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This study evaluates the decadal prediction skill of 13 forecast systems in predicting winter precipitation over Eurasia, contributing to the Decadal Climate Prediction Project of the Coupled Model Intercomparison Project Phase 6. Northeast Asia stands out as a region with improved decadal prediction skill for forecast years 2–5 due to the initialization. Observations show anticyclonic and cyclonic wind anomalies over the North Pacific and Northeast Asia, respectively, with southwesterly flow to the east of Northeast Asia. Ten forecast systems reproduce such circulation anomalies favoring abundant winter precipitation in Northeast Asia. The significant positive (negative) correlations between the detrended Northeast Asian precipitation (NEAP) and AMV (PDO-like) time series are reproduced by seven (nine) forecast systems. However, most forecast systems underestimate the correlation between the NEAP and the AMV, and have relatively low skill in predicting the PDO. Further improvements in these aspects will help to improve the decadal prediction skill of winter precipitation over Northeast Asia. The multi-model ensemble (MME) is able to reproduce both links of NEAP with AMV and PDO-like variability. The MME demonstrates significant skill and outperforms the individual forecast systems in predicting the NEAP for all 4-year averaged periods in the range of 1–8 years, demonstrating the benefits of using the ensemble mean of multiple models. [ABSTRACT FROM AUTHOR]

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]

This paper provides a systematic evaluation of the ability of 12 Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the spatial inhomogeneity of the atmospheric carbon dioxide (CO2) concentration. The multi-model ensemble mean (MME) can reasonably simulate the increasing trend of CO2 concentration from 1850 to 2014, compared with the observation data from the Scripps CO2 Program and CMIP6 prescribed data, and improves upon the CMIP5 MME CO2 concentration (which is overestimated after 1950). The growth rate of CO2 concentration in the northern hemisphere (NH) is higher than that in the southern hemisphere (SH), with the highest growth rate in the mid-latitudes of the NH. The MME can also reasonably simulate the seasonal amplitude of CO2 concentration, which is larger in the NH than in the SH and grows in amplitude after the 1950s (especially in the NH). Although the results of the MME are reasonable, there is a large spread among ESMs, and the difference between the ESMs increases with time. The MME results show that regions with relatively large CO2 concentrations (such as northern Russia, eastern China, Southeast Asia, the eastern United States, northern South America, and southern Africa) have greater seasonal variability and also exhibit a larger inter-model spread. Compared with CMIP5, the CMIP6 MME simulates an average spatial distribution of CO2 concentration that is much closer to the site observations, but the CMIP6-inter-model spread is larger. The inter-model differences of the annual means and seasonal cycles of atmospheric CO2 concentration are both attributed to the differences in natural sources and sinks of CO2 between the simulations. [ABSTRACT FROM AUTHOR]

In the late twentieth century, global mean surface air temperature especially on land is continuously warming. Our analyses show that the global mean of dust increased since 1980, using the Modern-Era Retrospective Analysis version 2 for Research and Applications (MERRA-2) reanalysis data. This variation of global dust is mainly contributed by the dust increase outside of dust core areas (i.e. high dust mass concentration region). The causes to result in global dust variations are explored. In dust core areas, surface wind is the primary driving factor for surface dust, both of which show no remarkable trends of increase or decrease since 1980. In areas outside of the core areas, especially in arid and semi-arid areas in North and Middle Asia, surface air temperature warming is the primary impact factor causing the dust increase. An increase in surface air temperature is accompanied by enhancement of atmospheric instability which can trigger more upward motion and bring more dust. All 9 Earth System Models (ESMs) for the Aerosol Chemistry Model Intercomparison Project (AerChemMIP) reproduce the reasonable spatial distribution and seasonal cycle of dust in the present day. But only a few models such as BCC-ESM1 and GFDL-ESM4 simulate the increasing trend of dust similar to MERRA-2. While the primary impact of wind in dust core areas, and surface temperature outside of the core areas, especially in middle to high latitudes in Eurasian continent, are presented in most ESMs. [ABSTRACT FROM AUTHOR]

The sub-seasonal to seasonal (S2S) prediction of precipitation is not only a hot topic but also a challenge. The traditional ensemble mean and ensemble probabilistic forecast methods cannot avoid the uncertainty of the initial value in the S2S prediction. Is there a more suitable ensemble postprocessing method for the S2S prediction? In this study, the hindcast data during the 1999–2010 summers from nine operational models in the international S2S prediction project has been evaluated. Based on the quantitative objective precipitation evaluation methods, such as the Equitable Threat Score and frequency bias methods, the climatological spatio-temporal distribution of the optimal probabilistic threshold on the S2S scale is proven to exist, and it can be used as the standard to judge how many ensemble members are credible. Then, different ensemble forecast strategies are adopted in different regions to construct a Deterministic Ensemble Forecast using an Optimal Probabilistic Threshold (DEFOPT) method for precipitation prediction. The hindcast data of eight S2S models outside the period 1999–2010 are used to verify the applicability of the DEFOPT method by using the historical optimal probabilistic threshold during 1999–2010. The results show that the DEFOPT outperforms the deterministic forecast from one initial value, the ensemble mean, and the deterministic ensemble forecast using a probabilistic threshold for the occurrence days of rainfall at the 1 mm and 5 mm thresholds (≥ 1 mm and ≥ 5 mm) over China during each pentad in most S2S models. [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]

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]

