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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]

A total of 20 urban neighbourhood-scale eddy covariance flux tower datasets are made openly available after being harmonized to create a 50 site–year collection with broad diversity in climate and urban surface characteristics. Variables needed as inputs for land surface models (incoming radiation, temperature, humidity, air pressure, wind and precipitation) are quality controlled, gap-filled and prepended with 10 years of reanalysis-derived local data, enabling an extended spin up to equilibrate models with local climate conditions. For both gap filling and spin up, ERA5 reanalysis meteorological data are bias corrected using tower-based observations, accounting for diurnal, seasonal and local urban effects not modelled in ERA5. The bias correction methods developed perform well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015). Other variables (turbulent and upwelling radiation fluxes) are harmonized and quality controlled without gap filling. Site description metadata include local land cover fractions (buildings, roads, trees, grass etc.), building height and morphology, aerodynamic roughness estimates, population density and satellite imagery. This open collection can help extend our understanding of urban environmental processes through observational synthesis studies or in the evaluation of land surface environmental models in a wide range of urban settings. These data can be accessed from https://doi.org/10.5281/zenodo.7104984 (Lipson et al., 2022). [ABSTRACT FROM AUTHOR]

To validate the Geostationary Environment Monitoring Spectrometer (GEMS), the GEMS Map of Air Pollution (GMAP) campaign was conducted during 2020–2021 by integrating Pandora Asia Network, aircraft, and in situ measurements. In the present study, GMAP-2020 measurements were applied to evaluate urban air quality and explore the synergy of Pandora column (PC) NO2 measurements and surface in situ (SI) NO2 measurements for Seosan, South Korea, where large point source (LPS) emissions are densely clustered. Due to the difficulty of interpreting the effects of LPS emissions on air quality downwind of Seosan using SI monitoring networks alone, we explored the combined analysis of both PC- NO2 and SI- NO2 measurements. Agglomerative hierarchical clustering using vertical meteorological variables combined with PC- NO2 and SI- NO2 yielded three distinct conditions: synoptic wind-dominant (SD), mixed (MD), and local wind-dominant (LD). These results suggest meteorology-dependent correlations between PC- NO2 and SI- NO2. Overall, yearly daytime mean (11:00–17:00 KST) PC- NO2 and SI- NO2 statistical data showed good linear correlations (R=∼0.73); however, the differences in correlations were largely attributed to meteorological conditions. SD conditions characterized by higher wind speeds and advected marine boundary layer heights suppressed fluctuations in both PC- NO2 and SI- NO2 , driving a uniform vertical NO2 structure with higher correlations, whereas under LD conditions, LPS plumes were decoupled from the surface or were transported from nearby cities, weakening correlations through anomalous vertical NO2 gradients. The discrepancies suggest that using either PC- NO2 or SI- NO2 observations alone involves a higher possibility of uncertainty under LD conditions or prevailing transport processes. However, under MD conditions, both pollution ventilation due to high surface wind speeds and daytime photochemical NO2 loss contributed to stronger correlations through a decline in both PC- NO2 and SI- NO2 towards noon. Thus, Pandora Asia Network observations collected over 13 Asian countries since 2021 can be utilized for detailed investigation of the vertical complexity of air quality, and the conclusions can be also applied when performing GEMS observation interpretation in combination with SI measurements. [ABSTRACT FROM AUTHOR]

The so-called Green Sahara (GS), which was a wet and vegetative Sahara region in the early to mid-Holocene, provides useful information on our climate simulation because it is a consequence of complex interaction between biophysical and climatic processes. It is still a challenge to simulate the GS in terms of vegetative extent and precipitation using current climate models. This study attempts to simulate the Green Sahara 8000 years ago by using the state-of-the-art Earth system model CESM that incorporates the nitrogen cycle and the soil–precipitation feedbacks. Our study puts more emphasis on the impact of soil biophysical properties (e.g., bare-soil albedo, porosity, heat capacity, and hydraulic conductivity) and soil nitrogen influenced by soil organic matter on the simulation of the GS. In this coupled simulation, vegetation interacts with changes in soil properties and soil organic matter by phenology, decomposition, and allocation of carbon and nitrogen. With changes in the Earth's orbit and dust in the early to mid-Holocene, the model simulates increased precipitation in North Africa but does not capture the extent of the GS. Our analysis shows that the Holocene greening is simulated better if the amount of soil nitrogen and soil texture is properly modified for the humid and vegetative GS period. Soil biochemical and physical properties increase precipitation and vegetation cover in North Africa through their influence on photosynthesis and surface albedo as well as their consequent enhanced albedo–precipitation and evapotranspiration–precipitation feedbacks. Our findings suggest that future climate simulation needs to consider consequent changes in soil nitrogen and texture with changes in vegetation cover and density for proper climate simulations. [ABSTRACT FROM AUTHOR]

