scholarly journals ENSO Asymmetry in CMIP5 Models

2014 ◽  
Vol 27 (11) ◽  
pp. 4070-4093 ◽  
Author(s):  
Tao Zhang ◽  
De-Zheng Sun
Keyword(s):  
Coupled Model ◽  
La Niña ◽  
Eastern Pacific ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Coupled Models ◽  
Zonal Winds ◽  
La Nina ◽  
Enso Asymmetry ◽  
Intercomparison Project

Abstract The El Niño–La Niña asymmetry is evaluated in 14 coupled models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The results show that an underestimate of ENSO asymmetry, a common problem noted in CMIP3 models, remains a common problem in CMIP5 coupled models. The weaker ENSO asymmetry in the models primarily results from a weaker SST warm anomaly over the eastern Pacific and a westward shift of the center of the anomaly. In contrast, SST anomalies for the La Niña phase are close to observations. Corresponding Atmospheric Model Intercomparison Project (AMIP) runs are analyzed to understand the causes of the underestimate of ENSO asymmetry in coupled models. The analysis reveals that during the warm phase, precipitation anomalies are weaker over the eastern Pacific, and westerly wind anomalies are confined more to the west in most models. The time-mean zonal winds are stronger over the equatorial central and eastern Pacific for most models. Wind-forced ocean GCM experiments suggest that the stronger time-mean zonal winds and weaker asymmetry in the interannual anomalies of the zonal winds in AMIP models can both be a contributing factor to a weaker ENSO asymmetry in the corresponding coupled models, but the former appears to be a more fundamental factor, possibly through its impact on the mean state. The study suggests that the underestimate of ENSO asymmetry in the CMIP5 coupled models is at least in part of atmospheric origin.

El Niño–La Niña Asymmetry in the Coupled Model Intercomparison Project Simulations*

2005 ◽  
Vol 18 (14) ◽  
pp. 2617-2627 ◽  
Author(s):  
Soon-Il An ◽  
Yoo-Geun Ham ◽  
Jong-Seong Kug ◽  
Fei-Fei Jin ◽  
In-Sik Kang
Keyword(s):  
El Niño ◽  
El Nino ◽  
Coupled Model ◽  
La Niña ◽  
Model Intercomparison ◽  
Decadal Change ◽  
Tropical Eastern Pacific ◽  
Enso Events ◽  
La Nina ◽  
Intercomparison Project

Abstract The El Niño–La Niña asymmetry was estimated in the 10 different models participating in the Coupled Model Intercomparison Project (CMIP). Large differences in the “asymmetricity” (a variance-weighted skewness) of SST anomalies are found between models and observations. Most of the coupled models underestimate the nonlinearity and only a few exhibit the positively skewed SST anomalies over the tropical eastern Pacific as seen in the observation. A significant association between the nonlinear dynamical heating (NDH) and asymmetricity in the model–ENSO indices is found, inferring that asymmetricity is caused mainly by NDH. Among the 10 models, one coupled GCM simulates the asymmetricity of the tropical SST realistically, and its simulation manifests a strong relationship between the intensity and the propagating feature of ENSO—the strong ENSO events moving eastward and the weak ENSO events moving westward—which is consistent with the observation. Interestingly, the coupled general circulation models, of which the ocean model is based on the one used by Bryan and Cox, commonly showed the reasonably positive skewed ENSO. The decadal changes in the skewness, variance, and NDH of the model-simulated ENSO are also observed. These three quantities over the tropical eastern Pacific are significantly correlated to each other, indicating that the decadal change in ENSO variability is closely related to the nonlinear process of ENSO. It is also found that these decadal changes in ENSO variability are related to the decadal variation in the tropical Pacific SST, implying that the decadal change in the El Niño–La Niña asymmetry could manifest itself as a rectified change in the background state.

scholarly journals Impacts of Atmospheric Processes on ENSO Asymmetry: A Comparison between CESM1 and CCSM4

