models (ESMs). Here, we analyze the existing uncertainty in the Arctic chlorophyll projections using the 26 ESMs participating in Coupled Model Intercomparison Projects 5 and 6 (CMIP5 and CMIP6). We found that the uncertainty in the Arctic chlorophyll projections in the CMIP6 ESMs is greater than in the CMIP5 ESMs due to increasing uncertainty in the background nitrate concentration. A significant relationship between background nitrate and projected chlorophyll (r = 0.86) is demonstrated using the observational climatology of nitrate. Based on this strong relationship, the emergent constraint is applied to reduce the uncertainty of future chlorophyll projections. Declines in chlorophyll concentration based on emergent constraint are estimated to be further decreased in the future (44.9% % to 50.9% %) than at present, which is about three‐fold larger than the multi‐model mean projection (−13.5% %). Comparing cumulative density functions before and after the emergent constraint, the probability of the decreasing chance of chlorophyll is increased by approximately 36% from 60% in prior CMIP5,6 to 93%–96% after constraint. Our results imply that reducing the uncertainty in background nitrate concentration can improve the fidelity of future projections of the Arctic ecosystem in the ESMs.

Amazon windthrow disturbances are likely to increase with storm frequency under global warming

Forest mortality caused by convective storms (windthrow) is a major disturbance in the Amazon. However, the linkage between windthrows at the surface and convective storms in the atmosphere remains unclear. In addition, the current Earth system models (ESMs) lack mechanistic links between convective wind events and tree mortality. Here we find an empirical relationship that maps convective available potential energy, which is well simulated by ESMs, to the spatial pattern of large windthrow events. This relationship builds connections between strong convective storms and forest dynamics in the Amazon. Based on the relationship, our model projects a 51 ± 20% increase in the area favorable to extreme storms, and a 43 ± 17% increase in windthrow density within the Amazon by the end of this century under the high-emission scenario (SSP 585). These results indicate significant changes in tropical forest composition and carbon cycle dynamics under climate change.

Phosphorus and water supply independently control productivity and soil enzyme activity responses to elevated CO2 in an understorey community from a Eucalyptus woodland

AimsWhile it is well-established that nitrogen (N) availability regulates elevated [CO2] (eCO2) effects on plant growth and soil carbon (C) storage in N-limited environments, there are fewer studies investigating the role of phosphorous (P) supply on such responses in P-limited environments. In this study, we explored whether P fertilization influences the response of plant growth, soil enzyme activity and C fluxes to eCO2, and determined how different levels of water availability regulate these processes.MethodsWe used soil collected from a temperate, P-limited Eucalyptus woodland containing the native soil seed bank to grow a potted replica of local understory communities. We exposed the emerging communities to eCO2 under two contrasting water levels and two levels of P fertilization. We assessed plant biomass allocation, the rhizosphere activity of extracellular enzymes related to C, N and P cycles, and pot-level CO2 fluxes.ResultsThe positive effects of eCO2 on plant production and ecosystem C dynamics were strongly constrained by low levels of P availability. Enhanced water supply increased rhizosphere enzyme activity with minor impacts on plant biomass responses to eCO2. Our data also suggest that plant and microbial mechanisms that increase nutrient release from SOM may not be able to overcome this P limitation.ConclusionsWhile current Earth System Models predict positive feedback responses of terrestrial ecosystems on C storage under eCO2, here we emphasize the importance of accounting for the widespread phenomenon of P-limitation in such responses.

Disentangling Aerosol and Cloud Effects on Dimming and Brightening in Observations and CMIP6

