Results from An Ensemble Reanalysis with the Community Earth System Model 2.1

Author(s):  
Kevin Raeder ◽  
Jeffrey Anderson ◽  
TImothy Hoar ◽  
Nancy Collins ◽  
Moha El Gharamti

<p>The National Center for Atmospheric Research (NCAR) has recently released version 2.1 of the Community Earth System Model (CESM 2.1). A twenty-year, 80-member ensemble atmospheric reanalysis with 1-degree resolution in the CAM6 atmospheric model is being produced using NCAR’s Data Assimilation Research Testbed (DART) to support a variety of climate research goals. A standard configuration of CAM and the CLM5 land surface model will be coupled to a prescribed ocean and sea ice. Eventually, the reanalyisis will generate a final product that extends from 1999 to the present. Observations being assimilated include in situ observations used in the operational NCEP CFSR reanalysis along with GPS occultation observations and remote sensing temperature retrievals. The primary goal is to provide an ensemble of atmospheric forcing that can be used to generate additional ensemble reanalyses for other components of CESM including CLM, the POP and MOM6 ocean models, and the CICE sea ice model. Highlights of results from the first 10-years of the reanalysis will be presented. Results will include evaluation of short-term forecasts in observation space for root mean square error, ensemble spread, and ensemble consistency. In addition, key aspects of the atmospheric forcing files for other components of the climate system will be discussed. </p>

2014 ◽  
Vol 28 (1) ◽  
pp. 272-291 ◽  
Author(s):  
Daniela Dalmonech ◽  
Sönke Zaehle ◽  
Gregor J. Schürmann ◽  
Victor Brovkin ◽  
Christian Reick ◽  
...  

Abstract The capacity of earth system models (ESMs) to make reliable projections of future atmospheric CO2 and climate is strongly dependent on the ability of the land surface model to adequately simulate the land carbon (C) cycle. Defining “adequate” performance of the land model requires an understanding of the contributions of climate model and land model errors to the land C cycle. Here, a benchmarking framework is applied based on significant, observed characteristics of the land C cycle for the contemporary period, for which sufficient evaluation data are available, to test the ability of the JSBACH land surface component of the Max Planck Institute Earth System Model (MPI-ESM) to simulate land C trends. Particular attention is given to the role of potential effects caused by climate biases, and therefore investigation is made of the results of model configurations in which JSBACH is interactively “coupled” to atmosphere and ocean components and of an “uncoupled” configuration, where JSBACH is driven by reconstructed meteorology. The ability of JSBACH to simulate the observed phase of phenology and seasonal C fluxes is not strongly affected by climate biases. Contrarily, noticeable differences in the simulated gross primary productivity and land C stocks emerge between coupled and uncoupled configurations, leading to significant differences in the decadal terrestrial C balance and its sensitivity to climate. These differences are strongly controlled by climate biases of the MPI-ESM, in particular those affecting soil moisture. To effectively characterize model performance, the potential effects of climate biases on the land C dynamics need to be considered during the development and calibration of land surface models.


2016 ◽  
Author(s):  
S. Tilmes ◽  
J.-F. Lamarque ◽  
L. K. Emmons ◽  
D. E. Kinnison ◽  
D. Marsh ◽  
...  

Abstract. The Community Earth System Model, CESM1 CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model Version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low top model that reaches up to approximately 40 km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis For Research And Applications (MERRA) reanalysis. We summarize the performance of the three reference simulations suggested by CCMI, with a focus on the observed period. Comparisons with elected datasets are employed to demonstrate the general performance of the model. We highlight new datasets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics, and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20 % of values from available observations for most regions. In particular, the trend and magnitude of surface ozone has been much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. All experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.


2021 ◽  
Vol 14 (1) ◽  
pp. 603-628
Author(s):  
Shiming Xu ◽  
Jialiang Ma ◽  
Lu Zhou ◽  
Yan Zhang ◽  
Jiping Liu ◽  
...  

