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This study applies three widely used land models (SSiB, CLM, and Noah-MP) coupled in a regional climate model to quantitatively assess their skill in preserving the imposed ± 5 °C anomalies on the initial land surface and subsurface temperature (LST/SUBT) and generating the 2-m air temperature (T2m) anomalies over Tibetan Plateau (TP) during May–August. The memory of the LST/SUBT initial anomalies (surface/soil memory) is defined as the first time when time series of the differences in daily LST/SUBT cross the zero line during the simulation, with the unit of days. The memory of the T2m anomalies (T2m memory) is defined in the same way. The ensemble results indicate that the simulated soil memory generally increases with soil depth, which is consistent with the results based on the observations with statistic methods. And the soil memory is found to change rapidly with depth above ~ 0.6–0.7 m and vary slowly below it. The land models have fairly long soil memories, with the regional mean 1.0-m soil memory generally longer than 60 days. However, they have short T2m memory, with the regional means generally below 20 days. This may bring a big challenge to use the LST/SUBT approach on the sub-seasonal to seasonal (S2S) prediction. Comparison between the three land models shows that CLM and Noah-MP have longer soil memory at the deeper layers (> ~ 0.05 m) while SSiB has longer T2m/surface memories and near-surface (≤ ~ 0.05 m) soil memory. As a result, it is difficult to say which land model is optimal for the application of the LST/SUBT approach on the S2S prediction. The T2m/surface/soil memories are various over TP, distinct among the land models, and different between the + 5 °C and − 5 °C experiment, which can be explained by both changes in the surface heat fluxes and variances in the hydrological processes over the plateau. [ABSTRACT FROM AUTHOR]

Quantitative assessment of urbanization effect on surface air temperature (SAT) change provides crucial basis for formal detection and attribution analyses of climate change. However, debates about urbanization‐related warming bias in documented regional SAT trend still persist, mainly due to different determination of rural stations. Here the urbanization effect on SAT change over the Beijing–Tianjin–Hebei region in China during 1980–2019 is estimated through three kinds of ways (i.e., comparisons between urban and rural stations [arithmetically station‐averaged], urban‐dominated and rural‐dominated patches [patch‐weighted mean], and realistic urban and rural areas [area‐weighted mean]). The last method explicitly takes urban and rural land cover fractions into account when calculating urban/rural and regional mean SAT trends. Urbanization‐induced warming in the annual mean SAT change of urban stations (areas) through the three ways are estimated as 0.159°C, 0.195°C, and 0.138°C per decade, respectively. And urbanization effect on regional averaged annual mean SAT calculated by patch‐weighted and area‐weighted methods are 0.113°C and 0.050°C per decade, respectively, which account for 33.8% and 14.8% of the total regional warming. The urbanization effect on observed SAT change estimated by considering realistic urban/rural land cover proportions is much lower than traditional station‐unweighted way. [ABSTRACT FROM AUTHOR]

To understand the potential impacts of projected climate change on the vulnerable agriculture in Central Asia (CA), six agroclimatic indicators are calculated based on the 9-km-resolution dynamical downscaled results of three different global climate models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and their changes in the near-term future (2031–50) are assessed relative to the reference period (1986–2005). The quantile mapping (QM) method is applied to correct the model data before calculating the indicators. Results show the QM method largely reduces the biases in all the indicators. Growing season length (GSL, day), summer days (SU, day), warm spell duration index (WSDI, day), and tropical nights (TR, day) are projected to significantly increase over CA, and frost days (FD, day) are projected to decrease. However, changes in biologically effective degree days (BEDD, °C) are spatially heterogeneous. The high-resolution projection dataset of agroclimatic indicators over CA can serve as a scientific basis for assessing the future risks to local agriculture from climate change and will be beneficial in planning adaption and mitigation actions for food security in this region. [ABSTRACT FROM AUTHOR]

Central Asia (referred to as CA) is one of the climate change hot spots due to the fragile ecosystems, frequent natural hazards, strained water resources, and accelerated glacier melting, which underscores the need of high-resolution climate projection datasets for application to vulnerability, impacts, and adaption assessments in this region. In this study, a high-resolution (9 km) climate projection dataset over CA (the HCPD-CA dataset) is derived from dynamically downscaled results based on multiple bias-corrected global climate models and contains four geostatic variables and 10 meteorological elements that are widely used to drive ecological and hydrological models. The reference and future periods are 1986–2005 and 2031–2050, respectively. The carbon emission scenario is Representative Concentration Pathway (RCP) 4.5. The evaluation shows that the data product has good quality in describing the climatology of all the elements in CA despite some systematic biases, which ensures the suitability of the dataset for future research. Main features of projected climate changes over CA in the near-term future are strong warming (annual mean temperature increasing by 1.62–2.02 ∘ C) and a significant increase in downward shortwave and longwave flux at the surface, with minor changes in other elements (e.g., precipitation, relative humidity at 2 m, and wind speed at 10 m). The HCPD-CA dataset presented here serves as a scientific basis for assessing the potential impacts of projected climate changes over CA on many sectors, especially on ecological and hydrological systems. It has the DOI 10.11888/Meteoro.tpdc.271759 (Qiu, 2021). [ABSTRACT FROM AUTHOR]

In the late 1920's, a mega-drought in China resulted in widespread crop failure and famine. Sufficient evidence suggests that this drought belonged to a dry period ranging from approximately 1922 to 1932. To understand the characteristics and the cause of this persistent drought period, we combined various data, including observations, tree ring proxy data, reanalysis data, simulation results of the Fifth Phase of the Coupled Model Intercomparison Project and numerical downscaling simulations. The results show that during 1922–1932, most regions in eastern China suffered from a persistent drought that lasted for six years, and the maximum negative precipitation anomaly reached −1.5 times the standard deviation. Given its spatial coverage, duration, and strength, the 1920s drought was unique for the 20th century. The 1920s drought was primarily caused by internal variability. Strong easterlies in lower latitudes, strong monsoon circulation, and abnormally high geopotential heights at middle and upper levels were responsible for the 1920s drought conditions in eastern China; these drought conditions could be further attributed to the joint impact of the Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation and Indian Ocean Basin Mode. [ABSTRACT FROM AUTHOR]

Central Asia (CA) is among the most vulnerable regions to climate change due to the fragile ecosystems, frequent natural hazards, strained water resources, and accelerated glacier melting, which underscores the need to achieve robust projection of regional climate change. In this study, we applied three bias-corrected global climate models (GCMs) to conduct 9 km-resolution regional climate simulations in CA for the reference (1986–2005) and future (2031–2050) periods. The regional climate model (RCM) and GCM simulated daily temperature and precipitation are evaluated and the results show that both the bias-correction technique and dynamical downscaling method obtain numerous added values in reproducing the historical climate in CA, respect to the original GCMs. The former contributes more to reducing the biases of the climatology and the latter contributes more to capturing the spatial pattern. The RCM simulations indicate significant warming over CA in the near-term future, with the regional mean increase of annual mean temperature in a range of 1.63–2.01 ℃, relative to the reference period. Pronounced warming is detected north of ~ 45° N in CA from autumn to spring, which can be explained by the snow-albedo feedback. Enhanced warming projected in many mountains in the world is not found in CA, which is consistent with the study based on the reanalysis datasets during the past. Heatwave day frequency, number and maximum duration are expected to become more severe by 2031–2050. Changes in precipitation and Standard Precipitation Index (SPI) shows a wetter condition in CA in the coming decades. However, a fairer assessment of the wet/dry change with Standard Precipitation Evapotranspiration Index (SPEI) which takes into account of both precipitation and potential evapotranspiration reveals a drier condition. The climate change projections presented here serve as a robust scientific basis for assessment of future risk from climate change in CA. [ABSTRACT FROM AUTHOR]

