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.

Evaluation of Organized Convection Parameterization in Global Climate Models

2020 ◽  
Author(s):  
Chih-Chieh Chen ◽  
Changhai Liu ◽  
Mitch Moncrieff ◽  
Yaga Richter
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Earth System Model ◽  
Global Climate Models ◽  
System Model ◽  
Moist Convection ◽  
Earth System ◽  
Mesoscale Convective ◽  
Convective Organization ◽  
Organized Convection

&lt;p&gt;The importance of convective organization on the global circulation has been recognized for a long time, but parameterizations of the associated processes are missing in global climate models. Contemporary convective parameterizations commonly use a convective plume model (or a spectrum of plumes). This is perhaps appropriate for unorganized convection but the assumption of a gap between the small cumulus scale and the large-scale motion fails to recognize mesoscale dynamics manifested in mesoscale convective systems (MCSs) and multi-scale cloud systems associated with the MJO. Organized convection is abundant in environments featuring vertical wind shear, and significantly modulates the life cycle of moist convection, the transport of heat and momentum, and accounts for a large percentage of precipitation in the tropics. Mesoscale convective organization is typically associated with counter-gradient momentum transport, and distinct heating profiles between the convective and stratiform regions.&lt;/p&gt;&lt;p&gt;Moncrieff, Liu and Bogenschutz (2017) recently developed a dynamical based parameterization of organized moisture convection, referred to as multiscale coherent structure parameterization (MCSP), for global climate models. A prototype version of MCSP has been implemented in the NCAR Community Earth System Model (CESM) and the Energy Exascale Earth System Model (E3SM), positively affecting the distribution of tropical precipitation, convectively coupled tropical waves, and the Madden-Julian oscillation. We will show the further development of the MCSP and its impact on the simulation of mean precipitation and variability in the two global climate models.&lt;/p&gt;

scholarly journals Improving the representation of anthropogenic CO<sub>2</sub> emissions in climate models: impact of a new parameterization for the Community Earth System Model (CESM)

2018 ◽  
Vol 9 (3) ◽  
pp. 1045-1062 ◽  
Author(s):  
Andrés Navarro ◽  
Raúl Moreno ◽  
Francisco J. Tapiador
Keyword(s):  
Human Activities ◽  
Climate Models ◽  
Global Climate ◽  
Grid Point ◽  
Earth System Model ◽  
Population Projections ◽  
Pollutant Emissions ◽  
System Model ◽  
Earth System ◽  
Community Earth System Model

Abstract. ESMs (Earth system models) are important tools that help scientists understand the complexities of the Earth's climate. Advances in computing power have permitted the development of increasingly complex ESMs and the introduction of better, more accurate parameterizations of processes that are too complex to be described in detail. One of the least well-controlled parameterizations involves human activities and their direct impact at local and regional scales. In order to improve the direct representation of human activities and climate, we have developed a simple, scalable approach that we have named the POPEM module (POpulation Parameterization for Earth Models). This module computes monthly fossil fuel emissions at grid-point scale using the modeled population projections. This paper shows how integrating POPEM parameterization into the CESM (Community Earth System Model) enhances the realism of global climate modeling, improving this beyond simpler approaches. The results show that it is indeed advantageous to model CO2 emissions and pollutants directly at model grid points rather than using the same mean value globally. A major bonus of this approach is the increased capacity to understand the potential effects of localized pollutant emissions on long-term global climate statistics, thus assisting adaptation and mitigation policies.

scholarly journals Impact of an extremely large magnitude volcanic eruption on the global climate and carbon cycle estimated from ensemble Earth System Model simulations

2012 ◽  
Vol 9 (7) ◽  
pp. 8693-8732 ◽  
Author(s):  
J. Segschneider ◽  
A. Beitsch ◽  
C. Timmreck ◽  
V. Brovkin ◽  
T. Ilyina ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Carbon Content ◽  
Volcanic Eruption ◽  
Global Climate ◽  
Earth System Model ◽  
System Model ◽  
Carbon Pools ◽  
Earth System ◽  
Ensemble Mean ◽  
Atmospheric Carbon

