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Increasing the Depth of a Land Surface Model. Part I: Impacts on the Subsurface Thermal Regime and Energy Storage
Abstract
The representation of the thermal and hydrological states in Land Surface Models is important for a realistic simulation of land-atmosphere coupling processes. The available evidence indicates that the simulation of subsurface thermodynamics in Earth System Models is inaccurate due to a zero-heat-flux bottom boundary condition being imposed too close to the surface. In order to assess the influence of soil model depth on the simulated terrestrial energy and subsurface thermal state, sensitivity experiments have been carried out in piControl, historical and RCP scenarios. A deeper bottom boundary condition placement has been introduced into the JSBACH land surface model by enlarging the vertical stratification from 5 to 12 layers, thereby expanding its depth from 9.83 to 1416.84 m. The model takes several hundred years to reach an equilibrium state in stand-alone piControl simulations. A depth of 100 m is necessary, and 300 m recommendable, to handle the warming trends in historical and scenario simulations. Using a deep bottom boundary, warming of the soil column is reduced by 0.5 to 1.5 K in scenario simulations over most land areas, with the largest changes occurring in northern high latitudes, consistent with polar amplification. Energy storage is 3 to 5 times larger in the deep than in the shallow model and increases progressively with additional soil layers until the model depth reaches about 200 m. While the contents of Part I focus on the sensitivity of subsurface thermodynamics to enlarging the space for energy, Part II (Steinert et al. 2021) addresses the sensitivity to changing the space for water and improving hydrological and phase-change interactions.
... Ground thermodynamic definitions are based on ground temperatures (table 1: SLT, ALT, ZAA, TTOP). These definitions assume permafrost presence to be predominantly determined by the propagation of surface temperatures into the ground, though are influenced by the depth of the model bottom boundary condition [35,36] and soil thermal diffusivity [37,38]. Definitions of this type differ in the depth at which ground temperatures below 0 • C are considered to determine the presence of permafrost (fixed for SLT and variable for ALT, ZAA, and TTOP). ...
... Additionally, permafrost area differences between ESMs can be expected due to differences in the structure and parameterization of the land surface model components, recognized as one of the primary sources of uncertainty in Arctic climate change projections [44,45]. Differences in the representation of processes such as the snow insulation, the thermal and hydrological discretization, the depth of the soil column, the definition of thermal properties due to water phase changes, and the physical characteristics of the organic layer near the ground surface, limit their ability to represent subsurface processes, particularly relevant for cold regions [17,21,25,36,37,46]. ...
... Many models employ a zero-flux bottom boundary condition that distorts the representation of subsurface temperatures by impacting thermal heat diffusion [36,37,47]. The effect of model depth is investigated in figure 3. We divide the CMIP6 models into two sub-ensembles, separated by model depth. ...
Global permafrost regions are undergoing significant changes due to global warming, whose assessments often rely on permafrost extent estimates derived from climate model simulations. These assessments employ a range of definitions for the presence of permafrost, leading to inconsistencies in the calculation of permafrost area. Here, we present permafrost area calculations using 10 different definitions for detecting permafrost presence based on either ground thermodynamics, soil hydrology, or air-ground coupling from an ensemble of 32 Earth system models. We find that variations between permafrost-presence definitions result in substantial differences of up to 18 million km2, where any given model could both over- or underestimate the present-day permafrost area. Ground-thermodynamic-based definitions are, on average, comparable with observations but are subject to a large inter-model spread. The associated uncertainty of permafrost area estimates is reduced in definitions based on ground-air coupling. However, their representation of permafrost area strongly depends on how each model represents the ground-air coupling processes. The definition-based spread in permafrost area can affect estimates of permafrost-related impacts and feedbacks, such as quantifying permafrost carbon changes. For instance, the definition spread in permafrost area estimates can lead to differences in simulated permafrost-area soil carbon changes of up to 28%. We therefore emphasize the importance of consistent and well-justified permafrost-presence definitions for robust projections and accurate assessments of permafrost from climate model outputs.
... Deep subsurface temperatures allow recovery of past GST histories by borehole temperature profile (BTP) inversion techniques (Mareschal and Beltrami, 1992;Huang et al., 2000;Pollack and Smerdon, 2004;Jaume-Santero et al., 2016;Cuesta-Valero et al., 2022), which makes them a valuable source for climate reconstruction as far as the two fundamental hypotheses are sustained: SAT and GST changes are coupled at long-term scales and GST changes are propagated downwards by heat conduction, the main heat transfer mechanism in solids. Support for SAT-GST coupling has been found so far from observational temperature data at some sites in North America (e.g., Putnam and Chapman, 1996;Beltrami and Kellman, 2003;Smerdon et al., 2004;Bartlett et al., 2005Bartlett et al., , 2006 and Europe (e.g., Cermak et al., 2014;Cermak and Bodri, 2016;Melo-Aguilar et al., 2022;Petersen, 2022;Dorau et al., 2022) as well as from climate simulations (González-Rouco et al., 2006;Smerdon et al., 2009;García-García et al., 2016Melo-Aguilar et al., 2018;González-Rouco et al., 2021). These studies showed a strong coupling at long-term scales globally, with some degree of seasonal decoupling due to snow cover (Beltrami and Kellman, 2003) or changes in the surface energy balance Melo-Aguilar et al., 2018) at regional scales. ...
An assessment of the soil and bedrock thermal structure of the Sierra de Guadarrama, in central Spain, is provided using subsurface and ground surface temperature data coming from four deep (20 m) monitoring profiles belonging to the Guadarrama Monitoring Network (GuMNet) and two shallow profiles (1 m) from the Spanish Meteorology Service (Agencia Estatal de Meteorología, AEMET) covering the time spans of 2015–2021 and 1989–2018, respectively. An evaluation of air and ground surface temperature coupling showed that soil insulation due to snow cover is the main source of seasonal decoupling, being especially relevant in winter at high-altitude sites. Temperature propagation in the subsurface was characterized by assuming a heat conductive regime by considering apparent thermal diffusivity values derived from the amplitude attenuation and phase shift of the annual cycle with depth. This methodology was further extended to consider the attenuation of all harmonics in the spectral domain, which allowed for analysis of thermal diffusivity from high-frequency changes in the soil near the surface at short timescales. For the deep profiles, the apparent thermal diffusivity ranges from 1 to 1.3×10-6 m2 s−1, which is consistent with values for gneiss and granite, the major bedrock components in the Sierra de Guadarrama. However, thermal diffusivity is lower and more heterogeneous in the soil layers close to the surface (0.4–0.8×10-6 m2 s−1). An increase in diffusivity with depth was observed that was generally larger in the soil–bedrock transition at 4–8 m depth. The outcomes are relevant for the understanding of soil thermodynamics in relation to other soil properties. Results with the spectral method suggest that changes in near-surface thermal diffusivity are related to changes in soil moisture content, which makes it a potential tool to gain information about soil drought and water resource availability from soil temperature data.
... This is very different to the standard vertical setup which represents the soil column by 5 layers reaching to a depth of less than 10 m. Imposing a deeper bottom boundary is important for a realistic representation of the soil thermodynamic regime, with implications for subsurface heat conduction and energy distribution (MacDougall et al., 2008;González-Rouco et al., 2009;González-Rouco et al., 2021), as too shallow LSMs alter the distribution of temperatures in the subsurface (Alexeev et al., 2007;Smerdon and Stieglitz, 2006). As shown by Steinert et al. (2021a) a depth > 150 m is required to resemble an infinitely deep soil in climate change simulations of centennial timescales. ...
The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone, with differences in model structure and parametrizations being one of the main sources of uncertainty. One particularly challenging aspect in modelling is the representation of terrestrial processes in permafrost-affected regions, which are often governed by spatial heterogeneity far below the resolution of the models' land surface components. Here, we use the Max Planck Institute (MPI) Earth System Model to investigate how different plausible assumptions for the representation of permafrost hydrology modulate land–atmosphere interactions and how the resulting feedbacks affect not only the regional and global climate, but also our ability to predict whether the high latitudes will become wetter or drier in a warmer future. Focusing on two idealized setups that induce comparatively “wet” or “dry” conditions in regions that are presently affected by permafrost, we find that the parameter settings determine the direction of the 21st-century trend in the simulated soil water content and result in substantial differences in the land–atmosphere exchange of energy and moisture. The latter leads to differences in the simulated cloud cover during spring and summer and thus in the planetary energy uptake. The respective effects are so pronounced that uncertainties in the representation of the Arctic hydrological cycle can help to explain a large fraction of the inter-model spread in regional surface temperatures and precipitation. Furthermore, they affect a range of components of the Earth system as far to the south as the tropics. With both setups being similarly plausible, our findings highlight the need for more observational constraints on the permafrost hydrology to reduce the inter-model spread in Arctic climate projections.
