scholarly journals The CCSM4 Land Simulation, 1850–2005: Assessment of Surface Climate and New Capabilities

2012 ◽  
Vol 25 (7) ◽  
pp. 2240-2260 ◽  
Author(s):  
David M. Lawrence ◽  
Keith W. Oleson ◽  
Mark G. Flanner ◽  
Christopher G. Fletcher ◽  
Peter J. Lawrence ◽  
...  
Keyword(s):  
Land Use ◽  
Air Temperature ◽  
Climate Simulation ◽  
Biogeochemical Model ◽  
Earth System ◽  
Climate System Model ◽  
Community Land Model ◽  
Model Version ◽  
Surface Climate ◽  
Global Land

Abstract This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon–nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels. Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia. New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°–2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as +0.083 W m−2 for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change.

scholarly journals Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

2013 ◽  
Vol 9 (3) ◽  
pp. 1111-1140 ◽  
Author(s):  
M. Eby ◽  
A. J. Weaver ◽  
K. Alexander ◽  
K. Zickfeld ◽  
A. Abe-Ouchi ◽  
...  
Keyword(s):  
Land Use ◽  
Carbon Cycle ◽  
Air Temperature ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Carbon Fluxes ◽  
Carbon Uptake ◽  
Earth System ◽  
Model Experiments ◽  
Earth System Models

Abstract. Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Estimates of the Earth surface influence on the accuracy of numerical prediction of air temperature in Belarus using the WRF model

2021 ◽  
Vol 4 ◽  
pp. 50-68
Author(s):  
S.А. Lysenko ◽  
◽  
P.О. Zaiko ◽  
Keyword(s):  
Land Use ◽  
Air Temperature ◽  
Numerical Weather Prediction ◽  
Land Surface ◽  
Lead Time ◽  
Weather Prediction ◽  
Wrf Model ◽  
Surface Model ◽  
Numerical Weather ◽  
Global Land

The spatial structure of land use and biophysical characteristics of land surface (albedo, leaf index, and vegetation cover) are updated using the GLASS (Global Land Surface Satellite) and GLC2019 (Global Land Cover, 2019) modern satellite databases for mesoscale numerical weather prediction with the WRF model for the territory of Belarus. The series of WRF-based numerical experiments was performed to verify the influence of the updated characteristics on the forecast quality for some difficult to predict winter cases. The model was initialized by the GFS (Global Forecast System, NCEP) global numerical weather prediction model. It is shown that the use of high-resolution land use data in the WRF and the consideration of the new albedo and leaf index distribution over the territory of Belarus can reduce the root-mean-square error (RMSE) of short-range (to 48 hours) forecasts of surface air temperature by 16–33% as compared to the GFS. The RMSE of the temperature forecast for the weather stations in Belarus for a forecast lead time of 12, 24, 36, and 48 hours decreased on average by 0.40°С (19%), 0.35°С (10%), 0.68°С (23%), and 0.56°С (15%), respectively. The most significant decrease in RMSE of the numerical forecast of temperature (up to 2.1 °С) was obtained for the daytime (for a lead time of 12 and 36 hours), when positive feedbacks between albedo and temperature of the land surface are manifested most. Keywords: numerical weather prediction, WRF, digital land surface model, albedo, leaf area index, forecast model validation

Reconciling global land model estimates and country reporting of anthropogenic land CO2 sources and sinks with the CMIP6 LUMIP NOAA/GFDL LM4.1 simulations

2020 ◽  
Author(s):  
Elena Shevliakova ◽  
Sergey Malyshev ◽  
Richard Houghton ◽  
Louis Verchot
Keyword(s):  
Land Use ◽  
Environmental Changes ◽  
Historical Period ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Earth System ◽  
Sources And Sinks ◽  
Global Land ◽  
Natural Response ◽  
Earth System Models

