Wind Direction Research Articles

Bias correction of the hourly satellite precipitation product using machine learning methods enhanced with high-resolution WRF meteorological simulations

Accurate precipitation data are crucial in atmospheric and hydrological studies, especially for water resource management and disaster early warning. Satellite precipitation product (SPP) with high spatiotemporal resolution has been regarded as a valuable alternative precipitation source to ground observations. However, the hourly SPP generally performs poorly compared to daily SPP, thereby bias correction is urgently required. This study investigates the viability of utilizing machine learning methods to correct the bias of the hourly Integrated Multi-satellitE Retrievals for Global Precipitation Measurement-Early (IMERG-E) product. Meanwhile, the Weather Research and Forecasting (WRF) model is utilized to generate high-resolution fields of four hourly meteorological variables, namely, temperature at 2 m (TEMP2), specific humidity at 2 m (Q2), wind direction at 10 m (WDIR10), and wind speed at 10 m (WSPD10), which further serve as covariates in machine learning models to enhance the correction process. Four machine learning models were developed, i.e., Random Forest (RF) and Bidirectional Long Short-Term Memory Networks (Bi-LSTM) without WRF-simulated covariates, and RF-WRF and Bi-LSTM-WRF with meteorological covariates. The results demonstrated that incorporating WRF-simulated meteorological covariates improved model performance. Specifically, correlation coefficient (CC) values increased from 0.47 (RF) to 0.51 (RF-WRF) and rose from 0.55 (Bi-LSTM) to 0.60 (Bi-LSTM-WRF), along with reduced root mean square error (RMSE) and increased critical success index (CSI) values. Furthermore, two Bi-LSTM models consistently outperformed two RF models. Overall, the Bi-LSTM-WRF model emerged as the most effective correction method, which increased CC from 0.43 (IMERG-E) to 0.60, reduced RMSE from 1.91 mm to 1.08 mm, and enhanced CSI from 0.34 to 0.41. This study underscores the potential of integrating high-resolution WRF meteorological outputs into machine learning frameworks for correcting hourly SPPs, contributing significantly to the advancement of precipitation estimation in meteorological and hydrological applications.

Dynamic performance of a supertall building with an active tuned mass damper system during Super Typhoon Saola

This paper investigates the dynamic characteristics (natural frequencies and damping ratios) of a 600-m-tall supertall building with an active tuned mass damper (ATMD) system during Super Typhoon Saola. Based on the wind speed, wind direction, and wind-induced acceleration response records by the structural health monitoring (SHM) system installed on the skyscraper, the wind characteristics during the passage of Saola are first investigated, and the relations between the mean wind speeds atop the skyscraper and the root-mean-square (RMS) acceleration responses are established. Then, employing the stochastic subspace identification (SSI) method and an uncertainty quantification method, this paper comprehensively investigates the uncertainty bounds, time-varying features, and amplitude-dependency characteristics of the modal parameters with and without the operation of the ATMD system. Next, on the basis of the identified modal parameters and time-frequency analysis, the performance and effectiveness of the ATMD system in suppressing the wind-induced vibrations of the skyscraper is investigated. Lastly, the structural health condition is evaluated from the perspective of building natural frequency and damping ratio changes before and after the typhoon hit. The goal of this study is to advance the understanding of the wind effects on supertall buildings and provide useful information for the wind-resistant design and vibration control of supertall buildings in tropical cyclone-prone regions.

Intelligent evaluation of interference effects between tall buildings based on wind tunnel experiments and explainable machine learning

The interference effects of taller high-rise buildings significantly impact the nearby shorter high-rise buildings in dense urban areas, potentially leading to severe wind-induced disasters. This study aims to develop a universal intelligent assessment method to predict the aerodynamic forces and wind-induced responses of buildings, considering various interfering and coupling factors. A database containing 61440 samples is established through a series of synchronous pressure measurement wind tunnel tests. The aerodynamic forces and wind-induced responses were predicted using six machine learning models under varying wind fields, interfering building locations, interfering building sizes, and dynamic characteristics of the principal building. The performance of the models was enhanced through Bayesian hyperparameter optimization and evaluated using the R2 and NRMSE. Additionally, the SHapley Additive exPlanations (SHAP) method was applied to evaluate the impact of each factor on the aerodynamic force and wind-induced response coefficients. Eight specific cases were examined using local SHAP explanations to explore the influence of seven input variables on maximum wind-induced response coefficients. Results indicated that the XGB model exhibited superior predictive performance, with R2 exceeding 0.99 in both training and testing sets. The SHAP analysis revealed significant impacts from wind direction angle, reduced wind speed, and damping ratio on wind-induced response. Consequently, irrelevant or minimally impactful input variables were removed from the XGB models. The R2 and NRMSE variation rate with reduced inputs for the optimized XGB model was less than 0.45 %. The graphical user interface (GUI) was designed can effectively guide intelligent urban planning and building design.

