Asia-Pacific Journal of Atmospheric Sciences最新文献

The formation mechanisms of the record-breaking rainfall event during the Dragon Boat Rainy Season (DBRS) of 2022 are comprehensively analyzed from the synoptic scale and the mesoscale perspectives. The extreme rainfall event is characterized by the highest rainfall amount since 1981, and an abnormal spatial distribution with much higher (lower) rainfall amount in the northern (southern) part of South China. The abnormal circulation and thermodynamic conditions are mainly responsible for the extreme rainfall. The favorite synoptic condition for rainfall is the combination of warm advection, frontal forcing, orographic lifting and low-level jet favor the convection development. The similar configurations repeatedly impact South China during the DBRS of 2022, causing multiple heavy rainfall events, leading to the extreme rainfall of the whole period. The abnormal moisture convergence together with the frontal zone, which is stronger than the climatology, results in the rainfall centers over the northern part of South China. 54.35% of the rainfall amount is related to mesoscale convective systems (MCSs) which mainly originate from four regions. The MCSs from the four regions are characterized by different formation peaks, spatial scales, lifetimes and propagations. The large-scale warm and moist air mass, the moistening caused by synoptic advection and the local diabatic heating are responsible for the increasing instability for the MCSs. The low-level jets play an important role in the formation of MCSs by providing moisture. The thermodynamic (dynamic) environmental conditions control the formation of MCSs in the afternoon (night).

This study investigates the multiscale variability of rainfall over eastern Taiwan during October–November, focusing on the companion effect of tropical cyclone (TC) activity in the South China Sea (SCS) and northeasterly monsoon flow. The interannual variation of autumn rainfall is significantly influenced by the ENSO Phase. During La Niña years, the moisture transport from the SCS-Philippine Sea to eastern Taiwan is enhanced by the anomalous southeasterly winds owing to the cyclonic flow over the SCS. The response of autumn rainfall to ENSO is contributed by intraseasonal variability and the associated TC activity in SCS. During La Niña years, the Madden–Julian Oscillation (MJO) convective areas during phases 4–7 shift into the SCS-Philippine Sea, and the quasi bi-weekly oscillation (QBWO) convective activity is enhanced around the north of Luzon Island. We categorize TCs moving westward into or forming within the SCS into the groups causing significant rainfall in eastern Taiwan or not (the rainfall and non-rainfall groups). The rainfall group predominantly occurs during La Niña years in MJO phases 5. Both groups have similar average TC intensities, but the rainfall group’s path and the associated cyclonic circulation are placed more northward. Both groups of TCs coincide with QBWO’s cyclonic circulation, but the cyclonic circulation associated with the rainfall group stretched from the SCS to the Ryukyu Islands, favoring the moisture transport from the Philippine Sea to eastern Taiwan. We concluded that, excluding direct TC influences, the most favorable conditions for heavy rainfall in eastern Taiwan in Autumn are La Niña years during MJO phases 4–5, when the coinciding of TCs with appropriately structured QBWOs passing through the Bashi Channel or the Northern Philippines into the SCS. A regression model is developed based on the diagnostics in this study using vertically integrated moisture transport and divergence from 1000–700 hPa, which provide the basis of the storyline approach to estimate autumn rainfall over eastern Taiwan from the future projection of global climate models.

Meteorological disasters pose a serious threat to the State Grid Corporation of China, which covers ~ 88% of Chinese national territory. Of these, strong winds deserve a special attention, as they often induce windage yaw discharge of transmission lines and even toppling of transmission towers, resulting in serious economic losses. On 28 June 2023, a severe tripping incident of transmission line appears in Eastern Inner Mongolia due to strong winds. In this study, we conduct comprehensive analyses to clarify the favorable background conditions and governing mechanisms for producing the strong winds. Main results are shown as follows. Synoptic analysis indicates that, the favorable background environments for the event are characterized by a strong upper-level jet associated upper tropospheric divergence; an intense middle-level warm advection ahead of a shortwave trough; and a long-lived lower-tropospheric mesoscale vortex. The strong winds that cause the tripping incident mainly occur in the southeastern quadrant of the vortex. Vorticity budget presents that the period from the mesoscale-vortex’s formation to 4 h before is crucial to the mesoscale vortex, as cyclonic vorticity increases rapidly mainly due to the lower-level convergence-related vertical stretching. In contrast, the horizontal transport mainly results in a net export of cyclonic vorticity, which is the most detrimental factor. Kinetic energy (KE) budget shows that, after the mesoscale vortex forms, the strong winds within its southeastern quadrant enhance rapidly. Overall, the positive work done by the pressure gradient force associated with the mesoscale vortex dominates the enhancement of strong winds; the horizontal transport of KE is the second dominant factor, and the vertical transport of KE (i.e., the downward momentum transportation) shows the least contribution.