<p>Global land models, which often served as components Earth system models, and national GHG inventories rely on different methods and produce different estimates of anthropogenic CO<sub>2</sub> emissions and uptakes from land use land cover changes throughout historical period. For example, for 2005 -2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO2 yr<sup>–1</sup> while the bookkeeping models is 5.2 ± 2.6 GtCO2 yr<sup>–1</sup> (IPCC SPM 2019).  Previous estimates with the 16 global stand-alone land models produced an estimate of the net land sink of 11.2 ± 2.6 GtCO2 yr<sup>–1</sup> during 2007– 2016 for the natural response of land to human-induced environmental changes such as increasing atmospheric CO<sub>2</sub> concentration, nitrogen deposition, and climate change (IPCC SPM 2019).  However, these 16 models do not provide separate estimates for the managed and unmanaged lands. </p><p> </p><p>Here we use results from simulations with the NOAA/GFDL new land model LM4.1 from the CMIP6 Land Use Model Inercomparison Project (LUMIP) to demonstrate how to reconcile the discrepancy between the inventories and land models estimates of the anthropogenic CO<sub>2 </sub>land emissions by using bookkeeping accounting approach applied to the model results.  In addition, we separate estimates of land fluxes on managed and unmanaged lands. Key features of this model include advanced, second generation dynamic vegetation representation and canopy competition, fire, and land use representation driven by full set of gross transitions from the CMIP6 land use scenarios.  We demonstrate how bookkeeping accounting combined with the LUMIP experiments can enhance understanding of land sector net emission estimates and their applications.</p>

scholarly journals On linking an Earth system model to the equilibrium carbon representation of an economically optimizing land use model

2014 ◽  
Vol 7 (6) ◽  
pp. 2545-2555 ◽  
Author(s):  
B. Bond-Lamberty ◽  
K. Calvin ◽  
A. D. Jones ◽  
J. Mao ◽  
P. Patel ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Carbon Cycle ◽  
Integrated Assessment ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Earth System ◽  
Climate Effects ◽  
Community Land Model ◽  
Proxy Variables

Abstract. Human activities are significantly altering biogeochemical cycles at the global scale, and the scope of these activities will change with both future climate and socioeconomic decisions. This poses a significant challenge for Earth system models (ESMs), which can incorporate land use change as prescribed inputs but do not actively simulate the policy or economic forces that drive land use change. One option to address this problem is to couple an ESM with an economically oriented integrated assessment model, but this is challenging because of the radically different goals and underpinnings of each type of model. This study describes the development and testing of a coupling between the terrestrial carbon cycle of an ESM (CESM) and an integrated assessment (GCAM) model, focusing on how CESM climate effects on the carbon cycle could be shared with GCAM. We examine the best proxy variables to share between the models, and we quantify how carbon flux changes driven by climate, CO2 fertilization, and land use changes (e.g., deforestation) can be distinguished from each other by GCAM. The net primary production and heterotrophic respiration outputs of the Community Land Model (CLM), the land component of CESM, were found to be the most robust proxy variables by which to recalculate GCAM's assumptions of equilibrium ecosystem steady-state carbon. Carbon cycle effects of land use change are spatially limited relative to climate effects, and thus we were able to distinguish these effects successfully in the model coupling, passing only the latter to GCAM. This paper does not present results of a fully coupled simulation but shows, using a series of offline CLM simulations and an additional idealized Monte Carlo simulation, that our CESM–GCAM proxy variables reflect the phenomena that we intend and do not contain erroneous signals due to land use change. By allowing climate effects from a full ESM to dynamically modulate the economic and policy decisions of an integrated assessment model, this work will help link these models in a robust and flexible framework capable of examining two-way interactions between human and Earth system processes.

scholarly journals The COSMO-CLM 4.8 regional climate model coupled to regional ocean, land surface and global earth system models using OASIS3-MCT: description and performance

2017 ◽  
Vol 10 (4) ◽  
pp. 1549-1586 ◽  
Author(s):  
Andreas Will ◽  
Naveed Akhtar ◽  
Jennifer Brauch ◽  
Marcus Breil ◽  
Edouard Davin ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Direct Cost ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Ocean Model ◽  
Earth System ◽  
Climate System Model ◽  
Community Land Model ◽  
Computational Performance