High-Resolution WRF Modeling of Wind and Thermal Regimes with LCZ in Almaty, Kazakhstan

This study evaluates the effectiveness of the Weather Research and Forecasting (WRF) model in simulating high-resolution atmospheric conditions for Almaty, Kazakhstan, a city prone to stagnant winter air. While the previously used Bougeault and Lacarrere scheme for parameterizing the planetary boundary layer was applied in high-resolution modeling, the number of vertical levels was increased, and a detailed local climate zones (LCZs) map was included. Ground-based observations from meteorological stations and monitoring stations, remote sensing data, and radiosonde measurements are used to verify the model. Comparison results with ground-based observations show that the WRF model with the LCZ map provides a better representation of the wind and thermal regimes of Almaty compared to the three-class land use map, including in high resolution. A good correspondence of wind direction is demonstrated by comparing the modeling results with pollutant transport plumes recorded by remote sensing data. In addition, a good correlation was found between land surface temperature from satellite data and air temperature simulated by WRF with a resolution of 333 m. A comparison of simulated data and aerological measurements confirmed that downscaling did not have a significant impact on boundary layer calculations. Analysis of turbulent processes showed that the adopted model effectively describes the attenuation and dissipation of turbulent kinetic energy and reflects the typical diurnal variations of meteorological processes in the atmosphere of Almaty in the anticyclonic winter period. The results of high-resolution WRF modeling can form the basis for the development of a hybrid system capable of modeling atmospheric processes at the building level.

Exploring technology options for future wind energy converters

This analysis aims to identify appropriate technology options for wind energy converters across all sizes by matching the sizes of the primary mover and the time scales of the extraction and conversion processes to the wind conditions as quantified by mean winds and turbulence intensity. The approach was to set out the options in a process tree and then group technology options according to common characteristics which can be used to estimate productivity in wind scenarios characterised by the wind speed, wind direction and turbulence statistics.

Machine learning-based predicting of PCM-integrated building thermal performance: An application under various weather conditions in Morocco

As is now stands, the building sector is among the “big three” significant energy consumer and greenhouse gas contributor in the world. Consequently, there has been a growing movement towards the development and adoption of renewable energy sources, energy efficient measures and energy management strategies. Phase change materials (PCMs) are considered as an alluring option for energy efficiency measures in building. In this paper, a case study building, based on typical residential construction in Morocco, was selected to assess the potential energy savings of adding PCM to the roof for twenty-four cities using the dynamic simulation tool, TRNSYS. Thereafter, thirteen machine learning techniques, including ANN, DT, SVM, ELM, GB, RF, TB, GLRM, GPR, LR, GAM, KRRM and LRR were assessed for predicting the hourly heating, cooling, and total energy consumptions. The models were trained and tested on a dataset that was gathered from the simulations in twenty-four locations in Morocco. The outdoor dry-bulb temperature, the relative humidity, the wind velocity, the wind direction, and the total solar radiation were considered as the key features. The obtained results revealed that using PCM, can effectively lower the total energy demand for all the cities under study, with exception for very cold climate given by Ifrane and Midelt, where the annual total energy consumption shows an increasing trend. Furthermore, comparing the statistical results for each machine learning model, it is found that the SVM model consistently outperforms all models and can be successfully employed to predict the hourly network's outputs of the building.

