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Fine particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) has adverse effects on human health and the atmospheric environment. The estimation of surface PM2.5 concentrations has made intensive use of satellite-derived aerosol products. However, it has been a great challenge to obtain high-quality and high-resolution PM2.5 data from both ground and satellite observations, which is essential to monitor air pollution over small-scale areas such as metropolitan regions. Here, the space–time extremely randomized trees (STET) model was enhanced by integrating updated spatiotemporal information and additional auxiliary data to improve the spatial resolution and overall accuracy of PM2.5 estimates across China. To this end, the newly released Moderate Resolution Imaging Spectroradiometer Multi-Angle Implementation of Atmospheric Correction AOD product, along with meteorological, topographical and land-use data and pollution emissions, was input to the STET model, and daily 1 km PM2.5 maps for 2018 covering mainland China were produced. The STET model performed well, with a high out-of-sample (out-of-station) cross-validation coefficient of determination (R2) of 0.89 (0.88), a low root-mean-square error of 10.33 (10.93) µg m−3, a small mean absolute error of 6.69 (7.15) µg m−3 and a small mean relative error of 21.28 % (23.69 %). In particular, the model captured well the PM2.5 concentrations at both regional and individual site scales. The North China Plain, the Sichuan Basin and Xinjiang Province always featured high PM2.5 pollution levels, especially in winter. The STET model outperformed most models presented in previous related studies, with a strong predictive power (e.g., monthly R2=0.80), which can be used to estimate historical PM2.5 records. More importantly, this study provides a new approach for obtaining high-resolution and high-quality PM2.5 dataset across mainland China (i.e., ChinaHighPM2.5), important for air pollution studies focused on urban areas.

The next-generation geostationary meteorological Himawari-8 satellite carrying the Advanced Himawari Imager (AHI) allows frequent observations of the atmosphere, the surface, and oceans every 10 min. With its retrieval algorithms recently updated, Himawari-8/AHI Version 2 Level 2 aerosol products are now available. However, these retrievals have not yet undergone a quality assessment. This study aims to comprehensively validate the official aerosol optical properties derived from Himawari-8/AHI over land and ocean. Aerosol Robotic Network and Sun-Sky Radiometer Observation Network ground-based measurements at 98 stations in the Himawari-domain region are used to validate aerosol optical depth (AOD, or τ) retrievals at 500 nm and Angstrom exponent (AE) retrievals at 440–675 nm from the year 2016. The AOD retrievals agree well with surface observations (i.e., from linear regression, slope = 0.876, intercept = 0.076, and correlation coefficient = 0.756) with a mean absolute error and a root-mean-square error of 0.168 and 0.293, respectively. On site and regional scales, large uncertainties are seen, especially in Australia (significant overestimation) and South Asia (significant underestimation). The AOD retrievals can correctly capture daily variations and show the best (worst) performance in summer (spring). The AE performance is poorer on all scales, showing overall underestimations, especially in Australia, Southeast Asia, and China. The data quality of AOD retrievals improves as the vegetation coverage and the AE increases. This suggests that the official aerosol retrieval algorithm still faces great challenges over bright surfaces and under coarse-particle-dominated conditions. In general, approximately 61% and 64% of the AOD matchups meet the newly defined expected errors of [0.330 × τ + 0.024; −0.132 × τ − 0.125] and [0.519 × τ + 0.005; −0.007 × τ − 0.194] determined by ground measurements and aerosol retrievals, respectively. The highly variable accuracy of aerosol retrievals raises a concern about the reliability of the current product under different environmental conditions and underlying surfaces. It also sheds light on what future improvements need implementing to the aerosol retrieval algorithm.