... Such a result is in agreement with previous analyses comparing ground heat flux and ground heat storage from subsurface temperature profiles and climate simulations, which has lead to the development of deeper LSMs (MacDougall et al., 2008(MacDougall et al., , 2010Cuesta-Valero et al., 2016). Furthermore, this deeper subsurface in LSMs has also improved the representation of permafrost dynamics, showing how the ground heat storage retrieved from measurements of subsurface temperature profiles has informed the development of land surface model components for global climate models Nicolsky et al., 2007;Hermoso de Mendoza et al., 2020;González-Rouco et al., 2021;Steinert et al., 2021). Another approach may be to use the retrieved estimates of continental heat storage as a reference to constraint projections of climate change (Tokarska et al., 2020;Ribes et al., 2021). ...
Heat storage within the Earth system is a fundamental metric for understanding climate change. The current energy imbalance at the top of the atmosphere causes changes in energy storage within the ocean, the atmosphere, the cryosphere, and the continental landmasses. After the ocean, heat storage in land is the second largest term of the Earth heat inventory, affecting physical processes relevant to society and ecosystems, such as the stability of the soil carbon pool. Here, we present an update of the continental heat storage, combining for the first time the heat in the land subsurface, inland water bodies, and permafrost thawing. The continental landmasses stored 23.8 ± 2.0 × 10 21 J during the period 1960-2020, but the distribution of heat among the three components is not homogeneous. The sensible diffusion of heat through the ground accounts for ∼ 90 % of the continental heat storage, with inland water bodies and permafrost degradation (i.e. latent heat) accounting for ∼ 0.7 % and ∼ 9 % of the continental heat, respectively. Although the inland water bodies and permafrost soils store less heat than the solid ground, we argue that their associated climate phenomena justify their monitoring and inclusion in the Earth heat inventory.
... These long-term estimates of surface temperature and ground heat flux changes have also been used to evaluate the ability of general circulation models (GCMs) to reproduce past changes in the conditions of the shallow continental subsurface, which has increased our knowledge of the Earth system as well as our confidence in future projections (González-Rouco et al., 2006;González-Rouco et al., 2009;Cuesta-Valero et al., 2019;Melo-Aguilar et al., 2020). Furthermore, ground surface temperature and heat flux reconstructions from subsurface temperature data have been essential for informing the development of land surface model components, improving the representation of heat transfer through the continental subsurface in climate simulations Nicolsky et al., 2007;Stevens et al., 2007Stevens et al., , 2008MacDougall et al., 2010;Cuesta-Valero et al., 2016;Hermoso de Mendoza et al., 2020;Cuesta-Valero et al., 2021b;González-Rouco et al., 2021). ...
Estimates of the past thermal state of the land surface are crucial to assess the magnitude of current anthropogenic climate change as well as to assess the ability of Earth System Models (ESMs) to forecast the evolution of the climate near the ground, which is not included in standard meteorological records. Subsurface temperature reacts to long-term changes in surface energy balance – from decadal to millennial time scales – thus constituting an important record of the dynamics of the climate system that contributes, with low-frequency information, to proxy-based paleoclimatic reconstructions. Broadly used techniques to retrieve past temperature and heat flux histories from subsurface temperature profiles based on a singular value decomposition (SVD) algorithm were able to provide robust global estimates for the last millennium, but the approaches used to derive the corresponding 95 % confidence interval were wrong from a statistical point of view in addition to being difficult to interpret. To alleviate the lack of a meaningful framework for estimating uncertainties in past temperature and heat flux histories at regional and global scales, we combine a new bootstrapping sampling strategy with the broadly used SVD algorithm and assess its performance against the original SVD technique and another technique based on generating perturbed parameter ensembles of inversions. The new bootstrap approach is able to reproduce the prescribed surface temperature series used to derive an artificial profile. Bootstrap results are also in agreement with the global mean surface temperature history and the global mean heat flux history retrieved in previous studies. Furthermore, the new bootstrap technique provides a meaningful uncertainty range for the inversion of large sets of subsurface temperature profiles. We suggest the use of this new approach particularly for aggregating results from a number of individual profiles, and to this end, we release the programs used to derive all inversions in this study as a suite of codes labeled CIBOR v1: Codes for Inverting BORholes, version 1.
... This 315 is very different to the standard vertical setup which represents the soil column by 5 layers reaching to a depth of less than 10 m. Imposing a deeper bottom boundary is important for a realistic representation of the soil thermodynamic regime, with implications for subsurface heat conduction and energy distribution (MacDougall et al., 2008;González-Rouco et al., 2009;González-Rouco et al., 2021), as too shallow LSMs alter the distribution of temperatures in the subsurface (Alexeev et al., 2007;Smerdon and Stieglitz, 2006). As shown by Steinert et al. (2021b) a depth > 150 m is required to resemble an infinitely 320 deep soil in climate-change simulations of centennial timescales. ...
The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone, with differences in model structure and parametrizations being one of the main sources of uncertainty. One particularly challenging aspect in modelling is the representation of terrestrial processes in permafrost-affected regions, which are often governed by spatial heterogeneity far below the resolution of the models' land surface components. Here, we use the MPI Earth System model to investigate how different plausible assumptions for the representation of the permafrost hydrology modulate the land-atmosphere interactions and how the resulting feedbacks affect not only the regional and global climate, but also our ability to predict whether the high latitudes will become wetter or drier in a warmer future. Focusing on two idealized setups that induce comparatively "wet" or "dry" conditions in regions that are presently affected by permafrost, we find that the parameter settings determine the direction of the 21st-century trend in the simulated soil water content and result in substantial differences in the land-atmosphere exchange of energy and moisture. The latter leads to differences in the simulated cloud cover and thus in the planetary energy uptake. The respective effects are so pronounced that uncertainties in the representation of the Arctic hydrological cycle can help to explain a large fraction of the inter-model spread in regional surface temperatures and precipitation. Furthermore, they affect a range of components of the Earth system as far to the south as the tropics. With both setups being similarly plausible, our findings highlight the need for more observational constraints on the permafrost hydrology to reduce the inter-model spread in Arctic climate projections.
... Including the Tibetan Plateau and the permafrost zones of Antarctica will be possible in the near future, as those require a modest increase in computational resources and input data to derive soil stratigraphies. Nicolsky et al., 2007;Hermoso de Mendoza et al., 2020;González-Rouco et al., 2021;Steinert et al., 2021). Another approach may be to use the retrieved estimates of continental heat storage as a reference to constraint projections of climate change (Tokarska et al., 2020;Ribes et al., 2021). ...
Heat storage within the Earth system is a fundamental metric to understand climate change. The current energy imbalance at the top of the atmosphere causes changes in energy storage within the ocean, the atmosphere, the cryosphere, and the continental landmasses. After the ocean, heat storage in land is the second largest term of the Earth heat inventory, affecting physical processes relevant to society and ecosystems, such as the stability of the soil carbon pool. Here, we present an update of the continental heat storage combining for the first time the heat in the land subsurface, inland water bodies, and permafrost thawing. The continental landmasses stored 23.9±0.4×1021 J during the period 1960–2020, but the distribution of heat among the three components is not homogeneous. The ground stores ~90 % of the continental heat storage, with inland water bodies and permafrost degradation accounting for ~0.7 % and ~9 % of the continental heat, respectively. Although the inland water bodies and permafrost soils store less heat than the ground, we argue that their associated climate phenomena justify their monitoring and inclusion in the Earth heat inventory.
Plain Language Summary
Global warming is associated with heat accumulation in the Earth system due to the intensification of the greenhouse effect. The available heat is distributed unevenly throughout the climate subsystems: the ocean, land, atmosphere, and cryosphere. Overall, the current generation of climate models captures this partitioning well but, on average, shows an overestimation of the ocean heat uptake and an underestimation of the land heat uptake. Previous studies have shown that the lack of heat input into the land comes from structural limitations in the land model components used. In this study, we account for these shortcomings, which greatly improve the land heat uptake in simulations of future climate scenarios. We find that, as a result, the fraction of simulated heat taken up by the ocean is reduced. This leads to a heat distribution among the climate subsystems that is closer to observational estimates. Our results highlight that land heat uptake is relevant for the Earth system heat distribution and that future research should consider modeling approaches including a more realistic land heat sink.
Quantifying permafrost carbon feedback is a critical step in conveying the significance of perma-frost carbon emissions to decision-makers and stakeholders and achieving sustainable development goals. Simply assuming a rapid reduction in permafrost area may be an overaggressive approach. This study revisited permafrost carbon feedback by incorporating relatively clear permafrost physics into the Dynamic Integrated model of Climate and the Economy (DICE). The results show that the total carbon released from permafrost regions in 2100 is 30.5 GtC, which is accompanied by an additional atmospheric warming of 0.038 ℃, much lower than previous studies. This study provides a potential perspective to scrutinize the climate feedback and related economic impacts due to permafrost thawing. We may need to pay more attention to carbon processes during nongrowing seasons and sudden changes in permafrost.
