Storm Development Research Articles

Evaluating the Prediction Performance of the WRF-CUACE Model in Xinjiang, China

Dust and air pollution events are increasingly occurring around the Taklimakan Desert in southern Xinjiang and in the urban areas of northern Xinjiang. Predicting such events is crucial for the advancement, growth, and prosperity of communities. This study evaluated a dust and air pollution forecasting system based on the Weather Research and Forecasting model coupled with the China Meteorological Administration Chemistry Environment (WRF-CUACE) model using ground and satellite observations. The results showed that the forecasting system accurately predicted the formation, development, and termination of dust events. It demonstrated good capability for predicting the evolution and spatial distribution of dust storms, although it overestimated dust intensity. Specifically, the correlation coefficient (R) between simulated and observed PM10 was up to 0.85 with a mean absolute error (MAE) of 721.36 µg·m−3 during dust storm periods. During air pollution events, the forecasting system displayed notable variations in predictive accuracy across various urban areas. The simulated trends of PM2.5 and the Air Quality Index (AQI) closely aligned with the actual observations in Ürümqi. The R for simulated and observed PM2.5 concentrations at 24 and 48 h intervals were 0.60 and 0.54, respectively, with MAEs of 28.92 µg·m−3 and 29.10 µg·m−3, respectively. The correlation coefficients for simulated and observed AQIs at 24 and 48 h intervals were 0.79 and 0.70, respectively, with MAEs of 24.21 and 27.56, respectively. The evolution of the simulated PM10 was consistent with observations despite relatively high concentrations. The simulated PM2.5 concentrations in Changji and Shihezi were notably lower than those observed, resulting in a lower AQI. For PM10, the simulation–observation error was relatively small; however, the trends were inconsistent. Future research should focus on optimizing model parameterization schemes and emission source data.

CircMETTL3-156aa reshapes the glycolytic metabolism of macrophages to promote M1 polarization and induce cytokine storms in sHLH

Persistent macrophage activation and cytokine storms are critical causes for the rapid disease progression and high mortality rate of Secondary Hemophagocytic lymphohistiocytosis (sHLH). Identification of key regulatory factors that govern the activation of macrophages is vital. Plasma exosomal circular RNAs (circRNAs) are considered important biomarkers and potential therapeutic targets for various diseases, however, their function in sHLH is still unclear. In this study, we demonstrated for the first time that circMETTL3, derived from METTL3, is upregulated in sHLH patient plasma exosomes, which may plays an important role in the diagnosis of sHLH. Significantly, we also revealed that a novel peptide encoded by circMETTL3, METTL3-156aa, is an inducer of M1 macrophage polarization, which is responsible for the development of cytokine storms during sHLH. We then identified that METTL3-156aa binding with lactate dehydrogenase A (LDHA) and promotes M1 macrophage polarization by enhancing macrophage glycolysis. Additionally, the glycolysis metabolite lactate upregulates the cleavage factor SRSF10 expression by lactylation. This results in increased splicing of the pre-METTL3 mRNA, leading to an enchance in the production of cirMETTL3. Therefore, our results suggest that the circMETTL3/METTL3-156aa/LDHA/Lactate/SRSF10 axis forms a positive feedback loop and may be a novel therapeutic target for the treatment of sHLH.

The origins of Storm Ciarán: From diabatic Rossby wave to warm‐seclusion cyclone with a sting jet

AbstractThe evolution of Storm Ciarán was different from what is commonly attributed to windstorms affecting northwest Europe. Ciarán initially developed as a diabatic Rossby wave, driven by low‐level latent heat release and with negligible upper tropospheric forcing. It then crossed the jet stream, intensifying explosively while developing a low‐level warm seclusion and producing extreme near‐surface winds, including sting jets. Ciarán is an example of an extreme windstorm following this pathway and highlights the need of a systematic assessment of its relevance in our warming climate.

