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Jun Ying and 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.

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Jun Ying and Ping Huang

Abstract

The role of the intermodel spread of cloud–radiation feedback in the uncertainty in the tropical Pacific SST warming (TPSW) pattern under global warming is investigated based on the historical and RCP8.5 runs from 32 models participating in CMIP5. The large intermodel discrepancies in cloud–radiation feedback contribute 24% of the intermodel uncertainty in the TPSW pattern over the central Pacific. The mechanism by which the cloud–radiation feedback influences the TPSW pattern is revealed based on an analysis of the surface heat budget. A relatively weak negative cloud–radiation feedback over the central Pacific cannot suppress the surface warming as greatly as in the multimodel ensemble and thus induces a warm SST deviation over the central Pacific, producing a low-level convergence that suppresses (enhances) the evaporative cooling and zonal cold advection in the western (eastern) Pacific. With these processes, the original positive SST deviation over the central Pacific will move westward to the western and central Pacific, with a negative SST deviation in the eastern Pacific. Compared with the observed cloud–radiation feedback from six sets of reanalysis and satellite-observed data, the negative cloud–radiation feedback in the models is underestimated in general. It implies that the TPSW pattern should be closer to an El Niño–like pattern based on the concept of observational constraint. However, the observed cloud–radiation feedback from the various datasets also demonstrates large discrepancies in magnitude. Therefore, the authors suggest that more effort should be made to improve the precision of shortwave radiation observations and the description of cloud–radiation feedback in models for a more reliable projection of the TPSW pattern in future.

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Ping Huang and Jun Ying

Abstract

This study develops a new observational constraint method, called multimodel ensemble pattern regression (EPR), to correct the projections of regional climate change by the conventional unweighted multimodel mean (MMM). The EPR method first extracts leading modes of historical bias using intermodel EOF analysis, then builds up the linear correlated modes between historical bias and change bias using multivariant linear regression, and finally estimates the common change bias induced by common historical bias. Along with correcting common change bias, the EPR method implicitly removes the intermodel uncertainty in the change projection deriving from the intermodel diversity in background simulation.

The EPR method is applied to correct the patterns of tropical Pacific SST changes using the historical and representative concentration pathway 8.5 (RCP8.5) runs in 30 models from phase 5 of CMIP (CMIP5) and observed SSTs. The common bias patterns of the tropical Pacific SSTs in historical runs, including the excessive cold tongue, the southeastern warm bias, and the narrower warm pool, are estimated to induce La Niña–like change biases. After the estimated common change biases are removed, the corrected SST changes display a pronounced El Niño–like pattern and have much greater zonal gradients. The bias correction decreases by around half of the intermodel uncertainties in the MMM SST projections. The patterns of corrected tropical precipitation and circulation change are dominated by the enhanced SST change patterns, displaying a pronounced warmer-get-wetter pattern and a decreased Walker circulation with decreased uncertainties.

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Shou-Jun Chen, Ying-Hwa Kuo, Wei Ming, and Hong Ying

Abstract

Severe dust storms frequently occur over northwestern China during spring. They are often associated with strong fronts. In this paper, numerical simulations are performed to examine the effect of dust radiative heating on surface frontogenesis.

The absorption and multiple scattering of the dust are included in an atmospheric radiation scheme. A two-dimensional primitive equation model with 20 levels in the vertical is used for idealized simulations. After a 12-h integration a strong narrow front zone is created below 650 mb. The horizontal potential temperature gradient reaches 6 K (100 km)−1, which is three times as large as that in the initial data. A direct vertical transverse circulation is established along the frontal zone. which is qualitatively similar to the observations.

The results show positive interaction between low-level frontogenesis and dust radiative heating. The adiabatic frontogenesis forcing is enhanced by the feedback of the dust radiative heating. These results suggest that the dust heating can significantly affect mesoscale weather systems in arid and desert regions.