AbstractPeriods of dimming and brightening have been recorded in observational datasets of surface solar radiation (SSR) between the mid‐20th century and present day. Atmospheric components affect SSR, including aerosols and clouds, though studies disagree somewhat about the relative effect of each component in different regions. Current Earth system models (ESMs) are unable to simulate observed trends in SSR. This study includes an investigation into observed SSR variations between 1961 and 2014 and an evaluation of the effects of cloud cover variations and impacts of aerosol extinction, using timeseries of SSR and cloud cover from in‐situ measurements. Historical simulations by 42 ESMs participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) have also been studied and compared to observations. The observational study indicates that cloud cover has had a dampening effect on the variations of SSR and that emissions of aerosol and aerosol precursors are the main cause of the general trends in observed SSR in four regions—China, Japan, Europe, and the United States—during 1961–2014. The study of simulated SSR in CMIP6 yields the conclusion that current ESMs remain unable to simulate the magnitude of observed dimming and brightening in China, Japan, and the United States, but that the European SSR trends between 1961 and 2014 are fairly well reproduced in the ESMs. A rough quantification of the regional surface radiation extinction efficiency of aerosol and precursor emissions in the simulations is found to agree with observed values in Europe, but not in the other three regions.

Positive feedback mechanism between biogenic volatile organic compounds and the methane lifetime in future climates

A multitude of biogeochemical feedback mechanisms govern the climate sensitivity of Earth in response to radiation balance perturbations. One feedback mechanism, which remained missing from most current Earth System Models applied to predict future climate change in IPCC AR6, is the impact of higher temperatures on the emissions of biogenic volatile organic compounds (BVOCs), and their subsequent effects on the hydroxyl radical (OH) concentrations. OH, in turn, is the main sink term for many gaseous compounds including methane, which is the second most important human-influenced greenhouse gas in terms of climate forcing. In this study, we investigate the impact of this feedback mechanism by applying two models, a one-dimensional chemistry-transport model, and a global chemistry-transport model. The results indicate that in a 6 K temperature increase scenario, the BVOC-OH-CH4 feedback increases the lifetime of methane by 11.4% locally over the boreal region when the temperature rise only affects chemical reaction rates, and not both, chemistry and BVOC emissions. This would lead to a local increase in radiative forcing through methane (ΔRFCH4) of approximately 0.013 Wm−2 per year, which is 2.1% of the current ΔRFCH4. In the whole Northern hemisphere, we predict an increase in the concentration of methane by 0.024% per year comparing simulations with temperature increase only in the chemistry or temperature increase in chemistry and BVOC emissions. This equals approximately 7% of the annual growth rate of methane during the years 2008–2017 (6.6 ± 0.3 ppb yr−1) and leads to an ΔRFCH4 of 1.9 mWm−2 per year.

Strong isoprene emission response to temperature in tundra vegetation

Emissions of biogenic volatile organic compounds (BVOCs) are a crucial component of biosphere-atmosphere interactions. In northern latitudes, climate change is amplified by feedback processes in which BVOCs have a recognized, yet poorly quantified role, mainly due to a lack of measurements and concomitant modeling gaps. Hence, current Earth system models mostly rely on temperature responses measured on vegetation from lower latitudes, rendering their predictions highly uncertain. Here, we show how tundra isoprene emissions respond vigorously to temperature increases, compared to model results. Our unique dataset of direct eddy covariance ecosystem-level isoprene measurements in two contrasting ecosystems exhibited Q10 (the factor by which the emission rate increases with a 10 °C rise in temperature) temperature coefficients of up to 20.8, that is, 3.5 times the Q10 of 5.9 derived from the equivalent model calculations. Crude estimates using the observed temperature responses indicate that tundra vegetation could enhance their isoprene emissions by up to 41% (87%)-that is, 46% (55%) more than estimated by models-with a 2 °C (4 °C) warming. Our results demonstrate that tundra vegetation possesses the potential to substantially boost its isoprene emissions in response to future rising temperatures, at rates that exceed the current Earth system model predictions.

Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime

Abstract. The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs.