Legacy of aerosol radiative effect predominates daytime dust loading evolution

Dust radiative effect imposes pronounced perturbations on planetary boundary layer (PBL) development. In turn, the modified PBL characteristics and circulation fields regulate subsequent dust processes, which have not been explored sufficiently. In this study, parallel experiments are designed to isolate the instant, legacy and nonlinear impacts of aerosol radiative effect on daytime dust storm evolution over the Tarim Basin. During a typical dust storm event, legacy radiative effect is found to dominate dust loading dynamics and modulates mean dust burden by more than 16 % in the central basin and − 41 % in the marginal basin. Specifically, the dust column concentration increases in central regions but decreases in marginal regions. Dust aerosols cause opposite heating rate distributions and PBL structure between the central and marginal regions through altering radiative balance. Dust-induced cooling effect in the marginal regions leads to PBL suppression and attenuates entrainment mixing. Negative net heating also results in lowered potential temperature, elevated air pressure and thus increases their horizontal gradients. Accordingly, wind speeds are amplified through geostrophic and thermal wind effects, which further accelerate deposition rates, and eventually weaken dust suspension. In the central basin, dust plumes stimulate a warm mixing layer and unstable entrainment zone, which inhibit dry deposition removal and favor dust accumulation in the atmosphere. Our study highlights the importance of accounting PBL dynamics and geostrophic balance in quantifying the impacts of preceding radiative effect on subsequent dust evolution.

Effect of Different Fluorescence Iabelling Methods of the Actin Cytoskeleton for Storm Application

The Abbe limit was a major challenge in optical microscopy, making it difficult to observe microscopic biological structures. However, the development of STORM, a new fluorescence localization microscopy technique, has enabled much higher resolution imaging by causing dye molecules to blink under laser light. Advances in computational analysis have further improved image processing and resolution, leading to clearer observations and a better understanding of biological structures. Actin, a common protein in eukaryotic cells, forms F-actin, a filament involved in essential processes like cell division, migration, and muscle contraction. Fluorescence labeling is crucial for visualizing F-actin and other cellular structures, allowing scientists to study these important processes. This project explored two methods to visualize actin structures in Hela cells: phalloidin labeling with Alexa-647 dye and DNA-PAINT using GFP. ThunderSTORM analysis produced normalized images for both methods, and resolution values were calculated using FRC. The results indicated that phalloidin labeling provided higher resolution but lower-quality images, while DNA-PAINT with GFP offered better-quality images but with lower resolution.

Bailixiang tea, an herbal medicine formula, co-suppresses TLR2/MAPK8 and TLR2/NF-κB signaling pathways to protect against LPS-triggered cytokine storm in mice

Ethnopharmacological relevanceTraditional Chinese medicine (TCM) has shown notable effectiveness and safety in managing illnesses linked to cytokine storm(CS). Bailixiang tea (BLX), an herbal medicine formula, which is a compound Chinese medicine composed of Thymus mongolicus (Ronniger) Ronniger (Bailixiang), Glycyrrhiza uralensis Fisch. (Gancao), Citrus reticulata Blanco (Chenpi), Cyperus rotundus L. (Xiangfu), and Perilla frutescens (L.) Britton (Zisu). The objective of this study was to explore the capacity of BLX in improving LPS-induced CS. Aim of the studyThis study aimed to validate the mitigating effect of BLX on CS and to further investigate its mechanism. Materials and methodsmice were orally administered BLX for 24 h after being treated with 5 mg/kg lipopolysaccharide (LPS). Histopathological observations further confirmed the significant protective effect of BLX treatment against LPS-induced lung and spleen damage. Additionally, we aimed to explore the molecular mechanism underlying its effects through blood proteomics and transcriptomics analyses. Real-Time Quantitative PCR (RT-qPCR) was utilized to detect the levels of Toll-like receptor 2 (TLR2), Matrix metalloproteinase 8 (MMP8), Matrix metalloproteinase 9 (MMP9), Integrin beta 2 (ITGB2), Mitogen-activated protein kinase 8 (MAPK8), Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, epsilon (NFKBIE), Nuclear factor of kappa light polypeptide gene enhancer in B-cells 2 (NFKB2), and Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH)expressions in the lung tissue. ResultsThe results demonstrated that BLX effectively down-regulated the overproduction of interleukin 6 (IL-6) and tumor necrosis factor-α (TNF-α) in both the serum and lung and spleen tissues. Furthermore, BLX effectively mitigated the overproduction of monocyte chemoattractant protein-1 (MCP-1) in the serum. Through comprehensive multi-omics analysis, it was revealed that BLX specifically targeted and regulated TLR2/MAPK8 and TLR2/NF-κB signaling pathways, which play a crucial role in the production of key cytokines. ConclusionsThe findings of this study demonstrate that Bailixiang tea possesses the ability to alleviate lung tissue damage and inhibit the development of LPS-induced cytokine storm in mice. These effects are attributed to the tea's ability to suppress the TLR2/MAPK8 and TLR2/NF-κB pathways. Consequently, this research highlights the potential application of Bailixiang tea as a treatment option for cytokine storm.

