scholarly journals The Interannual Relationship between the Latitude of the Eddy-Driven Jet and the Edge of the Hadley Cell

2011 ◽  
Vol 24 (2) ◽  
pp. 563-568 ◽  
Author(s):  
Sarah M. Kang ◽  
Lorenzo M. Polvani
Keyword(s):  
Coupled Model ◽  
Austral Summer ◽  
Hadley Cell ◽  
Model Intercomparison ◽  
Phase 3 ◽  
Long Term Trends ◽  
Intercomparison Project ◽  
Highly Correlated ◽  
Universal Ratio

Abstract A strong correlation between the latitudes of the eddy-driven jet and of the Hadley cell edge, on interannual time scales, is found to exist during austral summer, in both the NCEP–NCAR reanalysis and the models participating in the Coupled Model Intercomparison Project, phase 3 (CMIP3). In addition, a universal ratio close to 1:2 characterizes the robust connection between these two latitudes on a year-to-year basis: for a 2° shift of the eddy-driven jet, the edge of the Hadley cell shifts by 1°. This 1:2 interannual ratio remains the same in response to climate change, even though the values of the two latitudes increase. The corresponding trends are also highly correlated; in the CMIP3 scenario integrations, however, no universal ratio appears to exist connecting these long-term trends. In austral winter and in the Northern Hemisphere, no strong interannual correlations are found.

scholarly journals Atmospheric and Surface Contributions to Planetary Albedo

2011 ◽  
Vol 24 (16) ◽  
pp. 4402-4418 ◽  
Author(s):  
Aaron Donohoe ◽  
David S. Battisti
Keyword(s):  
Surface Albedo ◽  
Coupled Model ◽  
Small Contribution ◽  
Model Intercomparison ◽  
Radiation Model ◽  
Phase 3 ◽  
Surface Reflection ◽  
Global Average ◽  
Intercomparison Project ◽  
Planetary Albedo

Abstract The planetary albedo is partitioned into a component due to atmospheric reflection and a component due to surface reflection by using shortwave fluxes at the surface and top of the atmosphere in conjunction with a simple radiation model. The vast majority of the observed global average planetary albedo (88%) is due to atmospheric reflection. Surface reflection makes a relatively small contribution to planetary albedo because the atmosphere attenuates the surface contribution to planetary albedo by a factor of approximately 3. The global average planetary albedo in the ensemble average of phase 3 of the Coupled Model Intercomparison Project (CMIP3) preindustrial simulations is also primarily (87%) due to atmospheric albedo. The intermodel spread in planetary albedo is relatively large and is found to be predominantly a consequence of intermodel differences in atmospheric albedo, with surface processes playing a much smaller role despite significant intermodel differences in surface albedo. The CMIP3 models show a decrease in planetary albedo under a doubling of carbon dioxide—also primarily due to changes in atmospheric reflection (which explains more than 90% of the intermodel spread). All models show a decrease in planetary albedo due to the lowered surface albedo associated with a contraction of the cryosphere in a warmer world, but this effect is small compared to the spread in planetary albedo due to model differences in the change in clouds.

Observational and Model Estimates of Cloud Amount Feedback over the Indian and Pacific Oceans

2014 ◽  
Vol 27 (2) ◽  
pp. 925-940 ◽  
Author(s):  
Katinka Bellomo ◽  
Amy C. Clement ◽  
Joel R. Norris ◽  
Brian J. Soden
Keyword(s):  
Coupled Model ◽  
Cloud Amount ◽  
Western Indian Ocean ◽  
Model Intercomparison ◽  
Central Pacific ◽  
Radiative Impact ◽  
Southern Central ◽  
Intercomparison Project ◽  
Very High

AbstractConstraining intermodel spread in cloud feedback with observations is problematic because available cloud datasets are affected by spurious behavior in long-term variability. This problem is addressed by examining cloud amount in three independent ship-based [Extended Edited Cloud Reports Archive (EECRA)] and satellite-based [International Satellite Cloud Climatology Project (ISCCP) and Advanced Very High Resolution Radiometer Pathfinder Atmosphere–Extended (PATMOS-X)] observational datasets, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The three observational datasets show consistent cloud variability in the overlapping years of coverage (1984–2007). The long-term cloud amount change from 1954 to 2005 in ship-based observations shares many of the same features with the multimodel mean cloud amount change of 42 CMIP5 historical simulations, although the magnitude of the multimodel mean is smaller. The radiative impact of cloud changes is estimated by computing an observationally derived estimate of cloud amount feedback. The observational estimates of cloud amount feedback are statistically significant over four regions: the northeast Pacific subtropical stratocumulus region and equatorial western Pacific, where cloud amount feedback is found to be positive, and the southern central Pacific and western Indian Ocean, where cloud amount feedback is found to be negative. Multimodel mean cloud amount feedback is consistent in sign but smaller in magnitude than in observations over these four regions because models simulate weaker cloud changes. Individual models, however, can simulate cloud amount feedback of the same magnitude if not larger than observed. Focusing on the regions where models and observations agree can lead to improved understanding of the mechanisms of cloud amount changes and associated radiative impact.