Assessing the Benthic Response to Climate-Driven Methane Hydrate Destabilisation: State of the Art and Future Modelling Perspectives

Modern observations and geological records suggest that anthropogenic ocean warming could destabilise marine methane hydrate, resulting in methane release from the seafloor to the ocean-atmosphere, and potentially triggering a positive feedback on global temperature. On the decadal to millennial timescales over which hydrate-sourced methane release is hypothesized to occur, several processes consuming methane below and above the seafloor have the potential to slow, reduce or even prevent such release. Yet, the modulating effect of these processes on seafloor methane emissions remains poorly quantified, and the full impact of benthic methane consumption on ocean carbon chemistry is still to be explored. In this review, we document the dynamic interplay between hydrate thermodynamics, benthic transport and biogeochemical reaction processes, that ultimately determines the impact of hydrate destabilisation on seafloor methane emissions and the ocean carbon cycle. Then, we provide an overview of how state-of-the-art numerical models treat such processes and examine their ability to quantify hydrate-sourced methane emissions from the seafloor, as well as their impact on benthic biogeochemical cycling. We discuss the limitations of current models in coupling the dynamic interplay between hydrate thermodynamics and the different reaction and transport processes that control the efficiency of the benthic sink, and highlight their shortcoming in assessing the full implication of methane release on ocean carbon cycling. Finally, we recommend that current Earth system models explicitly account for hydrate driven benthic-pelagic exchange fluxes to capture potential hydrate-carbon cycle-climate feed-backs.

A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlands

Abstract. Peatlands have often been neglected in Earth system models (ESMs). Where they are included, they are usually represented via a separate, prescribed grid cell fraction that is given the physical characteristics of a peat (highly organic) soil. However, in reality soils vary on a spectrum between purely mineral soil (no organic material) and purely organic soil, typically with an organic layer of variable thickness overlying mineral soil below. They are also dynamic, with organic layer thickness and its properties changing over time. Neither the spectrum of soil types nor their dynamic nature can be captured by current ESMs. Here we present a new version of an ESM land surface scheme (Joint UK Land Environment Simulator, JULES) where soil organic matter accumulation – and thus peatland formation, degradation and stability – is integrated in the vertically resolved soil carbon scheme. We also introduce the capacity to track soil carbon age as a function of depth in JULES and compare this to measured peat age–depth profiles. The new scheme is tested and evaluated at northern and temperate sites. This scheme simulates dynamic feedbacks between the soil organic material and its thermal and hydraulic characteristics. We show that draining the peatlands can lead to significant carbon loss, soil compaction and changes in peat properties. However, negative feedbacks can lead to the potential for peatlands to rewet themselves following drainage. These ecohydrological feedbacks can also lead to peatlands maintaining themselves in climates where peat formation would not otherwise initiate in the model, i.e. displaying some degree of resilience. The new model produces similar results to the original model for mineral soils and realistic profiles of soil organic carbon for peatlands. We evaluate the model against typical peat profiles based on 216 northern and temperate sites from a global dataset of peat cores. The root-mean-squared error (RMSE) in the soil carbon profile is reduced by 35 %–80 % in the best-performing JULES-Peat simulations compared with the standard JULES configuration. The RMSE in these JULES-Peat simulations is 7.7–16.7 kg C m−3 depending on climate zone, which is considerably smaller than the soil carbon itself (around 30–60 kg C m−3). The RMSE at mineral soil sites is also reduced in JULES-Peat compared with the original JULES configuration (reduced by ∼ 30 %–50 %). Thus, JULES-Peat can be used as a complete scheme that simulates both organic and mineral soils. It does not require any additional input data and introduces minimal additional variables to the model. This provides a new approach for improving the simulation of organic and peatland soils and associated carbon-cycle feedbacks in ESMs.

The DOE E3SM v1.2 Cryosphere Configuration: Description and Simulated Antarctic Ice‐Shelf Basal Melting

AbstractThe processes responsible for freshwater flux from the Antarctic Ice Sheet (AIS), ice‐shelf basal melting and iceberg calving, are generally poorly represented in current Earth System Models (ESMs). Here we document the cryosphere configuration of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) v1.2. This includes simulating Antarctic ice‐shelf basal melting, which has been implemented through simulating the ocean circulation within static Antarctic ice‐shelf cavities, allowing for the ability to calculate ice‐shelf basal melt rates from the associated heat and freshwater fluxes. In addition, we added the capability to prescribe forcing from iceberg melt, allowing for realistic representation of the other dominant mass loss process from the AIS. In standard resolution simulations (using a noneddying ocean) under preindustrial climate forcing, we find high sensitivity of modeled ocean/ice shelf interactions to the ocean state, which can result in a transition to a high basal melt regime under the Filchner‐Ronne Ice Shelf (FRIS), presenting a significant challenge to representing the ocean/ice shelf system in a coupled ESM. We show that inclusion of a spatially dependent parameterization of eddy‐induced transport reduces biases in water mass properties on the Antarctic continental shelf. With these improvements, E3SM produces realistic ice‐shelf basal melt rates across the continent that are generally within the range inferred from observations. The accurate representation of ice‐shelf basal melting within a coupled ESM is an important step toward reducing uncertainties in projections of the Antarctic response to climate change and Antarctica's contribution to global sea‐level rise.