Central Asia (referred to as CA) is one of the climate change Hot-Spots due to the fragile ecosystems, strained water resources, and accelerated glacier melting, which underscores the need of high-resolution climate projection datasets for application to vulnerability, impacts, and adaption assessments in ecological and hydrological systems. In this study, a high-resolution (9 km) climate projection dataset over CA (the HCPD-CA dataset) is derived from dynamically downscaled results based on multiple bias-corrected global climate models, and contains ten meteorological elements that are widely used to drive ecological and hydrological models. The reference and future periods are 1986-2005 and 2031-2050, respectively. The carbon emission scenario is Representative Concentration Pathway (RCP) 4.5. The results show the data product has good quality in describing the climatology of all the elements in CA, which ensures the suitability of the dataset for future research. The main feature of projected climate changes in CA in the near-term future is strong warming (annual mean temperature increasing by 1.62-2.02) and significant increase in downward shortwave and longwave flux at surface, with minor changes in other elements (e. g., precipitation, relative humidity at 2 m, and wind speed at 10 m). The HCPD-CA dataset presented here serves as a scientific basis for assessing the impacts of climate change over CA on many sectors, especially on ecological and hydrological systems. It is publicly available at http://data.tpdc.ac.cn/en/disallow/24c7467c-44a6-44ab-bbcf-e6e346dd41d0/(Qiu, 2021). [ABSTRACT FROM AUTHOR]

[Display omitted] • A CoO x ultrathin nanosheet composed of interfacial Co 3 O 4 and CoO was synthesized. • The CoO x catalyst exhibited 100 % BPA removal in 2 min with a reaction rate of 2.69 min−1. • In situ interfacial effect optimized the adsorption and electron transfer during PMS activation. • The OH and 1O 2 played key contribution for contaminates degradation. Cobalt-based oxides have attracted extensive attention in heterogeneous catalytic peroxymonosulfate (PMS) activation towards emerging pollutants degradation, while the improvement of their catalytic performance is still a severe challenge. Herein, a CoO x ultrathin nanosheet composed of in situ interfacial Co 3 O 4 and CoO (CoO x -Ar-350) was synthesized and employed in PMS activation for micro-contaminates removal. The catalyst shows 100 % bisphenol A (BPA) conversion within 2 min ([BPA] = 20 mg/L, [Catalyst] = 20 mg/L, [PMS] = 200 mg/L) with a remarkable reaction rate of 2.69 min−1, which is 3.84 and 2.66 times of pure Co 3 O 4 and CoO, respectively. Characterization and theoretical calculation results indicates that the interfacial synergy between Co 3 O 4 and CoO could modulate the adsorption behavior and enhance the electron acceptance of PMS, which boosts the breaking of O-O bonds and the generation of reactive oxygen species (ROS) and thereby the pollutant removal efficiency. The ROS quenching and capture experiments demonstrate that the enhanced OH and 1O 2 play significant contribution during the degradation process. This work provides a novel in situ interfacial engineering for the development of highly efficient catalyst and reveals the activity enhancement mechanism for PMS activation. [ABSTRACT FROM AUTHOR]

The Weather Research and Forecasting model (WRF) comprises a number of parameterization schemes, and therefore the different combined physical parameterization schemes should be discussed before determining optimal configurations. The regional climate of central Asia is simulated from 2003 to 2008 using the WRFv4.0.1 with nine physical combinations (microphysics [MP], cumulus [CU], planetary boundary layer [PBL]) on a 25‐km horizontal grid. The goal is to identify a reasonable configuration assemble of physical parameterization schemes for long‐term simulations through the sensitivity experiments of regional climate respond to microphysics, convection, and boundary layer processes. Compared to the observation data, all the groups mostly simulate the daily and seasonal variations of precipitation but with a shift from wet bias to dry bias based on the daily precipitation categories of the Tropical Rainfall Measuring Mission (TRMM). The large‐scale precipitation caused by the microphysics schemes is 3–4 times the amount of precipitation caused by the subscale precipitation generated by the cumulus schemes. The simulated difference of the vertical temperature shows results similar to those of the surface air temperature. The microphysics schemes play the dominant role among the three physical options, and the Thompson scheme addresses better precipitation and surface temperature simulations in contrast to the WDM6 scheme. By combining with the bias, correlation and root‐mean‐square error (RMSE) between the reproduced temperature and precipitation, it can be concluded that the best optimal physical schemes combination is the Thompson–Tiedtke–YSU, which can be used for long‐term simulations. [ABSTRACT FROM AUTHOR]

The square conservation law is implemented in atmospheric dynamic cores on latitude–longitude grids, but it is rarely implemented on quasi-uniform grids, given the difficulty involved in constructing anti-symmetrical spatial discrete operators on these grids. Increasingly more models are being developed on quasi-uniform grids, such as arbitrarily structured C-grids. Thuburn–Ringler–Skamarock–Klemp (TRiSK) is a shallow water dynamic core on an arbitrarily structured C-grid. The spatial discrete operator of TRiSK is able to naturally maintain the conservation properties of total mass and total absolute vorticity and conserving total energy with time truncation error; the first two integral invariants are exactly conserved during integration, but the total energy dissipates when using the dissipative temporal integration schemes, i.e., Runge–Kutta (RK). The method of strictly conserving the total energy simultaneously, which means conserving energy in the round-off error over the entire temporal integration period, uses both an anti-symmetrical spatial discrete operator and a square conservative temporal integration scheme. In this study, we demonstrate that square conservation is equivalent to energy conservation in both a continuous shallow water system and a discrete shallow water system of TRiSK. After that, we attempt to extend the square conservation law to the TRiSK framework. To overcome the challenge of constructing an anti-symmetrical spatial discrete operator, we unify the unit of evolution variables of shallow water equations using the Institute of Atmospheric Physics (IAP) transformation, and the temporal derivatives of new evolution variables can be expressed by a combination of temporal derivatives of original evolution variables, which means the square conservative spatial discrete operator can be obtain by using original spatial discrete operators in TRiSK. Using the square conservative Runge–Kutta scheme, the total energy is completely conserved, and there is no influence on the properties of conserving total mass and total absolute vorticity. In the standard shallow water numerical test, the square conservative scheme not only helps maintain total conservation of the three integral invariants but also creates less simulation error norms. [ABSTRACT FROM AUTHOR]

The spatial-seasonal distributions of carbon dioxide (CO2) data derived from satellite observation data are introduced into the coupled BNU-ESM (Beijing Normal University Earth System Model) global model to study the differences in global atmospheric temperature changes caused by the uniform and nonuniform distributions of CO2. A series of ensemble simulations are conducted under different CO2 distributions from 1850 to 2005. From the seasonal to interannual scale, the spatial distributions of CO2 concentration and surface air temperature between the nonuniform and uniform simulations are different. The CO2 concentrations in the nonuniform simulations are higher than those in the uniform simulations in most areas of the Northern Hemisphere and lower in almost all of the Southern Hemisphere; however, the air temperatures are higher in the nonuniform simulations than in the uniform simulations over most land areas, especially in North America. The amplitudes of the temperature increase in both ensemble runs (nonuniform-uniform) from 1986 to 2005 caused by increases in the CO2 concentration are smaller in the Southern Hemisphere than in the Northern Hemisphere. The amplitudes of the temperature increase over the two decades in the ensemble uniform simulation is approximately 0.2~0.3 °C higher than that in the ensemble nonuniform simulations at the global scale. [ABSTRACT FROM AUTHOR]

