Asia-Pacific Journal of Atmospheric Sciences最新文献

Many operational forecasting centres of tropical cyclones (TCs) issue a static Cone of Uncertainty (COU) to convey the uncertainty associated with the forecast track. This COU is based on the climatological distribution of forecast position errors. The uncertainty information from an ensemble prediction system can help in producing a dynamic COU. The objective of the present work is to build a dynamic COU using multiple member forecasts from India’s National Centre for Medium Range Weather Forecasting (NCMRWF) Global Ensemble Prediction System (NEPS-G), where the radius at each forecast is determined such that it includes 67% of the ensemble members. This dynamic COU is then compared against a static COU constructed using the fixed radii prescribed by the India Meteorological Department (IMD), which are derived from climatological forecast position errors of previous years. All TCs for the period 2019–2021 over the North Indian Ocean (NIO) have been considered in the present study. At shorter lead times (till 18 h), static probability circles are too small to capture most of the best tracks. The dynamic circles show higher detection rate than the static circles till at least 72 h forecast lead time. The static circles outperform the dynamic circles at longer lead times due to large errors in ensemble mean and inadequate ensemble spread. The dynamic circles, over both Bay of Bengal (BoB) and Arabian Sea (AS), perform better till 72-h lead time for the straight and recurving TCs. At longer lead times (84-h onwards), for BOB cyclones, static circles perform better but for AS cyclones, dynamic circles are slightly more effective. For storms with severe cyclonic and higher intensity, dynamic circles are more effective during 18 to 72-h forecasts. During the post-monsoon season for all lead times (except 120-h) best tracks lie within dynamic circles more often than static circles.

Monthly characteristics of temperature lapse rate (TLR) or gradient with latitude (TLR_Lat), longitude (TLR_Lon), and elevations (TLR_E) in Bangladesh were analyzed using 31 years (1980–2010) of monthly climate data from 28 stations, employing linear and multicollinearity models. TLR_Lat is shallower in the summer and steeper in winter, whereas TLR_Lon shows the opposite trend. Diurnal TLR_R monthly variations peak during the pre-monsoon season and are at their lowest during the monsoon months, aligning with synoptic weather patterns and variations in moisture, rainfall, cloud cover, pressure, and wind speed. Moisture-related variables (e_s LR, e LR, and Δe LR) positively correlate with TLRs, while R LR, P LR, W_s LR (excluding TLR_Lon), and C_c LR correlate inversely. Summer’s TLR_Lat and TLR_Lon changes are driven by the southwest monsoon, causing increased rainfall and cloud cover in the southern and eastern regions. The effects of orographic rainfall further steepen the TLR_Lon value in summer. In winter, steep TLR_Lat and shallow TLR_Lon are associated with cold, dry, westerly winds, reduced rainfall, and clear skies in the northern parts. Pre-monsoon months’ TLRs exhibit steep gradients, especially in longitude, attributed to disturbances, high humidity, and frequent thunderstorms in the northeast. Post-monsoon TLR_Lon and TLR_Lat are less pronounced than pre-monsoon due to decreased rainfall and reduced thermal forcing. Diurnal patterns exhibit shallower TLRs with latitude and elevation during the day, attributed to high humidity, cloud cover, and weak adiabatic mixing. The largest diurnal range occurs during the pre-monsoon months, influenced by high sensible heat flux, radiative cooling, and frequent thunderstorms, with the smallest range occurring in summer due to elevated moisture levels, monsoon rains, high latent heat flux, and dense cloud cover. These results offer valuable insights into thermal dynamics, in addition to hydroclimatic processes and their relationship to local and regional climate and topography for variation, contributing to future hydroclimatic modeling in this region.

