scholarly journals The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations

2018 ◽  
Vol 10 (2) ◽  
pp. 357-380 ◽  
Author(s):  
K. D. Williams ◽  
D. Copsey ◽  
E. W. Blockley ◽  
A. Bodas‐Salcedo ◽  
D. Calvert ◽  
...  
Keyword(s):  
Coupled Model ◽  
Global Coupled Model

scholarly journals Dynamics of the Indian monsoon and ENSO relationships in the SINTEX global coupled model

2004 ◽  
Vol 24 (2-3) ◽  
pp. 145-168 ◽  
Author(s):  
P. Terray ◽  
E. Guilyardi ◽  
A. S. Fischer ◽  
P. Delecluse
Keyword(s):  
Indian Monsoon ◽  
Coupled Model ◽  
Global Coupled Model

scholarly journals IPCC global coupled model simulations of the South America monsoon system

2008 ◽  
Vol 33 (7-8) ◽  
pp. 893-916 ◽  
Author(s):  
Rodrigo J. Bombardi ◽  
Leila M. V. Carvalho
Keyword(s):  
South America ◽  
Coupled Model ◽  
The South ◽  
Model Simulations ◽  
Monsoon System ◽  
Global Coupled Model

scholarly journals The Met Office Global Coupled model 2.0 (GC2) configuration

2015 ◽  
Vol 8 (1) ◽  
pp. 521-565 ◽  
Author(s):  
K. D. Williams ◽  
C. M. Harris ◽  
A. Bodas-Salcedo ◽  
J. Camp ◽  
R. E. Comer ◽  
...  
Keyword(s):  
Coupled Model ◽  
Systematic Errors ◽  
Diagnostic Techniques ◽  
Seasonal Forecast ◽  
Unified Model ◽  
Climate Projection ◽  
Forecast System ◽  
Projection System ◽  
Model Components ◽  
Global Coupled Model

Abstract. The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems.

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

2013 ◽  
Vol 42 (1-2) ◽  
pp. 271-290 ◽  
Author(s):  
Chloé Prodhomme ◽  
Pascal Terray ◽  
Sébastien Masson ◽  
Takeshi Izumo ◽  
Tomoki Tozuka ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Indian Monsoon ◽  
Coupled Model ◽  
Global Coupled Model

scholarly journals Monsoon intra-seasonal variability in a high-resolution version of Met Office Global Coupled model

2017 ◽  
Vol 69 (1) ◽  
pp. 1354661 ◽  
Author(s):  
Yongjie Fang ◽  
Peili Wu ◽  
M.S. Mizielinski ◽  
M.J. Roberts ◽  
Bo Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Seasonal Variability ◽  
Coupled Model ◽  
Global Coupled Model

scholarly journals Sea ice in the Barents Sea: seasonal to interannual variability and climate feedbacks in a global coupled model

2008 ◽  
Vol 32 (7-8) ◽  
pp. 1119-1138 ◽  
Author(s):  
Torben Koenigk ◽  
Uwe Mikolajewicz ◽  
Johann H. Jungclaus ◽  
Alexandra Kroll
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Barents Sea ◽  
Coupled Model ◽  
Climate Feedbacks ◽  
The Barents Sea ◽  
Global Coupled Model

scholarly journals Development of Global Sea Ice 6.0 CICE configuration for the Met Office Global Coupled Model

2015 ◽  
Vol 8 (3) ◽  
pp. 2529-2554 ◽  
Author(s):  
J. G. L. Rae ◽  
H. T. Hewitt ◽  
A. B. Keen ◽  
J. K. Ridley ◽  
A. E. West ◽  
...  
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Ocean Model ◽  
The Arctic ◽  
Large Reduction ◽  
Sea Ice Extent ◽  
Warm Bias ◽  
The Antarctic ◽  
Global Coupled Model

Abstract. The new sea ice configuration GSI6.0, used in the Met Office global coupled configuration GC2.0, is described and the sea ice extent, thickness and volume are compared with the previous configuration and with observationally-based datasets. In the Arctic, the sea ice is thicker in all seasons than in the previous configuration, and there is now better agreement of the modelled concentration and extent with the HadISST dataset. In the Antarctic, a warm bias in the ocean model has been exacerbated at the higher resolution of GC2.0, leading to a large reduction in ice extent and volume; further work is required to rectify this in future configurations.

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