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Ping Huang, Dong Chen, and Jun Ying

Abstract

In the tropics, the atmospheric circulation response to sea surface temperature (SST) anomalies is a crucial part of the tropical air–sea interaction—the primary process of tropical climate. How it will change under global warming is of great importance to tropical climate change. Here, it is shown that the atmospheric vertical circulation response to local SST anomalies will likely be weakened under global warming using 28 selected models from phase 5 of the Coupled Model Intercomparison Project. The weakening of the circulation response to SST anomalies is closely tied to the increased atmospheric stability under global warming, which increases at the same rate as the circulation response decreases—around 8% for 1 K of tropical-mean SST warming. The spatial pattern of background warming can modify—especially in the equatorial central-eastern Pacific—the spatial distribution of the changes in the circulation response. The atmospheric response to SST anomalies may increase where the local background warming is pronouncedly greater than the tropical mean. The general weakening of the atmospheric circulation response to SST anomalies leads to a decreased circulation response to the structured variability of tropical SST anomalies, such as the El Niño–Southern Oscillation and the Indian Ocean dipole. The decreased circulation response will offset some of the enhancement of the tropical rainfall response to these SST modes as a result of global-warming-induced moisture increase and also implies a decreased amplitude of the tropical air–sea interaction modes.

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Ping Huang, Xiao-Tong Zheng, and Jun Ying

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This study disentangles the changes in Indian Ocean (IO) dipole (IOD)-related SST and rainfall variability under global warming projected by the RCP8.5 runs in 29 CMIP5 models. The IOD rainfall changes consist of the thermodynamic component due to the surface moisture increase and the dynamic component due to the changes in IOD-related circulation. The IOD circulation changes are dominated by the IOD SST changes, which were further clarified using the amplitude and structural decomposition. The amplitudes of IOD SST and circulation are both decreased at rates of around 7.2% and 13.7% °C−1, respectively. The structural changes in IOD SST and circulation show a pattern with increases from the eastern to the western coast of the equatorial IO, similar to the pattern of so-called extreme IOD events in previous studies. Disentangling previous mechanisms and projections, we conclude that the increased atmospheric stability suppresses the amplitudes in IOD SST and circulation, whereas the positive IOD (pIOD)-like mean-state SST changes, leading to greater warming in the west than the east, mainly alter the structure of IOD SST and circulation. Both the amplitude and structural changes in the IOD SST and circulation are robust among the CMIP5 models, but their distinct patterns and out-of-step changes lead to an uncertain projection of IOD changes defined by the dipole mode index or EOF analysis in previous studies. Furthermore, the structural changes, dominated by the pIOD-like mean-state SST changes, are significantly correlated with the historical IOD amplitude among the models. Considering the commonly overestimated IOD amplitude as an emergent constraint, the structural changes in IOD SST and circulation should not be as robust as the original multimodel projection.

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Jun Yang, Weitao Lu, Ying Ma, and Wen Yao

Abstract

Cloud detection is a basic research for achieving cloud-cover state and other cloud characteristics. Because of the influence of sunlight, the brightness of sky background on the ground-based cloud image is usually nonuniform, which increases the difficulty for cirrus cloud detection, and few detection methods perform well for thin cirrus clouds. This paper presents an effective background estimation method to eliminate the influence of variable illumination conditions and proposes a background subtraction adaptive threshold method (BSAT) to detect cirrus clouds in visible images for the small field of view and mixed clear–cloud scenes. The BSAT algorithm consists of red-to-blue band operation, background subtraction, adaptive threshold selection, and binarization. The experimental results show that the BSAT algorithm is robust for all types of cirrus clouds, and the quantitative evaluation results demonstrate that the BSAT algorithm outperforms the fixed threshold (FT) and adaptive threshold (AT) methods in cirrus cloud detection.