BCC-ESM1 is the first version of the Beijing Climate Center's Earth System Model, and is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is the only CMIP6-endorsed MIP in which BCC-ESM1 is involved. All AerChemMIP experiments in priority 1 and seven experiments in priorities 2 and 3 have been conducted. The DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations have also been run as the entry card of CMIP6. The AerChemMIP outputs from BCC-ESM1 have been widely used in recent atmospheric chemistry studies. To facilitate the use of the BCC-ESM1 datasets, this study describes the experiment settings and summarizes the model outputs in detail. Preliminary evaluations of BCC-ESM1 are also presented, revealing that: the climate sensitivities of BCC-ESM1 are well within the likely ranges suggested by IPCC AR5; the spatial structures of annual mean surface air temperature and precipitation can be reasonably captured, despite some common precipitation biases as in CMIP5 and CMIP6 models; a spurious cooling bias from the 1960s to 1990s is evident in BCC-ESM1, as in most other ESMs; and the mean states of surface sulfate concentrations can also be reasonably reproduced, as well as their temporal evolution at regional scales. These datasets have been archived on the Earth System Grid Federation (ESGF) node for atmospheric chemistry studies. [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]

The Beijing Climate Center Earth System Model version 1 (BCC-ESM1) is the first version of a fully coupled Earth system model with interactive atmospheric chemistry and aerosols developed by the Beijing Climate Center, China Meteorological Administration. Major aerosol species (including sulfate, organic carbon, black carbon, dust, and sea salt) and greenhouse gases are interactively simulated with a whole panoply of processes controlling emission, transport, gas-phase chemical reactions, secondary aerosol formation, gravitational settling, dry deposition, and wet scavenging by clouds and precipitation. Effects of aerosols on radiation, cloud, and precipitation are fully treated. The performance of BCC-ESM1 in simulating aerosols and their optical properties is comprehensively evaluated as required by the Aerosol Chemistry Model Intercomparison Project (AerChemMIP), covering the preindustrial mean state and time evolution from 1850 to 2014. The simulated aerosols from BCC-ESM1 are quite coherent with Coupled Model Intercomparison Project Phase 5 (CMIP5)-recommended data, in situ measurements from surface networks (such as IMPROVE in the US and EMEP in Europe), and aircraft observations. A comparison of modeled aerosol optical depth (AOD) at 550 nm with satellite observations retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR) and surface AOD observations from the AErosol RObotic NETwork (AERONET) shows reasonable agreement between simulated and observed AOD. However, BCC-ESM1 shows weaker upward transport of aerosols from the surface to the middle and upper troposphere, likely reflecting the deficiency of representing deep convective transport of chemical species in BCC-ESM1. With an overall good agreement between BCC-ESM1 simulated and observed aerosol properties, it demonstrates a success of the implementation of interactive aerosol and atmospheric chemistry in BCC-ESM1. [ABSTRACT FROM AUTHOR]

It is well known that the stratospheric quasi-biennial oscillation (QBO) is forced by equatorial waves with different horizontal/vertical scales, including Kelvin waves, mixed Rossby–gravity (MRG) waves, inertial gravity waves (GWs), and mesoscale GWs, but the relative contribution of each wave is currently not very clear. Proper representation of these waves is critical to the simulation of the QBO in general circulation models (GCMs). In this study, the vertical resolution in the Beijing Climate Center Atmospheric General Circulation Model (BCC-AGCM) is increased to better represent large-scale waves, and a mesoscale GW parameterization scheme, which is coupled to the convective sources, is implemented to provide unresolved wave forcing of the QBO. Results show that BCC-AGCM can spontaneously generate the QBO with realistic periods, amplitudes, and asymmetric features between westerly and easterly phases. There are significant spatiotemporal variations of parameterized convective GWs, largely contributing to a great degree of variability in the simulated QBO. In the eastward wind shear of the QBO at 20 hPa, forcing provided by resolved waves is 0.1–0.2 m s−1 day−1 and forcing provided by parameterized GWs is ~0.15 m s−1 day−1. On the other hand, westward forcings by resolved waves and parameterized GWs are ~0.1 and 0.4–0.5 m s−1 day−1, respectively. It is inferred that the eastward forcing of the QBO is provided by both Kelvin waves and mesoscale convective GWs, whereas the westward forcing is largely provided by mesoscale GWs. MRG waves barely contribute to the formation of the QBO in the model. [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]

As one of the participants in the Subseasonal to Seasonal (S2S) Prediction Project, the China Meteorological Administration (CMA) has adopted several model versions to participate in the S2S Project. This study evaluates the models' capability to simulate and predict the Madden-Julian Oscillation (MJO). Three versions of the Beijing Climate Center Climate System Model (BCC-CSM) are used to conduct historical simulations and re-forecast experiments (referred to as EXP1, EXP1-M, and EXP2, respectively). In simulating MJO characteristics, the newly-developed high-resolution BCC-CSM outperforms its predecessors. In terms of MJO prediction, the useful prediction skill of the MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M, and further to 24 days in EXP2. Within the first forecast week, the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction skill. However, during forecast weeks 2–3, EXP2 shows little advantage compared with EXP1-M because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–3. Particularly at initial phases 2–3, EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection, leading to the highest prediction skill of the MJO. Our results reveal that, during the participation of the CMA models in the S2S Project, both the improved model initialization and updated model physics played positive roles in improving MJO prediction. Future efforts should focus on improving the model physics to better simulate MJO convection over the Maritime Continent and further improve MJO prediction at long lead times. [ABSTRACT FROM AUTHOR]

