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ABSTRACT Hurricanes are natural periodic events that disrupt marine ecosystems along their path, altering the distribution and abundance of organisms. In October 2016, Hurricane Matthew struck the Santa Marta region (Colombia) and impacted its coastal zone, yet there have been insufficient studies to measure its effects. The aim of this study was to assess the impact of Hurricane Matthew on the meiofaunal community in the region. To achieve this, sediment samples were collected from the intertidal zone of three beaches 5 days after the hurricane had passed. The results were compared with previous data collected in October 2014, on the abundance and diversity of taxonomic groups of intertidal meiofauna, as well as physicochemical variables such as granulometry, organic matter in sediments, salinity, and water temperature. Following Hurricane Matthew, the physicochemical variables showed changes due to the effect of the cyclonic surge in the coastal zone. The average organism abundance not only experienced a decline in both abundance and richness but also underwent changes in composition. Nematoda, originally the fourth most abundant group in 2014, became the most dominant taxon post‐hurricane. Conversely, the relative abundance of Copepoda decreased. The total number of recorded taxa was 13, which is close to the 15 previously reported. The ANOSIM and PERMANOVA tests confirmed differences in the meiofaunal community before and after Hurricane Matthew, with Tardigrada, Cnidaria, Ostracoda and Mollusca, being the main groups that contributed the most to the dissimilarity between periods. The environmental variables of organic matter and temperature best explained the structure of the meiofaunal community after the natural phenomenon. This study highlights the importance of meiofauna as a monitoring tool for beaches and the effects of environmental disturbances such as hurricanes, which are expected to become more common in coastal areas due to climate change. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Power outages caused by tropical storms significantly impact the United States economy and citizens every year. If the impacts of these storms could be better anticipated, they could be more effectively mitigated. While there has been some research focused on predicting the impacts of tropical storms on the power grid, they have not yet resulted in effective decision making support tools that can effectively improve storm response. This paper attempts to improve upon previous work by describing a novel predictive modeling approach designed to accurately forecast tropical storm related power outages across the Continental United States. This framework considers a wide range of multidisciplinary data derived from numerical weather prediction, US Census Bureau products, and various other earth datasets to describe the environmental and infrastructural conditions during storms. A rigorous evaluation of 38 historical tropical storms shows that model performance compares favorably to established, smaller-scale outage models and demonstrates a greater than 50% reduction in Mean Squared Error over the most similar large-scale outage model in the literature. This modeling approach has potential to inform decision makers about the overall severity of storm impacts, as well as which regions are more likely to be more effected by persistent power outages. This information could allow emergency managers to prepare more effectively and reduce the felt impacts of these storms.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To explore the nourishment effect and disaster reduction efficiency of a fully dissipative dry beach under the impact of storms, this paper uses the measured topography and hydrodynamic data to establish a one-dimensional numerical model of the XBeach beach profile. By numerically modeling the change in the nourished profile for different dry beach widths under normal waves and storm conditions and the recovery process of the profile after the storm, the degree of response in dry beach nourishment for the fully dissipative beach is analyzed. The results show that under normal wave conditions, the response of the nourished dry beach is obvious. Sediment on the dry beach erodes heavily, and the shoreline moves landward over a long distance. With the increase in the width and size of the dry beach, the wave height at the bottom of the backshore profile decreases, the wave height attenuation rate increases continuously, and the wave elimination effect is remarkable. When the storm incident wave intensifies, the wave height attenuation rate of the nourished dry beach decreases, indicating that the smaller the storm intensity is, the more significant the wave reduction effect of the nourished dry beach is. At the same time, different profile arrangements of nourished dry beaches suffer from different degrees of erosion under storm conditions, with significant changes in profile morphology. With intensified storm action, the intensity of sediment erosion in the nourished dry beach increases, the nourishment is weakened, and the recovery effect of the profile after the storm is not obvious. The results of the numerical modeling highlight that the dry beach nourishment method can resist storms to a certain extent, but the overall effect is relatively limited. [ABSTRACT FROM AUTHOR]

