Early Eocene simulations with three different palaeogeographic conditions

Author(s):  
Zijian Zhang ◽  
Zhongshi Zhang ◽  
Zhengtang Guo

<p>The early Eocene is a warm period with a very high atmosphere CO<sub>2</sub> level in the Cenozoic. It  provides a good reference for our future climate under the Representative Concentration Pathway 8.5 scenario. Therefore, the early Eocene climate has received many attentions in  modeling studies, for example, the Deep-Time Model Intercomparison Project (DeepMIP). However, the early Eocene palaeogeographic conditions show remarkable contrasts to the present conditions. Meanwhile, there are a few different reconstructions for the early Eocene palaeogeography, which may cause further model spreads in simulating the early Eocene warm climate. Here, we present a series of experiments carried out with the NorESM1-F, under the framework of DeepMIP. In these experiments, we consider three different palaeogeographic reconstructions for the early Eocene. We also compare our simulations with climate proxy records, to validate which palaeogeographic reconstructions can reproduce simulations that agree better with the climate proxy records.</p>

2019 ◽  
Vol 12 (7) ◽  
pp. 3149-3206 ◽  
Author(s):  
Christopher J. Hollis ◽  
Tom Dunkley Jones ◽  
Eleni Anagnostou ◽  
Peter K. Bijl ◽  
Margot J. Cramwinckel ◽  
...  

Abstract. The early Eocene (56 to 48 million years ago) is inferred to have been the most recent time that Earth's atmospheric CO2 concentrations exceeded 1000 ppm. Global mean temperatures were also substantially warmer than those of the present day. As such, the study of early Eocene climate provides insight into how a super-warm Earth system behaves and offers an opportunity to evaluate climate models under conditions of high greenhouse gas forcing. The Deep Time Model Intercomparison Project (DeepMIP) is a systematic model–model and model–data intercomparison of three early Paleogene time slices: latest Paleocene, Paleocene–Eocene thermal maximum (PETM) and early Eocene climatic optimum (EECO). A previous article outlined the model experimental design for climate model simulations. In this article, we outline the methodologies to be used for the compilation and analysis of climate proxy data, primarily proxies for temperature and CO2. This paper establishes the protocols for a concerted and coordinated effort to compile the climate proxy records across a wide geographic range. The resulting climate “atlas” will be used to constrain and evaluate climate models for the three selected time intervals and provide insights into the mechanisms that control these warm climate states. We provide version 0.1 of this database, in anticipation that this will be expanded in subsequent publications.


2019 ◽  
Author(s):  
Christopher J. Hollis ◽  
Tom Dunkley Jones ◽  
Eleni Anagnostou ◽  
Peter K. Bijl ◽  
Margot J. Cramwinckel ◽  
...  

Abstract. The early Eocene (56 to 48 million years ago) is inferred to have been the most recent time that Earth's atmospheric CO2 concentrations exceeded 1000 ppm. Global mean temperatures were also substantially warmer than present day. As such, study of early Eocene climate provides insight into how a super-warm Earth system behaves and offers an opportunity to evaluate climate models under conditions of high greenhouse gas forcing. The Deep Time Model Intercomparison Project (DeepMIP) is a systematic model-model and model-data intercomparison of three early Paleogne time slices: latest Paleocene, Paleocene-Eocene thermal maximum and early Eocene climatic optimum. A previous article outlined the model experimental design for climate model simulations. In this article, we outline the methodologies to be used for the compilation and analysis of climate proxy data, primarily proxies for temperature and CO2. This paper establishes the protocols for a concerted and coordinated effort to compile the climate proxy records across a wide geographic range. The resulting climate atlas will be used to constrain and evaluate climate models for the three selected time intervals, and provide insights into the mechanisms that control these warm climate states. We provide version 0.1 of this database, in anticipation that this will be expanded in subsequent publications.


2014 ◽  
Vol 27 (2) ◽  
pp. 925-940 ◽  
Author(s):  
Katinka Bellomo ◽  
Amy C. Clement ◽  
Joel R. Norris ◽  
Brian J. Soden

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.


Author(s):  
Bian He ◽  
Xiaoqi Zhang ◽  
Anmin Duan ◽  
Qing Bao ◽  
Yimin Liu ◽  
...  

