Relevant bibliographies by topics / Community Atmospheric Model

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  1. Journal articles

Academic literature on the topic 'Community Atmospheric Model'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Community Atmospheric Model"

1

Long, M. S., W. C. Keene, R. Easter, et al. "Implementation of the chemistry module MECCA (v2.5) in the modal aerosol version of the Community Atmosphere Model component (v3.6.33) of the Community Earth System Model." Geoscientific Model Development Discussions 5, no. 2 (2012): 1483–501. http://dx.doi.org/10.5194/gmdd-5-1483-2012.

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Abstract. A coupled atmospheric chemistry and climate system model was developed using the modal aerosol version of the National Center for Atmospheric Research Community Atmosphere Model (modal-CAM) and the Max Planck Institute for Chemistry's Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA) to provide enhanced resolution of multiphase processes, particularly those involving inorganic halogens, and associated impacts on atmospheric composition and climate. Three Rosenbrock solvers (Ros-2, Ros-3, RODAS-3) were tested in conjunction with the basic load balancing options available to modal CAM (1) to establish an optimal configuration of the implicitly-solved multiphase chemistry module that maximizes both computational speed and repeatability of Ros-2 and RODAS-3 results versus Ros-3, and (2) to identify potential implementation strategies for future versions of this and similar coupled systems. RODAS-3 was faster than Ros-2 and Ros-3 with good reproduction of Ros-3 results, while Ros-2 was both slower and substantially less reproducible relative to Ros-3 results. Modal-CAM with MECCA chemistry was a factor of 15 slower than modal-CAM using standard chemistry. MECCA chemistry integration times demonstrated a systematic frequency distribution for all three solvers, and revealed that the change in run-time performance was due to a change in the frequency distribution chemical integration times; the peak frequency was similar for all solvers. This suggests that efficient chemistry-focused load-balancing schemes can be developed that rely on the parameters of this frequency distribution.
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2

Long, M. S., W. C. Keene, R. Easter, et al. "Implementation of the chemistry module MECCA (v2.5) in the modal aerosol version of the Community Atmosphere Model component (v3.6.33) of the Community Earth System Model." Geoscientific Model Development 6, no. 1 (2013): 255–62. http://dx.doi.org/10.5194/gmd-6-255-2013.

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Abstract. A coupled atmospheric chemistry and climate system model was developed using the modal aerosol version of the National Center for Atmospheric Research Community Atmosphere Model (modal-CAM; v3.6.33) and the Max Planck Institute for Chemistry's Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA; v2.5) to provide enhanced resolution of multiphase processes, particularly those involving inorganic halogens, and associated impacts on atmospheric composition and climate. Three Rosenbrock solvers (Ros-2, Ros-3, RODAS-3) were tested in conjunction with the basic load-balancing options available to modal-CAM (1) to establish an optimal configuration of the implicitly-solved multiphase chemistry module that maximizes both computational speed and repeatability of Ros-2 and RODAS-3 results versus Ros-3, and (2) to identify potential implementation strategies for future versions of this and similar coupled systems. RODAS-3 was faster than Ros-2 and Ros-3 with good reproduction of Ros-3 results, while Ros-2 was both slower and substantially less reproducible relative to Ros-3 results. Modal-CAM with MECCA chemistry was a factor of 15 slower than modal-CAM using standard chemistry. MECCA chemistry integration times demonstrated a systematic frequency distribution for all three solvers, and revealed that the change in run-time performance was due to a change in the frequency distribution of chemical integration times; the peak frequency was similar for all solvers. This suggests that efficient chemistry-focused load-balancing schemes can be developed that rely on the parameters of this frequency distribution.
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3

Chen, Yong, Yong Han, Quanhua Liu, Paul Van Delst, and Fuzhong Weng. "Community Radiative Transfer Model for Stratospheric Sounding Unit." Journal of Atmospheric and Oceanic Technology 28, no. 6 (2011): 767–78. http://dx.doi.org/10.1175/2010jtecha1509.1.

