Search Results (284)

Tropical cyclones kill thousands and inflict vast destruction annually. While ocean temperatures and atmospheric conditions dominate their formation and behaviour, forests’ potential influence has received little systematic attention. This review examines whether and how forests may affect tropical cyclone frequency, intensity, and behaviour. Support varies by mechanism and stage. Post-landfall effects have the strongest support: forests slow storms, moderate wind speeds and curb flooding through enhanced soil infiltration. Forests also influence storm tracks, though magnitudes are uncertain. Pre-landfall effects are less certain. These include processes that modify offshore humidity, temperature, and aerosols. The Biotic Pump theory proposes that forest cover creates pressure gradients drawing moisture inland, reducing its availability for ocean storms. Forest influences are likely to be most evident near thresholds for storm formation or intensification, where small perturbations in conditions can alter outcomes. This context-dependency reconciles divergent findings and aids the integration of forests into climate risk assessments. Forest conservation provides clear post-landfall protection; pre-landfall effects, while uncertain, further strengthen the case for protection and highlight research priorities. Full article

We investigate the multi-layer atmospheric impacts of Typhoon Hagibis (2019), which formed on 6 October, tracked across 12–35° N and 135–155° E, and made landfall on 12 October over the Izu Peninsula, central Honshu, Japan. We present a multi-layer study that involves the troposphere, stratosphere and upper ionosphere to examine the thermodynamic and electromagnetic coupling between these layers due to such extreme weather conditions. Using ERA5 reanalysis, we identify pronounced stratospheric temperature perturbations, elevated atmospheric gravity wave (AGW) potential energy, substantial spatiotemporal variability in the zonal (U) and meridional (V) wind components, relative humidity, and specific rainwater content throughout the cyclone’s evolution. Quantitatively, AGW potential energy increased from background levels of <5 J kg⁻¹ to >40 J kg⁻¹ near the cyclone core, while tropospheric wind anomalies reached $\pm 30$–40 m s⁻¹, accompanied by relative humidity values exceeding 90% and specific rainwater content up to $1.5\times {10}^{-3}$ kg kg⁻¹, indicative of vigorous moist convection and strong vertical energy transport. The ionospheric response, derived from GPS-based Total Electron Content (TEC) at 10 Japanese IGS stations, reveals vertical TEC (VTEC) perturbations whose amplitudes and temporal evolution vary systematically with GPS-station-to-typhoon-eye distance, including clear enhancements and reductions around the closest-approach day. These signatures indicate a measurable ionospheric response to cyclone-driven atmospheric forcing under geomagnetically quiet conditions, confirming that Hagibis produced vertically coupled disturbances linking stratospheric AGW activity with ionospheric electron density variability. Full article

Wind energy has the potential to become an important source of energy for remote Arctic regions. However, there are risks associated with the exposure of coastal wind parks to extremely strong winds caused by storms and polar lows. Extreme winds can either enhance or reduce wind energy production. The outcomes largely depend on the coastal landscape surrounding the wind park. To address these questions, we conducted a series of simulations using the Weather Research and Forecasting (WRF) model. This study focuses on one of the strongest wind events along the western Norwegian coast—the landfall of the storm “Ylva” (24–27 November 2017). The study employs terrain-resolving downscaling by zooming in on the area of the Kvitfjell–Raudfjell wind park, Norway. The terrain-resolving WRF simulations reveal stronger winds at turbine hub height (80 m to 100 m above the ground level) in the coastal area. However, it was previously overlooked that the landfall of an Atlantic storm, which approaches this area from the southwest, brings the strongest winds from southeast directions, i.e., from the land. This creates geographically extensive and vertically deep wind-sheltered areas along the coast. Wind speeds at hub height in these sheltered areas are reduced, while they remain extreme over wind-channeling sea fjords. The novelty and applied value of this study is that it reveals an overlooked opportunity for optimal wind park siting. The coastal wind parks can take advantage of both sustained westerly winds during normal weather conditions and wind sheltering during extreme storm conditions. We found that the Kvitfjell–Raudfjell location is nearly optimal with respect to the extreme winds of “Ylva.” Full article

