Monsoon Regimes in the CCSM3

2006 ◽  
Vol 19 (11) ◽  
pp. 2482-2495 ◽  
Author(s):  
Gerald A. Meehl ◽  
Julie M. Arblaster ◽  
David M. Lawrence ◽  
Anji Seth ◽  
Edwin K. Schneider ◽  
...  
Keyword(s):  
Coupled Model ◽  
Atmospheric Model ◽  
West African ◽  
South American ◽  
Climate System Model ◽  
Model Version ◽  
Monsoon Variability ◽  
Intercomparison Project ◽  
Atmospheric Model Intercomparison Project ◽  
The Tropical Pacific

Abstract Simulations of regional monsoon regimes, including the Indian, Australian, West African, South American, and North American monsoons, are described for the T85 version of the Community Climate System Model version 3 (CCSM3) and compared to observations and Atmospheric Model Intercomparison Project (AMIP)-type SST-forced simulations with the Community Atmospheric Model version 3 (CAM3) at T42 and T85. There are notable improvements in the regional aspects of the precipitation simulations in going to the higher-resolution T85 compared to T42 where topography is important (e.g., Ethiopian Highlands, South American Andes, and Tibetan Plateau). For the T85 coupled version of CCSM3, systematic SST errors are associated with regional precipitation errors in the monsoon regimes of South America and West Africa, though some aspects of the monsoon simulations, particularly in Asia, improve in the coupled model compared to the SST-forced simulations. There is very little realistic intraseasonal monsoon variability in the CCSM3 consistent with earlier versions of the model. Teleconnections to the tropical Pacific are well simulated for the South Asian monsoon.

scholarly journals Monsoon Regimes and Processes in CCSM4. Part II: African and American Monsoon Systems

2012 ◽  
Vol 25 (8) ◽  
pp. 2609-2621 ◽  
Author(s):  
Kerry H. Cook ◽  
Gerald A. Meehl ◽  
Julie M. Arblaster
Keyword(s):  
North American ◽  
Monsoon Rainfall ◽  
West African ◽  
South American ◽  
Gulf Of Guinea ◽  
The West ◽  
Maximum Rainfall ◽  
Climate System Model ◽  
Early Season ◽  
Model Version

Abstract This is the second part of a two part series studying simulation characteristics of the Community Climate System Model, version 4 (CCSM4) for various monsoon regimes around the global tropics. Here, the West African, East African, North American, and South American monsoons are documented in CCSM4. Comparisons are made to an Atmospheric Model Intercomparison Project (AMIP) simulation of the atmospheric component in CCSM4 (CAM4), to deduce differences in the monsoon simulations run with observed SSTs and with ocean–atmosphere coupling. These simulations are also compared to a previous version of the coupled model (CCSM3) to evaluate progress. In most, but not all instances, monsoon rainfall is too heavy in the uncoupled AMIP run with the Community Atmosphere Model, version 4 (CAM4), and monsoon rainfall amounts are generally better simulated with ocean coupling in CCSM4. Some aspects of the monsoon simulations are improved in CCSM4 compared to CCSM3. Early-season rainfall in the West African monsoon is better simulated in CAM4 than in CCSM4 presumably because of the specification of SSTs in the Gulf of Guinea, but the Sahel rainfall season is captured better in CCSM4 as are the African easterly jet and the tropical easterly jet. Improvements in the simulation of the Sahel rainy season (July, August, and September) in CCSM4 compared with CCSM3 are significant, but problems remain in the simulation of the early season (May and June) in association with the misrepresentation of eastern Atlantic (Gulf of Guinea) SSTs. Precipitation distributions and the southwesterly low-level inflow in the North American monsoon are improved in CCSM4 compared to CCSM3. Both CAM4 and CCSM4 reproduce the seasonal evolution of rainfall over the South American monsoon region, but the location of maximum rainfall is misplaced to the northeast in both models.

scholarly journals Changes in the Tropical Pacific SST Trend from CMIP3 to CMIP5 and Its Implication of ENSO

2012 ◽  
Vol 25 (21) ◽  
pp. 7764-7771 ◽  
Author(s):  
Sang-Wook Yeh ◽  
Yoo-Geun Ham ◽  
June-Yi Lee
Keyword(s):  
Coupled Model ◽  
Research Programme ◽  
Tropical Pacific ◽  
Multimodel Ensemble ◽  
Phase 3 ◽  
Intercomparison Project ◽  
Sst Anomaly ◽  
Earth System Models ◽  
Background State ◽  
The Tropical Pacific

This study assesses the changes in the tropical Pacific Ocean sea surface temperature (SST) trend and ENSO amplitude by comparing a historical run of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP) phase-5 multimodel ensemble dataset (CMIP5) and the CMIP phase-3 dataset (CMIP3). The results indicate that the magnitude of the SST trend in the tropical Pacific basin has been significantly reduced from CMIP3 to CMIP5, which may be associated with the overestimation of the response to natural forcing and aerosols by including Earth system models in CMIP5. Moreover, the patterns of tropical warming over the second half of the twentieth century have changed from a La Niña–like structure in CMIP3 to an El Niño–like structure in CMIP5. Further analysis indicates that such changes in the background state of the tropical Pacific and an increase in the sensitivity of the atmospheric response to the SST changes in the eastern tropical Pacific have influenced the ENSO properties. In particular, the ratio of the SST anomaly variance in the eastern and western tropical Pacific increased from CMIP3 to CMIP5, indicating that a center of action associated with the ENSO amplitude has shifted to the east.