Natural ventilation potential of teaching building complexes with different block shapes and layout patterns

Natural ventilation significantly enhances building energy efficiency and indoor air quality, thereby reducing virus transmission risks, especially crucial in teaching buildings on university campuses frequently occupied by large numbers of students. This study investigates the design impacts of teaching building complexes on indoor and outdoor wind environments, aiming to propose practical design recommendations. Firstly, a typological analysis of teaching building complexes from ten universities in Guangzhou University Town (GUT) was conducted, screening out several archetypes representing diverse design features. Computational fluid dynamics (CFD) simulations were then performed on 16 hypothetical teaching building complexes derived from these archetypes. The wind velocity distributions and area-weighted wind velocities across various hypothetical scenarios were compared and analyzed, allowing for a thorough assessment of the natural ventilation performance associated with different block shapes and layout patterns. The findings reveal that canyons between buildings have a marginal impact on natural ventilation within scenarios characterized by aligned layouts. In contrast, staggered layouts notably enhance natural ventilation, particularly with orthogonal prevailing winds. Furthermore, semi-enclosed courtyard blocks outperform fully enclosed courtyard blocks in natural ventilation, especially when their openings align with prevailing wind directions. Finally, several practical recommendations were summarized for achieving sustainable teaching building design in similar climate regions. Key contributions include demonstrating the significant influence of block shape and layout on ventilation performance and offering novel insights into optimizing building designs for improved natural ventilation.

Evaluating the impact of evolving green and grey urban infrastructure on local particulate pollution around city square parks

The relationship between green and grey urban infrastructure, local meteorological conditions, and traffic-related air pollution is complex and dynamic. This case study examined the effect of evolving morphologies around a city square park in Dublin and explores the twin impacts of local urban development (grey) and maturing parks (green) on particulate matter (PM) pollution. A fixed air quality monitoring campaign and computational fluid dynamic modelling (ENVI-met) were used to assess current (baseline) and future scenarios. The baseline results presented the distribution of PM in the study area, with bimodal (PM2.5) and unimodal (PM10) diurnal profiles. The optimal vegetation height for air quality within the park also differed by wind direction with 21 m vegetation optimal for parallel winds (10.45% reduction) and 7 m vegetation optimal for perpendicular winds (30.36% reduction). Increased building heights led to higher PM2.5 concentrations on both footpaths ranging from 25.3 to 37.0% under perpendicular winds, whilst increasing the height of leeward buildings increased PM2.5 concentrations by up to 30.9% under parallel winds. The findings from this study provide evidence of the importance of more in-depth analysis of green and grey urban infrastructure in the urban planning decision-making process to avoid deteriorating air quality conditions around city square parks.

Spatiotemporal Distribution Characteristics of Ground-level-ozone and Its Relationship with Meteorological Conditions in a Representative City in the Bohai Rim from 2017 to 2022

In recent years, ground-level-ozone（O3） pollution in urban areas in the Bohai Rim has attracted wide attention. Based on the analysis of the spatiotemporal distribution characteristics of O3 concentration in Dongying, a representative city in the Bohai Rim from 2017 to 2022, the effects of meteorological factors and sea-land breeze circulation on O3 concentration were evaluated. The results showed that： ① From 2017 to 2022, the annual assessment value of O3 concentration in Dongying showed a fluctuating upward trend, and the pollution days with O3 as the primary pollutant increased. O3 pollution mainly occurred in spring, summer, and autumn, with the most severe O3 pollution episodes typically occurring in May and June, and the duration of O3 pollution season tended to be longer. The monthly variation in the daily maximum 8-h average ozone （MDA8 O3） presented a bimodal distribution, with significant increases in the 5th and 25th percentiles, and the spatial distribution was "high in the north and south, low in the middle." In addition, the nocturnal O3 concentration in recent years in Dongying also showed a significant increase trend. ② Meteorological factors greatly influenced O3 concentration in Dongying. When the temperature was greater than 30℃, the relative humidity was less than 50%, and the wind direction was south-southwest or east-northeast, a high O3 value was more likely to occur. Meteorological factors contributed 30% of the MDA8 O3 variation in Dongying during the study period. In the case of moderate and severe O3 pollution, the contribution of meteorological factors to the change in MDA8 O3 could be as high as 40%. ③ To some extent, sea-land breeze contributed to the occurrence of MDA8 O3 exceeding the secondary standard limit value of the National Ambient Air Quality Standard. In the afternoon, the hourly concentration of O3 during the sea-land breeze days was approximately 20 μg·m-3 higher than that during the non-sea-land breeze days. On the days of moderate and severe O3 pollution, the O3 concentration during the sea-land breeze days from 10：00 to 16：00 was higher than that during non-sea-land breeze days, and the O3 concentration was also at a high level from 20：00 to 23：00 on sea-land breeze days. In the O3 pollution season, the sea-land breeze could significantly affect the O3 level in coastal cities, which could bring significant challenges for O3 pollution prevention and control in this region. In the future, cities in the Bohai Rim need to further strengthen regional joint prevention and control of O3 pollution and increase emission reduction efforts of nitrogen oxides and volatile organic compounds. This strategy could effectively lower pollutant concentrations within the land breeze air mass, consequently reducing the impact of the sea breeze air mass on air quality in cities in the Bohai Rim.