Vegetation plays a fundamental role in modulating the exchange of water, energy, and carbon fluxes between the land and the atmosphere. These exchanges are modeled by Land Surface Models (LSMs), which are an essential part of numerical weather prediction and data assimilation. However, most current LSMs implemented specifically in weather forecasting systems use climatological vegetation indices, and land use/land cover data sets in these models are often outdated. In this study, we update land surface data in the European Centre for Medium‐range Weather Forecast (ECMWF) land surface modeling system (ECLand) using Earth observation‐based time varying leaf area index and land use/land cover data, and evaluate the impact of vegetation dynamics on model performance. The performance of the simulated latent heat flux and soil moisture is then evaluated against global gridded observation‐based data sets. Updating the vegetation information does not always yield better model performances because the model's parameters are adapted to the previously employed land surface information. Therefore we recalibrate key soil and vegetation‐related parameters at individual grid cells to adjust the model parameterizations to the new land surface information. This substantially improves model performance and demonstrates the benefits of updated vegetation information. Interestingly, we find that a regional parameter calibration outperforms a globally uniform adjustment of parameters, indicating that parameters should sufficiently reflect spatial variability in the land surface. Our results highlight that newly available Earth‐observation products of vegetation dynamics and land cover changes can improve land surface model performances, which in turn can contribute to more accurate weather forecasts.
Plain Language Summary
In recent decades, planet Earth has received more energy from the sun than it has radiated back into space. This has led to an excess of energy that is causing global warming and climate change. While most of this excess energy is absorbed by Earth's oceans, some of it is used to melt ice in perennially frozen ground called permafrost. However, we do not know how much. In this study, we use a computer model to calculate how much energy the permafrost in the Arctic has absorbed over the past four decades. We find that permafrost has absorbed about 3.9 sextillion Joules of energy between 1980 and 2018. About 44% of this energy was used to melt ice contained in the ground, while the remaining energy was used to warm the ground. Our results suggest that permafrost absorbs a similar amount of energy as other large bodies of ice on Earth, such as ice sheets, glaciers, or sea ice. Our study implies that the energy taken up by permafrost needs to be considered in global assessments of Earth's energy budget, which has not been the case in the past.
Soil moisture is an essential variable for the exchange of energy, moisture, and substances between the land surface and the atmosphere. Its effects on temperature and precipitation are diverse and complex. However, the schemes used in climate models to simulate soil moisture, also called soil hydrological schemes, are often very simplified due to the origin of climate models from weather models. In climate models, which compute simulations at coarse resolutions of tens or hundreds of kilometers of edge length, many processes can be neglected. However, the resolution of those models is steadily increasing and now generally has 0.22° in the recently published coordinated project of regional climate models called CORDEX-CORE. As a consequence, higher resolved data and more processes have to be simulated. This is even more true with respect to convection-permitting simulations having edge lengths of a few kilometers. With increasing model resolutions, the complexity and differentiation of questions to be answered by the use of climate models increases as well. This is also the case of the BigData@Geo-project, in which framework this thesis was written. The aim of this project is to provide high-resolution climate information for the Bavarian administrative district of Lower Franconia for stakeholders from agriculture, forestry, and viticulture.
Due to these applied and basic requirements and objectives, there is also the need of model development for the regional climate model REMO (version 2015) used in this work. Thus, the main goal of this thesis is to replace the existing singlelayer soil hydrological scheme by a multilayer one. The advantage of multiple simulated soil layers is that the vertical movement of water, thus percolation and capillary rise, can now be simulated. This is done on the basis of soil hydrological parameters, those value is determined by the water retention curve as a function of soil texture and soil moisture. Various parameterizations have been developed for this curve, whereas the one of Clapp-Hornberger and van Genuchten were used herein. Additionally, the soil moisture can now be simulated to a depth of approximately 10 m or the bedrock's depth, respectively. Thus, in contrast to the previous scheme, which depth is limited to the rooting depth, there is the possibility that water is also available below the root zone. Hence, the absolute amount of water in the root zone is increased. Furthermore, the layering allows evaporation from bare soil based only on the water available in the uppermost layer. Another process, that can be reparameterized due to the layering and the data sets explained subsequently, is infiltration.
To use the new scheme, information on soil hydrological parameters, rooting depth, and the depth to bedrock is required. For this purpose, appropriate data sets have to be prepared and implemented into the model. Regarding the rooting depth, three data sets with different depths, definitions, and resolutions were compared. Finally, the rooting depth from the vegetation module iMOVE, coupled with another REMO version, is used since a coupling between iMOVE and the multilayer soil scheme is planned in the future. With this, the rooting depths are consistent. In addition, the underlying resolution of the data is high and maximum rooting depths are considered, which are particularly important for simulating land surface-atmosphere interactions. These advantages were not provided by the other data sets. In the final model version, SoilGrids data are used for the depth to bedrock and grain size distributions. A comparison with other soil data sets was done in a parallel thesis (Ziegler 2022). For SoilGrids, it should be underlined that the grain size distributions enable the use of continuous pedotransfer functions instead of five discrete texture classes for the soil hydrological parameters. This leads to a much better differentiation of the heterogeneous soil.
For this thesis, 19 simulations were calculated for Europe and an extended German region with resolutions of 0.44° and 0.11°, respectively, covering the period of 2000 to 2018. The implementation of the multilayer soil scheme leads to a decrease in root zone soil moisture compared to the singlelayer scheme. Nevertheless, the absolute amount of soil moisture increases by the consideration of soil below the root zone. Related to the individual layers, the soil moisture is thus underestimated, but in the process of model development an improvement can be achieved compared to ERA5. Furthermore, the new scheme results in a reduction of evapotranspiration that occurs across all model development steps and is especially present during summer. When compared to validation data from ERA5 and GLEAM, this is shown to be an improvement that occurs in space as well as bias and distribution.
The same was found for surface runoff. Schemes implemented for this purpose (Philip, Geen-Ampt), which differ from the defaultly used Improved-Arno scheme by taking hydrlogical parameters into account, were able to show a further improvement in lowlands. In mountainous regions, however, the bias increased due to the not included consideration of slopes. Consequently, the final model version uses the Improved-Arno scheme. Temperature initially increases through the original version of the multilayer scheme, resulting in an overestimation instead of the previous underestimation by the singlelayer soil relative to E-OBS. Although the model development leads to a reduction in temperature, this reduction turns out to be too large, so that the temperature bias is ultimately higher than in the singlelayer model version. However, since evapotranspiration has been significantly improved, this error can possibly be attributed to a temperature overtuning.
The analysis of heat events investigating the summers of 2003 and 2018 has shown that the model development leads to an improved simulation of these events compared to the singlelayer scheme. While this is not true for the spatial behavior of the mean temperature, there is a clear improvement of its temporal one. Additionally, the better simulation of daily extreme temperatures, especially its minimum, leads to an increase of the daily temperature range. This is usually underestimated too much by climate models.
The consideration of vertical water fluxes has shown that there is still enormous potential for model development with regard to (soil) hydrological processes. This is especially true for future simulations with convection-permitting resolution. Thus, subgrid information of the soil and the orography should be considered. On the one hand, this serves to represent existing heterogeneities and, on the other hand, can contribute to the improvement of existing processes, as shown by the example of infiltration schemes. Since the simulated drainage increases due to the multilayer soil scheme to the same extent as the surface runoff decreases, the water is subsequently no longer available to the model. Therefore, groundwater should also be considered in the model. A number of studies have found an added value from integrating this variable and related processes. In the medium term, however, coupling to a hydrological model is generally recommended in order to be able to adequately represent the processes relevant in high-resolution simulations. ParFlow or mHM, for example, are suitable for this purpose.
Overall, it can be noted that the multilayer soil scheme provides an added value because variables like evapotranspiration and surface runoff, that are difficult to simulate and subsequently to be bias adjusted in postprocessing, are modeled much better than using the singlelayer scheme. This is also true for extreme temperatures. Both improvements are caused by the soil layering and associated processes. Regarding the data, it can be seen that the rooting depth, the consideration of SoilGrids, and the vertical soil information is are responsible for the further optimization. In addition, the higher information content available by representing the layered soil moisture can also be classified as an added value.