scholarly journals Decadal Prediction of the Sahelian Precipitation in CMIP5 Simulations

2013 ◽  
Vol 26 (19) ◽  
pp. 7708-7719 ◽  
Author(s):  
Marco Gaetani ◽  
Elsa Mohino
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
System Model ◽  
Low Resolution ◽  
Coupled Models ◽  
Climate System Model ◽  
Model Version ◽  
Coupled Global Climate Model

Abstract In this study the capability of eight state-of-the-art ocean–atmosphere coupled models in predicting the monsoonal precipitation in the Sahel on a decadal time scale is assessed. To estimate the importance of the initialization, the predictive skills of two different CMIP5 experiments are compared, a set of 10 decadal hindcasts initialized every 5 years in the period 1961–2009 and the historical simulations in the period 1961–2005. Results indicate that predictive skills are highly model dependent: the Fourth Generation Canadian Coupled Global Climate Model (CanCM4), Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5 (CNRM-CM5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR) models show improved skill in the decadal hindcasts, while the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) is skillful in both the decadal and historical experiments. The Beijing Climate Center, Climate System Model, version 1.1 (BCC-CSM1.1), Hadley Centre Coupled Model, version 3 (HadCM3), L'Institut Pierre-Simon Laplace Coupled Model, version 5, coupled with NEMO, low resolution (IPSL-CM5A-LR), and Meteorological Research Institute Coupled Atmosphere–Ocean General Circulation Model, version 3 (MRI-CGCM3) models show insignificant or no skill in predicting the Sahelian precipitation. Skillful predictions are produced by models properly describing the SST multidecadal variability and the initialization appears to play an important role in this respect.

scholarly journals Bulk Connectivity of Global SST and Land Precipitation Variations

2021 ◽  
Author(s):  
Xiaofan Li ◽  
Zeng-Zhen Hu ◽  
Bohua Huang ◽  
Cristiana Stan
Keyword(s):  
Climate Models ◽  
Atmospheric Model ◽  
Precipitation Anomaly ◽  
Connectivity Matrix ◽  
Ensemble Averaging ◽  
Seasonal Evolution ◽  
Global Land ◽  
Precipitation Variation ◽  
Intercomparison Project ◽  
Atmospheric Model Intercomparison Project

Abstract The land climate predictability at seasonal and interannual time scales is largely due to the influence of the ocean. The connections between global sea surface temperature anomaly (SSTA) and precipitation anomaly over land as a whole are assessed using observations and Atmospheric Model Intercomparison Project (AMIP) simulations for 1957-2018 in this work. With a novel bulk connectivity matrix, the regions of SSTA having the most significant connections with global land precipitation anomaly are identified and the seasonal evolution is evaluated. The similarities and differences between the observations and AMIP simulations are examined. In both observations and AMIP simulations, SSTA in the tropical central and eastern Pacific connects strongly with the global land precipitation anomaly. Compared with that in the tropical Pacific, the connections with SSTA along the equatorial Indian and Atlantic Oceans are weaker. However, the seasonal evolution of the connection shows distinguished patterns between the observations and the AMIP simulations with the strongest (weakest) connections in October (June) in the observations, in March and October (June) in a single-member of the AMIP simulation, and in February (June) in the 17-member ensemble mean of the AMIP simulations. The ensemble averaging enhances the strength of the connectivity and improves its seasonality. The results of the bulk connectivity matrix in this work can serve as a benchmark to evaluate the connection of SSTA with global land precipitation variation in climate models.

Snow Mass over North America: Observations and Results from the Second Phase of the Atmospheric Model Intercomparison Project

2005 ◽  
Vol 6 (5) ◽  
pp. 681-695 ◽  
Author(s):  
Allan Frei ◽  
Ross Brown ◽  
James A. Miller ◽  
David A. Robinson
Keyword(s):  
North America ◽  
Large Scale ◽  
Atmospheric Model ◽  
The United States ◽  
Second Phase ◽  
Model Intercomparison ◽  
Continental Scale ◽  
Intercomparison Project ◽  
Atmospheric Model Intercomparison Project ◽  
Snow Mass

Abstract Eighteen global atmospheric general circulation models (AGCMs) participating in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2) are evaluated for their ability to simulate the observed spatial and temporal variability in snow mass, or water equivalent (SWE), over North America during the AMIP-2 period (1979–95). The evaluation is based on a new gridded SWE dataset developed from objective analysis of daily snow depth observations from Canada and the United States with snow density estimated from a simple snowpack model. Most AMIP-2 models simulate the seasonal timing and the relative spatial patterns of continental-scale SWE fairly well. However, there is a tendency to overestimate the rate of ablation during spring, and significant between-model variability is found in every aspect of the simulations, and at every spatial scale analyzed. For example, on the continental scale, the peak monthly SWE integrated over the North American continent in AMIP-2 models varies between ±50% of the observed value of ∼1500 km3. The volume of water in the snowpack, and the magnitudes of model errors, are significant in comparison to major fluxes in the continental water balance. It also appears that the median result from the suite of models tends to do a better job of estimating climatological mean features than any individual model. Year-to-year variations in large-scale SWE are only weakly correlated to observed variations, indicating that sea surface temperatures (specified from observations as boundary conditions) do not drive interannual variations of SWE in these models. These results have implications for simulations of the large-scale hydrologic cycle and for climate change impact assessments.

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