Marine lakes are emerging ecological and evolutionary natural experimental systems, with genetically isolated resident populations that exhibit extreme population dynamics and rapid phenotypic change. Marine lakes are posited to be marine islands, however, unlike terrestrial islands for which rich models have been developed over the past half-century, we know little of the mechanisms driving changes in marine lakes. This is a critical knowledge gap in efforts to reconcile theory on, or distinguish differences among, island and island-like systems. To reduce this critical knowledge gap, we present a mathematical model describing marine lakes based on a case study of Jellyfish Lake (Ongeim’l Tketau, Mecherchar: OTM), Palau. Empirical data show that marine lakes exhibit delayed and reduced tidal motions, suggesting exchange of a limited amount of water with the neighboring (‘mainland’) ocean. Our model tracks changes in lake level, allowing determination of an exchange rate that is a physical null model for biological colonization and a proxy for colonization distance in island biogeography theory. In addition, we track horizontally averaged in-lake quantities such as salinity and temperature (i.e., marine weather, climate) and stratification (i.e., habitat) — that are known to influence resident species’ distributions and population dynamics — by solving an advection-diffusion equation. We find that weather, ocean conditions, groundwater, and exchanges through tunnels determine the abiotic environment in OTM. By comparing simulations and data, we estimate the difficult-to-measure properties of the surrounding groundwater — the ‘matrix’ in the vernacular of habitat islands — and give a range of realistic values for the effective diffusion coefficient. This coefficient is found to increase in a tropical storm, suggesting that other drivers can be important during perturbations.

Abstract 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

Climate change is a major source of external shocks to the economy. In this article, we estimate the short‐term impacts of tropical storms on food prices. After matching the track records of tropical storms with retail prices of food products during 1998 and 2012 in China, we find that tropical storms lead to food prices increasing by 2.3%, and the effect lasts more than one month. The positive impacts on prices mainly concentrate on fresh vegetable products. One main channel of price increases caused by tropical storms is the supply‐side shock to the transportation and distribution system. We find limited evidence of price increases driven by demand‐side shocks such as food displacement and food composition changes. The impacts of tropical storms on food price increases lead to a total loss amounting to $92 million each year on average. This study contributes to literature evaluating the price impacts caused by tropical storms and provides policy implications on enhancing food supply resilience. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) play an important role in sea‐air interactions and cross-scale impacts on of El Niño–Southern Oscillation events by influencing the turbulent mixing and heat distribution in the upper ocean. Utilizing the observational data and simulations from a numerical model with modified surface wind forcing, this study systematically investigates the effects of a tropical storm (TS) on equatorial Kelvin waves based on TS Dujuan, which is a low-intensity TC. Observations of anomalies combine with the equatorial wave decomposition method are used to confirm the passage of a downwelling Kelvin wave during the same period with properties similar to those of the modeled wave. Modeling results indicate that the TS amplifies the equatorial Kelvin wave, raising the sea surface height by ~2.1 cm and the upper ocean temperature by ~0.34°C and accelerating the eastward zonal current. These signals propagate eastward with the wave and decrease rapidly, and finally decrease to approximately 3-35% of their original strength, particularly the temperature decrease is greatest. Our findings reveal that, in the region close to the equator, even low-intensity cyclones like TS Dujuan can significantly impact the dynamics and propagation of Kelvin waves. TS Dujuan is capable of altering the thermal structure of the equatorial Pacific by amplifying the Kelvin waves. As TS Dujuan occurred during a La Niña event, we infer from our specific study that the forcing effects of TS on equatorial Kelvin waves may reduce the duration of La Niña events.

Studies of the impact of tropical storms on various economic activities including energy production are on the rise given higher frequencies of tropical storms and the increasingly large and negative impact in more recent years. However, we found no academic study of tropical storms on natural gas consumption. This paper provides such a study. In carrying out the empirical investigation, we created a dataset that includes the detailed path of the storms and the cities and states impacted. We estimated the storms' impact on temperature and also the temperature's impact on consumption to gauge the specific impact of tropical storms by state and by end use. We found significant storm impact on natural gas consumption, especially consumption of gas to produce power. However, the impact of a typical storm on gas consumption was relatively small on a monthly basis even though it could have a large impact on storm days. This study provides an important empirical result to better understand natural gas price dynamics in the presence of a tropical storm. [ABSTRACT FROM AUTHOR]

This study analyzes tropical disturbances in a region usually not affected by these events, the southeastern North Atlantic. This is an extensive area between Macaronesia and the coasts of northwest Africa and the southwest of the Iberian Peninsula. In the context of climate change, a statistical analysis has been conducted of the main database of the National Hurricane Center for the Atlantic basin, as well as a bibliographical compilation, in order to analyze the temporal and spatial evolution of these phenomena. The starting hypothesis is to verify the existence of an increase in the risk of these situations in the region of study, through research that characterizes and charts these phenomena. The results indicate that, although with long periods of recurrence, some events with notable impacts had occurred before the first systematic records were kept. In addition, over the last fifty years, a much more reliable period from a scientific perspective, there has been an increase in their number, especially in recent decades. Furthermore, an approximate estimate is made of the population likely to be affected by tropical disturbances, which estimates that more than twenty million people are at risk. [ABSTRACT FROM AUTHOR]

