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Locust swarms had periodically raged in both North American Plains (NAP) and East Asian Plains (EAP) before 1880 AD. After this period, the locust outbreaks almost never recurred in NAP but have continued to occur in EAP. Since large quantities of pesticides were used in the major agriculture regions of NAP in the late 1870s; this has been suggested as a possible major cause of the disappearing of locust outbreaks. Extensive applications of more effective chemical pesticides were also used in the granary regions of EAP in the 1950s in an effort to kill the pests at a much higher intensity. However, locust swarms came back again in many areas of China in the 1960s. Therefore, NAP locust extinction still remains a puzzle. Frequent locust outbreaks in EAP over the past 130 yr may offer clues to probe key control elements in the disappearing of locust outbreaks in NAP. This paper analyzes the climate extremes and monthly temperature-precipitation combines of NAP and EAP, and found the differences in their frequencies of these climate combines caused different locust fates in the two regions: restrained the locust outbreak in NAP but induced such events in EAP. Validation shows that severer EAP locust outbreak years were coincided with the climate extreme combines years. Thus we suggest that climate changes in frequency, extremes and trends can explain why the fate of the locust plague in EAP was different from that in NAP. The study also points out that, under the present global warming, cautions should be taken to make sure the pest hazard being nipped in the-bud. [ABSTRACT FROM AUTHOR]

The article presents a study that determines the ensemble-based data assimilation system through the observing system simulation experiments (OSSEs). It details the method of the study that uses the Method for Object-based Diagnostic Evaluation (MODE) to analyze the aerosol optical thickness (AOT) distributions in East Asia. It notes the result of the study, which suggests that the use of real CALIPSO data provides benefits in obtaining more accurate sulfate and dust aerosol analyses.

Organic aerosol (OA) simulations using the volatility basis-set approach were made for East Asia and its outflow region. Model simulations were evaluated through comparisons with OA measured by aerosol mass spectrometers in and around Tokyo (at Komaba and Kisai in summer 2003 and 2004) and over the outflow region in East Asia (at Fukue and Hedo in spring 2009). The simulations with aging processes of organic vapors reasonably well reproduced mass concentrations, temporal variations, and formation efficiency of observed OA at all sites. As OA mass was severely underestimated in the simulations without the aging processes, the oxidations of organic vapors are essential for reasonable OA simulations over East Asia. By considering the aging processes, simulated OA concentrations increased from 0.24 to 1.28 µgm-3 in the boundary layer over the whole of East Asia. OA formed from the interaction of anthropogenic and biogenic sources was also enhanced by the aging processes. The fraction of controllable OA was estimated to be 87% of total OA over the whole of East Asia, showing that most of the OA in our simulations formed anthropogenically (controllable). Even a large portion of biogenic secondary OA (78% of biogenic secondary OA) was formed through the influence of anthropogenic sources. The high fraction of controllable OA in our simulations is likely because anthropogenic emissions are dominant over East Asia and OA formation is enhanced by anthropogenic sources and their aging processes. Both the amounts (from 0.18 to 1.12 µgm-3) and the fraction (from 75% to 87 %) of controllable OA were increased by aging processes of organic vapors over East Asia. [ABSTRACT FROM AUTHOR]

Optimization of land surface models has been very challenging due to the increasing complexity of such models. Typical parameter calibration techniques often limit the solution of the spatiotemporal discrepancy in the modeling performance levels especially for regional applications. Thus, in this study, an attempt was made to perform schemebased model optimization by designing a framework for coupling a micro-genetic algorithm (micro-GA) with the Noah land surface model that has multiple physics options (Noah-MP). Micro-GA controls the scheme selections in 10 different land surface parameterization fields in Noah-MP in order to extract the optimal scheme combination for a certain region. This coupling framework was successfully applied to the optimization of the surface water partitioning in the Korean Peninsula, promising not only the effectiveness of the scheme-based optimization but also model diagnosis capability by exploring the scheme sensitivity during the micro-GA evolution process. Then, the method was applied to four different regions in East Asia that have different climatic characteristics. The results indicate that (1) the optimal scheme combinations vary with the regions, (2) schemes related to the surface water partitioning are important for the modeling accuracy, and (3) specialized post-parameter optimization for each region may be required. [ABSTRACT FROM AUTHOR]

This REgional Carbon Cycle Assessment and Processes regional study provides a synthesis of the carbon balance of terrestrial ecosystems in East Asia, a region comprised of China, Japan, North- and South-Korea, and Mongolia. We estimate the current terrestrial carbon balance of East Asia and its driving mechanisms during 1990-2009 using three di?erent approaches: inventories combined with satellite greenness measurements, terrestrial ecosystem carbon cycle models and atmospheric inversion models. The magnitudes of East Asia's natural carbon sink from these three approaches are comparable: -0.264±0.033 PgC yr-1 from inventory-remote sensing model-data fusion approach, -0.393±0.141 PgC yr-1 (not considering biofuel emissions) or -0.204±0.141 PgC yr-1 (considering biofuel emissions) for carbon cycle models, and -0.270±0.507 PgC yr-1 for atmospheric inverse models. The ensemble of ecosystem modeling based analyses further suggests that at the regional scale, climate change and rising atmospheric CO2 together resulted in a carbon sink of -0.289±0.135 PgC yr-1 , while land use change and nitrogen deposition had a contribution of -0.013±0.029 PgCyr and -0.107±0.025 PgC yr-1 , respectively. Although the magnitude of climate change effects on the carbon balance varies among different models, all models agree that in response to climate change alone, southern China experienced an increase in carbon storage from 1990 to 2009, while northern East Asia including Mongolia and north China showed a decrease in carbon storage. Overall, our results suggest that about 13-26% of East Asia's CO2 emissions from fossil fuel burning have been offset by carbon accumulation in its terrestrial ecosystems over the period from 1990 to 2009. The underlying mechanisms of carbon sink over East Asia still remain largely uncertain, given the diversity and intensity of land management processes, and the regional conjunction of many drivers such as nutrient deposition, climate, atmospheric pollution and CO2 changes, which cannot be considered as independent for their effects on carbon storage. [ABSTRACT FROM AUTHOR]

The article investigates the application of multi-angular total and polarized remote sensing for aerosol optical depth and fine-mode fraction retrieval in East Asia. It states that the algorithm retrieves aerosol optical depth (AOD), fine-mode fraction (FMF) for studying the climatic impact of aerosol. It indicates that the best features of aerosol model over East Asia are constrained using the cluster analysis technique based on the AERONET sun-photometer observation over East Asia.

The article presents a study which examines the effectiveness of satellite-based remote sensing technology to detect atmospheric aerosols, polluted air and dust storm in East Asian region. Look-up Table (LUT) method and moderate resolution imaging spectroradiometer (MODIS) are applied to determine and estimate aerosol optical thickness (AOT) which developed more than three decades. Based on cluster analysis, MODIS and Aerosol Robotic Network (AERONET) have showed accurate results.

Cold surge (CS) is considered a favorable weather process to improve air quality and is widely recognized. However, there is no detailed study on the differences in the dispersion ability of different types of CSs in relation to haze days in eastern China (HD EC). This paper uses the hierarchical clustering algorithm to classify the cool-season (November to February of the following year) CSs across eastern China into blocking CSs and wave-train CSs and compares their influences on the number of HD EC from 1980 to 2017. Results show that the wave-train CSs can significantly improve the visibility in eastern China and generally improve air quality for about 2 d longer than the blocking CSs, which indicates that the blocking CSs have a weaker ability to dissipate HD EC compared with the wave-train CSs. The CSs affect the HD EC by changing meteorological elements like thermal inversion potential, horizontal surface wind, sea level pressure (SLP), and surface air temperature (SAT). A period of 4 d after the outbreak of CSs, the variations of thermal inversion potential and horizontal surface wind of two types of CSs tend to be consistent. However, the negative SAT anomalies and the positive SLP anomalies caused by the blocking CSs lasted shorter than those caused by the wave-train CSs, forming favorable conditions for the rapid growth of HD EC. Furthermore, results show that in recent years, especially after the 1990s, the frequency of wave-train CSs has decreased significantly, while the frequency of blocking CSs has slightly increased, indicating that the overall ability of CSs to dissipate HD EC has weakened in general. This work may provide reference for the future formulation of haze control policies in East Asia. [ABSTRACT FROM AUTHOR]

When calibrating simulations of dust clouds, both the intensity and the position are important. Intensity errors arise mainly from uncertain emission and sedimentation strengths, while position errors are attributed either to imperfect emission timing or to uncertainties in the transport. Though many studies have been conducted on the calibration or correction of dust simulations, most of these focus on intensity solely and leave the position errors mainly unchanged. In this paper, a grid-distorted data assimilation, which consists of an image-morphing method and an ensemble-based variational assimilation, is designed for realigning a simulated dust plume to correct the position error. This newly developed grid-distorted data assimilation has been applied to a dust storm event in May 2017 over East Asia. Results have been compared for three configurations: a traditional assimilation configuration that focuses solely on intensity correction, a grid-distorted data assimilation that focuses on position correction only and the hybrid assimilation that combines these two. For the evaluated case, the position misfit in the simulations is shown to be dominant in the results. The traditional emission inversion only slightly improves the dust simulation, while the grid-distorted data assimilation effectively improves the dust simulation and forecasting. The hybrid assimilation that corrects both position and intensity of the dust load provides the best initial condition for forecasting of dust concentrations. [ABSTRACT FROM AUTHOR]

Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called "Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction" (LS4P) as the first international grass-roots effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regional climate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond East Asia and its S2S prediction. Preliminary studies and analysis have also shown that LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems. [ABSTRACT FROM AUTHOR]