Abstract Statistical downscaling (SD) of daily precipitation is a challenging task, and the identification of predictors is crucial for constructing SD models. This study focuses on identifying SD predictors for summer (June–September) daily precipitation in China. Six large-scale variables (LSVs) in ERA-Interim reanalysis were used to select predictors for 177 sites. For each site, the predictor identification was conducted by searching the grid box having the best correlation to precipitation in a three-dimensional way: across different grid boxes and multiple pressure levels. The result indicates that correlations are often sensitive to the pressure levels. Adjacent sites share similar spatial patterns of correlations, indicating regionally different physical relations between LSVs and precipitation. The predictor selection reasonably reflects the regional circulations related to precipitation. Twelve candidate predictors were used to train generalized linear models by least absolute shrinkage and selection operator (LASSO) algorithm. The validation indicates the models have generally high performance, and also shows relatively poor performance for the sites in North China, Northwest China, and Yunnan when compared to that in the east of China. The downscaled outputs can roughly reflect the annual variations of summer total precipitation and rainy days. Two experiments on the stationarity assumption of the models under different climate conditions were conducted, indicating that no areas/sites were found significantly violated the stationarity assumption. This study presents guidance on how to select suitable predictors for downscaling daily precipitation in different areas of China. Highlights • Predictor-precipitation correlations are sensitive to the pressure levels. • The pressure levels having best correlations are different for stations. • 3-D Predictor selection reflects the related prevailing circulations. • Performances are satisfying on daily and monthly scales. • Performance varies in different stations/regions of China. [ABSTRACT FROM AUTHOR]

Drought is the major natural disaster that affects northern China and has regional distinctions in duration, strength, and spatial range. Using five sets of twentieth-century reanalysis data, we investigated a decadal-scale extreme drought recorded in historical documents and tree-ring chronologies during late 1920s to early 1930s. The results indicated that the characteristics of drought were different in North China and the middle reach of the Yellow River. Drought in North China showed an interannual variation coinciding strongly with El Niño. For the middle reach of the Yellow River, a persistently dry period lasting from 1922 to 1932 was found, while the driest years were 1928 and 1929.The dataset ERA-20C had better performance than other reanalysis datasets in both regions. The drought that happened in North China during these years may have been primarily determined by ENSO. The joint impact of PDO and AMO may have been responsible for the decadal dry anomaly in the middle reach of the Yellow River. [ABSTRACT FROM AUTHOR]

Statistical downscaling (SD) is a method that acquires the local information required for hydrological impact assessment from large-scale atmospheric variables. Very few statistical and deterministic downscaling models for daily precipitation have been conducted for local sites influenced by the East Asian monsoon. In this study, SD models were constructed by selecting the best predictors and using generalized linear models (GLMs) for Feixian, a site in the Yishu River Basin and Shandong Province. By calculating and mapping Spearman rank correlation coefficients between the gridded standardized values of five large-scale variables and daily observed precipitation, different cyclonic circulation patterns were found for monsoonal precipitation in summer (June-September) and winter (November-December and January-March); the values of the gridded boxes with the highest absolute correlations for observed precipitation were selected as predictors. Data for predictors and predictands covered the period 1979-2015, and different calibration and validation periods were divided when fitting and validating the models. Meanwhile, the bootstrap method was also used to fit the GLM. All the above thorough validations indicated that the models were robust and not sensitive to different samples or different periods. Pearson's correlations between downscaled and observed precipitation (logarithmically transformed) on a daily scale reached 0.54-0.57 in summer and 0.56-0.61 in winter, and the Nash-Sutcliffe efficiency between downscaled and observed precipitation reached 0.1 in summer and 0.41 in winter. The downscaled precipitation partially reflected exact variations in winter and main trends in summer for total interannual precipitation. For the number of wet days, both winter and summer models were able to reflect interannual variations. Other comparisons were also made in this study. These results demonstrated that when downscaling, it is appropriate to combine a correlation-based predictor selection across a spatial domain with GLM modeling. [ABSTRACT FROM AUTHOR]

[Display omitted] • An oxygen vacancy-rich CoMoO 4 catalyst is prepared and applied for PMS activation. • The catalyst exhibits high SMX removal efficiency with 1.29 min−1 of reaction rate. • The oxygen vacancy enhances reduction capacity of the catalyst and formation of ROS. • The improved degradation performance is attributed to the boosted radical pathway. Cobalt-based oxides are promising candidates for heterogeneous activation of peroxymonosulfate-based (PMS) advanced oxidation processes towards contaminants degradation, hence improving their catalytic performance is desirable requirement. Herein, an oxygen vacancy-rich flower-like CoMoO 4 catalyst (CoMoO 4 -V O) assembled with nanosheets was successfully synthesized and applied for PMS activation to eliminate emerging contaminants. The CoMoO 4 -V O catalyst exhibits superior organic pollutants (e.g. sulfamethoxazole, SMX) removal performance with an apparent reaction rate of 1.29 min−1, which is much higher than that of the original CoMoO 4 catalyst (0.30 min−1). Additionally, the catalyst also shows remarkable contaminants conversion in real river water, and even achieves more than 90 % of SMX degradation efficiency under a continuous flow reaction condition with a hydraulic retention time of approximately 2 min. The characterization and density functional theory (DFT) calculation results indicate that much electron accumulates around the formed oxygen vacancy on the surface of catalyst and transfers towards substrates. Meanwhile, the introduction of more oxygen vacancies could boost the adsorption of PMS as well as SMX, and the electron-donation capacity of catalyst, thus improving the generation of reactive oxygen species and the subsequent contaminate elimination. Radical quenching and capture experiments demonstrate that the enhanced degradation performance of CoMoO 4 -V O catalyst is attributed to the boosted radical pathway, especially for SO 4 − species, while scarcely contributed from the non-radical 1O 2 species. This work provides an effective catalyst for contaminant elimination through PMS activation and deeply reveals the defect engineering-induced activity enhancement mechanism. [ABSTRACT FROM AUTHOR]

The WRF model with chemistry (WRF-Chem) was employed to simulate the impacts of anthropogenic aerosols on summer precipitation over the Beijing-Tianjin-Hebei urban agglomeration in China. With the aid of a high-resolution gridded inventory of anthropogenic emissions of trace gases and aerosols, we conducted relatively long-term regional simulations, considering direct, semi-direct and indirect effects of the aerosols. Comparing the results of sensitivity experiments with and without emissions, it was found that anthropogenic aerosols tended to enhance summer precipitation over the metropolitan areas. Domain-averaged rainfall was increased throughout the day, except for the time around noon. Aerosols shifted the precipitation probability distribution from light or moderate to extreme rain. Further analysis showed that the anthropogenic aerosol radiative forcing had a cooling effect at the land surface, but a warming effect in the atmosphere. However, enhanced convective strength and updrafts accompanied by water vapor increases and cyclone-like wind shear anomalies were found in the urban areas. These responses may originate from cloud microphysical effects of aerosols on convection, which were identified as the primary cause for the summer rainfall enhancement. [ABSTRACT FROM AUTHOR]

Precipitation and other hydrologic variables play important roles in river basins. In this study, summer precipitation, evaporation, and water vapor transport from 16 models that have participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) for the Yellow River basin (a water-limited basin) and the Yangtze River basin (an energy-limited basin) over the period 1986-2005 are analyzed and evaluated. The results suggest that most models tend to overestimate precipitation in the Yellow River basin, whereas precipitation in the Yangtze River basin is generally well simulated. Models that overestimate precipitation in the Yellow River basin also simulate evaporation with large positive biases. For water vapor transport, models and reanalysis data concur that both basins are moisture sinks in summer. In addition, models that strongly overestimate precipitation in the Yellow River basin tend to produce strong water vapor convergence in that region, which is likely to be related to the situation that the western Pacific subtropical high (WPSH) simulated by these models strengthens and advances further westward and northward, resulting in stronger water vapor convergence in the Yellow River basin. Moreover, convective precipitation biases simulated by the models are also partially responsible for their total precipitation biases. Finally, summer precipitation and evaporation are negatively correlated in the Yangtze River basin, whereas the relation between these variables is weak in the Yellow River basin. In both basins, precipitation and water vapor convergence are positively correlated, which is well simulated by all models. [ABSTRACT FROM AUTHOR]