Climate change intensifies natural disasters, requiring enhanced understanding of urban resilience mechanisms. While green infrastructure’s disaster mitigation role has been established through engineering studies, empirical evidence linking green infrastructure quality to post-disaster economic adaptation remains limited. This study examines whether community-level green infrastructure quality correlates with post-disaster economic adaptation following Hurricane Laura’s August 2020 landfall. [Methods] Using a natural experiment design, we analyzed 247 Census Block Groups in two coastal Texas communities (Galveston and Port Arthur) experiencing differential disaster severity. We employed ordinary least squares regression with SafeGraph foot traffic data to measure economic recovery and satellite-derived Normalized Difference Vegetation Index (NDVI) to measure green infrastructure quality. Results demonstrate that green infrastructure quality significantly correlates with post-disaster adaptation (β = 1.27, p < 0.001), independent of socioeconomic characteristics. The NDVI–severity interaction proved non-significant, indicating consistent associations across impact contexts. These findings suggest that green infrastructure supports resilience universally rather than only in moderate-risk areas. From an environmental justice perspective, equitable distribution may reduce disaster-related inequalities, supporting “bouncing forward” adaptation trajectories. Full article

This study aims to investigate the effects of Chan-Hom (2015) typhoon-induced variations in enthalpy flux (EF) and moisture flux (MF) on intensity variations and rainfall. Chan-Hom (2015) made landfall at Zhoushan, then changed its direction and moved towards Korea. This analysis used ERA5 reanalyzed data, encompassing daily surface latent and sensible heat flux, along with wind measurements at a height of 10 m. Furthermore, wind components and specific humidity data from the 1000–200 hPa level in ERA5 were utilized to compute the MF and MF convergence, in accordance with the equations outlined in the methodology. This study examines the correlation among typhoon intensity, precipitation, MF, and EF. The mechanism by which Typhoon Chan-Hom has caused a decline in sea surface temperature (SST) was analyzed. Typhoons need a higher EF that can affect them before landfall to maintain their intensity. The highest LHF was observed (340 W/m²) prior to typhoon landfall, indicating that LHF responds to intensity-induced wind during Chan-Hom. Typhoon-induced rainfall is mainly controlled by the MF convergence, rather than the typhoon intensity. The spatial and temporal distributions of MF and MF convergence (MFC) during typhoon formation to landfall reveal that the symmetric MFC is dominated by typhoon intensity; a symmetrical structure is observed when the intensity is high. MFC includes wind convergence and moisture advection. Wind convergence dominates the MFC during typhoons, but moisture advection forms at the eyewall. MF during the typhoon’s landfall can relate to the amount of rainfall that occurred over the land. However, the rainfall pattern changed after landfall, and the typhoon changed its direction. SST cooling observed in the study area is mainly due to the upwelling process with strong cyclonic winds. Full article

A two-dimensional ultrasonic anemometer was installed at a height of 20 m on a wind measurement tower in Haiyan Town, Jiangmen, to monitor flow conditions in typhoon Mangkhut (1822) before and after landfall. Mean wind speed, wind direction, turbulence intensity, gust factor, turbulence integral scale, and turbulence power spectral density were derived and analyzed before and after landing. The results show that the central wind speed time history before and after landfall exhibits significant differences, and the mean wind direction undergoes a reverse change of about 180°. The mean downwind and crosswind turbulence intensity before landing were 0.25 and 0.22, respectively, and 0.20 and 0.16 after landing. The associated mean downwind and crosswind gust factors were 1.70 and 0.61 before landing, and 1.55 and 0.46 after. These differences before and after landing are considered significant, and both turbulence intensity and gust factor showed a certain decreasing trend with the increase in wind speed. The relationship between turbulence intensity and gust factor, though somewhat scattered, was basically consistent with the commonly used Ishizaki and Choi empirical formulas. Mean streamwise and crosswind turbulence integral scales before landfall were 218 m and 100 m, respectively, and 198 m and 177 m after. They showed a weak increasing trend with increase in mean wind speed. Power spectra before and after landing were basically consistent. Comparisons with standard forms were inconclusive, though the von Karman spectrum appeared to be slightly superior to the others, particularly as the wind speed and turbulence integral scale increased. Full article

