Search Results (7)

The southern slope of the Tianshan Mountains features complex terrain and an arid climate, yet paradoxically experiences frequent extreme precipitation events (EPEs), which pose significant challenges for weather forecasting. This study investigates an EPE that occurred from 20 to 21 August 2019 using multi-source data to examine circulation patterns, mesoscale characteristics, moisture dynamics, and energy-instability mechanisms. The results reveal distinct spatiotemporal variability in precipitation, prompting a two-stage analytical framework: stage 1 (western plains), dominated by localized convective cells, and stage 2 (northeastern mountains), characterized by orographically enhanced precipitation clusters. The event was associated with a “two ridges and one trough” circulation pattern at 500 hPa and a dual-core structure of the South Asian high at 200 hPa. Dynamic forcing stemmed from cyclonic convergence, vertical wind shear, low-level convergence lines, water vapor (WV) transport, and jet-induced upper-level divergence. A stronger vorticity, divergence, and vertical velocity in stage 1 resulted in more intense precipitation. The thermodynamic analysis showed enhanced low-level cold advection in the plains before the event. Sounding data revealed increases in precipitable water and convective available potential energy (CAPE) in both stages. WV tracing showed vertical differences in moisture sources: at 3000 m, ~70% originated from Central Asia via the Caspian and Black Seas; at 5000 m, source and path differences emerged between stages. In stage 1, specific humidity along each vapor track was higher than in stage 2 during the EPE, with a 12 h pre-event enhancement. Both stages featured rapid convective cloud growth, with decreases in total black body temperature (TBB) associated with precipitation intensification. During stage 1, the EPE center aligned with a large TBB gradient at the edge of a cold cloud zone, where vigorous convection occurred. In contrast to typical northern events, which are linked to colder cloud tops and vigorous convection, the afternoon EPE in stage 2 formed near cloud edges with lesser negative TBB values. These findings advance the understanding of multi-scale extreme precipitation mechanisms in arid mountains, aiding improved forecasting in complex terrains. Full article

The intensity change of Typhoon Songda (TY-0418) in the vicinity of the semi-enclosed Sea of Japan (SJ) was numerically investigated using 3D-WRF and UM-KMA models and GOES-IR satellite images on 4 to 8 September 2004. After the typhoon originated in the Western Pacific Ocean in August, it moved to the East China Sea. Following the north-eastward Kuroshio Warm Current, it developed with horizontal and vertical asymmetrical wind and moisture patterns until 5 September. On 7 September, closing to the Kyushu Island, it was divided into three wind fields near the surface due to the increased friction from the surrounding lands and shallower sea depth close to the land, but it still maintained its circular shape over 1 km in height. As it passed by the Korea Strait and entered the SJ, it became a smaller, deformed typhoon due to the SJ’s surrounding mountains, located between the East Korea and Tsushima Warm Currents inside the SJ. Its center matched a high equivalent potential temperature area, releasing significant latent heat through the condensation of water particles over warm currents. The latent heat converted to kinetic energy could be supplied into the typhoon circulation, causing its development. Moist flux and streamline at 1.5 km in height clearly showed the moisture transportation via the mutual interaction of the cyclonic circulation of the typhoon and the anti-cyclonic circulation of the North Pacific High Pressure from the typhoon’s tail toward both the center of the SJ and the Russian Sakhalin Island in the north of Japan, directly causing large clouds in its right quadrant. Simultaneously, the central pressure decrease with time could converge both transported moist air by the typhoon itself and water particles evaporated from the sea, causing them to rise and resulting in the formation of large clouds and the rapid development of the typhoon circulation. The strong downslope winds from the surrounding mountains of the SJ to its center also produced a cyclonic vortex due to the Coriolis force to the right, enhancing the typhoon’s circulation. Full article

In this study, 10 min and 2 km high-resolution blended fog data (HRBFD) were generated using grid visibility data (GVD) and data from a GK2A (GEO-KOMPSAT-2A) fog product (GKFP) in Korea. As the blending method, the decision tree method (DTM) was used to consider the different characteristics of the two-input data (categorical data and continuity data). The blending of the two datasets was performed according to the presence or absence of the input data and considered the spatial representation of the GVD and the accuracy of the GKFP. The quality of the HRBFD was evaluated through visual comparison using GVD, GKFP, and visible images of the GK2A. The HRBFD seems to have partly solved the problem of fog detection in areas where visibility meters are rare or absent through the detection of fog occurring in the sea or mountain areas. In addition, the critical problem of the GKFP, which has limitations in detecting fog occurring under clouds, has been mostly overcome. Using the DTM, we generated 23 fog cases of 10 min and 2 km HRBFD. The results confirmed that detailed spatiotemporal characteristics of fog in Korea can be analyzed if such HRBFD is generated for a long time. Full article

The micro-physical characteristics of a typical sea of clouds process in Jiuxian Mountain are investigated by comprehensively analyzing parameters that delineate the micro-physical characteristics of clouds and atmospheric stratification based on data from a cloud radar, wind profiler, meteorological gradient observation in high mountains, and other observations. The results show that water vapor condenses into cloud particles via an entrained and mixing process accompanied by an updraft originating from orographic uplift. During the thickening stage of the sea of clouds, atmospheric motion within the clouds is featured as “downdraft on the top—updraft on the bottom”. The zero vertical velocity area is located closely to the maximum of liquid water content. The thermal inversion layer is formed during the maintenance stage; however, the enhancement of inversion on the cloud top could suppress updraft in areas with a high liquid water content. The values mainly concentrate on the cloud top, and repetitively lifting and falling processes caused by the atmospheric upward and downward motion are in favor of the coalescence growth of cloud particles, which result in the persistence of strong radar echo. At the dissipation stage, warming on the cloud top is greater than that on the cloud bottom due to the short-wave absorption of clouds as the solar radiation enhances. As a result, the inversion layer thickens and elevates, evaporation caused by heating outweighs the condensation caused by cooling, a strong radar echo band descends from the top to the middle part of clouds, a sea of clouds dissipates gradually as cloud particles evaporates, and the particle size and concentration number of cloud particles decrease simultaneously. Full article