Abstract. High-resolution sea ice modeling is becoming widely available for both operational forecasts and climate studies. In traditional Eulerian grid-based models, small-scale sea ice kinematics represent the most prominent feature of high-resolution simulations, and with rheology models such as viscous–plastic (VP) and Maxwell elasto-brittle (MEB), sea ice models are able to reproduce multi-fractal sea ice deformation and linear kinematic features that are seen in high-resolution observational datasets. In this study, we carry out modeling of sea ice with multiple grid resolutions by using the Community Earth System Model (CESM) and a grid hierarchy (22, 7.3, and 2.4 km grid stepping in the Arctic). By using atmospherically forced experiments, we simulate consistent sea ice climatology across the three resolutions. Furthermore, the model reproduces reasonable sea ice kinematics, including multi-fractal spatial scaling of sea ice deformation that partially depends on atmospheric circulation patterns and forcings. By using high-resolution runs as references, we evaluate the model's effective resolution with respect to the statistics of sea ice kinematics. Specifically, we find the spatial scale at which the probability density function (PDF) of the scaled sea ice deformation rate of low-resolution runs matches that of high-resolution runs. This critical scale is treated as the effective resolution of the coarse-resolution grid, which is estimated to be about 6 to 7 times the grid's native resolution. We show that in our model, the convergence of the elastic–viscous–plastic (EVP) rheology scheme plays an important role in reproducing reasonable kinematics statistics and, more strikingly, simulates systematically thinner sea ice than the standard, non-convergent experiments in landfast ice regions of the Canadian Arctic Archipelago. Given the wide adoption of EVP and subcycling settings in current models, it highlights the importance of EVP convergence, especially for climate studies and projections. The new grids and the model integration in CESM are openly provided for public use.


2020 ◽  
Author(s):  
Shiming Xu ◽  
Jialiang Ma ◽  
Lu Zhou ◽  
Yan Zhang ◽  
Jiping Liu ◽  
...  

Abstract. High-resolution sea ice modeling is becoming widely available for both operational forecasts and climate studies. Sea ice kinematics is the most prominent feature of high-resolution simulations, and with rheology models such as Viscous-Plastic, current models are able to reproduce multi-fractality and linear kinematic features in satellite observations. In this study, we carry out multi-scale sea ice modeling with Community Earth System Model (CESM) by using a grid hierarchy (22 km, 7.3 km, and 2.5 km grid stepping in the Arctic). By using atmospherically forced experiments, we simulate consistent sea ice climatology across the 3 resolutions. Furthermore, the model reproduces reasonable sea ice kinematics, including multi-fractal deformation and scaling properties that are temporally changing and dependent on circulation patterns and forcings (e.g., Arctic Oscillation). With the grid hierarchy, we are able to evaluate the model's effective spatial resolution regarding the statistics of kinematics, which is estimated to be about 6 to 7 times that of the grid's native resolution. Besides, we show that in our model, the convergence of the Elastic-Viscous-Plastic (EVP) rheology scheme plays an important role in reproducing reasonable kinematics statistics, and more strikingly, simulates systematically thinner sea ice than the standard, non-convergent experiments in landfast ice regions of Canadian Arctic Archipelago. Given the wide adoption of EVP and subcycling settings in current models, it highlights the importance of EVP convergence especially for climate studies and projections. The new grids and the model integration in CESM are openly provided for public use.


2021 ◽  
Author(s):  
Amélie Desmarais ◽  
Bruno Tremblay

AbstractUncertainties in the timing of a seasonal ice cover in the Arctic Ocean depend on model physics and parameterizations, natural variability at decadal timescales and uncertainties in climate scenarios and forcings. We use the Gridded Monthly Sea-Ice Extent and Concentration, 1850 Onward product to assess the simulated decadal variability from the Community Earth System Model – Large Ensemble (CESM-LE) in the Pacific, Eurasian and Atlantic sector of the Arctic where a longer observational record exists. Results show that sea-ice decadal (8-16 years) variability in CESM-LE is in agreement with the observational record in the Pacific sector of the Arctic, underestimated in the Eurasian sector of the Arctic, specifically in the East-Siberian Sea, and slightly overestimated in the Atlantic sector of the Arctic, specifically in the Greenland Sea. Results also show an increase in variability at decadal timescales in the Eurasian and Pacific sectors during the transition to a seasonally ice-free Arctic, in agreement with the observational record although this increase is delayed by 10-20 years. If the current sea-ice retreat in the Arctic continues to be Pacific-centric, results from the CESM-LE suggest that uncertainty in the timing of an ice-free Arctic associated with natural variability is realistic, but that a seasonal ice cover may occur earlier than projected.


2016 ◽  
Vol 9 (1) ◽  
pp. 125-135 ◽  
Author(s):  
A. J. G. Baumgaertner ◽  
P. Jöckel ◽  
A. Kerkweg ◽  
R. Sander ◽  
H. Tost

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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