Asia-Pacific Journal of Atmospheric Sciences最新文献

Snow plays a vital role in the interaction between land and atmosphere in the state-of-the-art land surface models (LSMs) and the real world. While snow plays a crucial role as a boundary condition in meteorological applications and serves as a vital water resource in certain regions, the acquisition of its observational data poses significant challenges. An effective alternative lies in utilizing simulation data generated by Land Surface Models (LSMs), which accurately calculate the snow-related physical processes. The LSMs show significant differences in the complexities of the snow parameterizations in terms of variables and processes considered. In this regard, the synthetic intercomparisons of the snow physics in the LSMs can give insight for further improvement of each LSM. This study revealed and discussed the differences in the parameterizations among LSMs related to snow cover fraction, albedo, and snow density. We selected the most popular and well-documented LSMs embedded in the earth system models or operational forecasting systems. We examined single-layer schemes, including the Unified Noah Land Surface Model (Noah LSM), the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL), the Biosphere-Atmosphere Transfer Scheme (BATS), the Canadian Land Surface Scheme (CLASS), the University of Torino land surface Process Interaction model in Atmosphere (UTOPIA), and multilayer schemes of intermediate complexity including the Community Noah Land Surface Model with Multi-Parameterization Options (Noah-MP), the Community Land Model version 5 (CLM5), the Joint UK Land Environment Simulator (JULES), and the Interaction Soil-Biosphere-Atmosphere (ISBA). Through the comparison analysis, we emphasized that inclusion of geomorphic and vegetation-related variables such as elevation, slope, time-varying roughness length, and vegetation indexes as well as optimized parameters for specific regions, in the snow-related physical processes, are crucial for further improvement of the LSMs.

Fifteen GCMs in the Coupled Model Intercomparison Project Phase 6 are evaluated for the skill in simulating the atmospheric river (AR) frequency (F_AR) and integrated vapor transport (IVT) during 1995–2014. All GCMs simulate well the annual and seasonal climatology of F_AR and IVT for both the global and East Asia domains. Large biases in F_AR and IVT occur in the same regions characterized by high AR activities including the midlatitude Pacific and Atlantic oceans, the Southern Ocean, and the tropical region from the eastern Indian Ocean to the western Pacific. The sign and magnitude of large model errors vary across the GCMs to result in small model-mean biases. The seasonal variation of the skill of individual GCMs is smaller than the variation of the skill across the GCMs, implying that the model skill varies more widely by the difference in model formulations than the response of individual GCMs to seasonal forcing variations. A novel method to relate the skill for simulating F_AR and IVT to that for winds and water vapor is introduced. The method shows that the vertical integration of the covariance of wind and water vapor in the definition of IVT can be well approximated by the multiplication of two separate functions obtained by vertically integrating either winds or water vapor, especially in the regions of strong AR activities. Spearman’s rank correlation in conjunction with this method suggests that the model skill for F_AR and IVT is significantly related only to that for winds.

Limited observations hinder understanding of turbulent characteristics in mountainous terrain resulting from heating or cooling of slopes, wind, vertical motions, and heat or moisture advection, which disperse aerosols and other pollutants over the region. In this study, the 1290 MHz radar wind profiler data are utilized to compute the boundary layer height (BLH), the refractive index structure constant (C_n²), and the energy dissipation rate (ɛ) over the central Himalayan site for the period of November 2011 to March 2012, from the intense Ganges Valley Aerosol Experiment (GVAX) field measurements. The radar wind profiler (RWP) based estimation of BLH and ɛ is validated against the radiosonde, representing the effectiveness of the datasets for further investigation. The strong seasonal variation of log C_n² and log ɛ, with average values of ≈ -12 m^−2/3 and -2 m² s⁻³, respectively, is associated with the mountain-induced local circulations and stability in the atmospheric boundary layer. The weak stratification during weak flow is found to be responsible for deep mixing, particularly in the nocturnal boundary layer in spring. Furthermore, the level of cloud cover significantly impacts the strength of turbulence, with the highest cloud cover resulting in a substantial increase in log C_n² (approximately -11 m^−2/3) due to intense updraft and downdraft motions compared to clear skies. Additionally, the distribution of aerosol loading across the site, coupled with the behavior of BLH, atmospheric stability, and orographic-induced circulations, implies distinctive seasonal mechanisms for transporting aerosols toward the mountains. This study offers valuable insights into the diurnal and seasonal patterns of turbulent mixing and the mechanisms behind the transport of pollutants through boundary layer processes over the region.