By conducting several sets of hindcast experiments using the Beijing Climate Center Climate System Model, which participates in the Sub-seasonal to Seasonal (S2S) Prediction Project, we systematically evaluate the model's capability in forecasting MJO and its main deficiencies. In the original S2S hindcast set, MJO forecast skill is about 16 days. Such a skill shows significant seasonal-to-interannual variations. It is found that the model-dependent MJO forecast skill is more correlated with the Indian Ocean Dipole (IOD) than with the El Niño-Southern Oscillation. The highest skill is achieved in autumn when the IOD attains its maturity. Extended skill is found when the IOD is in its positive phase. MJO forecast skill's close association with the IOD is partially due to the quickly strengthening relationship between MJO amplitude and IOD intensity as lead time increases to about 15 days, beyond which a rapid weakening of the relationship is shown. This relationship transition may cause the forecast skill to decrease quickly with lead time, and is related to the unrealistic amplitude and phase evolutions of predicted MJO over or near the equatorial Indian Ocean during anomalous IOD phases, suggesting a possible influence of exaggerated IOD variability in the model. The results imply that the upper limit of intraseasonal predictability is modulated by large-scale external forcing background state in the tropical Indian Ocean. Two additional sets of hindcast experiments with improved atmosphere and ocean initial conditions (referred to as S2S_IEXP1 and S2S_IEXP2, respectively) are carried out, and the results show that the overall MJO forecast skill is increased to 21-22 days. It is found that the optimization of initial sea surface temperature condition largely accounts for the increase of the overall MJO forecast skill, even though the improved initial atmosphere conditions also play a role. For the DYNAMO/CINDY field campaign period, the forecast skill increases to 27 days in S2S_IEXP2. Nevertheless, even with improved initialization, it is still difficult for the model to predict MJO propagation across the western hemisphere-western Indian Ocean area and across the eastern Indian Ocean-Maritime Continent area. Especially, MJO prediction is apparently limited by various interrelated deficiencies (e.g., overestimated IOD, shorter-than-observed MJO life cycle, Maritime Continent prediction barrier), due possibly to the model bias in the background moisture field over the eastern Indian Ocean and Maritime Continent. Thus, more efforts are needed to correct the deficiency in model physics in this region, in order to overcome the well-known Maritime Continent predictability barrier. [ABSTRACT FROM AUTHOR]

The possible impact of the stratospheric polar vortex on East Asian spring rainfall and the representation of this effect in seasonal forecast models are assessed. A strong stratospheric polar vortex is typically associated with dry conditions across Southeastern China and wet conditions across Korea and Japan in spring. Seasonal forecast models have a decent skill of forecasting the stratospheric polar vortex strength in March. However, they show a wide spread in the predictability of East Asian spring rainfall, possibly due to the underrepresentation of the linkage between the stratospheric polar vortex and East Asian rainfall. The dry impact of strong polar vortex on Southeastern China is forecasted, but the wet impact on Korea and Japan is missing. Tropospheric positive height anomalies over Lake Baikal extend farther equatorward in East Asia during a strong vortex, corresponding to an anomalous anticyclone and less rainfall across Southeastern China. In contrast, the observed anomalous cyclonic shear at 200 hPa and the observed anomalous cyclone at 850 hPa in spring are not realistically forecasted over Northeast Asia, explaining the low skill of producing the wet anomalies in Korea and Japan by models. All models can forecast the wet pattern in East Asia during the El Niño spring. The observed southwesterly anomalies along the coastal China, Korea, and Japan following El Niño are also forecasted by models. Compared with the remote impact of El Niño, the downward impact of the stratosphere on East Asian spring rainfall is still a challenge for most models. [ABSTRACT FROM AUTHOR]

A modified thermodynamic sea ice model suitable for large-scale climate simulations is described. Originated from the Winton's three-layer model framework, this new model includes several improvements in the vertical thermodynamics: (1) the number of ice layers increases from two to three; (2) the snow heat capacity is included; (3) a vertically varying salinity profile is implemented; and (4) a temperature- and salinity-dependent heat conductivity parameterization scheme is introduced. A non-iterative fully implicit time-stepping scheme similar to Winton's model is used to calculate the temperature of ice and snow. Results from a series of one-dimensional experiments show that equilibrium ice thickness in the modified model is increased by 45 cm when compared with the original Winton's model. All modifications mentioned above contribute to this change of ice thickness, among which the increase of ice layer has the most significant effect. Experiments using the Modular Ocean Model version 4 (MOM4) coupled with the modified model show an improved sea ice simulation which includes an increase in both the sea ice volume and thickness over the entire Arctic region, confirming the above founding. However, contrary model behavior exhibits when the snow heat capacity is considered that warrants further investigation. • A modified thermodynamic sea ice model is described. • The number of ice layer is increased and the snow heat capacity is considered. • Implementation of a vertically varying salinity profile in sea ice model. • Implementation of a heat conductivity parameterization scheme in sea ice model. • Ice thickness simulation is improved due to modifications in sea ice thermodynamic. [ABSTRACT FROM AUTHOR]

This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge-satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011-14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events. [ABSTRACT FROM AUTHOR]

The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center (BCC GODAS2.0) has been run daily in a pre-operational mode. It spans the period 1990 to the present day. The goal of this paper is to introduce the main components and to evaluate BCC GODAS2.0 for the user community. BCC GODAS2.0 consists of an observational data preprocess, ocean data quality control system, a three-dimensional variational (3DVAR) data assimilation, and global ocean circulation model [Modular Ocean Model 4 (MOM4)]. MOM4 is driven by six-hourly fluxes from the National Centers for Environmental Prediction. Satellite altimetry data, SST, and in-situ temperature and salinity data are assimilated in real time. The monthly results from the BCC GODAS2.0 reanalysis are compared and assessed with observations for 1990-2011. The climatology of the mixed layer depth of BCC GODAS2.0 is generally in agreement with that ofWorld Ocean Atlas 2001. The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales. Performances in predicting variations in the SST using BCC GODAS2.0 are evaluated. The standard deviation of the SST in BCC GODAS2.0 agrees well with observations in the tropical Pacific. BCC GODAS2.0 is able to capture the main features of El Ni˜no Modoki I and Modoki II, which have different impacts on rainfall in southern China. In addition, the relationships between the Indian Ocean and the two types of El Ni˜no Modoki are also reproduced. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive assessment of Asian summer monsoon prediction skill as a function of lead time and its relationship to sea surface temperature prediction using the seasonal hindcasts of the Beijing Climate Center Climate System Model, BCC CSM1.1(m). For the South and Southeast Asian summer monsoon, reasonable skill is found in the model's forecasting of certain aspects of monsoon climatology and spatiotemporal variability. Nevertheless, deficiencies such as significant forecast errors over the tropical western North Pacific and the eastern equatorial Indian Ocean are also found. In particular, overestimation of the connections of some dynamical monsoon indices with large-scale circulation and precipitation patterns exists in most ensemble mean forecasts, even for short lead-time forecasts. Variations of SST, measured by the first mode over the tropical Pacific and Indian oceans, as well as the spatiotemporal features over the Ni˜no3.4 region, are overall well predicted. However, this does not necessarily translate into successful forecasts of the Asian summer monsoon by the model. Diagnostics of the relationships between monsoon and SST show that difficulties in predicting the South Asian monsoon can be mainly attributed to the limited regional response of monsoon in observations but the extensive and exaggerated response in predictions due partially to the application of ensemble average forecasting methods. In contrast, in spite of a similar deficiency, the Southeast Asian monsoon can still be forecasted reasonably, probably because of its closer relationship with large-scale circulation patterns and El Ni˜no-Southern Oscillation. [ABSTRACT FROM AUTHOR]