Based on observations and 12 simulations from Coupled Model Intercomparison Project Phase 5 (CMIP5) models, climatic extremes and their changes over China in the past and under the future scenarios of three Representative Concentration Pathways (RCPs) are analyzed. In observations, frost days (FD) and low-temperature threshold days (TN10P) show a decreasing trend, and summer days (SU), high-temperature threshold days (TX90P), heavy precipitation days (R20), and the contribution of heavy precipitation days (P95T) show an increasing trend. Most models are able to simulate the main characteristics of most extreme indices. In particular, the mean FD and TX90P are reproduced the best, and the basic trends of FD, TN10P, SU and TX90P are represented. For the FD and SU indexes, most models show good ability in capturing the spatial differences between the mean state of the periods 1986-2005 and 1961-80; however, for other indices, the simulation abilities for spatial disparity are less satisfactory and need to be improved. Under the high emissions scenario of RCP8.5, the century-scale linear changes of the multi-model ensemble (MME) for FD, SU, TN10P, TX90P, R20 and P95T are −46.9, 46.0, −27.1, 175.4, and 2.9 days, and 9.9%, respectively; and the spatial change scope for each index is consistent with the emissions intensity. Due to the complexities of physical process parameterizations and the limitation of forcing data, great uncertainty still exists with respect to the simulation of climatic extremes. [ABSTRACT FROM AUTHOR]

The East Asian summer monsoon (EASM) is a distinctive component of the Asian climate system and critically influences the economy and society of the region. To understand the ability of AGCMs in capturing the major features of EASM, 10 models that participated in Coupled Model Intercomparison Project/Atmospheric Model Intercomparison Project (CMIP5/AMIP), which used observational SST and sea ice to drive AGCMs during the period 1979-2008, were evaluated by comparing with observations and AMIP II simulations. The results indicated that the multi-model ensemble (MME) of CMIP5/AMIP captures the main characteristics of precipitation and monsoon circulation, and shows the best skill in EASM simulation, better than the AMIP II MME. As for the Meiyu/Changma/Baiyu rainbelt, the intensity of rainfall is underestimated in all the models. The biases are caused by a weak western Pacific subtropical high (WPSH) and accompanying eastward southwesterly winds in group I models, and by a too strong and west-extended WPSH as well as westerly winds in group II models. Considerable systematic errors exist in the simulated seasonal migration of rainfall, and the notable northward jumps and rainfall persistence remain a challenge for all the models. However, the CMIP5/AMIP MME is skillful in simulating the western North Pacific monsoon index (WNPMI). [ABSTRACT FROM AUTHOR]

We simulated the impact of anthropogenic heat release (AHR) on the regional climate in three vast city agglomerations in China using the Weather Research and Forecasting model with nested high-resolution modeling. Based on energy consumption and high-quality land use data, we designed two scenarios to represent no-AHR and current-AHR conditions. By comparing the results of the two numerical experiments, changes of surface air temperature and precipitation due to AHR were quantified and analyzed. We concluded that AHR increases the temperature in these urbanized areas by about 0.5°C-1°C, and this increase is more pronounced in winter than in other seasons. The inclusion of AHR enhances the convergence of water vapor over urbanized areas. Together with the warming of the lower troposphere and the enhancement of ascending motions caused by AHR, the average convective available potential energy in urbanized areas is increased. Rainfall amounts in summer over urbanized areas are likely to increase and regional precipitation patterns to be altered to some extent. [ABSTRACT FROM AUTHOR]

The trends and fluctuations of observed and CMIP5-simulated yearly mean surface air temperature over China were analyzed. In general, the historical simulations replicate the observed increase of temperature, but the multi-model ensemble (MME) mean does not accurately reproduce the drastic interannual fluctuations. The correlation coefficient of the MME mean with the observations over all runs and all models was 0.77, which was larger than the largest value (0.65) from any single model ensemble. The results showed that winter temperatures are increasing at a higher rate than summer temperatures, and that winter temperatures exhibit stronger interannual variations. It was also found that the models underestimate the differences between winter and summer rates. The ensemble empirical mode decomposition technique was used to obtain six intrinsic mode functions (IMFs) for the modeled temperature and observations. The periods of the first two IMFs of the MME mean were 3.2 and 7.2, which represented the cycle of 2-7-yr oscillations. The periods of the third and fourth IMFs were 14.7 and 35.2, which reflected a multi-decadal oscillation of climate change. The corresponding periods of the first four IMFs were 2.69, 7.24, 16.15 and 52.5 in the observed data. The models overestimate the period of low frequency oscillation of temperature, but underestimate the period of high frequency variation. The warming rates from different representative concentration pathways (RCPs) were calculated, and the results showed that the temperature will increase by approximately 0.9°C, 2.4°C, 3.2°C and 6.1°C in the next century under the RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios, respectively. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) serve a narrow, filamentary channels responsible for intense moisture and heat transport, which are vital for the Arctic sea ice loss and surface air warming, particularly in winter. In this study, ERA5 reanalysis data from 1979 to 2020 are used to investigate the evolution of ARs in the Arctic and the corresponding atmospheric circulation patterns in winter. Our findings indicate that atmospheric circulation is a key factor that facilitates the transport and dispersion of ARs. Cyclonic circulation anomalies provide the dynamical support for ARs in the early development stages, while anticyclonic anomalies are essential for maintaining the thermal and moisture conditions of ARs, particularly after their intrusions into the Arctic region. The cooperation between cyclonic and anticyclonic anomalies plays a critical role in the infiltration and dispersion of ARs, governed by distinct circulation modes for regional intrusions. A positive Arctic Oscillation‐like pattern manifests as a cyclonic system over the Arctic, increasing the likelihood of AR intrusion into Baffin Bay. Conversely, a negative pattern induces a more intense anticyclonic system over the Arctic, thereby raising the frequency of ARs in the Bering Strait. The Pacific‐North American pattern not only directly affects ARs entering the Arctic via the Pacific but also has downstream impacts on ARs intruding the Arctic through Baffin Bay. [ABSTRACT FROM AUTHOR]

Near‐surface wind speed (NSWS) over China shows multiple time‐scale changes at a centennial scale, but the contributions of internal variability (IV), anthropogenic forcing (ANT), and natural forcing (NAT) to those changes remain unknown. This study investigated the contributions of IV, ANT, and NAT to NSWS changes at a centennial scale. Results show that the NSWS changes were attributed mainly to IV. IV not only modulated the interannual changes in NSWS but also determined the interdecadal transition in NSWS. The relative contributions of IV to the interannual and decadal NSWS exceeded 75.0%. ANT contributed particularly to the long‐term reduction in NSWS; especially, it has contributed 55.0% of the reduction in NSWS since 1957, serving as the major contributor to the reduction in NSWS. NAT had a small‐to‐negligible effect on China's NSWS throughout the study period. This study enhances our understanding of NSWS changes at different time scales. Plain Language Summary: Near‐surface wind speed (NSWS) is crucial because it can influence energy, water, and air move between the Earth's surface and the atmosphere, which can also affect weather and climate systems like dust storms, evaporation rates, and the water cycle. In the past decades, interannual and interdecadal changes in NSWS, as well as the long‐term trend of NSWS have been analyzed; however, the causes behind these changes are not clear. Our research focuses on understanding these changes over nearly a century. We discover that internal variability (IV) is a primary factor driving these changes in NSWS, especially in terms of its fluctuations and shifts over decades. In addition to IV, anthropogenic forcing also plays a crucial role, particularly for the decrease of NSWS since 1957. On the other hand, natural forcing seem to have a minimal or almost no impact on NSWS changes in China during the study period. This study not only enhances our understanding of NSWS changes over multiple time scales but also provides essential information for policymakers to develop climate strategies and adaptation measures. Key Points: Internal variability determines the interannual and interdecadal changes in near‐surface wind speed (NSWS) across ChinaAnthropogenic forcing is responsible for the slowdown in NSWS since 1957, its contribution reaches 55.0%Natural forcing has a small‐to‐negligible influence on the changes in NSWS [ABSTRACT FROM AUTHOR]

