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Although many climate predictions suggest that the frequency and intensity of large storm events might increase in the coming decades, few studies document the full impact of such events along their path. Here, we synthesize information on the impact of Hurricane Irene (formed August 21 2011) and Tropical Storm Lee (formed August 30, 2011) on erosion and sediment transport, lake metabolism, riparian hydrology and biogeochemistry, and stream water quality, from North Carolina to Maine. In almost all cases, these storms generated unprecedented changes in water quality (concentrations, loads), from tenfold increases in DOC and 100-fold increases in POC in Maryland, to 100-fold increases in TSS concentrations in Pennsylvania. Overbank flooding and up to 200-year streamflow events were recorded in New York and Vermont. In many cases, particulate loads (e.g. POC, PP, TSS) occurring during Irene and Lee represented more than 30% of the annual load. The dominance of particulate exports over solutes during Irene and Lee is consistent with the mobilization of normally immobile sediment pools, and massive erosion as reported at many locations across the Northeastern US. Several studies reported long lasting (> 1 year) effects of Irene and Lee on cyanobacterial blooms, erosion, or stream suspended sediment concentrations. However, this review also highlighted the lack of a consistent strategy in terms of methods, and measured water quality parameters. This strongly hinders our ability to fully assess the largescale impact of such events on our environment, and ultimately their impact on our economy and society.

The Indian Ocean tsunami in 2004 revealed the inferiority of hard engineering solutions in coastal protection and provided sound evidence over the potential of coastal vegetation, particularly mangroves in protecting the coast against erosion, tropical storm surges, and occasional natural calamities like tsunamis. The present study was initiated therefore to determine the extent to which mangroves could be used to protect the coasts against damage by tsunamis. The structure of mangrove vegetation at Kirinda, Kalametiya, and Rekawa in Sri Lanka that resisted tsunami waves for varying extents in 2004 was studied in detail to discern the wave attenuation function of mangrove vegetation. Vegetation structure is a salient factor that contributes to reduction of the impact of natural disturbances to which mangrove ecosystems are vulnerable. The current study highlights that mangrove parameters such as canopy, trunk, and complex root system and wave parameters such incident wave height and inundation distance play vital role in mangroves-induced wave attenuation. The study found that tsunami run-up height and tsunami inundation distance were negatively correlated with tree volume, forest width and tree height whereas that was positively correlated with porosity of the mangrove vegetation. Depth of sedimentation caused by tsunami waves decreased across the mangrove vegetation from the proximal end (in relation to the advancing wave) to the distal end at all mangrove study sites indicating the progressive dissipation of energy of the wave. The mangrove plant communities comprised of Avicenni a marina, Ceriops tagal, Excoecaria agallocha and, Rhizophora mucronata evidently, have served as natural coastal barriers and contribute to mitigate impacts of natural disturbances such as tsunamis and tropical storms. As such our study revealed that the effectiveness of coastal bio-shields is based on the make-up of the coastal forests.

On August 14, 2021, a Mw 7.2 earthquake struck the Tiburon Peninsula of western Haiti triggering thousands of landslides. Three days after the earthquake on August 17, 2021, Tropical Storm Grace crossed shallow waters offshore of southern Haiti triggering more landslides worsening the situation. In the aftermath of these events, several organizations with disaster response capabilities or programs activated to provide information on the location of landslides to first responders on the ground. Utilizing remote sensing to support rapid response, one organization manually mapped initiation point of landslides and three automatically detected landslides. The 2021 Haiti event also provided a unique opportunity to test different automated landslide detection methods that utilized both SAR and optical data in a rapid response scenario where rapid situational awareness was critical. As the methods used are highly replicable, the main goal of this study is to summarize the landslide rapid response products released by the organizations, detection methods, quantify accuracy and provide guidelines on how some of the shortcomings encountered in this effort might be addressed in the future. To support this validation, a manually mapped polygon-based landslide inventory covering the entire affected area was created and is also released through this effort.