Near‐surface wind profiles from numerical model predictions. Part II: Verifications against Australia‐wide surface wind observations

AbstractThe new scheme for deriving the near‐surface wind profiles discussed in Ma (in review) is applied to an Australian Bureau of Meteorology operational convective scale model over various domains. Both the new and conventional schemes' diagnostic 10‐m winds are then verified against Australia‐wide automatic weather station observations. Analyses of bulk statistics reveal that the new scheme's 10‐m wind forecasts have generally better accuracy than the current conventional scheme with a consistent reduction of biases over all domains. A widely recognised diurnal bias pattern of surface wind speed over the land is substantially reduced, and the inclusion of Ekman spiral effect on the 10‐m wind marginally improves statistics of the wind direction during the nighttime. The new scheme introduces no systemic bias, given the histogram of a bulk mean bias is analogiased to a Gaussian distribution, and moves the distribution of diagnostic wind speed closer to that observed.

Pollutant cross-transmission in courtyard buildings: Wind tunnel experiments and computational fluid dynamics (CFD) evaluation

Courtyards, a historical architectural feature surrounded by buildings, are common in urban housing and residential complexes. These spaces, often open-air and with rooms facing them, are crucial for daylight and natural ventilation. While courtyards are essential for introducing fresh airflow into adjacent indoor areas, the effectiveness of natural ventilation may be compromised due to potentially poor air circulation from limited openings. This raises a significant concern: could the design of courtyards inadvertently facilitate pollutant cross-transmission? Despite a wealth of research focused on airflow within courtyards, the indoor spaces in proximity to these courtyards have often been neglected in previous works, particularly concerning the exchange of pollutants between the indoor and courtyard environment. This research investigates the dynamics of indoor-outdoor pollutant cross-transmission in courtyard buildings, assessing factors like external wind flow patterns and internal pollutant sources. Wind tunnel experiments were conducted to measure internal pressure and CO2 concentration and to validate a computational model of the courtyard with 12 rooms. The validated Computational Fluid Dynamics (CFD) models were used to simulate the dispersion of pollutants from internal rooms under different wind conditions. The results showed that the k-epsilon Realizable model accurately simulated internal surface pressure distribution and pollutant dispersion in the courtyard building. It was observed that when pollutants were released from the downwind east-facing ground floor room, CO2 concentrations in adjacent side rooms on the same floor were significantly higher, increasing from the baseline of 400 ppm and reaching up to 3211 ppm in the north-facing room at a wind speed of 4.51 m/s and wind direction of 0°. Conversely, when pollutants originated from north- and south-facing side rooms, pollutants were minimally dispersed to adjacent rooms. Furthermore, at a wind direction of 45°, pollutants from wind-exposed rooms predominantly dispersed to downwind rooms, with peak concentrations exceeding 2400 ppm in downwind rooms. These findings demonstrate that pollutant dispersion is highly dependent on wind direction and the location of the pollutant source. The study concludes that while courtyards enhance indoor environmental quality through natural ventilation, their design must be carefully considered to prevent unintended pollutant cross-transmission, particularly under varying wind conditions and pollutant source locations.