An assessment of the soil and bedrock thermal structure of the Sierra de Guadarrama, in Central Spain, is provided using subsurface and ground surface temperature data coming from four deep (20 m) monitoring profiles belonging to the Guadarrama Monitoring Network (GuMNet), and two shallow (1 m) from the Spanish Meteorology Service (AEMET), covering the time span of 2015–2021 and 1989–2018, respectively. An evaluation of air and ground surface temperature coupling shows soil insulation due to snow cover is the main source of seasonal decoupling, being especially relevant in winter at high altitude sites. Temperature propagation in the subsurface is characterized by assuming a heat conductive regime, by considering apparent thermal diffusivity values derived from the amplitude attenuation and phase shift of the annual cycle with depth. For the deep profiles, the apparent thermal diffusivity ranges from 1 to 1.3 10−6 m2s−1, consistent with values for gneiss and granite, the major bedrock components in the Sierra de Guadarrama. However, thermal diffusivity is lower and more heterogeneous in the soil layers close to the surface (0.4–0.8 10−6 m2s−1). An increase of diffusivity with depth is observed, being generally larger in the soil-bedrock transition, at 4–8 m depth. A new method based on the spectral attenuation of temperature harmonics allows for analyzing thermal diffusivity from high-frequency changes in the soil near the surface at short timescales. The results are relevant for the understanding of soil thermodynamics in relation to other soil properties and suggest that changes in heat diffusivity are related to soil moisture content changes, which makes this method a potential tool in soil drought and water resource availability reconstruction from soil temperature data.
The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone, with differences in model structure and parametrizations being one of the main sources of uncertainty. One particularly challenging aspect in modelling is the representation of terrestrial processes in permafrost-affected regions, which are often governed by spatial heterogeneity far below the resolution of the models' land surface components. Here, we use the MPI Earth System model to investigate how different plausible assumptions for the representation of the permafrost hydrology modulate the land-atmosphere interactions and how the resulting feedbacks affect not only the regional and global climate, but also our ability to predict whether the high latitudes will become wetter or drier in a warmer future. Focusing on two idealized setups that induce comparatively "wet" or "dry" conditions in regions that are presently affected by permafrost, we find that the parameter settings determine the direction of the 21 st century trend in the simulated soil water content and result in substantial differences in the land-atmosphere exchange of energy and moisture. The latter leads to differences in the simulated cloud cover and thus in the planetary energy uptake. The respective effects are so pronounced that uncertainties in the representation of the Arctic hydrological cycle can help to explain a large fraction of the inter-model spread in regional surface temperatures and precipitation. Furthermore, they affect a range of components of the Earth system as far to the south as the tropics. With both setups being similarly plausible, our findings highlight the need for more observational constraints on the permafrost hydrology to reduce the inter-model spread in Arctic climate projections.
Plain Language Summary
Many current‐generation climate models have land components that are too shallow. Under climate change conditions, the long‐term warming trend at the surface propagates deeper into the ground than the commonly used 3–10 m. Shallow models alter the terrestrial heat storage and distribution of temperatures in the subsurface, influencing the simulated land‐atmosphere interactions. Previous studies focusing on annual timescales suggest that deeper models are required to match subsurface‐temperature observations and the classic analytical heat conduction solution. However, for a systematic investigation of land‐model deepening in the frame of anthropogenic climate change, the classic analytical solution is inaccurate because it does not mimic the timescale and amplitude of the simulated warming trend. This study intends to bridge the gap between analytical and simulation‐based estimates of the subsurface thermodynamic state by adapting the classic analytical framework to mimic long‐term anthropogenic warming. The analysis shows that a land‐model depth of at least 170 m is recommended for a proper simulation of the post‐1850 ground climate, which differs up to 30% from the estimate of the classic approach. Compared to previous studies, this provides an accurate estimate of the required land model depth for long‐term climate‐change simulations and indicates the relative bias in insufficiently deep land models.
The impact of various modifications of the JSBACH Land Surface Model to represent soil temperature and cold-region hydro-thermodynamic processes in climate projections of the 21st century is examined. We explore the sensitivity of JSBACH to changes in the soil thermodynamics, energy balance and storage, and the effect of including freezing and thawing processes. The changes involve 1) the net effect of an improved soil physical representation and 2) the sensitivity of our results to changed soil parameter values and their contribution to the simulation of soil temperatures and soil moisture, both aspects being presented in the frame of an increased bottom boundary depth from 9.83 m to 1418.84 m. The implementation of water phase changes and supercooled water in the ground creates a coupling between the soil thermal and hydrological regimes through latent heat exchange. Momentous effects on subsurface temperature of up to ±3 K, together with soil drying in the high northern latitudes, can be found at regional scales when applying improved hydro-thermodynamic soil physics. The sensitivity of the model to different soil parameter datasets occurs to be low but shows important implications for the root zone soil moisture content. The evolution of permafrost under pre-industrial forcing conditions emerges in simulated trajectories of stable states that differ by 4 – 6 • 10 ⁶ km ² and shows large differences in the spatial extent of 10 ⁵ –10 ⁶ km ² by 2100, depending on the model configuration.
The impact of various modifications of the JSBACH Land Surface Model to represent soil temperature and cold-region hydro-thermodynamic processes in climate projections of the 21st century is examined. We explore the sensitivity of JSBACH to changes in the soil thermodynamics, energy balance and storage, and the effect of including freezing and thawing processes. The changes involve 1) the net effect of an improved soil physical representation and 2) the sensitivity of our results to changed soil parameter values and their contribution to the simulation of soil temperatures and soil moisture, both aspects being presented in the frame of an increased bottom boundary depth from 9.83 m to 1418.84 m. The implementation of water phase changes and supercooled water in the ground creates a coupling between the soil thermal and hydrological regimes through latent heat exchange. Momentous effects on subsurface temperature of up to ±3 K, together with soil drying in the high northern latitudes, can be found at regional scales when applying improved hydro-thermodynamic soil physics. The sensitivity of the model to different soil parameter datasets occurs to be low but shows important implications for the root zone soil moisture content. The evolution of permafrost under pre-industrial forcing conditions emerges in simulated trajectories of stable states that differ by 4 – 6 • 10 ⁶ km ² and shows large differences in the spatial extent of 10 ⁵ –10 ⁶ km ² by 2100, depending on the model configuration.
Energy exchanges among climate subsystems are of critical importance to determine the climate sensitivity of the Earth's system to greenhouse gases, to quantify the magnitude and evolution of the Earth's energy imbalance, and to project the evolution of future climate. Thus, ascertaining the magnitude of and change in the Earth's energy partition within climate subsystems has become urgent in recent years. Here, we provide new global estimates of changes in ground surface temperature, ground surface heat flux, and continental heat storage derived from geothermal data using an expanded database and new techniques. Results reveal markedly higher changes in ground heat flux and heat storage within the continental subsurface than previously reported, with land temperature changes of 1 K and continental heat gains of around 12 ZJ during the last part of the 20th century relative to preindustrial times. Half of the heat gain by the continental subsurface since 1960 has occurred in the last 20 years.
Human-induced atmospheric composition changes cause a radiative imbalance at
the top of the atmosphere which is driving global warming. This Earth energy imbalance (EEI) is the most critical number defining the prospects for continued global warming and climate change. Understanding the heat gain of
the Earth system – and particularly how much and where the heat is
distributed – is fundamental to understanding how this affects warming
ocean, atmosphere and land; rising surface temperature; sea level; and loss
of grounded and floating ice, which are fundamental concerns for society.
This study is a Global Climate Observing System (GCOS) concerted
international effort to update the Earth heat inventory and presents an
updated assessment of ocean warming estimates as well as new and updated estimates
of heat gain in the atmosphere, cryosphere and land over the period
1960–2018. The study obtains a consistent long-term Earth system heat gain
over the period 1971–2018, with a total heat gain of 358±37 ZJ,
which is equivalent to a global heating rate of 0.47±0.1 W m−2.
Over the period 1971–2018 (2010–2018), the majority of heat gain is reported
for the global ocean with 89 % (90 %), with 52 % for both periods in
the upper 700 m depth, 28 % (30 %) for the 700–2000 m depth layer and 9 % (8 %) below 2000 m depth. Heat gain over land amounts to 6 %
(5 %) over these periods, 4 % (3 %) is available for the melting of
grounded and floating ice, and 1 % (2 %) is available for atmospheric warming. Our
results also show that EEI is not only continuing, but also increasing: the EEI
amounts to 0.87±0.12 W m−2 during 2010–2018. Stabilization of
climate, the goal of the universally agreed United Nations Framework Convention on Climate
Change (UNFCCC) in 1992 and the Paris
Agreement in 2015, requires that EEI be reduced to approximately zero to
achieve Earth's system quasi-equilibrium. The amount of CO2 in the
atmosphere would need to be reduced from 410 to 353 ppm to increase heat
radiation to space by 0.87 W m−2, bringing Earth back towards energy
balance. This simple number, EEI, is the most fundamental metric that the
scientific community and public must be aware of as the measure of how well
the world is doing in the task of bringing climate change under control, and
we call for an implementation of the EEI into the global stocktake based on
best available science. Continued quantification and reduced uncertainties
in the Earth heat inventory can be best achieved through the maintenance of
the current global climate observing system, its extension into areas of
gaps in the sampling, and the establishment of an international framework for
concerted multidisciplinary research of the Earth heat inventory as
presented in this study. This Earth heat inventory is published at the German Climate Computing Centre (DKRZ, https://www.dkrz.de/, last access: 7 August 2020) under the DOI
https://doi.org/10.26050/WDCC/GCOS_EHI_EXP_v2
(von Schuckmann et al., 2020).
Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 %–40 %∘C-1 of global mean surface air temperature increase.
For the current generation of earth system models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), the range of equilibrium climate sensitivity (ECS, a hypothetical value of global warming at equilibrium for a doubling of CO 2 ) is 1.8°C to 5.6°C, the largest of any generation of models dating to the 1990s. Meanwhile, the range of transient climate response (TCR, the surface temperature warming around the time of CO 2 doubling in a 1% per year CO 2 increase simulation) for the CMIP6 models of 1.7°C (1.3°C to 3.0°C) is only slightly larger than for the CMIP3 and CMIP5 models. Here we review and synthesize the latest developments in ECS and TCR values in CMIP, compile possible reasons for the current values as supplied by the modeling groups, and highlight future directions. Cloud feedbacks and cloud-aerosol interactions are the most likely contributors to the high values and increased range of ECS in CMIP6.
For years, carbon cycle scientists have sought to understand how a warming climate will impact the decay of soil carbon. However, there have been relatively few investigations of how soils will warm in comparison to the atmosphere. Three recent papers in American Geophysical Union journals have looked at expected soil warming by synthesizing predictions in the Climate Model Intercomparison Project 5 (CMIP5). Collectively, these papers show that soil warming will keep pace with air warming except where snow and ice occur, and that the magnitude of soil warming in northern latitudes is uncertain due to model variability in snow and ice extent. They also show that a considerable portion of anthropogenic warming is being stored in deep soils, and that in comparison to observations, soil heat storage is underrepresented by land models. These studies highlight how important continued investigations of soil climatology are to understanding carbon cycling and Earth energy balance.
Earth system models (ESMs) use bottom boundaries for their land surface model (LSM) components which are shallower than the depth reached by surface temperature changes in the centennial timescale associated with recent climate change. Shallow bottom boundaries reflect energy to the surface, which along with the lack of geothermal heat flux in current land surface models, alter the surface energy balance and therefore affect some feedback processes between the ground surface and the atmosphere, such as permafrost and soil carbon stability. To evaluate these impacts, we modified the subsurface model in the Community Land Model version 4.5 (CLM4.5) by setting a non-zero crustal heat flux bottom boundary condition uniformly across the model and by increasing the depth of the lower boundary from 42.1 to 342.1 m. The modified and original land models were run during the period 1901–2005 under the historical forcing and between 2005 and 2300 under forcings for two future scenarios of moderate (Representative Concentration Pathway 4.5; RCP4.5) and high (RCP8.5) emissions. Increasing the thickness of the subsurface by 300 m increases the heat stored in the subsurface by 72 ZJ (1 ZJ = 1021 J) by the year 2300 for the RCP4.5 scenario and 201 ZJ for the RCP8.5 scenario (respective increases of 260 % and 217 % relative to the shallow model), reduces the loss of near-surface permafrost area in the Northern Hemisphere between 1901 and 2300 by 1.6 %–1.9 %, reduces the loss of intermediate-depth permafrost area (above 42.1 m depth) by a factor of 3–5.5 and reduces the loss of soil carbon by 1.6 %–3.6 %. Each increase of 20 mW m−2 of the crustal heat flux increases the temperature at 3.8 m (the soil–bedrock interface) by 0.04±0.01 K. This decreases near-surface permafrost area slightly (0.3 %–0.8 %) and produces local differences in initial stable size of the soil carbon pool across the permafrost region, which reduces the loss of soil carbon across the region by as much as 1.1 %–5.6 % for the two scenarios. Reducing subsurface thickness from 42.1 to 3.8 m, used by many LSMs, produces a larger effect than increasing it to 342.1 m, because 3.8 m is not enough to damp the annual signal and the subsurface closely follows the air temperature. We determine the optimal subsurface thickness to be 100 m for a 100-year simulation and 200 m for a simulation of 400 years. We recommend short-term simulations to use a subsurface of at least 40 m, to avoid the perturbation of seasonal temperature propagation.
Regional coupled system models require a high-resolution discharge component to couple their atmosphere/land components to the ocean component and to adequately resolve smaller catchments and the day-to-day variability of discharge. As the currently coupled discharge models usually do not fulfill this requirement, we improved a well-established discharge model, the Hydrological Discharge (HD) model, to be globally applicable at 5 Min. resolution. As the first coupled high-resolution discharge simulations are planned over Europe and the Baltic Sea catchment, we focus on the respective regions in the present study. As no river specific parameter adjustments were conducted and since the HD model parameters depend on globally available gridded characteristics, the model is, in principle, applicable for climate change studies and over ungauged catchments. For the validation of the 5 Min. HD (HD5) model, we force it with prescribed fields of surface and subsurface runoff. As no large-scale observations of these variables exist, they need to be calculated by a land surface scheme or hydrology model using observed or re-analyzed meteorological data. In order to pay regard to uncertainties introduced by these calculations, three different methods and datasets were used to derive the required fields of surface and subsurface runoff for the forcing of the HD5 model. However, the evaluation of the model performance itself is hampered by biases in these fields as they impose an upper limit on the accuracy of simulated discharge. 10-years simulations (2000–2009) show that for many European rivers, where daily discharge observations were available for comparison, the HD5 model captures the main discharge characteristics reasonably well. Deficiencies of the simulated discharge could often be traced back to deficits in the various forcing datasets. As direct anthropogenic impact on the discharge, such as by regulation or dams, is not regarded in the HD model, those effects can generally not be simulated. Thus, discharges for many heavily regulated rivers in Scandinavia or for the rivers Volga and Don are not well represented by the model. The comparison of the three sets of simulated discharges indicates that the HD5 model is suitable to evaluate the terrestrial hydrological cycle of climate models or land surface models, especially with regard to the separation of throughfall (rain or snow melt) into surface and subsurface runoff.
Natural and anthropogenic disturbances, in particular forest management, affect forest age structures all around the globe. Forest age structures in turn influence key land surface processes, such as photosynthesis and thus the carbon cycle. Yet, many dynamic global vegetation models (DGVMs), including those used as land surface models (LSMs) in Earth system models (ESMs), do not account for subgrid forest age structures, despite being used to investigate land-use effects on the global carbon budget or simulating biogeochemical responses to climate change. In this paper we present a new scheme to introduce forest age classes in hierarchical tile-based DGVMs combining benefits of recently applied approaches the first being a computationally efficient age-dependent simulation of all relevant processes, such as photosynthesis and respiration, using a restricted number of age classes and the second being the tracking of the exact forest age, which is a prerequisite for any implementation of age-based forest management. This combination is achieved by using the tile hierarchy to track the area fraction for each age on an aggregated plant functional type level, whilst simulating the relevant processes for a set of age classes. We describe how we implemented this scheme in JSBACH4, the LSM of the ICOsahedral Non-hydrostatic Earth system model (ICON-ESM). Subsequently, we compare simulation output to global observation-based products for gross primary production, leaf area index, and above-ground biomass to assess the ability of simulations with and without age classes to reproduce the annual cycle and large-scale spatial patterns of these variables. The comparisons show decreasing differences and increasing computation costs with an increasing number of distinguished age classes. The results demonstrate the benefit of the introduction of age classes, with the optimal number of age classes being a compromise between computation costs and error reduction.
Despite the fundamental importance of soil temperature for Earth's carbon and energy budgets, ecosystem functioning, and agricultural production, studies of climate change impacts on soil processes have mainly relied on air temperatures, assuming they are accurate proxies for soil temperatures. We evaluated changes in soil temperature, moisture, and air temperature predicted over the 21st century from 14 Earth system models. The model ensemble predicted a global mean soil warming of 2.3 ± 0.7 and 4.5 ± 1.1 °C at 100‐cm depth by the end of the 21st century for RCPs 4.5 and 8.5, respectively. Soils at 100 cm warmed at almost exactly the same rate as near‐surface (~1 cm) soils. Globally, soil warming was slightly slower than air warming above it, and this difference increased over the 21st century. Regionally, soil warming kept pace with air warming in tropical and arid regions but lagged air warming in colder regions. Thus, air warming is not necessarily a good proxy for soil warming in cold regions where snow and ice impede the direct transfer of sensible heat from the atmosphere to soil. Despite this effect, high‐latitude soils were still projected to warm faster than elsewhere, albeit at slower rates than surface air above them. When compared with observations, the models were able to capture soil thermal dynamics in most biomes, but some failed to recreate thermal properties in permafrost regions. Particularly in cold regions, using soil warming rather than air warming projections may improve predictions of temperature‐sensitive soil processes.