The pairing of ions of opposite charge is a central principle of chemistry. Even though the ability to intercalate anions is desirable for many applications, it remains a key challenge for numerous host materials with their outmost layers beingn anions. In this work, we introduce a hydrothermal ion-exchange synthesis to intercalate oxidative S and Se anions between the Se layers of FeSe, which leads to single crystals of novel compounds (Se/S)x(NH3)yFe2Se2. In particular, the unusual anion-anion bonding between the intercalated S (or Se) and Se layers exhibits strong ionic characteristics. The charge transfer through the Se layer to S (or Se) intercalants is further confirmed by the elevated oxidation state of Fe ions and the dominant hole carriers in the intercalated compounds. By intercalating S, for the first time superconductivity emerged in hole-doped iron chalcogenides. The generality of this chemical approach was further demonstrated with layered FeS and NiSe. Our findings thus open an avenue to exploring diverse aspects of anionic intercalation in similar materials.

This study evaluates the long-term Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) Level 3 atmospheric aerosol products over land. For this purpose, three monthly aerosol optical depth (AOD) datasets, including Dark Target (DT), Deep Blue (DB) and combined DT and DB (DTB) during 2003–2017, are collected. Aerosol Robotic Network (AERONET) Version 2 Level 2.0 (cloud-screened and quality-assured) monthly measurements at 431 sites around the world are selected for comparison. This study attempts to provide a better understanding of the different MODIS products for their applicability at multiple spatial scales and their suitability for representing the long-term trend of aerosol characteristics. Experiments are performed with direct comparisons between MODIS retrievals and AERONET measurements at global, local to site scales. Meanwhile, the spatial and temporal variations are also compared and discussed. Our results illustrate that C6.1 MODIS AOD retrievals are well correlated with AERONET AOD measurements globally, while the DTB product performs best at most regions, yet the DB product is superior at the site scale. In general, Terra AOD products always overestimate while Aqua AOD products are more accurate in describing the annual mean AOD loadings over land. For long-term aerosol trends, there are small differences between Terra and Aqua aerosol products. Among the three aerosol datasets, neither one can consistently outperform the others in both spatial and temporal aerosol variations over land. In general, DTB products can more accurately capture the correct aerosol changes and are strongly recommended for selection in related aerosol studies at the global scale.

Satellite-derived aerosol products provide long-term and large-scale observations for analysing aerosol distributions and variations, climate-scale aerosol simulations, and aerosol–climate interactions. Therefore, a better understanding of the consistencies and differences among multiple aerosol products is important. The objective of this study is to compare 11 global monthly aerosol optical depth (AOD) products, which are the European Space Agency Climate Change Initiative (ESA-CCI) Advanced Along-Track Scanning Radiometer (AATSR), Advanced Very High Resolution Radiometer (AVHRR), Multi-angle Imaging SpectroRadiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Visible Infrared Imaging Radiometer (VIIRS), and POLarization and Directionality of the Earth's Reflectance (POLDER) products. AErosol RObotic NEtwork (AERONET) Version 3 Level 2.0 monthly measurements at 308 sites around the world are selected for comparison. Our results illustrate that the spatial distributions and temporal variations of most aerosol products are highly consistent globally but exhibit certain differences on regional and site scales. In general, the AATSR Dual View (ADV) and SeaWiFS products show the lowest spatial coverage with numerous missing values, while the MODIS products can cover most areas (average of 87 %) of the world. The best performance is observed in September–October–November (SON) and the worst is in June–July–August (JJA). All the products perform unsatisfactorily over northern Africa and Middle East, southern and eastern Asia, and their coastal areas due to the influence from surface brightness and human activities. In general, the MODIS products show the best agreement with the AERONET-based AOD values on different spatial scales among all the products. Furthermore, all aerosol products can capture the correct aerosol trends at most cases, especially in areas where aerosols change significantly. The MODIS products perform best in capturing the global temporal variations in aerosols. These results provide a reference for users to select appropriate aerosol products for their particular studies.

