scholarly journals Low-Frequency North Atlantic Climate Variability in the Community Earth System Model Large Ensemble

2018 ◽  
Vol 31 (2) ◽  
pp. 787-813 ◽  
Author(s):  
Who M. Kim ◽  
Stephen Yeager ◽  
Ping Chang ◽  
Gokhan Danabasoglu
Keyword(s):  
Boundary Conditions ◽  
Time Scales ◽  
North Atlantic ◽  
Low Frequency ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Large Ensemble ◽  
Low Frequency Variability ◽  
Community Earth System Model

There is observational and modeling evidence that low-frequency variability in the North Atlantic has significant implications for the global climate, particularly for the climate of the Northern Hemisphere. This study explores the representation of low-frequency variability in the Atlantic region in historical large ensemble and preindustrial control simulations performed with the Community Earth System Model (CESM). Compared to available observational estimates, it is found that the simulated variability in Atlantic meridional overturning circulation (AMOC), North Atlantic sea surface temperature (NASST), and Sahel rainfall is underestimated on multidecadal time scales but comparable on interannual to decadal time scales. The weak multidecadal North Atlantic variability appears to be closely related to weaker-than-observed multidecadal variations in the simulated North Atlantic Oscillation (NAO), as the AMOC and consequent NASST variability is impacted, to a great degree, by the NAO. Possible reasons for this weak multidecadal NAO variability are explored with reference to solutions from two atmosphere-only simulations with different lower boundary conditions and vertical resolution. Both simulations consistently reveal weaker-than-observed multidecadal NAO variability despite more realistic boundary conditions and better resolved dynamics than coupled simulations. The authors thus conjecture that the weak multidecadal NAO variability in CESM is likely due to deficiencies in air–sea coupling, resulting from shortcomings in the atmospheric model or coupling details.

scholarly journals CNOP-P-Based Parameter Sensitivity Analysis for North Atlantic Oscillation in Community Earth System Model Using Intelligence Algorithms

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Bin Mu ◽  
Jing Li ◽  
Shijin Yuan ◽  
Xiaodan Luo ◽  
Guokun Dai
Keyword(s):  
Sensitivity Analysis ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Solar Irradiance ◽  
Total Solar Irradiance ◽  
Earth System Model ◽  
System Model ◽  
Model Parameters ◽  
Earth System ◽  
Community Earth System Model

Model error, which results from model parameters, can cause the nonnegligible uncertainty in the North Atlantic Oscillation (NAO) simulation. Conditional nonlinear optimal perturbation related to parameter (CNOP-P) is a powerful approach to investigate the range of uncertainty caused by model parameters under a specific constraint. In this paper, we adopt intelligence algorithms to implement the CNOP-P method and conduct the sensitivity analysis of parameter combinations for NAO events in the Community Earth System Model (CESM). Among 28 model parameters of the atmospheric component, the most sensitive parameter combination for the NAO + consists of parameter for deep convection (cldfrc_dp1), minimum relative humidity for low stable clouds (cldfrc_rhminl), and the total solar irradiance (solar_const). As for the NAO − , the parameter set that can trigger the largest variation of the NAO index (NAOI) is comprised of the constant for evaporation of precip (cldwat_conke), characteristic adjustment time scale (hkconv_cmftau), and the total solar irradiance (solar_const). The most prominent uncertainties of the NAOI ( Δ NAOI ) caused by these two combinations achieve 2.12 for NAO + and −2.72 for NAO − , respectively. In comparison, the maximum level of the NAOI variation resulting from single parameters reaches 1.45 for NAO + and −1.70 for NAO − . It is indicated that the nonlinear impact of multiple parameters would be more intense than the single parameter. These results present factors that are closely related to NAO events and also provide the direction of optimizing model parameters. Moreover, the intelligence algorithms adopted in this work are proved to be adequate to explore the nonlinear interaction of parameters on the model simulation.

