Showing papers by "Nanjing University of Information Science and Technology published in 2023"

Synthesis and modification of ultrathin g-C3N4 for photocatalytic energy and environmental applications

Abstract: Nanostructured heterogeneous photocatalysts process represent attractive strategies to convert directly solar energy to chemical energy, which is important to address the increasing challenges of clean energy and environmental issues. Graphitic carbon nitride, as a metal-free photocatalyst with a suitable bandgap, has played an irreplaceable role in energy and environmental fields. Ultrathin g-C3N4 (UCN) with few layers owns a larger specific area for more reactive sites and intimate interface contact possibility, which provides more function modifications for overcoming inherent drawbacks to realize target-specific applications. In the last few years, developments have been witnessed in the studies of UCN with different synthesis methods or further modifications in photocatalytic energy and environmental application. This review first comprehensively summarized two synthetic approaches of UCN, namely, top-down exfoliation approaches and bottom-up molecular assembly approaches. Then, various modification strategies of UCN including element doping, introduction of vacancies and formation of heterostructure were elaborated for multifarious photocatalytic applications. The roles of UCN in diversiform applications and specific mechanisms are detailly discussed. Finally, on account of clear cognition and a general overview of the state of UCN, the promising direction of designing and application of UCN was emphasized based on the existing opportunities and challenges.

Diverse Dispersion Effects and Parameterization of Relative Dispersion in Urban Fog in Eastern China

Abstract: Understanding cloud droplet relative dispersion is critical for mitigating the confounding effect of aerosol-cloud interactions in the simulation of the global climatic patterns. Diverse dispersion effects, meaning that the correlation between relative dispersion (ε) and fog droplet number concentration (Nf) changes from positive to negative as Nf increases at a fixed liquid water content (LWC) condition, were found in the urban fog observed during the winters of 2017 and 2018 in Nanjing, China. The dominant microphysical processes driving the diverse dispersion effects were found to be activation, condensation, deactivation, evaporation, and sedimentation. The critical first bin (diameter range of 2–4 μm) strength and volume-mean diameter (Dv) for classifying the diverse dispersion effects are 0.3–0.4 and 10–12 μm, respectively. The mean dispersion offset (DO) was −27.6% for weakening the Twomey effect and 27.5% for enhancing it. Assuming the Gamma distribution for the fog droplet number size distribution, the mean dispersion effect was significantly underestimated at DO < 0. Based on the measured nonmonotonic relationship between ε and Dv, we establish ε parameterization using a Nelder function, which can be applied to the diverse dispersion effects. The mean deviation for diagnosing DO was less than 10% for DO > 0 and less than 50% for DO < 0. These results could shed new light on understanding the diverse dispersion effects, which cloud help reduce the uncertainties in the simulation of aerosol-cloud interactions.

Trait-based ozone plant sensitivity to assess global vegetation damage risks

Abstract: A major limitation in modeling global O3 vegetation damage has long been the reliance on empirical O3 sensitivity parameters derived from a limited number of species and applied at the level of plant functional types (PFTs), which ignore the large interspecific variations within the same PFT. Here, we present a major advance in large-scale assessments of O3 plant injury by linking the trait leaf mass per area (LMA) and plant O3 sensitivity in a broad and global perspective. Application of the new approach and a global LMA map in a dynamic global vegetation model reasonably represents the observed interspecific responses to O3 with a unified sensitivity parameter for all plant species. Simulations suggest a contemporary global mean reduction of 4.8% in gross primary productivity by O3, with a range of 1.1%-12.6% for varied PFTs. Hotspots with damages > 10% are found in agricultural areas in the eastern U.S., western Europe, eastern China, and India, accompanied by moderate to high levels of surface O3. Furthermore, we reveal an inherent plant sensitivity spectrum for O3 which is highly linked with plant leaf trait trade-off strategy, revealing high risks for fast-growing species with low LMA, such as crops, grasses and deciduous trees.