Abstract. The response of the global climate-carbon cycle system to an extremely large Northern Hemisphere mid latitude volcanic eruption is investigated using ensemble integrations with the comprehensive Earth System Model MPI-ESM. The model includes dynamical compartments of the atmosphere and ocean and interactive modules of the terrestrial biosphere as well as ocean biogeochemistry. The MPI-ESM was forced with anomalies of aerosol optical depth and effective radius of aerosol particles corresponding to a super eruption of the Yellowstone volcanic system. The model experiment consists of an ensemble of fifteen model integrations that are started at different pre-ENSO states of a contol experiment and run for 200 yr after the volcanic eruption. The climate response to the volcanic eruption is a maximum global monthly mean surface air temperature cooling of 3.8 K for the ensemble mean and from 3.3 K to 4.3 K for individual ensemble members. Atmospheric pCO2 decreases by a maximum of 5 ppm for the ensemble mean and by 3 ppm to 7 ppm for individual ensemble members approximately 6 yr after the eruption. The atmospheric carbon content only very slowly returns to near pre-eruption level at year 200 after the eruption. The ocean takes up carbon shortly after the eruption in response to the cooling, changed wind fields, and ice cover. This physics driven uptake is weakly counteracted by a reduction of the biological export production mainly in the tropical Pacific. The land vegetation pool shows a distinct loss of carbon in the initial years after the eruption which has not been present in simulations of smaller scale eruptions. The gain of the soil carbon pool determines the amplitude of the CO2 perturbation and the long term behaviour of the overall system: an initial gain caused by reduced soil respiration is followed by a rather slow return towards pre-eruption levels. During this phase, the ocean compensates partly for the reduced atmospheric carbon content in response to the land's gain. In summary, we find that the volcanic eruption has long lasting effects on the carbon cycle: after 200 yr, the ocean and the land carbon pools are still different from the pre-eruption state, and the land carbon pools (vegetation and soil) show some long lasting local anomalies that are only partly visible in the global signal.

scholarly journals Analysis of Secondary Organic Aerosol Simulation Bias in the Community Earth System Model (CESM2.1)

2020 ◽  
Author(s):  
Yaman Liu ◽  
Xinyi Dong ◽  
Minghuai Wang ◽  
Louisa K. Emmons ◽  
Yawen Liu ◽  
...  
Keyword(s):  
Climate Models ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
The United States ◽  
Earth System Model ◽  
Basis Set ◽  
System Model ◽  
Earth System ◽  
Model Version ◽  
Community Earth System Model

Abstract. Organic aerosol (OA) has been considered as one of the most important uncertainties in climate modeling due to the complexity in presenting its chemical production and depletion mechanisms. To better understand the capability of climate models and probe into the associated uncertainties in simulating OA, we evaluate the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 (CAM6) with comprehensive tropospheric and stratospheric chemistry representation (CAM6-Chem), through a long-term simulation (1988–2019) with observations collected from multiple datasets in the United States. We find that CESM generally reproduces the inter-annual variation and seasonal cycle of OA mass concentration at surface layer with correlation of 0.40 as compared to ground observations, and systematically overestimates (69 %) in summer and underestimates (−19 %) in winter. Through a series of sensitivity simulations, we reveal that modeling bias is primarily related to the dominant fraction of monoterpene-formed secondary organic aerosol (SOA), and a strong positive correlation of 0.67 is found between monoterpene emission and modeling bias in eastern US during summer. In terms of vertical profile, the model prominently underestimates OA and monoterpene concentrations by 37–99 % and 82–99 % respectively in the upper air (> 500 m) as validated against aircraft observations. Our study suggests that the current Volatility Basis Set (VBS) scheme applied in CESM might be parameterized with too high monoterpene SOA yields which subsequently result in strong SOA production near emission source area. We also find that the model has difficulty in reproducing the decreasing trend of surface OA in southeast US, probably because of employing pure gas VBS to represent isoprene SOA which is in reality mainly formed through multiphase chemistry, thus the influence of aerosol acidity and sulfate particle change on isoprene SOA formation has not been fully considered in the model. This study reveals the urgent need to improve the SOA modeling in climate models.

Higher Vertical Resolution for Select Physical Processes in the Energy Exascale Earth System Model (E3SM)

2020 ◽  
Author(s):  
Hsiang-He Lee ◽  
Peter Bogenschutz ◽  
Takanobu Yamaguchi
Keyword(s):  
Boundary Layer ◽  
Climate Models ◽  
Computational Cost ◽  
Earth System Model ◽  
Global Climate Models ◽  
Computational Method ◽  
System Model ◽  
Vertical Resolution ◽  
Earth System ◽  
Low Cloud

&lt;p&gt;The low cloud bias in atmospheric models for climate and weather remains an unsolved problem. Coarse vertical resolution in the current global climate models (GCM) may be a significant cause of low cloud bias because planetary boundary layer (PBL) parameterizations, including higher-order turbulence closure (HOC), cannot resolve sharp temperature and moisture gradients often found at the top of subtropical stratocumulus layers. The aim of this work is to implement a new computational method, the Framework for Improvement by Vertical Enhancement (FIVE) into the Energy Exascale Earth System Model (E3SM) and its single column model. Three physics schemes are interfaced to vertically enhanced physics (VEP), which allows for these schemes to be computed on a higher vertical resolution grid compared to rest of the E3SM model.&amp;#160; In this presentation we use VEP for turbulence, microphysics, and radiation parameterizations and demonstrate better representation of subtropical boundary layer clouds while limiting additional computational cost from the increased number of levels.&amp;#160; We will also briefly discuss future plans for an adaptive vertical grid for VEP, which will allow for additional layers to be added only when/where they are needed.&lt;/p&gt;

scholarly journals Improving the representation of anthropogenic CO<sub>2</sub> emissions in climate models: a new parameterization for the Community Earth System Model (CESM)