A Deterministic Time-lagged Ensemble Forecast using a Probabilistic Threshold (DEFPT) method is suggested for improving summer 6–15 day categorical precipitation prediction in China from the Beijing Climate Center Atmospheric General Circulation Model version 2.1 (BCC_AGCM2.1). It is based on a time-lagged ensemble system that consists of 13 ensemble members separated sequentially at 6 hour intervals lagging the last three days. The DEFPT is not intended to predict the probability of rainfall, but rather to forecast rainfall (yes/no) occurrence for different categories of precipitation at any model grid box. A given categorical precipitation is forecasted to occur at one gridbox only when the ensemble probability for that categorical precipitation exceeds a certain threshold. This method is useful for providing an estimate of whether precipitation events will occur to decision-makers based on probabilistic forecasts during days 6–15. A large number of hindcast experiments for 1996–2005 summers reveal that this threshold can be best (and empirically) set as 5/13 and 4/13 respectively for the 6–15 day prediction of 1 + mm (i.e., above 1 mm per day) and 5 + mm rainfall events, using the Relative Operating Characteristic (ROC) curve, the Equitable Threat Score (ETS), the Hanssen and Kuipers (HK) score, and frequency bias (BIA) to achieve best prediction performance. With this set of thresholds, the DEFPT shows skill improvement over the corresponding single deterministic forecast using one initial value and the Time-Lagged Average Forecast (LAF) ensemble method. Similar improvements by the DEFPT are also found for the prediction of several other categories of precipitation between 1 + mm and 10 + mm per day. Application of DEFPT to larger ensemble size and BCC_AGCM version 2.2 with a higher horizontal resolution also demonstrates the effectiveness of the DEFPT for 6–15 day categorical precipitation forecasts. [ABSTRACT FROM AUTHOR]

Using hindcasts of the Beijing Climate Center Climate System Model, the relationships between interannual variability (IAV) and intraseasonal variability (ISV) of the Asian-western Pacific summer monsoon are diagnosed. Predictions show reasonable skill with respect to some basic characteristics of the ISV and IAV of the western North Pacific summer monsoon (WNPSM) and the Indian summer monsoon (ISM). However, the links between the seasonally averaged ISV (SAISV) and seasonal mean of ISM are overestimated by the model. This deficiency may be partially attributable to the overestimated frequency of long breaks and underestimated frequency of long active spells of ISV in normal ISM years, although the model is capable of capturing the impact of ISV on the seasonal mean by its shift in the probability of phases. Furthermore, the interannual relationships of seasonal mean, SAISV, and seasonally averaged long-wave variability (SALWV; i.e., the part with periods longer than the intraseasonal scale) of the WNPSM and ISM with SST and low-level circulation are examined. The observed seasonal mean, SAISV, and SALWV show similar correlation patterns with SST and atmospheric circulation, but with different details. However, the model presents these correlation distributions with unrealistically small differences among different scales, and it somewhat overestimates the teleconnection between monsoon and tropical central-eastern Pacific SST for the ISM, but underestimates it for the WNPSM, the latter of which is partially related to the too-rapid decrease in the impact of El Niño-Southern Oscillation with forecast time in the model. [ABSTRACT FROM AUTHOR]

A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model, version 2.0.1. The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs, all at the same forecast valid time. This lagged average forecast (LAF) method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean. Our analyses of the Equitable Threat Score, the Hanssen and Kuipers Score, and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d and 5 mm d in many regions of China, and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members. In particular, significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40%-50% in the summer season; these regions include northeastern and central to southern China, and the southeastern Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The nocturnal precipitation in the Sichuan Basin in summer has been studied in many previous works. This paper expands the study on the diurnal cycle of precipitation in the Sichuan Basin to the whole year. Results show that the nocturnal precipitation has a specific quasi-stationary feature in the basin. It occurs not only in summer but also in other three seasons, even more remarkable in spring and autumn than in summer. There is a prominent eastward timing delay in the nocturnal precipitation, that is, the diurnal peak of precipitation occurs at early-night in the western basin whereas at late-night in the center and east of the basin. The Tibetan Plateau plays an essential role in the formation of this quasi-stationary nocturnal precipitation. The early-night peak of precipitation in the western basin is largely due to strong ascending over the plateau and its eastern lee side. In the central and eastern basin, three coexisting factors contribute to the late-night peak of precipitation. One is the lower-tropospheric southwesterly flow around the southeastern edge of the Tibetan Plateau, which creates a strong cyclonic rotation and ascendance in the basin at late-night, as well as brings abundant water vapor. The second is the descending motion downslope along the eastern lee side of the plateau, together with an air mass accumulation caused by the warmer air mass transport from the southeast of the Yunnan-Guizhou Plateau, creating a diabatic warming at low level of the troposphere in the central basin. The third is a cold advection from the plateau to the basin at late-night, which leads to a cooling in the middle troposphere over the central basin. All these factors are responsible for precipitation to occur at late-night in the central to eastern basin. [ABSTRACT FROM AUTHOR]

