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This study investigates the impacts of modifying the deep convection scheme on the ability to simulate the Madden–Julian Oscillation (MJO) in the Beijing Climate Center Climate System Model version 2 with a medium resolution (BCC-CSM2-T159) and a high resolution (BCC-CSM2-T382). On the basis of the original deep convection scheme, a modified scheme is suggested, which involves the transport processes of deep convective cloud water. The liquid cloud water that is detrained is transferred horizontally to its neighboring grids, and a portion of the cloud water that is horizontally transported is allowed to be transported downward into the lower troposphere. Both BCC-CSM2-T159 and BCC-CSM2-T382 with the modified deep convection scheme perform better than that used the original deep convection scheme in reproducing the major features of the MJO, such as its spectrum, period, intensity, eastward propagation and life cycle. Further analysis shows that those pronounced improvements in the MJO features in both BCC-CSM2-T159 and BCC-CSM2-T382 with the modified scheme are caused by transport processes of deep convective cloud water. The modified deep convection scheme enhances moisture and energy exchange from the lower troposphere to the upper troposphere around convective cloud, and promotes the convergence of moisture in the lower troposphere to the east of the MJO convection center, and then induces eastward propagation of the MJO. The comparisons between the coupled experiments and their corresponding experiments following Atmospheric Model Intercomparison Project (AMIP) simulations indicated that atmosphere–ocean interactions are also important to improve MJO simulations in the models. [ABSTRACT FROM AUTHOR]

Gravity wave parameterizations contribute to uncertainties in middle atmosphere modeling. To investigate the potential for using machine learning to represent atmospheric gravity waves and the impact of implementing such schemes in a general circulation model (GCM), we train a random forest (RF) emulator on outputs from an existing complex parameterization scheme for orographic gravity wave drag (GWD). The performance of the RF emulator is then evaluated with a focus on stratospheric climatology and variability in climate simulations from the middle atmosphere resolving Beijing Climate Center Atmospheric Circulation Model. In offline tests, the predicted orographic GWD by the RF agrees remarkably well with the target GWD throughout the troposphere and the middle atmosphere. The RF emulator can reproduce the observed climatology of zonal‐mean wind and air temperature in the GCM simulation, as well as its target scheme. Compared to the target orographic GWD parameterization scheme, the RF emulator can reproduce the breakdown of the polar vortex in the Southern Hemisphere stratosphere. This study demonstrates the feasibility of using machine learning to emulate parameterized orographic GWD for modeling the stratosphere with a GCM. Plain Language Summary: Machine learning has been utilized to learn atmospheric physical parameterizations such as moist convection, cloud microphysics, radiation, nonorographic gravity waves, etc. However, it remains unknown whether it is feasible to apply machine learning algorithms to parameterize orographic gravity waves and how such schemes perform when interactively coupled in atmospheric general circulation models. Here we employ the widely used random forest algorithm to learn from an existing complex parameterization scheme for orographic gravity wave drag. Then, we implement the random forest scheme in a high‐top atmospheric general circulation model to test its performance. We find that the random forest scheme acts as well as the target parameterization scheme. This study demonstrates the potential of using machine learning to emulate parameterized orographic gravity waves for modeling the middle atmosphere. In future work, it is recommended that machine learning may be used to develop new parameterization schemes directly from observations or high‐resolution model outputs to overcome critical deficiencies in current orographic gravity wave parameterizations, helping to reduce the common biases in simulating the stratosphere with general circulation models. Key Points: Parameterized gravity wave drag from unresolved orography can be emulated with a random forestThe random forest emulator simulates vertical distributions of the zonal wind and air temperature quite well in a general circulation model (GCM)The GCM configured with the random forest scheme reproduces a reasonable breakdown of the austral polar vortex in the stratosphere [ABSTRACT FROM AUTHOR]