About Height of the Surface Air Layer by Sodar Data

Average empirical estimations of the surface air layer height in Moscow have been received by the data of long-term acoustic remote sensing of the atmosphere using MODOS Doppler sodar of METEK (Germany) production. Based on the assumption that the average conditions are close to neutral stratification, this height, as the top of the quasi-linear section of the average long-term wind velocity profile in semi-logarithmic coordinates, is 40–60 m. The wind rotation height, i. e. the height of intersection of day and night wind profiles is on average 95 meters per year. The roughness length in conditions of loose but high urban development in vicinity of Moscow State University in Moscow is 5 m. According to the criterion of the constant wind direction in the surface air layer, its height appears in the average monthly wind direction profiles over the “dead zone” of the sodar (40 m) in approximately one case out of three and usually amounts to 60 m, less often 80 or 100 m. In the rest cases, it is apparently masked by “dead zone”. The average height of the surface layer according to this approach is probably a little less than 50 m, which is close to the estimate obtained from the logarithmic distribution of wind velocity with height in this layer. The daily course of the surface air layer height is noted by the largest values in the afternoon (80–100 m in summer under conditions of prevailing unstable stratification and 60–80 m in winter) and the smallest ones (less than 40 m) in the late evening and at night in summer and from evening to noon in winter.

Fire behavior simulation of Xintian forest fire in 2022 using WRF-fire model

IntroductionThe behavior of forest fire is a complex phenomenon, and accurate simulation of forest fire is conducive to emergency response management after ignition. In order to further understand the characteristics of forest fire spread and the applicability of WRF-Fire in China, which is a coupled fire-atmospheric wildfire model, this study simulated a high-intensity forest fire event that occurred on October 17, 2022 in Xintian County, southern Hunan Province.MethodsBased on the fire-atmosphere coupled WRF-Fire model, we used high-resolution geographic information, meteorological observation and fuel classification data to analyze the forest fire behavior. At the same time, the simulation results are compared with the fire burned area observed by satellite remote sensing forest fire monitoring data.ResultsThe study found that, the simulated wind speed, direction and temperature trends are similar to the observation results, but the simulated wind speed is overestimated, the dominant wind direction is N, and the temperature is slightly underestimated. The simulated wind field is close to the actual wind field, and the simulation results can show the spatial and temporal variation characteristics of the local wind field under complex terrain while obtaining the high-resolution wind field. The simulated fire burned area is generally overestimated, spreading to the north and southwest compared with the observed fires, but it can also capture the overall shape and spread trend of the fire well.DiscussionThe results show that the model can accurately reproduce the real spread of fire, and it is more helpful to forest fire management.

Simulation of Water Isotopes in Combustion‐Derived Vapor Emissions in Winter

AbstractWith urbanization, anthropogenic water vapor emissions have become a significant component of the urban atmosphere. Fossil fuel combustion‐derived vapor (CDV) is a primary source of these emissions. Owing to the notably low CDV d‐excess, stable hydrogen and oxygen isotopes are promising for distinguishing CDV from natural sources. Considering the limitations of in situ observations, this study aims to explore the feasibility of using IsoRSM, an isotopically enabled regional atmospheric model, to simulate CDV emissions in urban areas in winter. Two experiments were conducted: one in Salt Lake City (SLC) in January 2017 and another in Beijing in January 2007. The simulation results showed that the CDV addition significantly reduced the water vapor d‐excess, particularly when the boundary layer was stable. The simulation with CDV emissions aligned better with the time series of in situ observations in SLC. The modification led to a more pronounced positive correlation between vapor d‐excess and specific humidity, which was similar to the observation of SLC. The CDV inclusion significantly increased the vapor d‐excess variability with varying wind directions in both sites. However, in Beijing, the underestimation of d‐excess variation from natural sources caused a bigger discrepancy between the observed and simulated d‐excess and CDV fraction. Thus, though there were still biases, the inclusion of CDV could improve the accuracy of isotopic simulation in the urban regions where CDV was one of the controlling factors of vapor d‐excess.

Simulation of Ship Berthing Operation at Luojing Container Terminal Under Extreme Sea Conditions

The Luojing Port Area of the Port of Shanghai, specifically the coal terminal and ore terminal, used to be the main port area for coal and ore bulk cargo transportation services in the Port of Shanghai.To enhance the container handling capacity at Shanghai port, this study conducted a series of simulation tests at Luojing Container Terminal. The tests were designed according to the terminal's specifications, taking into account the limit berthing wind direction and wind speed (levels 6 and 7). This study selected an appropriate representative ship type for the comprehensive simulation tests, and it thoroughly tested the berthing limits under various extreme conditions using an advanced navigation simulator. The experiment obtained the motion parameters and trajectory of the simulated ship. Based on these results, this study analyzed and evaluated the safety of the rotary waters and berthing operations, ensuring they met the safety assessment requirements for wharf engineering. The study examined the berthing time window, berthing mode, boundary conditions, and safety guarantee measures under extreme sea conditions at Luojing Container Terminal. Finally, By analyzing the berthing simulation trajectory diagrams, tugboat usage, and vessel maneuvering data under the eight extreme berthing conditions, this study formulated a safe berthing plan for ships.