The bandgap of organics is an important descriptor to evaluate the interface adhesion of an organic agent on metal surface. However, insight into the role of chalcogens tuning of π-conjugated materials in influencing the bandgap is still deficient. Here, a family of diketopyrrolopyrrole(DPP)-based quaternary ammonium salts containing different chalcogens are innovatively synthesized through bottom-up strategy and served as new levelers in conformal copper electrodeposition. The photophysical and electrochemical properties including cyclic voltammetry (CV),potentiodynamic polarization curves and galvanostatic measurements (GMs) of those compounds were tested. Compared with other counterparts, SeDPP-QAS presents the narrowest bandgap showing great potential in conformal copper electrodeposition. Through-hole electroplating test and the scanning electron microscope (SEM) images of coating layer demonstrate that bandgap tuning is an efficient method to level and regulate the electrodeposition performance. Besides, theoretical calculations and X-ray photoelectron spectroscopy (XPS) were applied detect the adsorption mechanism between organic agent and copper surface. This work broadens the understanding of bandgap engineering of organics in copper electrodeposition, and provides guidance for the future design of organic materials in adsorbing other metal-based materials. Image 1 • Four quaternary ammonium salts based on diketopyrrolopyrroles were synthesized. • The electrochemical performance was correlate negatively with the bandgap. • SeDPP-QAS Shows the best performance in inhibiting copper electrodeposition. • Provides guidance for directional design of levelers. [ABSTRACT FROM AUTHOR]

In the last two decades, southwestern China (SWC) has experienced severe droughts, which are always accompanied by severe deficiencies in precipitation. In this study, we found that the interannual variability in boreal winter precipitation in SWC is modulated by the Philippine Sea anomalous anticyclone (PSAC). The interannual relationship between the PSAC and SWC precipitation experienced an interdecadal change around the early 1980s. The correlation between them was enhanced in the period from 1981 to 2001 (P2) compared to the period from 1961 to 1980 (P1). In P1, the moisture transported by the PSAC mainly affected eastern China, as the PSAC was located over the northern Philippine Sea, and the moisture budget of SWC was dominated by moisture transport at the western boundary. The PSAC, however, strengthened and shifted southwestward in P2, accompanied by a deepened India–Burma trough. As such, the PSAC transported moist air from the western North Pacific and the Indian Ocean into SWC through its southern boundary. Meanwhile, the stronger PSAC in P2 was accompanied by an upper-level convergence from the western North Pacific to the Bay of Bengal, which induced an upper-level divergence and ascending motion over SWC. Thus, the PSAC caused a significant increase in precipitation in P2. Stronger air–sea interactions in the western North Pacific induced by El Niño–Southern Oscillation may be responsible for the enhancement and southwestward shift of the PSAC in P2 compared to that in P1. [ABSTRACT FROM AUTHOR]

As one of the largest arid and semiarid regions, Central Asia (CA) is prone to drought, which imposes significant impacts on human communities and ecosystems. Understanding the historical and future wetting/drying trend with the backdrop of climate change is paramount to sustainable development in CA. However, previous studies for the historical period yielded inconsistent results due to different data, study durations and methods used and those for the future period are rare. By analyzing the latest generated long-term (1894–2020) homogenized station observations, multiple global climate model (GCM) outputs and their dynamically and statistically downscaled results, we find robust historical and future drying trend in CA, especially in the growing season (April–September). Though there is an increasing tendency in regional precipitation during 1894–2020 in CA, the Standard Precipitation Evapotranspiration Index (SPEI) shows a decreasing trend due to the dominating influence of regional warming. Compared to the non-growing season (October–March), the decreasing trend of SPEI is more profound in the growing season. Moreover, the SPEI calculated based on the GCM outputs and their dynamically and statistically downscaled results consistently shows future drying trend in CA throughout the 21st century, which robustly holds against the approaches used to calculate potential evapotranspiration (i.e., Thornthwaite and Penman-Monteith equations). Besides SPEI, the simulated soil moisture of surface layer also exhibits a decreasing tendency. All these lines of evidence suggest robust historical and future drying trends in CA, which have important implications for climate change adaptation in this region. [ABSTRACT FROM AUTHOR]

Plastic film mulch, which effectively maintains soil moisture by suppressing soil evaporation, has been widely used in cropland in Northwest China, where water scarcity severely restricts agricultural development. Plastic mulch affects surface albedo and blocks water vapor exchange between soil and atmosphere. Therefore, the large area of cropland covered by plastic film will have serious impacts on regional climate by modifying the surface-atmosphere partitioning of vapor and energy. In this study, a dynamic irrigation scheme was incorporated into the Weather Research and Forecasting model with Noah land surface scheme; two experiments (with and without plastic mulch) were designed to simulate the impacts of plastic mulch over cropland in Northwest China on regional climate. In irrigated cropland, the irrigation amount decreased substantially during the early stage of crop growth (ESCG; from 22 April to 1 July) with plastic mulch, especially in May, indicating that plastic mulch conserved agricultural water. In nonirrigated cropland, soil moisture in cropland with plastic mulch was clearly greater than that without plastic mulch. The influences of plastic mulch on land surface processes were mainly reflected in the ESCG, such that upward shortwave radiation increased and latent heat flux decreased. In cropland during the ESCG, after plastic mulch, the latent heat flux decreased significantly by 12–30 W m−2, the sensible heat flux increased significantly by 8–16 W m−2, and the surface air temperature increased significantly by 0.2–0.8 °C. The plastic mulch reduced water vapor in the lower atmosphere, which might lead to decrease precipitation in Northwest China. [ABSTRACT FROM AUTHOR]

The impacts of three periods of urban land expansion during 1990-2010 on near-surface air temperature in summer in Beijing were simulated in this study, and then the interrelation between heat waves and urban warming was assessed. We ran the sensitivity tests using the mesoscaleWeather Research and Forecasting model coupled with a single urban canopy model, as well as high-resolution land cover data. The warming area expanded approximately at the same scale as the urban land expansion. The average regional warming induced by urban expansion increased but the warming speed declined slightly during 2000-2010. The smallest warming occurred at noon and then increased gradually in the afternoon before peaking at around 2000 LST—the time of sunset. In the daytime, urban warming was primarily caused by the decrease in latent heat flux at the urban surface. Urbanization led to more ground heat flux during the day and then more release at night, which resulted in nocturnal warming. Urban warming at night was higher than that in the day, although the nighttime increment in sensible heat flux was smaller. This was because the shallower planetary boundary layer at night reduced the release efficiency of near-surface heat. The simulated results also suggested that heat waves or high temperature weather enhanced urban warming intensity at night. Heat waves caused more heat to be stored in the surface during the day, greater heat released at night, and thus higher nighttime warming. Our results demonstrate a positive feedback effect between urban warming and heat waves in urban areas. [ABSTRACT FROM AUTHOR]