The Spatio-Temporal Dynamic Patterns of Shallow Groundwater Level and Salinity: The Yellow River Delta, China

Abstract: Shallow groundwater in coastal aquifers is a highly dynamic and complex system with a high risk of seawater intrusion. Analyzing the spatio-temporal dynamic patterns of groundwater can help to manage the groundwater resource and prevent it from degradation. Based on the groundwater level (GWL) and electrical conductivity (EC) monitoring data of 18 observation wells in the Yellow River Delta (YRD) from 2004 to 2010, this research analyses the groundwater dynamics using a robust seasonal trend decomposition technique (STL) and spatial interpolation method to detect the groundwater spatio-temporal dynamic patterns of groundwater level and salinity. Combined with hydro-climatic data, the Pearson correlation method and the Mann-Kendall (MK) trend analysis were used to further reveal the impacts that induce their trends and seasonal variations. Our analyses show that the risk of seawater intrusion into local shallow aquifers in this region is high, with the mean groundwater level over 42% of the region lower than the local sea level, and the mean groundwater EC over 96% of the region met the standards for seawater intrusion. In addition, the trends of groundwater level generally declined by 0.01~0.45 m/a and salinity increased by 1.153~25.608 μs/cm.a, which are consistent with the trend of precipitation decline. The seasonal dynamics of groundwater level and salinity are highly correlated with the seasonal components of rainfall and evaporation. It can be concluded that the extent of seawater intrusion will increase in the future with sea level rise. The approaches used in this study proved to be effective and can certainly serve as an example for the analysis of the spatio-temporal dynamics of groundwater in other coastal regions.

Season‐Dependent Modulation of Pacific Meridional Mode on Tropical Cyclone Genesis Over the Western North Pacific

Abstract: Pacific Meridional Mode (PMM) has been found to be significantly correlated with tropical cyclone (TC) genesis in the western North Pacific (WNP), while the seasonality in their relationship remains unknown. Here we found that their relationship experiences remarkable seasonality, with a significant positive correlation in January–April and August–December but an insignificant relationship in May–July. This seasonality stems from the diverse responses of large-scale conditions to the different magnitude of the PMM-related sea surface temperature (SST) warming that is dependent on the strength of trade wind in the three seasons. In January–July, strong trade wind facilitates great PMM SST warming that stimulates large-scale ascending motion in the eastern WNP but compensated descending motion in the western WNP, favoring TC genesis in January–April because its main genesis region is in the eastern WNP. However, the main genesis region extends to the whole WNP in May–July, the inconsistent large-scale condition anomalies across the western and eastern WNP thus lead to the insignificant relationship in May–July. In August–December, the PMM-related SST warming and the associated ascending motion fade away due to the much-weakened trade wind, and the favorable large-scale ascending motion over the whole WNP is linked to the PMM-related SST cooling induced descending motion through a modification of the Walker circulation. The results highlight the season-dependent mechanism of PMM influencing TC genesis and have some insights for improving seasonal forecasting.

Interdecadal Shift in Dipole Pattern Precipitation Trends Over the Tibetan Plateau: Roles of Local Vortices

Abstract: Trends of precipitation over the Tibetan Plateau (TP) are characterized by a north-south dipole pattern, and the role of local mesoscale systems, TP vortices (TPVs), remains ambiguous. This work reports that the north-south dipole pattern trends in the TPVs-associated precipitation have experienced an interdecadal shift in the last two decades, that is, increases in northern TP and decreases in southern TP first and then varies opposite trends, which greatly contributes to the similar interdecadal shift in TP precipitation trends. Furthermore, the causes of changes in TPV frequency are explored from the perspective of lower troposphere conditions. We find that the lower-level winds, that is, zonal winds over the TP and meridional winds across the northwestern TP boundary, are responsible for the regionally different variations in TPV frequency. The variations in Indian Ocean Dipole are suggested to contribute to the changes in lower-level winds over the TP.

