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

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.

2021 ◽  
Vol 34 (2) ◽  
pp. 449-464
Author(s):  
Samantha Stevenson ◽  
Andrew T. Wittenberg ◽  
John Fasullo ◽  
Sloan Coats ◽  
Bette Otto-Bliesner

AbstractThe majority of future projections in the Coupled Model Intercomparison Project (CMIP5) show more frequent exceedances of the 5 mm day−1 rainfall threshold in the eastern equatorial Pacific rainfall during El Niño, previously described in the literature as an increase in “extreme El Niño events”; however, these exceedance frequencies vary widely across models, and in some projections actually decrease. Here we combine single-model large ensemble simulations with phase 5 of the Coupled Model Intercomparison Project (CMIP5) to diagnose the mechanisms for these differences. The sensitivity of precipitation to local SST anomalies increases consistently across CMIP-class models, tending to amplify extreme El Niño occurrence; however, changes to the magnitude of ENSO-related SST variability can drastically influence the results, indicating that understanding changes to SST variability remains imperative. Future El Niño rainfall intensifies most in models with 1) larger historical cold SST biases in the central equatorial Pacific, which inhibit future increases in local convective cloud shading, enabling more local warming; and 2) smaller historical warm SST biases in the far eastern equatorial Pacific, which enhance future reductions in stratus cloud, enabling more local warming. These competing mechanisms complicate efforts to determine whether CMIP5 models under- or overestimate the future impacts of climate change on El Niño rainfall and its global impacts. However, the relation between future projections and historical biases suggests the possibility of using observable metrics as “emergent constraints” on future extreme El Niño, and a proof of concept using SSTA variance, precipitation sensitivity to SST, and regional SST trends is presented.


2014 ◽  
Vol 32 (7) ◽  
pp. 793-807 ◽  
Author(s):  
M. Calisto ◽  
D. Folini ◽  
M. Wild ◽  
L. Bengtsson

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.


2018 ◽  
Vol 31 (4) ◽  
pp. 1315-1335 ◽  
Author(s):  
Samantha Ferrett ◽  
Matthew Collins ◽  
Hong-Li Ren

The rate of damping of tropical Pacific sea surface temperature anomalies (SSTAs) associated with El Niño events by surface shortwave heat fluxes has significant biases in current coupled climate models [phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. Of 33 CMIP5 models, 16 have shortwave feedbacks that are weakly negative in comparison to observations, or even positive, resulting in a tendency of amplification of SSTAs. Two biases in the cloud response to El Niño SSTAs are identified and linked to significant mean state biases in CMIP5 models. First, cool mean SST and reduced precipitation are linked to comparatively less cloud formation in the eastern equatorial Pacific during El Niño events, driven by a weakened atmospheric ascent response. Second, a spurious reduction of cloud driven by anomalous surface relative humidity during El Niño events is present in models with more stable eastern Pacific mean atmospheric conditions and more low cloud in the mean state. Both cloud response biases contribute to a weak negative shortwave feedback or a positive shortwave feedback that amplifies El Niño SSTAs. Differences between shortwave feedback in the coupled models and the corresponding atmosphere-only models (AMIP) are also linked to mean state differences, consistent with the biases found between different coupled models. Shortwave feedback bias can still persist in AMIP, as a result of persisting weak shortwave responses to anomalous cloud and weak cloud responses to atmospheric ascent. This indicates the importance of bias in the atmosphere component to coupled model feedback and mean state biases.


2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Gunnar Myhre ◽  
Kari Alterskjær ◽  
William Collins ◽  
...  

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.


2012 ◽  
Vol 25 (20) ◽  
pp. 6942-6957 ◽  
Author(s):  
Jong-Seong Kug ◽  
Yoo-Geun Ham

Abstract Observational studies hypothesized that Indian Ocean (IO) feedback plays a role in leading to a fast transition of El Niño. When El Niño accompanies IO warming, IO warming induces the equatorial easterlies over the western Pacific (WP), leading to a rapid termination of El Niño via an oceanic adjust process. In this study, this IO feedback is reinvestigated using the Coupled Model Intercomparison Project phase 3 (CMIP3) coupled GCM simulations. It is found that most of the climate models mimic this IO feedback reasonably, supporting the observational hypothesis. However, most climate models tend to underestimate the strength of the IO feedback, which means the phase transition of ENSO due to the IO feedback is less effective than the observed one. Furthermore, there is great intermodel diversity in simulating the strength of the IO feedback. It is shown that the strength of the IO feedback is related to the precipitation responses to El Niño and IO SST forcings over the warm-pool regions. Moreover, the authors suggest that the distribution of climatological precipitation is one important component in controlling the strength of the IO feedback.