About 16% of typhoons making landfall in China strike Hainan Island, where near-surface extreme winds in dense urban areas exhibit a strong spatiotemporal heterogeneity that is difficult to capture with current observations and mesoscale models. Focusing on Haikou during Super Typhoon Yagi (2024)—the strongest autumn typhoon to hit China since 1949—we developed a multiscale ERA5–WRF–PALM framework to conduct 30 m resolution large-eddy simulations. PALM results are in reasonable agreement with most of the five automatic weather stations, while performance is weaker at the most sheltered park site. Mean near-surface wind speeds increased by 20–50% relative to normal conditions, showing a coastal–urban gradient: maps of weighted cumulative exposure to strong winds (≥Beaufort force 8) show much longer and more intense events along open coasts than within built-up urban cores. Urban morphology exerted nonlinear effects: wind speeds followed a U-shaped relation with both the open-space ratio and mean building height, with suppression zones at ~0.5–0.7 openness and ~20–40 m height, while clusters of super-tall buildings induced Venturi-like acceleration of 2–3 m s⁻¹. Spatiotemporal analysis revealed banded swaths of high winds, with open areas and islands sustaining longer, broader extremes, and dense street grids experiencing shorter, localized events. Methodologically, this study provides a rare, systematically evaluated application of a multiscale ERA5–WRF–PALM framework to a real typhoon case at 30 m resolution in a tropical coastal city. These findings clarify typhoon–city interactions, quantify morphological regulation of extreme winds, and support risk assessment, urban planning, and wind-resilient design in coastal megacities. Full article

FY-4B/GIIRS (Geostationary Interferometric Infrared Sounder) is a new-generation infrared hyperspectral atmospheric vertical sounder onboard a Chinese geostationary meteorological satellite. Its observations with high spatial and temporal resolution play an important role in high-impact weather forecasts. The GIIRS data assimilation module is developed in the GSI (Gridpoint Statistical Interpolation) assimilation system. Super Typhoon Doksuri in 2023 (No. 5) is taken as an example based on this module in this paper. Firstly, the sensitivity of analysis fields to five data thinning schemes at four daily assimilation times from 22 to 28 July 2023 is analyzed: the wavelet transform modulus maxima (WTMM) scheme, the grid-distance schemes of 30 km, 60 km, and 120 km in the GSI assimilation system, and a center field of view (FOV) scheme. Taking the ERA5 reanalysis fields as true, it is found that the mean error of temperature and humidity analysis for the WTMM scheme is the smallest, followed by the 120 km thinning scheme. Subsequently, a 72 h cycling assimilation and forecast experiments are conducted for the WTMM and 120 km thinning schemes. It is found that the root mean square error (RMSE) profiles of temperature and humidity forecast fields with no thinning scheme are the largest at all pressure levels and forecast times. The temperature forecast error decreases after data thinning at altitudes below 300 hPa. Since the WTMM scheme has assimilated more observations than the 120 km scheme, the accuracy of its temperature and humidity forecast fields gradually increases with the forecast time. In terms of typhoon track and intensity forecast, the typhoon intensities are underestimated before landfall and overestimated after landfall for all thinning schemes. As the forecast time increases, the advantage of the WTMM is increasingly evident, with both the forecast intensity and track being closest to the actual observations. Similarly, the forecasted 24 h accumulated precipitation over land is overestimated after typhoon landfall compared with the IMERG Final precipitation products. The location of precipitation simulated by no thinning scheme is more westward overall. The forecast accuracy of the locations and intensities of severe precipitation cores and the typhoon’s outer spiral rain bands over the South China Sea has been improved after thinning. The Equitable Threat Scores (ETSs) of the WTMM thinning scheme are the highest for most precipitation intensity thresholds. Full article

This study analyzes wave data from Typhoons Hinnamnor and Muifa in 2022, improves the traditional one-dimensional wind–wave and swell separation method (PM method), and proposes a wind–wave and swell separation strategy suitable for the Dafeng sea area during typhoon events. Combining this with the WH enables high-precision separation of wind–wave and swell. A numerical model of MIKE21 SW waves was established based on the superposition of the Holland typhoon wind field and the ERA5 background wind field. Furthermore, the study conducts controlled variable experiments through numerical simulations to systematically quantify the differential effects of the maximum wind speed radius (RMW), translation speed, and track geometry. The mathematical model in this study couples MIKE 21 SW and MIKE 21 FM, importing hydrodynamic conditions through FM as key variables into the SW model. This enables real-time data exchange during the computational process, thereby yielding results that better align with physical reality. The results from factorial sensitivity experiments demonstrate that the significant wave height and average period of offshore waves, far from the typhoons, significantly increase with the expansion of the maximum wind speed radius, with wave heights at offshore points reaching a maximum of 7.5 m. Specifically, when the RMW increased by 50%, the wave height increased by 2.5 m. The wave characteristics of landing typhoons are more influenced by terrain effects and the location of typhoon landfall. Additionally, changes in typhoon translation speed lead to a first increase and then a decrease in significant wave height. The typhoon’s path significantly affects the propagation direction and energy distribution of waves. In the Dafeng area, distant typhoons often generate long-period swells, which continuously exert high loads on actual engineering foundations. These findings inform early warning systems and the design of shelf-aware port and coastal infrastructure in northern Jiangsu and similar regions. Full article

