scholarly journals Cloud radiative forcing intercomparison between fully coupled CMIP5 models and CERES satellite data

2014 ◽  
Vol 32 (7) ◽  
pp. 793-807 ◽  
Author(s):  
M. Calisto ◽  
D. Folini ◽  
M. Wild ◽  
L. Bengtsson
Keyword(s):  
Radiative Forcing ◽  
Cloud Cover ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Radiative Fluxes ◽  
Cloud Radiative Forcing ◽  
Summer Hemisphere ◽  
Intercomparison Project ◽  
Annual Means ◽  
The Tropics

Abstract. In this paper, radiative fluxes for 10 years from 11 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and from CERES satellite observations have been analyzed and compared. Under present-day conditions, the majority of the investigated CMIP5 models show a tendency towards a too-negative global mean net cloud radiative forcing (NetCRF) as compared to CERES. A separate inspection of the long-wave and shortwave contribution (LWCRF and SWCRF) as well as cloud cover points to different shortcomings in different models. Models with a similar NetCRF still differ in their SWCRF and LWCRF and/or cloud cover. Zonal means mostly show excessive SWCRF (too much cooling) in the tropics between 20° S and 20° N and in the midlatitudes between 40 to 60° S. Most of the models show a too-small/too-weak LWCRF (too little warming) in the subtropics (20 to 40° S and N). Difference maps between CERES and the models identify the tropical Pacific Ocean as an area of major discrepancies in both SWCRF and LWCRF. The summer hemisphere is found to pose a bigger challenge for the SWCRF than the winter hemisphere. The results suggest error compensation to occur between LWCRF and SWCRF, but also when taking zonal and/or annual means. Uncertainties in the cloud radiative forcing are thus still present in current models used in CMIP5.

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 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.

scholarly journals Cloud and Water Vapor Feedbacks to the El Niño Warming: Are They Still Biased in CMIP5 Models?

2013 ◽  
Vol 26 (14) ◽  
pp. 4947-4961 ◽  
Author(s):  
Lin Chen ◽  
Yongqiang Yu ◽  
De-Zheng Sun
Keyword(s):  
Water Vapor ◽  
El Niño ◽  
Radiative Forcing ◽  
Large Scale ◽  
El Nino ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Cold Tongue ◽  
Key Factor ◽  
Intercomparison Project

Abstract Previous evaluations of model simulations of the cloud and water vapor feedbacks in response to El Niño warming have singled out two common biases in models from phase 3 of the Coupled Model Intercomparison Project (CMIP3): an underestimate of the negative feedback from the shortwave cloud radiative forcing (SWCRF) and an overestimate of the positive feedback from the greenhouse effect of water vapor. Here, the authors check whether these two biases are alleviated in the CMIP5 models. While encouraging improvements are found, particularly in the simulation of the negative SWCRF feedback, the biases in the simulation of these two feedbacks remain prevalent and significant. It is shown that bias in the SWCRF feedback correlates well with biases in the corresponding feedbacks from precipitation, large-scale circulation, and longwave radiative forcing of clouds (LWCRF). By dividing CMIP5 models into two categories—high score models (HSM) and low score models (LSM)—based on their individual skills of simulating the SWCRF feedback, the authors further find that ocean–atmosphere coupling generally lowers the score of the simulated feedbacks of water vapor and clouds but that the LSM is more affected by the coupling than the HSM. They also find that the SWCRF feedback is simulated better in the models that have a more realistic zonal extent of the equatorial cold tongue, suggesting that the continuing existence of an excessive cold tongue is a key factor behind the persistence of the feedback biases in models.

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

2012 ◽  
Vol 5 (4) ◽  
pp. 3621-3645 ◽  
Author(s):  
J. Xu ◽  
A. M. Powell
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 simulation in some of 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 Excessive ITCZ but Negative SST Biases in the Tropical Pacific Simulated by CMIP5/6 Models: The Role of the Meridional Pattern of SST Bias

2020 ◽  
Vol 33 (12) ◽  
pp. 5305-5316 ◽  
Author(s):  
Shijie Zhou ◽  
Gang Huang ◽  
Ping Huang
Keyword(s):  
Coupled Model ◽  
Tropical Pacific ◽  
Cmip5 Models ◽  
Climate Anomalies ◽  
Sst Bias ◽  
Key Factor ◽  
Intercomparison Project ◽  
The Tropics ◽  
The Tropical Pacific