Diagnosing the precipitation forecast biases in numerical weather prediction (NWP) is an important step and method to improve the accuracy of precipitation forecasts.This study utilizes deterministic precipitation forecast data from the ECMWF Integrated Forecasting System (IFS), along with precipitation observations from 2415 meteorological stations in China and ERA5 data, to analyze the characteristics and possible causes of precipitation forecast biases in the IFS over China. Methods include, such as Root Mean Square Error (RMSE), Mean Error (ME), Frequency Bias (FBias), forecast verification scores, and Integrated Water Vapor Transport (IVT) diagnostics. The main conclusions are as follows: (1) The precipitation forecast from the IFS exhibits a significantly high Fbias with a pronounced wet bias. The ME shows larger positive deviations under lower daily average precipitation, transitioning to negative errors as daily precipitation increases. The RMSE of precipitation demonstrates distinct spatiotemporal variations: higher values are observed during summer half-year compared to winter, and in southern regions versus northern areas. The influence of underlying surface topography on RMSE is clearly evident. (2)The RMSE and ME increase with increasing forecast lead time. The RMSE for 1200 UTC precipitation forecasts performs better than for 0000 UTC beyond 48 hours. (3) The Threat Score (TS) and Equitable Threat Score (ETS) scores for summer half-year precipitation forecasts are higher than in the winter half-year, with 1200 UTC initial forecast times being higher than 0000 UTC, indicating that the true forecast capability of 1200 UTC initial forecast times is better than for 0000 UTC. (4) The forecasts initialized at 0000 UTC exhibit overestimated southerly wind components and stronger vertical velocity, with larger standard deviations in both vertical motion and IVT. In contrast, the forecasts initialized at 1200 UTC show amplified easterly wind biases yet demonstrate smaller IVT discrepancies. These systematic differences in dynamical and moisture variables may be important reasons for the differences in precipitation forecasts between the two initialization times.

On May 22, 2020, Qiaotou Meteorological Station in Kaohsiung City of southern Taiwan recorded 415.5 mm of daily rainfall. This heavy rainfall event was driven by the Mei-yu front, a strong and moist southwesterly flow, a mesoscale convective system (MCS), and the complex terrain of southern Taiwan. The study indicates that on May 22, the low-level jet (LLJ) intensified to southwesterly flow strength, rapidly bringing abundant moisture to southwestern Taiwan, resulting in higher equivalent potential temperatures in the lower atmosphere. This study, through observational data analysis and case simulation, found that the first important cause of heavy rainfall in southwestern Taiwan is the presence of a strong southwesterly LLJ in an unstable atmospheric environment, which transports abundant moisture to the land in southwestern Taiwan. At the same time, the lifting mechanisms ahead of the Mei-yu front and low-level convergence over the ocean contribute to the intensification of the MCS. The second factor is Taiwan’s complex terrain effects, which functioned as a barrier to moisture transport and enhanced orographic lifting on the windward side, further intensifying the rainfall when combined with the strong southwesterly flow and MCS. Numerical simulations show that under the influence of complex terrain, mean precipitation over the southern section of Taiwan’s Central Mountain Range increases from north to south as elevation decreases, the average precipitation gradually decreases when the terrain is below 1100 m. For mountains between 2000 and 2500 m, maximum precipitation occurs on the windward slopes or in front of mountains, while rainfall and moisture sharply decrease on the leeward side. For elevations between 1000 and 1500 m, mean precipitation on the windward slopes increases, with the peak shifting closer to the mountain tops. Below 1000 m, mean precipitation decreases but aligns with the terrain, with the maximum near the peaks. At elevations below 600 m, leeward mean precipitation was above average.

Convective boundary layer height (CBLH) is an essential parameter of the boundary layer climatology, which is associated with the intensity of turbulence mixing. Radiosonde data derived from the "Sino-Japanese Center for Cooperation on Meteorological Disasters" (JICA) during three intensive observation periods in 2008 in Gerze (32.17°N, 84.03°E) were used to verify the applicability of ERA5 reanalysis data in the Tibetan Plateau (TP). Thus, the spatiotemporal variations in the CBLH (boundary layer height from 08:00 to 20:00) and the contributions of the influencing factors during different monsoon seasons in various regions of the TP were investigated using the ERA5 data (1983–2022). The results indicate that variable characteristics in the CBLH derived from radiosonde data are basically consistent with that from ERA5 during the three observation periods. The monthly-averaged CBLH showed only one peak in the eastern region during the full development of the CBL (14:00–18:00), while two peaks were shown in the western region. The CBLH over the TP exhibited a decreasing trend during the monsoon period while the CBLH in the eastern region showed an increasing trend during the post-monsoon period. Wind speed at 10 m height was a key factor influencing the CBLH during the non-monsoon period, while surface sensible heat flux considerably influenced variations in the CBLH during the monsoon period.