The unique tropical storm (TS) Deliwe (2014) occurred in the northern Mozambique Channel on 17 January 2014 and turned right during its whole life cycle, moving south along the west coast of Madagascar Island. During the development of the TS, the anticyclonic eddies in the Mozambique Channel had an important influence on the intensity and track of Deliwe, which existed for months. In this study, multisource reanalysis, conductivity temperature depth (CTD) and Argo buoy data were used to investigate the mechanism of dynamics. The results showed that the anticyclonic eddies in the Mozambique Channel were a major cause of Deliwe strengthening, weakening and then deflection to the right. On 17 January, the maximum latent heat flux of anticyclonic eddy W1 reached 103.1 w/m2. After Deliwe passed, the tropical cyclone heat potential (TCHP) of anticyclonic eddy W1 was significantly reduced by 3 kJ/cm2. The mixed layer of anticyclonic eddy W1 was deeper than the surrounding waters, supporting the development of Deliwe. As the TS intensity decreased, the low-pressure center of 500 hPa moved above anticyclonic eddy W2, and the westerly wind belt moved northward to form a westerly trough of low pressure, which caused the TS to keep turning right and formed a unique TS track. This study provides a new understanding of the influence of marine anticyclonic eddies on the development of tropical cyclones (TCs) in the Mozambique channel. [ABSTRACT FROM AUTHOR]

Climate change and human activity can both exert a role in the river discharge and sediment load in river deltas when the sea level remains relatively stable. The Pearl River Delta constitutes the metropolitan region of the Guangdong–Hong Kong–Macau Greater Bay Area, and its evolution in the past and future impacts the sustainable development of this region. In this manuscript, a core situated in the northern South China Sea, adjacent to Qiao Island of Zhuhai city in the Pearl River Delta, was selected to investigate the hydrodynamic variation influenced by tropical processes and the sediment flux imposed by human activities. Using paleosecular variations (PSVs) in geomagnetic field correlations constrained by seven radiocarbon ages, an ∼2.5 kyr chronology was provided for core sediments ∼2.8 m in length. The magnetic fabric results suggest that deposition was influenced by the two types of hydrodynamic-weak energy modulated by El Niño–Southern Oscillation (ENSO) activity and higher energy regulated by high-frequency tropical storms. The cyclic variations in the degree of anisotropy of magnetic susceptibility (P) indicate two periodic changes at approximately 300 and 100 years, which were forced by ENSO activity, while the ratio of lineation with foliation (q value) implies a higher energy flow period of 1.3–1.9 kyr, arising from strong tropical storms. Moreover, the high saturation remanence (SIRM) introduces more sediment flux, which is impacted by growing human activity during the period of 1.0–1.6 kyr.

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. [ABSTRACT FROM AUTHOR]

Tropical storms (TSs) can induce sea surface cooling, freshening, and phytoplankton blooms. The dissolved oxygen (DO) concentration response to TSs within an anticyclone is still unclear due to the rarity of in situ observations. In this study, we investigate the variations in DO concentration attributed to TS 'Haitang' within an anticyclonic eddy in the northern South China Sea based on Chinese underwater glider data. DO concentrations have a higher value at the edge of eddy than at the core. Influenced by TS, DO concentrations decrease remarkably in the subsurface layer in all three regions (inside, edge, and outside of the anticyclonic eddy). The mean DO concentrations decrease more at the edge of the anticyclone than those inside the anticyclone. The recovery time of DO concentration after TS is around one week at the edge of the anticyclone and is >10 days within the eddy. Our observations show that the DO concentrations decrease above the subsurface chlorophyll a maxima layer. Quantitative analysis shows that variations in DO concentration are dominated by horizontal advection and vertical advection terms in the subsurface layer. [ABSTRACT FROM AUTHOR]

Abstract Tropical cyclones are the most powerful storms on earth, causing catastrophic damage to human lives and infrastructure. Hurricanes also cause wildlife mortality when they make landfall, but the severity of these effects is difficult to quantify because data collection is either logistically impossible or deprioritized in the wake of human tragedy. On August 27, 2020, Hurricane Laura made landfall in southwestern Louisiana with maximum sustained winds of 241 kph (150 mph), making it one of the most powerful storms to strike the mainland United States. Hurricane Laura passed directly over the core breeding range of the western Gulf Coast population of Mottled Duck (Anas fulvigula), during a time when many adult birds were undergoing a simultaneous wing feather molt and were flightless. We used GPS‐GSM telemetry data to evaluate survival rates of adult female Mottled Ducks in late summer 2020 (bracketing August 27 by one month on either side) relative to the same period in 2018 and 2019. Mortality was lower in 2018 (12 out of 29; 41%) and 2019 (8 out of 28; 29%) than in 2020 (12 out of 18; 67%), and 7 out of 12 mortalities documented in 2020 occurred when Hurricane Laura made landfall. Survival analyses in program MARK confirmed lower survival probability in 2020, but there was overlap in 85% confidence intervals in all years. This single storm resulted in the death of ~40% of all marked birds in our sample, suggesting that hurricanes have the potential to influence population demographics. In addition, Hurricane Laura resulted in widespread habitat loss and degradation that has reduced available nesting habitat in 2021, and possibly for years to come. The acute and chronic effects of hurricanes may exacerbate Mottled Duck population declines, which may worsen in the face of increasingly frequent and more severe tropical storms.

