scholarly journals Development of Coupled Data Assimilation With the BCC Climate System Model: Highlighting the Role of Sea‐Ice Assimilation for Global Analysis

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
X. Liu ◽  
J. Yao ◽  
T. Wu ◽  
S. Zhang ◽  
F. Xu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Ice ◽  
Global Analysis ◽  
Climate System ◽  
System Model ◽  
Climate System Model ◽  
Coupled Data Assimilation

Response of the NCAR Climate System Model to Increased CO2and the Role of Physical Processes

2000 ◽  
Vol 13 (11) ◽  
pp. 1879-1898 ◽  
Author(s):  
Gerald A. Meehl ◽  
William D. Collins ◽  
Byron A. Boville ◽  
Jeffrey T. Kiehl ◽  
T. M. L. Wigley ◽  
...  
Keyword(s):  
Climate System ◽  
System Model ◽  
Physical Processes ◽  
Climate System Model

scholarly journals The CSIRO Mk3L climate system model version 1.0 – Part 1: Description and evaluation

2011 ◽  
Vol 4 (2) ◽  
pp. 483-509 ◽  
Author(s):  
S. J. Phipps ◽  
L. D. Rotstayn ◽  
H. B. Gordon ◽  
J. L. Roberts ◽  
A. C. Hirst ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation Model ◽  
Land Surface ◽  
General Circulation ◽  
Regional Scale ◽  
Circulation Model ◽  
Climate System ◽  
System Model ◽  
Desktop Computer ◽  
Climate System Model

Abstract. The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulations and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. This paper describes the model physics and software, analyses the control climatology, and evaluates the ability of the model to simulate the modern climate. Mk3L incorporates a spectral atmospheric general circulation model, a z-coordinate ocean general circulation model, a dynamic-thermodynamic sea ice model and a land surface scheme with static vegetation. The source code is highly portable, and has no dependence upon proprietary software. The model distribution is freely available to the research community. A 1000-yr climate simulation can be completed in around one-and-a-half months on a typical desktop computer, with greater throughput being possible on high-performance computing facilities. Mk3L produces realistic simulations of the larger-scale features of the modern climate, although with some biases on the regional scale. The model also produces reasonable representations of the leading modes of internal climate variability in both the tropics and extratropics. The control state of the model exhibits a high degree of stability, with only a weak cooling trend on millennial timescales. Ongoing development work aims to improve the model climatology and transform Mk3L into a comprehensive earth system model.

scholarly journals The Community Climate System Model Version 4

2011 ◽  
Vol 24 (19) ◽  
pp. 4973-4991 ◽  
Author(s):  
Peter R. Gent ◽  
Gokhan Danabasoglu ◽  
Leo J. Donner ◽  
Marika M. Holland ◽  
Elizabeth C. Hunke ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Frequency Distribution ◽  
Arctic Sea Ice ◽  
Climate System ◽  
System Model ◽  
The Arctic ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Arctic Sea

The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1° results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4°-resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in CCSM4 producing El Niño–Southern Oscillation variability with a much more realistic frequency distribution than in CCSM3, although the amplitude is too large compared to observations. These changes also improve the Madden–Julian oscillation and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the Gulf Stream path and the North Atlantic Ocean meridional overturning circulation. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than CCSM3, and for several reasons the Arctic sea ice concentration is improved in CCSM4. An ensemble of twentieth-century simulations produces a good match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4°C. This is consistent with the fact that CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of shortwave and longwave cloud forcings.

Initial-value predictability of Antarctic sea ice in the Community Climate System Model 3

2013 ◽  
Vol 40 (10) ◽  
pp. 2121-2124 ◽  
Author(s):  
Marika M. Holland ◽  
Edward Blanchard-Wrigglesworth ◽  
Jennifer Kay ◽  
Steven Vavrus
Keyword(s):  
Sea Ice ◽  
Climate System ◽  
System Model ◽  
Initial Value ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Antarctic Sea Ice ◽  
Community Climate

scholarly journals Simulation of sea ice in the NCAR Climate System Model

1997 ◽  
Vol 25 ◽  
pp. 107-110 ◽  
Author(s):  
John W. Weatherly ◽  
Thomas W. Bettge ◽  
Bruce P. Briegleb
Keyword(s):  
Sea Ice ◽  
Ad Hoc ◽  
Climate System ◽  
System Model ◽  
The Arctic ◽  
Climate Simulation ◽  
Climate System Model ◽  
Polar Climate ◽  
Ice Drift ◽  
Cavitating Fluid