Sea ice is a central part of the Arctic climate system, and its changes have a significant impact on the Earth's climate. Yet, its state, especially in summer, is not fully understood and correctly predicted in dynamical forecast systems. In this study, the seasonal prediction skill of Arctic sea ice is investigated in a high‐resolution dynamical forecast system, the China Meteorological Administration Climate Prediction System (CMA‐CPSv3). A 7‐month‐long retrospective forecast is made every other month from 2001 to 2021. Employing the anomaly correlation coefficient as the metric of the prediction skill, we show that CMA‐CPSv3 can predict regional Arctic sea ice extent and sea ice thickness up to 7 lead months. The Bering Sea exhibits the highest prediction skill among the 14 Arctic subregions. CMA‐CPSv3 outperforms the anomaly persistence forecast in the Bering Sea, Sea of Okhotsk, Laptev Sea, and East Siberian Sea. The sources of the sea ice prediction skill partly come from the good performance of upper ocean temperature in CMA‐CPSv3. This holds true not only for winter sea ice in the Arctic marginal seas but also for summer sea ice in several Arctic central seas. Furthermore, CMA‐CPSv3 exhibits a strong relationship between the variability of sea ice and surface heat fluxes. This underscores the importance of enhancing the representation of air‐sea heat exchanges in dynamical forecast systems to improve the prediction skill of sea ice. Plain Language Summary: The reduction of Arctic sea ice has a significant impact on the climate and ecosystems, and accurately predicting Arctic sea ice is of broad interest. In this work, we investigate the seasonal prediction skill of sea ice in a high‐resolution climate model. Using the anomaly correlation coefficient as the skill metric, we find that the prediction skill of sea ice is good up to 7 months and varies by region and target month. Notably, the Bering Sea shows the highest prediction accuracy among the 14 Arctic subregions. Then, we explore the sources of sea ice prediction skill and find that the skill is closely related to the good performance of upper ocean temperature in the model. Furthermore, we show that the regional Arctic sea ice variability is significantly modulated by surface heat fluxes. These results suggest that improving the representation of air‐sea heat exchanges in climate models can enhance the prediction skill of sea ice. Our study contributes to an improved understanding and predicting of the Arctic sea ice variability. Key Points: The China Meteorological Administration Climate Prediction System (CMA‐CPSv3) is used for seasonal predictions of Arctic sea iceCMA‐CPSv3 has skill to predict regional Arctic sea ice up to 7 months and shows the highest skill in the Bering SeaGood performance of ocean subsurface temperature provides crucial sources of regional sea ice prediction skills [ABSTRACT FROM AUTHOR]

Large perturbations in chlorophyll (Chl) are observed to coexist at interannual and tropical instability wave (TIW) scales in the tropical Pacific; at present, their combined effects on El Niño-Southern Oscillation (ENSO) through ocean biology-induced heating (OBH) feedbacks are not understood well. Here, a hybrid coupled model (HCM) for the atmosphere and ocean physics-biogeochemistry (AOPB) in the tropical Pacific is adopted to quantify how ENSO can be modulated by Chl perturbations at interannual and TIW scales, individually or collectively, respectively. The HCM-based sensitivity experiments demonstrate a counteracting effect on ENSO: the bio-climate feedback due to large-scale Chl interannual variability acts to damp ENSO through its impact on upper-ocean stratification and vertical mixing, whereas that due to TIW-scale Chl perturbations tends to amplify ENSO. Because ENSO simulations are sensitively dependent on the ways Chl effects are represented at these different scales, it is necessary to adequately take into account these related differential Chl effects in climate modeling. A bias source for ENSO simulations is illustrated that is related with the Chl effects in the tropical Pacific, adding in a new insight into interactions between the climate system and ocean ecosystem on different scales in the region. These results reveal a level of complexity of ENSO modulations resulting from Chl effects at interannual and TIW scales, which are associated with ocean biogeochemical processes and their interactions with physical processes in the tropical Pacific. [ABSTRACT FROM AUTHOR]

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The BCC-CSM2 model is the second generation of the Beijing Climate Center Climate System Model developed by the National Center of China Meteorological Administration. Using the outputs of two versions of the BCC-CSM2 model with different resolutions, namely: BCC-CSM2-MR and BCC-CSM2-HR, their performance in simulating the climate characteristics of Northwest China was compared. The BCC-CSM2-HR had a better ability to simulate the detailed distribution of the average temperature and precipitation in Northwest China, and could delineate the influence of the topography in detail. The extreme events in Northwest China were evaluated further using the BCC-CSM2-HR and the observation data from China Meteorological Data Center. The BCC-CSM2-HR provided a good simulation of the spatial distribution of extreme climate events in Northwest China, and the spatial distribution of TXx, TNx, TXn, and TNn in Northwest China show closer proximity to the observation than that of TX90p, TN90p, TX10p, and TN10p, even in the case of extreme heavy precipitation. This case study of the extreme weather events showed that the BCC-CSM2-HR model had the best simulation performance for extreme high temperature events in Northwest China, followed by extreme low temperature events, and had the worst simulation ability for extreme precipitation events. [ABSTRACT FROM AUTHOR]