Urban aerosol measurements are necessary to establish associations between air pollution and human health outcomes and to evaluate the efficacy of air quality legislation and emissions standards. The measurement of urban aerosol particle size distributions (PSDs) is of particular importance as they enable characterization of size-dependent processes that govern a particle's transport, transformation, and fate in the urban atmosphere. PSDs also improve our ability to link air pollution to health effects through evaluation of particle deposition in the respiratory system and inhalation toxicity. To inform future measurements of urban aerosol observations, this paper reviews and critically analyzes the current state of knowledge on urban aerosol PSD measurements by synthesizing 737 PSD observations made between 1998 to 2017 in 114 cities in 43 countries around the globe. Significant variations in the shape and magnitude of urban aerosol number and mass PSDs were identified among different geographical regions. In general, number PSDs in Europe (EU) and North America, Australia, and New Zealand (NAAN) are dominated by nucleation- and Aitken-mode particles. PSDs in Central, South, and Southeast Asia (CSSA) and East Asia (EA) are shifted to larger sizes, with a meaningful contribution from the accumulation mode. Urban mass PSDs are typically bimodal, presenting a dominant mode in the accumulation mode and a secondary mode in the coarse mode. Most PSD observations published in the literature are short-term, with only 14 % providing data for longer than 6 months. There is a paucity of PSDs measured in Africa (AF), CSSA, Latin America (LA), and West Asia (WA), demonstrating the need for long-term aerosol measurements across wide size ranges in many cities around the globe. Geographical variations in urban aerosol effective densities were also reviewed. Size-resolved urban aerosol effective density functions from 3 to 10 000 nm were established for different geographical regions and intra-city sampling locations in order to accurately translate number PSDs to mass PSDs, with significant variations observed between near-road and urban background sites. The results of this study demonstrate that global initiatives are urgently needed to develop infrastructure for routine and long-term monitoring of urban aerosol PSDs spanning the nucleation to coarse mode. Doing so will advance our understanding of spatiotemporal trends in urban PSDs throughout the world and provide a foundation to more reliably elucidate the impact of urban aerosols on atmospheric processes, human health, and climate. [ABSTRACT FROM AUTHOR]

Emission inversion using data assimilation fundamentally relies on having the correct assumptions about the emission background error covariance. A perfect covariance accounts for the uncertainty based on prior knowledge and is able to explain differences between model simulations and observations. In practice, emission uncertainties are constructed empirically; hence, a partially unrepresentative covariance is unavoidable. Concerning its complex parameterization, dust emissions are a typical example where the uncertainty could be induced from many underlying inputs, e.g., information on soil composition and moisture, land cover and erosive wind velocity, and these can hardly be taken into account together. This paper describes how an adjoint model can be used to detect errors in the emission uncertainty assumptions. This adjoint-based sensitivity method could serve as a supplement of a data assimilation inverse modeling system to trace back the error sources in case large observation-minus-simulation residues remain after assimilation based on empirical background covariance. The method follows an application of a data assimilation emission inversion for an extreme severe dust storm over East Asia. The assimilation system successfully resolved observation-minus-simulation errors using satellite AOD observations in most of the dust-affected regions. However, a large underestimation of dust in Northeast China remained despite the fact that the assimilated measurements indicated severe dust plumes there. An adjoint implementation of our dust simulation model is then used to detect the most likely source region for these unresolved dust loads. The backward modeling points to the Horqin desert as the source region, which was indicated as a non-source region by the existing emission scheme. The reference emission and uncertainty are then reconstructed over the Horqin desert by assuming higher surface erodibility. After the emission reconstruction, the emission inversion is performed again, and the posterior dust simulations and reality are now in much closer harmony. Based on our results, it is advised that emission sources in dust transport models include the Horqin desert as a more active source region. [ABSTRACT FROM AUTHOR]

Severe haze occurred in the North China Plain (NCP) from November to December 2015, with a wide spatial range and long duration. In this paper, the combined effect of the anomalous stationary Rossby waves within two westerly jet waveguides on this haze event in the NCP is investigated based on observational visibility data and NCEP/NCAR reanalysis data. The results show that circulation anomalies in Eurasia caused by the propagation of anomalous stationary Rossby wave energy along two waveguides within the westerly jet originating from the Mediterranean were responsible for haze formation in the NCP. The Rossby waves propagated eastward along the subtropical westerly jet and the polar front jet, causing an anomalous anticyclone over the Sea of Japan and anticyclonic wind shear at 850 hPa over the NCP, which enhanced the anomalous descent in the middle and lower troposphere and subsequently resulted in a stable lower atmosphere. Furthermore, the anomalous stationary Rossby waves propagating along the polar front jet weakened the East Asia trough and Ural ridge and strengthened the anomalous southerly wind at 850 hPa over the coastal areas of eastern China, decelerating the East Asia winter monsoon. The above meteorological conditions modulated haze accumulation in November and December 2015. Meanwhile, continuous rainfall related to ascending motion due to Rossby wave propagation along the waveguide provided by the subtropical westerly jet occurred in a large area of southern China. The associated latent heat release acted as a heat source, intensifying the ascending motion over southern China so that the descending motion over the NCP was strengthened, favoring the maintenance of severe haze. This study elucidates the formation and maintenance mechanism of large-scale haze in the NCP in late fall and boreal winter. [ABSTRACT FROM AUTHOR]

Cold extremes have large impacts on human society. Understanding the physical processes dominating the changes in cold extremes is crucial for a reliable projection of future climate change. The observed cold extremes have decreased during the last several decades, and this trend will continue under future global warming. Here, we quantitatively identify the contributions of dynamic (changes in large-scale atmospheric circulation) and thermodynamic (rising temperatures resulting from global warming) effects to East Asian cold extremes in the past several decades and in a future warm climate by using two sets of large-ensemble simulations of climate models. We show that the dynamic component accounts for over 80 % of the cold-month (coldest 5 % boreal winter months) surface air temperature (SAT) anomaly over the past 5 decades. However, in a future warm climate, the thermodynamic change is the main contributor to the decreases in the intensity and occurrence probability of East Asian cold extremes, while the dynamic change is also contributive. The intensity of East Asian cold extremes will decrease by around 5 °C at the end of the 21st century, in which the thermodynamic (dynamic) change contributes approximately 75 % (25 %). The present-day (1986–2005) East Asian cold extremes will almost never occur after around 2035, and this will happen 10 years later due solely to thermodynamic change. The upward trend of a positive Arctic Oscillation-like sea level pressure pattern dominates the changes in the dynamic component. The finding provides a useful reference for policymakers in climate change adaptation activities. [ABSTRACT FROM AUTHOR]

Reliable attribution of Asian summer monsoon variations to aerosol forcing is critical to reducing uncertainties in future projections of regional water availability, which is of utmost importance for risk management and adaptation planning in this densely populated region. Yet, simulating the monsoon remains a challenge for climate models that suffer from long-standing biases, undermining their reliability in attributing anthropogenically forced changes. We analyze a suite of climate model experiments to identify a link between model biases and monsoon responses to Asian aerosols and associated physical mechanisms, including the role of large-scale circulation changes. The aerosol impact on monsoon precipitation and circulation is strongly influenced by a model's ability to simulate the spatio-temporal variability in the climatological monsoon winds, clouds, and precipitation across Asia, which modulates the magnitude and efficacy of aerosol–cloud–precipitation interactions, an important component of the total aerosol response. There is a strong interplay between South Asia and East Asia monsoon precipitation biases and their relative predominance in driving the overall monsoon response. We found a striking contrast between the early- and late-summer aerosol-driven changes ascribable to opposite signs and seasonal evolution of the biases in the two regions. A realistic simulation of the evolution of the large-scale atmospheric circulation is crucial to realize the full extent of the aerosol impact over Asia. These findings provide important implications for better understanding and constraining the diversity and inconsistencies of model responses to aerosol changes over Asia in historical simulations and future projections. [ABSTRACT FROM AUTHOR]

Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO 2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO 2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx , but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO 2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO 2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO 2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO 2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO 2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO 2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO 2 reflects a dynamic balance between emission and chemical loss. [ABSTRACT FROM AUTHOR]

Anthropogenic emissions of aerosols and precursor gases have changed significantly in the past few decades around the world. In this study, the Explicit Aerosol Source Tagging (EAST) system is merged into the Energy Exascale Earth System Model version 1 (E3SMv1) to quantify the variations in anthropogenic aerosol concentrations, source contributions, and their subsequent radiative impact in four major emission regions across the globe during 1850–1980, 1980–2010, and 2010–2017. In North America and Europe, changes in anthropogenic PM2.5 were mainly caused by changes in emissions from local energy and industrial sectors. The local industrial sector caused the largest increase in PM2.5 in East Asia during 1980–2010 and decrease during 2010–2017. In South Asia, the increase in energy-related emissions dominated the rise in PM2.5 levels during 1980–2017. During 1850–1980, the increases in emissions from North America contributed to the increase in the European PM2.5 burden by 1.7 mgm-2 and the sources from the Europe were also responsible for the PM2.5 burden increase in East Asia and South Asia by about 1.0 mgm-2. During 1980–2010, East Asia contributed to an increase of 0.4–0.6 mgm-2 in the PM2.5 burden in North America and Europe, while South Asia contributed about 0.3 mgm-2. During 2010–2017, the contributions from East Asia to the PM2.5 burdens in the North America, Europe, and South Asia declined by 0.3–0.6 mgm-2 due to the clean air actions in China, while the contributions from South Asia still increased due to the continuous increase in emissions in South Asia. The historical changes in aerosols had an impact on effective radiative forcing through aerosol–radiation interactions (ERFari). During 1980–2010, a decline in North American aerosols resulted in a positive ERFari change (warming effect) in Europe and a decline in aerosols in Europe caused a warming effect in Russia and northern China. The changes in ERFari from the increase and decrease in aerosols in China during 1980–2010 and 2010–2017, respectively, are comparable in magnitude. The continuous aerosol increases in South Asia from 1980 to 2017 resulted in negative ERFari (cooling) changes in South Asia, Southeast Asia, and southern China. [ABSTRACT FROM AUTHOR]