Intensification and Changing Spatial Extent of Heavy Rainfall in Urban Areas

AbstractUrban areas have been shown to impact rainfall by altering both its intensity and spatial structure at sub‐hourly and sub‐kilometer scales. However, there is currently no clear understanding of the precise pattern of change and the mechanisms that drive these changes. Since the hydrological response in urban areas is highly sensitive to such rainfall properties, understanding these changes is critical to improving our ability to assess urban flood risk. We use 7 years of high‐resolution weather radar data (4‐ or 5‐min and 1 km) to analyze changes in patterns of rainfall intensity, spatial structure, and storm evolution across eight urban areas within Europe and the United States. The use of the same methodology across the different cities enables a consistent comparison among them. We track convective rainfall events using a storm tracking algorithm and assess changes in rainfall properties in the upwind, center, and downwind regions of each city. We also investigate changes in the frequency of storm initiations, terminations, splitting, and merging. Our results show that urban areas act to intensify rainfall—mostly over them, but sometimes on their peripheries. Overall, larger cities tend to show the largest rainfall enhancements. Our findings highlight that rainfall spatial structure is altered over the urban core; usually resulting in more spatially concentrated rainfall. We also observe increased storm initiations over most cities and increased storm splitting over one. Given that demographic projections show that future urban population will increase, our results point toward an increased future flood risk in growing cities.

Ionospheric TEC Prediction in China during Storm Periods Based on Deep Learning: Mixed CNN-BiLSTM Method

Applying deep learning to high-precision ionospheric parameter prediction is a significant and growing field within the realm of space weather research. This paper proposes an improved model, Mixed Convolutional Neural Network (CNN)—Bidirectional Long Short-Term Memory (BiLSTM), for predicting the Total Electron Content (TEC) in China. This model was trained using the longest available Global Ionospheric Maps (GIM)-TEC from 1998 to 2023 in China, and underwent an interpretability analysis and accuracy evaluation. The results indicate that historical TEC maps play the most critical role, followed by Kp, ap, AE, F10.7, and time factor. The contributions of Dst and Disturbance Index (DI) to improving accuracy are relatively small but still essential. In long-term predictions, the contributions of the geomagnetic index, solar activity index, and time factor are higher. In addition, the model performs well in short-term predictions, accurately capturing the occurrence, evolution, and classification of ionospheric storms. However, as the predicted length increases, the accuracy gradually decreases, and some erroneous predictions may occur. The northeast region exhibits lower accuracy but a higher F1 score, which may be attributed to the frequency of ionospheric storm occurrences in different locations. Overall, the model effectively predicts the trends and evolution processes of ionospheric storms.

A Comprehensive Classification and Analysis of Geomagnetic Storms Over Solar Cycle 24