Seasonal forecasting models have a harder time accurately predicting regional precipitation anomalies in East Asia than the large‐scale drivers of these precipitation anomalies. These large‐scale drivers include both sea surface temperature (SST) anomalies and conditions in the polar stratosphere. A maximum covariance analysis is used to isolate the SST and stratospheric patterns most associated with anomalous East Asian precipitation, which are employed to correct seasonal forecasts by projecting the forecasted stratospheric circulation and SST onto the observed combined modes. The nonuniform predictability of East Asian rainfall in seasonal forecast models is improved after error correction with the observed linkage between the stratosphere–tropical ocean modes and East Asian rainfall. This method should be helpful for improving rainfall forecasts in other regions as well. Plain Language Summary: Seasonal predictability of East Asian rainfall in summer is mainly associated with sea surface temperatures (SSTs) across the tropical Pacific and Indian Oceans. In contrast, East Asian rainfall in spring can be affected by both the state of tropical oceans and downward propagation of extratropical stratospheric variability. This study reports the most common combinations between the extratropical stratosphere and tropical SST in early spring, which in turn are associated with East Asian rainfall variations in spring. Rainfall in some regions like Japan and near the China‐Russia border is poorly forecasted in most seasonal models. After error correction based on the physical linkage between the most frequent stratosphere–tropical SST combinations and East Asian rainfall, an improvement especially in less predictable regions is identified in seasonal forecast models. Key Points: A novel method is proposed to improve (i.e., error correct) seasonal forecasts of East Asian spring precipitationMaximum covariance analysis is used to identify large‐scale drivers associated with rainfallThese drivers are better predicted by models than rainfall, and can be utilized to improve upon the nonuniform predictability of East Asian spring rainfall [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]

To analyze the middle-to-lower-troposphere atmospheric thermal contrast between the middle latitude over the Asian continent and over its eastern adjacent ocean near Japan, an empirical orthogonal function (EOF) analysis of the 40-yr ECMWF Re-Analysis (ERA-40) data of the June–August (JJA) 500-hPa geopotential height over the Asia–Pacific area (10°–80°N, 60°–180°E) during 1958–2000 was done. It shows that the dominating pattern of the thermal contrast may well be represented by a “seesaw” of 500-hPa geopotential height anomalies between a land area (40°–55°N, 75°–90°E) and an oceanic area (35°–42.5°N, 140°– 150°E). An index showing the difference between the two areas is defined as the middle-latitude land–sea thermal contrast index (LSI). The LSI has significant interannual and interdecadal variability. Its interannual variation is mainly attributed to the atmospheric thermal condition over the ocean, which has a remarkably regional unique feature, while the interdecadal variability is greatly attributed to that over the land. The LSI has a close connection to the East Asian summer precipitation. The results show that large (small) LSI is related to high (low) summer precipitation in the middle to lower reaches of the Yangtze River, Korea, Japan, and its eastern adjacent ocean at the same latitude, and low (high) precipitation in the South China Sea and tropical western Pacific, as well as low (high) precipitation in north China and high-latitude northeast Asia. The pattern of correlation between LSI and precipitation resembles the spatial distribution of the principle EOF mode of year-to-year precipitation variations. Furthermore, the variation of LSI is highly correlated to the time series of the first EOF mode of summer precipitation anomalies. This suggests that the middle-latitude land–sea thermal contrast is one of important factors to influence on the summer precipitation variations over the area from the whole East Asia to the western Pacific. The possible physical mechanisms of the land–sea thermal contrast impacting the East Asian summer monsoon precipitation are also investigated. [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]

This study aimed to examine the spatio-temporal variations in the atmospheric boundary layer height (ABLH) over the Tarim Basin (TB). Monthly ABLH data from the ERA-Interim dataset from January 1979 to December 2018 were used. Periodicity analysis and the Mann–Kendall Abrupt Changes test were employed to identify the change cycle and abrupt change year of the boundary layer height. The Empirical Orthogonal Function (EOF) method was utilized to determine the spatial distribution of the boundary layer height, and the RF method was used to establish the relationship between the ABLH and influencing factors. The results demonstrated that the highest values of ABLH (over 1900 m) were observed in the middle parts of the study area in June, and the ABLH exhibited a significant increase over the TB throughout the study period. Abrupt changes in the ABLH were also identified in 2004, as well as in 2-, 5-, 9-, and 15-year changing cycles. The first EOF ABLH mode indicated that the middle and northeast regions are relatively high ABLH areas within the study area. Additionally, the monthly variations in ABLH show a moderately positive correlation with air temperature, while exhibiting a negative correlation with air pressure and relative humidity. [ABSTRACT FROM AUTHOR]