Four East Asian winter monsoon (EAWM) indices are compared in this paper. In the research periods, all the indices show similar interannual and decadal-interdecadal variations, with predominant periods centering in 3--4 years, 6.5 years and 9--15 years, respectively. Besides, all the indices show remarkable weakening trends since the 1980s. The correlation coefficient of each two indices is positive with a significance level of 99%. Both the correlation analyses and the composites indicate that in stronger EAWM years, the Siberian high and the higher-level subtropical westerly jet are stronger, and the Aleutian low and the East Asia trough are deeper. This circulation pattern is favorable for much stronger northwesterly wind and lower air temperature in the subtropical regions of East Asia, while it is on the opposite in weaker EAWM years. Besides, EAWM can also exert a remarkable leading effect on the summer monsoon. After stronger (weaker) EAWM, less (more) summer precipitation is seen over the regions from the Yangtze River valley of China to southern Japan, while more (less) from South China Sea to the tropical western Pacific. [ABSTRACT FROM AUTHOR]

The current best-estimate of the global annual mean radiative forcing (RF) attributable to contrail cirrus is thought to be 3 times larger than the RF from aviation's cumulative CO 2 emissions. Here, we simulate the global contrail RF for 2019–2021 using reanalysis weather data and improved engine emission estimates along actual flight trajectories derived from Automatic Dependent Surveillance–Broadcast telemetry. Our 2019 global annual mean contrail net RF (62.1 mW m -2) is 44 % lower than current best estimates for 2018 (111 [33, 189] mW m -2 , 95 % confidence interval). Regionally, the contrail net RF is largest over Europe (876 mW m -2) and the USA (414 mW m -2), while the RF values over East Asia (64 mW m -2) and China (62 mW m -2) are close to the global average, because fewer flights in these regions form persistent contrails resulting from lower cruise altitudes and limited ice supersaturated regions in the subtropics due to the Hadley Circulation. Globally, COVID-19 reduced the flight distance flown and contrail net RF in 2020 (- 43 % and - 56 %, respectively, relative to 2019) and 2021 (- 31 % and - 49 %, respectively) with significant regional variations. Around 14 % of all flights in 2019 formed a contrail with a net warming effect, yet only 2 % of all flights caused 80 % of the annual contrail energy forcing. The spatiotemporal patterns of the most strongly warming and cooling contrail segments can be attributed to flight scheduling, engine particle number emissions, tropopause height, and background radiation fields. Our contrail RF estimates are most sensitive to corrections applied to the global humidity fields, followed by assumptions on the engine particle number emissions, and are least sensitive to radiative heating effects on the contrail plume and contrail–contrail overlapping. Using this sensitivity analysis, we estimate that the 2019 global contrail net RF could range between 34.8 and 74.8 mW m -2. [ABSTRACT FROM AUTHOR]

The interactions between the terrestrial biosphere, atmospheric chemistry, and climate involve complex feedbacks that have traditionally been modeled separately. We present a new framework that couples the Yale Interactive terrestrial Biosphere (YIBs) model, a dynamic plant-chemistry model, with the RegCM-Chem model. RegCM-Chem–YIBs integrates meteorological variables and atmospheric chemical composition from RegCM-Chem with land surface parameters from YIBs. The terrestrial carbon flux calculated by YIBs is fed back into RegCM-Chem interactively, thereby representing the interactions between fine particulate matter (PM 2.5), ozone (O 3), and carbon dioxide (CO 2). For testing purposes, we carry out a 1-year simulation (2016) at a 30 km horizontal resolution over East Asia with RegCM-Chem–YIBs. The model accurately captures the spatio-temporal distribution of climate, chemical composition, and ecological parameters. In particular, the estimated O 3 and PM 2.5 are consistent with ground observations, with correlation coefficients (R) of 0.74 and 0.65, respectively. The simulated CO 2 concentration is consistent with observations from six sites (R ranged from 0.89 to 0.97) and exhibits a similar spatial pattern when compared with carbon assimilation products. RegCM-Chem–YIBs produces reasonably good gross primary productivity (GPP) and net primary productivity (NPP), showing seasonal and spatial distributions consistent with satellite observations, and mean biases (MBs) of 0.13 and 0.05 kg C m -2 yr -1. This study illustrates that RegCM-Chem–YIBs is a valuable tool to investigate coupled interactions between the terrestrial carbon cycle, atmospheric chemistry, and climate change at a higher resolution on a regional scale. [ABSTRACT FROM AUTHOR]

The use of remote sensing methods to accurately measure cloud properties and their spatiotemporal changes has been widely welcomed in many fields of atmospheric research. The Nanjing Joint Institute for Atmospheric Sciences (NJIAS) Himawari-8/9 Cloud Feature Dataset (HCFD) provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the 7-year period from April 2016 to December 2022. Multiple cloud variables, such as cloud mask, phase/type, top height, optical thickness, and particle effective radius, as well as snow, dust, and haze masks, were generated from the visible and infrared measurements of the Advanced Himawari Imager (AHI) on board the Japanese geostationary satellites Himawari-8 and Himawari-9 using a series of recently developed cloud retrieval algorithms. Verifications with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) 1 km cloud layer product and the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 cloud product (MYD06) demonstrate that the NJIAS HCFD gives higher skill scores than the Japanese Himawari-8/9 operational cloud product for all cloud variables except for cloud particle effective radius. The NJIAS HCFD even outperforms the MYD06 in nighttime cloud detection; cloud-top height, pressure, and temperature estimation; and infrared-only cloud-top phase determination. All evaluations are performed at the nominal 2 km scale, not including the effects of sub-pixel cloudiness or very thin cirrus. Two examples are presented to demonstrate applications of the NJIAS HCFD for climate and typhoon research. The NJIAS HCFD has been published in the Science Data Bank (https://doi.org/10.57760/sciencedb.09950 , Zhuge 2023a; https://doi.org/10.57760/sciencedb.09953 , Zhuge 2023b; https://doi.org/10.57760/sciencedb.09954 , Zhuge 2023c; https://doi.org/10.57760/sciencedb.10158 , Zhuge 2023d; https://doi.org/10.57760/sciencedb.09945 , Zhuge 2023e). [ABSTRACT FROM AUTHOR]

Biogenic volatile organic compounds (BVOCs) are important precursors to ozone and secondary organic aerosols in the atmosphere, affecting air quality, clouds, and climate. However, the trend in BVOC emissions and driving factors for the emission changes in different geographic regions over the past 2 decades has remained unclear. Here, regional to global changes in BVOC emissions during 2001–2020 are simulated using the latest Model of Emission of Gases and Aerosols from Nature (MEGANv3.2) with the input of time-varying satellite-retrieved vegetation and reanalysis meteorology data. Comparison of model simulations with the site observations shows that the model can reasonably reproduce the magnitude of isoprene and monoterpene emission fluxes. The spatial distribution of the modeled isoprene emissions is generally comparable to the satellite retrievals. The estimated annual average global BVOC emissions are 835.4 Tg yr -1 with the emissions from isoprene, monoterpenes, sesquiterpenes, and other BVOC comprised of 347.7, 184.8, 23.3, and 279.6 Tg yr -1 , respectively. We find that the decrease in global isoprene emissions (-0.07 % per year) caused by the increase in CO 2 concentrations (-0.20 % per year) is stronger than that caused by changes in vegetation (-0.03 % per year) and meteorological factors (0.15 % per year). However, regional disparities are large. Isoprene emissions increase significantly in Europe, East Asia, and South Asia (0.37 % per year–0.66 % per year). Half of the increasing trend is contributed by increased leaf area index (LAI) (maximum over 0.02 m 2 m -2 yr -1) and tree cover. Changes in meteorological factors contribute to another half, with elevated temperature dominating in Europe and increased soil moisture dominating in East and South Asia. In contrast, in South America and Southeast Asia, shifts in vegetation type associated with the BVOC emission capacity, which partly results from the deforestation and agricultural expansion, decrease the BVOC emission and offset nearly half of the emission increase caused by changes in meteorological factors. Overall, isoprene emission increases by 0.35 % per year and 0.25 % per year in South America and Southeast Asia, respectively. In Central Africa, a decrease in temperature dominates the negative emission trend (-0.74 % per year). Global monoterpene emissions show a significantly increasing trend (0.34 % per year, 0.6 Tg yr -1) compared to that of isoprene (-0.07 % per year, -0.2 Tg yr -1) , especially in strong greening hotspots. This is mainly because the monoterpene emissions are more sensitive to changes in LAI and are not subject to the inhibition effect of CO 2. The findings highlight the important roles of vegetation cover and biomass, temperature, and soil moisture in modulating the temporal variations of global BVOC emissions in the past 2 decades. [ABSTRACT FROM AUTHOR]

Organic aerosols from marine sources over the western Pacific Ocean of East Asia were investigated using an online coupled regional chemistry–climate model RIEMS-Chem for the entire year 2014. Model evaluation against a wide variety of observations from research cruises and in situ measurements demonstrated a good skill of the model in simulating temporal variation and spatial distribution of particulate matter with aerodynamic diameter less than 2.5 and 10 µm (PM 2.5 and PM 10), black carbon (BC), organic carbon (OC), sodium, and aerosol optical depth (AOD) in the marine atmosphere. The inclusion of marine organic aerosols improved model performance on OC concentration by reducing model biases of up to 20 %. The regional and annual mean near-surface marine organic aerosol (MOA) concentration was estimated to be 0.27 µgm-3 , with the maximum in spring and the minimum in winter, and contributed 26 % of the total organic aerosol concentration on average over the western Pacific. Marine primary organic aerosol (MPOA) accounted for the majority of marine organic aerosol (MOA) mass, and the MPOA concentration exhibited the maximum in autumn and the minimum in summer, whereas marine secondary organic aerosol (MSOA) was approximately 1–2 orders of magnitude lower than MPOA, having a distinct summer maximum and a winter minimum. MOA induced a direct radiative effect (DRE MOA) of - 0.27 Wm-2 and an indirect radiative effect (IRE MOA) of - 0.66 Wm-2 at the top of the atmosphere (TOA) in terms of annual and oceanic average over the western Pacific, with the highest seasonal mean IRE MOA up to - 0.94 Wm-2 in spring. IRE MOA was stronger than, but in a similar magnitude to, the IRE due to sea salt aerosol on average, and it was approximately 9 % of the IRE due to anthropogenic aerosols in terms of annual mean over the western Pacific. This ratio increased to 19 % in the northern parts of the western Pacific in autumn. This study reveals an important role of MOA in perturbing cloud properties and shortwave radiation fluxes in the western Pacific of East Asia. [ABSTRACT FROM AUTHOR]