Stratospheric ozone trends and attribution over 1984–2020 using ordinary and regularised multivariate regression models

Abstract: Abstract. Accurate quantification of long-term trends in stratospheric ozone can be challenging due to their sensitivity to natural variability, the quality of the observational datasets, non-linear changes in forcing processes as well as the statistical methodologies. Multivariate linear regression (MLR) is the most commonly used tool for ozone trend analysis, however, the complex coupling in most atmospheric processes can make it prone to the over-fitting or multi-collinearity-related issues when using the conventional Ordinary Least Squares (OLS) setting. To overcome this issue, we adopt a regularised (Ridge) regression method to estimate ozone trends and quantify the influence of individual processes. Here, we use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) merged data set (v2.7) to derive stratospheric ozone profile trends for the period 1984–2020. Beside SWOOSH, we also analyse a machine-learning-based satellite-corrected gap-free global stratospheric ozone profile dataset from a chemical transport model (ML-TOMCAT), and output from two chemical transport model (TOMCAT) simulations forced with ECMWF reanalyses ERA-Interim and ERA5. With Ridge regression, the stratospheric ozone profile trends from SWOOSH data show smaller declines during 1984–1997 compared to OLS with the largest differences in the lowermost stratosphere (> 4 % per decade at 100 hPa). Upper stratospheric ozone has increased since 1998 with maximum (~2 % per decade near 2 hPa) in local winter for mid-latitudes. Negative trends with large uncertainties are observed in the lower stratosphere with the most pronounced in the tropics. The largest differences in post-1998 trend estimates between OLS and Ridge regression methods appear in the tropical lower stratosphere (with ~7 % per decade difference at 100 hPa). Ozone variations associated with natural processes such as the quasi-biennial oscillation (QBO), the solar variability, the El Niño–Southern Oscillation (ENSO), the Arctic oscillation (AO) and the Antarctic oscillation (AAO) also indicate that Ridge regression coefficients are somewhat smaller and less variable compared to the OLS-based estimates. Additionally, ML-TOMCAT based trend estimates are consistent with SWOOSH data set. Finally, we argue that the large differences between the satellite-based data and model simulations confirm that there are still large uncertainties in ozone trend estimates especially in the lower stratosphere, and caution is needed when discussing results if explanatory variables used are correlated.

Tibetan Plateau surface albedo responds instantly to both snow coverage and depth

Abstract: The Tibetan Plateau snow cover is characterized by rapid changes on a weekly time-scale, which can cause rapid changes in surface albedo. Using snow and surface albedo data from satellite observations, we find that changes in snow coverage on the Tibetan Plateau dominate the rapid changes in surface albedo. However, snow depth also has a distinct effect on rapid changes in surface albedo in some areas especially with unstable snow cover. We test the snow depth-dependent snow albedo parameterization scheme in the land surface model. The results show that whether or not the variation of snow albedo with snow depth is considered directly affects the rapidly changing characteristics of the simulated snow cover on the Tibetan Plateau, which further affects the simulation of surface albedo. These results highlight the rapid response of surface albedo to both snow coverage and depth over the Tibetan Plateau.

On the atmospheric background for the occurrence of three heat wave types in East China

Abstract: Compared with daytime (occurring only in daytime) and nighttime (occurring only in nighttime) heat waves (HWs), daytime-nighttime compound HWs (occurring simultaneously in daytime and nighttime) are highlighted to exert much severer impacts especially on human health. However, the physical mechanisms underlying compound HWs are poorly understood. Based on the observed maximum and minimum temperatures and NCEP/ NCAR reanalysis data, this article addressed the physical processes for the occurrence of compound HWs in East China, where compound HWs occur most frequently across China. Comparisons with those related to daytime or nighttime HWs were also performed. The results indicate that the occurrences of three HW types are all associated with anticyclonic circulation anomalies from the upper troposphere to the lower troposphere, whereas their locations and intensities determine the configuration of atmospheric conditions for different categories of HWs. The resultant less (more) cloud cover and humidity as well as increased downward shortwave (longwave) radiation at the surface favor the warming of daytime (nighttime), conducive to the occurrence of daytime (nighttime) HWs. The combination of above conditions associated with daytime and nighttime HWs, which helps the persistence of high temperatures from daytime to nighttime, benefits the occurrence of compound HWs. In addition, nighttime and compound HWs occur with the northwestward extension of the western Pacific subtropical high (WPSH), while it stays in the climatological location for the occurrence of daytime HWs. Further investigation suggests that daytime (nighttime) HWs are accompanied with an upper-tropospheric meridional (zonal) wave train propagating downstream from western Siberia (the east to the Caspian Sea). In comparison, the wave train related to compound HWs shares the mixed features of daytime and nighttime HWs, characterized by a meridional wave propagation from the Scandinavian Peninsula to East China and then a zonal propagation toward the western Pacific.