Biota-mediated carbon cycling-A synthesis of biotic-interaction controls on blue carbon.

Research into biotic interactions has been a core theme of ecology for over a century. However, despite the obvious role that biota play in the global carbon cycle, the effects of biotic interactions on carbon pools and fluxes are poorly understood. Here we develop a conceptual framework that illustrates the importance of biotic interactions in regulating carbon cycling based on a literature review and a quantitative synthesis by means of meta-analysis. Our study focuses on blue carbon ecosystems-vegetated coastal ecosystems that function as the most effective long-term CO2 sinks of the biosphere. We demonstrate that a multitude of mutualistic, competitive and consumer-resource interactions between plants, animals and microbiota exert strong effects on carbon cycling across various spatial scales ranging from the rhizosphere to the landscape scale. Climate change-sensitive abiotic factors modulate the strength of biotic-interaction effects on carbon fluxes, suggesting that the importance of biota-mediated carbon cycling will change under future climatic conditions. Strong effects of biotic interactions on carbon cycling imply that biosphere-climate feedbacks may not be sufficiently represented in current Earth system models. Inclusion of new functional groups in these models, and new approaches to simplify species interactions, may thus improve the predictions of biotic effects on the global climate.

Ice Algae Model Intercomparison Project phase 2 (IAMIP2)

Abstract. Ice algae play a fundamental role in shaping sea-ice-associated ecosystems and biogeochemistry. This role can be investigated by field observations; however the influence of ice algae at the regional and global scales remains unclear due to limited spatial and temporal coverage of observations and because ice algae are typically not included in current Earth system models. To address this knowledge gap, we introduce a new model intercomparison project (MIP), referred to here as the Ice Algae Model Intercomparison Project phase 2 (IAMIP2). IAMIP2 is built upon the experience from its previous phase and expands its scope to global coverage (both Arctic and Antarctic) and centennial timescales (spanning the mid-20th century to the end of the 21st century). Participating models are three-dimensional regional and global coupled sea-ice–ocean models that incorporate sea-ice ecosystem components. These models are driven by the same initial conditions and atmospheric forcing datasets by incorporating and expanding the protocols of the Ocean Model Intercomparison Project, an endorsed MIP of the Coupled Model Intercomparison Project phase 6 (CMIP6). Doing so provides more robust estimates of model bias and uncertainty and consequently advances the science of polar marine ecosystems and biogeochemistry. A diagnostic protocol is designed to enhance the reusability of the model data products of IAMIP2. Lastly, the limitations and strengths of IAMIP2 are discussed in the context of prospective research outcomes.

Coupling the U.K. Earth System Model to Dynamic Models of the Greenland and Antarctic Ice Sheets

AbstractThe physical interactions between ice sheets and the atmosphere and ocean around them are major factors in determining the state of the climate system, yet many current Earth System models omit them entirely or treat them very simply. In this work we describe how models of the Greenland and Antarctic ice sheets have been incorporated into the global U.K. Earth System model (UKESM1) via substantial technical developments with a two‐way coupling that passes fluxes of energy and water, and the topography of the ice sheet surface and ice shelf base, between the component models. File‐based coupling outside the running model executables is used throughout to pass information between the components, which we show is both physically appropriate and convenient within the UKESM1 structure. Ice sheet surface mass balance is computed in the land surface model using multi‐layer snowpacks in subgrid‐scale elevation ranges and compares well to the results of regional climate models. Ice shelf front discharge forms icebergs, which drift and melt in the ocean. Ice shelf basal mass balance is simulated using the full three‐dimensional ocean model representation of the circulation in ice‐shelf cavities. We show a range of example results, including from simulations with changes in ice sheet height and thickness of hundreds of meters, and changes in ice sheet grounding line and land‐terminating margin of many tens of kilometres, demonstrating that the coupled model is computationally stable when subject to significant changes in ice sheet geometry.