Western China has experienced rapid urbanization since the Chinese reform process began in the late 1970s. It is essential to study the spatiotemporal patterns of warming induced by historical and future urban expansion and to evaluate adaptation strategies for the Chengdu–Chongqing metropolitan region (CCMR) in western China. The observed urban heat island intensity was ~ 1.5 K in July 2009–2011. We employed the weather research and forecasting (WRF) model using real and projected urban land-use data to simulate near-surface air temperatures for a crop, urban in 2010 and urban in 2030 scenarios in summer over the CCMR. The difference between urban 2010 and cropland scenarios is 0.93 K. Warming induced by urban development in 2010–2030 is in the range of 1–1.5 K, but warming induced by future urban development will be less intense than historical warming over eastern China. We increased roof albedo to 0.8 to assess the difference in near-surface air temperature between cool roofs (CR) and urban 2030 scenarios, which represents the maximum potential impact of CR; we also assessed the cooling caused by green roofs (GR) (i.e., the difference between the GR and urban 2030 scenarios). Greater cooling occurs during the day due to reflection of solar radiation by CR and additional water evaporation by GR. We provided an evaluation criterion, cooling efficiency (CE), to measure the local performances of CR and GR. CE represents the local cooling capability based on urban warming rather than absolute cooling over a larger spatial scale. CE reveals a lower nocturnal cooling capability, which poses a significant challenge to the applications of CR and GR at night. CR has a better cooling capability across CCMR than GR, only when roof albedo of CR exceeds 0.68. Measures enacted should be appropriately adjusted to optimize for cost, technology and energy savings. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei (BTH) region of China is one of the most frequently referenced areas with PM 2.5 air pollution and various control measures; hence, it is critical to project the future air quality on this region under different emission scenarios. In this study, using a global climate model, regional meteorological model, emission process model and air quality model, a future air quality research modeling system is designed and utilized to explore the air quality conditions over the BTH region in 2050. Two sensitivity experiments with different intensity emission inventories were set to quantify the influence of anthropogenic emissions on the future air quality in the BTH region under the identical representative concentration pathway (RCP) scenarios of RCP4.5, which is provided by the famous climate model Geophysical Fluid Dynamics Laboratory Earth System Model with the Generalized Ocean Layer Dynamics component (GFDL-ESM2G). The results show that the annual PM 2.5 concentration over BTH under the EIT1 (Emissions for Interim Target-1) scenario is 32.7 μg/m3, less than 35 μg/m3, approximately half of the value under the baseline emission scenario, and reaches the Interim Target-1 by the World Health Organization (WHO), which is also the national air quality standard for annual PM 2.5 concentrations in China. The frequency of nonpolluted projects can reach 95%, and the frequency of heavily polluted projects is well under 1% under the EIT1 emission scenario. These results indicate that emission reduction is significantly required to achieve the new Chinese PM 2.5 target. • The annual PM 2.5 concentration over BTH in EIT1 emission scenario is 32.7 μg/m3. • The frequency of non-polluted projects reaches to 95% under EIT1 emission scenario. • The EIT1 emission scenario be still effective in keeping the future sky cleaner. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation will become one of the main energy sources to achieve goals of carbon peak and carbon-neutral in China in the future. However, serious haze events have occurred frequently due to massive anthropogenic emissions in autumn and winter in China and resulted in a significant reduction of solar radiation reaching the Earth's surface. In this study, we conducted modifications to modelled solar radiation with the Weather Research and Forecasting (WRF)-Solar model by implementing the satellite-based aerosol optical depth (AOD) data into the model. The satellite-based AOD data have a higher spatial resolution and better accuracy. The studies were performed during the heavy haze period in the winter of 2016/2017 over North China (NC). Comparison with observations shows that the temporal-spatial variations of satellite-based AOD are consistent with those of AERONET and surface PM 2.5 concentration, and satellite-based AOD at different sites or some months is slightly underestimated. Satellite-based AOD and surface PM 2.5 concentrations in most of the southern areas of NC are significantly larger than in the northern parts. Simulated errors of Global horizontal irradiance (GHI) are reduced remarkably compared with those excluding the AOD data, especially in regions of the BTH (Beijing, Tianjin, and Hebei province), west of Shandong province, and north of Henan province. All RMSE and MAE of simulated GHI under three types of weather conditions declined by more than 20%, and 37%, respectively. Modelled errors of GHI on all-sky and cloudy-sky days are larger than those on clear-sky days due to the complicated aerosol-cloud-radiation interaction and simulated bias of cloud. Reductions of GHI caused by aerosols fall in between -140～-20 W m−2, and the spatial distribution is more refined and perform well compared to observations. Our results show that direct application of the satellite-based AOD data into the WRF-Solar model is very effective for improving the simulation of solar radiation and investigating the attenuation effect of solar radiation caused by aerosol in winter. [ABSTRACT FROM AUTHOR]

As a typical inland arid and semiarid region, Central Asia (CA) is vulnerable to the forced global warming (FGW) due to anthropogenic activity. Aiming at the interdecadal variation of the FGW-forced aridity pattern (FAP) in CA, we try to extract the associated oceanic and atmospheric modes by analyzing observations, reanalysis data and multi-model simulations during 1950–2016. The FAP in CA features a tripolar pattern with wetting–drying-wetting responses arranging from southeast to northwest and shows strong interdecadal-to-interannual amplitude variations. It is found that the sea surface temperature (SST) in the tropical South Atlantic (TSA) well correlates with the amplitude variation of FAP on interdecadal time scale, possibly through modulating the interannual SST modes characterized by the North Atlantic horseshoe-like dipole (NAHD) and the El Ninõ and South Oscillation (ENSO). Corresponding to the enhancing FAP from the middle 1970s to early 2000s, the TSA-modulated NAHD and ENSO, together with the Pacific Decadal Oscillation-modulated Indian Ocean Dipole-like mode, show connections with an Eurasian middle-latitude wave train coupled with the North Arctic Oscillation and equatorial low, which favors the moisture transport to strengthen the tripolar FAP by forming a local circulation dipole with positive/negative anomaly over the northwest/southeast CA. But after the early 2000s, the increasing FAP amplitude is decelerated due to the interdecadal decline of TSA accompanied by the weakened/reversed relationship between FAP and the NAHD/ENSO. Because of the corresponding breakdown of the wave train, the favorable local circulation is unavailable to support the sustained enhancement of FAP. Therefore, the multiscale coupling between the above oceanic and atmospheric modes is significantly related to the characteristic of stage of the forced aridity change in CA under the background of global warming. [ABSTRACT FROM AUTHOR]

North Central China (NCC) (34°–42°N, 95°–107°E), a typical transitional climate zone between westerlies and monsoon, shows multiple time‐scale variations in precipitation under the background of global warming. Thus, NCC moisture transport (NMT) was analysed based on reanalysis data from 1979–2015. By using the spatially unbounded dynamic recycling model, main NMT pathways and moisture sources were identified for the summer rainfall of NCC. The trend pattern of NMT manifests as a seesaw pattern with a weakening northwesterly transport but an enhancing southwesterly transport, suggesting an interaction between the mid‐latitude westerlies and the Indian monsoon. The temporal evolution of the NMT trend pattern exhibits interannual and multidecadal variability superimposed on long‐term trends, which correspond to the atmospheric and oceanic physical processes, respectively. The partial least squares regression analysis demonstrated that the temporal evolution of NMT trend patterns can be well explained by atmospheric and oceanic internal climate variability (ICV). At interannual time scales, the atmospheric ICV, composed of the circumglobal teleconnection (CGT) and East Atlantic (EA) and East Atlantic/Western Russia (EAWR) teleconnections, forms a Eurasian wave train that weakens westerly transport via the Europe blocking flow and enhances southwesterly transport via local circulation anomalies with a zonal dipole structure. However, oceanic ICV, composed of the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), exerts influence on a multidecadal time scale to decelerate the mid‐latitude westerly jet over the North Atlantic, providing favourable upstream background conditions for the formation of the Europe blocking and further maintaining the atmospheric ICV‐induced Eurasian wave train. Thus, the internal oceanic and atmospheric processes at different time scales couple to contribute to long‐term changes in precipitation over NCC under the background of global warming. [ABSTRACT FROM AUTHOR]

Heatwaves have considerable socioeconomic impact. Because of the urban heat island effect, risks associated with heatwaves are exacerbated in urban areas compared with surrounding regions. This study investigated the behaviors of local-scale urban heat island during a heatwave in Beijing using in situ observations and kilometer-scale simulations based on the Weather Research and Forecasting model. Results showed the observed urban heat island was enhanced by 0.78 °C during the heatwave episode, with greater increase at night than during daytime. The model with gridded urban canopy parameters was able to capture the spatiotemporal variation of surface air temperature, although it overestimated the magnitude. Spatial variation of urban canopy parameters could improve simulation of the spatiotemporal variations of near-surface air temperature in urban areas. Using a biophysical factorization method, urbanization-induced temperature changes were attributed to different driving factors. Results suggested that heatwave-related enhancement of urban heat island during daytime is primarily because of increased urban–rural contrast in surface evapotranspiration, whereas such enhancement at night is associated mainly with greater anthropogenic heat and enhanced warm advection. Since climate change make heatwaves more frequent, intense and persistent, targeted implementation of adaptation measures are needed to reduce the negative effects of urban heat island and to minimize their related risks to public health, power grids, and infrastructure. • This paper demonstrates the enhancement of urban heat island (UHI) due to heat wave using observations and numerical model. • Observed UHI in Beijing was enhanced by 0.78 °C during a heatwave episode, more profoundly during night than during daytime. • Enhanced UHI is due to increased urban–rural contrasts in surface evapotranspiration, anthropogenic heat and warm advection. • Synergistic interactions between UHI and heatwave present further heat-related risks for urban society and residents. [ABSTRACT FROM AUTHOR]