2017 ◽  
Vol 30 (23) ◽  
pp. 9743-9762 ◽  
Author(s):  
Tao Zhang ◽  
Xiaolu Shao ◽  
Shuanglin Li
Keyword(s):  
Interannual Variability ◽  
La Niña ◽  
Cold Bias ◽  
Coupled Models ◽  
Easterly Wind ◽  
Zonal Winds ◽  
La Nina ◽  
Enso Asymmetry ◽  
Precipitation Anomalies ◽  
Sst Anomaly

An evaluation of El Niño–La Niña asymmetry is conducted in the two recent NCAR coupled models (CCSM4 and CESM1) sharing the same ocean component. Results show that two coupled models generally underestimate observed ENSO asymmetry, mainly owing to an overestimate of the cold SST anomaly during the La Niña phase. The weaker ENSO asymmetry corresponds to a cold bias in mean SST climatology that is more severe in CESM1 than in CCSM4, despite a better performance in simulating ENSO asymmetry in the former. Corresponding AMIP (CAM4 and CAM5) runs are examined to probe the origin of the weaker ENSO asymmetry in coupled models. The analysis reveals a stronger time mean zonal wind in AMIP models, favoring a cold bias in mean SST. The bias of the stronger mean wind, associated with changes in mean precipitation, is more significant in CAM5 than in CAM4. The simulated skewness of the interannual variability of zonal winds is weaker than observations but somewhat improved in CAM5 compared to CAM4, primarily resulting from a more westward shift of easterly wind anomalies tied to the displacement of precipitation anomalies during the cold phase. Wind-forced ocean GCM experiments confirm that the bias in AMIP model winds can weaken ENSO asymmetry, with the contribution from the wind interannual variability being larger than from the mean winds. This demonstrates that the bias in ENSO asymmetry in coupled models can be traced back to the bias in the stand-alone atmosphere models to a large extent. The results pinpoint a pathway to reduce the bias in ENSO asymmetry in coupled models.

scholarly journals Intercomparison of temperature trends in IPCC CMIP5 simulations with observations, reanalyses and CMIP3 models

2013 ◽  
Vol 6 (5) ◽  
pp. 1705-1714 ◽  
Author(s):  
J. Xu ◽  
L. Zhao ◽  
Keyword(s):  
Coupled Model ◽  
Temperature Trend ◽  
The Arctic ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Model Simulations ◽  
Temperature Trends ◽  
Intercomparison Project ◽  
Stratospheric Cooling ◽  
The Tropics

Abstract. On the basis of the fifth Coupled Model Intercomparison Project (CMIP5) and the climate model simulations covering 1979 through 2005, the temperature trends and their uncertainties have been examined to note the similarities or differences compared to the radiosonde observations, reanalyses and the third Coupled Model Intercomparison Project (CMIP3) simulations. The results show noticeable discrepancies for the estimated temperature trends in the four data groups (radiosonde, reanalysis, CMIP3 and CMIP5), although similarities can be observed. Compared to the CMIP3 model simulations, the simulations in some of the CMIP5 models were improved. The CMIP5 models displayed a negative temperature trend in the stratosphere closer to the strong negative trend seen in the observations. However, the positive tropospheric trend in the tropics is overestimated by the CMIP5 models relative to CMIP3 models. While some of the models produce temperature trend patterns more highly correlated with the observed patterns in CMIP5, the other models (such as CCSM4 and IPSL_CM5A-LR) exhibit the reverse tendency. The CMIP5 temperature trend uncertainty was significantly reduced in most areas, especially in the Arctic and Antarctic stratosphere, compared to the CMIP3 simulations. Similar to the CMIP3, the CMIP5 simulations overestimated the tropospheric warming in the tropics and Southern Hemisphere and underestimated the stratospheric cooling. The crossover point where tropospheric warming changes into stratospheric cooling occurred near 100 hPa in the tropics, which is higher than in the radiosonde and reanalysis data. The result is likely related to the overestimation of convective activity over the tropical areas in both the CMIP3 and CMIP5 models. Generally, for the temperature trend estimates associated with the numerical models including the reanalyses and global climate models, the uncertainty in the stratosphere is much larger than that in the troposphere, and the uncertainty in the Antarctic is the largest. In addition, note that the reanalyses show the largest uncertainty in the lower tropical stratosphere, and the CMIP3 simulations show the largest uncertainty in both the south and north polar regions.

