New Approach Based on Termite's Hill Building for Prediction of Successful Simulations in Climate Models

2017 ◽  
Vol 8 (3) ◽  
pp. 43-60 ◽  
Author(s):  
Mohamed Elhadi Rahmani ◽  
Abdelmalek Amine ◽  
Reda Mohamed Hamou
Keyword(s):  
Climate Models ◽  
System Model ◽  
Training Set ◽  
Intergovernmental Panel ◽  
Test Set ◽  
Climate System Model ◽  
New Approach ◽  
Building Behavior ◽  
A New Technique ◽  
Parallel Ocean Program

Quantitative analysis of the failures and crashes in simulation of climate models can yield useful insights to better understanding and improvement of the models results using Intergovernmental Panel on Climate Change (IPCC) class. In this paper, the authors propose a new technique inspired by termite's hill building behavior to analyze a series of simulation in climate models and predict which one was succeeded within the Parallel Ocean Program (POP2) component of the community Climate System Model (CCSM4). The authors' approach is a distance based approach used to predict the success of the values of 18 POP2 parameters. And in order to predict better results, they used for each experiment one of the studies as a training set and two as a test set, then they used two of the studies as a training set and one as a test set. Results of classification were very satisfactory (Accuracy > 0.87). This paper gives a very useful method to quantify, predict, and understand simulation success in climate models.

New Approach Based on Termite's Hill Building for Prediction of Successful Simulations in Climate Models

2018 ◽  
pp. 325-344
Author(s):  
Mohamed Elhadi Rahmani ◽  
Abdelmalek Amine ◽  
Reda Mohamed Hamou
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Training Set ◽  
Intergovernmental Panel ◽  
Test Set ◽  
Climate System Model ◽  
New Approach ◽  
Building Behavior ◽  
A New Technique ◽  
Parallel Ocean Program

Quantitative analysis of the failures and crashes in simulation of climate models can yield useful insights to better understanding and improvement of the models results using Intergovernmental Panel on Climate Change (IPCC) class. In this paper, the authors propose a new technique inspired by termite's hill building behavior to analyze a series of simulation in climate models and predict which one was succeeded within the Parallel Ocean Program (POP2) component of the community Climate System Model (CCSM4). The authors' approach is a distance based approach used to predict the success of the values of 18 POP2 parameters. And in order to predict better results, they used for each experiment one of the studies as a training set and two as a test set, then they used two of the studies as a training set and one as a test set. Results of classification were very satisfactory (Accuracy > 0.87). This paper gives a very useful method to quantify, predict, and understand simulation success in climate models.

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.

scholarly journals Evaluation of CMIP5 Global Climate Models over the Volta Basin: Precipitation

2018 ◽  
Vol 2018 ◽  
pp. 1-24 ◽  
Author(s):  
Jacob Agyekum ◽  
Thompson Annor ◽  
Benjamin Lamptey ◽  
Emmannuel Quansah ◽  
Richard Yao Kuma Agyeman
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Earth System Model ◽  
Global Climate Models ◽  
System Model ◽  
Earth System ◽  
Climate System Model ◽  
Model Version ◽  
Volta Basin ◽  
Ensemble Mean

A selected number of global climate models (GCMs) from the fifth Coupled Model Intercomparison Project (CMIP5) were evaluated over the Volta Basin for precipitation. Biases in models were computed by taking the differences between the averages over the period (1950–2004) of the models and the observation, normalized by the average of the observed for the annual and seasonal timescales. The Community Earth System Model, version 1-Biogeochemistry (CESM1-BGC), the Community Climate System Model Version 4 (CCSM4), the Max Planck Institute Earth System Model, Medium Range (MPI-ESM-MR), the Norwegian Earth System Model (NorESM1-M), and the multimodel ensemble mean were able to simulate the observed climatological mean of the annual total precipitation well (average biases of 1.9% to 7.5%) and hence were selected for the seasonal and monthly timescales. Overall, all the models (CESM1-BGC, CCSM4, MPI-ESM-MR, and NorESM1-M) scored relatively low for correlation (<0.5) but simulated the observed temporal variability differently ranging from 1.0 to 3.0 for the seasonal total. For the annual cycle of the monthly total, the CESM1-BGC, the MPI-ESM-MR, and the NorESM1-M were able to simulate the peak of the observed rainy season well in the Soudano-Sahel, the Sahel, and the entire basin, respectively, while all the models had difficulty in simulating the bimodal pattern of the Guinea Coast. The ensemble mean shows high performance compared to the individual models in various timescales.

scholarly journals On the Usage of Spectral and Broadband Satellite Instrument Measurements to Differentiate Climate Models with Different Cloud Feedback Strengths

2013 ◽  
Vol 26 (17) ◽  
pp. 6561-6574 ◽  
Author(s):  
Daniel R. Feldman ◽  
Daniel M. Coleman ◽  
William D. Collins
Keyword(s):  
Near Infrared ◽  
Climate Models ◽  
Longwave Radiation ◽  
Cloud Feedback ◽  
Climate System ◽  
Spectral Radiance ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Cloud Feedbacks ◽  
The Difference