FAMOUS version xotzt (FAMOUS-ice): a general circulation model (GCM) capable of energy- and water-conserving coupling to an ice sheet model

Abstract. The physical interactions between ice sheets and their surroundings are major factors in determining the state of the climate system, yet many current Earth system models omit them entirely or approximate them in a heavily parameterised manner. In this work we have improved the snow and ice sheet surface physics in the FAMOUS climate model, with the aim of improving the representation of polar climate and implementing a bidirectional coupling to the Glimmer dynamic ice sheet model using the water and energy fluxes calculated by FAMOUS. FAMOUS and Glimmer are both low-resolution, computationally affordable models used for multi-millennial simulations. Glaciated surfaces in the new FAMOUS-ice are modelled using a multi-layer snow scheme capable of simulating compaction of firn and the percolation and refreezing of surface melt. The low horizontal resolution of FAMOUS compared to Glimmer is mitigated by implementing this snow model on sub-grid-scale tiles that represent different elevations on the ice sheet within each FAMOUS grid box. We show that with this approach FAMOUS-ice can simulate relevant physical processes on the surface of the modern Greenland ice sheet well compared to higher-resolution climate models and that the ice sheet state in the coupled FAMOUS-ice–Glimmer system does not drift unacceptably. FAMOUS-ice coupled to Glimmer is thus a useful tool for modelling the physics and co-evolution of climate and grounded ice sheets on centennial and millennial timescales, with applications to scientific questions relevant to both paleoclimate and future sea level rise.

Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks.

Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO2) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carbon sinks. Using global datasets derived from machine-learning methods and process-based ecosystem models, this study reveals that the interannual variability of the atmospheric vapor pressure deficit (VPD) was significantly negatively correlated with net ecosystem production (NEP) and substantially impacted the interannual variability of the atmospheric CO2 growth rate (CGR). Further analyses found widespread constraints of VPD interannual variability on terrestrial gross primary production (GPP), causing VPD to impact NEP and CGR. Partial correlation analysis confirms the persistent and widespread impacts of VPD on terrestrial carbon sinks compared to other environmental variables. Current Earth system models underestimate the interannual variability in VPD and its impacts on GPP and NEP. Our results highlight the importance of VPD for terrestrial carbon sinks in assessing ecosystems’ responses to future climate conditions.

Oceanic primary production decline halved in eddy-resolving simulations of global warming

Abstract. The decline in ocean primary production is one of the most alarming consequences of anthropogenic climate change. This decline could indeed lead to a decrease in marine biomass and fish catch, as highlighted by recent policy-relevant reports. Because of computational constraints, current Earth system models used to project ocean primary production under global warming scenarios have to parameterize flows occurring below the resolution of their computational grid (typically 1∘). To overcome these computational constraints, we use an ocean biogeochemical model in an idealized configuration representing a mid-latitude double-gyre circulation and perform global warming simulations under an increasing horizontal resolution (from 1 to 1/27∘) and under a large range of parameter values for the eddy parameterization employed in the coarse-resolution configuration. In line with projections from Earth system models, all our simulations project a marked decline in net primary production in response to the global warming forcing. Whereas this decline is only weakly sensitive to the eddy parameters in the eddy-parameterized coarse 1∘ resolution simulations, the simulated decline in primary production in the subpolar gyre is halved at the finest eddy-resolving resolution (−12 % at 1/27∘ vs. −26 % at 1∘) at the end of the 70-year-long global warming simulations. This difference stems from the high sensitivity of the sub-surface nutrient transport to model resolution. Although being only one piece of a much broader and more complicated response of the ocean to climate change, our results call for improved representation of the role of eddies in nutrient transport below the seasonal mixed layer to better constrain the future evolution of marine biomass and fish catch potential.