September is widely considered to be the final month of the monsoon season on the Indian subcontinent. Precipitation levels during this month exert a pivotal influence on the duration of monsoon rainfall, with the potential to substantially impact subsequent dry spells in the region. Consequently, further investigation into the variations in September rainfall is imperative for ensuring social and agricultural security. This study, therefore, examined the possible role of the South Asian high (SAH) modulating Indian rainfall in September. The study found that the SAH was generally stable around South Asia in September, prior to its retreat over the ocean. The SAH was found to be weaker and shifted in a southeastward direction in September compared to its summer mean. A strong SAH in September was often concomitant with a delayed withdrawal of Indian summer monsoon (ISM) rainfall and vice versa, with positive rainfall anomalies primarily manifesting over central-northeastern, west-central, and peninsular India. The enhanced SAH was accompanied by stronger westerly and easterly jet streams, respectively, over the southern Caspian Sea and northwest India in the upper troposphere. A notable upper-tropospheric anticyclonic circulation has been observed over the western Tibetan Plateau. Additionally, a significant lower-tropospheric cyclonic circulation has been observed over India, accompanied by an enhanced Somali cross-equatorial flow. The associated anomalous westerly anomaly over southern India and southeasterly anomaly over northern India can transport abundant moisture over most of India. Consequently, there is a tendency for substantial rainfall tends to occur in conjunction with an enhanced SAH.

Convectively induced turbulence (CIT) is a severe aviation hazard. It is challenging to forecast CIT because low-resolution models cannot explicitly resolve convective motions at kilometer scales. In this study, we used the Model for Prediction Across Scales (MPAS) to simulate CIT cases with convection-permitting resolution ((sim )1 km) in the region of the CIT events and coarse resolution in other parts of the globe. We developed a method to estimate the eddy dissipation rate (EDR) using the resolved wind field of the MPAS simulations. The method is based on explicit filtering and reconstruction in the turbulence modeling for large-eddy simulations (LES). It estimates turbulence kinetic energy (TKE), which is then used to derive EDR. The new method produces different turbulence distribution and intensity than previous methods based on second-order structure functions and convective gravity wave drag, with higher accuracy and better correlation with observations for CIT cases tested in this study. The 1-km resolution simulation generates more accurate EDR and improves spatial patterns, but it is computationally demanding. The 3-km resolution can get benefits from reasonable accuracy and affordable computational cost. Because convection-permitting resolutions are in the gray zone for simulating convection, we evaluated the sensitivity of the prediction to the variations in physical and numerical schemes. Varying cumulus convection parameterization and monotonicity of numerical schemes are identified as practical approaches to generate beneficial ensemble spread. However, the physical perturbation-based ensemble has limitations, and initial condition perturbations are still necessary to encompass uncertainties in the development of convection.