Abstract Top-of-atmosphere radiometric signals associated with different high- and low-cloud–radiative feedbacks have been examined through the use of an observing system simulation experiment (OSSE). The OSSE simulates variations in the spectrally resolved and spectrally integrated signals that are due to a range of plausible feedbacks of the climate system when forced with CO2 concentrations that increase at 1% yr−1. This initial version of the OSSE is based on the Community Climate System Model, version 3 (CCSM3), and exploits the fact that CCSM3 exhibits different cloud feedback strengths for different model horizontal resolutions. In addition to the conventional broadband shortwave albedos and outgoing longwave fluxes, a dataset of shortwave spectral reflectance and longwave spectral radiance has been created. These data have been analyzed to determine simulated satellite instrument signals of poorly constrained cloud feedbacks for three plausible realizations of Earth's climate system produced by CCSM3. These data have been analyzed to estimate the observational record length of albedo, outgoing longwave radiation, shortwave reflectance, or longwave radiance required to differentiate these dissimilar Earth system realizations. Shortwave spectral measurements in visible and near-infrared water vapor overtone lines are best suited to differentiate model results, and a 33% difference in shortwave–cloud feedbacks can be detected with 20 years of continuous measurements. Nevertheless, at most latitudes and with most wavelengths, the difference detection time is more than 30 years. This suggests that observing systems of sufficiently stable calibration would be useful in addressing the contribution of low clouds to the spread of climate sensitivities currently exhibited by the models that report to the Intergovernmental Panel on Climate Change (IPCC).

scholarly journals Temporal- and Spatial-Scale Dependence of Three CMIP3 Climate Models in Simulating the Surface Temperature Trend in the Twentieth Century

2012 ◽  
Vol 25 (7) ◽  
pp. 2456-2470 ◽  
Author(s):  
Koichi Sakaguchi ◽  
Xubin Zeng ◽  
Michael A. Brunke
Keyword(s):  
Twentieth Century ◽  
Climate Models ◽  
Global Climate ◽  
Time Windows ◽  
Scale Dependence ◽  
Global Climate Models ◽  
System Model ◽  
Temporal Scales ◽  
Climate System Model ◽  
Linear Trends

Abstract Motivated by increasing interests in regional- and decadal-scale climate predictions, this study systematically analyzed the spatial- and temporal-scale dependence of the prediction skill of global climate models in surface air temperature (SAT) change in the twentieth century. The linear trends of annual mean SAT over moving time windows (running linear trends) from two observational datasets and simulations by three global climate models [Community Climate System Model, version 3.0 (CCSM3.0), Climate Model, version 2.0 (CM2.0), and Model E-H] that participated in CMIP3 are compared over several temporal (10-, 20-, 30-, 40-, and 50-yr trends) and spatial (5° × 5°, 10° × 10°, 15° × 15°, 20° × 20°, 30° × 30°, 30° latitudinal bands, hemispheric, and global) scales. The distribution of root-mean-square error is improved with increasing spatial and temporal scales, approaching the observational uncertainty range at the largest scales. Linear correlation shows a similar tendency, but the limited observational length does not provide statistical significance over the longer temporal scales. The comparison of RMSE to climatology and a Monte Carlo test using preindustrial control simulations suggest that the multimodel ensemble mean is able to reproduce robust climate signals at 30° zonal mean or larger spatial scales, while correlation requires hemispherical or global mean for the twentieth-century simulations. Persistent lower performance is observed over the northern high latitudes and the North Atlantic southeast of Greenland. Although several caveats exist for the metrics used in this study, the analyses across scales and/or over running time windows can be taken as one of the approaches for climate system model evaluations.

scholarly journals Bayesian Design and Analysis for Superensemble-Based Climate Forecasting

2008 ◽  
Vol 21 (9) ◽  
pp. 1891-1910 ◽  
Author(s):  
L. Mark Berliner ◽  
Yongku Kim
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
Climate System ◽  
System Model ◽  
Climate System Model ◽  
Bayesian Hierarchical ◽  
Climate Forecasting ◽  
Forecasting Analysis ◽  
States Of Nature

Abstract The authors develop statistical data models to combine ensembles from multiple climate models in a fashion that accounts for uncertainty. This formulation enables treatment of model specific means, biases, and covariance matrices of the ensembles. In addition, the authors model the uncertainty in using computer model results to estimate true states of nature. Based on these models and principles of decision making in the presence of uncertainty, this paper poses the problem of superensemble experimental design in a quantitative fashion. Simple examples of the resulting optimal designs are presented. The authors also provide a Bayesian climate modeling and forecasting analysis. The climate variables of interest are Northern and Southern Hemispheric monthly averaged surface temperatures. A Bayesian hierarchical model for these quantities is constructed, including time-varying parameters that are modeled as random variables with distributions depending in part on atmospheric CO2 levels. This allows the authors to do Bayesian forecasting of temperatures under different Special Report on Emissions Scenarios (SRES). These forecasts are based on Bayesian posterior distributions of the unknowns conditional on observational data for 1882–2001 and climate system model output for 2002–97. The latter dataset is a small superensemble from the Parallel Climate Model (PCM) and the Community Climate System Model (CCSM). After summarizing the results, the paper concludes with discussion of potential generalizations of the authors’ strategies.