AbstractIn phases 5 and 6 of the state-of-the-art Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively) models, there is an apparent excessive rainfall bias with a negative SST bias in the tropical Pacific intertropical convergence zone (ITCZ). The regime of the excessive ITCZ but negative SST bias is inconsistent with the common positive rainfall–SST correlation of climate anomalies over the tropics. Using a two-mode model, we decomposed the rainfall bias into two components and found that the surface convergence (SC) bias is the key factor forming the excessive ITCZ bias in the historical runs of 25 CMIP5 models and 23 CMIP6 models. A mixed layer model was further applied to connect the formation of the SC bias with the SST pattern bias. The results suggest that the meridional pattern of the SST bias plays a key role in forming the SC bias. In the CMIP5 and CMIP6 models, the overall negative SST bias has two apparent meridional troughs at around 10°S and 10°N, respectively. The two meridional troughs in the SST bias drive two convergence centers in the SC bias favoring the excessive ITCZ, even though the local SST bias is negative.

scholarly journals Indirect Aerosol Effect Increases CMIP5 Models’ Projected Arctic Warming

2016 ◽  
Vol 29 (4) ◽  
pp. 1417-1428 ◽  
Author(s):  
Petr Chylek ◽  
Timothy J. Vogelsang ◽  
James D. Klett ◽  
Nicholas Hengartner ◽  
Dave Higdon ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Arctic Warming ◽  
Aerosol Effect ◽  
Cmip5 Climate Models ◽  
Intercomparison Project ◽  
Aerosol Effects

Abstract Phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate models’ projections of the 2014–2100 Arctic warming under radiative forcing from representative concentration pathway 4.5 (RCP4.5) vary from 0.9° to 6.7°C. Climate models with or without a full indirect aerosol effect are both equally successful in reproducing the observed (1900–2014) Arctic warming and its trends. However, the 2014–2100 Arctic warming and the warming trends projected by models that include a full indirect aerosol effect (denoted here as AA models) are significantly higher (mean projected Arctic warming is about 1.5°C higher) than those projected by models without a full indirect aerosol effect (denoted here as NAA models). The suggestion is that, within models including full indirect aerosol effects, those projecting stronger future changes are not necessarily distinguishable historically because any stronger past warming may have been partially offset by stronger historical aerosol cooling. The CMIP5 models that include a full indirect aerosol effect follow an inverse radiative forcing to equilibrium climate sensitivity relationship, while models without it do not.

scholarly journals Patterns of Precipitation Change and Climatological Uncertainty among CMIP5 Models, with a Focus on the Midlatitude Pacific Storm Track*

2015 ◽  
Vol 28 (19) ◽  
pp. 7857-7872 ◽  
Author(s):  
Baird Langenbrunner ◽  
J. David Neelin ◽  
Benjamin R. Lintner ◽  
Bruce T. Anderson
Keyword(s):  
Radiative Forcing ◽  
Storm Track ◽  
Coupled Model ◽  
Internal Variability ◽  
Empirical Orthogonal Functions ◽  
Cmip5 Models ◽  
Orthogonal Functions ◽  
Maximum Covariance Analysis ◽  
The Pacific ◽  
The Tropics

Abstract Projections of modeled precipitation (P) change in global warming scenarios demonstrate marked intermodel disagreement at regional scales. Empirical orthogonal functions (EOFs) and maximum covariance analysis (MCA) are used to diagnose spatial patterns of disagreement in the simulated climatology and end-of-century P changes in phase 5 of the Coupled Model Intercomparison Project (CMIP5) archive. The term principal uncertainty pattern (PUP) is used for any robust mode calculated when applying these techniques to a multimodel ensemble. For selected domains in the tropics, leading PUPs highlight features at the margins of convection zones and in the Pacific cold tongue. The midlatitude Pacific storm track is emphasized given its relevance to wintertime P projections over western North America. The first storm-track PUP identifies a sensitive region of disagreement in P increases over the eastern midlatitude Pacific where the storm track terminates, related to uncertainty in an eastward extension of the climatological jet. The second PUP portrays uncertainty in a zonally asymmetric meridional shift of storm-track P, related to uncertainty in the extent of a poleward jet shift in the western Pacific. Both modes appear to arise primarily from intermodel differences in the response to radiative forcing, distinct from sampling of internal variability. The leading storm-track PUPs for P and zonal wind change exhibit similarities to the leading uncertainty patterns for the historical climatology, indicating important and parallel sensitivities in the eastern Pacific storm-track terminus region. However, expansion coefficients for climatological uncertainties tend to be weakly correlated with those for end-of-century change.

scholarly journals Arctic Cloud Fraction and Radiative Fluxes in Atmospheric Reanalyses