Our previous study illustrated that the operational Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) Dark Target (DT) and Deep Blue (DB) combined products (denoted as DTB0) are not always the best in most regions due to its unsuitable merge approach. Therefore, the objective of this study is to develop an improved merge approach to increase the spatiotemporal data coverage and reduce the estimation uncertainty. For this, three tests, i.e., a land-use-type test, a surface-relief test, and an aerosol-type test are performed according to the strengths and weakness of the performances of the DT and DB algorithms with their high-quality assurance retrievals (QA = 3 for DT and QA ≥ 2 for DB) against the newest Aerosol Robotic Network (AERONET) Version 3 Level 2.0 measurements. Based on this, new merged DT and DB products (denoted as DTB1) are generated. The Terra and Aqua DTB1 products are then validated against AERONET measurements at 286 sites on site, continental, and global scales, and for varying underlying surfaces and elevated terrains from 2013 to 2017. The DTB0 products for the same period are collected for comparison. More than 90% of the sites now have more data points, and the performances of the DTB1 products are improved with an increased percentage of the data falling within the expected error [±(0.05 + 15%)] envelope and reduced mean absolute errors and root-mean-square errors compared with DTB0 products at most sites. Separate- and equal-number comparisons show that the DTB1 products significantly improve both the data coverage and data quality. The new merged products are more accurate and less affected by varying surface structures than the operational products. These results suggest that the improved merge approach is more robust and can be used for generating more accurate global aerosol products.

The accuracies of the two-stream discrete-ordinate-method (DOM) and Eddington approximation schemes are systematically compared using the BCC_RAD radiative transfer scheme used in a general circulation model (GCM). It is found that the two-stream DOM produces more accurate results for the upward radiative flux, downward radiative flux and heating rate under clear-sky conditions in an offline radiation model, whereas the Eddington approximation is more accurate under all-sky conditions. An experiment using satellite data as the approximation of cloud properties confirms the superiority of the Eddington approximation under cloudy-sky conditions. Experiments using the GCM of the Beijing Climate Center (BCC_AGCM2.0.1) show that, compared to the two-stream DOM, the Eddington approximation can enhance the fraction of low cloud, and this increased cloud fraction can affect the differences in radiative fluxes between these schemes. This study suggests that the more suitable approach in GCMs is to use the Eddington approximation.

Numerical simulation of the buoyant river plume in the Jiulongjiang River (JR) estuary, China, and its shelf in a wet season, April–September 2015, is constructed and applied to explore the evolution of the JR plume. The model is forced with realistic forcing, including river discharge, tides, wind stress, surface heat flux and freshwater flux, and ocean open boundary conditions. The simulation results agree well with in-situ and satellite observations. A Lagrangian particle tracking method is used to identify the freshwater pathway. It is found that the JR freshwater tends to escape the estuary-shelf system to the north from April to mid-August but to the south since late August. Based on a self-organizing map (SOM) analysis, four major JR patterns are identified. A northeastward plume pattern has the highest frequency of occurrence (44.8%), while a southwestward plume pattern has the second highest frequency of occurrence (33.9%). The other two patterns are transitional. The analysis of the alongshore and cross-shore momentum balances indicates that the JR plume is largely shaped by wind and background alongshore current. Particularly, the background coastal current plays an important role for the JR freshwater escape to the north in the Taiwan Strait.

Dust size distributions from the two-mode scheme and the continuous scheme are compared with AERONET observations. The two-mode dust scheme contains fine and coarse modes with fixed effective radius and effective variance for each mode. The continuous scheme takes into account the size distribution with a prognostic variation of effective radius and effective variance. The size distribution of the two-mode scheme changes with the fine/coarse mode mass ratio. However, it is impossible to make both effective radius and effective variance to match with the observed result by adjusting the fine/coarse mode mass ratio. The size distribution from the continuous scheme can be much closer to the observations. A new parameterization for dust optical properties is proposed based on the continuous scheme. The shape of non-spherical dust particles is approximated using a rotational symmetric spheroid in optical property calculations. This parameterization can also be used for the two-mode scheme. The parameterization is applied to a set of idealized one-dimensional radiative transfer calculations to investigate the sensitivity of dust radiative forcing to various attributes, including dust loading, dust solar heating rate, surface albedo, effective radius and variance. The parameterization is also evaluated in a climate model. Though at each selected region the two-mode scheme can always be tuned to approximate the results of the continuous scheme, on global scales, however, the two-mode dust scheme cannot produce similar radiative forcing as the continuous scheme and the relative error can be over 30% in several desert regions. The accurate results in radiative forcing can not be achieved by tuning the mass ratio.