Given the slow unfolding of what may become catastrophic changes to Earth’s climate, many are understandably distraught by failures of public policy to rise to the magnitude of the challenge. Few in the science community would think to question the scientific response to the unfolding changes. However, is the science community continuing to do its part to the best of its ability? In the domains where we can have the greatest influence, is the scientific community articulating a vision commensurate with the challenges posed by climate change? We think not.
The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time‐evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.
A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI-ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low-level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO 2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO 2 forcing, which nonetheless can be represented by a simple two-layer model.
This paper describes ESM-SnowMIP, an international coordinated modelling
effort to evaluate current snow schemes, including snow schemes that are
included in Earth system models, in a wide variety of settings against local
and global observations. The project aims to identify crucial processes and
characteristics that need to be improved in snow models in the context of
local- and global-scale modelling. A further objective of ESM-SnowMIP is to
better quantify snow-related feedbacks in the Earth system. Although it is
not part of the sixth phase of the Coupled Model Intercomparison Project
(CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface,
Snow and Soil Moisture Model Intercomparison (LS3MIP).
Past climate variations may be uncovered via reconstruction methods
that use proxy data as predictors. Among them, borehole reconstruction is a
well-established technique to recover the long-term past surface air
temperature (SAT) evolution. It is based on the assumption that SAT changes
are strongly coupled to ground surface temperature (GST) changes and
transferred to the subsurface by thermal conduction. We evaluate the SAT–GST
coupling during the last millennium (LM) using simulations from the Community
Earth System Model LM Ensemble (CESM-LME). The validity of such a premise is
explored by analyzing the structure of the SAT–GST covariance during the LM
and also by investigating the evolution of the long-term SAT–GST
relationship. The multiple and single-forcing simulations in the CESM-LME are
used to analyze the SAT–GST relationship within different regions and spatial
scales and to derive the influence of the different forcing factors on producing
feedback mechanisms that alter the energy balance at the surface. The results
indicate that SAT–GST coupling is strong at global and above multi-decadal
timescales in CESM-LME, although a relatively small variation in the
long-term SAT–GST relationship is also represented. However, at a global scale
such variation does not significantly impact the SAT–GST coupling, at local
to regional scales this relationship experiences considerable long-term
changes mostly after the end of the 19th century. Land use land cover changes
are the main driver for locally and regionally decoupling SAT and GST, as
they modify the land surface properties such as albedo, surface roughness and
hydrology, which in turn modifies the energy fluxes at the surface. Snow cover feedbacks
due to the influence of other external forcing are also important for
corrupting the long-term SAT–GST coupling. Our findings suggest that such
local and regional SAT–GST decoupling processes may represent a source of
bias for SAT reconstructions from borehole measurement, since the thermal
signature imprinted in the subsurface over the affected regions is not fully
representative of the long-term SAT variations.
Land surface–atmosphere interaction is one of the most important characteristic for understanding the terrestrial climate system, as it determines the exchange fluxes of energy and water between the land and the overlying air mass.
In several current climate models, it is common practice to use an unphysical approach to close the surface energy balance within the uppermost soil layer with finite thickness and heat capacity. In this study, a different approach is investigated by means of a physically based estimation of the canopy heat storage (SkIn⁺).
Therefore, as a first step, results of an offline simulation of the land component JSBACH of the Max Planck Institute Earth system model (MPI-ESM) – constrained with atmospheric observations – are compared to energy fluxes and water fluxes derived from eddy covariance measurements observed at the CASES-99 field experiment in Kansas, where shallow vegetation prevails. This comparison of energy and evapotranspiration fluxes with observations at the site-level provides an assessment of the model's capacity to correctly reproduce the diurnal cycle. Following this, a global coupled land–atmosphere experiment is performed using an AMIP (Atmospheric Model Intercomparison Project) type simulation over 30 years to evaluate the regional impact of the SkIn⁺ scheme on a longer timescale, in particular, with respect to the effect of the canopy heat storage.
The results of the offline experiment show that SkIn⁺ leads to a warming during the day and to a cooling at night relative to the old reference scheme, thereby improving the performance in the representation of the modeled surface fluxes on diurnal timescales. In particular: nocturnal heat releases unrealistically destroying the stable boundary layer disappear and phase errors are removed. On the global scale, for regions with no or low vegetation and a pronounced diurnal cycle, the nocturnal cooling prevails due to the fact that stable conditions at night maintain the delayed response in temperature, whereas the daytime turbulent exchange amplifies it. For the tropics and boreal forests as well as high latitudes, the scheme tends to warm the system.
Arctic and subarctic regions are amongst the most
susceptible regions on Earth to global warming and climate change.
Understanding and predicting the impact of climate change in these regions
require a proper process representation of the interactions between climate,
carbon cycle, and hydrology in Earth system models. This study focuses on
land surface models (LSMs) that represent the lower boundary condition of
general circulation models (GCMs) and regional climate models (RCMs), which
simulate climate change evolution at the global and regional scales,
respectively. LSMs typically utilize a standard soil configuration with a
depth of no more than 4 m, whereas for cold, permafrost regions, field
experiments show that attention to deep soil profiles is needed to
understand and close the water and energy balances, which are tightly
coupled through the phase change. To address this gap, we design and run a
series of model experiments with a one-dimensional LSM, called CLASS
(Canadian Land Surface Scheme), as embedded in the MESH (Modélisation
Environmentale Communautaire – Surface and Hydrology) modelling system, to
(1) characterize the effect of soil profile depth under different climate
conditions and in the presence of parameter uncertainty; (2) assess the
effect of including or excluding the geothermal flux in the LSM at the
bottom of the soil column; and (3) develop a methodology for temperature
profile initialization in permafrost regions, where the system has an
extended memory, by the use of paleo-records and bootstrapping. Our study
area is in Norman Wells, Northwest Territories of Canada, where measurements
of soil temperature profiles and historical reconstructed climate data are
available. Our results demonstrate a dominant role for parameter
uncertainty, that is often neglected in LSMs. Considering such high
sensitivity to parameter values and dependency on the climate condition, we
show that a minimum depth of 20 m is essential to adequately represent
the temperature dynamics. We further show that our proposed initialization
procedure is effective and robust to uncertainty in paleo-climate
reconstructions and that more than 300 years of reconstructed climate time
series are needed for proper model initialization.
Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were diagnosed large discrepancies in their land carbon turnover times, which partly explains the differences in the future projections of terrestrial carbon storage from the models. Carvalhais et al. (2014) focused on evaluation of model-based ecosystem carbon turnover times (τ_eco) in relation with climate factors. In this study, τ_eco from models was analyzed separately for biomass and soil carbon pools, and its spatial dependency upon temperature and precipitation was evaluated using observational datasets. The results showed that, eight of fourteen models slightly underestimated global biomass carbon turnover times (τ_veg, modeled median of 8 yr versus observed 11 yr), and eleven models grossly underestimated the soil carbon turnover time (τ_soil, modeled median of 16 yr versus observed 26 yr). The underestimation of global carbon turnover times in ESMs was mainly due to too low values of τ_veg and τ_soil in the high northern latitudes and arid and semi-arid regions. In addition, the models did not capture the observed spatial climate sensitivity of carbon turnover time in these regions. Modeled τ_veg and τ_soil values were generally weakly correlated with climate variables, implying that differences between carbon cycle models primarily originated from structural differences rather than from differences in atmospheric climate models (i.e., related to the temperature and precipitation). This study indicates that most models don’t reproduce the underlying processes driving regional τ_veg and τ_soil, highlighting the need for improving the model parameterization and adding key process such as biotic disturbance and permafrost-carbon climate responses.
An adapted Earth system model is used to investigate the limitations that future climate and water availability impose on the potential expansion and productivity of croplands. The model maximizes the cropland area under prevailing climate conditions and accounts for an optimized, sustainable irrigation practice, thus allowing us to consider the two-way feedback
between climate and agriculture. For three greenhouse gas concentration scenarios (RCP2.6, RCP4.5, RCP8.5), we show that the total cropland area could be extended substantially throughout the 21st century, especially in South America and sub-Saharan Africa, where the rising water demand resulting from increasing temperatures can largely be met by increasing precipitation and irrigation rates. When accounting for the CO2 fertilization effect, only a few agricultural areas have to be abandoned owing to declines in productivity, while increasing temperatures allow for the expansion of croplands even into high northern latitudes. Without the CO2 fertilization effect there is no increase in the overall cropland fraction during the second half of the century but areal losses in increasingly water-stressed regions can be compensated for by an expansion in regions that were previously too cold. However, global yields are more sensitive and, without the benefits of CO2 fertilization, they may decrease when greenhouse gas concentrations exceed the RCP4.5 scenario. For certain regions the situation is even more concerning and guaranteeing food security in dry areas in
Northern Africa, the Middle East and South Asia will become increasingly difficult, even for the idealized scenarios investigated in this study.