The elevated occurrence rate of wind shear (WS) events near airport runways presents one of the major hazards to the safe and efficient operation of landing and takeoff procedures. As a consequence of this, aircraft are more likely to experience the possibility of losing control or encountering hindrances. Hence, it is crucial to assess the factors influencing wind shear occurrence. Previous studies extensively reported the susceptibility of the runways at Hong Kong International Airport (HKIA) to significant wind shear events. Therefore, in order to estimate WS magnitude near runways at HKIA and assess various contributing factors, this study presents a novel Local Cascade Ensemble (LCE) model with its hyperparameters optimized via a Tree-Structured Parzen Estimator (TPE) to estimate the wind shear magnitude. The pilot report data obtained from HKIA between 2017 and 2021 was employed for the training and evaluation of the TPE-tuned LCE model. The outcomes of the TPE-tuned LCE model were also compared to those of other contemporary machine learning (ML) models. The findings indicated that the TPE-tuned LCE model exhibited better predictive performance in comparison to other models, as assessed by a mean absolute error (MAE) of 4.38 knots, a mean squared error (MSE) of 70.28 knots, a root mean squared error (RMSE) of 8.38 knots, and coefficient of determination (R²) value of 0.79. Subsequently, model interpretation via SHapley Additive exPlanations (SHAP) technique was performed on the outcomes of TPE-tuned LCE. It indicated that that certain runways at HKIA, such as runway 07 C, 07 L, 25 C, and 25R, had a higher likelihood of experiencing elevated wind shear conditions within 1000 ft above the runway level.

Western disturbances (WDs) are upper-tropospheric mid-latitude synoptic systems propagating eastward along the subtropical westerly jet stream. They are capable of causing extreme precipitation events and have strengthened their impact over the Karakoram part of the Himalayas in recent decades. They play a crucial role in the sustenance of the “Karakoram Anomaly,” which refers to the anomalous stability/surge of a few Karakoram glaciers in contrast to the other glaciers of the Himalayas. Using the existing WD-catalog derived from ERA5 and MERRA2 reanalysis datasets, we observed that the core genesis zone for Karakoram WDs had undergone a statistically significant shift of ~ 9.7^oE, migrating towards more favourable conditions for cyclogenesis. The study proposes a new parameter to identify regions of potential extratropical cyclogenesis. The shift can be attributed to an enhanced genesis potential, convergence, and higher moisture availability along the WD path. Composite analysis suggests that moisture availability has risen significantly over the shifted zone. Moreover, the propagation speeds of these systems have significantly declined, which explains the recent intensification of precipitation events related to WDs over the Karakoram and hints toward a crucial synoptic influence on the anomalous regional mass-balance phenomenon.

In this study, we propose a new approach to improve the accuracy of the horizontal atmospheric motion vector (AMV) in cloud-free skies and its forecasting. We adapted the optical flow of the convolutional neural network (CNN) framework model using two 10-min interval infrared images at water vapor channels (centered at 6.3, 7.0, and 7.3 (mu m)) from the Korean geostationary satellite GEO-KOMPSAT-2A (GK2A). Since all pixels had seamless AMVs calculated by CNN (CNN AMVs), we could also predict AMVs using the linear regression method. The tracking performance of the CNN-based algorithm was validated using AMVs retrieved from GK2A (GK2A AMVs) by estimating the difference between those values and the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis v5 (ERA5) wind data over Korea in 2022. CNN AMVs showed similar or better root-mean-square vector differences (RMSVDs) than GK2A AMVs (12.33–12.86 vs. 15.89–19.96 m/s). The RMSVDs of the forecasted AMVs were 2.74, 2.95, 3.41, and 4.79 m/s at lead times of 10, 20, 30, and 60 min, respectively. Consequently, our method showed higher accuracy for tracking motion in the production of AMVs and succeeded in forecasting AMVs. We expect that such potential improvements in computational accuracy for operational GK2A AMVs will contribute to increased accuracy when forecasting meteorological phenomena related to wind.