A geomagnetic storm is a global disturbance of Earth's magnetosphere, occurring as a result of the interaction with magnetic plasma ejected from the Sun. Despite considerable research, a comprehensive classification of storms for a complete solar cycle has not yet been fully developed, as most previous studies have been limited to specific storm types. This study, therefore, attempted to present complete statistics for solar cycle 24, detailing the occurrence of geomagnetic storm events and classifying them by type of intensity (moderate, intense, and severe), type of complete interval (normal or complex), duration of the recovery phase (rapid or long), and the number of steps in the storm's development. The analysis was applied to data from ground-based magnetometers, which measured the Dst index as provided by the World Data Center for Geomagnetism, Kyoto, Japan. This study identified 211 storm events, comprising moderate (177 events), intense (33 events), and severe (1 event) types. About 36% of ICMEs and 23% of CIRs are found to be geoeffective, which caused geomagnetic storms. Up to four-step development of geomagnetic storms was exhibited during the main phase for this solar cycle. Analysis showed the geomagnetic storms developed one or more steps in the main phase, which were probably related to the driver that triggered the geomagnetic storms. A case study was additionally conducted to observe the variations of the ionospheric disturbance dynamo (Ddyn) phenomenon that resulted from the geomagnetic storm event of 2015 July 13. The attenuation of the Ddyn in the equatorial region was analyzed using the H component of geomagnetic field data from stations in the Asian sector (Malaysia and India). The variations in the Ddyn signatures were observed at both stations, with the TIR station (India) showing higher intensity than the LKW station (Malaysia).

Revisiting the evolution of downhill thunderstorms over Beijing: a new perspective from a radar wind profiler mesonet

Abstract. Downhill thunderstorms frequently occur in Beijing during the rainy seasons, leading to substantial precipitation. The accurate intensity prediction of these events remains a challenge, partly attributed to insufficient observational studies that unveil the thermodynamic and dynamic structures along the vertical direction. This study provides a comprehensive methodology for identifying both enhanced and dissipated downhill thunderstorms. In addition, a radar wind profiler (RWP) mesonet has been built in Beijing to characterize the pre-storm environment downstream of the thunderstorms at the foothill. This involves deriving vertical distributions of high-resolution horizontal divergence and vertical motion from the horizontal wind profiles measured by the RWP mesonet. A case study of an enhanced downhill thunderstorm on 28 September 2018 is carried out for comparison with a dissipated downhill thunderstorm on 23 June 2018, supporting the notion that a deep convergence layer detected by the RWP mesonet, combined with the enhanced southerly flow, favors the intensification of thunderstorms. Statistical analyses based on radar reflectivity from April to September 2018–2021 have shown that a total of 63 thunderstorm events tend to be enhanced when entering the plain, accounting for about 66 % of the total number of downhill thunderstorm events. A critical region for intensified thunderstorms lies on the downslope side of the mountains west to Beijing. The evolution of a downhill storm is associated with the dynamic conditions over the plain compared to its initial morphology. Strong westerly winds and divergence in the middle of troposphere exert a critical influence on the enhancement of convection, while low-level divergence may lead to dissipation. The findings underscore the significant role of an RWP mesonet in elucidating the evolution of a downhill storm.

Etiological and immunopathogenetic aspects of multiorgan failure development in coronavirus disease (COVID-19)

The COVID-19 epidemic has already come to be seen as an emergency of international concern. This relates not only to the wide occurrence of the infection, but also to a fairly high mortality rate, currently more than 6.5 million deaths in the world. The aim of this study was to analyze, generalize and systematize the currently available literary data on the study of the novel coronavirus infection pathogenesis in the human body and to determine key changes that occur after the SARS-CoV-2 penetration into cells. In this way to target physicians primarily based on the pathogenetic processes that occur in the human body, syndromes and symptom complexes that are observed in treatments. Results. The article presents a literature review demonstrating that the specific interaction between the virus and somatic cells is the triggering mechanism for the pathogenesis of coronavirus infection. The main route for SARS-CoV-2 entry into the body is the angiotensin-converting enzyme 2 (ACE2) receptor, which is expressed not only in type 2 alveolar epithelial cells, but also in cells of the kidney, heart, blood vessels and gastrointestinal tract, including endotheliocytes and pericytes. Expression of the ACE2 receptor has also been shown in various structures and parts of the brain, cells of the conjunctiva, limbus, cornea and cells of the substantia propria. A high expression of the ACE2 receptor has been found in the epithelial cells of the oral mucosa, salivary glands, tonsils and tongue. These factors explain a possible involvement of different organs and systems in the development of multiorgan failure. Conclusions. In the development of multiorgan disfunction, two components are important: first, direct cell tropism and viral load, that may be unique in each patient. Secondly, it is the development of immune-mediated reactions to infected cells. Under conditions of hyperimmune inflammation, that is, the development of cytokine storm, acute respiratory distress syndrome progresses, and multiple organ failure develops. Endothelial damage is directly involved in the pathophysiology of this process, that results in the development of endothelial dysfunction, disruption of microcirculation, as well as perivascular inflammation, which aggravates damage to the endothelium and can lead to thrombus formation. The use of modern knowledge about the immunopathogenesis of COVID-19 would help to estimate the risk for severe infection and the possible development of complications, allowing for the timely implementation of effective pathogenetic therapy.