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.

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. [ABSTRACT FROM AUTHOR]

This study investigated the impact of the assimilation of satellite radiance observations in a three-dimensional variational data assimilation system (3DVAR) that could improve the tracking and intensity forecasts of the Tropical Storm Dianmu in 2021, which occurred over parts of southeast mainland Asia. The weather research and forecasting (WRF) model was used to conduct the assimilation experiments of the storm. Four sets of numerical experiments were performed using the WRF. In the first, the control experiment, only conventional data in Binary Universal Form for the Representation of Meteorological Data (PREPBUFR) observations from the National Centers for Environmental Prediction (NCEP) were assimilated. The second experiment (RDA1) was performed with PREPBUFR observations and satellite radiance data from the Advanced Microwave Unit-A (AMSU-A), and the Advanced Technology Microwave Sounder (ATMS). PREPBUFR observations and the High-resolution Infrared Radiation Sounder (HIRS-4) were used in the third experiment (RDA2). The fourth experiment (ALL-OBS) used the assimilation of PREPBUFR observations and all satellite radiance data (AMSU-A, ATMS, and HIRS-4). The community radiative transfer model was used on the forward operator for the satellite radiance assimilation, along with quality control and bias correction procedures, before assimilating the radiance data. To evaluate the impact of the assimilation experiments, a forecast starting on 00 UTC 23 September 2021, was produced for 72 h. The results showed that the ALL-OBS experiment improved the short-term forecast up to ~24 h lead time, as compared to the assimilation considering only PREPBUFR observations. When all observations were assimilated into the model, the storm's landfall position, intensity, and structure were accurately predicted. In the deterministic forecast, the tracking errors of the ALL-OBS experiment was consistently less than 40 km within 24 h. The case study of Tropical Storm Dianmu exhibited the significant positive impact of all observations in the numerical model, which could improve updates for initial conditions and storm forecasting. [ABSTRACT FROM AUTHOR]