The role of multi-scale interaction on subseasonal prediction of extreme events

Abstract: The northward/northwestward propagation of boral summer intraseasonal oscillation (BSISO) modulates the subtropical variability ad typhoon activity and has significant impacts on the extreme weather and climate events in Asia. BSISO strongly interacts with background mean fields and tends to be stronger and longer in its northward propagation during La Nina than El Nino summers. It is further found that BSISO-related convections are stronger and more organized with northward propagation on 30-60-day timescales during El Nino developing than decaying summers over the western Pacific. Thus, for skillful subseasonal prediction of extreme events in Asia, it is crucial for climate models to well represent BSISO and its interaction with the background mean state and synoptic variability. Our case study shows that the rare extreme flooding event in Henan Province, China, during July 2021 (referred to as the &#8220;21.7&#8221; flooding event) was a result of scale interactions between the background mean field associated with the weak La Nina condition, intraseasonal oscillations, and synoptic disturbances. The two distinct modes of the BSISO (10-30- and 30-90-day modes) unusually had a crucial combined role in moisture convergence, aided by the increased seasonal-mean moisture content, maintaining persistent rainfall during the 21.7 event. Synoptic-scale moisture convergence was also contributed to the extreme values in the peak day of the event. The five state-of-the art subseasonal-to-seasonal prediction models showed limited skills in predicting this extreme event one to two weeks in advance, partly because of their biases in representing the BSISO and multiscale interactions. Our results highlight that an accurate prediction of subseasonal perturbations and their interactions with the background moisture content is crucial for improving the extended-range forecast skill of extreme precipitation events.

Sub-seasonal Variations and Predictions of Precipitation over the Asian Monsoon Area with BCC_DERF2.0 in Spring-Summer Transition Season

Abstract: The sub-seasonal characteristics and prediction of rainfall over the Asian Monsoon Area during spring-summer transitional season (April-May-June) are investigated using a full set of hindcasts generated by the Dynamic Extended Range Forecast operational system version 2.0 (DERF2.0) of Beijing Climate Center, China Meteorological Administration. The onset and development of Asian summer monsoon and the seasonal migration of rain belt&#160; over East Asia can be well depicted by the model hindcasts at various leads. However, there exist considerable differences between model results and observations, and model biases depend not only on lead time, but also on the stage of monsoon evolution. In general, forecast skill drops with&#160; increasing lead time, but rises again after lead time becomes longer than 30 days, possibly associated with the effect of slowly-varying forcing or&#160; atmospheric variability. An abrupt turning point of bias development appears around mid-May, when bias growths of wind and precipitation exhibit significant changes over the northwestern Pacific and South Asia, especially over the Bay of Bengal and the South China Sea. This abrupt bias change is&#160; reasonably captured by the first two modes of multivariate empirical orthogonal function analysis, which reveals several important features associated&#160; with the bias change. This analysis may provide useful information for further improving model performance in sub-seasonal rainfall prediction.

Anthropogenic impact on the severity of compound extreme high temperature and drought/rainy events in China

Abstract: Extreme events seriously affect human health&#160;and natural environment. In the present study, several indexes that can describe the severity of compound extreme high temperature and drought/rainy events&#160;(CHTDE/CHTRE) are constructed based on copulas. According to&#160;observations,&#160;CHTDE&#160;and CHTRE&#160;have intensified in most areas of China during 1961&#8211;2014.&#160;The significant increase trend in the severity of CHTDE&#160;and CHTRE is&#160;basically consistent with simulations under historical anthropogenic forcing. This result proves that changes in&#160;CHTDE can be largely attributed to anthropogenic climate change. The historical greenhouse gas forcing is identified to be the dominant factor that affects the severity of CHTDE in China, particularly&#160;in the Tibetan Plateau&#160;and Northwest China. Moreover, the contribution of anthropogenic forcing&#160;to&#160;the linear change of&#160;the CHTRE&#160;severity in China is more than 90%.&#160;In addition, the&#160;ozone&#160;and&#160;land use&#160;signals also&#160;can be detected on change of CHTDE and CHTRE.