Site adaptation has become a necessary step in resource assessment for ensuring the bankability of a renewable energy project. The process involves collecting short-term observation data to correct the long-term dataset available from the satellite-derived models, which could thus provide a more accurate estimate of the solar resource data. This study aims to enhance the site-adaptation of direct normal irradiance, as its correction remains notably challenging in comparison to global horizontal irradiance due to its larger error, which is often attributed to the complexity of cloud modeling. A new methodology for site-adaptation is proposed that exploits the use of a new indicator variable that describes the correctness of sky-condition classification by the clear-sky index. This variable has dual applications within the context of site adaptation: firstly, it is employed in the two-step binning procedure subsequent to the conventional clear-sky binning during preprocessing, and secondly, it serves as an additional input feature in machine-learning-based site adaptation. The results show that the former method can reduce the mean bias error to a mere 0.4%, while the latter is better for reducing large discrepancies as shown by the lower root mean squared error.

On August 8 and 9, 2022, a record-breaking rain rate of 142 mm h⁻¹, with an accumulated rainfall of more than 500 mm, was observed in the Seoul metropolitan area, Republic of Korea. This study focuses on analyzing the concentration of lightning in southern Seoul, which occurred solely on August 8. It is worth noting that the daily rainfall of August 8 was approximately twice that of August 9 (381 mm on August 8 vs. 198 mm on August 9). The RKSG (located in Yongin, 40 km south of Seoul) Weather Surveillance Radar-1988 Doppler was used to explore the characteristics of cloud microphysics associated with lightning activity. Four major heavy rain periods on August 8 were grouped into three categories of lightning rate (e.g., intense, moderate, and none), and their polarimetric signatures were compared. Significant differences in the vertical distribution of graupel were found within the temperature range of 0 °C and − 20 °C, as indicated by radar reflectivity (Z_H) > 40 dBZ and differential reflectivity (Z_DR) < 0.5 dB. Although graupel was detected in all three categories at the relatively warm temperatures of 0 °C to − 10 °C, its presence extended into colder regions exclusively in the intense category. This observation preceded the appearance of lightning by approximately 6 min. At heights with temperature ≤  − 20 °C, a high concentration of vertically aligned ice crystals was observed in lightning-prone regions, leading to a decrease in differential phase (Φ_DP). In summary, this study provides valuable insights into the microphysical characteristics of thunderstorms and their relationship to lightning activity in the Seoul metropolitan area.

The severe acute respiratory syndrome (SARS-CoV-2), also referred to as COVID-19 originated in the Wuhan city of Hubei Province of China in late December 2019 and spread to more than 200 countries, including many in Southeast Asia. This review has established a close relationship between the spread of coronavirus and air pollution and suggests that the prevailing environmental factors played a role in the spread of infection in the region. The rate of coronavirus transmission significantly declined as effective strategies and measures such as lockdowns, quarantine curfews, and country-wide lockdowns were adopted, eventually resulting in a dramatic improvement in air quality in different South Asian countries. The imposition of the lockdown improved air quality, contributing to lower incidences of COVID-19 infection and fatality rates across the region. Studies conducted by various scientists indicated a significant reduction in the level of air pollutants, especially the particulate matter (PM₁₀, PM_2.5) CO, SO₂, and NO₂ due to stringent restrictions on movement, shutting down of most industries, and halting of commercial and construction activities. However, ozone levels did not show any significant decrease. The results provided by the various agencies clearly suggest that the respiratory spread of infections is directly proportional to the air-quality parameters, and steps taken to decrease the particulate matter and other pollutants can help in containing the infection. The studies can help understand the epidemiology of the disease and thus serve as a useful tool for governments to manage the spread of respiratory infections and help mitigate air pollution and disease spread by adopting staggered lockdowns.