Search Results (16)

Raindrop size distribution (DSD) is a crucial parameter for microphysics parameterizations and radar quantitative precipitation estimation (QPE). Using disdrometer and ERA5 reanalysis data collected during the rainy season (July–September 2021) in the Liupan Mountains (LP), this study investigated how the two dominant airflow transport pathway types—the deep warm-moist monsoon (C1) and deep dry-cold continental (C2) types—modulated DSDs in the LP. The results showed that C1 had maritime characteristics, with higher number concentrations and a smaller mass-weighted mean diameter (D_m). C2 showed continental characteristics: low-level evaporation preferentially depleted small drops and increased the contribution of large drops (>2.38 mm), resulting in a larger D_m. Under both types, convective precipitation had broader DSDs than stratiform precipitation. Triggered by orographic lifting, C2 convective precipitation enhanced large-drop growth, making its D_m much larger than that of C1. The Z–R relationships were highly sensitive to airflow transport pathways. Dominated by small drops, C1 yielded a smaller Z–R coefficient A than C2, whereas reflectivity in C2 was more sensitive to the enhanced large-drop tail. These findings provide an observational basis for improving regional radar QPE accuracy, hydrometeorological forecasting, and water-resource assessment over complex terrain. Full article

The mountainous southwest of Saudi Arabia exhibits complex, highly seasonal precipitation driven by Indian Ocean monsoon inflows and orographic lifting. To characterize storm hyetographs, cluster analysis was applied to 8972 rainfall events recorded at 151 gauges. Two primary clusters emerged: one with early, intense peaks and another with later peak intensities, broadly reflecting windward versus leeward storm behavior. A locally derived hyetograph profile (AI) was constructed from the cluster centroids and benchmarked against standard design-storm distributions (Uniform, SCS Type II, Huff quartiles). Across fit metrics—cumulative RMSE, Kolmogorov–Smirnov distance, and cosine-intensity similarity—the AI distribution provided the best match for ~46% of storms, markedly outperforming canonical profiles (Uniform and SCS Type II each best-fit only ~11–12%). These results indicate that region-specific rainfall distributions more accurately represent precipitation patterns than conventional profiles, and that tailored hyetographs can improve hydrologic modeling and water-resources assessments in this climatically heterogeneous region. Full article

In July 2024, a severe rainfall event struck Sichuan Province, Southwest China, triggering deadly landslides and causing significant societal impacts. This study investigates the spatiotemporal characteristics and underlying mechanisms of the event using high-resolution surface observations, radar reflectivity, and ERA5 reanalysis data. The rainfall exhibited distinct mesoscale organization, with two primary precipitation centers identified: subregion A located within the plateau-lain transitional zone of the western Sichuan Basin, and subregion B situated over the Chengdu Plain. Synoptic-scale analysis indicated that the rainfall developed under favorable large-scale atmospheric conditions, including a mid-tropospheric trough, a pronounced low-level jet, and a well-defined Southwest Vortex (SWV), which is a dominant lower-tropospheric circulation system in this region. The evolution of rainfall was closely tied to the initiation and subsequent eastward progression of the SWV. The rainfall-producing mesoscale convective system (MCS) first formed over subregion A at approximately 2300 BST (UTC + 8) on 19 July. Vorticity budget diagnostics revealed that vertical advection and low-level convergence significantly contributed to vortex intensification during this initial phase, closely associated with the orographic lifting of low-level airflow. Convective activity in subregion B commenced roughly four hours later, coinciding with the eastward propagation of the SWV, during which horizontal vorticity advection became the primary mechanism sustaining the vortex. After 1400 BST on 20 July, the SWV weakened significantly, leading to the dissipation of the MCS and the cessation of rainfall. Full article