Abstract. We developed a coupled regional climate system model based on the CCLM regional climate model. Within this model system, using OASIS3-MCT as a coupler, CCLM can be coupled to two land surface models (the Community Land Model (CLM) and VEG3D), the NEMO-MED12 regional ocean model for the Mediterranean Sea, two ocean models for the North and Baltic seas (NEMO-NORDIC and TRIMNP+CICE) and the MPI-ESM Earth system model.We first present the different model components and the unified OASIS3-MCT interface which handles all couplings in a consistent way, minimising the model source code modifications and defining the physical and numerical aspects of the couplings. We also address specific coupling issues like the handling of different domains, multiple usage of the MCT library and exchange of 3-D fields.We analyse and compare the computational performance of the different couplings based on real-case simulations over Europe. The usage of the LUCIA tool implemented in OASIS3-MCT enables the quantification of the contributions of the coupled components to the overall coupling cost. These individual contributions are (1) cost of the model(s) coupled, (2) direct cost of coupling including horizontal interpolation and communication between the components, (3) load imbalance, (4) cost of different usage of processors by CCLM in coupled and stand-alone mode and (5) residual cost including i.a. CCLM additional computations.Finally a procedure for finding an optimum processor configuration for each of the couplings was developed considering the time to solution, computing cost and parallel efficiency of the simulation. The optimum configurations are presented for sequential, concurrent and mixed (sequential+concurrent) coupling layouts. The procedure applied can be regarded as independent of the specific coupling layout and coupling details.We found that the direct cost of coupling, i.e. communications and horizontal interpolation, in OASIS3-MCT remains below 7 % of the CCLM stand-alone cost for all couplings investigated. This is in particular true for the exchange of 450 2-D fields between CCLM and MPI-ESM. We identified remaining limitations in the coupling strategies and discuss possible future improvements of the computational efficiency.

scholarly journals Evaluation of CMIP5 Global Climate Models over the Volta Basin: Precipitation

2018 ◽  
Vol 2018 ◽  
pp. 1-24 ◽  
Author(s):  
Jacob Agyekum ◽  
Thompson Annor ◽  
Benjamin Lamptey ◽  
Emmannuel Quansah ◽  
Richard Yao Kuma Agyeman
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Earth System Model ◽  
Global Climate Models ◽  
System Model ◽  
Earth System ◽  
Climate System Model ◽  
Model Version ◽  
Volta Basin ◽  
Ensemble Mean

A selected number of global climate models (GCMs) from the fifth Coupled Model Intercomparison Project (CMIP5) were evaluated over the Volta Basin for precipitation. Biases in models were computed by taking the differences between the averages over the period (1950–2004) of the models and the observation, normalized by the average of the observed for the annual and seasonal timescales. The Community Earth System Model, version 1-Biogeochemistry (CESM1-BGC), the Community Climate System Model Version 4 (CCSM4), the Max Planck Institute Earth System Model, Medium Range (MPI-ESM-MR), the Norwegian Earth System Model (NorESM1-M), and the multimodel ensemble mean were able to simulate the observed climatological mean of the annual total precipitation well (average biases of 1.9% to 7.5%) and hence were selected for the seasonal and monthly timescales. Overall, all the models (CESM1-BGC, CCSM4, MPI-ESM-MR, and NorESM1-M) scored relatively low for correlation (<0.5) but simulated the observed temporal variability differently ranging from 1.0 to 3.0 for the seasonal total. For the annual cycle of the monthly total, the CESM1-BGC, the MPI-ESM-MR, and the NorESM1-M were able to simulate the peak of the observed rainy season well in the Soudano-Sahel, the Sahel, and the entire basin, respectively, while all the models had difficulty in simulating the bimodal pattern of the Guinea Coast. The ensemble mean shows high performance compared to the individual models in various timescales.