When calibrating simulations of dust clouds, both the intensity and the position are important. Intensity errors arise mainly from uncertain emission and sedimentation strengths, while position errors are attributed either to imperfect emission timing, or to uncertainties in the transport. Though many studies have been conducted on the calibration or correction of dust simulations, most of these focus on intensity solely, and leave the position errors mainly unchanged. In this paper, a grid distorted data assimilation, which consists of an imaging morphing method and an ensemble-based variational assimilation, is designed for re-aligning a simulated dust plume to correct the position error. This new developed grid distorted data assimilation has been applied to a dust storm event in May 2017 over East Asia. Results have been compared for three configurations: a traditional assimilation that focuses solely on intensity correction, a grid distorted data assimilation that focuses on position correction only, and the hybrid assimilation that combines these two. For the evaluated case, the position misfit in the simulations is shown to be dominant in the results. The traditional emission inversion improves only slightly the dust simulation, while the grid distorted data assimilation effectively improves the dust simulation and forecast. The hybrid assimilation that corrects both position and intensity of the dust load provides the best initial condition for forecast of dust concentrations. [ABSTRACT FROM AUTHOR]

For the purpose of improving PM prediction skills in East Asia, we estimated a new background error covariance matrix (BEC) for aerosol data assimilation using surface PM2.5 observations that accounts for the uncertainties in anthropogenic emissions. In contrast to the conventional method to estimate the BEC that uses perturbations in meteorological data, this method additionally considered the perturbations using two different emission inventories. The impacts of the new BEC were then tested for the prediction of surface PM2.5 over East Asia using Community Multi-scale Air Quality (CMAQ) initialized by three-dimensional variational method (3D-VAR). The surface PM2.5 data measured at 154 sites in South Korea and 1,535 sites in China were assimilated every six hours during the Korea-United States Air Quality Study (KORUS-AQ) campaign period (1 May-14 June 2016). Data assimilation with our new BEC showed better agreement with the surface PM2.5 observations than that with the conventional method. Our method also showed closer agreement with the observations in 24-hour PM2.5 predictions with ~ 44 % fewer negative biases than the conventional method. We conclude that increased standard deviations, together with horizontal and vertical length scales in the new BEC, tend to improve the data assimilation and short-term predictions for the surface PM2.5. This paper also suggests further research efforts devoted to estimating the BEC to improve PM2.5 predictions. [ABSTRACT FROM AUTHOR]

In this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O 3 simulations with three bottom-up emission inventories (EDGAR-HTAP v2 and v3 and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O 3 and its main precursor NO 2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h average (MDA8) O 3 in the model do not completely align with the observations. The model MDA8 O 3 had a negative (positive) bias north (south) of 30° N over China. All simulations underestimated the observed CO by 50 %–60 % over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2 and v3 and KORUS v5 simulated the vertical shapes and diurnal patterns of O 3 and other precursors effectively, but the model underestimated the observed O 3 , CO, and HCHO concentrations. Notably, the model aromatic volatile organic compounds (VOCs) were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O 3 biases and the effects of the long-range transport on the O 3 over South Korea. The doubled CO and VOC emission simulations improved the model O 3 simulations for the local-emission-dominant case but led to the model O 3 overestimations for the transport-dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea. [ABSTRACT FROM AUTHOR]

This study explores the differences in performance and results by various versions of the ISORROPIA thermodynamic module implemented within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. Three different versions of the module were used, ISORROPIA II v1, ISORROPIA II v2.3, and ISORROPIA-lite. First, ISORROPIA II v2.3 replaced ISORROPIA II v1 in EMAC to improve pH predictions close to neutral conditions. The newly developed ISORROPIA-lite has been added to EMAC alongside ISORROPIA II v2.3. ISORROPIA-lite is more computationally efficient and assumes that atmospheric aerosols exist always as supersaturated aqueous (metastable) solutions, while ISORROPIA II includes the option to allow for the formation of solid salts at low RH conditions (stable state). The predictions of EMAC by employing all three aerosol thermodynamic models were compared to each other and evaluated against surface measurements from three regional observational networks in the polluted Northern Hemisphere (Interagency Monitoring of Protected Visual Environments (IMPROVE), European Monitoring and Evaluation Programme (EMEP), and Acid Deposition Monitoring Network of East Asia (EANET)). The differences between ISORROPIA II v2.3 and ISORROPIA-lite were minimal in all comparisons with the normalized mean absolute difference for the concentrations of all major aerosol components being less than 11 % even when different phase state assumptions were used. The most notable differences were lower aerosol concentrations predicted by ISORROPIA-lite in regions with relative humidity in the range of 20 % to 60 % compared to the predictions of ISORROPIA II v2.3 in stable mode. The comparison against observations yielded satisfactory agreement especially over the USA and Europe but higher deviations over East Asia, where the overprediction of EMAC for nitrate was as high as 4 µ g m -3 (∼20%). The mean annual aerosol pH predicted by ISORROPIA-lite was on average less than a unit lower than ISORROPIA II v2.3 in stable mode, mainly for coarse-mode aerosols over the Middle East. The use of ISORROPIA-lite accelerated EMAC by nearly 5 % compared to the use of ISORROPIA II v2.3 even if the aerosol thermodynamic calculations consume a relatively small fraction of the EMAC computational time. ISORROPIA-lite can therefore be a reliable and computationally efficient alternative to the previous thermodynamic module in EMAC. [ABSTRACT FROM AUTHOR]

Methods based on the absorption Ångström exponent (AAE) are widely used to estimate the absorption by brown carbon (BrC), and the estimated absorption by BrC can be significantly different from 0, even for pure black carbon (BC). However, few studies have systematically quantified the effects of BC microphysical properties. Moreover, the conditions under which AAE-based methods are applicable are still unclear. In this work, we used BC models partially coated with non-absorbing materials to calculate the total absorption. Since the total absorption is entirely due to BC, the estimated BrC absorption should be 0 if the retrieval methods are accurate. Thus, the ratio of the estimated BrC absorption to BC absorption (ABS BrC) should be the proportion of the BC absorption that is incorrectly attributed to BrC. The results show that a BC AAE of 1 can generally provide reasonable estimates for freshly emitted BC, since ABS BrC is generally in the range of -4.8 % to 2.7 % during that period. However, when BC aerosols are aged, ABS BrC can sometimes reach about 38.7 %. The wavelength dependence of the AAE (WDA) method does not necessarily improve the estimates; sometimes a negative ABSBrC of about -40.8 % is found for partially coated BC. By combining simulations of a global chemical transport model, this work also quantified the effects of BC microphysical properties on BrC global aerosol absorption optical depth (AAOD) estimates. The AAE = 1 method sometimes leads to a misassigned global mean AAOD of about - 0.43– 0.46×10-3 if the BC aerosols have a complex morphology. The WDA method does not necessarily improve the estimates. In our cases, the WDA methods based on spherical models could lead to a global-mean misassigned AAOD range of about -0.87 – 0.04×10-3. At the regional scale, the AAE = 1 method sometimes leads to a distributed AAOD of about -7.3 to 5.7×10-3 in some specific regions. Mie-theory-based WDA methods lead to an estimated AAOD error of about -22×10-3 in some regions (e.g., East Asia). This work also showed that the misattributed BrC absorption would lead to substantial uncertainties in the estimation of the global direct radiative forcing (DRF) of absorbing aerosols from different sources. [ABSTRACT FROM AUTHOR]

Using the reanalysis and multiple observations, the possible impact of the Madden–Julian Oscillation (MJO) on early summer (June–July) rainfall in eastern China and its modulation by the Quasi-Biennial Oscillation (QBO) are examined. The composite results show that the suppressed (enhanced) convection anomalies for MJO phases 8–1 (4–5) are more concentrated over the maritime continent and the western Pacific during easterly QBO (EQBO). As a consequence, more significant wet (dry) anomalies develop in South (eastern) China during MJO phases 8–1 (4–5) configured with easterly (westerly) QBO. The enhancement and expansion of the anomalous tropical convection band do not necessarily correspond to enhancement of the extratropical circulation response to MJO phases 8–1 (4–5) configured with westerly (easterly) QBO. The anomalous high (low) over the maritime continent and western Pacific associated with MJO phases 8–1 (4–5) is intensified (deepened) during easterly (westerly) QBO, leading to large southwesterly (northeasterly) anomalies in South China and the coasts, carrying abundant (sparse) moisture. Two anomalous meridional circulation cells are observed for MJO phases 8–1 in the East Asia sector, with downwelling anomalies around 5–20 ∘ N, upwelling anomalies around 20–30 ∘ N, and another downwelling branch northward of 30 ∘ N, which are enhanced during easterly QBO. The anomalous meridional circulation cells are reversed for MJO phases 4–5, which are stronger during westerly QBO with the anomalous downwelling and dry anomalies covering eastern China. The combined impact of MJO phases 8–1 and easterly QBO on the early summer rainfall is noticeable in 1996, 2016, and 2020. The enormous rainfall amount appeared along the Yangtze River in 1996, 2016, and 2020 due to the extended period of MJO phases 8–1 under the background of the easterly QBO. [ABSTRACT FROM AUTHOR]