AbstractLarge-ensemble simulations of the atmosphere-only time-slice experiments for the Polar Amplification Model Intercomparison Project (PAMIP) were carried out by the model group of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L). Eight groups of experiments forced by different combinations of the sea surface temperature (SST) and sea ice concentration (SIC) for pre-industrial, present-day, and future conditions were performed and published. The time-lag method was used to generate the 100 ensemble members, with each member integrating from 1 April 2000 to 30 June 2001 and the first two months as the spin-up period. The basic model responses of the surface air temperature (SAT) and precipitation were documented. The results indicate that Arctic amplification is mainly caused by Arctic SIC forcing changes. The SAT responses to the Arctic SIC decrease alone show an obvious increase over high latitudes, which is similar to the results from the combined forcing of SST and SIC. However, the change in global precipitation is dominated by the changes in the global SST rather than SIC, partly because tropical precipitation is mainly driven by local SST changes. The uncertainty of the model responses was also investigated through the analysis of the large-ensemble members. The relative roles of SST and SIC, together with their combined influence on Arctic amplification, are also discussed. All of these model datasets will contribute to PAMIP multi-model analysis and improve the understanding of polar amplification.


Genetics ◽  
2000 ◽  
Vol 155 (4) ◽  
pp. 1991-2001 ◽  
Author(s):  
A García-Dorado ◽  
A Caballero

Abstract T. Mukai and co-workers in the late 1960s and O. Ohnishi in the 1970s carried out a series of experiments to obtain direct estimates of the average coefficient of dominance (h¯) of minor viability mutations in Drosophila melanogaster. The results of these experiments, although inconsistent, have been interpreted as indicating slight recessivity of deleterious mutations, with h¯≈0.4. Mukai obtained conflicting results depending on the type of heterozygotes used, some estimates suggesting overdominance and others partial dominance. Ohnishi's estimates, based on the ratio of heterozygous to homozygous viability declines, were more consistent, pointing to the above value. However, we have reanalyzed Ohnishi's data, estimating h¯ by the regression method, and obtained a much smaller estimate of ~0.1. This significant difference can be due partly to the different weighting implicit in the estimates, but we suggest that this is not the only explanation. We propose as a plausible hypothesis that a putative nonmutational decline in viability occurring in the first half of Ohnishi's experiment (affecting both homozygotes and heterozygotes) has biased upward the estimates from the ratio, while it would not bias the regression estimates. This hypothesis also explains the very high h¯≈0.7 observed in Ohnishi's high-viability chromosomes. By constructing a model of spontaneous mutations using parameters in the literature, we investigate the above possibility. The results indicate that a model of few mutations with moderately large effects and h¯≈0.2 is able to explain the observed estimates and the distributions of homozygous and heterozygous viabilities. Accounting for an expression of mutations in genotypes with the balancer chromosome Cy does not alter the conclusions qualitatively.


Author(s):  
Isaac Kwesi Nooni ◽  
Daniel Fiifi T. Hagan ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Jiao Lu ◽  
...  

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.


Author(s):  
Binghao Jia ◽  
Longhuan Wang ◽  
Yan Wang ◽  
Ruichao Li ◽  
Xin Luo ◽  
...  

AbstractThe datasets of the five Land-offline Model Intercomparison Project (LMIP) experiments using the Chinese Academy of Sciences Land Surface Model (CAS-LSM) of CAS Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3 (CAS FGOALS-g3) are presented in this study. These experiments were forced by five global meteorological forcing datasets, which contributed to the framework of the Land Surface Snow and Soil Moisture Model Intercomparison Project (LS3MIP) of CMIP6. These datasets have been released on the Earth System Grid Federation node. In this paper, the basic descriptions of the CAS-LSM and the five LMIP experiments are shown. The performance of the soil moisture, snow, and land-atmosphere energy fluxes was preliminarily validated using satellite-based observations. Results show that their mean states, spatial patterns, and seasonal variations can be reproduced well by the five LMIP simulations. It suggests that these datasets can be used to investigate the evolutionary mechanisms of the global water and energy cycles during the past century.


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