The Protective Role of IL-17 and IL-22 in COVID-19 Infection.

The development of a cytokine storm in Coronavirus Disease 2019 (COVID-19) infection can make the disease fatal. We hypothesize that this excessive cytokine production impairs mucosal healing. IL-17 and IL-22 are cytokines that play a key role in protecting and regenerating mucosal tissues.IL-17 and IL-22 support each other and the imbalance between them plays a role in the pathogenesis of many rheumatologic diseases. To investigate whether COVID-19 severity is related to IL17, IL-22, and the IL-17/IL-22 ratio. The study was planned prospectively and included 69 patients with active COVID-19 infection.Three groups were created: patients with upper respiratory tract infection, pneumonia, and cytokine storm. Blood samples were taken from the patients upon their first admission and serum levels of IL-17 and IL-22 were measured using the enzyme-linked immunosorbent assay (ELISA). We assessed the relationship between IL17, IL22, IL17/IL22 ratio, clinical and lung involvement by comparing them with the healthy group. The levels of IL-17 were significantly higher in COVID-19 patients with upper respiratory tract infection compared to the control group (p=0.027). IL17/IL-22 ratio significantly increased in patients with cytokine storm compared to the healthy controls (p=0.027). Serum levels of IL-22 were negatively correlated with the CO-RADS score (r=-0.31, p=0.004), while IL-17/IL-22 ratio was positively correlated with the CO-RADS score (r= 0.29, p=0.008). Levels of IL-17, IL-22 and IL-17/IL-22 may provide valuable insights into the progression of COVID-19.

Impaired arginine/ornithine metabolism drives severe HFMD by promoting cytokine storm.

The Hand, Foot and Mouth Disease (HFMD), caused by enterovirus 71 infection, is a global public health emergency. Severe HFMD poses a significant threat to the life and well-being of children. Numerous studies have indicated that the occurrence of severe HFMD is associated with cytokine storm. However, the precise molecular mechanism underlying cytokine storm development remains elusive, and there are currently no safe and effective treatments available for severe HFMD in children. In this study, we established a mouse model of severe HFMD to investigate the molecular mechanisms driving cytokine storm. We specifically analyzed metabolic disturbances, focusing on arginine/ornithine metabolism, and assessed the potential therapeutic effects of spermine, an ornithine metabolite. Our results identified disturbances in arginine/ornithine metabolism as a pivotal factor driving cytokine storm onset in severe HFMD cases. Additionally, we discovered that spermine effectively mitigated the inflammatory injury phenotype observed in mice with severe HFMD. In conclusion, our findings provide novel insights into the molecular mechanisms underlying severe HFMD from a metabolic perspective while offering a promising new strategy for its safe and effective treatment.

Cassini spacecraft reveals global energy imbalance of Saturn

The global energy budget is pivotal to understanding planetary evolution and climate behaviors. Assessing the energy budget of giant planets, particularly those with large seasonal cycles, however, remains a challenge without long-term observations. Evolution models of Saturn cannot explain its estimated Bond albedo and internal heat flux, mainly because previous estimates were based on limited observations. Here, we analyze the long-term observations recorded by the Cassini spacecraft and find notably higher Bond albedo (0.41 ± 0.02) and internal heat flux (2.84 ± 0.20 Wm−2) values than previous estimates. Furthermore, Saturn’s global energy budget is not in a steady state and exhibits significant dynamical imbalances. The global radiant energy deficit at the top of the atmosphere, indicative of the planetary cooling of Saturn, reveals remarkable seasonal fluctuations with a magnitude of 16.0 ± 4.2%. Further analysis of the energy budget of the upper atmosphere including the internal heat suggests seasonal energy imbalances at both global and hemispheric scales, contributing to the development of giant convective storms on Saturn. Similar seasonal variabilities of planetary cooling and energy imbalance exist in other giant planets within and beyond the Solar System, a prospect currently overlooked in existing evolutional and atmospheric models.