The spurious double Intertropical Convergence Zone (ITCZ) is one of the most prominent systematic biases in coupled atmosphere–ocean general circulation models (CGCMs), and the underestimated marine stratus over eastern subtropical oceans has been recognized as a possible contributor. Rather than modifying the cloud scheme itself, this study significantly ameliorates the marine stratus simulation through improving parameterizations of boundary-layer turbulence and shallow convection in the medium-resolution Beijing Climate Center Climate System Model version 2 (BCC-CSM2-MR). The University of Washington moist turbulence scheme is implemented in BCC-CSM2-MR to better represent the stratocumulus, and a decoupling criterion is also introduced to the shallow convection scheme for improving the simulation of the stratocumulus-to-cumulus transition. Results show that the simulated precipitation in the eastern Pacific south of the Equator is largely reduced, alleviating the double ITCZ problem. The tropical precipitation asymmetry index increases from - 0.024 in the original BCC-CSM2-MR to 0.147 in the revised BCC-CSM2-MR, which is much closer to the observation. The study suggests that improving parameterizations of boundary-layer turbulence and shallow convection is effective for mitigating the double ITCZ syndrome in CGCMs. [ABSTRACT FROM AUTHOR]

We present results from the first 6 years of this major U.K. government funded project to accelerate and enhance collaborative research and development in climate science, forge a strong strategic partnership between U.K. and Chinese climate scientists, and demonstrate new climate services developed in partnership. The development of novel climate services is described in the context of new modeling and prediction capability, enhanced understanding of climate variability and change, and improved observational datasets. Selected highlights are presented from over 300 peer reviewed studies generated jointly by U.K. and Chinese scientists within this project. We illustrate new observational datasets for Asia and enhanced capability through training workshops on the attribution of climate extremes to anthropogenic forcing. Joint studies on the dynamics and predictability of climate have identified new opportunities for skillful predictions of important aspects of Chinese climate such as East Asian summer monsoon rainfall. In addition, the development of improved modeling capability has led to profound changes in model computer codes and climate model configurations, with demonstrable increases in performance. We also describe the successes and difficulties in bridging the gap between fundamental climate research and the development of novel real-time climate services. Participation of dozens of institutes through subprojects in this program, which is governed by the Met Office Hadley Centre, the China Meteorological Administration, and the Institute of Atmospheric Physics, is creating an important legacy for future collaboration in climate science and services. [ABSTRACT FROM AUTHOR]

BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model (T266 in the atmosphere and 1/4 ∘ latitude × 1/4 ∘ longitude in the ocean). Its development is on the basis of the medium-resolution version BCC-CSM2-MR (T106 in the atmosphere and 1 ∘ latitude × 1 ∘ longitude in the ocean) which is the baseline for BCC participation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamical core and physical processes. BCC-CSM2-HR is evaluated for historical climate simulations from 1950 to 2014, performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. Observed global warming trends of surface air temperature from 1950 to 2014 are well captured by both BCC-CSM2-MR and BCC-CSM2-HR. Present-day basic atmospheric mean states during the period from 1995 to 2014 are then evaluated at global scale, followed by an assessment on climate variabilities in the tropics including the tropical cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden–Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR represents the global energy balance well and can realistically reproduce the main patterns of atmospheric temperature and wind, precipitation, land surface air temperature, and sea surface temperature (SST). It also improves the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of the double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, almost disappears in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, and the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observations than their counterparts in BCC-CSM2-MR. Some imperfections are, however, noted in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold SST biases and the insufficient number of tropical cyclones in the North Atlantic. [ABSTRACT FROM AUTHOR]