Abstract The cloud structure determined from ground-based measurements is generally important to the better understanding of the climate system. This study examines vertically-resolved cloud structures and their characteristics over Beijing using one year (1 December 2016 to 30 November 2017) of ground-based Ka-band (35 GHz) millimeter-wave cloud radar (MMCR) measurements. MMCR-derived cloud-base heights (CBHs) and cloud-top heights (CTHs) are compared with those derived from a Vaisala CL51 ceilometer (CL51) and those retrieved from the Himawari-8 geostationary satellite (HW8). Overall, the MMCR-derived CBHs are slightly higher (by 0.08 km) than those derived from the CL51. By contrast, the MMCR-derived CTHs are significantly higher (by 0.82 km) than those retrieved from the HW8 satellite. In the presence of precipitation, the MMCR-derived cloud boundaries are generally lower than those obtained by the CL51 due to the much larger rain-induced attenuation of MMCR signals. In particular, the discrepancy between MMCR- and CL51-derived CBHs decreases with rainfall intensity, as opposed to CTHs from the MMCR and the HW8 satellite that increase with rainfall intensity. CL51 and HW8 data can be used to complement MMCR data when there is rainfall or when MMCR data is missing. This enables the development of a seasonal cloud climatology for Beijing. CTHs reach a peak in summer, and CBHs are lowest in winter. The observed cloud properties reported here will not only facilitate future cloud forcing studies but also provide a validation data source for climate models. Highlights • The vertically-resolved cloud structures in Beijing are elucidated using MMCR, ceilometer and Himawari-8. • MMCR-derived cloud base is slightly higher than that from CL51, as opposed to cloud top from MMCR and HW8. • The rainfall impact has been analyzed on MMCR-derived cloud base height and top height. [ABSTRACT FROM AUTHOR]

Clouds are critical to the global radiation budget and hydrological cycle, but knowledge is still poor concerning the observed climatology of cloud-base height (CBH) in China. Based on fine-resolution sounding observations from the China Radiosonde Network (CRN), the method used to estimate CBH was modified, and uncertainty analyses indicated that the CBH is good enough. The accuracy of CBH estimation is verified by the comparison between the sounding-derived CBHs and those estimated from the micro-pulse lidar and millimeter-wave cloud radar. As such, the CBH climatology was compiled for the period 2006-16. Overall, the CBH exhibits large geographic variability across China, at both 0800 Local Standard Time (LST) and 2000 LST, irrespective of season. In addition, the summertime cloud base tends to be elevated to higher altitudes in dry regions [i.e., Inner Mongolia and the North China Plain (NCP)]. By comparison, the Tibetan Plateau (TP), Pearl River Delta (PRD) and Sichuan Basin (SCB) have relatively low CBHs (< 2.4 km above ground level). In terms of seasonality, the CBH reaches its maximum in summer and minimum in winter. A low cloud base tends to occur frequently (> 70%) over the TP, PRD and SCB. In contrast, at most sites over the Yangtze River Delta (YRD) and the NCP, about half the cloud belongs to the high-cloud category. The CBH does not exhibit marked diurnal variation in summer, throughout all CRN sites, probably due to the persistent cloud coverage caused by the East Asia Summer Monsson. To the best of our knowledge, this is the first CBH climatology produced from sounding measurements in China, and provides a useful reference for obtaining observational cloud base information. [ABSTRACT FROM AUTHOR]

Water-sealed underground oil caverns are quite different from conventional underground projects because of the harsher conditions. For one of the largest such caverns in China, conventional grouting materials could not meet the project standard. Therefore, the authors invented a new grouting material based on sulfoaluminate cement (SAC) and studied its properties under pressure circulation. During circulation, the time to the hydration exothermic peak time was reduced, and the peak temperature increased with the pressure. The compressive strength decreased during circulation and with the circulation time. These results were important for grouting during the project. [ABSTRACT FROM AUTHOR]

The impact of urban warming during the 2013 July-August extreme heat wave event across the Yangtze River Delta (YRD) in China was assessed. Using a newly developed high-resolution, land-use dataset, urban stations were identified from a total of 101 stations in the YRD. The difference between urban and non-urban/rural stations indicates that urban warming reached 1.22 °C in the 2013 summer heat wave. The new land-use dataset was then input to the Weather Research and Forecasting model to further understand the dynamical/physical processes of the urban warming during the heat wave. The model-simulated urban warming is ~1.5 °C. Impacts of urbanization on near-surface temperature had strong diurnal variation, reaching a peak at 19:00 LST, around sunset. In the daytime, urban warming was mainly caused by enhanced sensible heat fluxes and longwave radiation from the surface. Because of reduced latent heat flux and increased heat capacity, urban ground stored much more heat than rural ground during the daytime, which is later released as sensible heat flux from the surface at night, leading to the nocturnal urban warming. The simulation results also suggest a positive feedback between urban warming and heat wave intensity, which makes the heat wave more intense in urban than rural areas and the urban warming during the extreme heat wave stronger than its climatological mean. [ABSTRACT FROM AUTHOR]

Unique structural and electric properties of inorganic layered crystals (ILCs) have enlarged their functions as hosting matrixes in material manipulations. While most doping routes were carried out via introducing hetero dopants into the ILC compounds, doping with their component elements or element clusters is scarcely reported. Here, we demonstrated a first-principles investigation of the ILC MoS 2 monolayer decorated with deficient and excessive Mo n and S n ( n = −3 → 3) clusters on 5 × 5 supercells, with more emphasis on the n > 0 cases. The X n @MoS 2 (X = Mo or S, n = −3 → 3) systems can keep intrinsic monolayer form. When n > 0, most X n clusters prefer to be adsorbed on the host. However, the Mo n ( n = 2, 3) clusters will extrude one S atom from the host, forming new SMo 2 and SMo 3 clusters above the slab. System magnetism was inherited from cluster dopants, and the Mo 1 @MoS 2 and Mo 3 @MoS 2 possess 3 μB. All bandgaps in the defective complexes are lower than the pristine host, with a transition from direct to an indirect bandgap in Mo n @MoS 2 ( n = −3, −1, 3) and in S n @MoS 2 ( n = −3, −2 −1). The Mo n @MoS 2 ( n > 0) systems are stable at room temperature according to molecular dynamic simulations. Combining the 0D isoelement clusters to the 2D layered hosts, the present work offers a possible manipulation strategy to boost semiconductive ILCs applications in magnetics without needs of introducing hetero impurities. [ABSTRACT FROM AUTHOR]

The development of structurally diversified surfactants with multifunctional performance is an important task. Herein, we report a series of quaternary ammonium salts (QAS) as surfactants with hydrazone linker between a long chain and a triggered release of various fragrances. The resulting QAS with build-in aldehydes as a carrier of fragrances exhibited excellent amphiphilicity in water, their surface activity is evaluated by testing surface tension of the micelles in water with γ-CMC values ranging from 16.19 to 38.02 mN/m. Releasing performance by hydrolysis of hydrazones, meanwhile the formation of hydrazine derivatives as dynamic mixtures in acidic aqueous solutions, is investigated by headspace solid-phase micro-extraction (SPME) in combination with gas chromatography (GC) analysis, the results showed significant retention capacity for volatile aldehydes in up to 25 times higher than the neat reference of the corresponding aldehydes. The antibacterial performance of QAS is expressed by the minimum inhibitory concentration (MIC) values, along with an excellent activity on Gram-positive bacteria in the lowest concentration of 2 μg/mL. These QAS could be regarded as suitable fragrance delivery system in potential applications. [Display omitted] [ABSTRACT FROM AUTHOR]