A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

Climate models generally fail to produce a warmer (by as much as 0.5 °C) early to mid-Holocene than the pre-industrial in the global annual temperature, which has been termed the Holocene temperature conundrum. Here we use a fully coupled atmosphere-ocean general circulation model to test whether the conundrum can be partially resolved by considering the fact that atmospheric dust loading was much reduced during the early to mid-Holocene. Our experiments show that the global annual mean surface temperature increases by 0.30 °C and 0.23 °C for the mid-Holocene (6 ka) and early Holocene (9 ka), respectively, if the dust is completely removed. The temperature increase scales almost linearly with the fraction of dust being removed, with the 50% dust reduction experiment for the 6 ka being the only one deviating from the linear trend. The indirect effect of dust, which is highly uncertain and is not included in the model, may further enhance the warming. Therefore, the neglect of dust reduction in the Holocene in climate models could contribute significantly to the model-data discrepancy, especially in the Northern Hemisphere.

Chiang Mai suffers from adverse haze associated with heavy biomass burning (BB) during almost every dry season (February to April). As an important source of light-absorbing carbonaceous aerosols (black carbon and brown carbon), BB can have strong radiative effects on local and regional climate. However, studies on characterizing the impacts of BB aerosols on climate in Chiang Mai are quite limited. In this study, we use a global chemical transport model (GEOS-Chem) coupled with the rapid radiative transfer model for GCMs (RRTMG) to estimate the radiative forcing (RF) of BB aerosols in Chiang Mai. Brown carbon (BrC) is included as an absorber and treated as an individual tracer in the model. To our best knowledge, this is the first study to estimate the BrC RF in Chiang Mai. As evaluated, our simulations that were assigned with medium- and high-absorbing kBrC (BrC imaginary refractive index) well reproduces the absorption coefficient of ambient BrC in Chiang Mai. Based on our estimations, 33–40% of total carbonaceous aerosol absorption at 440 nm is attributed to BrC and 60–67% to BC during dry season. As estimated, BrC contributes 14 ± 3% to the instantaneous RF of total carbonaceous aerosol (IRFCAs) at the top of atmosphere (TOA) and 16 ± 3% to IRFCAs at surface. Moreover, including BrC in model strengthens (reduces) the surface (TOA) cooling effect of total organic carbon by 9 ± 5% (9 ± 3%), indicating the warming effect of BrC in the atmosphere in Chiang Mai.

Aerosol-induced increase of relative dispersion of cloud droplet size distribution ε exerts a warming effect and partly offsets the cooling of aerosol indirect radiative forcing (AIF) associated with increased droplet concentration by increasing the cloud droplet effective radius (Re) and enhancing the cloud-to-rain autoconversion rate (Au) (labeled as the dispersion effect), which can help reconcile global climate models (GCMs) with the satellite observations. However, the total dispersion effects on both Re and Au are not fully considered in most GCMs, especially in different versions of the Community Atmospheric Model (CAM). In order to accurately evaluate the dispersion effect on AIF, the new complete cloud parameterizations of Re and Au explicitly accounting for ε are implemented into the CAM version 5.1 (CAM5.1), and a suite of sensitivity experiments is conducted with different representations of ε reported in the literature. It is shown that the shortwave cloud radiative forcing is much better simulated with the new cloud parameterizations as compared to the standard scheme in CAM5.1, whereas the influences on longwave cloud radiative forcing and surface precipitation are minimal. Additionally, consideration of the dispersion effect can significantly reduce the changes induced by anthropogenic aerosols in the cloud-top effective radius and the liquid water path, especially in the Northern Hemisphere. The corresponding AIF with the dispersion effect considered can also be reduced substantially by a range of 0.10 to 0.21 W m−2 at the global scale and by a much bigger margin of 0.25 to 0.39 W m−2 for the Northern Hemisphere in comparison with that of fixed relative dispersion, mainly dependent on the change of relative dispersion and droplet concentrations (Δε∕ΔNc).