scholarly journals Transient simulations of the present and the last interglacial climate using the Community Climate System Model version 3: effects of orbital acceleration

2016 ◽  
Vol 9 (11) ◽  
pp. 3859-3873 ◽  
Author(s):  
Vidya Varma ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Climate System ◽  
System Model ◽  
Scale Model ◽  
Last Interglacial ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Model Version ◽  
Surface Climate ◽  
Transient Simulations ◽  
Community Climate

Abstract. Numerical simulations provide a considerable aid in studying past climates. Out of the various approaches taken in designing numerical climate experiments, transient simulations have been found to be the most optimal when it comes to comparison with proxy data. However, multi-millennial or longer simulations using fully coupled general circulation models are computationally very expensive such that acceleration techniques are frequently applied. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model version 3). Our study shows that in low-latitude regions, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor of 10) and hence, large-scale model–data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere.

Simulation of Present-Day and Future Permafrost and Seasonally Frozen Ground Conditions in CCSM4

2012 ◽  
Vol 25 (7) ◽  
pp. 2207-2225 ◽  
Author(s):  
David M. Lawrence ◽  
Andrew G. Slater ◽  
Sean C. Swenson
Keyword(s):  
First Century ◽  
Arctic Climate ◽  
Active Layer Thickness ◽  
Permafrost Degradation ◽  
Frozen Ground ◽  
Climate System Model ◽  
Near Surface ◽  
Community Land Model ◽  
Model Version ◽  
Twenty First Century

Abstract The representation of permafrost and seasonally frozen ground and their projected twenty-first century trends is assessed in the Community Climate System Model, version 4 (CCSM4) and the Community Land Model version 4 (CLM4). The combined impact of advances in CLM and a better Arctic climate simulation, especially for air temperature, improve the permafrost simulation in CCSM4 compared to CCSM3. Present-day continuous plus discontinuous permafrost extent is comparable to that observed [12.5 × 106 versus (11.8–14.6) × 106 km2], but active-layer thickness (ALT) is generally too thick and deep ground (&gt;15 m) temperatures are too warm in CCSM4. Present-day seasonally frozen ground area is well simulated (47.5 × 106 versus 48.1 × 106 km2). ALT and deep ground temperatures are much better simulated in offline CLM4 (i.e., forced with observed climate), which indicates that the remaining climate biases, particularly excessive high-latitude snowfall biases, degrade the CCSM4 permafrost simulation. Near-surface permafrost (NSP) and seasonally frozen ground (SFG) area are projected to decline substantially during the twenty-first century [representative concentration projections (RCPs); RCP8.5: NSP by 9.0 × 106 km2, 72%, SFG by 7.1 × 106, 15%; RCP2.6: NSP by 4.1 × 106, 33%, SFG by 2.1 × 106, 4%]. The permafrost degradation rate is slower (2000–50) than in CCSM3 by ~35% because of the improved soil physics. Under the low RCP2.6 emissions pathway, permafrost state stabilizes by 2100, suggesting that permafrost related feedbacks could be minimized if greenhouse emissions could be reduced. The trajectory of permafrost degradation is affected by CCSM4 climate biases. In simulations with this climate bias ameliorated, permafrost degradation in RCP8.5 is lower by ~29%. Further reductions of Arctic climate biases will increase the reliability of permafrost projections and feedback studies in earth system models.

scholarly journals The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0

2021 ◽  
Vol 13 (21) ◽  
pp. 4460
Author(s):  
Dayang Wang ◽  
Dagang Wang ◽  
Chongxun Mo
Keyword(s):  
Remote Sensing ◽  
Water Supply ◽  
Bias Correction ◽  
Land Surface ◽  
Land Surface Models ◽  
Community Land Model ◽  
Model Version ◽  
Correction Effect ◽  
Surface Models ◽  
Global Land