Land surface models used in climate models neglect the roughness sublayer and
parameterize within-canopy turbulence in an ad hoc manner. We implemented a
roughness sublayer turbulence parameterization in a multilayer canopy model
(CLM-ml v0) to test if this theory provides a tractable parameterization
extending from the ground through the canopy and the roughness sublayer. We
compared the canopy model with the Community Land Model (CLM4.5) at seven forest,
two grassland, and three cropland AmeriFlux sites over a range of canopy heights,
leaf area indexes, and climates. CLM4.5 has pronounced biases during summer
months at forest sites in midday latent heat flux, sensible heat flux,
gross primary production, nighttime friction velocity, and the radiative
temperature diurnal range. The new canopy model reduces these biases by
introducing new physics. Advances in modeling stomatal conductance and canopy
physiology beyond what is in CLM4.5 substantially improve model
performance at the forest sites. The signature of the roughness sublayer is
most evident in nighttime friction velocity and the diurnal cycle of
radiative temperature, but is also seen in sensible heat flux. Within-canopy
temperature profiles are markedly different compared with profiles obtained
using Monin–Obukhov similarity theory, and the roughness sublayer produces
cooler daytime and warmer nighttime temperatures. The herbaceous sites also
show model improvements, but the improvements are related less systematically
to the roughness sublayer parameterization in these canopies. The multilayer
canopy with the roughness sublayer turbulence improves simulations compared
with CLM4.5 while also advancing the theoretical basis for surface flux
parameterizations.
Significance
We applied regional and global-scale biogeochemical models that coupled thaw depth with soil carbon exposure to evaluate the dependence of the evolution of future carbon storage in the northern permafrost region on the trajectory of climate change. Our analysis indicates that the northern permafrost region could act as a net sink for carbon under more aggressive climate change mitigation pathways. Under less aggressive pathways, the region would likely act as a source of soil carbon to the atmosphere, but substantial net losses would not occur until after 2100. These results suggest that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback.
The pre-industrial millennium is among the periods selected by the
Paleoclimate Model Intercomparison Project (PMIP) for experiments
contributing to the sixth phase of the Coupled Model Intercomparison Project
(CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000
transient simulations serve to investigate the response to (mainly) natural
forcing under background conditions not too different from today, and to
discriminate between forced and internally generated variability on
interannual to centennial timescales. This paper describes the motivation and
the experimental set-ups for the PMIP4-CMIP6 past1000 simulations,
and discusses the forcing agents orbital, solar, volcanic, and land use/land
cover changes, and variations in greenhouse gas concentrations. The
past1000 simulations covering the pre-industrial millennium from 850
Common Era (CE) to 1849 CE
have to be complemented by historical simulations (1850 to 2014 CE)
following the CMIP6 protocol. The external forcings for the past1000
experiments have been adapted to provide a seamless transition across these
time periods. Protocols for the past1000 simulations have been
divided into three tiers. A default forcing data set has been defined for the
Tier 1 (the CMIP6
past1000) experiment. However, the PMIP community has maintained the
flexibility to conduct coordinated sensitivity experiments to explore
uncertainty in forcing reconstructions as well as parameter uncertainty in
dedicated Tier 2 simulations. Additional experiments (Tier 3) are defined to
foster collaborative model experiments focusing on the early instrumental
period and to extend the temporal range and the scope of the simulations.
This paper outlines current and future research foci and common analyses for
collaborative work between the PMIP and the observational communities
(reconstructions, instrumental data).
OASIS is coupling software developed primarily for use in the climate community. It provides the ability to couple different models with low implementation and performance overhead. OASIS3-MCT is the latest version of OASIS. It includes several improvements compared to OASIS3, including elimination of a separate hub coupler process, parallelization of the coupling communication and run-time grid interpolation, and the ability to easily reuse mapping weight files. OASIS3-MCT_3.0 is the latest release and includes the ability to couple between components running sequentially on the same set of tasks as well as to couple within a single component between different grids or decompositions such as physics, dynamics, and I/O. OASIS3-MCT has been tested with different configurations on up to 32 000 processes, with components running on high-resolution grids with up to 1.5 million grid cells, and with over 10 000 2-D coupling fields. Several new features will be available in OASIS3-MCT_4.0, and some of those are also described.
Significance
Agricultural production is vulnerable to climate change. Understanding climate change, especially the temperature impacts, is critical if policymakers, agriculturalists, and crop breeders are to ensure global food security. Our study, by compiling extensive published results from four analytical methods, shows that independent methods consistently estimated negative temperature impacts on yields of four major crops at the global scale, generally underpinned by similar impacts at country and site scales. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops, with important implications for developing crop- and region-specific adaptation strategies to ensure future food supply of an increasing world population.
Studies addressing climate variability during the last millennium generally focus on variables with a direct influence on climate variability, like the fast thermal response to varying radiative forcing, or the large-scale changes in atmospheric dynamics (e.g. North Atlantic Oscillation). The ocean responds to these variations by slowly integrating in depth the upper heat flux changes, thus producing a delayed influence on ocean heat content (OHC) that can later impact low frequency SST (sea surface temperature) variability through reemergence processes. In this study, both the externally and internally driven variations of the OHC during the last millennium are investigated using a set of fully coupled simulations with the ECHO-G (coupled climate model ECHAMA4 and ocean model HOPE-G) atmosphere–ocean general circulation model (AOGCM). When compared to observations for the last 55 yr, the model tends to overestimate the global trends and underestimate the decadal OHC variability. Extending the analysis back to the last one thousand years, the main impact of the radiative forcing is an OHC increase at high latitudes, explained to some extent by a reduction in cloud cover and the subsequent increase of short-wave radiation at the surface. This OHC response is dominated by the effect of volcanism in the preindustrial era, and by the fast increase of GHGs during the last 150 yr. Likewise, salient impacts from internal climate variability are observed at regional scales. For instance, upper temperature in the equatorial Pacific is controlled by ENSO (El Niño Southern Oscillation) variability from interannual to multidecadal timescales. Also, both the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) modulate intermittently the interdecadal OHC variability in the North Pacific and Mid Atlantic, respectively. The NAO, through its influence on North Atlantic surface heat fluxes and convection, also plays an important role on the OHC at multiple timescales, leading first to a cooling in the Labrador and Irminger seas, and later on to a North Atlantic warming, associated with a delayed impact on the AMO.
Permafrost or perennially frozen ground is an important part of the
terrestrial cryosphere; roughly one quarter of Earth's land surface is
underlain by permafrost. The currently observed global warming is most
pronounced in the Arctic region and is projected to persist during the coming
decades due to anthropogenic CO2 input. This warming will certainly have
effects on the ecosystems of the vast permafrost areas of the high northern
latitudes. The quantification of such effects, however, is still an open
question. This is partly due to the complexity of the system, including
several feedback mechanisms between land and atmosphere. In this study we
contribute to increasing our understanding of such land–atmosphere
interactions using an Earth system model (ESM) which includes a
representation of cold-region physical soil processes, especially the effects
of freezing and thawing of soil water on thermal and hydrological states and
processes. The coupled atmosphere–land models of the ESM of the Max Planck
Institute for Meteorology, MPI-ESM, have been driven by prescribed observed
SST and sea ice in an AMIP2-type setup with and without newly implemented
cold-region soil processes. Results show a large improvement in the simulated
discharge. On the one hand this is related to an improved snowmelt peak of runoff
due to frozen soil in spring. On the other hand a subsequent reduction in soil moisture enables a positive feedback to precipitation over the high
latitudes, which reduces the model's wet biases in precipitation and
evapotranspiration during the summer. This is noteworthy as soil-moisture–atmosphere feedbacks have previously not been the focus of research on the
high latitudes. These results point out the importance of high-latitude
physical processes at the land surface for regional climate.
By coordinating the design and distribution of global
climate model simulations of the past, current, and future climate, the
Coupled Model Intercomparison Project (CMIP) has become one of the
foundational elements of climate science. However, the need to address an
ever-expanding range of scientific questions arising from more and more
research communities has made it necessary to revise the organization of
CMIP. After a long and wide community consultation, a new and more federated
structure has been put in place. It consists of three major elements: (1) a
handful of common experiments, the DECK (Diagnostic, Evaluation and
Characterization of Klima) and CMIP historical simulations (1850–near present) that will maintain continuity and help document basic
characteristics of models across different phases of CMIP; (2) common
standards, coordination, infrastructure, and documentation that will
facilitate the distribution of model outputs and the characterization of the
model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison
Projects (MIPs) that will be specific to a particular phase of CMIP (now
CMIP6) and that will build on the DECK and CMIP historical simulations to
address a large range of specific questions and fill the scientific gaps of
the previous CMIP phases. The DECK and CMIP historical simulations, together
with the use of CMIP data standards, will be the entry cards for models
participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual
modelling groups will be at their own discretion and will depend on their
scientific interests and priorities. With the Grand Science Challenges of
the World Climate Research Programme (WCRP) as its scientific backdrop,
CMIP6 will address three broad questions:
– How does the Earth system respond to forcing?
