Simulation of the observed climate extremes trends during 1901–2010 with INMCM5

2020 ◽  
Author(s):  
Maria Tarasevich ◽  
Evgeny Volodin
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Great Influence ◽  
Coupled Model ◽  
Climate Extremes ◽  
Reanalysis Data ◽  
Natural Systems ◽  
Weather Events ◽  
Intercomparison Project

<p>Extreme climate and weather events have a great influence on society and natural systems. That’s why it is important to be able to precisely simulate these events with the climate models. To asses the quality of such simulations 27 climate extremes indices were defined by ETCCDI. In the present work these indices are calculated for the 1901–2010 in order to estimate their trends.<br>Climate extremes trends are studied on the basis of ten historical runs with the up-to-date INM RAS climate model (INMCM5) under the scenario proposed for the Coupled Model Intercomparison Project Phase 6 (CMIP6). Developed by ECMWF ERA-20C and CERA-20C reanalyses are taken as observational data.<br>Trends obtained from the reanalysis data are compared with the simulation results of the INMCM5. The comparison shows that the simulated land-averaged climate extremes trends are in good agreement with the reanalysis data, but their spatial distributions differ significantly even between the reanalyses themselves.</p>

scholarly journals Defining Sudden Stratospheric Warming in Climate Models: Accounting for Biases in Model Climatologies

2017 ◽  
Vol 30 (14) ◽  
pp. 5529-5546 ◽  
Author(s):  
Junsu Kim ◽  
Seok-Woo Son ◽  
Edwin P. Gerber ◽  
Hyo-Seok Park
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Polar Vortex ◽  
Reanalysis Data ◽  
Cmip5 Models ◽  
Stratospheric Warming ◽  
Sudden Stratospheric Warming ◽  
Intercomparison Project ◽  
Wave Flux

A sudden stratospheric warming (SSW) is often defined as zonal-mean zonal wind reversal at 10 hPa and 60°N. This simple definition has been applied not only to the reanalysis data but also to climate model output. In the present study, it is shown that the application of this definition to models can be significantly influenced by model mean biases (i.e., more frequent SSWs appear to occur in models with a weaker climatological polar vortex). To overcome this deficiency, a tendency-based definition is proposed and applied to the multimodel datasets archived for phase 5 of the Coupled Model Intercomparison Project (CMIP5). In this definition, SSW-like events are defined by sufficiently strong vortex deceleration. This approach removes a linear relationship between SSW frequency and intensity of the climatological polar vortex in the CMIP5 models. The models’ SSW frequency instead becomes significantly correlated with the climatological upward wave flux at 100 hPa, a measure of interaction between the troposphere and stratosphere. Lower stratospheric wave activity and downward propagation of stratospheric anomalies to the troposphere are also reasonably well captured. However, in both definitions, the high-top models generally exhibit more frequent SSWs than the low-top models. Moreover, a hint of more frequent SSWs in a warm climate is found in both definitions.

How to combine climate models and observations in event attribution?

2021 ◽  
Author(s):  
Yoann Robin ◽  
Aurélien Ribes
Keyword(s):  
Bayesian Method ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Model Data ◽  
Human Influence ◽  
Scale Parameters ◽  
Event Attribution ◽  
Intercomparison Project ◽  
Climate Model Simulations

<p>We describe a statistical method to derive event attribution diagnoses combining climate model simulations and observations. We fit nonstationary Generalized Extreme Value (GEV) distributions to extremely hot temperatures from an ensemble of Coupled Model Intercomparison Project phase 5 (CMIP)<br>models. In order to select a common statistical model, we discuss which GEV parameters have to be nonstationary and which do not. Our tests suggest that the location and scale parameters of GEV distributions should be considered nonstationary. Then, a multimodel distribution is constructed and constrained by observations using a Bayesian method. This new method is applied to the July 2019 French heatwave. Our results show that<br>both the probability and the intensity of that event have increased significantly in response to human influence.<br>Remarkably, we find that the heat wave considered might not have been possible without climate change. Our<br>results also suggest that combining model data with observations can improve the description of hot temperature<br>distribution.</p>

scholarly journals A community diagnostic tool for Chemistry Climate Model Validation

2012 ◽  
Vol 5 (2) ◽  
pp. 1229-1261
Author(s):  
A. Gettelman ◽  
V. Eyring ◽  
C. Fischer ◽  
H. Shiona ◽  
I. Cionni ◽  
...  
Keyword(s):  
Model Validation ◽  
Climate Models ◽  
Performance Metrics ◽  
Climate Model ◽  
Model Development ◽  
Coupled Model ◽  
Technical Note ◽  
Complex Evaluation ◽  
System User ◽  
Intercomparison Project