The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability

2015 ◽  
Vol 96 (8) ◽  
pp. 1333-1349 ◽  
Author(s):  
J. E. Kay ◽  
C. Deser ◽  
A. Phillips ◽  
A. Mai ◽  
C. Hannay ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Model Error ◽  
Earth System Model ◽  
First Century ◽  
System Model ◽  
Earth System ◽  
Large Ensemble ◽  
Internal Climate Variability ◽  
Community Earth System Model

Abstract While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920–2100) 30 times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 1000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Early results demonstrate the substantial influence of internal climate variability on twentieth- to twenty-first-century climate trajectories. Global warming hiatus decades occur, similar to those recently observed. Internal climate variability alone can produce projection spread comparable to that in CMIP5. Scientists and stakeholders can use CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change.

scholarly journals Predicting Near-Term Changes in the Earth System: A Large Ensemble of Initialized Decadal Prediction Simulations Using the Community Earth System Model

2018 ◽  
Vol 99 (9) ◽  
pp. 1867-1886 ◽  
Author(s):  
S. G. Yeager ◽  
G. Danabasoglu ◽  
N. A. Rosenbloom ◽  
W. Strand ◽  
S. C. Bates ◽  
...  
Keyword(s):  
Earth System Model ◽  
Prediction Skill ◽  
System Model ◽  
Decadal Prediction ◽  
Earth System ◽  
Large Ensemble ◽  
Past Climate ◽  
Radiative Forcings ◽  
Community Earth System Model ◽  
Near Term

AbstractThe objective of near-term climate prediction is to improve our fore-knowledge, from years to a decade or more in advance, of impactful climate changes that can in general be attributed to a combination of internal and externally forced variability. Predictions initialized using observations of past climate states are tested by comparing their ability to reproduce past climate evolution with that of uninitialized simulations in which the same radiative forcings are applied. A new set of decadal prediction (DP) simulations has recently been completed using the Community Earth System Model (CESM) and is now available to the community. This new large-ensemble (LE) set (CESM-DPLE) is composed of historical simulations that are integrated forward for 10 years following initialization on 1 November of each year between 1954 and 2015. CESM-DPLE represents the “initialized” counterpart to the widely studied CESM Large Ensemble (CESM-LE); both simulation sets have 40-member ensembles, and they use identical model code and radiative forcings. Comparing CESM-DPLE to CESM-LE highlights the impacts of initialization on prediction skill and indicates that robust assessment and interpretation of DP skill may require much larger ensembles than current protocols recommend. CESM-DPLE exhibits significant and potentially useful prediction skill for a wide range of fields, regions, and time scales, and it shows widespread improvement over simpler benchmark forecasts as well as over a previous initialized system that was submitted to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The new DP system offers new capabilities that will be of interest to a broad community pursuing Earth system prediction research.

scholarly journals Simulations of the Mid-Pliocene Warm Period using the NASA/GISS ModelE2-R Earth System Model

2012 ◽  
Vol 5 (3) ◽  
pp. 2811-2842 ◽  
Author(s):  
M. A. Chandler ◽  
L. E. Sohl ◽  
J. A. Jonas ◽  
H. J. Dowsett
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Climate Model ◽  
Geographic Region ◽  
Earth System Model ◽  
Warm Period ◽  
System Model ◽  
Earth System ◽  
Intergovernmental Panel ◽  
Future Global Warming

Abstract. Climate reconstructions of the mid-Pliocene Warm Period (mPWP) bear many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change. In particular, marine and terrestrial paleoclimate data point to high latitude temperature amplification, with associated decreases in sea ice and land ice and altered vegetation distributions that show expansion of warmer climate biomes into higher latitudes. NASA GISS climate models have been used to study the Pliocene climate since the USGS PRISM project first identified that the mid-Pliocene North Atlantic sea surface temperatures were anomalously warm. Here we present the most recent simulations of the Pliocene using the AR5/CMIP5 version of the GISS Earth System Model known as ModelE2-R. These simulations constitute the NASA contribution to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. We provide discussion of features that show considerable improvement compared with simulations from previous versions of the NASA GISS models, improvement defined here as simulation results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene climate. In some regions even qualitative agreement between model results and paleodata are an improvement over past studies, but the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea in these new simulations is by far the most accurate portrayal ever of this key geographic region by the GISS climate model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterizations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.

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