The prevalent soil moisture probe algorithms are based on a polynomial function that does not account for the variability in soil organic matter. Users are expected to choose a model before application: either a model for mineral soil or a model for organic soil. Both approaches inevitably suffer from limitations with respect to estimating the volumetric soil water content in soils with a wide range of organic matter content. In this study, we propose a new algorithm based on the idea that the amount of soil organic matter (SOM) is related to major uncertainties in the in situ soil moisture data obtained using soil probe instruments. To test this theory, we derived a multiphase inversion algorithm from a physically based dielectric mixing model capable of using the SOM amount, performed a selection process from the multiphase model outcomes, and tested whether this new approach improves the accuracy of soil moisture (SM) data probes. The validation of the proposed new soil probe algorithm was performed using both gravimetric and dielectric data from the Soil Moisture Active Passive Validation Experiment in 2012 (SMAPVEX12). The new algorithm is more accurate than the previous soil-probe algorithm, resulting in a slightly improved correlation (0.824 to 0.848), 12 % lower root mean square error (RMSE; 0.0824 to 0.0727 cm 3 cm -3), and 95 % less bias (-0.0042 to 0.0001 cm 3 cm -3). These results suggest that applying the new dielectric mixing model together with global SOM estimates will result in more reliable soil moisture reference data for weather and climate models and satellite validation. [ABSTRACT FROM AUTHOR]

Cities represent a key space for our sustainable trajectory in a changing environment, and our society is steadily embracing urban green space for its role in mitigating heatwaves and anthropogenic CO2 emissions. This study reports two-year surface fluxes of energy and CO2 measured via the eddy covariance method in an artificially constructed urban forest to examine the impact of urban forests on air temperature and net CO2 exchange. The urban forest site shows typical seasonal patterns of forest canopies with the seasonal march of the East Asian summer monsoon. Our analysis indicates that the urban forest reduces both the warming trend and urban heat island intensity compared to the adjacent high-rise urban areas and that photosynthetic carbon uptake is large despite relatively small tree density and leaf area index. During the significant drought period in the second year, gross primary production and evapotranspiration decreased, but their reduction was not as significant as those in natural forest canopies. We speculate that forest management practices, such as artificial irrigation and fertilization, enhance vegetation activity. We also stipulate that ecosystem respiration in urban forests is more pronounced than typical natural forests in a similar climate zone. This can be attributed to the substantial amount of soil organic carbon available due to intensive historical soil use and soil transplantation during forest construction, as well as relatively warmer temperatures in urban heat domes. Our observational study also indicates the need for caution in soil management for less CO2 emissions in urban areas. [ABSTRACT FROM AUTHOR]

The roughness sublayer (RSL) is one compartment of the surface layer (SL) where turbulence deviates from Monin–Obukhov similarity theory. As the computing power increases, model grid sizes approach the gray zone of turbulence in the energy-containing range and the lowest model layer is located within the RSL. From this perspective, the RSL has an important implication in atmospheric modeling research. However, it has not been explicitly simulated in atmospheric mesoscale models. This study incorporates the RSL model proposed by Harman and Finnigan (2007, 2008) into the Jiménez et al. (2012) SL scheme. A high-resolution simulation performed with the Weather Research and Forecasting model (WRF) illustrates the impacts of the RSL parameterization on the wind, air temperature, and rainfall simulation in the atmospheric boundary layer. As the roughness parameters vary with the atmospheric stability and vegetative phenology in the RSL model, our RSL implementation reproduces the observed surface wind, particularly over tall canopies in the winter season by reducing the root mean square error (RMSE) from 3.1 to 1.8 m s -1. Moreover, the improvement is relevant to air temperature (from 2.74 to 2.67 K of RMSE) and precipitation (from 140 to 135 mm per month of RMSE). Our findings suggest that the RSL must be properly considered both for better weather and climate simulations and for the application of wind energy and atmospheric dispersion. [ABSTRACT FROM AUTHOR]