Abstract. This technical note presents an overview of the Chemistry-Climate Model Validation Diagnostic (CCMVal-Diag) tool for model evaluation. The CCMVal-Diag tool is a flexible and extensible open source package that facilitates the complex evaluation of global models. Models can be compared to other models, ensemble members (simulations with the same model), and/or many types of observations. The tool can also compute quantitative performance metrics. The initial construction and application is to coupled Chemistry-Climate Models (CCMs) participating in CCMVal, but the evaluation of climate models that submitted output to the Coupled Model Intercomparison Project (CMIP) is also possible. The package has been used to assist with analysis of simulations for the 2010 WMO/UNEP Scientific Ozone Assessment and the SPARC Report on the Evaluation of CCMs. The CCMVal-Diag tool is described and examples of how it functions are presented, along with links to detailed descriptions, instructions and source code. The CCMVal-Diag tool is supporting model development as well as quantifying model improvements, both for different versions of individual models and for different generations of community-wide collections of models used in international assessments. The code allows further extensions by different users for different applications and types, e.g. to other components of the Earth System. User modifications are encouraged and easy to perform with a minimum of coding.

scholarly journals Global exposure to flooding from the new CMIP6 climate model projections

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yukiko Hirabayashi ◽  
Masahiro Tanoue ◽  
Orie Sasaki ◽  
Xudong Zhou ◽  
Dai Yamazaki
Keyword(s):  
Spatial Patterns ◽  
Flood Risk ◽  
Climate Models ◽  
Climate Model ◽  
Model Development ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Internal Climate Variability ◽  
Intercomparison Project ◽  
New Generation

AbstractEstimates of future flood risk rely on projections from climate models. The relatively few climate models used to analyze future flood risk cannot easily quantify of their associated uncertainties. In this study, we demonstrated that the projected fluvial flood changes estimated by a new generation of climate models, the collectively known as Coupled Model Intercomparison Project Phase 6 (CMIP6), are similar to those estimated by CMIP5. The spatial patterns of the multi-model median signs of change (+ or −) were also very consistent, implying greater confidence in the projections. The model spread changed little over the course of model development, suggesting irreducibility of the model spread due to internal climate variability, and the consistent projections of models from the same institute suggest the potential to reduce uncertainties caused by model differences. Potential global exposure to flooding is projected to be proportional to the degree of warming, and a greater threat is anticipated as populations increase, demonstrating the need for immediate decisions.

scholarly journals The representation of Northern Hemisphere blocking in current global climate models

2020 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Development ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
The Pacific ◽  
Intercomparison Project ◽  
Blocking Index

Abstract. Global Climate Models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations, and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and in winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 32 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 19 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 km to 20 km grid spacing, in the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer, and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

scholarly journals Northern Hemisphere Snow-Cover Trends (1967–2018): A Comparison between Climate Models and Observations

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 135 ◽  
Author(s):  
◽  
◽  
◽  
◽  
◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Poor Performance ◽  
Four Seasons ◽  
Intercomparison Project ◽  
Autumn And Winter

Observed changes in Northern Hemisphere snow cover from satellite records were compared to those predicted by all available Coupled Model Intercomparison Project Phase 5 (“CMIP5”) climate models over the duration of the satellite’s records, i.e., 1967–2018. A total of 196 climate model runs were analyzed (taken from 24 climate models). Separate analyses were conducted for the annual averages and for each of the seasons (winter, spring, summer, and autumn/fall). A longer record (1922–2018) for the spring season which combines ground-based measurements with satellite measurements was also compared to the model outputs. The climate models were found to poorly explain the observed trends. While the models suggest snow cover should have steadily decreased for all four seasons, only spring and summer exhibited a long-term decrease, and the pattern of the observed decreases for these seasons was quite different from the modelled predictions. Moreover, the observed trends for autumn and winter suggest a long-term increase, although these trends were not statistically significant. Possible explanations for the poor performance of the climate models are discussed.

scholarly journals Set-up of the PMIP3 paleoclimate experiments conducted using an Earth system model, MIROC-ESM

2013 ◽  
Vol 6 (3) ◽  
pp. 819-836 ◽  
Author(s):  
T. Sueyoshi ◽  
R. Ohgaito ◽  
A. Yamamoto ◽  
M. O. Chikamoto ◽  
T. Hajima ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Volcanic Eruptions ◽  
Earth System ◽  
Good Test ◽  
Effective Measure ◽  
Intercomparison Project

Abstract. Paleoclimate experiments using contemporary climate models are an effective measure to evaluate climate models. In recent years, Earth system models (ESMs) were developed to investigate carbon cycle climate feedbacks, as well as to project the future climate. Paleoclimate events can be suitable benchmarks to evaluate ESMs. The variation in aerosols associated with the volcanic eruptions provide a clear signal in forcing, which can be a good test to check the response of a climate model to the radiation changes. The variations in atmospheric CO2 level or changes in ice sheet extent can be used for evaluation as well. Here we present implementations of the paleoclimate experiments proposed by the Coupled Model Intercomparison Project phase 5/Paleoclimate Modelling Intercomparison Project phase 3 (CMIP5/PMIP3) using MIROC-ESM, an ESM based on the global climate model MIROC (Model for Interdisciplinary Research on Climate). In this paper, experimental settings and spin-up procedures of the mid-Holocene, the Last Glacial Maximum, and the Last Millennium experiments are explained. The first two experiments are time slice experiments and the last one is a transient experiment. The complexity of the model requires various steps to correctly configure the experiments. Several basic outputs are also shown.