2017 ◽  
Vol 18 (8) ◽  
pp. 2131-2141 ◽  
Author(s):  
Michael D. Warner ◽  
Clifford F. Mass

Abstract This paper describes changes in the climatology, structure, and seasonality of cool-season atmospheric rivers influencing the U.S. West Coast by examining the climate simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) that are forced by the representative concentration pathway (RCP) 8.5 scenario. There are only slight changes in atmospheric river (AR) frequency and seasonality between historical (1970–99) and future (2070–99) periods considering the most extreme days (99th percentile) in integrated water vapor transport (IVT) along the U.S. West Coast. Changes in the 99th percentile of precipitation are only significant over the southern portion of the coast. In contrast, using the number of future days exceeding the historical 99th percentile IVT threshold produces statistically significant increases in the frequency of extreme IVT events for all winter months. The peak in future AR days appears to occur approximately one month earlier. The 10-model mean historical and end-of-century composites of extreme IVT days reflect canonical AR conditions, with a plume of high IVT extending from the coast to the southwest. The similar structure and evolution associated with ARs in the historical and future periods suggest little change in large-scale structure of such events during the upcoming century. Increases in extreme IVT intensity are primarily associated with integrated water vapor increases accompanying a warming climate. Along the southern portion of the U.S. West Coast there is less model agreement regarding the structure and intensity of ARs than along the northern portions of the coast.


2020 ◽  
Vol 33 (6) ◽  
pp. 2407-2426 ◽  
Author(s):  
Chen Xing ◽  
Fei Liu ◽  
Bin Wang ◽  
Deliang Chen ◽  
Jian Liu ◽  
...  

AbstractWe analyzed global surface air temperature (SAT) responses to five major tropical volcanic eruptions from 1870 to 2005 using outputs from 97 historical and 58 Atmospheric Model Intercomparison Project (AMIP) runs that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5). In observations, there was a 3-yr global cooling trend after the eruption due to reduced shortwave radiation, and a 0.1-K average global-mean SAT recovery, consisting of El Niño–like tropical warming and Eurasian warming, occurred in the first posteruption boreal winter. This global cooling pause was simulated by the multimodel ensemble (MME) mean of the AMIP runs, but not the MME of the historical runs due to the absence of El Niño–like warming. In the historical runs, simulation of El Niño–like warming was influenced by the initial ocean condition (IOC). An El Niño–like response was simulated when the IOC was not in an El Niño state, but the warming was much weaker compared to observations. The Eurasian warming response, despite being reproduced by the MME mean of both AMIP and historical runs, was not as strong as in observations. This is because the simulated positive polar vortex response, an important stratospheric forcing for Eurasian warming, was very weak, which suggests that the CMIP5 models, and even the Climate Forecast System model, underestimate volcanic effects on the stratosphere. Most of the coupled models failed to replicate both the El Niño and the enhanced polar vortex responses, indicating an urgent need for improving air–sea interaction and stratospheric processes in these models.


2016 ◽  
Vol 29 (22) ◽  
pp. 8051-8065 ◽  
Author(s):  
Jun Ying ◽  
Ping Huang

Abstract This study investigates how intermodel differences in large-scale ocean dynamics affect the tropical Pacific sea surface temperature (SST) warming (TPSW) pattern under global warming, as projected by 32 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The largest cause of intermodel TPSW differences is related to the cloud–radiation feedback. After removing the effect of cloud–radiation feedback, the authors find that differences in ocean advection play the next largest role, explaining around 14% of the total intermodel variance in TPSW. Of particular importance are differences in climatological zonal overturning circulation among the models. With the robust enhancement of ocean stratification across models, models with relatively strong climatological upwelling tend to have relatively weak SST warming in the eastern Pacific. Meanwhile, the pronounced intermodel differences in ocean overturning changes contribute little to uncertainty in the TPSW pattern. The intermodel differences in climatological zonal overturning are found to be associated with the intermodel spread in climatological SST. In most CMIP5 models, there is a common cold tongue associated with an overly strong overturning in the climatology simulation, implying a La Niña–like bias in the TPSW pattern projected by the MME of the CMIP5 models. This provides further evidence for the projection that the TPSW pattern should be closer to an El Niño–like pattern than the MME projection.


2017 ◽  
Vol 30 (24) ◽  
pp. 10067-10079 ◽  
Author(s):  
Nicholas Siler ◽  
Yu Kosaka ◽  
Shang-Ping Xie ◽  
Xichen Li

The major El Niño of 2015/16 brought significantly less precipitation to California than previous events of comparable strength, much to the disappointment of residents suffering through the state’s fourth consecutive year of severe drought. Here, California’s weak precipitation in 2015/16 relative to previous major El Niño events is investigated within a 40-member ensemble of atmosphere-only simulations run with historical sea surface temperatures (SSTs) and constant radiative forcing. The simulations reveal significant differences in both California precipitation and the large-scale atmospheric circulation between 2015/16 and previous strong El Niño events, which are similar to (albeit weaker than) the differences found in observations. Principal component analysis indicates that these ensemble-mean differences were likely related to a pattern of tropical SST variability with a strong signal in the Indian Ocean and western Pacific and a weaker signal in the eastern equatorial Pacific and subtropical North Atlantic. This SST pattern was missed by the majority of forecast models, which could partly explain their erroneous predictions of above-average precipitation in California in 2015/16.


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