Anthropogenic amplification of biogenic secondary organic aerosol production

Abstract: Abstract. Biogenic secondary organic aerosols (SOA) contribute to a large fraction of fine aerosols globally, impacting air quality and climate. The formation of biogenic SOA depends on not only emissions of biogenic volatile organic compounds (BVOCs) but also anthropogenic pollutants including primary organic aerosol, sulfur dioxide (SO2), and nitrogen oxides (NOx). However, the anthropogenic impact on biogenic SOA production (AIBS) remains unclear. Here we use the decadal trend and variability of observed OA in the southeast US, combined with a global chemistry-climate model, to better constrain AIBS. We show that the reduction in SO2 emissions can only explain 40 % of the decreasing decadal trend of OA in this region, constrained by the low summertime month-to-month variability of surface OA. We hypothesize that the rest of OA decreasing trend is largely due to reduction in NOx emissions. By implementing a scheme for monoterpene SOA with enhanced sensitivity to NOx, our model can reproduce the decadal trend and variability of OA in this region. Extending to centennial scale, our model shows that global SOA production increases by 36 % despite BVOC reductions from preindustrial period to present day, largely amplified by AIBS. Our work suggests a strong coupling between anthropogenic and biogenic emissions in biogenic SOA production that is missing from current climate models.

Spatiotemporal characteristics of soil Moisture and land – atmosphere coupling over the Tibetan Plateau derived from three gridded datasets

Abstract: Soil moisture is a crucial component of the water cycle and plays an important role in regional weather and climate. However, owing to the lack of In Situ observations, an accurate understanding of the spatiotemporal variations of soil moisture (SM) on the Tibetan Plateau (TP) is still lacking. In this study, we used three gridded SM products to characterize the spatiotemporal features of SM on the TP during the warm season (May to August). We analyzed the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5), Global Land Data Assimilation System (GLDAS), and Soil Moisture Active Passive (SMAP) datasets and used station observation data and triple collocation to quantify product accuracy and consistency. Results of the evaluation based on observation data show that both ERA5 and GLDAS overestimate SM, while the accuracy of SMAP is high. In terms of capturing the temporal variations of SM measured at stations, the performance of ERA5 and that of SMAP are superior to that of GLDAS. According to the evaluation based on triple collocation, SMAP exhibits the smallest random error over the TP and the highest temporal correlation with the unknown true SM in eastern TP. For SMAP, SM variability is the largest in the southern TP. For ERA5 and GLDAS, variability in the western TP is substantially larger than that for SMAP. Low-frequency (30&#8211;90 days) variations are the largest contributor to TP SM intraseasonal variability. Relative to SMAP, the contribution of high-frequency variations is low in ERA5 and GLDAS. Land-atmosphere coupling is stronger (weaker) in the western (southeastern) TP, which is relatively dry (wet). Our evaluation of SM product performance over the TP may facilitate the use of these products for disaster monitoring and climate and hydrological studies.