scholarly journals A community diagnostic tool for chemistry climate model validation

2012 ◽  
Vol 5 (5) ◽  
pp. 1061-1073 ◽  
Author(s):  
A. Gettelman ◽  
V. Eyring ◽  
C. Fischer ◽  
H. Shiona ◽  
I. Cionni ◽  
...  
Keyword(s):  
Model Validation ◽  
Climate Models ◽  
Climate Model ◽  
Model Development ◽  
Coupled Model ◽  
Technical Note ◽  
The Earth ◽  
Complex Evaluation ◽  
System User ◽  
Intercomparison Project

Abstract. This technical note presents an overview of the Chemistry-Climate Model Validation Diagnostic (CCMVal-Diag) tool for model evaluation. The CCMVal-Diag tool is a flexible and extensible open source package that facilitates the complex evaluation of global models. Models can be compared to other models, ensemble members (simulations with the same model), and/or many types of observations. The initial construction and application is to coupled chemistry-climate models (CCMs) participating in CCMVal, but the evaluation of climate models that submitted output to the Coupled Model Intercomparison Project (CMIP) is also possible. The package has been used to assist with analysis of simulations for the 2010 WMO/UNEP Scientific Ozone Assessment and the SPARC Report on the Evaluation of CCMs. The CCMVal-Diag tool is described and examples of how it functions are presented, along with links to detailed descriptions, instructions and source code. The CCMVal-Diag tool supports model development as well as quantifies model changes, both for different versions of individual models and for different generations of community-wide collections of models used in international assessments. The code allows further extensions by different users for different applications and types, e.g. to other components of the Earth system. User modifications are encouraged and easy to perform with minimum coding.

scholarly journals ASSESSMENT OF THE QUALITY OF SIMULATION OF CHANGES OF THE DOWNWELLING SHORTWAVE RADIATION IN THE SEVASTOPOL REGION USING THE CMIP6 MODELS

2021 ◽  
pp. 31-37
Author(s):  
О.Yu. Sukhonos ◽  
◽  
А.S. Lubkov ◽  
Е.N. Voskresenskaya ◽  
◽  
...  
Keyword(s):  
Climate Changes ◽  
Climate Models ◽  
Linear Trend ◽  
Coupled Model ◽  
Statistical Characteristics ◽  
Shortwave Radiation ◽  
Energy Potential ◽  
Intercomparison Project ◽  
Climatic Characteristic

Using the data of the Coupled Model Intercomparison Project 6 (CMIP6), the quality of the simulation of the observed climate changes of downwelling shortwave radiation in the Sevastopol region for the period 1983–2012 is assessed. It is shown that the average values of the considered characteristics of solar resources according to the data of climate models are, in general, higher than according to the ob-servational data, whereas the values of the standard deviation are lower. The analysis of linear trends of the downwelling shortwave radiation show that most climate models from the CMIP6 project correctly simulate the process up to the sign of the linear trend. Using a number of statistical characteristics, mod-els have been determined that best simulate the analyzed climatic characteristic and will be suitable for assessing future changes in the solar energy potential in the Sevastopol region.

scholarly journals Projected changes in persistent extreme summer weather events: The role of quasi-resonant amplification

2018 ◽  
Vol 4 (10) ◽  
pp. eaat3272 ◽  
Author(s):  
Michael E. Mann ◽  
Stefan Rahmstorf ◽  
Kai Kornhuber ◽  
Byron A. Steinman ◽  
Sonya K. Miller ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
High Amplitude ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Anthropogenic Aerosols ◽  
Pronounced Increase ◽  
Weather Events

Persistent episodes of extreme weather in the Northern Hemisphere summer have been associated with high-amplitude quasi-stationary atmospheric Rossby waves, with zonal wave numbers 6 to 8 resulting from the phenomenon of quasi-resonant amplification (QRA). A fingerprint for the occurrence of QRA can be defined in terms of the zonally averaged surface temperature field. Examining state-of-the-art [Coupled Model Intercomparison Project Phase 5 (CMIP5)] climate model projections, we find that QRA events are likely to increase by ~50% this century under business-as-usual carbon emissions, but there is considerable variation among climate models. Some predict a near tripling of QRA events by the end of the century, while others predict a potential decrease. Models with amplified Arctic warming yield the most pronounced increase in QRA events. The projections are strongly dependent on assumptions regarding the nature of changes in radiative forcing associated with anthropogenic aerosols over the next century. One implication of our findings is that a reduction in midlatitude aerosol loading could actually lead to Arctic de-amplification this century, ameliorating potential increases in persistent extreme weather events.

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