scholarly journals Response to Increasing Southern Hemisphere Winds in CCSM4

2011 ◽  
Vol 24 (19) ◽  
pp. 4992-4998 ◽  
Author(s):  
Peter R. Gent ◽  
Gokhan Danabasoglu
Keyword(s):  
Southern Hemisphere ◽  
Variable Coefficient ◽  
Climate Models ◽  
Climate Model ◽  
System Model ◽  
Climate System Model ◽  
Coarse Resolution ◽  
Ocean Response ◽  
Ocean Models ◽  
Eddy Parameterization

Results from two perturbation experiments using the Community Climate System Model version 4 where the Southern Hemisphere zonal wind stress is increased are described. It is shown that the ocean response is in accord with experiments using much-higher-resolution ocean models that do not use an eddy parameterization. The key to obtaining an appropriate response in the coarse-resolution climate model is to specify a variable coefficient in the Gent and McWilliams eddy parameterization, rather than a constant value. This result contrasts with several recent papers that have suggested that coarse-resolution climate models cannot obtain an appropriate response.

scholarly journals Failure analysis of parameter-induced simulation crashes in climate models

2013 ◽  
Vol 6 (4) ◽  
pp. 1157-1171 ◽  
Author(s):  
D. D. Lucas ◽  
R. Klein ◽  
J. Tannahill ◽  
D. Ivanova ◽  
S. Brandon ◽  
...  
Keyword(s):  
Climate Models ◽  
Ocean Model ◽  
Support Vector ◽  
Parameter Uncertainties ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Climate Simulations ◽  
Class Climate ◽  
Predicted Model ◽  
Parameter Values

Abstract. Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

scholarly journals A regional atmosphere-ocean climate system model (CCLMv5.0clm7-NEMOv3.3-NEMOv3.6) over Europe including three marginal seas: on its stability and performance

2019 ◽  
Author(s):  
Cristina Primo ◽  
Fanni D. Kelemen ◽  
Hendrik Feldmann ◽  
Bodo Ahrens
Keyword(s):  
20Th Century ◽  
Extreme Events ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled System ◽  
Climate System ◽  
Added Value ◽  
System Model ◽  
Climate System Model ◽  
Marginal Seas

Abstract. The frequency of extreme events has changed, having a direct impact on human lives. Regional climate models help us to predict these regional climate changes. This work presents an atmosphere-ocean coupled regional climate system model (RCSM, with the atmospheric component COSMO-CLM and the ocean component NEMO) over the European domain, including three marginal seas: the Mediterranean, the North and the Baltic Seas. To test the model, we evaluate a simulation of more than one hundred years (1900–2009) with a spatial grid resolution of about 25 km. The simulation was nested into a coupled global simulation with the model MPI-ESM, whose ocean temperature and salinity was nudged to an MPI-ESM ocean-ice component forced with the 20th Century Reanalysis (20CR). The evaluation shows the robustness of the RCSM and discusses the added value by the coupled marginal seas over an atmosphere-only simulation. The coupled system runs stable for the complete 20th century and provides a better representation of extreme temperatures compared to the atmosphere-only model. The produced long-term dataset will allow an improved study of extreme events, helping us to better understand the processes leading to meteorological and climate extremes and their prediction.

scholarly journals Regional and global climate for the mid-Pliocene using CCSM4 and PlioMIP2 boundary conditions

2017 ◽  
Author(s):  
Deepak Chandan ◽  
W. Richard Peltier
Keyword(s):  
Boundary Conditions ◽  
Climate Models ◽  
Global Climate ◽  
Phase 1 ◽  
System Model ◽  
High Latitudes ◽  
Climate System Model ◽  
Intercomparison Project ◽  
Proxy Reconstructions ◽  
Selection Of

Abstract. The Pliocene Model Intercomparison Project, Phase 2 (PlioMIP2) is an international collaboration to simulate the climate of the mid-Pliocene interglacial, marine isotope stage KM5c (3.205 Mya), using a wide selection of climate models with the objective of understanding the nature of the warming that is known to have occurred during the broader mid-Pliocene warm period. PlioMIP2 builds upon the successes of PlioMIP by shifting focus onto a specific interglacial and by using a revised set of geographic and orbital boundary conditions. In this paper, we present the details of the mid-Pliocene simulations that we have performed with the Community Climate System Model version 4 (CCSM4), and the enhanced variant of the PlioMIP2 boundary conditions, and discuss the simulated climatology through comparisons to our control simulations, and to proxy reconstructions of the climate of the mid-Pliocene. With the new boundary conditions, the CCSM4 model simulates a mid-Pliocene which is more than twice as warm as that with the boundary conditions used for PlioMIP Phase 1. The warming is more enhanced near the high-latitudes which is where most of the changes to the boundary conditions have been made. The elevated warming in the high-latitudes leads to a better match of the simulated climatology to proxy based reconstructions than what was possible with the previous version of the boundary conditions.

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