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)

Author(s):  
Andrés Navarro ◽  
Raúl Moreno ◽  
Francisco J. Tapiador

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.

2018 ◽  
Vol 9 (3) ◽  
pp. 1045-1062 ◽  
Author(s):  
Andrés Navarro ◽  
Raúl Moreno ◽  
Francisco J. Tapiador

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.


2020 ◽  
Vol 13 (2) ◽  
pp. 717-734 ◽  
Author(s):  
Nicholas A. Davis ◽  
Sean M. Davis ◽  
Robert W. Portmann ◽  
Eric Ray ◽  
Karen H. Rosenlof ◽  
...  

Abstract. Specified dynamics (SD) schemes relax the circulation in climate models toward a reference meteorology to simulate historical variability. These simulations are widely used to isolate the dynamical contributions to variability and trends in trace gas species. However, it is not clear if trends in the stratospheric overturning circulation are properly reproduced by SD schemes. This study assesses numerous SD schemes and modeling choices in the Community Earth System Model (CESM) Whole Atmosphere Chemistry Climate Model (WACCM) to determine a set of best practices for reproducing interannual variability and trends in tropical stratospheric upwelling estimated by reanalyses. Nudging toward the reanalysis meteorology as is typically done in SD simulations does not accurately reproduce lower-stratospheric upwelling trends present in the underlying reanalysis. In contrast, nudging to anomalies from the climatological winds or anomalies from the zonal-mean winds and temperatures better reproduces trends in lower-stratospheric upwelling, possibly because these schemes do not disrupt WACCM's climatology. None of the schemes substantially alter the structure of upwelling trends – instead, they make the trends more or less AMIP-like. An SD scheme's performance in simulating the acceleration of the shallow branch of the mean meridional circulation from 1980 to 2017 hinges on its ability to simulate the downward shift of subtropical lower-stratospheric wave momentum forcing. Key to this is not nudging the zonal-mean temperature field. Gravity wave momentum forcing, which drives a substantial fraction of the upwelling in WACCM, cannot be constrained by nudging and presents an upper limit on the performance of these schemes.


2020 ◽  
Author(s):  
Yaman Liu ◽  
Xinyi Dong ◽  
Minghuai Wang ◽  
Louisa K. Emmons ◽  
Yawen Liu ◽  
...  

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.


2020 ◽  
Author(s):  
Chih-Chieh Chen ◽  
Changhai Liu ◽  
Mitch Moncrieff ◽  
Yaga Richter

&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;


2018 ◽  
Vol 2018 ◽  
pp. 1-24 ◽  
Author(s):  
Jacob Agyekum ◽  
Thompson Annor ◽  
Benjamin Lamptey ◽  
Emmannuel Quansah ◽  
Richard Yao Kuma Agyeman

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.


Sociologias ◽  
2019 ◽  
Vol 21 (51) ◽  
pp. 44-75 ◽  
Author(s):  
Jean Carlos Hochsprung Miguel ◽  
Martin Mahony ◽  
Marko Synésio Alves Monteiro

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.


2021 ◽  
Author(s):  
Yaman Liu ◽  
Xinyi Dong ◽  
Minghuai Wang ◽  
Louisa Emmons ◽  
Yawen Liu ◽  
...  

&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;


2013 ◽  
Vol 26 (20) ◽  
pp. 7793-7812 ◽  
Author(s):  
Miren Vizcaíno ◽  
William H. Lipscomb ◽  
William J. Sacks ◽  
Jan H. van Angelen ◽  
Bert Wouters ◽  
...  

Abstract The modeling of the surface mass balance (SMB) of the Greenland Ice Sheet (GIS) requires high-resolution models in order to capture the observed large gradients in the steep marginal areas. Until now, global climate models have not been considered suitable to model ice sheet SMB owing to model biases and insufficient resolution. This study analyzes the GIS SMB simulated for the period 1850–2005 by the Community Earth System Model (CESM), which includes a new ice sheet component with multiple elevation classes for SMB calculations. The model is evaluated against observational data and output from the regional model Regional Atmospheric Climate Model version 2 (RACMO2). Because of a lack of major climate biases, a sophisticated calculation of snow processes (including surface albedo evolution) and an adequate downscaling technique, CESM is able to realistically simulate GIS surface climate and SMB. CESM SMB agrees reasonably well with in situ data from 475 locations (r = 0.80) and output from RACMO2 (r = 0.79). The simulated mean SMB for 1960–2005 is 359 ± 120 Gt yr−1 in the range of estimates from regional climate models. The simulated seasonal mass variability is comparable with mass observations from the Gravity Recovery and Climate Experiment (GRACE), with synchronous annual maximum (May) and minimum (August–September) and similar amplitudes of the seasonal cycle. CESM is able to simulate the bands of precipitation maxima along the southeast and northwest margins, but absolute precipitation rates are underestimated along the southeastern margin and overestimated in the high interior. The model correctly simulates the major ablation areas. Total refreezing represents 35% of the available liquid water (the sum of rain and melt).


2020 ◽  
Vol 14 (7) ◽  
pp. 2253-2265
Author(s):  
Jan T. M. Lenaerts ◽  
M. Drew Camron ◽  
Christopher R. Wyburn-Powell ◽  
Jennifer E. Kay

Abstract. The dominant mass input component of the Greenland Ice Sheet (GrIS) is precipitation, whose amounts and phase are poorly constrained by observations. Here we use spaceborne radar observations from CloudSat to map the precipitation frequency and phase on the GrIS, and we use those observations, in combination with a satellite simulator to enable direct comparison between observations and model, to evaluate present-day precipitation frequency in the Community Earth System Model (CESM). The observations show that substantial variability of snowfall frequency over the GrIS exists, that snowfall occurs throughout the year, and that snowfall frequency peaks in spring and fall. Rainfall is rare over the GrIS and only occurs in regions under 2000 m elevation and in the peak summer season. Although CESM overestimates the rainfall frequency, it reproduces the spatial and seasonal variability of precipitation frequency reasonably well. Driven by the high-emission, worst-case Representative Concentration Pathway (RCP) 8.5 scenario, CESM indicates that rainfall frequency will increase considerably across the GrIS, and will occur at higher elevations, potentially exposing a much larger GrIS area to rain and associated meltwater refreezing, firn warming, and reduced storage capacity. This technique can be applied to evaluate precipitation frequency in other climate models and can aid in planning future satellite campaigns.


2014 ◽  
Vol 6 (4) ◽  
pp. 1065-1094 ◽  
Author(s):  
R. Justin Small ◽  
Julio Bacmeister ◽  
David Bailey ◽  
Allison Baker ◽  
Stuart Bishop ◽  
...  

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