The cosmogenic radionuclides 7 Be and 10 Be are useful tracers for atmospheric transport studies. Combining 7 Be and 10 Be measurements with an atmospheric transport model can not only improve our understanding of the radionuclide transport and deposition processes but also provide an evaluation of the transport process in the model. To simulate these aerosol tracers, it is critical to evaluate the influence of radionuclide production uncertainties on simulations. Here we use the GEOS-Chem chemical transport model driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis to simulate 7 Be and 10 Be with the state-of-the-art production rate from the CRAC:Be (Cosmic Ray Atmospheric Cascade: Beryllium) model considering realistic spatial geomagnetic cutoff rigidities (denoted as P16spa). We also perform two sensitivity simulations: one with the default production rate in GEOS-Chem based on an empirical approach (denoted as LP67) and the other with the production rate from the CRAC:Be but considering only geomagnetic cutoff rigidities for a geocentric axial dipole (denoted as P16). The model results are comprehensively evaluated with a large number of measurements including surface air concentrations and deposition fluxes. The simulation with the P16spa production can reproduce the absolute values and temporal variability of 7 Be and 10 Be surface concentrations and deposition fluxes on annual and sub-annual scales, as well as the vertical profiles of air concentrations. The simulation with the LP67 production tends to overestimate the absolute values of 7 Be and 10 Be concentrations. The P16 simulation suggests less than 10 % differences compared to P16spa but a significant positive bias (∼18 %) in the 7 Be deposition fluxes over East Asia. We find that the deposition fluxes are more sensitive to the production in the troposphere and downward transport from the stratosphere. Independent of the production models, surface air concentrations and deposition fluxes from all simulations show similar seasonal variations, suggesting a dominant meteorological influence. The model can also reasonably simulate the stratosphere–troposphere exchange process of 7 Be and 10 Be by producing stratospheric contribution and 10Be/7Be ratio values that agree with measurements. Finally, we illustrate the importance of including the time-varying solar modulations in the production calculation, which significantly improve the agreement between model results and measurements, especially at mid-latitudes and high latitudes. Reduced uncertainties in the production rates, as demonstrated in this study, improve the utility of 7 Be and 10 Be as aerosol tracers for evaluating and testing transport and scavenging processes in global models. For future GEOS-Chem simulations of 7 Be and 10 Be, we recommend using the P16spa (versus default LP67) production rate. [ABSTRACT FROM AUTHOR]

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117-265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched. [ABSTRACT FROM AUTHOR]

It is thought that East Asian monsoon (EAM) is linked and sensitive to solar activity. In this paper, we have decomposed the Dongge cave speleothem δ18O record (proxy for EAM), and Δ14C and 10Be (proxies for solar activity) time series into variations at different time scales with the empirical mode decomposition (EMD) method to reveal the possible link between the EAM variability and solar activity. There are some common cycles in the EAM and solar variability from centennial to millennial scales, indicating a possible link between EAM and solar activity at these time scales. The correlation between EAM and solar activity is much higher at millennial scales than at centennial scales, which means direct responses to the solar variation are more likely at time scales longer than a few hundred years. At ~ 30, 60 and 600 yr time scales, the variation in EAM is amplified by the solar amplitude modulation at ~ 100, 200 and 2200 yr time scales. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, the sulfur dioxide (SO2) emission from China since 2000 is of increasing concern. In this study, we estimate the annual SO2 emission in China after 2000 using a technology-based methodology specifically for China. From 2000 to 2006, total SO2 emission in China increased by 53%, from 21.7 Tg to 33.2 Tg, at an annual growth rate of 7.3%. Emissions from power plants are the main sources of SO2 in China and they increased from 10.6 Tg to 18.6 Tg in the same period. Geographically, emission from north China increased by 85%, whereas that from the south increased by only 28%. The emission growth rate slowed around 2005, and emissions began to decrease after 2006 mainly due to the wide application of flue-gas desulfurization (FGD) devices in power plants in response to a new policy of China's government. This paper shows that the trend of estimated SO2 emission in China is consistent with the trends of SO2 concentration and acid rain pH and frequency in China, as well as with the increasing trends of background SO2 and sulfate concentration in East Asia. A longitudinal gradient in the percentage change of urban SO2 concentration in Japan is found during 2000-2007, indicating that the decrease of urban SO2 is lower in areas close to the Asian continent. This implies that the transport of increasing SO2 from the Asian continent partially counteracts the local reduction of SO2 emission downwind. The aerosol optical depth (AOD) products of Moderate Resolution Imaging Spectroradiometer (MODIS) are found to be highly correlated with the surface solar radiation (SSR) measurements in East Asia. Using MODIS AOD data as a surrogate of SSR, we found that China and East Asia excluding Japan underwent a continuous dimming after 2000, which is in line with the dramatic increase in SO2 emission in East Asia. The trends of AOD from both satellite retrievals and model over East Asia are also consistent with the trend of SO2 emission in China, especially during the second half of the year, when sulfur contributes the largest fraction of AOD. The arrested growth in SO2 emissions since 2006 is also reflected in the decreasing trends of SO2 and SO2- concentrations, acid rain pH values and frequencies, and AOD over East Asia. [ABSTRACT FROM AUTHOR]4 concentrations, acid rain pH values and frequencies, and AOD over East Asia. [ABSTRACT FROM AUTHOR]

Trace metals in aerosol particles impact Earth's radiative budget, human health, and ocean biogeochemistry. Semi-continuous measurements of the elemental composition of fine-mode (PM 2.5) aerosols were conducted using an automated X-ray fluorescence analyzer on a remote island of Japan during the spring of 2018. Temporal variations in mass concentrations of geochemically important elements for this period, such as Pb, Cu, Si, Fe, and Mn, and their relationships with the emission tracers, carbon monoxide (CO) and black carbon (BC), were reported. The Integrated Massively Parallel Atmospheric Chemical Transport (IMPACT) model was used to evaluate the source apportionment of these components and was evaluated in terms of emissions and wet removal processes. Pb and Cu originated mainly from anthropogenic sources (98 % and 93 % on average, respectively) over the East Asian continent. Positive correlations of Pb and Cu with BC and CO and the similarity of their concentration-weighted trajectories indicated that the emission sources of these metals share the region where the large CO (and BC) emission sources are located and that CO can be regarded as a tracer of continental anthropogenic emissions. The air masses with minimized impacts of the wet removal during transport were extracted to elucidate the "top-down" emission ratio of Pb and Cu to CO, which were, for the first time, evaluated as 152.7 and 63.1 µg g -1 , respectively, during the spring of 2018 in the East Asian outflow. The analysis of the tagged tracer simulations by the IMPACT model confirmed that BC and Si could be used as tracers for anthropogenic and dust emissions, respectively, during the observation period. The source apportionment of Fe and Mn in PM 2.5 aerosols was conducted using Si and BC tracers, which revealed that the anthropogenic contribution was 17 % and 44 % on average, respectively. Based on the air mass origins of Fe and Mn, their anthropogenic fraction varied from 2 % to 29 % and 9 % to 68 %, respectively, during the high-PM 2.5 -concentration periods. However, despite the non-dominant anthropogenic contributions of Fe, they could adversely affect human health and ocean biogeochemistry, owing to their higher water solubility. The modeled BC, Pb, Cu, and Fe were evaluated by separately diagnosing their emission and transport. Ratios of modeled to observed concentrations for these components were analyzed in terms of the accumulated precipitation along the transport from the East Asian continent. The current model simulations were found to overestimate the emissions (based on the Community Emissions Data System, CEDS v2021-02-05) of BC by 44 % and underestimate Cu by 45 %, anthropogenic Fe by 28 % in East Asia, and the wet deposition rates for BC and Pb. Overall, Cu in East Asia exhibited a different nature from BC and Pb in terms of emission sources and wet removal. [ABSTRACT FROM AUTHOR]

The economic and environmental impacts of persistent droughts in East Asia are of growing concern, and therefore it is important to study the cyclicity and causes of these regional droughts. The self-calibrating Palmer drought severity index (scPDSI) has been extensively employed to describe the severity of regional drought, and several scPDSI reconstructions based on tree rings have been produced. We compiled a tree-ring chronology for Hailar pine (Pinus sylvestris var. mongolica) from two sites in the Hailar region in the upper Heilongjiang (Amur) River basin. Analysis of the climate response revealed that scPDSI was the primary factor limiting tree ring growth from May to July. The mean May to July scPDSI in the Hailar region since 1796 was reconstructed from the tree-ring width chronology. The results of spatial correlation analysis revealed that the reconstructed scPDSI in this region responded significantly to climate change. Analysis of the synoptic climatology indicated that the drought in the upper Heilongjiang (Amur) River basin is closely related to El Niño–Southern Oscillation (ENSO) and the Silk Road teleconnection. The results of atmospheric water cycle analysis show that water vapor transport processes are the dominant factor in the development of drought in this region. [ABSTRACT FROM AUTHOR]