Numerical weather prediction (NWP) models are essential for precipitation forecasting but are constrained by coarse spatial resolutions (10–50 km), which fail to capture fine-scale variations required for regional disaster prevention, particularly in complex terrain. While statistical and machine learning downscaling methods have been developed to bridge this resolution gap, they predominantly operate as “black boxes” without explicit physical guidance, leading to predictions that violate meteorological principles and systematic underestimation of extreme precipitation events. To address these limitations, this study aims to develop a Physics-Informed Machine Learning framework that explicitly integrates multi-scale topographic modulation and physical consistency constraints into precipitation downscaling. Specifically, a Random Forest model enhanced with Multi-Scale Structural Similarity (MS-SSIM) loss and Physical Constraint Enhancement (MSSSIM-PCE-RF) was constructed. The model introduces elevation gradient weights at low-resolution layers and micro-topographic parameters (slope, surface roughness) at high-resolution layers, while enforcing physical consistency between precipitation intensity, radar reflectivity, and ground observations via the Z-R relationship. Based on hourly data from 2252 meteorological stations in Jiangxi Province (2021–2022), coupled with topographic factors (DEM, slope, aspect) and Normalized Difference Vegetation Index (NDVI), a technical framework of “data fusion–feature synergy–machine learning–spatial reconstruction” was established. Results demonstrate that the MSSSIM-PCE-RF model achieves a validation R² of 0.9465 and RMSE of 0.1865 mm, significantly outperforming the conventional RF model (R² = 0.9272). Notably, errors in high-altitude, steep-slope, and high-vegetation areas are reduced by 45.3%, 42.0%, and 43.1%, respectively, with peak precipitation period errors decreasing by 37.2%. Multi-scale topographic analysis reveals significant orographic lifting effects at 250–1000 m elevations, peak precipitation at 12–15° slopes, and abundant precipitation on south/southeast aspects. By explicitly embedding topographic modulation and physical consistency constraints, the model effectively alleviates systematic underestimation of extreme precipitation in complex terrain, providing high-resolution data support for transmission line disaster prevention and micro-meteorological risk assessment. Full article

This study presents a four-year (2021–2024) radar-based analysis of warm cloud (non-glaciated) dynamics across northern Thailand, specifically characterizing their properties, kinematics, and occurrence. Utilizing high-resolution S-band dual-polarization weather radar data, a total of 20,493 warm cloud events were tracked and analyzed, with identification based on a maximum reflectivity (≥35 dBZ) and a cloud top height below the seasonal 0 °C isotherm. Occurrence exhibited a profound seasonal disparity, with the rainy season (82.68% of events) dominating due to the influence of the moist Southwest Monsoon (SWM), while the spatial distribution confirmed that convective initiation is exclusively concentrated over mountainous terrain, underscoring orographic lifting as the essential mechanical trigger. Regarding properties, while vertical development and mass are greater in the warm seasons, microphysical intensity and Duration (mean ~26 min) remain highly uniform, suggesting a constrained, efficient warm rain process. In kinematics, clouds move fastest in winter (mean WSPD ~18.38 km/h), yet pervasive directional chaos (SD > 112°) highlights the strong influence of terrain-induced local circulations. In conclusion, while topography dictates where warm clouds form, the monsoon dictates when and how robustly they develop, creating intense, short-lived events that pose significant operational constraints for localized precipitation enhancement strategies. Full article

This study conducts a diagnostic analysis of an extremely heavy rainfall event and its causative factors that occurred in Libya, North Africa on 10 September 2023. The Weather Research and Forecasting (WRF) model was also employed to perform some sensitivity experiments for this heavy rainfall event and further reveal its causes. Results indicate that the primary synoptic system responsible for this extreme precipitation event was an extratropical cyclone (storm) named “Daniel”. During the formation and development of this cyclone, the circulation at the 500 hPa level from the eastern Atlantic to western Asia exhibited a stable “two troughs and one ridge” pattern, with a upper-level cold vortex over the eastern Atlantic, a high-pressure ridge over central Europe, and a cut-off low over western Asia, collectively facilitating the formation and development of this cyclone. As this cyclone moved southward, it absorbed substantial energy from the Mediterranean Sea; following landfall, the intrusion of weak cold air enabled the cyclone to continue intensifying. Meanwhile, the northwest low-level jet stream to the west of the extratropical cyclone moved alongside the cyclone to the coastal regions of northeastern Libya, where it converged with water vapor transport belts originating from the Ionian Sea, the Aegean Sea, and the coastal waters of northeastern Libya. This convergence provided abundant water vapor for the rainstorm event, and under the combined effects of convergence and orographic lifting on the windward slopes of the coastal mountains, extreme precipitation was generated. In addition, the atmosphere over the coastal regions of northeastern Libya exhibited strong stratification instability, which was conducive to the occurrence of extreme heavy precipitation. Although WRF successfully reproduced the precipitation process, the precipitation amount was underestimated. Sensitivity experiments revealed that both the topography in the precipitation area and the sea surface temperature (SST) of the Mediterranean Sea contributed to this extreme heavy precipitation event. Full article