To achieve net-zero carbon emissions by 2050, it is vital to prioritize climate action and monitor the progress of policies with accurate emission estimates. As CO₂ emission estimates can be independently verified using atmospheric CO₂ measurements, the need for optimal CO₂ monitoring networks has increased. This study proposed an experimental method for designing national-scale atmospheric CO₂ monitoring networks. We used gridded data for fossil fuel CO₂ emissions, facilitating the selection of emission grids as potential monitoring sites. First, we determined the appropriate number of CO₂ monitoring sites, which increased in proportion to the magnitude and variability of CO₂ emissions within the region. Subsequently, the emission grids corresponding to the region were arranged in descending order of emissions. Grids were then selected at regular intervals as potential monitoring sites, aligning with the predetermined number of sites. This selection process ensured that monitoring sites were evenly distributed, ranging from areas with high emissions to those with lower emissions. Lastly, as a verification step to assess the suitability of this potential network, a transport model simulating meteorological conditions was employed to evaluate its coverage to detect the influence of CO₂ emissions. This method was applied to South Korea, and 96 candidate monitoring sites were created. The optimal CO₂ monitoring network distributed evenly across South Korea could evaluate variations in CO₂ emissions. The simple monitoring network design method proposed in this study can accelerate the installation of a national CO₂ monitoring network, ultimately enabling the verification of CO₂ emissions and supporting climate policies.

Anomalous surface warming in Korea has been explained by the high-pressure anomaly accompanied by the vertical sinking motion and weakening of westerlies at the exit of the East Asian Jet. The large-scale circulations linked to this high pressure over East Asia are characterized by the low pressure over the Arctic (AC) and the high pressure over Western Europe (WE), East Asia, and the North Pacific (NP). To assess the contribution of these circulation anomalies to the hot summer in Korea, the four nudging experiments (AC, NP, AC + NP, and WE) are applied to the simulations with 50 different initial conditions in July. As a result, the most similar patterns on local and hemispheric scales are found in the AC + NP nudging experiment. However, the near-surface response in the AC + NP is still weak, and its center shifts to the north compared to the observed, which is induced by the weaker diabatic contribution for the downward motion in the nudging experiment. Using the quasi-geostrophic omega equation, we find that the simulated radiative feedback process is not sufficient to build up the large-scale subsidence with the short nudging period. Despite this limitation, AC + NP well simulates the coherent sinking motion and high-pressure system near Korea by the vorticity advection associated with the upper-level westerlies. It implies that the contribution of the North Pacific circulation (a downstream region) should also be considered to reasonably simulate the East Asia surface warming along with those in the upstream regions.

This study proposes a new approach to defining and analyzing the urbanization effects of temperature over South Korea. While the conventional method of distinguishing between urban and rural stations relies on population criteria, this study has developed an approach to differentiate between urban and rural stations by considering the proportion of natural environments and artificial objects surrounding each station. The long-term temperature changes exhibit a statistically more significant relationship with the proportion of artificial objects compared to the population size, and the new method provides a clearer distinction between urban and rural stations. In addition, based on the categorized stations, an urbanization contribution index (UCI) is calculated to quantitatively compare temperature changes between urban and rural stations. As a result, it is confirmed that the method based on the ratio of artificial features better captures the urbanization effect of temperature compared to the population-based method. In particular, the urbanization effect is found to be more pronounced during nighttime, with the largest difference between urban and rural stations observed in the daily minimum temperature. The new method effectively captures the thermal attributes of urban and rural stations, with a stronger emphasis on nocturnal differentiations. This study emphasizes the importance of considering the surrounding environments rather than population alone to accurately understand the urbanization effects.