We evaluate and compare the simulation of summer precipitation in China and the East Asian summer monsoon (EASM) by eight climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) and the corresponding eight previous models from CMIP5. Skill metrics are calculated to assess the climatology, interannual variation and linear trends during the time period 1961–2005. The CMIP6 multimodel ensemble (MME) is more skillful than the CMIP5 MME in the spatial correlation and standard deviation (SD) of the climatological precipitation over Eastern China. All the CMIP6 models improve the skill scores in the climatological pattern of the EASM relative to the previous models of CMIP5, which is related to their smaller sea surface temperature (SST) biases over the Northwestern Pacific Ocean. The models with a higher capability in reproducing the climatological pattern of the EASM tend to have a better skill in simulating summer precipitation over Eastern China. Most (six of eight) of the CMIP6 models have advantages over the previous CMIP5 models in reproducing the interannual anomalous rainfall pattern over Eastern China related to the EASM. Ten of the 16 models partly reproduce the weakening trend of the EASM during 1961–2005. The high‐skill models (GISS‐E2‐H, GISS‐E2‐1‐H) that simulate a clear weakening trend in the EASM also reasonably simulate the negative correlation between the EASM and the SST over Eastern Indian and the Western Pacific Oceans (EIWP). By contrast, the two models (CESM2 and CESM2‐WACCM) that simulate a positive correlation over the EIWP both produce increasing trends in the EASM indices. This indicates the importance of climate models in simulating the relationship between the EASM and the SST over the EIWP. Among the 16 models, only 2 CMIP6 models (BCC‐CSM2‐MR and GISS‐E2‐1‐H) partly reproduce the linear trend of precipitation over Eastern China, featured by the pattern of "southern flood and northern drought." [ABSTRACT FROM AUTHOR]

BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model. Its development is on the basis of the medium-resolution version BCC-CSM2-MR which is the baseline for BCC participation to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamic core and physical processes. BCC-CSM2-HR is evaluated for present-day climate simulations from 1971 to 2000, which are performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. We focus on basic atmospheric mean states over the globe and variabilities in the tropics including the tropic cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden-Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR keeps well the global energy balance and can realistically reproduce main patterns of atmosphere temperature and wind, precipitation, land surface air temperature and sea surface temperature. It also improves in the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, is almost disappeared in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observation than their counterparts in BCC-CSM2-MR. We also note some weakness in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold Sea Surface Temperature (SST) biases and the insufficient number of tropical cyclones in the North Atlantic. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the capability of the Beijing Climate Center Climate System Model (BCC-CSM) in simulating and forecasting the boreal summer intraseasonal oscillation (BSISO), using its simulation and sub-seasonal to seasonal (S2S) hindcast results. Results show that the model can generally simulate the spatial structure of the BSISO, but give relatively weaker strength, shorter period, and faster transition of BSISO phases when compared with the observations. This partially limits the model's capability in forecasting the BSISO, with a useful skill of only 9 days. Two sets of hindcast experiments with improved atmospheric and atmosphere/ocean initial conditions (referred to as EXP1 and EXP2, respectively) are conducted to improve the BSISO forecast. The BSISO forecast skill is increased by 2 days with the optimization of atmospheric initial conditions only (EXP1), and is further increased by 1 day with the optimization of both atmospheric and oceanic initial conditions (EXP2). These changes lead to a final skill of 12 days, which is comparable to the skills of most models participated in the S2S Prediction Project. In EXP1 and EXP2, the BSISO forecast skills are improved for most initial phases, especially phases 1 and 2, denoting a better description for BSISO propagation from the tropical Indian Ocean to the western North Pacific. However, the skill is considerably low and insensitive to initial conditions for initial phase 6 and target phase 3, corresponding to the BSISO convection's active-to-break transition over the western North Pacific and BSISO convection's break-to-active transition over the tropical Indian Ocean and Maritime Continent. This prediction barrier also exists in many forecast models of the S2S Prediction Project. Our hindcast experiments with different initial conditions indicate that the remarkable model errors over the Maritime Continent and subtropical western North Pacific may largely account for the prediction barrier. [ABSTRACT FROM AUTHOR]

El Niño-Southern Oscillation (ENSO) is the strongest interannual signal that is produced by basinscale processes in the tropical Pacific, with significant effects on weather and climate worldwide. In the past, extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies. A hierarchy of coupled ocean-atmosphere models has been formulated; in terms of their complexity, they can be categorized into intermediate coupled models (ICMs), hybrid coupled models (HCMs), and fully coupled general circulation models (CGCMs). ENSO modeling has made signifiscant progress over the past decades, reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance. Meanwhile, ENSO exhibits great diversity and complexity as observed in nature, which still cannot be adequately captured by current state-of-the-art coupled models, presenting a challenge to ENSO modeling. We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China; some selected representative examples are presented here to review the current status of ENSO model developments and applications, which have been actively pursued with noticeable progress being made recently. As ENSO simulations are very sensitive to model formulations and process representations etc., dedicated efforts have been devoted to ENSO model developments and improvements. Now, different ocean-atmosphere coupled models have been available in China, which exhibit good model performances and have already had a variety of applications to climate modeling, including the Coupled Model Intercomparison Project Phase 6 (CMIP6). Nevertheless, large biases and uncertainties still exist in ENSO simulations and predictions, and there are clear rooms for their improvements, which are still an active area of researches and applications. Here, model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models, pinpointing to the areas where they need to be further improved for ENSO studies. These analyses provide valuable guidance for future improvements in ENSO simulations and predictions. [ABSTRACT FROM AUTHOR]