scholarly journals A new end-to-end workflow for the Community Earth System Model (version 2.0) for the Coupled Model Intercomparison Project Phase 6 (CMIP6)

2020 ◽  
Vol 13 (11) ◽  
pp. 5567-5581
Author(s):  
Sheri Mickelson ◽  
Alice Bertini ◽  
Gary Strand ◽  
Kevin Paul ◽  
Eric Nienhouse ◽  
...  
Keyword(s):  
Coupled Model ◽  
Model Intercomparison ◽  
Phase 3 ◽  
Previous Generation ◽  
Data Volume ◽  
Community Earth System Model ◽  
Intercomparison Project ◽  
Version 2.0 ◽  
New Generation ◽  
Compressed Data

Abstract. The complexity of each Coupled Model Intercomparison Project grows with every new generation. The Phase 5 effort saw a dramatic increase in the number of experiments that were performed and the number of variables that were requested compared to its previous generation, Phase 3. The large increase in data volume stressed the resources of several centers including at the National Center for Atmospheric Research. During Phase 5, we missed several deadlines and we struggled to get the data out to the community for analysis. In preparation for the current generation, Phase 6, we examined the weaknesses in our workflow and addressed the performance issues with new software tools. Through this investment, we were able to publish approximately 565 TB of compressed data to the community, with another 30 TB yet to be published. When compared to the volumes we produced in the previous generation, 165 TB of uncompressed data, we were able to provide 6 times the amount of data and we accomplish this within one-third of the time. This provided us with an approximate 18 times faster speedup. While this paper discusses the improvements we have made to our own workflow for the Coupled Model Intercomparison Project Phase 6 (CMIP6), we hope to encourage other centers to evaluate and invest in their own workflows in order to be successful in these types of modeling campaigns.

scholarly journals LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project

2020 ◽  
Vol 37 (3) ◽  
pp. 239-249 ◽  
Author(s):  
Pengfei Lin ◽  
Zhipeng Yu ◽  
Hailong Liu ◽  
Yongqiang Yu ◽  
Yiwen Li ◽  
...  
Keyword(s):  
Coupled Model ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Model Intercomparison ◽  
Surface Data ◽  
Intercomparison Project ◽  
System Bias ◽  
The Mean ◽  
Fully Coupled

Abstract The datasets of two Ocean Model Intercomparison Project (OMIP) simulation experiments from the LASG/IAP Climate Ocean Model, version 3 (LICOM3), forced by two different sets of atmospheric surface data, are described in this paper. The experiment forced by CORE-II (Co-ordinated Ocean–Ice Reference Experiments, Phase II) data (1948–2009) is called OMIP1, and that forced by JRA55-do (surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis) data (1958–2018) is called OMIP2. First, the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described. Second, the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation. We find that the mean states, interannual variabilities, and long-term linear trends can be reproduced well by the two experiments. The differences between the two datasets are also discussed. Finally, the usage of these data is described. These datasets are helpful toward understanding the origin system bias of the fully coupled model.

scholarly journals Understanding the CMIP3 Multimodel Ensemble

2011 ◽  
Vol 24 (16) ◽  
pp. 4529-4538 ◽  
Author(s):  
J. D. Annan ◽  
J. C. Hargreaves
Keyword(s):  
Coupled Model ◽  
Model Intercomparison ◽  
Ensemble Size ◽  
Multimodel Ensemble ◽  
Phase 3 ◽  
Climate Research ◽  
Intercomparison Project ◽  
The Mean ◽  
Main Factors ◽  
And Behavior

Abstract The Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble has been widely utilized for climate research and prediction, but the properties and behavior of the ensemble are not yet fully understood. Here, some investigations are undertaken into various aspects of the ensemble’s behavior, in particular focusing on the performance of the multimodel mean. This study presents an explanation of this phenomenon in the context of the statistically indistinguishable paradigm and also provides a quantitative analysis of the main factors that control how likely the mean is to outperform the models in the ensemble, both individually and collectively. The analyses lend further support to the usage of the paradigm of a statistically indistinguishable ensemble and indicate that the current ensemble size is too small to adequately sample the space from which the models are drawn.

scholarly journals Do CMIP models capture long-term observed annual precipitation trends?