The atmospheric deposition of iron (Fe) promotes primary production in the surface ocean, which results in the enhanced uptake of carbon dioxide into surface seawater. Given that microorganisms in seawater utilize dissolved Fe (d-Fe) as a nutrient, the bioavailability of Fe in aerosol particles depends on its solubility. However, the factors controlling fractional Fe solubility (Fe sol %) in aerosol particles have not been fully understood. This study performed annual observations of the total and dissolved metal concentrations in size-fractionated (seven fractions) aerosol particles at Higashi-Hiroshima, Japan. The feasibility of the molar concentration ratio of d-Fe relative to dissolved Al ([d-Fe] / [d-Al]) as an indicator of sources of d-Fe in aerosol particles was investigated because this ratio is likely dependent on the emission sources of Fe (e.g., mineral dust, fly ash, and anthropogenic Fe oxides) and their dissolution processes (proton- and ligand-promoted dissolutions). Approximately 70 % of the total Fe in total suspended particulates (TSPs) was present in coarse aerosol particles, whereas about 70 % of d-Fe in TSPs was mainly found in fine aerosol particles. The average Fe sol % in fine aerosol particles (11.4 ± 7.0 %) was higher than that of coarse aerosol particles (2.19 ± 2.27 %). In addition, the average ratio of [d-Fe] / [d-Al] in coarse aerosol particles (0.408 ± 0.168) was lower than that in fine aerosol particles (1.15 ± 0.80). The range of [d-Fe] / [d-Al] ratios in the coarse aerosol particles (0.121–0.927) was similar to that obtained by proton-promoted dissolution of mineral dust (0.1–1.0), which indicates that the d-Fe in coarse aerosol particles was derived from mineral dust. The [d-Fe] / [d-Al] ratios of fine aerosol particles ranged from 0.386 to 4.67, and [d-Fe] / [d-Al] ratios greater than 1.50 cannot be explained by proton- and ligand-promoted dissolutions (1.00 < [d-Fe] / [d-Al] < 1.50). The [d-Fe] / [d-Al] ratio correlated with the enrichment factor of Fe in fine aerosol particles (r : 0.505), which indicates that anthropogenic Fe with a high [d-Fe] / [d-Al] ratio was the source of d-Fe in fine aerosol particles. The high [d-Fe] / [d-Al] ratio was attributed to anthropogenic Fe oxides emitted from high-temperature combustions. Finally, the fraction of anthropogenic Fe oxides to d-Fe in TSPs was calculated based on the [d-Fe] / [d-Al] ratio of aerosols and their emission source samples. As a result, the fraction of anthropogenic Fe oxides to d-Fe in TSPs varied from 1.48 % to 80.7 %. A high fraction was observed in summer when air masses originated from industrial regions in Japan. By contrast, approximately 10 % of d-Fe in the TSPs collected in spring and during Asian dust events was derived from anthropogenic Fe oxides when air masses were frequently transported from East Asia to the Pacific Ocean. Thus, mineral dust was the dominant source of d-Fe in Asian outflow to the Pacific Ocean. [ABSTRACT FROM AUTHOR]

Shipping contributes significantly to air pollutant emissions and atmospheric particulate matter (PM) concentrations. At the same time, worldwide maritime transport volumes are expected to continue to rise in the future. The Mediterranean Sea is a major short-sea shipping route within Europe and is the main shipping route between Europe and East Asia. As a result, it is a heavily trafficked shipping area, and air quality monitoring stations in numerous cities along the Mediterranean coast have detected high levels of air pollutants originating from shipping emissions. The current study is a part of the EU Horizon 2020 project SCIPPER (Shipping Contributions to Inland Pollution – Push for the Enforcement of Regulations), which intends to investigate how existing restrictions on shipping-related emissions to the atmosphere ensure compliance with legislation. To demonstrate the impact of ships on relatively large scales, the potential shipping impacts on various air pollutants can be simulated with chemical transport models. To determine the formation, transport, chemical transformation, and fate of particulate matter < 2.5 µ m (PM 2.5) in the Mediterranean Sea in 2015, five different regional chemical transport models (CAMx – Comprehensive Air Quality Model with Extensions, CHIMERE, CMAQ – Community Multiscale Air Quality model, EMEP – European Monitoring and Evaluation Programme model, and LOTOS-EUROS) were applied. Furthermore, PM 2.5 precursors (ammonia (NH 3), sulfur dioxide (SO 2), nitric acid (HNO 3)) and inorganic particle species (sulfate (SO 42-), ammonia (NH 4+), nitrate (NO 3-)) were studied, as they are important for explaining differences among the models. STEAM (see "List of abbreviations" in Appendix A) version 3.3.0 was used to compute shipping emissions, and the CAMS-REG version 2.2.1 dataset was used to calculate land-based emissions for an area encompassing the Mediterranean Sea at a resolution of 12 × 12 km 2 (or 0.1 ∘ × 0.1 ∘). For additional input, like meteorological fields and boundary conditions, all models utilized their regular configuration. The zero-out approach was used to quantify the potential impact of ship emissions on PM 2.5 concentrations. The model results were compared with observed background data from monitoring sites. Four of the five models underestimated the actual measured PM 2.5 concentrations. These underestimations are linked to model-specific mechanisms or underpredictions of particle precursors. The potential impact of ships on the PM 2.5 concentration is between 15 % and 25 % at the main shipping routes. Regarding particle species, SO 42- is the main contributor to the absolute ship-related PM 2.5 and to total PM 2.5 concentrations. In the ship-related PM 2.5 , a higher share of inorganic particle species can be found when compared with the total PM 2.5. The seasonal variabilities in particle species show that NO 3- is higher in winter and spring, while the NH 4+ concentrations displayed no clear seasonal pattern in any models. In most cases with high concentrations of both NH 4+ and NO 3- , lower SO 42- concentrations are simulated. Differences among the simulated particle species distributions might be traced back to the aerosol size distribution and how models distribute emissions between the coarse and fine modes (PM 2.5 and PM 10). The seasonality of wet deposition follows the seasonality of the precipitation, showing that precipitation predominates wet deposition. [ABSTRACT FROM AUTHOR]

We apply a local ensemble transform Kalman smoother (LETKS) in combination with the global aerosol–climate model ECHAM–HAM to estimate aerosol emissions from POLDER-3/PARASOL (POLarization and Directionality of the Earth's Reflectances) observations for the year 2006. We assimilate aerosol optical depth at 550 mnm (AOD550), the Ångström exponent at 550 and 865 nm (AE550–865), and single-scattering albedo at 550 nm (SSA550) in order to improve modeled aerosol mass, size and absorption simultaneously. The new global aerosol emissions increase to 1419 Tgyr-1 (+ 28 %) for dust, 1850 Tgyr-1 (+ 75 %) for sea salt, 215 Tgyr-1 (+ 143 %) for organic aerosol and 13.3 Tgyr-1 (+ 75 %) for black carbon, while the sulfur dioxide emissions increase to 198 Tgyr-1 (+ 42 %) and the total deposition of sulfates to 293 Tgyr-1 (+ 39 %). Organic and black carbon emissions are much higher than their prior values from bottom-up inventories, with a stronger increase in biomass burning sources (+ 193 % and + 90 %) than in anthropogenic sources (115 % and 70 %). The evaluation of the experiments with POLDER (assimilated) and AERONET as well as MODIS Dark Target (independent) observations shows a clear improvement compared with the ECHAM–HAM control run. Specifically based on AERONET, the global mean error in AOD550 improves from - 0.094 to - 0.006, while absorption aerosol optical depth at 550 nm (AAOD550) improves from - 0.009 to - 0.004 after the assimilation. A smaller improvement is also observed in the AE550–865 mean absolute error (from 0.428 to 0.393), with a considerably higher improvement over isolated island sites at the ocean. The new dust emissions are closer to the ensemble median of AEROCOM I, AEROCOM III and CMIP5 as well as some of the previous assimilation studies. The new sea salt emissions have become closer to the reported emissions from previous studies. Indications of a missing fraction of coarse dust and sea salt particles are discussed. The biomass burning changes (based on POLDER) can be used as alternative biomass burning scaling factors for the Global Fire Assimilation System (GFAS) inventory distinctively estimated for organic carbon (2.93) and black carbon (1.90) instead of the recommended scaling of 3.4 (Kaiser et al., 2012). The estimated emissions are highly sensitive to the relative humidity due to aerosol water uptake, especially in the case of sulfates. We found that ECHAM–HAM, like most of the global climate models (GCMs) that participated in AEROCOM and CMIP6, overestimated the relative humidity compared with ERA5 and as a result the water uptake by aerosols, assuming the kappa values are not underestimated. If we use the ERA5 relative humidity, sulfate emissions must be further increased, as modeled sulfate AOD is lowered. Specifically, over East Asia, the lower AOD can be attributed to the underestimated precipitation and the lack of simulated nitrates in the model. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NOx=NO+NO2) emissions are estimated in three regions in the Northern Hemisphere, generally located in North America, Europe, and East Asia, by calculating the directional derivatives of NO2 column amounts observed by the TROPOspheric Monitoring Instrument (TROPOMI) with respect to the horizontal wind vectors. We present monthly averaged emissions from 1 May 2018 to 31 January 2023 to capture variations before and after the COVID-19 pandemic. We focus on a diverse collection of 54 cities, 18 in each region. A spatial resolution of 0.04 ∘ resolves intracity emission variations and reveals NOx emission hotspots at city cores, industrial areas, and sea ports. For each selected city, post-COVID-19 changes in NOx emissions are estimated by comparing monthly and annually averaged values to the pre-COVID-19 year of 2019. While emission reductions are initially found during the first outbreak of COVID-19 in early 2020 in most cities, the cities' paths diverge afterwards. We group the selected cities into four clusters according to their normalized annual NOx emissions in 2019–2022 using an unsupervised learning algorithm. All but one of the selected North American cities fall into cluster 1 characterized by weak emission reduction in 2020 (- 7 % relative to 2019) and an increase in 2022 by + 5 %. Cluster 2 contains mostly European cities and is characterized by the largest reduction in 2020 (- 31 %), whereas the selected East Asian cities generally fall into clusters 3 and 4, with the largest impacts in 2022 (- 25 % and - 37 %). This directional derivative approach has been implemented in object-oriented, open-source Python and is available publicly for high-resolution and low-latency emission estimation for different regions, atmospheric species, and satellite instruments. [ABSTRACT FROM AUTHOR]