The aim of this study was to identify the sources of atmospheric pollutants in densely populated urban areas from a particle toxicity perspective. To this end, the Positive Matrix Factorization (PMF) model and vehicle flux analysis were used to identify the sources of atmospheric pollutants in an urban area based on the measured compounds and wind speed at the receptor site. Moreover, the toxicity of each emission source was compared with the dithiothreitol-oxidation potential normalized to 9,10-Phenanthrenequinone (QDTT-OP) analysis using the PMF source apportionment results. The study found that the dominant sources of atmospheric pollutants in the urban area examined were secondary product (43.7%), resuspended dust (25.4%), and vehicle emissions (14.4%). The vehicle flux analysis demonstrated that reducing the number of vehicles could directly reduce urban atmospheric pollutants. By comparing the time series of PMF source profiles with QDTT-OP, the QDTT-OP analysis showed an r² value of 0.9, thus indicating a strong correlation with biomass burning as the most harmful source of PM_2.5 based on emission sources. Overall, this study is expected to provide valuable guidance for managing atmospheric pollutants in densely populated urban areas, and the findings could serve as a helpful resource for improving urban air quality in the future.

Compound wind and precipitation extremes (CWPEs) are severe weather events that can have significant impacts on human health, ecological systems, and socioeconomic factors. Compared to isolated extreme events, CWPEs can result in higher economic losses and casualties. This study evaluates the ability of EC-Earth3, the sixth phase of the Coupled Model Intercomparison Project (CMIP6), to capture CWPEs by using ERA5 reanalysis as a reference dataset for model evaluation. Additionally, this study examines changes in CWPEs in the future, considering different Shared Socioeconomic Pathway (SSP) scenarios, including SSP1-2.6, SSP2-4.5, and SSP5-8.5. Our analysis indicates that EC-Earth3 accurately captures the spatial and temporal characteristics of global CWPEs during the historical period of 1979-2014. More CWPEs occur in the northern and southern hemispheres during their respective cold seasons, especially for the oceans. The frequency of CWPEs has increased over the historical period, with a greater increasing trend in the ocean than on land. The seasonal cycle of CWPEs differs significantly in land and ocean. Regarding future projections, the occurrence of CWPEs will change significantly with the increase of emissions, particularly in the late 21st century and over high latitudes. CWPEs will increase significantly at mid- and high-latitude regions and mainly decrease over low latitudes. The feature of more CWPEs occurring during the respective cold seasons will be more pronounced in the future.

The variability of the South Java Current (SJC) was observed by using reanalysis data spanning the years 1993 to 2021. This was done in order to determine whether or not the SJC was more influenced by the Indian Ocean Dipole (IOD), the El Niño-Southern Oscillation (ENSO), or a combination of the two. Employing empirical orthogonal function (EOF) analyses, we were able to determine that the time series of the principal component in the first mode (PC1) had an association with one of these occurrences. During the northwest monsoon in December, January, and February (DJF), it would appear that the IOD has a greater impact on the SJC than ENSO does, with a correlation of more than 0.8. During the first transition, which occurs in March, April, and May (MAM), the time series PC1 demonstrates that the SJC has a greater association with the ENSO (coefficient correlation more than 0.7). The study demonstrates that the PC1 has a negative association with both the IOD and the ENSO during the months of JJA, with a coefficient value less than 0.4. The JJA's SJC, however, is positively influenced by the coastal Kelvin wave in the vicinity of western Sumatra and southern Java. Moreover, the magnitude of the SJC, which was observed in DJF months, is affected by the Rossby wave that is moving in a westward direction south of 9˚S.