2021 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
R. García-Herrera ◽  
D. Peña-Angulo ◽  
M. Tomas-Burguera ◽  
F. Domínguez-Castro ◽  
...  
Keyword(s):  
Global Assessment ◽  
Climate Model ◽  
Coupled Model ◽  
Annual Precipitation ◽  
Model Intercomparison ◽  
The World ◽  
Intercomparison Project ◽  
Using Data ◽  
Precipitation Trends

AbstractThis study provides a long-term (1891–2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible effects of including a well-resolved stratosphere on the model’s ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically significant differences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically significant model-observation differences on trends (1891–2014) are found at the zonal mean scale. The different model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no significant differences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.

scholarly journals A New End-to-End Workflow for the Community Earth System Model (version 2.0) for CMIP6

2020 ◽  
Author(s):  
Sheri Mickelson ◽  
Alice Bertini ◽  
Gary Strand ◽  
Kevin Paul ◽  
Eric Nienhouse ◽  
...  
Keyword(s):  
Coupled Model ◽  
System Model ◽  
Model Intercomparison ◽  
Phase 3 ◽  
Atmospheric Research ◽  
Previous Generation ◽  
Community Earth System Model ◽  
Intercomparison Project ◽  
Version 2.0 ◽  
New Generation

Abstract. The complexity of each Coupled Model Intercomparison Project grows with every new generation. The Phase 5 effort saw a large increase in the number of experiments that were performed and the number of variables that were requested compared to its previous generation, Phase 3. Many centers were not prepared for the large demand and this stressed the resources of several centers including at the National Center for Atmospheric Research. During Phase 5, we missed several deadlines and we struggled to get the data out to the community for analysis. In preparation for the current generation, Phase 6, we examined the weaknesses in our workflow and addressed the performance issues with new software tools. Through this investment, we were able to publish approximately six times the amount of data to the community compared to the volumes we produced in the previous generation and we were able to accomplish this within one-third of the time, providing an 18 times speedup. This paper discusses the improvements we have made to accomplish this success for Phase 6 and further improvements we hope to make for the next generation.

scholarly journals Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6

2021 ◽  
Vol 18 (13) ◽  
pp. 6760
Author(s):  
Isaac Kwesi Nooni ◽  
Daniel Fiifi T. Hagan ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Jiao Lu ◽  
...  
Keyword(s):  
Extreme Events ◽  
Coupled Model ◽  
Baseline Period ◽  
Model Intercomparison ◽  
Additional Information ◽  
Intercomparison Project ◽  
Key Drivers ◽  
Model Ensembles ◽  
Projected Changes ◽  
Near Future

The main goal of this study was to assess the interannual variations and spatial patterns of projected changes in simulated evapotranspiration (ET) in the 21st century over continental Africa based on the latest Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) provided by the France Centre National de Recherches Météorologiques (CNRM-CM) model in the Sixth Phase of Coupled Model Intercomparison Project (CMIP6) framework. The projected spatial and temporal changes were computed for three time slices: 2020–2039 (near future), 2040–2069 (mid-century), and 2080–2099 (end-of-the-century), relative to the baseline period (1995–2014). The results show that the spatial pattern of the projected ET was not uniform and varied across the climate region and under the SSP-RCPs scenarios. Although the trends varied, they were statistically significant for all SSP-RCPs. The SSP5-8.5 and SSP3-7.0 projected higher ET seasonality than SSP1-2.6 and SSP2-4.5. In general, we suggest the need for modelers and forecasters to pay more attention to changes in the simulated ET and their impact on extreme events. The findings provide useful information for water resources managers to develop specific measures to mitigate extreme events in the regions most affected by possible changes in the region’s climate. However, readers are advised to treat the results with caution as they are based on a single GCM model. Further research on multi-model ensembles (as more models’ outputs become available) and possible key drivers may provide additional information on CMIP6 ET projections in the region.

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