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Abstract To better use the Stratospheric Sounding Unit (SSU) data for reanalysis and climate studies, issues associated with the fast radiative transfer (RT) model for SSU have recently been revisited and the results have been implemented into the Community Radiative Transfer Model version 2. This study revealed that the spectral resolution for the sensor’s spectral response functions (SRFs) calculations is very important, especially for channel 3. A low spectral resolution SRF results, on average, in 0.6-K brightness temperature (BT) errors for that channel. The variations of the SRFs due to the CO2 cell pressure variations have been taken into account. The atmospheric transmittance coefficients of the fast RT model for the Television and Infrared Observation Satellite (TIROS)-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-11, and NOAA-14 have been generated with CO2 and O3 as variable gases. It is shown that the BT difference between the fast RT model and line-by-line model is less than 0.1 K, but the fast RT model is at least two orders of magnitude faster. The SSU measurements agree well with the simulations that are based on the atmospheric profiles from the Earth Observing System Aura Microwave Limb Sounding product and the Sounding of the Atmosphere using Broadband Emission Radiometry on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. The impact of the CO2 cell pressures shift for SSU has been evaluated by using the Committee on Space Research (COSPAR) International Reference Atmosphere (CIRA) model profiles. It is shown that the impacts can be on an order of 1 K, especially for SSU NOAA-7 channel 2. There are large brightness temperature gaps between observation and model simulation using the available cell pressures for NOAA-7 channel 2 after June 1983. Linear fittings of this channel’s cell pressures based on previous cell leaking behaviors have been studied, and results show that the new cell pressures are reasonable. The improved SSU fast model can be applied for reanalysis of the observations. It can also be used to address two important corrections in deriving trends from SSU measurements: CO2 cell leaking correction and atmospheric CO2 concentration correction.
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4

Baumgaertner, A. J. G., P. Jöckel, A. Kerkweg, R. Sander, and H. Tost. "Implementation of the Community Earth System Model (CESM) version 1.2.1 as a new base model into version 2.50 of the MESSy framework." Geoscientific Model Development 9, no. 1 (2016): 125–35. http://dx.doi.org/10.5194/gmd-9-125-2016.

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Abstract. The Community Earth System Model (CESM1), maintained by the United States National Centre for Atmospheric Research (NCAR) is connected with the Modular Earth Submodel System (MESSy). For the MESSy user community, this offers many new possibilities. The option to use the Community Atmosphere Model (CAM) atmospheric dynamical cores, especially the state-of-the-art spectral element (SE) core, as an alternative to the ECHAM5 spectral transform dynamical core will provide scientific and computational advances for atmospheric chemistry and climate modelling with MESSy. The well-established finite volume core from CESM1(CAM) is also made available. This offers the possibility to compare three different atmospheric dynamical cores within MESSy. Additionally, the CESM1 land, river, sea ice, glaciers and ocean component models can be used in CESM1/MESSy simulations, allowing the use of MESSy as a comprehensive Earth system model (ESM). For CESM1/MESSy set-ups, the MESSy process and diagnostic submodels for atmospheric physics and chemistry are used together with one of the CESM1(CAM) dynamical cores; the generic (infrastructure) submodels support the atmospheric model component. The other CESM1 component models, as well as the coupling between them, use the original CESM1 infrastructure code and libraries; moreover, in future developments these can also be replaced by the MESSy framework. Here, we describe the structure and capabilities of CESM1/MESSy, document the code changes in CESM1 and MESSy, and introduce several simulations as example applications of the system. The Supplements provide further comparisons with the ECHAM5/MESSy atmospheric chemistry (EMAC) model and document the technical aspects of the connection in detail.
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5

Blackmon, Maurice, Byron Boville, Frank Bryan, et al. "The Community Climate System Model." Bulletin of the American Meteorological Society 82, no. 11 (2001): 2357–76. http://dx.doi.org/10.1175/1520-0477(2001)082<2357:tccsm>2.3.co;2.

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6

Collins, William D., Philip J. Rasch, Byron A. Boville, et al. "The Formulation and Atmospheric Simulation of the Community Atmosphere Model Version 3 (CAM3)." Journal of Climate 19, no. 11 (2006): 2144–61. http://dx.doi.org/10.1175/jcli3760.1.