A new COllaborative Carbon Column Observing Network (COCCON) site has been established in South Korea to monitor greenhouse gases (GHGs) effectively. This study focuses on the calibration of the COCCON observing instrument through precise measurements of the instrumental line shape (ILS) parameters and comparison with TCCON measurements. The COCCON network employs Bruker's EM27/SUN mobile Fourier transform infrared spectrometer (mFTIR), requiring validation against data from high-resolution (HR-FTIR) instruments. To achieve this, we compared data from the mFTIR with Bruker's IFS 125HR HR-FTIR to derive an instrument-specific calibration factor. Two ILS values were obtained by analyzing the water vapor spectrum using the open path (OP) method and the C₂H₂ Gas-filled cell (GFC) spectrum. The ILS measurements indicated a modulation efficiency amplitude (MEA) difference of 0.712% between the GFC and OP methods, with values of (0.982 ± 0.005) and (0.975 ± 0.008), respectively. Notably, a comparison of the XGas values derived from both sets of ILS parameters revealed a high degree of consistency, as indicated by slopes close to 1, suggesting that the choice of ILS parameters had minimal impact on the accuracy of XGas retrieval. In this study, a 0.82% increase in the MEA value led to increases of 0.17% in XCO₂, 0.09% in XCH₄, 0.13% in XCH₄_S5P, and 0.14% in XCO concentrations. Furthermore, seasonal variations were observed in the mFTIR measurements for XCO₂, XCH₄, and XCO. The highest XCO₂ value recorded was 427.82 ± 0.56 ppmv in April 2024, while the lowest monthly average of 415.23 ± 0.58 ppmv was observed in September 2023. The highest XCH₄ concentration was recorded in September 2024 at 1.966 ± 0.021 ppmv, while the lowest occurred in March 2024, with a value of 1.917 ± 0.016 ppmv. The highest XCO concentration was observed in spring, reaching 0.114 ± 0.014 ppmv in March 2024, while the lowest was recorded in fall at 0.102 ± 0.011 ppmv in September 2024. Additionally, the mFTIR measurements were compared to those obtained from HR-FTIR to evaluate the compatibility between the COCCON and TCCON measurement methods. Results indicated a strong correlation between the two measurement techniques, with instrument-specific calibration factors ranging from 0.9884 for XCO to 1.0017 for XH₂O. These results demonstrate that the mFTIR is ready for use in measurements at the COCCON site and for measurement campaigns in South Korea.

Typical snowfall structure over the coastal mountainous region of the Korean Peninsula is investigated. East coast-type snowfall (ET) due to the lake-effect over the East Sea of Korea is dominant for snowfall intensity and duration. The ET can be divided by the high-pressure system over the Gaema Plateau (GH) and the extratropical low-pressure system passing southern part of the Korean Peninsula in addition to the GH pattern (GHSL). Composite analysis showed that the GHSL can allow a greater inflow of the snowfall from the sea into the land than the GH. The key factors for snowfall structure are 1) the wind-turning layer (WTL), which is the transition level from the lower-level easterly to the upper-level westerly; 2) vertical wind shear suppressing updrafts near the WTL and 3) the Froude number (Fr), which determines the snowfall penetration beyond the mountain. A higher WTL height indicates a deeper easterly layer, indicating favorable conditions for inland snowfall penetration. The strong vertical wind shear plays a role of suppressed updrafts near the WTL via downward momentum transport. It is presented that updraft limitation is mostly exerted by the wind shear. Fr indicates whether the weather system is blocked or unblocked by the mountains. It is shown that the larger Fr generally increases with height, which means that snow systems or flows near the mountain tops can easily to overcome the topography. It is shown that both dynamic and thermodynamic factors are important for understanding and predicting the structure and regions of snowfall.

This case study presents a thorough investigation of the environmental setup that led to the hail-producing severe storm that impacted the municipality of Norzagaray and City of San Jose Del Monte, including other nearby areas, in the province of Bulacan on the afternoon of August 13, 2021. During this period, 2–5 cm and potentially as large as ~8 cm diameter hail was reported over these locations of Bulacan. For this purpose, the combination of HIMAWARI-8 AHI, PLDN and its flash counts, and meteorological indices; synoptic, thermodynamic, and kinematic indices, calculated from the ERA5 reanalysis are utilized to understand the nature of the hail event. In the morning, the pre-convective environment was comprised by a warm inversion layer that inhibited storm initiation, until the arrival of ample moisture and convective heating in the afternoon. By the afternoon, model sounding analysis revealed that the environment transitioned into uncapped profile with steep low-level lapse rate owing to warm, moist south-westerly wind flow from the Manila Bay in the lower troposphere and north-easterlies aloft crossing the SMMR induced by a weak low-pressure system located in the eastern Philippine Sea, with minimal turning on the wind profile. This promoted low-level convergence within the area of interest and build up of instability. The updraft associated with convectively unstable atmosphere, sufficient cloud-layer bulk shear, and storm nudging at its maturing phase countered entrainment-driven dilution and aided the growth of ice crystals by rapid collection of supercooled cloud liquid particles, which ultimately led to formation of hailstones.