scholarly journals Comparison of Monthly Temperature Extremes Simulated by CMIP3 and CMIP5 Models

2013 ◽  
Vol 26 (19) ◽  
pp. 7692-7707 ◽  
Author(s):  
Yao Yao ◽  
Yong Luo ◽  
Jianbin Huang ◽  
Zongci Zhao
Keyword(s):  
Coupled Model ◽  
Cmip5 Models ◽  
Temperature Extremes ◽  
Extreme Temperatures ◽  
Model Intercomparison ◽  
Annual Cycles ◽  
Monthly Temperature ◽  
Intercomparison Project ◽  
Cmip3 Ensemble ◽  
Cold Extremes

Abstract The extreme monthly-mean temperatures simulated by 28 models in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are evaluated and compared with those from 24 models in the third phase of the Coupled Model Intercomparison Project (CMIP3). Comparisons with observations and reanalyses indicate that the models from both CMIP3 and CMIP5 perform well in simulating temperature extremes, which are expressed as 20-yr return values. When the climatological annual cycle is removed, the ensemble spread in CMIP5 is smaller than that in CMIP3. Benefitting from a higher resolution, the CMIP5 models perform better at simulating extreme temperatures on the local gridcell scale. The CMIP5 representative concentration pathway (RCP4.5) and CMIP3 B1 experiments project a similar change pattern in the near future for both warm and cold extremes, and the pattern is in agreement with that of the seasonal extremes. By the late twenty-first century, the changes in monthly temperature extremes projected under the three CMIP3 (B1, A1B, and A2) and two CMIP5 (RCP4.5 and RCP8.5) scenarios generally follow the changes in climatological annual cycles, which is consistent with previous studies on daily extremes. Compared with the CMIP3 ensemble, the CMIP5 ensemble shows a larger intermodel uncertainty with regard to the change in cold extremes in snow-covered regions. Enhanced changes in extreme temperatures that exceed the global mean warming are found in regions where the retreat of snow (or the soil moisture feedback effect) plays an important role, confirming the findings for daily temperature extremes.

Challenges in Constraining Future Change of Global Land Precipitation in CMIP6 Models

2020 ◽  
Author(s):  
June-Yi Lee ◽  
Kyung-Sook Yun ◽  
Arjun Babu ◽  
Young-Min Yang ◽  
Eui-Seok Chung ◽  
...  
Keyword(s):  
Global Warming ◽  
Emission Scenario ◽  
Coupled Model ◽  
Precipitation Change ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Projected Change ◽  
Global Land ◽  
Intercomparison Project ◽  
Global Mean