Si/PEDOT:PSS core/shell nanowire hetero-junctions with adjustable electrical characteristics are reported. They exhibit an ohmic behavior ascribed to p-type Si/PEDOT:PSS, whereas n-type Si/PEDOT:PSS displays a rectifying nature. A large interfacial area within the core/shell nanowire configuration is beneficial for charge transport, decreasing the resistance by 60% for p-type Si/PEDOT:PSS, and increasing the rectification ratio by 10 times for n-type Si/PEDOT:PSS as compared to the planar structure. By incorporating a perfluorinated ionomer into PEDOT:PSS, the reverse saturation current densities of n-type Si/PEDOT:PSS core/shell nanowire hetero-junctions are reduced by 2 to 4 orders of magnitude, and the rectification performances are enhanced.

The current capacity of northern high-latitude forests to sequester carbon has been suggested to be undermined by the potential increase in fire and insect outbreaks. Here we investigate the response of the terrestrial ecosystems in the province of British Columbia (BC), Canada, to the recent large mountain pine beetle (MPB) outbreak that started in 1999 as well as changing climate and continually increasing atmospheric CO2 concentration up to 2050, in a combined framework, using a process-based model. Model simulations suggest that the recent MPB outbreak results in BC's forests accumulating 328 Tg less carbon over the 1999–2020 period. Over this same period changing climate and increasing atmospheric CO2 concentration, however, yield enhanced carbon uptake equal to a cumulative sink of around 900–1060 Tg C, depending on the future climate change scenario, indicating that the reduced carbon uptake by land due to the MPB disturbance may already be surpassed by 2020.

In this study, aerosol indirect effects suffer from large uncertainty in climate models and among observations. This study focuses on two plausible factors: regime dependence of aerosol-cloud interactions and the effect of cloud droplet spectral shape. We show, using a new parcel model, that combined consideration of droplet number concentration (Nc) and relative dispersion (e, ratio of standard deviation to mean radius of the cloud droplet size distribution) better characterizes the regime dependence of aerosol-cloud interactions than considering Nc alone. Given updraft velocity (w), e increases with increasing aerosol number concentration (Na) in the aerosol-limited regime, peaks in the transitional regime, and decreases with further increasing Na in the updraft-limited regime. This new finding further reconciles contrasting observations in literature and reinforces the compensating role of dispersion effect. The nonmonotonic behavior of e further quantifies the relationship between the transitional Na and w that separates the aerosol- and updraft-limited regimes.