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Abstract A new version of the Community Atmosphere Model (CAM) has been developed and released to the climate community. CAM Version 3 (CAM3) is an atmospheric general circulation model that includes the Community Land Model (CLM3), an optional slab ocean model, and a thermodynamic sea ice model. The dynamics and physics in CAM3 have been changed substantially compared to implementations in previous versions. CAM3 includes options for Eulerian spectral, semi-Lagrangian, and finite-volume formulations of the dynamical equations. It supports coupled simulations using either finite-volume or Eulerian dynamics through an explicit set of adjustable parameters governing the model time step, cloud parameterizations, and condensation processes. The model includes major modifications to the parameterizations of moist processes, radiation processes, and aerosols. These changes have improved several aspects of the simulated climate, including more realistic tropical tropopause temperatures, boreal winter land surface temperatures, surface insolation, and clear-sky surface radiation in polar regions. The variation of cloud radiative forcing during ENSO events exhibits much better agreement with satellite observations. Despite these improvements, several systematic biases reduce the fidelity of the simulations. These biases include underestimation of tropical variability, errors in tropical oceanic surface fluxes, underestimation of implied ocean heat transport in the Southern Hemisphere, excessive surface stress in the storm tracks, and offsets in the 500-mb height field and the Aleutian low.
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7

Pedatella, N. M., H. L. Liu, and A. D. Richmond. "Atmospheric semidiurnal lunar tide climatology simulated by the Whole Atmosphere Community Climate Model." Journal of Geophysical Research: Space Physics 117, A6 (2012): n/a. http://dx.doi.org/10.1029/2012ja017792.

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8

Bonan, Gordon B., Keith W. Oleson, Mariana Vertenstein, et al. "The Land Surface Climatology of the Community Land Model Coupled to the NCAR Community Climate Model*." Journal of Climate 15, no. 22 (2002): 3123–49. http://dx.doi.org/10.1175/1520-0442(2002)015<3123:tlscot>2.0.co;2.

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9

Sander, Rolf, Andreas Baumgaertner, David Cabrera-Perez, et al. "The community atmospheric chemistry box model CAABA/MECCA-4.0." Geoscientific Model Development 12, no. 4 (2019): 1365–85. http://dx.doi.org/10.5194/gmd-12-1365-2019.

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Abstract. We present version 4.0 of the atmospheric chemistry box model CAABA/MECCA that now includes a number of new features: (i) skeletal mechanism reduction, (ii) the Mainz Organic Mechanism (MOM) chemical mechanism for volatile organic compounds, (iii) an option to include reactions from the Master Chemical Mechanism (MCM) and other chemical mechanisms, (iv) updated isotope tagging, and (v) improved and new photolysis modules (JVAL, RADJIMT, DISSOC). Further, when MECCA is connected to a global model, the new feature of coexisting multiple chemistry mechanisms (PolyMECCA/CHEMGLUE) can be used. Additional changes have been implemented to make the code more user-friendly and to facilitate the analysis of the model results. Like earlier versions, CAABA/MECCA-4.0 is a community model published under the GNU General Public License.
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10

Jochum, Markus, Alexandra Jahn, Synte Peacock, et al. "True to Milankovitch: Glacial Inception in the New Community Climate System Model." Journal of Climate 25, no. 7 (2012): 2226–39. http://dx.doi.org/10.1175/jcli-d-11-00044.1.

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Abstract The equilibrium solution of a fully coupled general circulation model with present-day orbital forcing is compared to the solution of the same model with the orbital forcing from 115 000 years ago. The difference in snow accumulation between these two simulations has a pattern and a magnitude comparable to the ones inferred from reconstructions for the last glacial inception. This is a major improvement over previous similar studies, and the increased realism is attributed to the higher spatial resolution in the atmospheric model, which allows for a more accurate representation of the orography of northern Canada and Siberia. The analysis of the atmospheric heat budget reveals that, as postulated by Milankovitch’s hypothesis, the only necessary positive feedback is the snow–albedo feedback, which is initiated by reduced melting of snow and sea ice in the summer. However, this positive feedback is almost fully compensated by an increased meridional heat transport in the atmosphere and a reduced concentration of low Arctic clouds. In contrast to similar previous studies, the ocean heat transport remains largely unchanged. This stability of the northern North Atlantic circulation is explained by the regulating effect of the freshwater import through the Nares Strait and Northwest Passage and the spiciness import by the North Atlantic Current.
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