Progress and persistent biases in the simulation of the stratospheric polar vortex from three generations of Coupled Model Intercomparison Projects (CMIPs) are assessed. On average, the stratospheric cold bias is largest in CMIP3, but is improved in CMIP5 and CMIP6. The climatological ridge in the stratosphere over the North Pacific is underestimated persistently across CMIPs. Four parameters of the stratospheric polar vortex are evaluated among models and among CMIPs, and some common biases are identified for most models, including the too-large size of the vortex periphery, overstrong strength, too-small aspect ratio of the vortex shape, and too-westward displaced a vortex centroid. Intermodel spread in some parameters is highly correlated with the sea surface temperature (SST) bias in northern tropical oceans. Namely, a cold SST bias in the northern tropical Pacific is associated with a too-strong and too-large polar vortex, and a cold SST bias in the northern tropical Atlantic seems to be related to the westward bias of the vortex centroid. The implications of biases in the mean state of the vortex for stratospheric events such as sudden stratospheric warmings (SSWs) are also identified in this study. Models with a climatological vortex that is too strong, has too low an aspect ratio, or has a westward-biased centroid usually produce fewer SSWs, whereas ones with weaker strength, high aspect ratio, and eastward-biased centroid produce more. Based on the multimodel mean, the biases of all parameters have improved across three generations of CMIPs, although persistent biases in some individual models exist across CMIPs. Intermodel relationships between the polar vortex and SST highlights the important role of the SST simulation for the stratosphere. [ABSTRACT FROM AUTHOR]

The Antarctic stratospheric final warming (SFW) is usually simulated with a substantial delay in climate models, and the corresponding temperatures in austral spring are lower than observations, implying insufficient stratospheric wave drag. To investigate the role of orographic gravity wave drag (GWD) in modeling the Antarctic SFW, in this study the orographic GWD parameterization scheme is modified in the middle-atmosphere version of the Beijing Climate Center Atmospheric General Circulation Model. A pair of simulations are conducted to compare two orographic GWD schemes in simulating the breakdown of the stratospheric polar vortex over Antarctica. The control simulation with the default orographic GWD scheme exhibits delayed vortex breakdown and the cold-pole bias seen in most climate models. In the simulation with modified orographic GWD scheme, the simulated vortex breaks down earlier by 8 days, and the associated cold-pole bias is reduced by more than 2 K. The modified scheme provides stronger orographic GWD in the lower stratosphere, which drives an accelerated polar downwelling branch of the Brewer–Dobson circulation and, in turn, produces adiabatic warming. Our study suggests that modifying orographic GWD parameterizations in climate models would be a valid way of improving the SFW simulation over Antarctica. [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]

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]

Chemistry plays an indispensable role in investigations of the atmosphere; however, many climate models either ignore or greatly simplify atmospheric chemistry, limiting both their accuracy and their scope. We present the development and evaluation of the online global atmospheric chemical model BCC-GEOS-Chem v1.0, coupling the GEOS-Chem chemical transport model (CTM) as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model (BCC-AGCM). The GEOS-Chem atmospheric chemistry component includes detailed tropospheric HOx – NOx –volatile organic compounds–ozone–bromine–aerosol chemistry and online dry and wet deposition schemes. We then demonstrate the new capabilities of BCC-GEOS-Chem v1.0 relative to the base BCC-AGCM model through a 3-year (2012–2014) simulation with anthropogenic emissions from the Community Emissions Data System (CEDS) used in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The model captures well the spatial distributions and seasonal variations in tropospheric ozone, with seasonal mean biases of 0.4–2.2 ppbv at 700–400 hPa compared to satellite observations and within 10 ppbv at the surface to 500 hPa compared to global ozonesonde observations. The model has larger high-ozone biases over the tropics which we attribute to an overestimate of ozone chemical production. It underestimates ozone in the upper troposphere which is likely due either to the use of a simplified stratospheric ozone scheme or to biases in estimated stratosphere–troposphere exchange dynamics. The model diagnoses the global tropospheric ozone burden, OH concentration, and methane chemical lifetime to be 336 Tg, 1.16×106 molecule cm -3 , and 8.3 years, respectively, which is consistent with recent multimodel assessments. The spatiotemporal distributions of NO2 , CO, SO2 , CH2O , and aerosol optical depth are generally in agreement with satellite observations. The development of BCC-GEOS-Chem v1.0 represents an important step for the development of fully coupled earth system models (ESMs) in China. [ABSTRACT FROM AUTHOR]

Using 20 quasi-biennial oscillation (QBO)-resolving models from phases 5/6 of the Coupled Model Intercomparison Project (CMIP5/6), this study examines the projected Southern Hemisphere (SH) extratropical response to the QBO. Nine of the 22 models simulate decelerated circumpolar westerlies during easterly QBO (EQBO) in the historical climate as is observed, though only ∼30% of the observed change is reproduced in the multimodel ensemble mean (MME) of these high-skill models. These high-skill models project an enhanced stratospheric QBO teleconnection for both emissions scenarios. Further, the stratospheric wind anomaly in high latitudes is projected to move to midlatitudes in future scenarios. The climatological subtropical jet is projected to strengthen, while tropical easterlies are projected to weaken. As a consequence, upward wave activity in the future appears to become more sensitive to the QBO phase. Enhanced upward propagation of waves in mid- to high latitudes during EQBO are much stronger in future scenarios than in historical simulations. The anomalous downwelling over the Antarctic, as part of the Brewer–Dobson deep branch response to EQBO, is also projected to strengthen, corresponding to increased warm anomalies. In future scenarios, the areal extent of the deep convective response to EQBO over the Maritime Continent widens and includes a sharper reduction in outgoing longwave radiation, albeit with southward expansion from Indonesia to Australia. The enhancement and spatial shift in the stratospheric polar vortex pathway and tropical convection pathway subsequently lead to changes in the tropospheric QBO signal. An annular mode–like response forms in the troposphere and near-surface in the present climate, whereas this pattern shifts farther equatorward in future projections with circulation anomalies in the tropical Indian Ocean amplifying. Significance Statement: The influence of the equatorial stratospheric quasi-biennial oscillation (QBO) has been reported to intensify in the Northern Hemisphere under climate change, even as the QBO wind magnitude weakens. It is still unknown whether the influence of the QBO on the Southern Hemisphere intensifies or weakens in a warm climate. Using simulations from multiple models, this study finds that the influence of the QBO on the Southern Hemisphere is projected to strengthen in most models even as the QBO weakens. Two QBO pathways are explored, including the stratospheric polar vortex route and the tropical convection pathway, both of which are projected to amplify in both the moderate- and high-emissions scenarios. In addition to the amplification of the QBO signals in the Southern Hemisphere extratropics, an equatorward shift of the maximum anomalies is also projected. That is, the maximum easterly anomalies in the Antarctic stratosphere during easterly QBO and the annular mode–like pattern in the troposphere or the near-surface shifts farther equatorward. [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]