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Wenping Jiang, Ping Huang, Gang Huang, and Jun Ying

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An excessive westward extension of the simulated ENSO-related sea surface temperature (ENSO SST) variability in the CMIP5 and CMIP6 models is the most apparent ENSO SST pattern bias and dominates the intermodel spread in ENSO SST variability among the models. The ENSO SST bias lowers the models’ skill in ENSO-related simulations and induces large intermodel uncertainty in ENSO-related projections. The present study investigates the origins of the excessive westward extension of ENSO SST in 25 CMIP5 and 25 CMIP6 models. Based on the intermodel spread of ENSO SST variability simulated in the 50 models, we reveal that this ENSO SST bias among the models largely depends on the simulated cold tongue strength in the equatorial western Pacific (EWP). Models simulating a stronger cold tongue tend to simulate a larger mean zonal SST gradient in the EWP and then a larger zonal advection feedback in the EWP, favoring a more westward extension of the ENSO SST pattern. In addition, with the overall improvement in the EWP cold tongue from CMIP5 to CMIP6, the excessive westward extension bias of ENSO SST in CMIP6 models is also reduced relative to those in CMIP5 models. The results suggest that the bias and intermodel disagreement in the mean-state SST have been improved, which benefits to improving ENSO simulation.

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Shang-Min Long, Gen Li, Kaiming Hu, and Jun Ying

Abstract

Previous studies reveal that the last generation of coupled general circulation models (CGCMs) commonly suffer from the so-called Indian Ocean dipole (IOD)-like biases, lowering the models’ ability in climate prediction and projection. The present study shows that such IOD-like biases are reduced insignificantly or even worsen in CGCMs from phase 5 to phase 6 of the Coupled Model Intercomparison Project (CMIP). The origins of the IOD-like biases in CGCMs are further investigated by comparing model outputs from CMIP and the Atmospheric Model Intercomparison Project (AMIP). The CGCMs’ errors are divided into the biases from the AMIP simulation (AMIP biases) and ocean–atmosphere coupling (coupling biases). For the multimodel ensemble mean, the AMIP (coupling) biases account for about two-thirds (one-third) of the IOD-like CMIP biases. In AMIP simulations, the South Asian summer monsoon (SASM) is overly strong; therefore, it could advect overly large easterly momentum from the south Indian Ocean (IO) to the equator. The resultant equatorial easterly wind bias would initiate the convection–circulation feedback and develop large IOD-like AMIP biases. In contrast, the coupling biases weaken the SASM and hence generate warm SST error over the western IO during boreal summer. Such SST error persists to boreal autumn and triggers the Bjerknes feedback, developing the IOD-like coupling biases. Furthermore, the intermodel spread in the IOD-like CMIP biases is largely explained by the intermodel differences in the coupling biases rather than the AMIP biases. The results imply that substantial efforts should be respectively made on reducing the atmospheric models’ intrinsic monsoon biases as well as advancing the simulations of ocean–atmosphere coupling processes.

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Jun Ying, Ping Huang, Tao Lian, and Dake Chen

Abstract

This study investigates the mechanism of the large intermodel uncertainty in the change of ENSO’s amplitude under global warming based on 31 CMIP5 models. We find that the uncertainty in ENSO’s amplitude is significantly correlated to that of the change in the response of atmospheric circulation to SST anomalies (SSTAs) in the eastern equatorial Pacific Niño-3 region. This effect of the atmospheric response to SSTAs mainly influences the uncertainty in ENSO’s amplitude during El Niño (EN) phases, but not during La Niña (LN) phases, showing pronounced nonlinearity. The effect of the relative SST warming and the present-day response of atmospheric circulation to SSTAs are the two major contributors to the intermodel spread of the change in the atmospheric response to SSTAs, of which the latter is more important. On the one hand, models with a stronger (weaker) mean-state SST warming in the eastern equatorial Pacific, relative to the tropical-mean warming, favor a larger (smaller) increase in the change in the response of atmospheric circulation to SSTAs in the eastern equatorial Pacific during EN. On the other hand, models with a weaker (stronger) present-day response of atmospheric circulation to SSTAs during EN tend to exhibit a larger (smaller) increase in the change under global warming. The result implies that an improved simulation of the present-day response of atmospheric circulation to SSTAs could be effective in lowering the uncertainty in ENSO’s amplitude change under global warming.

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