To quantitatively assess the storm surge induced by Super Typhoon Doksuri (2023) along the complex coastline of Fujian Province, a high-resolution Finite-Volume Coastal Ocean Model (FVCOM) was developed, driven by a refined Holland–ERA5 hybrid wind field with integrated physical corrections. The hybrid approach retains the spatiotemporal coherence of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis in the far field, while incorporating explicit inner-core adjustments for quadrant asymmetry, sea-surface-temperature dependency, and bounded decay after landfall. A series of numerical experiments were conducted, including paired tidal-only and full storm-forcing simulations, along with a systematic sensitivity ensemble in which bottom-friction parameters were perturbed and the anomalous (typhoon-related) wind component was scaled by factors ranging from 0.8 to 1.2. Static sea-level rise (SLR) scenarios (+0.3 m, +0.5 m, +1.0 m) were imposed to evaluate their influence on extreme water levels. Storm surge extremes were analyzed using a multi-scale coastal buffer framework, comparing two extreme extraction methods: element-mean followed by time-maximum, and node-maximum then assigned to elements. The model demonstrates high skill in reproducing astronomical tides (Pearson r = 0.979–0.993) and hourly water level series (Pearson r > 0.98) at key validation stations. Results indicate strong spatial heterogeneity in the sensitivity of surge levels to both bottom friction and wind intensity. While total peak water levels rise nearly linearly with SLR, the storm surge component itself exhibits a nonlinear response. The choice of extreme-extraction method significantly influences design values, with the node-based approach yielding peak values 0.8% to 4.5% higher than the cell-averaged method. These findings highlight the importance of using physically motivated adjustments to wind fields, extreme-value analysis across multiple coastal buffer scales, and uncertainty quantification in future SLR-informed coastal risk assessments. By integrating analytical, physics-based inner-core corrections with sensitivity experiments and multi-scale analysis, this study provides an enhanced framework for storm surge modeling suited to engineering and coastal management applications. Full article

Louisiana is one of the most disaster-prone states, with hurricanes ranking among the most destructive hazards. Hurricanes impede sustainability by straining hospital infrastructure, overwhelming emergency departments, and disrupting continuity of care. Louisiana’s healthcare system, characterized by high uninsured rates, limited rural access, and notable racial and socioeconomic disparities, is particularly vulnerable during disasters. This research explores trends of mental and respiratory health in Louisiana surrounding Hurricanes Laura (2020), Delta (2020), and Ida (2021). Analysis reveals a substantial increase in admissions after landfall of all three storms, with mental health conditions showing a larger surge than respiratory ones in already-vulnerable communities. Gender disparities were evident, with female patients accounting for a higher percentage across all three hurricanes and across all age groups. The results suggest the importance of considering social determinants of health during disasters and ensuring adequate resources for older populations with complex medical needs, thereby promoting more sustainable health systems. These results underscore how critical preparedness and recovery planning are for hospitals in hurricane-prone areas. Incorporating resilience measures such as reliable power systems, clearer evacuation pathways, and better coordination of post-disaster care can help protect patients and providers in the future. Full article

Tropical cyclones (TCs) induce pronounced sea surface temperature (SST) cooling, which strongly influences their intensity. Accurate prediction of TC intensity is particularly important in coastal regions where landfall occurs. While SST cooling has been extensively studied in the open ocean, its characteristics in coastal seas remain less understood. Using satellite and reanalysis data from 2004 to 2021, this study systematically characterizes SST cooling in China’s coastal seas—the Yellow Sea, East China Sea, Taiwan Strait, and northern South China Sea—and compares the cooling with adjacent offshore regions. Composite analyses of about 6300 TC track points reveal that coastal SST cooling shows significant differences relative to their offshore cooling. Regionally, the Yellow Sea exhibits significantly stronger coastal cooling (−2.5 °C vs. −1.8 °C), whereas the Taiwan Strait shows weaker coastal cooling. Further analyses using a statistical subsampling method reveal that coastal–offshore cooling differences result from the combined effects of TC attributes and pre-TC oceanic conditions, with temperature stratification exerting the dominant control. Furthermore, an increasing trend in coastal cooling is linked to enhanced temperature stratification. These findings highlight the critical role of pre-TC temperature structure in modulating coastal SST responses, with implications for improving intensity forecasts and risk assessments. Full article