Tropical storm Isaias (2020) moved quickly northeast after its landfall in North Carolina and caused extensive damage to the east coast of the United States, with electric power distribution disruptions, infrastructure losses and significant economic and societal impacts. Improving the real-time prediction of tropical storms like Isaias can enable accurate disaster preparedness and strategy. We have explored the configuration, initialization and physics options of the Weather Research and Forecasting (WRF) model to improve the deterministic forecast for Isaias. The model performance has been evaluated based on the forecast of the storm track, intensity, wind and precipitation, with the support from in situ measurements and stage IV remote sensing products. Our results indicate that the Global Forecasting System (GFS) provides overall better initial and boundary conditions compared to the North American Model (NAM) for wind, mean sea level pressure and precipitation. The combination of tropical suite physics options and GFS initialization provided the best forecast improvement, with error reduction of 36% and an increase of the correlation by 11%. The choices for model spin-up time and forecast cycle did not affect the forecast of the storm significantly. In order to check the consistency of the result found from the investigation related to TS Isaias, Irene (2011), Henri (2021) and Elsa (2021), three other tropical storms, were also investigated. Similar to Isaias, these storms are simulated with NAM and GFS initialization and different physics options. The overall results for Henri and Elsa indicate that the models with GFS initialization and tropical suite physics reduced error by 44% and 57%, respectively, which resonates with the findings from the TS Isaias investigation. For Irene, the initialization used an older GFS version and showed increases in error, but applying the tropical physics option decreased the error by 20%. Our recommendation is to consider GFS for the initialization of the WRF model and the tropical physics suite in a future tropical storm forecast for the NE US.

The vertical profile of the wind structure of translating tropical cyclones, including the associated azimuthal asymmetry, has been the subject of existing theoretical and observational studies using dropsondes. Most of these studies are based on data collected from relatively strong cyclones over the Atlantic. Here we explore the tropical cyclone boundary layer wind profile of mainly relatively weak landfalling cyclones near Hong Kong. We find that decaying tropical storms have a much larger mid‐ to low‐level inflow angle than those that are intensifying or in steady‐state. The inflow angles of intensifying, steady‐state and decaying tropical storms converge towards the top of the boundary layer. The wind speed reduces through the boundary layer in a similar way in all three cases. The combination of these factors means that decaying tropical storms have stronger inflow than intensifying and steady‐state ones. We attribute these local effects to remote enhanced surface friction over land when the storms are weakening. Decaying tropical storms have a much larger mid‐ to low‐level inflow angle than those that are intensifying or in steady‐state but are similar towards the top of the boundary layer. On the other hand, the wind speed reduces through the boundary layer in a similar way in all cases—intensifying, steady‐state and decaying tropical storms. We attribute these local effects, which combine to give decaying tropical storms stronger inflow than intensifying and steady‐states ones, to remote enhanced surface friction over land when the storms are weakening.

This paper presents a re-analysis of the track and the intensity of tropical cyclone Senyar, an unprecedented tropical cyclone that formed over the Strait of Malacca south of 5 degrees North, moving eastwards towards the South China Sea. This cyclone brought about heavy rainfall, severe flooding and landslides to southern Thailand, Malaysia and Indonesia, and this re-analysis helps document such a special and disastrous storm. Some key meteorological observations are presented to support the re-analysis, including weather radar imageries and surface weather observations. Forecasting aspects of Senyar by medium-range models and a sub-seasonal model are also presented. It turns out that both the numerical weather prediction model and the artificial intelligence model manages to resolve the warm core structure of the cyclone, but the sub-seasonal forecast fails to capture the occurrence of this very rare storm even with a forecast time of one week ahead. The formation of Senyar is found to be related to the terrain of Malay Peninsula and Sumatra, as revealed by a number of numerical simulations using a mesoscale meteorological model with different modifications of the terrain. This may be related to the lee low downstream of the terrain of Malay Peninsula under the prevailing northeasterly flow.

Atlantic tropical cyclones often associate with heavy rainfall, which causes inland- and coastal-flooding in the United States, and the storm-induced rainfall is closely related to its storm scale, movement, and location. For a better performance in flood or risk analysis in a region, understanding the characteristics and distribution of tropical storm (TS) induced extreme rainfall is essential. This study proposes dimensionless rainfall-duration curves for designated four-quartile storms that represents the temporal distribution of TS induced extreme rainfall in the Gulf of Mexico from 1979 to 2021. Our study employs spatiotemporal analysis to compute rainfall while TSs are located overseas and inland from satellite based climate forcing data and hurricane track records, annual maximum approach to define TS induced extreme rainfall events, and designated track types to categorize events based on their trajectories. As a result, extreme rainfall relating to TSs in the Gulf of Mexico are found to be considerably higher in inland than overseas. For inland, majority of the TSs was found to be the 1st- and 2nd-quartile storms. However, the 3rd-quartile storms, which case are rare, were found to have the overall largest amount of rainfall per duration compared to the other quartile storms. As for overseas, more than half of the TSs were found to be the 4th-quartile storm while the 2nd-quartile storm has higher overall rainfall per duration. Spatial analysis shows that Texas, Louisiana, Mississippi, Florida, and South Carolina are determined as high-threatened areas by TS induced extreme rainfall.