Core IdeasIn the proposed model, the wilting point and porosity are a function of organic matter.In organic‐rich soil, the model improves accuracy of the microwave radiative transfer model.The model is applicable for both portable and satellite soil moisture sensors. Most dielectric mixing models have been developed for mineral soils without extensive consideration of organic matter (OM). In addition, when used for in situ measurement, most of these models focus only on the real part of the effective dielectric constant without the corresponding imaginary part. Organic matter fractions in soils are found globally (57%), with an especially significant amount in the boreal region (17%). Without proper consideration of OM in dielectric mixing models and subsequent microwave radiative transfer modeling, brightness temperature (TB) calculations may be erroneous. This would lead to uncertainties in the estimation of higher level products, such as soil moisture retrievals from portable soil moisture sensors (e.g., time‐domain reflectometers) or passive microwave sensors onboard the Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Advanced Microwave Scanning Radiometer (AMSR2) satellites. We incorporated OM into a dielectric mixing model by adjusting the wilting point and porosity according to the OM content, i.e., the effective soil dielectric constant decreases with higher OM due to a decrease in the fraction of free water and an increase in bound water. With the proposed soil parameters in the dielectric mixing model, high levels of OM increase the TB for a specific soil moisture by decreasing the microwave effective dielectric constant. The simulated TB better reproduced SMAP‐observed TB (11% in RMSE) through the improvement of the effective dielectric constant (40% reduction in RMSE). We anticipate that the application of our approach can improve microwave‐based surface soil moisture retrievals in areas with high OM. [ABSTRACT FROM AUTHOR]

In this study, the performance of wind forecasts over Svalbard, located between the Arctic Ocean and the Norwegian Sea, was evaluated using the Polar Weather Research and Forecasting (PWRF) model and three-dimensional variational data assimilation (DA) system. The forecasts of the analysis–forecast cycling experiment using the PWRF 3DVAR were compared with those of the cold start experiment using reanalysis as the initial condition. Three strong wind cases that occurred during January and February 2011–2012 were selected, where polar lows were generated on the east coast of Greenland and generated a wind speed above 20 m s−1 in Svalbard. The wind speed forecasts for both cycling and cold start experiments were similar to the highest 10-minute average wind speed for the last 1 hour (HAW). The average root mean square error (RMSE) of the forecasts in the cold start experiment from HAW was 3.78 m s−1 for three cases and was greater than that in the cycling experiment. The forecast performance in the cycling experiment was comparable to, or even better than, that in the cold start experiment, which implies that the cycling system with DA is more useful than the cold start system in forecasting polar weather to support research activities. [ABSTRACT FROM AUTHOR]

Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9 km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3 ppmv for 16 and 9 km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16 km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of -19.2 (16 km), -16.7 (9 km), and -20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO = dCO2 = 9 ppbv ppmv-1) compared to theWest Sea (dCO=dCO2 = 28 ppbv ppmv-1). This "combustion signature contrast" is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8-12 ppbv ppmv-1, the West Sea: ~30 ppbv ppmv-1) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64-0.90, the West Sea: ~0:80) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO2 variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO2 concentrations at the surface with steeper vertical gradients (~0:4 ppmv hPa-1 for CO2 and 3.5 ppbv hPa-1 for CO) in the morning samples than observed (0:25 ppmv hPa-1 for CO2 and 1.7 ppbv hPa-1 for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9 km vs. 16 km) generally produces better forecasts. [ABSTRACT FROM AUTHOR]

For regional weather forecasts and climate predictions, it is important to determine the optimal domain size, location, and top height. A wide model domain can be chosen to avoid noises from lateral boundaries but this can include the Tibetan Plateau and areas of northern Manchuria to the Kamchatka Peninsula in Northeast Asia. This study shows that topographic regions around the Tibetan Plateau and warm pool areas over the Manchuria in an extended model domain may have harmful effects on the accuracy of short‐ to medium‐range regional predictions on the downwind side in spring. The inaccuracy is related to model errors due to steep terrain regions in the Tibetan Plateau and cold bias in the lower stratosphere north of Manchuria. Well‐designed spectral nudging over the eastern flank of the Tibetan Plateau and the use of a higher model top are found to improve regional predictions for Northeast Asia in spring by effectively eliminating errors associated with steep topography and temperature biases in the upper troposphere and lower stratosphere, respectively. Our findings suggest possible ways to mitigate biases due to steep mountains and upper‐level processes in regional modeling. We discuss the role of our method in terms of uncertainties in regional weather forecasts and climate predictions. [ABSTRACT FROM AUTHOR]