Reply on CEC1

Abstract: Abstract. The layout of urban buildings shows significant heterogeneity, which leads to the significant spatial inhomogeneity of the wind field in and over the canopy of urban street canyons. However, most of the current urban canopy models do not fully consider the heterogeneity of the urban canopy. Large discrepancies thus exist between the wind speeds simulated by the current urban canopy models and those observed in the street canyon. In this study, a parameterization scheme for wind field, Inhomogeneous Wind Scheme for Urban Street (IWSUS), is developed to better characterize the heterogeneity of the urban canopy. We use a Computational Fuild Dynamics method to generate the IWSUS scheme and compare with observations of wind profile and turbulent flux in and over the street canyon for validation. In IWSUS, the wind speed vertical profiles at six representative positions located in a typical street canyon (i.e., the windward or leeward side of a long straight street, or the inflow or outflow end) are parameterized separately. The wind profile by IWSUS thus can better describe the horizontal heterogeneity of the urban near-surface wind field, e.g., the dynamic drag effect of building in the lower atmosphere layer over the urbanized land use. The validation based on observations shows that the performance of simulation results by IWSUS is better than that by logarithmic-exponential (exp-log) law widely used in the current urban schemes. As we consider typical building arrangement and specific street orientations in IWSUS for wind field simulations, which can better match the distribution characteristics of street canyons around the observation point in the street canyon. The averaged wind profiles and turbulence energy fluxes in the model grids of urban area by IWSUS are also more approach to the observation than those by exp-log law. The normalized mean errors (NME) between the simulated and the observed vertical average wind speed are 49.0 % for IWSUS and 56.1 % for exp-log law in the range from the ground to four times the average height of the building, and 70 % for IWSUS and 285.8 % for exp-log law in the street canyon (range from the ground to building top). This study proves that the accuracy of land surface process and near-grounded meteorological process simulations over urban canopy can be improved by fully considering the heterogeneity of the urban canopy layout structures and the inhomogeneous of wind field distributions in and over the street canyon. The IWSUS is expected to be coupled with mesoscale atmospheric models to improve the accuracy of the wind field, land surface energy budget, meteorological, and atmospheric chemistry simulations.

Reply on RC1

Abstract: Abstract. The paper investigates how to refine the ground meteorological observation network for greatly improving the PM_2.5 concentration forecasts by identifying the sensitive areas for targeted observations associated with a total of 48 forecasts in eight heavy haze events during the years of 2016–2018 over the Beijing-Tianjin-Hebei (BTH) region. The conditional non-linear optimal perturbation (CNOP) method is adopted to determine the sensitive area of the surface meteorological fields for each forecast and a total of 48 CNOP-type errors are obtained including wind, temperature, and water vapor mixing ratio components. It is found that, although all the sensitive areas tend to locate within and/or surrounding the BTH region, their specific distributions are dependent on the events and the start times of the forecasts. Based on these sensitive areas, the current ground meteorological stations within and surrounding the BTH region are refined to form a cost-effective observation network, which makes the relevant PM_2.5 forecasts starting from different initial times for varying events assimilate fewer observations but overall achieve the forecasting skill comparable to, even higher than that obtained by assimilating all ground station observations. This network sheds light on that some of the current ground stations within and surrounding the BTH region are very useless for improving the PM_2.5 forecasts in the BTH region and can be greatly scattered to avoid the thankless work.

Future projections of meteorological, agricultural and hydrological droughts in China using the emergent constraint

Abstract: In the context of global warming, droughts&#160;occur more frequently&#160;and have caused great losses&#160;to human society.&#160;Therefore, understanding the potential changes in future droughts under climate change is of great scientific importance. In this paper, combining with climate models from CMIP6, the emergent constraint and the Model Goodness Index (MGI)&#160;are used to analyze the characteristics of meteorological, agricultural and hydrological droughts&#160;in China under four socioeconomic scenarios in the mid- and late 21st century. The results show that in the mid-21st century, there will be more frequent meteorological, agricultural and hydrological droughts&#160;in northern China. In the late 21st century, longer and more intense droughts&#160;are more likely to occur in China than in the mid-21st century.&#160;This indicates that drought events in China will gradually become more continuous and serious from the middle to the late 21st century.&#160;Additionally, northwestern&#160;and central China will be the main areas where the three types of drought&#160;areas&#160;and extreme droughts&#160;will increase in the future.&#160;In the mid-21st century, a higher socioeconomic scenario will suppress drought, which will enhance drought conversely in the late 21st century.&#160;These findings are of great significance for drought monitoring under climate change and&#160;can provide a basis for making a drought response&#160;plan.