Cheng, J. and Wang, P., 2022. Factors controlling storm-induced morphology changes at an erosional hot spot on a nourished beach, Sand Key barrier island, west-central Florida. Journal of Coastal Research, 38(4), 750–765. Coconut Creek (Florida), ISSN 0749-0208. Beach nourishment has become the dominant sandy shore protection method over the past 40 years. The performance of nourished beaches and therefore the design of renourishment projects are significantly controlled by the presence of erosional hot spots and storm impacts. Based on 5.5-year bimonthly beach profile surveys, along a nourished beach spanning an erosional hot spot, this study examines the hydrodynamic conditions of extratropical (winter) and tropical (summer) storms that cause significant morphology changes. The sand volume loss above the short-term closure depth averaged along the 1.8-km stretch erosional hot spot was 178 m3/m over the 5.5 years after the nourishment. A large portion of this volume loss was caused by several extratropical storms and Hurricane Irma in 2017, when the high, northerly approaching waves were associated with a depressed water level. The northerly approaching waves induced a large longshore sediment transport gradient along the generally north-south trending coast due to wave refraction over a nearby ebb tidal delta. The energetic Hurricane Irma induced a large negative surge and also transported sediment seaward beyond the short-term closure depth. On the other hand, during the passages of typical tropical storms, the southerly approaching waves superimposed on elevated water levels caused substantial beach volume loss above the mean sea level. The eroded sediment deposited on the nearshore sandbar, resulting in conserved sand volume above the short-term closure depth. Understanding the different beach response to extratropical and tropical storms would benefit beach management, especially under the circumstance of increasing storm activities due to climate change.

Liu, H.; Deng, J., and Wu, J., 2023. Benthic turbulence affected by various wave conditions in the surf zone. Journal of Coastal Research, 39(6), 1082–1093. Charlotte (North Carolina), ISSN 0749-0208. To understand turbulence and associated sediment transport in the surf zone, it is of crucial importance to explore the effect of wind waves consisting of non-breaking (low) and breaking (moderate) waves. A bottom-mounted instrumental tripod was deployed on a dissipative beach in the surf zone in the south China coast to examine the relative importance of wave-induced turbulence and bed-induced turbulence in the different hydrodynamic conditions. The data were collected in 0.5–3 m water depth from 20–29 July 2016. During the survey, a tropical storm attacked the nearby coast from 26–27 July. The Synchrosqueezed Wavelet Transform method was used to decompose the wave and turbulent data. The results show that the bed-generated turbulence dominated with weak wind waves during neap tide. The Reynolds shear stresses and turbulent kinetic energy was almost vertically uniform in this period. On the contrary, the degree of turbulence anisotropy became weak and various turbulence properties or scaling (e.g., Reynolds shear stresses, turbulent kinetic energy, dissipation rate, Froude-scaled turbulence) enhanced significantly with moderate waves during spring tide and storm period. The turbulent properties increased in magnitude away from the bed beneath waves breaking. The observations suggest that breaking waves are the dominant source of turbulence under strong onshore winds, which are significant and may dominate over bottom boundary layer process in the surf zone.

Background Limited evidence is available about the association between tropical cyclones and dengue incidence. This study aimed to examine the effects of tropical cyclones on the incidence of dengue and to explore the vulnerable populations in Guangzhou, China. Methods Weekly dengue case data, tropical cyclone and meteorological data during the tropical cyclones season (June to October) from 2015 to 2019 were collected for the study. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model was conducted to quantify the association between tropical cyclones and dengue, controlling for meteorological factors, seasonality, and long-term trend. Proportion of dengue cases attributable to tropical cyclone exposure was calculated. The effect difference by sex and age groups was calculated to identify vulnerable populations. The tropical cyclones were classified into two levels to compare the effects of different grades of tropical cyclones on the dengue incidence. Results Tropical cyclones were associated with an increased number of dengue cases with the maximum risk ratio of 1.41 (95% confidence interval 1.17–1.69) in lag 0 week and cumulative risk ratio of 2.13 (95% confidence interval 1.28–3.56) in lag 0–4 weeks. The attributable fraction was 6.31% (95% empirical confidence interval 1.96–10.16%). Men and the elderly were more vulnerable to the effects of tropical cyclones than the others. The effects of typhoons were stronger than those of tropical storms among various subpopulations. Conclusions Our findings indicate that tropical cyclones may increase the incidence of dengue within a 4-week lag in Guangzhou, China, and the effects were more pronounced in men and the elderly. Precautionary measures should be taken with a focus on the identified vulnerable populations to control the transmission of dengue associated with tropical cyclones. Graphical Abstract