Recently, NASA has released the newest Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra Collection 6.1 (C6.1) aerosol product generated at a higher spatial resolution of 3 km (i.e., MOD04_3K) with main updates in the radiation calibration and the Dark Target (DT) aerosol algorithm. This product is of great importance for air pollution studies at small to medium scales but has not been fully evaluated. This paper aims to provide a comprehensive validation and error analysis of the MOD04_3K C6.1 aerosol optical depth (AOD) data set against Aerosol Robotic Network (AERONET) Version 3 AOD measurements at different spatiotemporal scales from 2013 to 2017 over land and ocean. Results suggest that the data quality of the MOD04_3K AOD data set is overall improved at different spatial scales after quality control. In general, the highest-quality 3 km AOD retrievals (quality assurance = 3) and ground-based measurements are highly correlated (correlation coefficient = 0.81), with a mean absolute error of 0.08 and a root-mean-square error of 0.12. About 63% of the data samples fall within the expected error envelope on a global scale. Nevertheless, there is large spatial heterogeneity in the performance at regional and site scales, with the worse accuracy generally observed in areas covered by bright surfaces or dominated by human activities. This is mainly due to the difficulties in estimating surface reflectance and the aerosol-type assumption. In addition, aerosol retrievals are overall overestimated, especially over North America, Europe, and East Asia. Furthermore, the estimation errors and uncertainties are highly related to varying surface and atmospheric aerosol conditions, which become larger with increases in surface brightness, aerosol loading, Angstrom exponent and single scattering albedo. The MODIS 3 km AOD data set is generally less accurate than its coarser-spatial-resolution (10 km) counterpart due to a decrease in the opportunity to discard marginal pixels from the retrieval. Therefore, further algorithm improvements are needed to reduce the estimation uncertainty, especially for heterogeneous urban and bright surfaces.

Fine particulate matter (PM2.5) is closely related to the atmospheric environment and human life. Satellite-based aerosol optical depth (AOD) products have been widely applied in estimating daily PM2.5 concentrations over large areas using statistical regression models. However, they are often given at coarse spatial resolutions which limit their applications in small or medium scales. This study aims to produce PM2.5 concentrations at a high spatial resolution (1 km) across China based on the newly released Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD product using a newly developed space-time random forest (STRF) model. Daily PM2.5 concentrations for 2016 were estimated from in-situ surface PM2.5 measurements, and meteorological and ancillary variables. The 10-fold cross-validation (CV) approach and three popular models, including the multiple linear regression model, the geographically weighted regression model, and the two-stage model, are employed for validation and cross-comparison. A sample-based CV of the STRF model shows a high and stable accuracy with a coefficient of determination equal to 0.85, a root-mean-square error of 15.57 μg m−3, and a mean prediction error of 9.77 μg m−3. This finding suggests that the STRF model can predict PM2.5 daily, monthly, and annual concentrations at an unprecedented spatial resolution and accuracy across China. It also appears to have outperformed the above popular models and the previous related studies. In general, the STRF model is robust and can accurately estimate PM2.5 concentrations by taking advantage of the ensemble regression approach, the synergy of space-time information, and the high-resolution, high-quality, and wide-spatial-coverage of the MAIAC AOD product. It may thus also be useful for applications in related air pollution studies, especially those focused on urban areas.

Despite the importance of precipitation and moisture transport over the Tibetan Plateau for glacier mass balance, river runoff and local ecology, changes in these quantities remain highly uncertain and poorly understood. Here we use observational data and model simulations to explore the close relationship between summer rainfall variability over the southwestern Tibetan Plateau (SWTP) and that over central-eastern India (CEI), which exists despite the separation of these two regions by the Himalayas. We show that this relationship is maintained primarily by ‘up-and-over' moisture transport, in which hydrometeors and moisture are lifted by convective storms over CEI and the Himalayan foothills and then swept over the SWTP by the mid-tropospheric circulation, rather than by upslope flow over the Himalayas. Sensitivity simulations confirm the importance of up-and-over transport at event scales, and an objective storm classification indicates that this pathway accounts for approximately half of total summer rainfall over the SWTP., While precipitation over the Tibetan Plateau is a vital resource for glacier mass balance, river runoff and local ecology, the controlling mechanisms are poorly understood. Here, the authors combine observations and simulations and show that convective storms over India sweep moisture up and over the plateau.