Convective Phenomenes in the Context of Meso-β-scale Convective Structures

This review article presents the results of radar studies of convective phenomena in Moldavia and the North Caucasus using Eulerian (ECS) and Lagrangian (LCS) coordinate systems. Application of the Lagrangian approach allowed us to exclude the influence of the tropospheric displacement and to obtain integral grid patterns of thunderstorm-hail processes. These structures are especially well manifested at small wind shears (up to 1 m/sec/km). At large shears, the mesh structures are transformed predominantly into linear structures. The methodology for obtaining integral pictures of radio echoes of thunderstorm processes is described. Intersections of linear elements, which we call faces, occur at nodes. The latter plays a particularly important role in the dynamics and kinematics of convective storms. The latter play a particularly important role in the dynamics and kinematics of convective storms. The development of storms occurs along the facets and at the nodes of meso-β-scale convective structures (MMCS), which explains the mechanisms of splitting and merging of storms: in the first case the facets diverge, in the second case they converge. The relations of motion vectors for different types of storms are obtained. It is shown that the direction of the radio echo canopy coincides with the storm motion trajectory; the evolution vector (propagation) for the most powerful storms deviates from the storm displacement direction by 80°–135°. The structure of the updated band within which the Flanking Line is formed for supercells and multicells is studied. Mnemonic rules have been derived that allow one to infer from instantaneous patterns of anvil orientation and the mutual location of storms whether they are converging or diverging, and to identify left- or right-moving storms. A hypothesis on the internal structure of the cold front of the 2nd kind is stated. The main conclusion of the work is that the evolution of storms is determined by the configuration of meso-β-scale convective structures. This explains various convective phenomena from unified positions. The results are applicable in works on modification of convective cloudiness, for ultra-short-term forecasts of dangerous phenomena, storm warnings of the population, rescue services, etc.

The Influence of Sudden Stratospheric Warming on the Development of Ionospheric Storms: The Alma-Ata Ground-Based Ionosonde Observations

This paper examines the response of the ionosphere to the impact of two moderate geomagnetic storms observed on January 17 and 26–27, 2013, under conditions of strong sudden stratospheric warming. The study uses data from ground-based ionosonde measurements at the Alma-Ata ionospheric station (43.25 N, 76.92 E) combined with optical observation data (The Spectral Airglow Temperature Imager (SATI)). Ionosonde data showed that the geomagnetic storms under consideration do not generate ionospheric storms but demonstrate some unusual types of diurnal foF2 variations with large (up to 60%) deviations in foF2 from median values observed during the night/morning periods on 13–15 and 20–23 January, which do not have any relation to solar or geomagnetic activity. Wave-like disturbances in foF2, h’F, and daily averaged foF2 values with a quasi-period of 5–8 days and peak-to-peak amplitude from about 1 MHz to 2 MHz (from 20% to 40%) and ~40 km are observed during the period 9–28 January, after registration of the occurrence of the major SSW event on 6–7 January. The observed variations in the OH emission rate are found to be quite similar to those observed in the ionospheric parameters that assume a community of processes in the stratosphere/mesosphere/ionosphere system. The study shows that the F region of the ionosphere is influenced by processes in the lower ionosphere, in this case by processes associated with sudden stratospheric warming SSW-2013, which led to modification of the structure of the ionosphere and compensation of processes associated with the development of the ionospheric storms.

Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during the Monsoon Season. Part I: Pre-storm Environment and Storm Evolution

Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during the Monsoon Season. Part I: Pre-storm Environment and Storm Evolution

On the Kinematics of Sea-Land Breeze and the Local Development of Convective Storms in the Metropolitan Area of Rio de Janeiro

This work presents an analysis of the kinematic properties of the wind flow in the Metropolitan Area of Rio de Janeiro in the State of Rio de Janeiro, Brazil, using meteorological data from the aerodromes Santos Dumont, Galeão and Campo dos Afonsos, located in the city of Rio de Janeiro. The calculation of these kinematic quantities is based on the 'Linear Vector Point Function' (LVPF) method. The results indicate the main role of the circulation of the sea-land breeze, the effects of topography (by blockages, channeling and differential heating) and the urban breeze associated with the development of the Urban Boundary Layer in the local formation of convective rainstorms in the Metropolitan Area of Rio de Janeiro.

Study of boundary layer parameterization simulation uncertainties of sand-dust storm windfield using high-resolution three-dimensional Doppler wind lidar data

The processes of dust emission, the development, and dissipation of sand and dust storms all exhibit dynamic and rapidly changing characteristics, posing significant challenges for us to accurately represent their complex behaviors in numerical simulations. In the numerical weather prediction model, the selection and optimization of planetary boundary layer (PBL) parameterization schemes have a direct impact on the simulation results of PBL wind fields, primarily due to the significant uncertainty in the fine-grained simulation of PBL wind field structure. To gain a deeper understanding of the sources of uncertainty in simulating sand-dust storms through vertical wind field structure simulations of the PBL, this study utilizes high-resolution 3D Doppler wind lidar (DWL) data. Focusing on sand-dust storm wind fields with distinctive regional characteristics in Inner Mongolia, China, it examines the turbulent momentum equation and assumptions of the PBL. A comprehensive and systematic evaluation was conducted on the characteristics of horizontal and vertical wind fields, wind shear, as well as the dynamic and thermodynamic differences that arise when simulating typical sand-dust storm wind fields using the Weather Research and Forecasting (WRF) Model with various PBL schemes. This evaluation focused on simulating the typical wind field of sand-dust storms during various stages, including dust generation, occurrence, development, and dissipation. The findings indicate that non-adiabatic heating plays a significant role in the sustainability and evolution of sand-dust storms. The wind shear index holds particular importance as it embodies the dynamic factor in the model. The PBL schemes such as Mellor-Yamada Nakanishi and Niino Level 2.5 (MYNN2), A new version of asymmetric convective model (ACM2), and Grenier-Bretherton-McCaa (GBM), which factor in buoyancy effects, demonstrate more accurate wind shear simulations in sand-dust storms. Furthermore, the ACM2 scheme effectively replicates the fundamental variation characteristics of meteorological elements throughout the sand-dust storm lifecycle.

Escalation of tropical cyclone impacts on the northwestern Bay of Bengal over the past decade

Tropical cyclones have resulted in casualties and economic losses in the areas surrounding the Bay of Bengal (BoB). Thus, a comprehensive investigation of these tropical cyclones holds vital implications for disaster preparedness and mitigation. This paper compares the occurrence of storms in the last two decades, i.e., 2002–2011 and 2012–2021, and results reveal that such storms exhibited predominantly a northwesterly track towards the northwestern BoB, with a severer intensity but equal total storm frequencies. Over the past decade, a southeast-northwest pathway (SNP) was identified, demonstrating a higher incidence of severe tropical cyclones (STC, with lifetime maximum intensity ≥ 64 knots) over the BoB. Further analysis of the changes in the environmental conditions between these two decades indicates that a southeasterly anomaly in the steering flow contributed to the formation of the SNP. During the same period, the more favorable oceanic conditions during the last decade, including higher sea surface temperatures, a greater upper ocean heat content, a thicker warm water layer, and a thicker barrier layer beneath the SNP, favored the development of these storms by providing more heat energy to the storms. The atmospheric conditions, including increased air-sea heat fluxes, moisture, and instability within the lower troposphere, as well as reduced vertical wind shear, facilitated the development of convection within these storm systems. These favorable conditions improved the potential for storm development into STCs and elevated the risk of the northwestern BoB being impacted by more destructive storms.