The main advancements of the Beijing Climate Center (BCC) climate system model from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to phase 6 (CMIP6) are presented, in terms of physical parameterizations and model performance. BCC-CSM1.1 and BCC-CSM1.1m are the two models involved in CMIP5, whereas BCC-CSM2-MR, BCC-CSM2-HR, and BCC-ESM1.0 are the three models configured for CMIP6. Historical simulations from 1851 to 2014 from BCC-CSM2-MR (CMIP6) and from 1851 to 2005 from BCC-CSM1.1m (CMIP5) are used for models assessment. The evaluation matrices include the following: (a) the energy budget at top-of-atmosphere; (b) surface air temperature, precipitation, and atmospheric circulation for the global and East Asia regions; (c) the sea surface temperature (SST) in the tropical Pacific; (d) sea-ice extent and thickness and Atlantic Meridional Overturning Circulation (AMOC); and (e) climate variations at different timescales, such as the global warming trend in the 20th century, the stratospheric quasi-biennial oscillation (QBO), the Madden–Julian Oscillation (MJO), and the diurnal cycle of precipitation. Compared with BCC-CSM1.1m, BCC-CSM2-MR shows significant improvements in many aspects including the tropospheric air temperature and circulation at global and regional scales in East Asia and climate variability at different timescales, such as the QBO, the MJO, the diurnal cycle of precipitation, interannual variations of SST in the equatorial Pacific, and the long-term trend of surface air temperature. [ABSTRACT FROM AUTHOR]

Using the sub-seasonal to seasonal forecast model of Beijing Climate Center, several key physical parameters are perturbed by the Latin hypercube sampling method to find a better configuration for representation of Madden–Julian oscillation (MJO) in the free-run simulation. We find that although model simulation is especially sensitive to some parameters, there are overall no significant linear relationships between model skill and any one of the parameters, and the optimum performance can be obtained by combined perturbations of multiple parameters. By optimization, MJO's spectrum, intensity, spatial structure and propagation, as well as the mean state and variance, are all improved to some extent, suggesting the correspondence and interrelation of model's performances in simulating different characteristics of MJO. Further, several sets of initialized hindcasts using the optimized parameters are conducted, and their results are compared with the hindcasts using only improved initial conditions. We show that with an optimized model, the forecast of MJO beyond 3-week lead time is not improved, and the maximum useful skill is only slightly increased, implying that a decrease of model error does not always translate into an increase of forecast skill at all lead time. However, the skill is obviously enhanced during lead times of 2–3 weeks for forecasts in most seasons and initial phases except for a few cases. Particularly, the deficiency in forecasting MJO's propagation from the Indian Ocean to the Pacific is relieved, further highlighting the positive contribution of reducing model error compared to previous work that only reduced initial condition error. In this study, we also show benefits of multi-scheme ensemble strategy in describing uncertainties of model error and initial condition error and thus improving MJO forecast. [ABSTRACT FROM AUTHOR]

The Quasi‐Biennial Oscillation (QBO) is the dominant mode of interannual variability in the tropical stratosphere, with easterly and westerly zonal wind regimes alternating over a period of about 28 months. It appears to influence the Northern Hemisphere winter stratospheric polar vortex and atmospheric circulation near the Earth's surface. However, the short observational record makes unequivocal identification of these surface connections challenging. To overcome this, we use a multicentury control simulation of a climate model with a realistic, spontaneously generated QBO to examine teleconnections with extratropical winter surface pressure patterns. Using a 30‐hPa index of the QBO, we demonstrate that the observed teleconnection with the Arctic Oscillation (AO) is likely to be real, and a teleconnection with the North Atlantic Oscillation (NAO) is probable, but not certain. Simulated QBO‐AO teleconnections are robust, but appear weaker than in observations. Despite this, inconsistency with the observational record cannot be formally demonstrated. To assess the robustness of our results, we use an alternative measure of the QBO, which selects QBO phases with westerly or easterly winds extending over a wider range of altitudes than phases selected by the single‐level index. We find increased strength and significance for both the AO and NAO responses, and better reproduction of the observed surface teleconnection patterns. Further, this QBO metric reveals that the simulated AO response is indeed likely to be weaker than observed. We conclude that the QBO can potentially provide another source of skill for Northern Hemisphere winter prediction, if its surface teleconnections can be accurately simulated. Key Points: QBO teleconnection with the winter Arctic Oscillation is likely to be real, but observations only weakly constrain its strengthAnalysis using new deep QBO phase measure increases the strength and significance of the winter surface teleconnectionsTeleconnections between the deep QBO and Arctic Oscillation simulated by the HadGEM3 climate model are likely weaker than those observed [ABSTRACT FROM AUTHOR]