2018 ◽  
Author(s):  
Andrés Navarro ◽  
Raúl Moreno ◽  
Francisco J. Tapiador
Keyword(s):  
Human Activities ◽  
Climate Models ◽  
Global Climate ◽  
Grid Point ◽  
Earth System Model ◽  
Population Projections ◽  
Pollutant Emissions ◽  
System Model ◽  
Earth System ◽  
Community Earth System Model

Abstract. ESMs (Earth System Models) are important tools that help scientists understand the complexities of the Earth's climate. Advances in computing power have permitted the development of increasingly complex ESMs and the introduction of better, more accurate parameterizations of processes that are too complex to be described in detail. One of the least well-controlled parameterizations involves human activities and their direct impact at local and regional scales. In order to improve the direct representation of human activities and climate, we have developed a simple, scalable approach that we have named the POPEM module (POpulation Parameterization for Earth Models). This module computes monthly fossil fuel emissions at grid point scale using the modeled population projections. This paper shows how integrating POPEM parameterization into the CESM (Community Earth System Model) enhances the realism of global climate modeling, improving this beyond simpler approaches. The results show that it is indeed advantageous to model CO2 emissions and pollutants directly at model grid points rather than using the forcing approach. A major bonus of this approach is the increased capacity to understand the potential effects of localized pollutant emissions on long-term global climate statistics, thus assisting adaptation and mitigation policies.

scholarly journals “Infrastructural geopolitics” of climate knowledge: the Brazilian Earth System Model and the North-South knowledge divide

Sociologias ◽  
2019 ◽  
Vol 21 (51) ◽  
pp. 44-75 ◽  
Author(s):  
Jean Carlos Hochsprung Miguel ◽  
Martin Mahony ◽  
Marko Synésio Alves Monteiro
Keyword(s):  
Climate Change ◽  
Latin American ◽  
Climate Models ◽  
Global Climate ◽  
Developed Countries ◽  
Earth System Model ◽  
System Model ◽  
Climate Modelling ◽  
Earth System ◽  
Climate Knowledge

Abstract This article examines how geopolitics are embedded into the efforts of Southern nations that try to build new climate knowledge infrastructures. It achieves this through an analysis of the composition of the international climate modelling basis of the Intergovernmental Panel on Climate Change (IPCC), viewed from the perspective of the Brazilian Earth System Model (BESM) - the scientific project which placed a Latin American country for the first time inside the global modelling bases of the IPCC. The paper argues that beyond the idea of “infrastructural globalism”, a historical process of global scientific cooperation led by developed countries, we also need to understand the “infrastructural geopolitics” of climate models. This concept seeks to describe the actions of developing countries towards minimizing the imbalance of global climate scientific production, and how these countries participate in global climate governance and politics. The analysis of the construction of BESM suggests that national investments in global climate modelling were aimed at attaining scientific sovereignty, which is closely related to a notion of political sovereignty of the nation-state within the international regime of climate change.

scholarly journals Analysis of Secondary Organic Aerosol Simulation Bias in the Community Earth System Model (CESM2.1)

2021 ◽  
Author(s):  
Yaman Liu ◽  
Xinyi Dong ◽  
Minghuai Wang ◽  
Louisa Emmons ◽  
Yawen Liu ◽  
...  
Keyword(s):  
Climate Models ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
The United States ◽  
Earth System Model ◽  
Basis Set ◽  
System Model ◽  
Earth System ◽  
Model Version ◽  
Community Earth System Model

&lt;p&gt;Organic aerosol (OA) has been considered as one of the most important uncertainties in climate modeling due to the complexity in presenting its chemical production and depletion mechanisms. To better understand the capability of climate models and probe into the associated uncertainties in simulating OA, we evaluate the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 (CAM6) with comprehensive tropospheric and stratospheric chemistry representation (CAM6-Chem), through a long-term simulation (1988&amp;#8211;2019) with observations collected from multiple datasets in the United States. We find that CESM generally reproduces the inter-annual variation and seasonal cycle of OA mass concentration at surface layer with correlation of 0.40 as compared to ground observations, and systematically overestimates (69 %) in summer and underestimates (-19 %) in winter. Through a series of sensitivity simulations, we reveal that modeling bias is primarily related to the dominant fraction of monoterpene-formed secondary organic aerosol (SOA), and a strong positive correlation of 0.67 is found between monoterpene emission and modeling bias in eastern US during summer. In terms of vertical profile, the model prominently underestimates OA and monoterpene concentrations by 37&amp;#8211;99 % and 82&amp;#8211;99 % respectively in the upper air (&gt;500 m) as validated against aircraft observations. Our study suggests that the current Volatility Basis Set (VBS) scheme applied in CESM might be parameterized with too high monoterpene SOA yields which subsequently result in strong SOA production near emission source area. We also find that the model has difficulty in reproducing the decreasing trend of surface OA in southeast US, probably because of employing pure gas VBS to represent isoprene SOA which is in reality mainly formed through multiphase chemistry, thus the influence of aerosol acidity and sulfate particle change on isoprene SOA formation has not been fully considered in the model. This study reveals the urgent need to improve the SOA modeling in climate models.&lt;/p&gt;