2009 ◽  
Vol 22 (9) ◽  
pp. 2316-2334 ◽  
Author(s):  
John E. Walsh ◽  
William L. Chapman ◽  
Diane H. Portis
Keyword(s):  
Surface Energy ◽  
Energy Budget ◽  
Radiative Forcing ◽  
Cloud Fraction ◽  
Surface Energy Budget ◽  
Japan Meteorological Agency ◽  
Central Research ◽  
Radiative Fluxes ◽  
Arctic Clouds ◽  
Cloud Radiative Forcing

Abstract Arctic radiative fluxes, cloud fraction, and cloud radiative forcing are evaluated from four currently available reanalysis models using data from the North Slope of Alaska (NSA) Barrow site of the Atmospheric Radiation Measurement Program (ARM). A primary objective of the ARM–NSA program is to provide a high-resolution dataset of direct measurements of Arctic clouds and radiation so that global climate models can better parameterize high-latitude cloud radiative processes. The four reanalysis models used in this study are the 1) NCEP–NCAR global reanalysis, 2) 40-yr ECMWF Re-Analysis (ERA-40), 3) NCEP–NCAR North American Regional Reanalysis (NARR), and 4) Japan Meteorological Agency and Central Research Institute of Electric Power Industry 25-yr Reanalysis (JRA25). The reanalysis models simulate the radiative fluxes well if/when the cloud fraction is simulated correctly. However, the systematic errors of climatological reanalysis cloud fractions are substantial. Cloud fraction and radiation biases show considerable scatter, both in the annual mean and over a seasonal cycle, when compared to those observed at the ARM–NSA. Large seasonal cloud fraction biases have significant impacts on the surface energy budget. Detailed comparisons of ARM and reanalysis products reveal that the persistent low-level cloud fraction in summer is particularly difficult for the reanalysis models to capture creating biases in the shortwave radiation flux that can exceed 160 W m−2. ERA-40 is the best performer in both shortwave and longwave flux seasonal representations at Barrow, largely because its simulation of the cloud coverage is the most realistic of the four reanalyses. Only two reanalyses (ERA-40 and NARR) capture the observed transition from positive to negative surface net cloud radiative forcing during a 2–3-month period in summer, while the remaining reanalyses indicate a net warming impact of Arctic clouds on the surface energy budget throughout the entire year. The authors present a variable cloud radiative forcing metric to diagnose the erroneous impact of reanalysis cloud fraction on the surface energy balance. The misrepresentations of cloud radiative forcing in some of the reanalyses are attributable to errors in both simulated cloud amounts and the models’ radiative response to partly cloudy conditions.

Evaluation of the tail of the probability distribution of daily and sub-daily precipitation in CMIP6 models

2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen
Keyword(s):  
General Circulation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Coupled Model ◽  
Lower Troposphere ◽  
General Circulation Models ◽  
Intercomparison Project ◽  
Cloud Tops ◽  
The Tropics ◽  
Fraction Models

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.

scholarly journals Effects of Ocean Slow Response under Low Warming Targets

2020 ◽  
Vol 33 (2) ◽  
pp. 477-496 ◽  
Author(s):  
Shang-Min Long ◽  
Shang-Ping Xie ◽  
Yan Du ◽  
Qinyu Liu ◽  
Xiao-Tong Zheng ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Coupled Model ◽  
Deep Ocean ◽  
Ocean Warming ◽  
Meridional Overturning Circulation ◽  
Slow Response ◽  
Intercomparison Project ◽  
Meridional Overturning ◽  
Near Future

AbstractThe 2015 Paris Agreement proposed targets to limit global-mean surface temperature (GMST) rise well below 2°C relative to preindustrial level by 2100, requiring a cease in the radiative forcing (RF) increase in the near future. In response to changing RF, the deep ocean responds slowly (ocean slow response), in contrast to the fast ocean mixed layer adjustment. The role of the ocean slow response under low warming targets is investigated using representative concentration pathway (RCP) 2.6 simulations from phase 5 of the Coupled Model Intercomparison Project. In RCP2.6, the deep ocean continues to warm while RF decreases after reaching a peak. The deep ocean warming helps to shape the trajectories of GMST and fuels persistent thermosteric sea level rise. A diagnostic method is used to decompose further changes after the RF peak into a slow warming component under constant peak RF and a cooling component due to the decreasing RF. Specifically, the slow warming component amounts to 0.2°C (0.6°C) by 2100 (2300), raising the hurdle for achieving the low warming targets. When RF declines, the deep ocean warming takes place in all basins but is the most pronounced in the Southern Ocean and Atlantic Ocean where surface heat uptake is the largest. The climatology and change of meridional overturning circulation are both important for the deep ocean warming. To keep the GMST rise at a low level, substantial decrease in RF is required to offset the warming effect from the ocean slow response.

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