ABSTRACT: The forecast skill of BCC‐CSM1.1 model in summer East Asian climate was evaluated with the decadal prediction experiments launched annually during 1961–2005. Results of the decadal prediction were compared with those of the historical simulation to estimate contribution of the initialization. Improved prediction skill is found for summer surface air temperature (SAT) in central eastern China measured by both root mean square error (RMSE) and anomaly correlation coefficient (ACC) for the forecast years 2–5. The decadal hindcast of precipitation in central eastern China shows increased skill in RMSE but not ACC. Such improvement in East Asia is related to enhanced prediction skill of the western Pacific (WP) sea surface temperature (SST) originated from the oceanic initialization. In the decadal hindcast, the lower tropospheric atmospheric circulation associated with warm WP exhibits an anticyclone over the South China Sea, which resembles the observation. The southwesterly increases over southeast China associated with warm WP, favouring higher SAT in central eastern China. This reveals that the decadal predictions could more realistically reproduce the relationship between summer East Asian atmospheric circulation and WP SST. The 4‐year average forecast within a decade shows that the initialization increases the ACC skill up to forecast years 4–7 for summer SAT in central eastern China. [ABSTRACT FROM AUTHOR]

The intra-seasonal oscillation (ISO) is a prominent feature of the East Asia summer monsoon. The Beijing Climate Center model is one of the IPCC models participating in the Coupled Model Inter-comparison Project (CMIP) 3 and CMIP5 experiments. This paper presents a systematic evaluation of ISO simulated by the Beijing Climate Center atmospheric general circulation model version 2.2 against observations. The model reasonably simulates some salient features of BSISO in terms of temporal spectrum, leading EOF modes, and vertical structure, however limitations are also evident. The strength of the BSISO is overestimated and the northward propagating rain belt is tilted southwest-northeast, which is also different from the observation. The model tends to produce unrealistically strong but shallow convection associated with the ISO, leading to a northward shift of the Western Pacific Subtropical High and the main rain band compared to observations. Process studies show that the anomalous convective heating associated with the wet model bias drives a Gill-type response, resulting in the northwesterly biased position of Western Pacific Subtropical High. The study has revealed how the interaction of moist processes and large-scale dynamics can lead to model bias in simulating the east Asian regional climate system and its variability (ISO in particular). Future improvements in model resolution and convection parameterization are expected to reduce such errors. [ABSTRACT FROM AUTHOR]

Upper-tropospheric ice cloud measurements from the Superconducting Submillimeter Limb Emission Sounder (SMILES) on the International Space Station (ISS) are used to study the diurnal cycle of upper-tropospheric ice cloud in the tropics and midlatitudes (40°S-40°N) and to quantitatively evaluate ice cloud diurnal variability simulated by 10 climate models. Over land, the SMILES-observed diurnal cycle has a maximum around 1800 local solar time (LST), while the model-simulated diurnal cycles have phases differing from the observed cycle by −4 to 12 h. Over ocean, the observations show much smaller diurnal cycle amplitudes than over land with a peak at 1200 LST, while the modeled diurnal cycle phases are widely distributed throughout the 24-h period. Most models show smaller diurnal cycle amplitudes over ocean than over land, which is in agreement with the observations. However, there is a large spread of modeled diurnal cycle amplitudes ranging from 20% to more than 300% of the observed over both land and ocean. Empirical orthogonal function (EOF) analysis on the observed and model-simulated variations of ice clouds finds that the first EOF modes over land from both observation and model simulations explain more than 70% of the ice cloud diurnal variations and they have similar spatial and temporal patterns. Over ocean, the first EOF from observation explains 26.4% of the variance, while the first EOF from most models explains more than 70%. The modeled spatial and temporal patterns of the leading EOFs over ocean show large differences from observations, indicating that the physical mechanisms governing the diurnal cycle of oceanic ice clouds are more complicated and not well simulated by the current climate models. [ABSTRACT FROM AUTHOR]

