Asia-Pacific Journal of Atmospheric Sciences最新文献

The microphysical properties of ice pellets (IP) are analyzed, and associated relevant thermodynamic conditions are investigated using rawinsonde soundings and model reanalysis data in the Yeongdong region of Korea. During the intensive observation campaign of snowfall, two distinctive IP events of 1 March 2021 (IP1) and 15 March 2018 (IP2) were observed when strong cold advection was prevalent below about 2 km as accompanied by distinctive inversion strength (4.7 ~ 9.3 ℃) above the cold layers. Cold air intrusion along the eastern side of Taebaek mountains appeared to abruptly decrease low level (850 hPa) temperature up to -4.7 ~ -3.4 ℃, but warmer than 8-year average (-9.5 ℃), respectively. Both episodes had smaller maximum size (1.8 mm in average) of ice pellets with greater fallspeed (4.2 m s⁻¹) in comparison to general snow crystals. Ice pellets occurred in the synoptic condition of the High in the north and the Low passing by the south, which resulted in cold northeasterly over the Yeongdong region. Rawinsonde soundings show a melting layer between 800 and 700 hPa just above the freezing layer of 900 ~ 800 hPa existed, such as a reversed S temperature profile, which is also consistent with the model reanalysis. The IPs’ life time was short within a couple of hours since it occurred along with low-level strong cold advection (IP1) or rapidly-moving squall line (IP2).

We note that the atmosphere has distinct tropical and extratropical regimes. The tropical regime is significantly dependent on the greenhouse effect and is characterized by temperatures that are largely horizontally homogenized. The extratropical regime is dominated by large scale unstable convective eddies that transport heat between the tropics and the poles (leaving the poles warmer than they otherwise would be) and serve to determine the temperature difference between the tropics and the poles. Changes in tropical temperature and in the tropics-to-pole temperature difference both contribute to changes in global mean temperature. It turns out that changes in global mean temperature associated with major climate change (i.e., the last glacial maximum and the warm period of the Eocene about 50 million years ago) were associated primarily with changes in the tropics-to-pole temperature differences. By contrast, changes in global mean temperature over the past 150 years or so are almost entirely associated with changes in tropical temperature. Thus, there is no intrinsic amplification associated with a change in the tropics-to-pole temperature difference. However, model simulations of climate behave differently from both observations and from each other. In particular, they all show more significant contributions for the tropics-to-pole temperature difference – sometimes much more significant. They also show excessive tropical warming.

The most frequent and concentrated rainfall in the pre-flood season in South China usually occurs around the Dragon Boat Festival every year, locally known as ‘Dragon-boat Rainfall (DBR)’. In 2022, a record-breaking DBR attacked South China, causing disastrous flooding. We suggest that this extreme DBR was jointly regulated by the tropical convective forcing and Tibetan Plateau (TP) heating. Distinctly strong low-level southwesterlies and ascending motions over South China were the key atmospheric conditions. And the abnormal low-level southwesterlies were contributed by both the anomalous anticyclone over the western North Pacific and the anomalous westerlies at the southern side of the TP. On the one hand, during the period of 2022 DBR, stronger-than-normal convective forcing over the Maritime Continent induced the low-level anomalous anticyclone over the western North Pacific through triggering the meridional vertical circulation and further promoted the upward motions over South China. On the other hand, positive diabatic heating over the TP forced abnormal warm anticyclone in the mid-upper troposphere, more warm air advected downstream by the background westerlies, intensifying the upward motions over South China. Meanwhile, the TP heating could induce the anomalous low-level westerlies at the southern side of the TP, which further merged into and intensified the southwesterlies over South China and greatly enhanced the moisture transport and convergence there. Therefore, we highlight the strong thermal forcing over the TP, exerting a combined and amplified effect with the convective forcing over the Maritime Continent, dominated the record-breaking DBR in 2022.

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.