Integrated assessment models and coupled earth system models both have their limitations in understanding the interactions between human activity and the physical earth system. In this paper, a new human-earth system model, BNU-HESM1.0, constructed by combining the economic and climate damage components of the Dynamic Integrated Model of Climate Change and Economy to the BNU-ESM model, is introduced. The ability of BNU-HESM1.0 in simulating the global CO concentration and surface temperature is also evaluated. We find that, compared to observation, BNU-HESM1.0 underestimates the global CO concentration and its rising trend during 1965-2005, due to the uncertainty in the economic components. However, the surface temperature simulated by BNU-HESM1.0 is much closer to observation, resulting from the overestimates of surface temperature by the original BNU-ESM model. The uncertainty of BNU-ESM falls within the range of present earth system uncertainty, so it is the economic and climate damage component of BNU-HESM1.0 that needs to be improved through further study. However, the main purpose of this paper is to introduce a new approach to investigate the complex relationship between human activity and the earth system. It is hoped that it will inspire further ideas that prove valuable in guiding human activities appropriate for a sustainable future climate. [ABSTRACT FROM AUTHOR]

Summary Evapotranspiration (ET) is critical to terrestrial ecosystems as it links the water, carbon, and surface energy exchanges. Numerous ET models were developed for the ET estimations, but there are large model uncertainties. In this study, a Bayesian Model Averaging (BMA) method was used to merge eight satellite-based models, including five empirical and three process-based models, for improving the accuracy of ET estimates. At twenty-three eddy covariance flux towers, we examined the model performance on all possible combinations of eight models and found that an ensemble with four models (BMA_Best) showed the best model performance. The BMA_Best method can outperform the best of eight models, and the Kling–Gupta efficiency (KGE) value increased by 4% compared with the model with the highest KGE, and decreased RMSE by 4%. Although the correlation coefficient of BMA_Best is less than the best single model, the bias of BMA_Best is the smallest compared with the eight models. Moreover, based on the water balance principle over the river basin scale, the validation indicated the BMA_Best estimates can explain 86% variations. In general, the results showed BMA estimates will be very useful for future studies to characterize the regional water availability over long-time series. [ABSTRACT FROM AUTHOR]

The demand for high-confidence regional climate change scenarios is increasing. It is therefore vitally important to better understand the behavior of Earth's climate system on regional scale and advance the knowledge of regional responses to global climate. With their ability to represent meso-scale forcings, such as coastline, complex topography, anthropogenic aerosols and land cover/use changes, Regional Climate Models (RCMs) are developed and used worldwide to investigate the effects of the above-mentioned meso-scale forcings on the local circulations that regulate the regional distribution of climatic variables. Considering the complexity of Asian Monsoon system, which is not only a physical process but also modulated by the interaction among physical, biological, chemical and social processes, a modeling framework Regional Integrated Environmental Modeling System (RIEMS) was proposed, developed and well tested before it was widely used in regional climate studies in the East Asia monsoon region. [ABSTRACT FROM AUTHOR]

The default fractional vegetation cover and terrain height were replaced by the estimated fractional vegetation cover, which was calculated by the Normalized Difference Vegetation Index (NDVI) of Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and the Digital Elevation Model of the Shuttle Radar Topography Mission (SRTM) system. The near-surface meteorological elements over northeastern China were assimilated into the three-dimensional variational data assimilation system (3DVar) module in the Weather Research and Forecasting (WRF) model. The structure and daily variations of air temperature, humidity, wind and energy fields over northeastern China were simulated using the WRF model. Four groups of numerical experiments were performed, and the simulation results were analyzed of latent heat flux, sensible heat flux, and their relationships with changes in the surface energy flux due to soil moisture and precipitation over different surfaces. The simulations were compared with observations of the stations Tongyu, Naiman, Jinzhou, and Miyun from June to August, 2009. The results showed that the WRF model achieves high-quality simulations of the diurnal characteristics of the surface layer temperature, wind direction, net radiation, sensible heat flux, and latent heat flux over semiarid northeastern China in the summer. The simulated near-surface temperature, relative humidity, and wind speed were improved in the data assimilation case (Case 2) compared with control case (Case 1). The simulated sensible heat fluxes and surface heat fluxes were improved by the land surface parameterization case (Case 3) and the combined case (Case 4). The simulated temporal variations in soil moisture over the northeastern arid areas agree well with observations in Case 4, but the simulated precipitation should be improved in the WRF model. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations. The assimilation datasets generated by this work can be applied to research on climate change and environmental monitoring of arid lands, as well as research on the formation and stability of climate over semiarid areas. [ABSTRACT FROM AUTHOR]

The regression tree method is used to upscale evapotranspiration (ET) measurements at eddy-covariance (EC) towers to the grassland ecosystems over the Dryland East Asia (DEA). The regression tree model was driven by satellite and meteorology datasets, and explained 82% and 76% of the variations of ET observations in the calibration and validation datasets, respectively. The annual ET estimates ranged from 222.6 to 269.1 mm yr−1 over the DEA region with an average of 245.8 mm yr−1 from 1982 through 2009. Ecosystem ET showed decreased trends over 61% of the DEA region during this period, especially in most regions of Mongolia and eastern Inner Mongolia due to decreased precipitation. The increased ET occurred primarily in the western and southern DEA region. Over the entire study area, water balance (the difference between precipitation and ecosystem ET) decreased substantially during the summer and growing season. Precipitation reduction was an important cause for the severe water deficits. The drying trend occurring in the grassland ecosystems of the DEA region can exert profound impacts on a variety of terrestrial ecosystem processes and functions. [ABSTRACT FROM AUTHOR]

Abstract: Evapotranspiration (ET) is a key component of terrestrial ecosystems because it links the hydrological, energy, and carbon cycles. Several satellite-based ET models have been developed for extrapolating local observations to regional and global scales, but recent studies have shown large model uncertainties in ET simulations. In this study, we compared eight ET models, including five empirical and three process-based models, with the objective of providing a reference for choosing and improving methods. The results showed that the eight models explained between 61 and 80% of the variability in ET at 23 eddy covariance towers in China and adjacent regions. The mean annual ET for all of China varied from 535 to 852mmyr−1 among the models. The interannual variability of yearly ET varied significantly between models during 1982–2009 because of different model structures and the dominant environmental factors employed. Our evaluation results showed that the parameters of the empirical methods may have different combination because the environmental factors of ET are not independent. Although the three process-based models showed high model performance across the validation sites, there were substantial differences among them in the temporal and spatial patterns of ET, the dominant environment factors and the energy partitioning schemes. The disagreement among current ET models highlights the need for further improvements and validation, which can be achieved by investigating model structures and examining the ET component estimates and the critical model parameters. [Copyright &y& Elsevier]

Global Land Surface Satellite-downward surface shortwave radiation (GLASS-DSSR) products have been routinely produced from 2008–2010 based on an improved look-up table algorithm, which explicitly accounts for the variations of cloud optical depth, water vapor content, and elevation. In this study, we validated and assessed the accuracy of these products in arid and semiarid regions of China. Toward this goal, observation data-sets provided by the Arid and Semiarid Region Collaborative Observation Project as well as four other metrological sites were collected, chosen, and preprocessed for the final validation. Due to the possible effect of spatial collocation and the strong adjacency pixel effect in instantaneous products, we used a more sophisticated validating scheme in order to reduce the impacts from these effects as much as possible. Evidences indicate that the GLASS-DSSR products are considerably accurate over most parts of arid and semiarid regions in China, but in complex terrain areas the products might need further refinements. TheR2at all sites (except Naqu) was larger than 0.8 with a root mean square error (RMSE) range of about in 90–130 W/m2. Linear regression analyses suggest that GLASS-DSSR products tend to overestimate DSSR in the interval of low surface-measured values and symmetrically underestimate DSSR in the interval of high values. This systematic error may result from inappropriate assumptions about clouds and aerosol loadings over the regions in the operational algorithm. [ABSTRACT FROM PUBLISHER]