A Comparison of Linear Conventional and Nonlinear Microbial Models for Simulating Pulse Dynamics of Soil Heterotrophic Respiration in a Semi‐Arid Grassland

AbstractAs a critical process in regulating terrestrial feedback to climate change, soil heterotrophic respiration is commonly simulated with the first‐order kinetics in current Earth system models. Compared with the first‐order kinetic models, explicit microbial models are expected to better simulate nonlinear carbon (C)‐cycle phenomena, such as the pulse dynamics of soil heterotrophic respiration driven by dry‐rewetting cycles in grasslands. However, these two types of models (i.e., linear conventional and nonlinear microbial models) have never been compared based on in situ observations of soil heterotrophic respiration in the semi‐arid grassland, which is significantly affected by the dry‐rewetting events. Here, based on the field data of soil heterotrophic respiration in a semi‐arid grassland in northern China, we first showed that the shift from a conventional linear model to a nonlinear microbial model did not substantially improve the simulation of soil heterotrophic respiration. Then, we quantified the contributions of different moisture‐response functions to the uncertainty in simulating the soil C dynamics. The results showed that the selection of moisture‐response functions combined with parameterization in the soil C models dominated the modeled uncertainties in soil heterotrophic respiration. These findings suggest that both the conventional linear model and nonlinear microbial model can simulate well the pulse dynamic of soil heterotrophic respiration in grasslands with an improved parameterization of water regulation on soil carbon decomposition. This study also calls for more observations of nonlinear C phenomena for reducing the simulation uncertainty on soil C cycling in Earth system models.

Multivariable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL (Institute Pierre Simon Laplace) climate model

Abstract. Evaluating land surface models (LSMs) using available observations is important for understanding the potential and limitations of current Earth system models in simulating water- and carbon-related variables. To reveal the error sources of a LSM, five essential climate variables have been evaluated in this paper (i.e., surface soil moisture, evapotranspiration, leaf area index, surface albedo, and precipitation) via simulations with the IPSL (Institute Pierre Simon Laplace) LSM ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) model, particularly focusing on the difference between (i) forced simulations with atmospheric forcing data (WATCH Forcing Data ERA-Interim – WFDEI) and (ii) coupled simulations with the IPSL atmospheric general circulation model. Results from statistical evaluation, using satellite- and ground-based reference data, show that ORCHIDEE is well equipped to represent spatiotemporal patterns of all variables in general. However, further analysis against various landscape and meteorological factors (e.g., plant functional type, slope, precipitation, and irrigation) suggests potential uncertainty relating to freezing and/or snowmelt, temperate plant phenology, irrigation, and contrasted responses between forced and coupled mode simulations. The biases in the simulated variables are amplified in the coupled mode via surface–atmosphere interactions, indicating a strong link between irrigation–precipitation and a relatively complex link between precipitation–evapotranspiration that reflects the hydrometeorological regime of the region (energy limited or water limited) and snow albedo feedback in mountainous and boreal regions. The different results between forced and coupled modes imply the importance of model evaluation under both modes to isolate potential sources of uncertainty in the model.

Improved model simulation of soil carbon cycling by representing the microbially derived organic carbon pool.

During the decomposition process of soil organic carbon (SOC), microbial products such as microbial necromass and microbial metabolites may form an important stable carbon (C) pool, called microbially derived C, which has different decomposition patterns from plant-derived C. However, current Earth System Models do not simulate this microbially derived C pool separately. Here, we incorporated the microbial necromass pool to the first-order kinetic model and the Michaelis-Menten model, respectively, and validated model behaviors against previous observation data from the decomposition experiments of 13C-labeled necromass. Our models showed better performance than existing models and the Michaelis-Menten model was better than the first-order kinetic model. Microbial necromass C was estimated to be 10-27% of total SOC in the study soils by our models and therefore should not be ignored. This study provides a novel modification to process-based models for better simulation of soil organic C under the context of global changes.