Improvement of fog simulation accuracy was investigated for the fogs that occurred on the south coast of the Korean Peninsula using the WRF (3D) and PAFOG (1D) coupled model. In total, 22 fog cases were simulated and accuracy of the fog simulation was examined based on Critical Success Index, Hit Rate and False Alarm Rate. The performance of the coupled WRF-PAFOG model was better than that of the single WRF model as expected. However, much more significant improvement appeared only when the data from a 300 m meteorological tower was not only used for the initial conditions but also nudged during the simulation. Moreover, a proper prescription of soil moisture was found to be important for accurate fog simulation especially for the fog cases with prior precipitation since efficient moisture supply from the precipitation-soaked soil might have been critical for fog formation. It was also demonstrated that with such optimal coupled model setting, a coastal radiation fog event with prior precipitation could be very realistically simulated: the fog onset and dissipation times matched so well with observation. In detail, radiative cooling at the surface was critical to form a surface inversion layer as the night fell. Then the vapor flux from the precipitation-soaked surface was confined within the inversion layer to form fog. It is suggested that a proper prescription of soil moisture in the model based on observations, if readily available, could be a cost-effective method for improving operational fog forecasting, considering the fact that tall meteorological towers are a rarity in the world. [ABSTRACT FROM AUTHOR]

Urban heat island (UHI), an iconic consequence of anthropogenic activities and climate condition, affects air pollution, energy use, and health. Therefore, better understanding of the temporal dynamics of UHI is required for sustainable urban planning to mitigate air pollution under a changing climate. Here, we present the evolution of UHI intensity (UHIi) and its controlling factors in the Seoul metropolitan area, Korea, over the last 56 years (1962–2017), which has experienced unique compressed economic growth and urban transformation under monsoon climate. The analysis demonstrated an inverted U-shape long-term variation of UHIi with the progress of urban transformation and economic climate which has not been reported in Asian cities before. Meanwhile, short-term variations in UHIi are related to both diurnal temperature range and duration after rainfall event unlike previous studies, and the UHIi was exacerbated by heat waves. Our findings suggest that the UHIi will exhibit different temporal dynamics with future changes in the monsoon climate, and heat waves in the urban area will be reinforced if current rapid urbanization continues without a shift toward sustainable and equitable development. Asian cities that are likely to face the similar urbanization trajectory and the implications are that urban (re)development strategy considers changes in rainfall magnitude and timing due to monsoon system variation under changing climate and plans to mitigate synergy between heat wave and UHI in this area. Rises and falls of urban heat island intensity (UHIi) with urbanization in Seoul over the last 56 years (1962–2017). Image 1 • This is the first study to report decrease of UHIi in Asian cities. • The complex relationships of urban climates, urban management, economy, weather. • Such decrease is closely related to change in urbanization management and economy. • Heatwave is reinforced by global warming in Seoul. • Rainfall duration controls UHIi that is important in cities under monsoon climate. [ABSTRACT FROM AUTHOR]

Background: It is important to quantify changes in CO2 sources and sinks with land use and land cover change. In the last several decades, carbon sources and sinks in East Asia have been altered by intensive land cover changes due to rapid economic growth and related urbanization. To understand impact of urbanization on carbon cycle in the monsoon Asia, we analyze net CO2 exchanges for various land cover types across an urbanization gradient in Korea covering high-rise high-density residential, suburban, cropland, and subtropical forest areas. Results: Our analysis demonstrates that the urban residential and suburban areas are constant CO2 sources throughout the year (2.75 and 1.02 kg C m−2 year−1 at the urban and suburban sites), and the net CO2 emission indicate impacts of urban vegetation that responds to the seasonal progression of the monsoon. However, the total random uncertainties of measurement are much larger in the urban and suburban areas than at the nonurban sites, which can make it challenging to obtain accurate urban flux measurements. The cropland and forest sites are strong carbon sinks because of a double-cropping system and favorable climate conditions during the study period, respectively (− 0.73 and − 0.60 kg C m−2 year−1 at the cropland and forest sites, respectively). The urban area of high population density (15,000 persons km−2) shows a relatively weak CO2 emission rate per capita (0.7 t CO2 year−1 person−1), especially in winter because of a district heating system and smaller traffic volume. The suburban area shows larger net CO2 emissions per capita (4.9 t CO2 year−1 person−1) because of a high traffic volume, despite a smaller building fraction and population density (770 persons km−2). Conclusions: We show that in situ flux observation is challenging because of its larger random uncertainty and this larger uncertainty should be carefully considered in urban studies. Our findings indicate the important role of urban vegetation in the carbon balance and its interaction with the monsoon activity in East Asia. Urban planning in the monsoon Asia must consider interaction on change in the monsoon activity and urban structure and function for sustainable city in a changing climate. [ABSTRACT FROM AUTHOR]