In the Himalayan regions of complex terrains, such as Himachal Pradesh, the occurrence of extreme rainfall events (EREs) has been increasing, triggering landslides and flash floods. Investigating the dynamics and precipitation characteristics and improving the prediction of such events are crucial and could play a vital role in contributing to sustainable development in the region. This study employs a high-resolution numerical weather prediction framework, the weather research and forecasting (WRF) model, to deeply investigate an ERE which occurred between 8 July and 13 July 2023. This ERE caused catastrophic floods in the Mandi and Kullu districts of Himachal Pradesh. The WRF model was configured with nested domains of 12 km and 4 km horizontal grid resolutions, and the results were compared with global high-resolution precipitation products and the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis dataset. The selected case study was amplified by the synoptic scale features associated with the position and intensity of the monsoon trough, including mesoscale processes like orographic lifting. The presence of a western disturbance and the heavy moisture transported from the Arabian Sea and the Bay of Bengal both intensified this event. The model has effectively captured the spatial distribution and large-scale dynamics of the phenomenon, demonstrating the importance of high-resolution numerical modeling in accurately simulating localized EREs. Statistical evaluation revealed that the WRF model overestimated extreme rainfall intensity, with the root mean square error reaching 17.33 mm, particularly during the convective peak phase. The findings shed light on the value of high-resolution modeling in capturing localized EREs and offer suggestions for enhancing disaster management and flood forecasting. Full article

The spatial and temporal distribution of heavy rainfall across the Taihang Mountains exhibits significant variation. Due to the region’s unstable geological conditions, frequent heavy rainfall events can lead to secondary disasters such as landslides, debris flows, and floods, thus intensifying both the frequency and severity of extreme events. Understanding the spatiotemporal evolution of heavy rainfall and its response to atmospheric circulation patterns is crucial for effective disaster prevention and mitigation. This study utilized daily precipitation data from 13 meteorological stations in the Taihang Mountains spanning from 1973 to 2022, employing Rotated Empirical Orthogonal Function (REOF), the Mann–Kendall Trend Test, and Continuous Wavelet Transform (CWT) to examine the spatiotemporal characteristics of heavy rainfall and its relationship with large-scale atmospheric circulation patterns. The results reveal that: (1) Heavy rainfall in the Taihang Mountains can be categorized into six distinct regions, each demonstrating significant spatial heterogeneity. Region I, situated in the transition zone between the plains and mountains, experiences increased rainfall due to orographic lifting, while Region IV, located in the southeast, receives the highest rainfall, driven primarily by monsoon lifting. Conversely, Regions III and VI receive comparatively less precipitation, with Region VI, located in the northern hilly area, experiencing the lowest rainfall. (2) Over the past 50 years, all regions have experienced an upward trend in heavy rainfall, with Region II showing a notable increase at a rate of 14.4 mm per decade, a trend closely linked to the intensification of the hydrological cycle driven by global warming. (3) The CWT results reveal significant 2–3-year periodic fluctuations in rainfall across all regions, aligning with the quasi-biennial oscillation (QBO) characteristic of the East Asian summer monsoon, offering valuable insights for future climate predictions. (4) Correlation and wavelet coherence analyses indicate that rainfall in Regions II, III, and IV is positively correlated with the Southern Oscillation Index (SOI) and the Pacific Warm Pool (PWP), while showing a negative correlation with the Pacific Decadal Oscillation (PDO). Rainfall in Region I is negatively correlated with the Indian Ocean Dipole (IOD). These climatic factors exhibit a lag effect on rainfall patterns. Incorporating these climatic factors into future rainfall prediction models is expected to enhance forecast accuracy. This study integrates REOF analysis with large-scale circulation patterns to uncover the complex spatiotemporal relationships between heavy rainfall and climatic drivers, offering new insights into improving heavy rainfall event forecasting in the Taihang Mountains. The complex topography of the Taihang Mountains, combined with unstable geological conditions, leads to uneven spatial distribution of heavy rainfall, which can easily trigger secondary disasters such as landslides, debris flows, and floods. This, in turn, further increases the frequency and severity of extreme events. Full article