Atmospheric ammonia (NH 3) is a reactive nitrogen compound that pollutes our environment and threatens public health. Monitoring the spatial and temporal variations is important for quantifying its emissions and depositions and evaluating the strategies for managing anthropogenic sources of NH 3. In this study, we present an NH 3 retrieval algorithm based on the optimal estimation method for the Geostationary Interferometric Infrared Sounder (GIIRS) on board China's FengYun-4B satellite (FY-4B/GIIRS). In particular, we examine the information content based on the degree of freedom for signal (DOFS) in retrieving the diurnal NH 3 in East Asia, with a focus on two source regions including the North China Plain and North India. Our retrieval is based on the FengYun Geostationary satellite Atmospheric Infrared Retrieval (FY-GeoAIR) algorithm and exploits the strong NH 3 absorption window of 955–975 cm -1. Retrieval results using FY-4B/GIIRS spectra from July to December 2022 show that the DOFS for the majority ranges from 0 to 1.0, mainly depending on the thermal contrast (TC) defined as the temperature difference between the surface and the lowest atmospheric layer. Consistent with retrievals from low-Earth-orbit (LEO) infrared sounders, the detection sensitivity, as quantified by the averaging kernel (AK) matrix, peaks in the lowest 2 km atmospheric layers. The DOFS and TC are highly correlated, resulting in a typical "butterfly" shape. That is, the DOFS increases when TC becomes either more positive or more negative. The NH 3 columns from FY-4B/GIIRS exhibit significant diurnal cycles that are consistent with the day–night gradient from the collocated IASI retrievals in the North China Plain and North India for the averages in July–August, September–October, and November–December, respectively. A collocated point-by-point intercomparison with the IASI NH 3 dataset shows generally good agreement with a small systematic difference in the summer months that may be attributed to the slight difference in a priori profiles. This study demonstrates the capability of FY-4B/GIIRS in capturing the diurnal NH 3 changes in East Asia, which will have the potential to improve regional and global air quality and climate research. [ABSTRACT FROM AUTHOR]

As a natural aerosol with the largest emissions on land, dust has important impacts on the atmospheric environment and climate systems. Both the emissions and transport of dust aerosols are tightly connected to meteorological conditions and as a result are confronted with strong modulations by the changing climate. Here, we project the changes in the global dust emissions and loading by the end of the 21st century, using an ensemble of model outputs from the Coupled Model Intercomparison Project version 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs). Based on the validations against site-level observations, we select 9 out of 14 models and estimate an ensemble global dust emissions of 2566 ± 1996 Tga-1 (1 Tg = 10 12 g) for the present day, in which 68 % is dry deposited and 31 % is wet deposited. Compared to 2005–2014, global dust emissions show varied responses, with a reduction of - 5.6 ± 503 Tga-1 under the SSP3–7.0 scenario but increased emissions up to 60.7 ± 542 Tga-1 under the SSP5–8.5 scenario at 2090–2099. For all scenarios, the most significant increase in the dust emissions appears in North Africa (0.6 %–5.6 %) due to the combined effects of reduced precipitation but strengthened surface wind. In contrast, all scenarios show decreased emissions in the Taklimakan and Gobi deserts (- 0.8 % to - 11.9 %) because of the increased precipitation but decreased wind speed on a regional scale. The dust loading shows uniform increases over North Africa (1.6 %–13.5 %) and the downwind Atlantic, following the increased emissions but decreases over East Asia (- 1.3 % to - 10.5 %), and the downwind Pacific, partly due to enhanced local precipitation that promotes wet deposition. In total, global dust loading will increase by 2.0 %–12.5 % at the end of the 21st century under different climate scenarios, suggesting a likelihood of strengthened radiative and climatic perturbations by dust aerosols in a warmer climate. [ABSTRACT FROM AUTHOR]

To quantify CH4 emissions at policy-relevant spatial scales, the Korea Meteorological Administration (KMA) started monitoring its atmospheric levels in 1999 at Anmyeondo (AMY) and expanded monitoring to Jeju Gosan Suwolbong (JGS) and Ulleungdo (ULD) in 2012. The monitoring system consists of a cavity ring-down spectrometer (CRDS) and a new cryogenic drying method, with a measurement uncertainty (68 % c.i. (confidence interval)) of ± 0.7–0.8 ppb. To determine the regional characteristics of CH4 at each KMA station, we assessed the CH4 level relative to local background (CH4xs), analyzed local surface winds and CH4 with bivariate polar plots, and investigated CH4 diurnal cycles. We also compared the CH4 levels measured at KMA stations with those measured at the Mt. Waliguan (WLG) station in China and Ryori (RYO) station in Japan. CH4xs followed the order AMY (55.3 ± 37.7 ppb) > JGS (24.1 ± 10.2 ppb) > ULD (7.4 ± 3.9 ppb). Although CH4 was observed in well-mixed air at AMY, it was higher than at other KMA stations, indicating that it was affected not only by local sources but also by distant air masses. Annual mean CH4 was highest at AMY among all East Asian stations, while its seasonal amplitude was smaller than at JGS, which was strongly affected in the summer by local biogenic activities. From the long-term records at AMY, we confirmed that growth rate increased by 3.3 ppbyr-1 during 2006/2010 and by 8.3 ppbyr-1 from 2016 to 2020, which is similar to the global trend. Studies indicated that the recent global accelerated CH4 -growth rate was related to biogenic sources. However, δ13CH4 indicates that the CH4 trend in East Asia is derived from both biogenic and fossil fuel sources from 2006 to 2020. We confirmed that long-term high-quality data can help understand changes in CH4 emissions in East Asia. [ABSTRACT FROM AUTHOR]

In response to the need for an up-to-date emissions inventory and the recent achievement of geostationary observations afforded by the Geostationary Environment Monitoring Spectrometer (GEMS) and its sister instruments, this study aims to establish a top-down approach for adjusting aerosol precursor emissions over East Asia. This study involves a series of the TROPOspheric Monitoring Instrument (TROPOMI) NO 2 product, the GEMS aerosol optical depth (AOD) data fusion product and its proxy product, and chemical transport model (CTM)-based inverse modeling techniques. We begin by sequentially adjusting bottom-up estimates of nitrogen oxides (NOx) and primary particulate matter (PM) emissions, both of which significantly contribute to aerosol loadings over East Asia to reduce model biases in AOD simulations during the year 2019. While the model initially underestimates AOD by 50.73 % on average, the sequential emissions adjustments that led to overall increases in the amounts of NOx emissions by 122.79 % and of primary PM emissions by 76.68 % and 114.63 % (single- and multiple-instrument-derived emissions adjustments, respectively) reduce the extents of AOD underestimation to 33.84 % and 19.60 %, respectively. We consider the outperformance of the model using the emissions constrained by the data fusion product to be the result of the improvement in the quantity of available data. Taking advantage of the data fusion product, we perform sequential emissions adjustments during the spring of 2022, the period during which the substantial reductions in anthropogenic emissions took place accompanied by the COVID-19 pandemic lockdowns over highly industrialized and urbanized regions in China. While the model initially overestimates surface PM 2.5 concentrations by 47.58 % and 20.60 % in the North China Plain (NCP) region and South Korea (hereafter referred to as Korea), the sequential emissions adjustments that led to overall decreases in NOx and primary PM emissions by 7.84 % and 9.03 %, respectively, substantially reduce the extents of PM 2.5 underestimation to 19.58 % and 6.81 %, respectively. These findings indicate that the series of emissions adjustments, supported by the TROPOMI and GEMS-involved data fusion products, performed in this study are generally effective at reducing model biases in simulations of aerosol loading over East Asia; in particular, the model performance tends to improve to a greater extent on the condition that spatiotemporally more continuous and frequent observational references are used to capture variations in bottom-up estimates of emissions. In addition to reconfirming the close association between aerosol precursor emissions and AOD as well as surface PM 2.5 concentrations, the findings of this study could provide a useful basis for how to most effectively exploit multisource top-down information for capturing highly varying anthropogenic emissions. [ABSTRACT FROM AUTHOR]

The reduction of fine particles (PM 2.5) and reactive N (N r) and S (S r) species is a key objective for air pollution control policies because of their major adverse effects on human health, ecosystem diversity, and climate. The sensitivity of global and regional N r , S r , and PM 2.5 to 20 % and 40 % individual and collective reductions in anthropogenic emissions of NH 3 , NO x , and SO x (with respect to a 2015 baseline) is investigated using the EMEP MSC-W (European Monitoring and Evaluation Programme Meteorological Synthesizing Centre – West) atmospheric chemistry transport model with WRF (Weather Research and Forecasting) meteorology. Regional comparisons reveal that the individual emissions reduction has multiple co-benefits and small disbenefits on different species, and those effects are highly geographically variable. A 40 % NH 3 emission reduction decreases regional average NH 3 concentrations by 47 %–49 % but only decreases NH 4+ by 18 % in Euro_Medi, 15 % in East Asia, 12 % in North America, and 4 % in South Asia. This order follows the regional ammonia richness. A disbenefit is the increased SO 2 concentrations in these regions (10 %–16 % for 40 % reductions) because reduced NH 3 levels decrease SO 2 deposition through altering atmospheric acidity. A 40 % NO x emission reduction reduces NO x concentrations in East Asia by 45 %, Euro_Medi and North America by ∼ 38 %, and South Asia by 22 %, whilst the regional order is reversed for fine NO 3- , which is related to enhanced O 3 levels in East Asia (and also, but by less, in Euro_Medi) and decreased O 3 levels in South Asia (and also, but by less, in North America). Consequently, the oxidation of NO x to NO 3- and of SO 2 to SO 42- is enhanced in East Asia but decreased in South Asia, which causes a less effective decrease in NO 3- and even an increase in SO 42- in East Asia but quite the opposite in South Asia. For regional policy making, it is thus vital to reduce three precursors together to minimize such adverse effects. A 40 % SO x emission reduction is slightly more effective in reducing SO 2 (42 %–45 %) than SO 42- (34 %–38 %), whilst the disbenefit is that it yields a ∼ 12 % increase in total NH 3 deposition in the four regions, which further threatens ecosystem diversity. This work also highlights important messages for policy makers concerning the mitigation of PM 2.5. More emissions controls focusing on NH 3 and NO x are necessary for regions with better air quality, such as northern Europe and eastern North America. In East Asia, the three individual reductions are equally effective, whilst in South Asia only SO x reduction is currently effective. The geographically varying non-one-to-one proportionality of chemical responses of N r , S r , and PM 2.5 to emissions reductions revealed by this work show the importance of both prioritizing emissions strategies in different regions and combining several precursor reductions together to maximize the policy effectiveness. [ABSTRACT FROM AUTHOR]