The multi-model ensemble (MME) of 20 models from the Coupled Model Intercomparison Project Phase Five (CMIP5) was used to analyze surface climate change in the 21st century under the representative concentration pathway RCP2.6, to reflect emission mitigation efforts. The maximum increase of surface air temperature (SAT) is 1.86°C relative to the pre-industrial level, achieving the target to limit the global warming to 2°C. Associated with the 'increase-peak-decline' greenhouse gases (GHGs) concentration pathway of RCP2.6, the global mean SAT of MME shows opposite trends during two time periods: warming during 2006-55 and cooling during 2056-2100. Our results indicate that spatial distribution of the linear trend of SAT during the warming period exhibited asymmetrical features compared to that during the cooling period. The warming during 2006-55 is distributed globally, while the cooling during 2056-2100 mainly occurred in the NH, the South Indian Ocean, and the tropical South Atlantic Ocean. Different dominant roles of heat flux in the two time periods partly explain the asymmetry. During the warming period, the latent heat flux and shortwave radiation both play major roles in heating the surface air. During the cooling period, the increase of net longwave radiation partly explains the cooling in the tropics and subtropics, which is associated with the decrease of total cloud amount. The decrease of the shortwave radiation accounts for the prominent cooling in the high latitudes of the NH. The surface sensible heat flux, latent heat flux, and shortwave radiation collectively contribute to the especial warming phenomenon in the high-latitude of the SH during the cooling period. [ABSTRACT FROM AUTHOR]

This study proposes primary diagnostic metrics to evaluate the integrated structure of interdecadal changes of East Asian climate in mid-summer (July-August) over the recent half-century (1955-2000) in numerical models. The metrics are applied to comprehensively examine the performance of BCC_AGCM (Beijing Climate Center atmospheric general circulation model) version 2.0.1. When forced by historical sea surface temperatures (SST), the ensemble simulation with the BCC_AGCM reasonably reproduced the coherent interdecadal changes of rainfall, temperature and circulation. The main feature of the 'southern-flooding-and-northern-drought' rainfall change is captured by the model. Correspondingly, the tropospheric cooling in the upper and middle troposphere, the southward shift of upper level westerly jet and weakening of the low-level southwesterly monsoon flow are also reproduced, as well as their relationships with rainfall changes. One of the main deficiencies of the simulation is that the amplitudes of the changes of tropospheric cooling and large-scale circulation are both much weaker than those in reanalysis, and they are consistent with the rainfall deficiency. Also, the upper and middle troposphere cooling center and decreasing of upper-level westerly jet axis shift westward in the model simulations compared with that in the observations. Overall, although BCC_AGCM shows problems in simulating the interdecadal changes of East Asia climate, especially the amplitude and locations of change centers, it reasonably represents the observed configuration of rainfall variation and the associated coherent temperature and circulation changes. Therefore, it could be further used to discuss the mechanisms of the interdecadal variation in East Asia. Meanwhile, the reasonably reproduced configuration of rainfall and its associated large-scale circulation by SST-forced runs indicate that the interdecadal variations in East Asia could mostly arise from the regional response to the global climate change. [ABSTRACT FROM AUTHOR]

A simple mass-flux cumulus parameterization scheme suitable for large-scale atmospheric models is presented. The scheme is based on a bulk-cloud approach and has the following properties: (1) Deep convection is launched at the level of maximum moist static energy above the top of the boundary layer. It is triggered if there is positive convective available potential energy (CAPE) and relative humidity of the air at the lifting level of convection cloud is greater than 75%; (2) Convective updrafts for mass, dry static energy, moisture, cloud liquid water and momentum are parameterized by a one-dimensional entrainment/detrainment bulk-cloud model. The lateral entrainment of the environmental air into the unstable ascending parcel before it rises to the lifting condensation level is considered. The entrainment/detrainment amount for the updraft cloud parcel is separately determined according to the increase/decrease of updraft parcel mass with altitude, and the mass change for the adiabatic ascent cloud parcel with altitude is derived from a total energy conservation equation of the whole adiabatic system in which involves the updraft cloud parcel and the environment; (3) The convective downdraft is assumed saturated and originated from the level of minimum environmental saturated equivalent potential temperature within the updraft cloud; (4) The mass flux at the base of convective cloud is determined by a closure scheme suggested by Zhang (J Geophys Res 107(D14), doi:, ) in which the increase/decrease of CAPE due to changes of the thermodynamic states in the free troposphere resulting from convection approximately balances the decrease/increase resulting from large-scale processes. Evaluation of the proposed convection scheme is performed by using a single column model (SCM) forced by the Atmospheric Radiation Measurement Program's (ARM) summer 1995 and 1997 Intensive Observing Period (IOP) observations, and field observations from the Global Atmospheric Research Program's Atlantic Tropical Experiment (GATE) and the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). The SCM can generally capture the convective events and produce a realistic timing of most events of intense precipitation although there are some biases in the strength of simulated precipitation. [ABSTRACT FROM AUTHOR]