Snowmelt significantly contributes to meltwater in most parts of High Mountain Asia. The Karakoram region is one of these densely glacierized and snow-covered regions. Several studies have reported that glaciers in the Karakoram region remained stable or experience slight mass loss. This trend has called for further investigation to understand changes in other components of the cryosphere. This study estimates the comparative snow cover area (SCA) and snowline altitude (SLA) changes between 2003 and 2018 in the Karakoram region and its subbasins, including Hunza, Shigar, and Shyok. We used three different 8-day composite snow products of the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study including (1) Original Aqua (MYD10A2), (2) Original Terra (MOD10A2), and (3) Improved Terra-Aqua (MOYDGL06*) snow products from 2003 to 2018. We used Mann–Kendall and Sen Slope methods to assess trends in the SCA and SLA. Our results show that the original snow products are significantly biased when investigating seasonal and annual trends. However, discarding a cloud cover of >20% in the original products improves the results and makes them more comparable to our improved snow product. The original products (without cloud removal) overestimate the SCA during summer and underestimate the SCA during winter and year-round throughout the Karakoram region. The bias in the mean annual SCA between improved and Aqua and Terra cloud threshold products for the Karakoram region is found to be −1.67% and 1.1%, respectively. The improved (MOYDGL06*) product reveals a statistically insignificant decreasing trend of the SCA on the annual scale between 2003 and 2018 in the Karakoram region and all three subbasins. The annual trends decreased at −0.13%, −0.1%, −0.08%, and −0.05% in the Karakoram, Hunza, Shigar, and Shyok, respectively. The monthly trends were slightly positive overall in December. The annual maximum SLA shows a statistically significant upward trend of 13 m above sea level (m a.s.l.) per year for the entire Karakoram region. This finding suggests a significant uncertainty in water resource planning based on the original snow data, and this study recommends the use of the improved snow product for a better understanding. Full article

High-resolution real-time satellite-based precipitation estimation datasets can play a more essential role in flood forecasting and risk analysis of infrastructures. This is particularly true for extended deserts or mountainous areas with sparse rain gauges like Iran. However, there are discrepancies between these satellite-based estimations and ground measurements, and it is necessary to apply adjustment methods to reduce systematic bias in these products. In this study, we apply a quantile mapping method with gauge information to reduce the systematic error of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). Due to the availability and quality of the ground-based measurements, we divide Iran into seven climate regions to increase the sample size for generating cumulative probability distributions within each region. The cumulative distribution functions (CDFs) are then employed with a quantile mapping 0.6° × 0.6° filter to adjust the values of PERSIANN-CCS. We use eight years (2009–2016) of historical data to calibrate our method, generating nonparametric cumulative distribution functions of ground-based measurements and satellite estimations for each climate region, as well as two years (2017–2018) of additional data to validate our approach. The results show that the bias correction approach improves PERSIANN-CCS data at aggregated to monthly, seasonal and annual scales for both the calibration and validation periods. The areal average of the annual bias and annual root mean square errors are reduced by 98% and 56% during the calibration and validation periods, respectively. Furthermore, the averages of the bias and root mean square error of the monthly time series decrease by 96% and 26% during the calibration and validation periods, respectively. There are some limitations in bias correction in the Southern region of the Caspian Sea because of shortcomings of the satellite-based products in recognizing orographic clouds. Full article

The Sistan Basin has been recognized as one of the most active dust sources and windiest desert environments in the world. Although the dust activity in Sistan maximizes during the summer, rare but intense dust storms may also occur in the winter. This study aims to elucidate the atmospheric dynamics related to dust emission and transport, dust-plume characteristics, and impacts on aerosol properties and air quality during an intense dust storm over Sistan in February 2019. The dust storm was initiated by strong northerly winds (~20 ms⁻¹) associated with the intrusion of a cold front from high latitudes. The upper-level potential vorticity (PV)-trough evolved into a cut-off low in the mid and upper troposphere and initiated unstable weather over Afghanistan and northern Pakistan. At the surface, density currents emanating from deep convective clouds and further strengthened by downslope winds from the mountains, caused massive soil erosion. The passage of the cold front reduced the temperature by ~10 °C and increased the atmospheric pressure by ~10 hPa, while the visibility was limited to less than 200 m. The rough topography played a major role in modulating the atmospheric dynamics, wind field, dust emissions, and transport pathways. Meso-NH model simulates large amounts of columnar mass dust loading (> 20 g m⁻²) over Sistan, while the intense dust plume was mainly traveling below 2 km and increased the particulate matter (PM₁₀) concentrations up to 1800 µg m⁻³ at Zabol. The dust storm was initially moving in an arc-shaped pathway over the Sistan Basin and then it spread away. Plumes of dust covered a large area in southwest Asia, reaching the northern Arabian Sea, and the Thar desert one to two days later, while they strongly affected the aerosol properties at Karachi, Pakistan, by increasing the aerosol optical depth (AOD > 1.2) and the coarse-mode fraction at ~0.7. Full article