The Climate System Model (CSM) developed at the National Center for Atmospheric Research (NCAR) consists of atmosphere, land and ocean models, as well as a dynamic-thermodynamic sea-ice model. The results of sea-ice simulation using the first coupled climate simulation with the CSM is presented. It was found that the simulated total-ice areas in both hemispheres compared well with observations for winter, but were too large for summer. The numerical solution of the cavitating fluid dynamics was found to allow excessive ridging of ice, and an ad hoc correction was implemented. The ice velocities were realistic for the Antarctic, but for the Arctic were turned toward Alaska and Siberia by modeled winds and currents. This ice-drift pattern was reflected by ice thickness, which lacks the observed ridging near Greenland. The results illustrate the sensitivity of sea ice to the simulation of polar climate and the challenge of modeling the entire climate system.

scholarly journals Simulation of sea ice in the NCAR Climate System Model

1997 ◽  
Vol 25 ◽  
pp. 107-110 ◽  
Author(s):  
John W. Weatherly ◽  
Thomas W. Bettge ◽  
Bruce P. Briegleb
Keyword(s):  
Sea Ice ◽  
Ad Hoc ◽  
Climate System ◽  
System Model ◽  
The Arctic ◽  
Climate Simulation ◽  
Climate System Model ◽  
Polar Climate ◽  
Ice Drift ◽  
Cavitating Fluid

The Climate System Model (CSM) developed at the National Center for Atmospheric Research (NCAR) consists of atmosphere, land and ocean models, as well as a dynamic-thermodynamic sea-ice model. The results of sea-ice simulation using the first coupled climate simulation with the CSM is presented. It was found that the simulated total-ice areas in both hemispheres compared well with observations for winter, but were too large for summer. The numerical solution of the cavitating fluid dynamics was found to allow excessive ridging of ice, and an ad hoc correction was implemented. The ice velocities were realistic for the Antarctic, but for the Arctic were turned toward Alaska and Siberia by modeled winds and currents. This ice-drift pattern was reflected by ice thickness, which lacks the observed ridging near Greenland. The results illustrate the sensitivity of sea ice to the simulation of polar climate and the challenge of modeling the entire climate system.

scholarly journals The Community Climate System Model Version 3 (CCSM3)

2006 ◽  
Vol 19 (11) ◽  
pp. 2122-2143 ◽  
Author(s):  
William D. Collins ◽  
Cecilia M. Bitz ◽  
Maurice L. Blackmon ◽  
Gordon B. Bonan ◽  
Christopher S. Bretherton ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Climate System ◽  
System Model ◽  
Ice Dynamics ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Model Version ◽  
Systematic Biases ◽  
Community Climate

Abstract The Community Climate System Model version 3 (CCSM3) has recently been developed and released to the climate community. CCSM3 is a coupled climate model with components representing the atmosphere, ocean, sea ice, and land surface connected by a flux coupler. CCSM3 is designed to produce realistic simulations over a wide range of spatial resolutions, enabling inexpensive simulations lasting several millennia or detailed studies of continental-scale dynamics, variability, and climate change. This paper will show results from the configuration used for climate-change simulations with a T85 grid for the atmosphere and land and a grid with approximately 1° resolution for the ocean and sea ice. The new system incorporates several significant improvements in the physical parameterizations. The enhancements in the model physics are designed to reduce or eliminate several systematic biases in the mean climate produced by previous editions of CCSM. These include new treatments of cloud processes, aerosol radiative forcing, land–atmosphere fluxes, ocean mixed layer processes, and sea ice dynamics. There are significant improvements in the sea ice thickness, polar radiation budgets, tropical sea surface temperatures, and cloud radiative effects. CCSM3 can produce stable climate simulations of millennial duration without ad hoc adjustments to the fluxes exchanged among the component models. Nonetheless, there are still systematic biases in the ocean–atmosphere fluxes in coastal regions west of continents, the spectrum of ENSO variability, the spatial distribution of precipitation in the tropical oceans, and continental precipitation and surface air temperatures. Work is under way to extend CCSM to a more accurate and comprehensive model of the earth's climate system.

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