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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]

The surface air temperature (SAT) trend on the Tibetan Plateau (TP) was 3.45°C 100 years−1 from 1961 to 2014. The multi‐model ensemble (MME) of 33 coupled models participated in the Coupled Model Intercomparison Project phase six (CMIP6) was about 1°C 100 years−1 lower than the observation. Although MME generally shows better skill in reproducing the distribution of SAT trend over TP than most of the CMIP6 models, its performance is greatly degraded by a small group of models, about 12% on average, with large biases. In this paper, the constrained multi‐model ensemble (CMME) based on a certain observation‐based threshold is used to constrain future projections of the SAT trend over TP. Compared with the MME results, the improvements in CMME are mainly over the eastern plateau in historical simulation and are relative to the reduction of the model biases to carbon dioxide (CO2) forcing. Under the high‐emission SSP5‐8.5 scenario, SAT increases significantly over the entire TP. The constraint of CMME on the MME is mainly over the eastern plateau with a difference of 0.5°C 100 years−1, about 6% of the MME results. Under the intermediate‐emission scenario SSP2‐4.5, the effect of CMME is relatively smaller, but the corresponding spatial distribution is similar to that under the SSP5‐8.5 scenario. The CMIP6 models tend to underestimate the warming trend projections over the water source regions in the northeastern plateau and should be noticed. Key Points: The Coupled Model Intercomparison Project phase six model ensemble in surface air temperature trend reproduction on the Tibetan Plateau are greatly degraded by a small group of models with large biasesThe impact of constrained ensemble (CMME) is mainly over the eastern plateau in relative to the reduction of model biases to CO2 forcingThe CMME results indicate the underestimated warming projections in multi‐model ensemble over the northeastern plateau [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 reliability of the near-land-surface air temperature (LSAT) projections from the state-of-the-art climate-system models that participated in the Coupled Model Intercomparison Project phase six (CMIP6) is debatable, particularly on regional scales. Here we introduce a method of constructing a constrained multi-model-ensemble (CMME), based on rejecting models that fail to reproduce observed LSAT trends. We use the CMME to constrain future LSAT projections under the Shared Socioeconomic Pathways 5–8.5 (SSP5–8.5) and 2–4.5 (SSP2–4.5), representing the high and intermediate scenarios. In comparison with the "raw" (unconstrained) CMIP6 multi-model ensemble (MME) mean, the impact of the observation-based constraint is less than 0.05oC 100 years−1 at a global scale over the second half of 21st century. However, the regional results show a wider range of positive and negative adjustments, from -1.0oC 100 years−1 to 1oC 100 years−1 under the SSP5–8.5 scenario. Although amplitude under SSP2–4.5 is relatively smaller, the CMME adjustment is similar to that under SSP5–8.5, indicating the scenario independency of the CMME impact. The ideal 1pctCO2 experiment suggests that the response of LSAT to carbon dioxide (CO2) forcing on regional scales is responsible for the MME biases in the historical period, implying the high reliability of CMME in the 21st century projections. The advantage of CMME is that it goes beyond the idea of "model democracy" assumed in MME. The unconstrained CMIP6 MME may be overestimating the risks of future warming over North America, but underestimating the risks over Asia. [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]

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]

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]

Because of natural decadal climate variability—Atlantic multi-decadal variability (AMV) and Pacific decadal variability (PDV) —the increase of global mean surface air temperature (GMSAT) has not been monotonic although atmospheric greenhouse-gas (GHG) concentrations have been increasing continuously. It has always been a challenge regarding how to separate the effects of these two factors on GMSAT. Here, we find a physically based quasi-linear relationship between transient GMSAT and well-mixed GHG changes for both observations and model simulations. With AMV and PDV defined as the combination of variability over both the Atlantic and Pacific basins after the GHG-related trend is removed, we show that the observed GMSAT changes from 1880 to 2017 on multi-decadal or longer timescales receive contributions of about 70% from GHGs, while AMV and PDV together account for roughly 30%. Moreover, AMV contributes more to time-evolving GMSAT on multi-decadal and longer timescales, but PDV leads AMV on decadal timescales with comparable contributions to GMSAT trends. Climate change: greenhouse gases contributions to temperature change Climate forecasts are challenged by the fact that climate is driven simultaneously by a combination of external forcing and natural variability. Separating these effects remains an important issue for understanding the past and future evolution of climate on global and regional scales. Tongwen Wu of the Beijing Climate Center and colleagues analyze both observational data and model simulations to determine the relative contributions of Atlantic multi-decadal variability (AMV), Pacific decadal variability (PDV), and a combination of well-mixed greenhouse gases (GHG) to global mean surface air temperature (GMSAT) changes between 1880 and 2017. They show that there is a reliable linear relationship between GHG concentrations and changes in GMSAT. Further, 70% of the observed change in GMSAT over this period is contributed by GHGs and a combined 30% by AMV and PDV. The influence of natural variability relative to GHGs is expected to decrease in the future. [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]