In the Hokitika region, on the west coast of the South Island of New Zealand on 18 June 2015, very heavy stratiform precipitation (>200 mm/per day) occurred under north-westerlies with small CAPE (<25 J/kg). Analyses of model simulations and observations showed that this heavy rainfall was due to cold-front lifting enhanced by orographic lifting over the Southern Alps. At 1.5 km grid-length, the model terrain underestimated the average height of the 103 tallest mountains over the South Island by ~800 m. This led to weaker orographic lifting and mountain blocking, and a faster-moving and stronger cold front in the Hokitika region. As a result, large errors in the heavy rainfall prediction occurred. By increasing either the resolved or the sub-grid mountain heights, the simulated rainfall errors were largely reduced through stronger orographic lifting and mountain blocking, and simulation of the cold front movement and strength was improved. All the experiments have the same “flow-over” regime with mountain waves and/or wave breaking ($F_m$ ranges 0.61–1.21). However, the rainfall amount and distribution on the windward side of the mountains varied significantly. Our new findings were that the Southern Alps can have significant indirect effects on heavy rainfall by altering the speed and strength of the cold front, in addition to the well-known direct dynamical effects (i.e., orographic lifting and mountain blocking). A combination of these direct and indirect effects makes the heavy rainfall simulation sensitive to mountain heights even under the same “flow-over” regime. 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

To analyze the difference in the microphysical development characteristics of orographic rainfall, several Parsivel disdrometers were installed along the windward and leeward slope of a mountain. There were differences in the raindrop size distribution according to the difference in height and distance from the center of the mountain. In low-altitude coastal areas and adjacent areas, the number concentration of raindrops smaller than 1 mm was relatively lower than in mountainous areas, and the rain rate increased with the growth in the size of the raindrops. On the other hand, a higher rain rate was observed as the number concentration of raindrops smaller than 1 mm increased in the hillside area. The increase in the number concentration of small raindrops was evident at the LCL (lifting condensation level) altitude. The main factors affecting the increase in the rain rate on the windward and leeward slopes were the concentration of raindrops and the growth of raindrops, which showed regional differences. As a result of a PCA (principal component analysis), it was found that raindrop development by vapor deposition and weak convection were the main rainfall development characteristics on the windward and leeward slopes, respectively. The difference in regional precipitation development characteristics in mountainous areas affects the parameters of the rainfall estimation relational expression. This means that the rainfall relation calculated through the disdrometer observation data observed in a specific mountainous area can cause spatial and quantitative errors. Full article

During 6–7 June 2003, a Mei-Yu jet/front system over Southern China is characterized by appreciable horizontal temperature contrast below the 850 hPa level (>8 K), where the cold, dry, postfrontal northeasterlies converge with the warm, moist southwesterly flow, and above the 400–hPa level (>18 K) associated with an upper-level front. The frontal baroclinic zone tilts northward with a slope of ~1/100. During the passage of a midlatitude trough, the upper-level jet/front system advances southeastward. The thermally direct circulation across the subsynoptic low-level jet (SLLJ)/Mei-Yu front system, coupled with dynamic forcing aloft on the equatorial side of the entrance region of a subsynoptic upper-level jet (SULJ), provides a favorable environment for the development of a frontal cyclone over Southern China. A southwesterly marine boundary layer jet (MBLJ) develops between the deepening Mei-Yu frontal cyclone and the West Pacific Subtropical High (WPSH). The MBLJ transports moisture from the northern South China Sea (NSCS) to Southern China. All three jets (SULJ, SLLJ, and MBLJ) interact together during the deepening of the Mei-Yu frontal cyclone with positive feedback effects of latent heat release. On 7 June 2003, as the Mei-Yu front arrives near the Taiwan area, the warm, moist, and unstable air associated with the MBLJ decelerates as it approaches the Central Mountain Range (CMR). The warm, moist, and unstable air is orographically lifted by the CMR and enhances the vertical motion already present with the frontal zone. A region of widespread heavy rainfall develops, with a maximum of more than 350 mm/day, over a region extending from the southwestern coast of Taiwan to the windward slopes of the CMR. Full article