Predictability of East Asian cold surges is studied using daily data from the hindcasts of 45-day integrations by the NCEP Climate Forecast System version 2 (CFSv2). Prediction skills of the CFSv2 in forecasting cold surges, their annual variation, and their physical links to large-scale atmospheric circulation patterns are examined. Results show that the climatological characteristics of the East Asian winter monsoon can be reasonably reproduced by the CFSv2. The model can well capture the frequency, intensity, and location of cold surges at a lead time of about two weeks. Obviously, fewer-than-observed cold surge days are found in the predictions when the lead time is above 14 days. The spatiotemporal evolutions of high-, mid-, and low-level circulation patterns during cold surge occurrences are all accurately indicated in the CFSv2 prediction. Except for precipitation, the other variables associated with cold surges, such as geopotential height, wind, sea level pressure, and surface air temperature, exhibit higher skills. The lead time of skillful prediction of precipitation is limited to around 1 week, with systematic wet biases over the South China Sea, the Philippine Islands, and the northwest Pacific, but dry biases over India, the Indo-China Peninsula, and most high-latitude regions. Wave train-like patterns of geopotential height and wind differ distinguishably when cold surges occur in northern and southern regions (using 35°N as the dividing line), and the CFSv2 gives a consistent prediction to these anomalous patterns. A weaker-than-observed Siberian high and weaker northerly winds over eastern China are found in the predictions especially at longer lead times. [ABSTRACT FROM AUTHOR]

Using 25 quasi-biennial oscillation (QBO)-resolving models from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5/6), this study systematically explores the Southern Hemisphere (SH) extratropical response to the QBO. The observed maximum stratospheric polar vortex–weakening response to the 20-hPa easterly QBO appears in the austral spring, which is reproduced qualitatively by seven models. The Eliassen–Palm (EP) flux convergence associated with enhanced upward propagation of waves from the SH midlatitude troposphere is also reasonably simulated following easterly QBO in these seven models. The Brewer–Dobson (BD) circulation response, especially its deep branch, has a large bias among models. The anomalous upwelling of the deep branch of the BD circulation and the cold anomalies are confined to midlatitudes above 20 hPa in reanalyses, while this deep branch is simulated to expand to the Antarctic stratosphere with unrealistically cold anomalies for some models. Models with a decent stratospheric pathway tend to simulate the observed negative Southern Annular Mode (SAM)-like response in the troposphere. Further, the largest enhanced convection center is observed over the tropical Indo-Pacific Ocean and simulated by 12 models, most of which also simulate a more reasonable height anomaly pattern in the troposphere. The near-surface response to the QBO also resembles the SAM pattern with warm anomalies over eastern Antarctic, which are simulated by only five models. Seven models simulate the observed wet signals in the midlatitude southern Indo-Pacific Ocean, where an anomalous low develops. Overall, models with a better reproduction of the SH stratospheric polar vortex response exhibit a more reasonable near-surface response, though for all models the response is too weak. Significance Statement: The equatorial stratospheric quasi-biennial oscillation (QBO) has been widely reported to influence the Northern Hemisphere. This paper focuses on the possible impact of the QBO on the Southern Hemisphere (SH) using 25 models. The maximum QBO signal in the Antarctic stratosphere forms in austral spring when the climatological vortex intensity has weakened relative to austral winter. The timing and magnitude of the QBO signal is simulated with different degrees of success by the 25 models, and those with a reasonable polar vortex response tend to better simulate the near-surface response. The QBO has another pathway for the extratropical circulation change via modifying tropical convection, and models also simulate a large spread in the tropical convection change associated with the QBO. [ABSTRACT FROM AUTHOR]

Several monsoon indices have been applied to multiple models from the sub-seasonal to seasonal ( S2S) prediction project database during the period May to October 1999-2010 to assess their ability to simulate the Asian monsoon. The bivariate anomaly correlation ( BAC) of the Boreal Summer IntraSeasonal Oscillation ( BSISO) index suggests that the operational models can predict the BSISO1 and BSISO2 events up to 6-24.5 and 6.5-14 days in advance respectively, although the models tend to underestimate the amplitude of BSISO as the lead time increases. For the strong BSISO events, BSISO1 ( BSISO2) display lower skill mostly in phases 3-5 for all the models, suggesting that the BSISO1 ( BSISO2) is not easy to predict when it is located over India and the Maritime Continent (South China Sea and Bay of Bengal). On the other hand, the higher skills appear in different phases for different models. For instance, the limit of predictive skill of strong BSISO1 and BSISO2 events in phases 6-7 for the ECMWF ensemble forecast could exceed 30 and 28 days, respectively. The comparisons of the BSISO life cycle among the ECMWF, NCEP and CMA models also indicate that the ECMWF model can better predict the evolution of strong BSISO events. Predictions of additional monsoon circulation indices including the Webster-Yang index ( WY), Indian Summer Monsoon index ( ISM), South Asian Monsoon index ( SAM), and SouthEast Asian Monsoon index ( SEAM) in the S2S models have statistically significant skill over the corresponding monsoon regions up to 9-31, 3-17, 7-13 and 7-14 days, respectively. However, the significant skill of summer monsoon precipitation over the SAM and SEAM regions varies significantly among the models, with the skill ranging from 2 days to 2 weeks lead time. [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]

Major disruptions of the winter season, high-latitude stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research. We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortex disturbances for surface predictability in subseasonal to seasonal forecast models. Based on a set of controlled, subseasonal ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models. Fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts. [ABSTRACT FROM AUTHOR]