Climate models participated in the High Resolution Model Intercomparison Project (HighResMIP) of Coupled Model Intercomparison Project 6 (CMIP6) are evaluated to reveal the impact of enhanced resolution in simulating the climatological distribution of precipitation over China. The multi-model mean (MME) of five models with 30–50 km horizontal resolution in the atmosphere (MME-50) had a better performance in reproducing the observed spatial patterns of precipitation over Northwest China and Southwest China than the MME of their lower-resolution (70–140 km) models (MME-100). Such an improvement is mainly attributed to the topographical rainfall reproduced by the higher-resolution models, which have the superiority of reproducing the local vertical circulation over the complex terrain. The MME-50 also improves the skill score of the 850-hPa southwesterly of the Indian-Burma trough relative to the MME-100, which may contribute to better simulation skill of precipitation over Southwest China. The MME-50 (0.92) has a close skill score to the MME-100 (0.91) in the simulation of East Asian summer monsoon, which explains why the MME-50 cannot improve the simulation skill of the precipitation over Southeast China and Northern China. The skill score of the precipitation over the Tibetan Plateau (TP) simulated by the MME-50 is even lower than the MME-100, revealing that simulating the climate over the high plateau is still a challenge for the high-resolution models. [ABSTRACT FROM AUTHOR]

Radiative forcing (RF) time series for total ozone from 1850 up to the present day are calculated based on historical simulations of ozone from 10 climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, RF is calculated for ozone fields prepared as an input for CMIP6 models without chemistry schemes and from a chemical transport model simulation. A radiative kernel for ozone is constructed and used to derive the RF. The ozone RF in 2010 (2005–2014) relative to 1850 is 0.35 W m−2 [0.08–0.61] (5–95% uncertainty range) based on models with both tropospheric and stratospheric chemistry. One of these models has a negative present-day total ozone RF. Excluding this model, the present-day ozone RF increases to 0.39 W m−2 [0.27–0.51] (5–95% uncertainty range). The rest of the models have RF close to or stronger than the RF time series assessed by the Intergovernmental Panel on Climate Change in the fifth assessment report with the primary driver likely being the new precursor emissions used in CMIP6. The rapid adjustments beyond stratospheric temperature are estimated to be weak and thus the RF is a good measure of effective radiative forcing. [ABSTRACT FROM AUTHOR]

The accuracy of air-sea flux algorithms significantly impacts the simulation performance of climate models. In this study, we evaluated nine widely-used air-sea flux algorithms: those used in the BCC model, the CAM model, the ECMWF model, and the WRF model (with three options), as well as three other commonly-used algorithms: COARE, UA, and VM. An offline comparison revealed significant discrepancies in the flux calculations obtained with different algorithms. Subsequently, we conducted nine sensitivity experiments by coupling these algorithms into the Community Atmosphere Model version 6 (CAM6) to assess the extent and manner in which the selection of flux algorithms influenced the simulated climate. The online simulations introduced complexities due to interactions between the atmosphere and surface fluxes, making the results more intricate. The iterative process of the model created negative feedback between wind speed and momentum flux, as well as between air temperature and heat flux, leading to inconsistencies between online and offline test results. Based on the comprehensive evaluation metric Distance between Indices of Simulation and Observation (DISO), a concept of combined or segmented algorithm was introduced, and a segmented algorithm based on wind speed was found resulting in an overall superior simulation performance compared to the previous nine experiments. • Nine widely used air-sea flux algorithms are evaluated offline and online with CAM. • Algorithms' performance varies across different regions and conditions. • On-offline deviation is caused by online negative wind-flux feedback. • A segmented algorithm is proposed to integrate the advantages of various algorithms. [ABSTRACT FROM AUTHOR]