Arctic tundra is undergoing a rapid transition due to global warming and will be exposed to snow-free conditions for longer periods under projected climate scenarios. Regional climate modeling is useful for understanding and predicting climate change in the Arctic tundra, however, the lack of in-situ observations of surface energy fluxes and the planetary boundary layer (PBL) structure hinders accurate predictions of local and regional climate around the Arctic. In this study, we investigate the performance of the Polar-optimized version of the Weather Research and Forecasting model (PWRF) in the Arctic tundra on clear days in summer. Based on simultaneous observations of surface fluxes and the PBL structure in Cambridge Bay, Nunavut, Canada, our validation shows that the PWRF simulates a drier environment, leading to a larger Bowen ratio and a warmer atmosphere compared to observations. Further sensitivity analyses indicate that the model biases are mainly from the uncertainties in physical parameters such as surface albedo and emissivity, the solar constant, and the model top height, rather than structural flaws in the model physics. Importantly, the PWRF reproduces the observations more accurately when the observed soil moisture is fed into the simulation. This indicates that there must be improvements in simulations of the land-atmosphere interaction at the Arctic tundra, not only in the accuracy of the initial soil moisture conditions but also in soil hydraulic properties and drainage processes. The mixing diagram analysis also shows that the entrainment process between the PBL and the overlying atmosphere needs to be improved for better weather and climate simulation. Our findings shed light on modeling studies in the Arctic region by disentangling the model error sources from uncertainties by parameters and physics package options. • Arctic tundra is exposed to warmer conditions with a warming global climate. • Polar WRF has bias in simulating climate near the surface on clear summer days. • Polar WRF reproduces the observations accurately with the observed soil moisture. • Regional climate simulation improves with proper numerical design over the Arctic. [ABSTRACT FROM AUTHOR]

To understand the characteristics of air quality in the Seoul Metropolitan Area, intensive measurements were conducted under the Korea-United States Air Quality (KORUS-AQ) campaign. Trace gases such as O 3 , NO x , NO y , SO 2 , CO, and volatile organic compounds (VOCs), photochemical byproducts such as H 2 O 2 and HCHO, aerosol species, and meteorological variables including planetary boundary layer height were simultaneously measured at Olympic Park in Seoul. During the measurement period, high O 3 episodes that exceeded the 90 ppbv hourly maximum occurred on 14 days under four distinct synoptic meteorological conditions. Furthermore, local circulation such as land-sea breeze and diurnal evolution of the boundary layer were crucial in determining the concentrations of precursor gases, including NO x and VOC as well as O 3 . During such episodes, the nighttime NO x and VOC and daytime UV levels were higher compared to non-episode days. The overall precursor levels and photochemical activity were represented fairly well by variations in the HCHO, which peaked in the morning during the high O 3 episodes. This study revealed that toluene was the most abundant VOC in Seoul, and its concentration increased greatly with NO x due to the large local influence under stagnant conditions. When O 3 was highly elevated concurrently with PM 2.5 under dominant westerlies, NO x and VOCs were relatively lower and CO was noticeably higher than in other episodes. Additionally, the O 3 production efficiency was the highest due to a low NO x with the highest NO z /NO y ratio among the four episodes. When westerlies were dominant in transport-south episode, the nighttime concentration of O 3 remained as high as 40~50 ppbv due to the minimum level of NO x titration. Overall, the Seoul Metropolitan Area is at NO x -saturated and VOC-limited conditions, which was diagnosed by indicator species and VOC/NO x ratios., Competing Interests: Competing interests The authors have no competing interests to declare.