A Cluster-Based Facial Image Anonymization Method Using Variational Autoencoder

Abstract: Existing methods for face de-identification often cause inevitable damage to the utility of facial information. The anonymized facial images can hardly be applied in practical applications. In this work, we propose a cluster-based generative model that conceals the identity of images while preserving the utility of facial images. We extract facial features in the first stage, then classify images into several clusters. Four naive protection methods, blindfold, mosaic, cartoon and mosaic, are adopted to form facial image inputs without private information. Along with the four de-identified images, a random facial image in the same cluster is also chosen as another input for better preservation of facial features. We train a novel model with multiple inputs, called Multi-stage Utility Maintenance-Variational AutoEncoder (MsUM-VAE), generating a facial image using the mentioned multi-inputs. The output of the model retains a large portion of the facial characteristics, but cannot be distinguished from the original image dataset, avoiding the disclosure of privacy. We perform numerous evaluations on the CelebA dataset to showcase the effectiveness of our model, and the findings indicate that the model surpasses conventional techniques for obscuring identity and maintaining the utility of images.

Reply on EC1

Abstract: Abstract. Abstract. Aerosol–fog interactions (AFIs) play pivotal roles in the fog cycle. However, few studies have focused on the differences in AFIs between two successive radiation fog events and the underlying mechanisms. To fill this knowledge gap, our study simulates two successive radiation fog events in the Yangtze River Delta, China, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Our simulations indicate that AFIs in the first fog (Fog1) promote AFIs in the second one (Fog2), resulting in higher number concentration, smaller droplet size, larger fog optical depth, wider fog distribution, and longer fog lifetime in Fog2 than in Fog1. This phenomenon is defined as the self-enhanced AFIs, which are related to the following physical factors. The first one is conducive meteorological conditions between the two fog events, including low temperature, high humidity and high stability. The second one is the feedbacks between microphysics and radiative cooling. A higher fog droplet number concentration increases the liquid water path and fog optical depth, thereby enhancing the long-wave radiative cooling and condensation near the fog top. The third one is the feedbacks between macrophysics, radiation, and turbulence. A higher fog top presents stronger long-wave radiative cooling near the fog top than near the fog base, which weakens temperature inversion and strengthens turbulence, ultimately increasing the fog-top height and fog area. In summary, AFIs postpone the dissipation of Fog1 due to these two feedbacks and generate more conducive meteorological conditions before Fog2 than before Fog1. These more conducive conditions promote the earlier formation of Fog2, further enhancing the two feedbacks and strengthening the AFIs. Our findings are critical for studying AFIs and shed new light on aerosol–cloud interactions.

Reply on RC1

Abstract: Abstract. Abstract. Aerosol–fog interactions (AFIs) play pivotal roles in the fog cycle. However, few studies have focused on the differences in AFIs between two successive radiation fog events and the underlying mechanisms. To fill this knowledge gap, our study simulates two successive radiation fog events in the Yangtze River Delta, China, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Our simulations indicate that AFIs in the first fog (Fog1) promote AFIs in the second one (Fog2), resulting in higher number concentration, smaller droplet size, larger fog optical depth, wider fog distribution, and longer fog lifetime in Fog2 than in Fog1. This phenomenon is defined as the self-enhanced AFIs, which are related to the following physical factors. The first one is conducive meteorological conditions between the two fog events, including low temperature, high humidity and high stability. The second one is the feedbacks between microphysics and radiative cooling. A higher fog droplet number concentration increases the liquid water path and fog optical depth, thereby enhancing the long-wave radiative cooling and condensation near the fog top. The third one is the feedbacks between macrophysics, radiation, and turbulence. A higher fog top presents stronger long-wave radiative cooling near the fog top than near the fog base, which weakens temperature inversion and strengthens turbulence, ultimately increasing the fog-top height and fog area. In summary, AFIs postpone the dissipation of Fog1 due to these two feedbacks and generate more conducive meteorological conditions before Fog2 than before Fog1. These more conducive conditions promote the earlier formation of Fog2, further enhancing the two feedbacks and strengthening the AFIs. Our findings are critical for studying AFIs and shed new light on aerosol–cloud interactions.