<p><span>The Coupled Model Intercomparison Project Phase 5 (CMIP5) models have showed substantial inter-model spread in estimating annual global-mean precipitation change per one-degree greenhouse-gas-induced warming (precipitation sensitivity), ranging from -4.5</span><span>–4.2</span><span>%</span><sup><span>o</span></sup><span>C<sup>-1</sup>in the Representative Concentration Pathway (RCP) 2.6, the lowest emission scenario, to 0.2–4.0</span><span>%</span><sup><span>o</span></sup><span>C<sup>-1</sup>in the RCP 8.5, the highest emission scenario. The observed-based estimations in the global-mean land precipitation sensitivity during last few decades even show much larger spread due to the considerable natural interdecadal variability, role of anthropogenic aerosol forcing, and uncertainties in observation. This study tackles to better quantify and constrain global land precipitation change in response to global warming by analyzing the new range of Shared Socio-economic Pathway (SSP) scenarios in the </span><span>Coupled Model Intercomparison Project Phase 6 (CMIP6) compared with RCP scenarios in the CMIP5. We show that the range of projected change in annual global-mean land (ocean) precipitation by the end of the 21<sup>st</sup>century relative to the recent past (1995-2014) in the 23 CMIP6 models is over 50% (20%) larger than that in corresponding scenarios of the 40 CMIP5 models. The estimated ranges of precipitation sensitivity in four Tier-1 SSPs are also larger than those in corresponding CMIP5 RCPs. The large increase in projected precipitation change in the highest quartile over ocean is mainly due to the increased number of high equilibrium climate sensitivity (ECS) models in CMIP6 compared to CMIP5, but not over land due to different response of thermodynamic moisture convergence and dynamic processes to global warming. We further discuss key challenges in constraining future precipitation change and source of uncertainties in land precipitation change.</span></p>

scholarly journals Intermodel Variability and Mechanism Attribution of Central and Southeastern U.S. Anomalous Cooling in the Twentieth Century as Simulated by CMIP5 Models

2013 ◽  
Vol 26 (17) ◽  
pp. 6215-6237 ◽  
Author(s):  
Zaitao Pan ◽  
Xiaodong Liu ◽  
Sanjiv Kumar ◽  
Zhiqiu Gao ◽  
James Kinter
Keyword(s):  
United States ◽  
Twentieth Century ◽  
Land Surface ◽  
Regional Scale ◽  
Coupled Model ◽  
The United States ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Central United States ◽  
Intercomparison Project

Abstract Some parts of the United States, especially the southeastern and central portion, cooled by up to 2°C during the twentieth century, while the global mean temperature rose by 0.6°C (0.76°C from 1901 to 2006). Studies have suggested that the Pacific decadal oscillation (PDO) and the Atlantic multidecadal oscillation (AMO) may be responsible for this cooling, termed the “warming hole” (WH), while other works reported that regional-scale processes such as the low-level jet and evapotranspiration contribute to the abnormity. In phase 3 of the Coupled Model Intercomparison Project (CMIP3), only a few of the 53 simulations could reproduce the cooling. This study analyzes newly available simulations in experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) from 28 models, totaling 175 ensemble members. It was found that 1) only 19 out of 100 all-forcing historical ensemble members simulated negative temperature trend (cooling) over the southeast United States, with 99 members underpredicting the cooling rate in the region; 2) the missing of cooling in the models is likely due to the poor performance in simulating the spatial pattern of the cooling rather than the temporal variation, as indicated by a larger temporal correlation coefficient than spatial one between the observation and simulations; 3) the simulations with greenhouse gas (GHG) forcing only produced strong warming in the central United States that may have compensated the cooling; and 4) the all-forcing historical experiment compared with the natural-forcing-only experiment showed a well-defined WH in the central United States, suggesting that land surface processes, among others, could have contributed to the cooling in the twentieth century.

scholarly journals Dynamical Downscaling Projections of Twenty-First-Century Atlantic Hurricane Activity: CMIP3 and CMIP5 Model-Based Scenarios

2013 ◽  
Vol 26 (17) ◽  
pp. 6591-6617 ◽  
Author(s):  
Thomas R. Knutson ◽  
Joseph J. Sirutis ◽  
Gabriel A. Vecchi ◽  
Stephen Garner ◽  
Ming Zhao ◽  
...  
Keyword(s):  
Inner Core ◽  
Dynamical Downscaling ◽  
Coupled Model ◽  
First Century ◽  
Cmip5 Models ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Model Intercomparison ◽  
Intercomparison Project ◽  
Hurricane Activity ◽  
Twenty First Century