Observed Impacts of Ground-Mounted Photovoltaic Systems on the Microclimate and Soil in an Arid Area of Gansu, China

Ground-mounted photovoltaic (GMPV) systems are a crucial component of photovoltaic (PV) applications, and their environmental impacts during large-scale development require thorough attention. This study conducted continuous observations at a GMPV plant in an arid region, employing a three-site comparative monitoring system to assess the environmental impact of both shaded and non-shaded areas within GMPV systems. The parameters measured included atmospheric temperature (AT), relative humidity (RH), soil temperature (ST), soil water content (SWC), and wind speed. The results revealed significant diurnal and seasonal variations in AT, with daytime warming and nighttime cooling ranging from 0.1 to 0.7 °C, with particularly large variations observed during high-temperature seasons. Shaded areas under the PV panels exhibited increased RH at night and decreased RH during the day, along with a cooling effect on ST, with a maximum reduction of 7 °C. SWC was higher in shaded areas during dry seasons but exhibited complex redistribution patterns during rainy seasons. Wind speed and direction were notably altered, demonstrating a corridor effect. These findings contrast with previous studies that only focused on the environmental assessment of non-shaded areas within PV systems and external areas using two-site monitoring. This study highlights the critical role of shaded areas in understanding the local environmental impacts of PV systems. This comprehensive approach offers deeper insights into how PV systems influence local meteorological and environmental conditions, suggesting that optimized design and placement of PV systems can enhance their ecological benefits and mitigate adverse environmental impacts in arid regions.

Assessing allergy risk from ornamental trees in a city: Integrating open access remote sensing data with pollen measurements

Platanus sp. pl. (plane trees) are common ornamental tree in Poland that produces a large amount of wind-transported pollen, which contains proteins that induce allergy symptoms. Allergy sufferers can limit their contact with pollen by avoiding places with high pollen concentrations, which are restricted mainly to areas close to plane trees. Their location is thus important, but creating a detailed street tree inventory is expensive and time-consuming. However, high-resolution remote sensing data provide an opportunity to detect the location of specific plants. But acquiring high-resolution spatial data of good quality also incurs costs and requires regular updates. Therefore, this study explored the potential of using open access remote sensing data to detect plane trees in the highly urbanized environment of Poznań (western Poland). Airborne light detection and ranging (LiDAR) was used to detect training treetops, which were subsequently marked as young plane trees, mature plane trees, other trees or artefacts. Spectral and spatial variables were extracted from circular buffers (r = 1 m) around the treetops to minimize the influence of shadows and crown overlap. A random forest machine learning algorithm was applied to assess the importance of variables and classify the treetops within a radius of 6.2 km around the functioning pollen monitoring station. The model performed well during 10-fold cross-validation (overall accuracy ≈ 92%). The predicted Platanus sp. pl. locations, aggregated according to 16 wind directions, were significantly correlated with the hourly pollen concentrations. Based on the correlation values, we established a threshold of prediction confidence, which allowed us to reduce the fraction of false-positive predictions. We proposed the spatially continuous index of airborne pollen exposure probability, which can be useful for allergy sufferers. The results showed that open-access geodata in Poland can be applied to recognize major local sources of plane pollen.