Terrestrial evapotranspiration (ET) is a critical component of water and energy cycles, and improving global land evapotranspiration is one of the challenging works in the development of land surface models (LSMs). In this study, we apply a bias correction approach into the Community Land Model version 5.0 (CLM5) globally by utilizing the remote sensing-based ET dataset. Results reveal that the correction approach can alleviate both overestimation and underestimation of ET by CLM5 over the globe. The adjustment to overestimation is generally effective, whereas the effectiveness for underestimation is determined by the ET regime, namely water-limited or energy-limited. In the areas with abundant precipitation, the underestimation is effectively corrected by increasing ET without the water supply limit. In areas with rare precipitation, however, increasing ET is limited by water supply, which leads to an undesirable correction effect. Compared with the ET simulated by CLM5, the bias correction approach can reduce the global-averaged relative bias (RB) and the root mean square error (RMSE) by 51.8% and 65.9% against Global Land Evaporation Amsterdam Model (GLEAM) ET data, respectively. Meanwhile, the correlation coefficient (CC) can also be improved from 0.93 to 0.98. Continentally, the most substantial ET improvement occurs in Asia, with the RB and RMSE decreased by 69.7% (from 7.04% to 2.14%) and 70.2% (from 0.312 mm day−1 to 0.093 mm day−1, equivalent to from 114 mm year−1 to 34 mm year−1), and the CC increased from 0.92 to 0.99, respectively. Consequently, benefiting from the improvement of ET, the simulations of runoff and soil moisture are also improved over the globe and each of the six continents, and the improvement varies with region. This study demonstrates that the use of satellite-based ET products is beneficial to hydrological simulations in land surface models over the globe.

scholarly journals Modeling the interinfluence of fertilizer-induced NH<sub>3</sub> emission, nitrogen deposition, and aerosol radiative effects using modified CESM2

2021 ◽  
Author(s):  
Ka Ming Fung ◽  
Maria Val Martin ◽  
Amos P. K. Tai
Keyword(s):  
Nitrogen Deposition ◽  
Atmospheric Chemistry ◽  
Earth System Model ◽  
System Model ◽  
Atmospheric Composition ◽  
Earth System ◽  
Community Land Model ◽  
Model Version ◽  
Nh3 Emission ◽  
Aerosol Radiative

Abstract. Global ammonia (NH3) emission is expected to continue to rise due to intensified fertilization for growing food to satisfy the increasing demand worldwide. Previous studies focused mainly on estimating the land-to-atmosphere NH3 injection but seldom addressed the other side of the bidirectional nitrogen exchange – deposition. Ignoring this significant input source of soil mineral nitrogen may lead to an underestimation of NH3 emissions from natural sources. Here, we used an Earth system model to quantify NH3-induced changes in atmospheric composition and the consequent impacts on the Earth's radiative budget and biosphere, as well as the impacts of deposition on NH3 emissions from the land surface. We implemented a new scheme into the Community Land Model version 5 (CLM5) of the Community Earth System Model version 2 (CESM2) to estimate the volatilization of ammonium salt (NH4+) associated with synthetical fertilizers into gaseous NH3. We further parameterized the amount of emitted NH3 captured in the plant canopy to derive a more accurate quantity of NH3 that escapes to the atmosphere. Our modified CLM5 estimated that 11 Tg-N yr−1 of global NH3 emission is attributable to synthetic fertilizers. Interactively coupling terrestrial NH3 emissions to atmospheric chemistry simulations by the Community Atmospheric Model version 4 with chemistry (CAM4-chem), we found that such emissions favor the formation and deposition of NH4+ aerosol, which in turn disrupts the aerosol radiative effect and enhances soil NH3 volatilization in regions downwind of fertilized croplands. Our fully-coupled simulations showed that global-total NH3 emission is enhanced by nitrogen deposition by 2.4 Tg-N yr−1, when compared to the baseline case with 2000-level fertilization but without deposition- induced enhancements. In synergy with observations and emission inventories, our work provides a useful tool for stakeholders to evaluate the intertwined relations between agricultural trends, fertilize use, NH3 emission, atmospheric aerosols, and climate, so as to derive optimal strategies for securing both food production and environmental sustainability.

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