Reanalysis data play a vital role in weather and climate study as well as meteorological resource development and application. In this work, the East Asia Reanalysis System (EARS) was developed using the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolations (GSI) data assimilation system. The regional reanalysis system is forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) global reanalysis ERA-Interim data at 6 h intervals. Hourly surface observations are assimilated by the Four-Dimension Data Assimilation (FDDA) scheme during the WRF model integration; upper observations are assimilated in three-dimensional variational data assimilation (3D-VAR) mode at the analysis moment. It should be highlighted that many of the assimilated observations have not been used in other reanalysis systems. The reanalysis runs from 1980 to 2018, producing a regional reanalysis dataset covering East Asia and surrounding areas at 12 km horizontal resolution, 74 sigma levels, and 3 h intervals. Finally, an evaluation of EARS has been performed with respect to the root mean square error (RMSE), based on the 10-year (2008–2017) observational data. Compared to the global reanalysis data of ERA-Interim, the regional reanalysis data of EARS are closer to the observations in terms of RMSE in both surface and upper-level fields. The present study provides evidence for substantial improvements seen in EARS compared to the ERA-Interim reanalysis fields over East Asia. The study also demonstrates the potential use of the EARS data for applications over East Asia and proposes further plans to provide the latest reanalysis in real-time operation mode. Simple data and updated information are available on Zenodo at 10.5281/zenodo.7404918 (Yin et al., 2022), and the full datasets are publicly accessible on the Data-as-a-Service platform of the China Meteorological Administration (CMA) at http://data.cma.cn (last access: 19 May 2023). [ABSTRACT FROM AUTHOR]

Despite the importance of aerosol height information for events such as volcanic eruptions and long-range aerosol transport, spatial coverage of its retrieval is often limited because of a lack of appropriate instruments and algorithms. Geostationary satellite observations in particular provide constant monitoring for such events. This study assessed the application of different viewing geometries for a pair of geostationary imagers to retrieve aerosol top height (ATH) information. The stereoscopic algorithm converts a lofted aerosol layer parallax, calculated using image-matching of two visible images, to ATH. The sensitivity study provides a reliable result using a pair of Advanced Himawari Imager (AHI) and Advanced Geostationary Radiation Imager (AGRI) images at 40 ∘ longitudinal separation. The pair resolved aerosol layers above 1 km altitude over East Asia. In contrast, aerosol layers must be above 3 km for a pair of AHI and Advanced Meteorological Imager (AMI) images at 12.5 ∘ longitudinal separation to resolve their parallax. Case studies indicate that the stereoscopic ATH retrieval results are consistent with aerosol heights determined using extinction profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP). Comparisons between the stereoscopic ATH and the CALIOP 90 % extinction height, defined by extinction coefficient at 532 nm data, indicated that 88.9 % of ATH estimates from the AHI and AGRI are within 2 km of CALIOP 90 % extinction heights, with a root-mean-squared difference (RMSD) of 1.66 km. Meanwhile, 24.4 % of ATH information from the AHI and AMI was within 2 km of the CALIOP 90 % extinction height, with an RMSD of 4.98 km. The ability of the stereoscopic algorithm to monitor hourly aerosol height variations is demonstrated by comparison with a Korea Aerosol Lidar Observation Network dataset. [ABSTRACT FROM AUTHOR]

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM 10 and PM 2.5. Coarse PM concentrations in 2015 averaged 52 µ g m -3 in the North China Plain (NCP) and 23 µ g m -3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM 10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM 2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM 2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM 2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM 2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM 2.5 nitrate. [ABSTRACT FROM AUTHOR]

Stable water isotopes are natural tracers in the hydrological cycle and have been applied in hydrology, atmospheric science, ecology, and paleoclimatology. However, the factors controlling the isotopic distribution, both at spatial and temporal scales, are debated in low and middle latitude regions, due to the significant influence of large-scale atmospheric circulation and complex sources of water vapor. For the first time, we made in situ observations of near-surface vapor isotopes over a large region (over 10 000 km) across China in both pre-monsoon and monsoon seasons, using a newly designed vehicle-based vapor isotope monitoring system. Combined with daily and multiyear monthly mean outputs from the isotope-incorporated global spectral model (Iso-GSM) and infrared atmospheric sounding interferometer (IASI) satellite to calculate the relative contribution, we found that the observed spatial variations in both periods represent mainly seasonal mean spatial variations, but are influenced by more significant synoptic-scale variations during the monsoon period. The spatial variations of vapor δ18 O are mainly controlled by Rayleigh distillation along air mass trajectories during the pre-monsoon period, but are significantly influenced by different moisture sources, continental recycling processes, and convection during moisture transport in the monsoon period. Thus, the North–South gradient observed during the pre-monsoon period is counteracted during the monsoon period. The seasonal variation of vapor δ18 O reflects the influence of the summer monsoon convective precipitation in southern China and a dependence on temperature in the North. The spatial and seasonal variations in d-excess reflect the different moisture sources and the influence of continental recycling. Iso-GSM successfully captures the spatial distribution of vapor δ18 O during the pre-monsoon period, but the performance is weaker during the monsoon period, maybe due to the underestimation of local or short-term high-frequency synoptic variations. These results provide an overview of the spatial distribution and seasonal variability of water isotopic composition in East Asia and their controlling factors, and they emphasize the need to interpret proxy records in the context of the regional system. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NO x≡ NO + NO 2) are of central importance for air quality, climate forcing, and nitrogen deposition to ecosystems. The Geostationary Environment Monitoring Spectrometer (GEMS) is now providing hourly NO 2 satellite observations over East Asia, offering the first direct measurements of NO 2 diurnal variation from space to guide understanding of NO x emissions and chemistry. The NO 2 retrieval requires independent vertical profile information from a chemical transport model (CTM) to compute the air mass factor (AMF) that relates the NO 2 column measured along the line of sight to the NO 2 vertical column. Here, we use aircraft observations from the Korea-United States Air Quality (KORUS-AQ) campaign over the Seoul metropolitan area (SMA) and around the Korean Peninsula in May–June 2016 to better understand the factors controlling the NO 2 vertical profile, its diurnal variation, the implications for the AMFs, and the ability of the GEOS-Chem CTM to compute the NO 2 vertical profiles used for AMFs. Proper representation of oxidant chemistry is critical for the CTM simulation of NO 2 vertical profiles and is achieved in GEOS-Chem through new model developments, including aerosol nitrate photolysis, reduced uptake of hydroperoxy (HO 2) radicals by aerosols, and accounting for atmospheric oxidation of volatile chemical products (VCPs). We find that the tropospheric NO 2 columns measured from space in the SMA are mainly contributed by the planetary boundary layer (PBL) below 2 km altitude, reflecting the highly polluted conditions. Repeated measurements of NO 2 vertical profiles over the SMA at different times of day show that diurnal change in mixing depth affecting the NO 2 vertical profile induces a diurnal variation in AMFs of comparable magnitude to the diurnal variation in the NO 2 column. GEOS-Chem captures this diurnal variation in AMFs and more generally the variability in the AMFs for the KORUS-AQ NO 2 vertical profiles (2.7 % mean bias, 7.6 % precision), with some outliers in the morning due to errors in the timing of mixed-layer growth. [ABSTRACT FROM AUTHOR]

Shipping has a significant share in the emissions of air pollutants such as NO x and particulate matter (PM), and the global maritime transport volumes are projected to increase further in the future. The major route for short sea shipping within Europe and the main shipping route between Europe and East Asia are found in the Mediterranean Sea. Thus, it is a highly frequented shipping area, and high levels of air pollutants with significant potential impacts from shipping emissions are observed at monitoring stations in many cities along the Mediterranean coast. The present study is part of the EU H2020 project SCIPPER (Shipping contribution to Inland Pollution Push for the Enforcement of Regulations). Five different regional chemistry transport models (CAMx – Comprehensive Air Quality Model with Extensions, CHIMERE, CMAQ, EMEP – European Monitoring and Evaluation Programme, LOTOS-EUROS) were used to simulate the transport, chemical transformation and fate of atmospheric pollutants in the Mediterranean Sea for 2015. Shipping emissions were calculated with the Ship Traffic Emission Assessment Model (STEAM) version 3.3.0, and land-based emissions were taken from the CAMS-REG v2.2.1 dataset for a domain covering the Mediterranean Sea at a resolution of 12 km × 12 km (or 0.1∘×0.1∘). All models used their standard setup for further input. The potential impact of ships was calculated with the zero-out method. The model results were compared to each other and to measured background data at monitoring stations. The model results differ regarding the time series and pattern but are similar concerning the overall underestimation of NO 2 and overestimation of O 3. The potential impact from ships on the total NO 2 concentration was especially high on the main shipping routes and in coastal regions (25 % to 85 %). The potential impact from ships on the total O 3 concentration was lowest in regions with the highest NO 2 impact (down to -20 %). CAMx and CHIMERE simulated the highest potential impacts of ships on the NO 2 and O 3 air concentrations. Additionally, the strongest correlation was found between CAMx and CHIMERE, which can be traced back to the use of the same meteorological input data. The other models used different meteorological input due to their standard setup. The CMAQ-, EMEP- and LOTOS-EUROS-simulated values were within one range for the NO 2 and O 3 air concentrations. Regarding simulated deposition, larger differences between the models were found when compared to air concentration. These uncertainties and deviations between models are caused by deposition mechanisms, which are unique within each model. A reliable output from models simulating ships' potential impacts can be expected for air concentrations of NO 2 and O 3. [ABSTRACT FROM AUTHOR]