Variations in gust factor with wind direction and height based on the measurements from a coastal tower during three landfalling typhoons

Using high-frequency onshore wind data from four different heights of a coastal tower, the variations in gust factor with turbulence intensity, height and wind speed were studied under typhoon conditions. The gust factor increases with increasing turbulence intensity and, most often, can be described by a linear relationship with the turbulence intensity. The gust factor decreases with height and is relatively small compared with those presented in the national codes and other studies. A value of 2.5 is acceptable for the peak factor, which is close to the recommended value of the national code in China. The gust factor increases with increasing wind speed and is also affected by the wind direction. The gust factor has a value to that of previously published results when the wind flows roughly perpendicular to the shoreline, and has a smaller value when the wind flows roughly parallel to the shoreline. The phenomenon is caused by the confinement of shoreline on the sea wave development. Sea waves tend to propagate normal to the shoreline because of the refraction effect. As a result, a shorter roughness length exists in the parallel direction to the shoreline. It can be further explained by the weakness in the momentum flux exchange between the air and sea based on the wave form drag theory when the wind flows parallel to the shoreline.

Distinguishing Extreme Precipitation Mechanisms Associated with Atmospheric Rivers and Nonatmospheric Rivers in the Lower Yangtze River Basin

Abstract This study investigates the disparity in quantitative moisture contribution and synoptic-scale vertical motion in the lower reaches of the Yangtze River basin (LYRB) for different extreme precipitation (EP) types, which are categorized as EP associated with atmospheric river (AR&EP) or EP associated with nonatmospheric river (non-AR&EP). To analyze moisture contribution, backward tracking using the Water Accounting Model-2layers is performed. In general, the remote moisture contribution is 9.7 times greater than the local contribution, with the ocean contribution being 1.67 times stronger than the land contribution. However, terrestrial and oceanic contributions obviously increase in the EP types, especially for oceanic contribution being double in magnitude. Notably, the west Pacific (WP) contribution emerges as the dominant differentia between the EP types, playing a crucial role in the AR formation. By solving the quasigeostrophic omega equation, the upper-level jet (ULJ) stream acts as the primary dynamic forcing for transverse vertical motion in AR&EP, while the baroclinic trough exhibits a relatively weaker influence. However, both systems have a nearly equal impact on vertical velocity in non-AR&EP. The enhanced shearwise elevation in the non-AR&EP type is the response of the stronger upper-level ridge over the Tibetan Plateau (TP), which induces enhanced Q vector, the divergence pointing toward the LYRB. However, the main dynamic difference is the location of ULJ, which serves as the trigger role although weak. Diabatic forcing proves to be the decisive factor for vertical motion development, the difference attributed to the released excessive latent heating with excess moisture contribution from the WP in AR&EP with enhanced precipitation. Significance Statement The main objective of this study is to investigate quantitative moisture contribution by applying Water Accounting Model-2layers and vertical motion attribution using the quasigeostrophic omega equation for extreme precipitation types based on the presence or absence of atmospheric river. Our findings reveal excessive moisture from the west Pacific serving not only as key in atmospheric river formation but also as the primary trigger for intensified diabatic vertical motion, inducing enhanced precipitation. The direction of strong winds in the north of the Tibetan Plateau holds crucial forecasting implications, which determine the location of the upper-level jet stream downstream. The transverse vertical motion, induced by the upper-level jet stream, plays the dominant dynamic role in both extreme precipitation (EP) types.

Tropical Cyclones in Nicaragua: Historical Impact and Contemporary Exposure to Disaster Risk

In tropical regions such as Nicaragua, the population’s vulnerability to hazards has escalated in recent decades. This increase in vulnerability has led to a surge in disasters, particularly those triggered by intense hurricanes. The implications at the national level are still poorly understood. The aim of this article has, therefore, been two-fold. First, to present a historical review of the direct effects of tropical cyclones on society in Nicaragua from 1852 to 2020. Second, to analyze the statistical probabilities of future hurricane-spawned high winds over Nicaragua. Data on cyclones hitting Nicaragua’s coasts were collected, including direct effects, wind speed, pressure, category, direction, and time of landfall. A database was created to classify intensity based on wind speed and frequency. Between 1852 and 2020, Nicaragua experienced 58 tropical cyclones with varying degrees of intensity between September and November. The trajectories of six past hurricanes were considered here regarding the areas that might have been under potential threat. Three zones of influence were delimited along each trajectory according to three wind intensities and the trajectory of these hurricanes. The consequent exposure of each Nicaraguan department and autonomous region was established. The findings are essential to delimitating priority areas for attention regarding the likely impact of tropical cyclones, mainly category 4 and 5 hurricanes. Public officials and the general public can use these data to identify the pressing need for enhanced strategies to mitigate disaster risk and avoid potential disasters.