Near-surface winds around the mountainous Caribbean islands contribute to orographic lifting and thermal diurnal rainfall that requires mesoscale analysis. Here, a new perspective is presented via high-resolution satellite and reanalysis products. Singular value decomposition is applied to 5 km cold-cloud duration satellite data to understand the leading mode of seasonal hydro-climate variability and its regional controls. The spatial loadings reflect wet islands in a dry marine climate, while temporal amplitude is modulated by the large-scale zonal circulation. When summer-time trade winds weaken, daytime confluence around Caribbean islands enlarges, gathering and lifting more moisture. In addition to the static geographic forcing, transient easterly waves impart the majority of marine rainfall between June and September. Higher resolution products capture the thermal orographic effect and reveal upward trends in island rainfall and soil moisture over the satellite era, while lower resolution products miss this effect. The climate of mountainous Caribbean islands is trending toward increased runoff and soil moisture. Full article

The eastern Tibetan Plateau is subjected to strong spatial variations in precipitation, but the underlying reasons are still not well understood due to sparse in-situ meteorological observations. In this study, streamflow observations were adopted to investigate the orographic controls on precipitation in the Qingyijiang (QYJ) Basin of the eastern Tibetan Plateau. The method of multi-year annual water balance was used to estimate the basin-level precipitation using in-situ streamflow and flux-based evapotranspiration. In addition, elevation transect was designed to examine the possible links between precipitation and geomorphology. The results showed the severe under-estimation of regional precipitation by weather sites (~1150 mm yr⁻¹) in the QYJ Basin, where the runoff depth was as high as ~1450 mm yr⁻¹. The water balance revealed a much higher level of precipitation (~2000 mm yr⁻¹) in the QYJ Basin, but precipitation in the two adjacent basins was contrastingly low (<1000 mm yr⁻¹). The spatial pattern of precipitation was well consistent with the local horn-mouth geomorphology, with more precipitation occurring in the geomorphologically converging and elevating region. Furthermore, within the the QYJ Basin, annual precipitation was larger in the sub-basins (>2200 mm) on or near the bottom of the horn-mouth geomorphology than the others (<1800 mm). With these results, we concluded that the high precipitation level in the QYJ Basin could be attributed to the combined converging and lifting effects of geomorphology on the westward atmospheric vapor. Therefore, flooding risk should be carefully accounted for in the basins with similar geomorphology in the eastern Tibetan Plateau. Full article

A high-resolution 3-D orographic precipitation model (OPM) forced by Climate Forecast System (CFS) reanalysis fields was developed for the Lake Kinneret watershed (Israel-Syria-Lebanon territories). The OPM was tuned to represent the interaction between the advected and stratiform rainfall, and the local orographic enhancement. The OPM evaluation was focused on the densely instrumented lower part of the watershed. To evaluate the ungauged upper-elevation, bias-adjusted precipitation estimates from the Global-Hydro-Estimator were used. The OPM simulates higher rainfall amounts in the upper-elevation watershed compared to currently used rainfall estimates from an elevation dependent regression. The larger differences are during rain events with southwesterly wind flow and high moisture flux. These conditions, according to the OPM, are conducive to enhanced orographic lifting in the Hermon Mountain. A sensitivity analysis indicated that the higher wind speeds for southwesterly–northwesterly trajectories generate significant orographic lifting and increase the precipitation differences between the lower and upper elevations. Full article