scholarly journals Temporal- and Spatial-Scale Dependence of Three CMIP3 Climate Models in Simulating the Surface Temperature Trend in the Twentieth Century

2012 ◽  
Vol 25 (7) ◽  
pp. 2456-2470 ◽  
Author(s):  
Koichi Sakaguchi ◽  
Xubin Zeng ◽  
Michael A. Brunke
Keyword(s):  
Twentieth Century ◽  
Climate Models ◽  
Global Climate ◽  
Time Windows ◽  
Scale Dependence ◽  
Global Climate Models ◽  
System Model ◽  
Temporal Scales ◽  
Climate System Model ◽  
Linear Trends

Abstract Motivated by increasing interests in regional- and decadal-scale climate predictions, this study systematically analyzed the spatial- and temporal-scale dependence of the prediction skill of global climate models in surface air temperature (SAT) change in the twentieth century. The linear trends of annual mean SAT over moving time windows (running linear trends) from two observational datasets and simulations by three global climate models [Community Climate System Model, version 3.0 (CCSM3.0), Climate Model, version 2.0 (CM2.0), and Model E-H] that participated in CMIP3 are compared over several temporal (10-, 20-, 30-, 40-, and 50-yr trends) and spatial (5° × 5°, 10° × 10°, 15° × 15°, 20° × 20°, 30° × 30°, 30° latitudinal bands, hemispheric, and global) scales. The distribution of root-mean-square error is improved with increasing spatial and temporal scales, approaching the observational uncertainty range at the largest scales. Linear correlation shows a similar tendency, but the limited observational length does not provide statistical significance over the longer temporal scales. The comparison of RMSE to climatology and a Monte Carlo test using preindustrial control simulations suggest that the multimodel ensemble mean is able to reproduce robust climate signals at 30° zonal mean or larger spatial scales, while correlation requires hemispherical or global mean for the twentieth-century simulations. Persistent lower performance is observed over the northern high latitudes and the North Atlantic southeast of Greenland. Although several caveats exist for the metrics used in this study, the analyses across scales and/or over running time windows can be taken as one of the approaches for climate system model evaluations.

Comparison of the surface mass and energy balance of CESM and MAR forced by CESM over Greenland: present and future

2020 ◽  
Author(s):  
Charlotte Lang ◽  
Charles Amory ◽  
Alison Delhasse ◽  
Stefan Hofer ◽  
Christoph Kittel ◽  
...  
Keyword(s):  
Energy Balance ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Earth System Model ◽  
Global Climate Models ◽  
Added Value ◽  
System Model ◽  
Earth System ◽  
Surface Mass

&lt;p&gt;We have compared the surface mass (SMB) and energy balance of the Earth System model (ESM) CESM (Community Earth System Model) with those of the regional climate model (RCM) MAR (Mod&amp;#232;le Atmosph&amp;#233;rique R&amp;#233;gional) forced by CESM over the present era (1981 &amp;#8212; 2010) and the future (2011 &amp;#8212; 2100 with SSP585 scenario).&lt;/p&gt;&lt;p&gt;Until now, global climate models (GCM) and ESMs forcing RCMs such as MAR didn&amp;#8217;t include a module able to simulate snow and energy balance at the surface of a snow pack like the SISVAT module of MAR and were therefore not able to simulate the SMB of an ice sheet. Evaluating the added value of an RCM compared to a GCM could only be done by comparing atmospheric outputs (temperature, wind, precipitation &amp;#8230;) in both models. CESM is the first ESM including a land model capable of simulating the surface of an ice sheet and thus to directly compare the SMB of an RCM and an ESM the first time.&lt;/p&gt;&lt;p&gt;Our results show that, if the SMB and is components are very similar in CESM and MAR over the present era, they quickly start to diverge in our future projection, the SMB of MAR decreasing more than that of CESM. This difference in SMB evolution is almost exclusively explained by a much larger increase of the melter runoff in MAR compared to CESM whereas the temporal evolution of snowfall, rainfall and sublimation is comparable in both runs.&lt;/p&gt;

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