Abstract Twenty-first-century projections of Atlantic climate change are downscaled to explore the robustness of potential changes in hurricane activity. Multimodel ensembles using the phase 3 of the Coupled Model Intercomparison Project (CMIP3)/Special Report on Emissions Scenarios A1B (SRES A1B; late-twenty-first century) and phase 5 of the Coupled Model Intercomparison Project (CMIP5)/representative concentration pathway 4.5 (RCP4.5; early- and late-twenty-first century) scenarios are examined. Ten individual CMIP3 models are downscaled to assess the spread of results among the CMIP3 (but not the CMIP5) models. Downscaling simulations are compared for 18-km grid regional and 50-km grid global models. Storm cases from the regional model are further downscaled into the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model (9-km inner grid spacing, with ocean coupling) to simulate intense hurricanes at a finer resolution. A significant reduction in tropical storm frequency is projected for the CMIP3 (−27%), CMIP5-early (−20%) and CMIP5-late (−23%) ensembles and for 5 of the 10 individual CMIP3 models. Lifetime maximum hurricane intensity increases significantly in the high-resolution experiments—by 4%–6% for CMIP3 and CMIP5 ensembles. A significant increase (+87%) in the frequency of very intense (categories 4 and 5) hurricanes (winds ≥ 59 m s−1) is projected using CMIP3, but smaller, only marginally significant increases are projected (+45% and +39%) for the CMIP5-early and CMIP5-late scenarios. Hurricane rainfall rates increase robustly for the CMIP3 and CMIP5 scenarios. For the late-twenty-first century, this increase amounts to +20% to +30% in the model hurricane’s inner core, with a smaller increase (~10%) for averaging radii of 200 km or larger. The fractional increase in precipitation at large radii (200–400 km) approximates that expected from environmental water vapor content scaling, while increases for the inner core exceed this level.

scholarly journals Effective radiative forcing and adjustments in CMIP6 models

2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Gunnar Myhre ◽  
Kari Alterskjær ◽  
William Collins ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Aerosol Forcing ◽  
Intercomparison Project ◽  
Effective Radiative Forcing

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

Simulation of wind damages associated with the PRIMAVERA European windstorm event set

2021 ◽  
Author(s):  
Tristan Perotin
Keyword(s):  
Climate Models ◽  
Dynamical Downscaling ◽  
Insurance Industry ◽  
Coupled Model ◽  
Correction Method ◽  
Weather Data ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Insurance Sector ◽  
Intercomparison Project

<p>Winter windstorms are one of the major natural hazards affecting Europe, potentially causing large damages. The study of windstorm risks is therefore particularly important for the insurance industry. Physical natural catastrophe models for the insurance industry appeared in the 1980s and enable a fine analysis of the risk by taking into account all of its components (hazard, vulnerability and exposure). One main aspect of this catastrophe modeling is the production and validation of extreme hazard scenarios. As observational weather data is very sparse before the 1980s, estimates of extreme windstorm risks are usually based on climate models, despite the limited resolution of these models. Even though this limitation can be partially corrected by statistical or dynamical downscaling and calibration techniques, new generations of climate models can bring new understanding of windstorm risks.</p><p>In that context, PRIMAVERA, a European Union Horizon2020 project, made available a windstorm event set based on 21 tier 1 (1950-2014) highresSST-present simulations of the High Resolution Model Intercomparison Project (HighResMIP) component of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The events were identified with a storm tracking algorithm, footprints were defined for each event as maximum gusts over a 72 hour period, and the footprints were re-gridded to the ERA5 grid and calibrated with a quantile mapping correction method. The native resolution of these simulations ranges from 150km (typical resolution of the CMIP5 models) to 25km.</p><p>We have studied the applicability of the PRIMAVERA European windstorm event set for the modeling of European windstorm risks for the insurance sector. Preliminary results show that losses simulated from the event set appear to be consistent with historical data for all of the included simulations. The event set enables a better representation of attritional events and storm clustering than other existing event sets. An alternative calibration technique for extreme gusts and potential future developments of the event set will be proposed.</p>

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