Accurate typhoon track forecasting is vital for disaster mitigation in East China, a region frequently impacted by landfalling typhoons. Despite advances in numerical weather prediction, uncertainties remain high, especially within 48 h of landfall, due to complex interactions among tropical cyclones, the subtropical high, and mesoscale systems. This study applies Ensemble-based Sensitivity Analysis (ESA) within a high-resolution regional ensemble prediction system (Shanghai Weather And Risk Model System-Ensemble Prediction System, SWARMS-EN) to investigate forecast uncertainties of three representative typhoons—Gaemi, Bebinca, and Kong-rey—that made landfall in East China in 2024. Our results reveal consistent sensitivity patterns across diverse large-scale environments, particularly around the western flank of the subtropical high and in proximity to nearby low-pressure systems. Track uncertainty was closely tied to fluctuations in the steering flow, notably its zonal component. Moreover, binary typhoon interactions emerged as key drivers of forecast divergence. ESA effectively identified sensitive regions where small initial perturbations exert significant downstream influence on typhoon tracks. This study demonstrates the operational value of ESA for diagnosing forecast error sources and guiding targeted observations. By linking forecast uncertainty to physical mechanisms, this research enhances our understanding of typhoon predictability and supports the development of more adaptive and accurate regional forecasting systems. Full article

Owing to their high vertical resolution, remote sensing data from meteorological satellite hyperspectral infrared sounders are well-suited for the identification, monitoring, and early warning of high-impact weather events. The effective utilization of full field-of-view (FOV) observations from satellite infrared sounders in high-impact weather applications remains a major research focus and technical challenge worldwide. This study proposes a generalized variational retrieval framework to estimate full FOV cloud fraction and precipitable water vapor (PWV) from observations of the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Fengyun-4A (FY-4A) satellite. Based on this method, experiments are performed using high-frequency FY-4A/GIIRS observations during the landfall periods of Typhoon Lekima (2019) and Typhoon Higos (2020). A three-step channel selection strategy based on information entropy is first designed for FY-4A/GIIRS. A constrained generalized variational retrieval method coupled with a cloud cost function is then established. Cloud parameters, including effective cloud fraction and cloud-top pressure, are initially retrieved using the Minimum Residual Method (MRM) and used as initial cloud information. These parameters are iteratively optimized through cost-function minimization, yielding full FOV cloud fields and atmospheric profiles. Full FOV brightness temperature simulations are conducted over cloudy regions to quantitatively evaluate the retrieved cloud fractions, and the derived PWV is further applied to the identification and analysis of hazardous weather events. Experimental results demonstrate that incorporating cloud parameters as auxiliary inputs to the radiative transfer model improves the simulation of FY-4A/GIIRS brightness temperature in cloud-covered areas and reduces brightness temperature biases. Compared with ERA5 Total Column Water Vapour (TCWV) data, the PWV derived from full FOV profiles containing cloud parameter information shows closer agreement and, at certain FOVs, more effectively indicates the occurrence of high-impact weather events. The simplified methodology proposed in this study provides a robust basis for the future assimilation and operational utilization of infrared data over cloud-affected regions in numerical weather prediction models. Full article

Accurate simulation of boundary layer wind field structures is essential for evaluating tropical cyclone (TC) wind hazards and supporting engineering design in coastal regions. However, existing models often assume radially symmetric and homogeneous surface conditions, leading to limited accuracy near landfall where surface roughness varies significantly. This study conducts a comprehensive evaluation of four representative TC boundary layer models of M95, K01, Y21a, and Y21b, under both idealized and real TC case conditions. The idealized experiments are used to clarify the role of vertical advection and turbulent diffusion in shaping the TC boundary layer, while the landfalling case of Typhoon Mangkhut (2018) is simulated to examine the impacts of surface roughness parameterization. Results show that Y21a, which incorporates nonlinear vertical advection, produces stronger and more realistic super-gradient phenomenon than linear models of M95 and K01. Furthermore, the model of Y21b, which accounts for spatially varying drag coefficients and using a terrain-following coordinate system, successfully reproduces the asymmetric wind patterns observed in the WRF simulations during landfall, achieving the highest correlation (R = 0.93). When the spatially varying drag coefficients incorporated into the linear models, their correlation with WRF improved markedly by about 37%. These findings highlight the necessity of incorporating nonlinear advection, dynamic turbulence, and surface heterogeneity for physically consistent TC boundary layer simulations. The results provide valuable guidance for improving parametric wind field models and enhancing TC wind hazard assessments over complex coastal terrains. Full article