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 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]

This study investigates the impact of coupled initialization on the extended-range prediction of the Madden–Julian oscillation (MJO). A set of reforecasts using combinations of the oceanic and atmospheric initial conditions produced with coupled and uncoupled data assimilation (DA) are conducted to evaluate the impact of coupling in the different domains, from the perspective of MJO forecasts. The coupled initial conditions are provided by CERA-SAT pilot coupled reanalysis for the satellite era recently produced by ECMWF. We focus on the prediction skill of the MJO using the real-time outgoing longwave radiation (OLR) MJO index in a series of reforecasts. The impact of atmospheric initial conditions produced by coupled DA shows slight benefit for the MJO prediction. However, compared with the operational ocean reanalysis, the ocean initial conditions created by CERA-SAT degrade the MJO prediction skill during the first 2–3 weeks of the reforecast by 1.5%–5.8%. A moist static energy budget analysis revealed that the underestimation of 0.2 K sea surface temperature, 1.4 W m−2 top of the atmosphere downward longwave radiation, and 3.8 W m−2 latent heat flux over the Maritime Continent leads to a small but statistically significant degradation of the MJO forecast skill. The results demonstrate that the MJO is sensitive to ocean initial conditions, and illustrate the value of the extended-range MJO prediction for evaluating the quality of coupled data assimilation, and suggest that future efforts on coupled data assimilation pay special attention to the balance of air–sea interaction processes over the warm pool area, in terms of modeling, observational needs and system design. [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]

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]

Phase 6 of the Coupled‐Model Intercomparison Project (CMIP6) is the first in which a significant number of models include a well‐resolved stratosphere. Changes in equatorial stratospheric variability in historical and Shared Socioeconomic Pathways (SSPs) scenario simulations are investigated in 10 models with realistic quasi‐biennial oscillations (QBO). All project a weakening of the QBO throughout the stratosphere for SSP370 and SSP585 scenarios and for 1960 to 2010. The weakening is strongest in the lower stratosphere, ranging from 5.8±0.5% to 4.3±0.5 % to 2.0±0.5% per decade at 50 hPa for SSP585, SSP370, and historical simulations, respectively. At 20 hPa a weakening of both westward and eastward phases contributes though the weakening eastward phase is only seen in 7 of the 10 models. Similar robust weakening occurs for the temperature QBO, but only from 30 hPa upward. In both scenarios the QBO period decreases in 7 of the 10 models. Plain Language Summary: At altitudes between roughly 16 and 50 km the equatorial atmosphere is dominated by strong zonal winds that reverse sign from eastward to westward roughly every 14 months in what is referred to as the quasi‐biennial oscillation. With developments in models the quasi‐biennial oscillation now features in a significant number of the latest state‐of‐the‐art climate projections. In those projections featuring the oscillation, the changing climate weakens it by up to ∼6% per decade for the more extreme of the scenarios considered. Somewhat less certain is a shortening of the time between wind reversals in several of the projections. Key Points: Many more CMIP6 models simulate a QBO than in previous CMIP phasesA weakening of the QBO in response to climate change is projected by 10 CMIP6 models with realistic QBOsUnder warming scenarios QBO periods shorten in 7 of the 10 CMIP6 models with realistic QBOs [ABSTRACT FROM AUTHOR]

Previous studies show that there are substantial influences of winter–spring Tibetan Plateau (TP) snow anomalies on the Asian summer monsoon and that autumn–winter TP heavy snow can lead to persisting hemispheric Pacific–North America-like responses. This study further investigates global atmospheric responses to realistic extensive spring TP snow anomalies using observations and ensemble transient model integrations. Model ensemble simulations are forced by satellite-derived observed March–May TP snow cover extent and snow water equivalent in years with heavy or light TP snow. Heavy spring TP snow causes simultaneous significant local surface cooling and precipitation decreases over and near the TP snow anomaly. Distant responses include weaker surface cooling over most Asian areas surrounding the TP, a weaker drying band extending east and northeast into the North Pacific Ocean, and increased precipitation in a region surrounding this drying band. Also, there is tropospheric cooling from the TP into the North Pacific and over most of North America and the North Atlantic Ocean. The TP snow anomaly induces a negative North Pacific Oscillation/western Pacific–like teleconnection response throughout the troposphere and stratosphere. Atmospheric responses also include significantly increased Pacific trade winds, a strengthened intertropical convergence zone over the equatorial Pacific Ocean, and an enhanced local Hadley circulation. This result suggests a near-global impact of the TP snow anomaly in nearly all seasons. [ABSTRACT FROM AUTHOR]

Abstract As the amount of environmental data expands exponentially worldwide, researchers are challenged to efficiently analyze data maintained in multiple data centers. Because distributed data access, server-side analysis, multinode collaboration, and extensible analytic functions are still research gaps in this field, this paper introduces a collaborative analysis framework for gridded environmental data, i.e. CAFE. Multiple CAFE nodes can collaborate to perform complex data analysis. Analytic functions are performed near where data are stored. A web-based user interface allows researchers to search for data of interest, submit analytic tasks, check the status of tasks, visualize the analysis results, and download the resulting data files. CAFE facilitates overall research efficiency by dramatically lowering the amount of data that must be transmitted from data centers to researchers for analysis. The results of this study may lead to the further development of collaborative computing paradigm for environmental data analysis. Highlights • CAFE enables data discovery, visualization, and analysis through a web-based portal. • CAFE always execute data analysis near where data are stored. • CAFE enables multiple nodes to collaboratively fulfill analysis task automatically. • CAFE can alleviate large data transfer from data centers to researchers. • CAFE can wrap executable analytic scripts as analytic functions for users to select. [ABSTRACT FROM AUTHOR]