– What are the origins and consequences of
systematic model biases?
– How can we assess future climate changes
given internal climate variability, predictability, and uncertainties in
scenarios?
This CMIP6 overview paper presents the background and rationale
for the new structure of CMIP, provides a detailed description of the DECK
and CMIP6 historical simulations, and includes a brief introduction to the
21 CMIP6-Endorsed MIPs.
Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) is one of the most damaging insect pests in the world. However, little is known about the effects of snow cover and soil temperature on the overwintering pupae of H. armigera. A field experiment was conducted from November 2, 2012 to April 24, 2013 at the agrometeorological experimental station in Wulanwusu, China. Overwintering pupae were embedded into the soil at depths of 5, 10 and 15 cm in the following four treatments: without snow cover, snow cover, and increased temperatures from 600 and 1200 W infrared lights. The results showed that snow cover and rising temperatures could all markedly increase soil temperatures, which was helpful in improving the survival of the overwintering pupae of H. armigera. The mortality of overwintering pupae (MOP) at a depth of 15 cm was the highest, and the MOP at a depth of 5 cm followed. The lower accumulated temperature (≤0°C) (AT ≤°C) led to the higher MOP, and the lower diurnal soil temperature range (DSTR) likely led to the lower MOP. After snowmelt, the MOPs at the depths of 5 and 10 cm increased as the soil temperature increased, especially in April. The AT of the soil (≤0°C) was the factor with the strongest effect on MOP. The soil moisture content was not a major factor affecting the MOP in this semi-arid region because precipitation was 45 mm over the entire experimental period. With climate warming, the MOP will likely decrease, and the overwintering boundary air temperatures of H. armigera should be expanded due to higher soil temperatures and increased snow cover.
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 affect 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. We found an uncertainty in the decadal LULCC fluxes of the recent past due to the parametrization of decomposition and direct emissions of 0.6 Pg C yr−1, which is three times larger than the un-certainty previously attributed to model and method in general. Pre-industrial natural land cover had a larger effect on decadal LULCC fluxes than the aforementioned parameter sensitivity (1.0 Pg C yr−1). Re-gional differences between reconstructed and dynamically-computed land cover, 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.
The climate of the past millennium provides a baseline for understanding the background of natural climate variability upon which current anthropogenic changes are superimposed. As this period also contains high data density from proxy sources (e.g., ice cores, stalagmites, corals, tree rings, and sediments), it provides a unique opportunity for understanding both global and regional-scale climate responses to natural forcing. Toward that end, an ensemble of simulations with the Community Earth System Model (CESM) for the period 850–2005 (the CESM Last Millennium Ensemble, or CESM-LME) is now available to the community. This ensemble includes simulations forced with the transient evolution of solar intensity, volcanic emissions, greenhouse gases, aerosols, land-use conditions, and orbital parameters, both together and individually. The CESM-LME thus allows for evaluation of the relative contributions of external forcing and internal variability to changes evident in the paleoclimate data record, a...
The Technical Notes series provides an outlet for a variety of NCAR Manuscripts that contribute in specialized ways to the body of scientific knowledge but that are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR scientific divisions. Designation symbols for the series include: EDD – Engineering, Design, or Development Reports Equipment descriptions, test results, instrumentation, and operating and maintenance manuals. IA – Instructional Aids Instruction manuals, bibliographies, film supplements, and other research or instructional aids. PPR – Program Progress Reports Field program reports, interim and working reports, survey reports, and plans for experiments. PROC – Proceedings Documentation or symposia, colloquia, conferences
[1] MPI-ESM is a new version of the global Earth system model developed at the Max Planck Institute for Meteorology. This paper describes the ocean state and circulation as well as basic aspects of variability in simulations contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The performance of the ocean/sea-ice model MPIOM, coupled to a new version of the atmosphere model ECHAM6 and modules for land surface and ocean biogeochemistry, is assessed for two model versions with different grid resolution in the ocean. The low-resolution configuration has a nominal resolution of 1.5°, whereas the higher resolution version features a quasiuniform, eddy-permitting global resolution of 0.4°. The paper focuses on important oceanic features, such as surface temperature and salinity, water mass distribution, large-scale circulation, and heat and freshwater transports. In general, these integral quantities are simulated well in comparison with observational estimates, and improvements in comparison with the predecessor system are documented; for example, for tropical variability and sea ice representation. Introducing an eddy-permitting grid configuration in the ocean leads to improvements, in particular, in the representation of interior water mass properties in the Atlantic and in the representation of important ocean currents, such as the Agulhas and Equatorial current systems. In general, however, there are more similarities than differences between the two grid configurations, and several shortcomings, known from earlier versions of the coupled model, prevail.
The current version of JSBACH incorporates phenomena specific to high
latitudes: freeze/thaw processes, coupling thermal and hydrological
processes in a layered soil scheme, defining a multilayer snow
representation and an insulating moss cover. Evaluations using comprehensive
Arctic data sets show comparable results at the site, basin, continental and
circumarctic scales. Such comparisons highlight the need to include
processes relevant to high-latitude systems in order to capture the
dynamics, and therefore realistically predict the evolution of this
climatically critical biome.
1] Shallow bottom boundary conditions (BBCs) in the soil components of general circulation models (GCMs) impose artificial limits on subsurface heat storage. To assess this problem we estimate the subsurface heat content from two future climate simulations and compare to that obtained from an offline soil model (FDLSM) driven by GCM skin temperatures. FDLSM is then used as an offline substitute for the subsurface of the GCM ECHO-G. With a 600-m BBC and driven by ECHO-G future temperatures, the FDLSM subsurface absorbs 6.2 (7.5) times more heat than the ECHO-G soil model (10 m deep) under the Intergovernmental Panel on Climate Change (IPCC) A2 (B2) emission scenario. This suggests that shallow BBCs in GCM simulations may underestimate the heat stored in the subsurface, particularly for northern high latitudes. This effect could be relevant in assessing the energy balance and climate change in the next century. Citation: MacDougall,
Key Points
Two metrics are proposed to evaluate vegetation cover simulated by ESMs
On a global scale, tree cover is satisfactory simulated by MPI‐ESM
Land‐surface albedois evaluated using the net surface radiation
Integrating the biosphere into climate models
High-quality climate predictions are crucial for understanding the impacts of different greenhouse gas emission scenarios and for mitigating and adapting to the resulting climatic changes. Bonan and Doney review advances in Earth system models that include the terrestrial and marine biosphere. Such models capture interactions between physical and biological aspects of the Earth system. This provides insight into climate impacts of societal importance, such as altered crop yields, wildfire risk, and water availability. Further research is needed to better understand model uncertainties, some of which may be unavoidable, and to better translate observations into abstract model representations.
Science , this issue p. eaam8328
Development and planning for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) has been years in the making. Nature Climate Change speaks to the Chair of the CMIP Panel, Veronika Eyring, about the aims and projected outcomes of the project.
Equilibrium climate sensitivity characterizes the Earth's long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the 'likely' range for climate sensitivity of 1.5 °C to 4.5 °C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 °C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.
Although much of the energy gained by the climate system over the last century has been stored in the oceans, continental energy storage remains important to estimate the Earth's energy imbalance and also because crucial positive climate feedback processes such as soil carbon and permafrost stability depend on continental energy storage. Here for the first time, 32 general circulation model simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are examined to assess their ability to characterize the continental energy storage. Results display a consistently lower magnitude of continental energy storage in CMIP5 simulations than the estimates from geothermal data. A large range in heat storage is present across the model ensemble, which is largely explained by the substantial differences in the bottom boundary depths used in each land surface component.
As a consequence of recent increased awareness of the social and political dimensions of climate, many non-specialists discover a need for information about the variety of available climate models. A Climate Modelling Primer, Third Edition explains the basis and mechanisms of all types of current physically-based climate models. A thoroughly revised and updated edition, this book assists the reader in understanding the complexities and applicabilities of today's wide range of climate models. Topics covered include the latest techniques for modelling the coupled biosphere-ocean-atmosphere system, information on current practical aspects of climate modelling and ways to evaluate and exploit the results, discussion of Earth System Models of Intermediate Complexity (EMICs), and interactive exercises based on Energy Balance Model (EBM) and the Daisyworld model. Source codes and results from a range of model types allows readers to make their own climate simulations and to view the results of the latest high resolution models. The accompanying CD contains: A suite of resources for those wishing to learn more about climate modelling. A range of model visualisations. Data from climate models for use in the classroom. Windows and Macintosh programs for an Energy Balance Model. Selected figures from the book for inclusion in presentations and lectures.
[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.