In this work, hole transport layer (HTL) free bulk heterojunction organic solar cells (BHJ-OSCs) based on PTB7:PCBM as active layer have been fabricated by employing various ITO anodes with different work function. The power conversion efficiency of the BHJ-OSCs is significantly improved from 3.76 to 8.47% with increasing the work function of the ITO anode. By combining Mott–Schottky curves, external quantum efficiency and reflectance spectra of the BHJ-OSCs, we identify that the improved optoelectronic conversion due to the enhanced built-in electric field within the active layer which is induced by the high work function ITO anodes. The hole transport layer free device structure can be considered for the fabrication of cost-effective BHJ-OSCs due to their simple structure and high efficiency.

The cloud longwave (LW) scattering effect has been ignored in most current climate models. To investigate its climate impact, we apply an eight-stream DIScrete Ordinates Radiative Transfer (DISORT) scheme to include the cloud LW scattering in the General circulation model version of the LongWave Rapid Radiative Transfer Model (RRTMG_LW) and the Community Atmospheric Model Version 5 (CAM5). Results from the standalone RRTMG_LW and from diagnostic runs of CAM5 (no climate feedback) show that the cloud LW scattering reduces the upward flux at the top of the atmosphere and leads to an extra warming effect in the atmosphere. In the interactive runs with climate feedback included in CAM5, the cloud LW scattering effect is amplified by the water vapor-temperature feedback in a warmer atmosphere and has substantial influences on cloud fraction and specific humidity. The thermodynamic feedbacks are more significant in the northern hemisphere and the resulting meridional temperature gradient is different between the two hemispheres, which strengthens the southern branch of Hadley circulation, and modulates the westerly jet near 50° S and the upper part of Walker circulation. Our study concludes that the cloud LW scattering effect could have complex impacts on the global energy budget and shall be properly treated in future climate models.

Formulation of the dust emission scheme in the global aerosol-climate modeling system ECHAM5-HAM has been improved. Modifications on the surface aerodynamic roughness length, soil moisture and East-Asian soil properties are included in the parameterization, which result in a large impact on the threshold wind friction velocity for aeolian erosion and thus influence the simulated dust emission amount. The annual global mean of dust emission in the year 2000 is reduced by 76.5% and 2.2%, respectively, due to changes in the aerodynamic roughness length and the soil moisture. An inclusion of detailed East-Asian soil properties leads to an increase of 16.6% in the annual global mean of dust emission, which exhibits mainly in the arid and semi-arid areas of northern China and southern Mongolia. Measurements of the surface dust concentrations are collected in remote marine sites globally and in dust source regions of East Asia. The averaged relative differences between model results and measurements are reduced from 17% to 12% in global remote marine sites and from 69% to 30% in East Asia, by including the improvements. Comparisons between model results and available measurements verify a more realistic dust distribution with the improved emission scheme.

The aerosol dispersion effect ( the influence of an increasing number of aerosol particles on the width of the cloud droplet size distribution) has been observed in maritime clouds [ e. g., Liu and Daum, 2002]. Climate model simulations show that the dispersion effect at least partially compensates the first indirect aerosol effect. The application of observational data from maritime stratus/stratocumulus clouds into an adiabatic parcel model allows to analyze the role of the aerosol activation process for the dispersion effect in order to better understand the microphysical mechanism of the dispersion effect in the early stage of cloud formation. When the total aerosol number concentration is increased, the parcel model simulations show that the higher number of aerosol particles at cloud base reduces the supersaturation, which results in a slower particle growth rate, and thus more cloud droplets remain small. This extends the droplet spectra toward the smaller size end and increases the spectral width. The broadening effect partially offsets the reduction of droplet radius because of an enhanced number of aerosol particles, leading to a positive aerosol dispersion effect. Sensitivity studies show that the dispersion effect decreases for increasing updraft velocities. When the updraft velocity approaches 55 cm s(-1), the dispersion effect almost vanishes for maritime stratus clouds. Aerosols composed of sulfate or of less soluble organics increase the dispersion effect as compared to sea-salt aerosols, whereas condensation of gaseous nitric acid on aerosols decreases the dispersion effect in marine stratus clouds.