Introduction Data and information from the Meteorological Department of India and the Joint Hurricane Warning Center (JHWC) were used to investigate the structural nature of Ashuba tropical storm in the Arabian Sea from June 7 to June 12, 2015. To study the atmospheric structure, the analyzed digital data were taken from the European Center for Medium-Term Forecasts and the Center for Environmental/Atmospheric Forecasts (NCEP/NCAR) for the Arabian Sea and beyond. The study area was the Arabian Sea, located between the Indian subcontinent (eastern part) and the Arabian Peninsula (western part) and northwest of the Indian Ocean. On average, 1-2 tropical cyclones form on the Arabian Sea each year. Even in some tropical regions, strong cyclonic cycles occur at the synoptic scale (Evan & Camargo, 2001: 145). Therefore, from previous years, climatologists have studied the types of storms, due to the increase in tropical cyclones in the last decade; and thereby, this issue is followed with more sensitivity. Consequently, the main purpose of this study was to explore the structural nature of Ashuba tropical storm on the Arabian Sea in order to identify one of the region's main moisture sources. Materials and Methods Storm data statistics were obtained from the Meteorological Department of India and the Hawaii Hurricane Warning Center. Analyzed digital data, including; Geopotential altitude (Hgt), orbital (u), meridional wind (v), sea surface pressure (SLP), air temperature and sea water temperature (SST) for standard levels at 17 compression levels with a resolution of average daily geographic degree belonged to the National Center for Environmental Prediction/Atmospheric Science and precipitated networked data were obtained from the European Center for Medium-Term Atmospheric Forecasting (ECMWF) with a resolution of 0.125 degrees Celsius for the Arabian Sea. NASA and MODIS satellite imagery were also used for the visible band for every six days. The CAPE index was applied to evaluate the energy required by the storm supplier. Findings and Discussion The results of study displayed that in the middle level of the atmosphere, while forming a low-altitude nucleus with very strong positive rotation, the conditions for the production of tropical storms in the region have been provided. On the other hand, on the surface, low pressure has formed in the southeast of the Arabian Sea with a central pressure of 995 hPa and has started moving westwards towards the coasts of Oman and northern Yemen. Creating a very strong convergence current on the surface and upper divergence caused the storm to reach its maximum strength in the region on June 9. However, the anomalous temperature of the water surface in the range where the storm reached its maximum intensity reaches to over than 5 degrees Celsius. The increase in water surface temperature and the transfer of heat and moisture into the storm has strengthened and, by its nature, caused heavy rainfall in the region. Finally, on June 12, as it approached the east coast of Oman, it began to disappear due to lack of moisture for its dynamic movements, and changed from a tropical storm to a tropical hurricane. Also examining the prepared maps for the amount of precipitation and the flow of the lower levels of the atmosphere, it was determined that on the first day of the storm, a cyclonic current occurred in the east of the Arabian Sea, resulting in the maximum amount of precipitation in the west of the system, which reaches more than 240 mm. On the second day, moving north of the system, the amount of precipitation was concentrated in the south, so that the southern coast of India was not unaffected by precipitation and had about 120 mm of rainfall. On the third day, with the placement of this tropical storm in the north of the Arabian Sea, the maximum precipitation was created in the east of the system, which was more than 160 mm. On the fourth day, the western half of the Indian coast was faced with a rainfall of nearly 110 mm, which was due to its location in the east of the cyclone, which in turn caused the rise of air and the transfer of moisture to the air parcel, floods in the region. On the fifth day, the maximum rainfall was close to the eye of the storm, which was close to 100 mm, and the coastal areas of the Indian subcontinent were still experiencing heavy rainfall. Examination of the 850 hPa pressure system revealed that on the first day, the maximum relative pressure system nucleus formed in the southeastern parts of the Arabian Sea. These conditions have led to very strong convergence in the lower levels. The presence of such strong convergence and amplification of rotation has caused this anomaly to reach its maximum in the region. The strong rotating nucleus then extended to the west coast of India and then moved westward on the third day to the central regions of the Arabian Sea, with a very strong rotating current extending from latitudes 10 to 30 degrees north. As the storm/hurricane approached the west coast of the Arabian Sea, it intensified to more than five pressure system units on the fourth day. On the fifth day, the positive nucleus became independent and formed a very strong rotating closed cell. On the sixth day, with the cyclone remaining on the eastern coast of the Arabian Peninsula, its power had gradually diminished. Considering the water temperature in the region, which is an average of 6 days, it showed that the water temperature in most parts of the Arabian Sea was high, so that these conditions reached more than 32 degrees Celsius in the coasts of India and the center of the Arabian Sea. These conditions were less only in the northern regions of the sea than in other regions. To understand the water surface temperature, its anomaly was also calculated for six days with the storm. Its output indicated that the eastern, northern, western and southwestern regions of the Arabian Sea were associated with a positive anomaly of 2 to 3° C. Negative anomalies only reached -1.5 degrees Celsius in the north and south of the sea. Occurrence of maximum positive anomalies in the region was one of the main reasons for the intensification of cyclones in the region, so that the western regions of the Arabian Sea had the maximum positive anomalies and on the other hand the maximum area of ​​tropical cyclone activity. The 12-hour reports from the Indian Meteorological Agency and the Hawaii Hurricane Warning Center were used to route the tropical storm. In these two centers, there were several data methods for routing and the origin of the storm. Geographical coordinate data with a 12-hour separation was used, which from the beginning of the storm to its decline, its characteristics and longitude and latitude were recorded as a text file. The onset of the storm was from the eastern part of the Arabian Sea, which migrated northward to higher elevations and deviated in its path due to the dominance of the Coriolis to the west of the region and disappeared off the coast of Oman. Conclusion Ashuba tropical storm/hurricane formed on June 7, 2015 in the Arabian Sea and disappeared on June 12, 2015. This investigation revealed that on the first day, a low-lying cell was formed in the eastern part of the Arabian Sea, during which a positive rotating nucleus or vortex was formed in the mentioned area and strengthened in the following days. The role of the Arabian Sea and abnormal changes in its water surface temperature in the occurrence of hurricanes has been mentioned in the researches of Ghavidel Rahimi (2015: 31) and Lashkari and Kaykhosravi (2010: 19). On June 9, as the subtropical anticyclone expanded further east, the Arabian Sea's low-pressure cell became oval in a circle, contributing to the deepening of the system, creating another bond at the heart of the closed cell with a height of 5,810 geopotential meters. In the last days, as the coasts of Oman and Yemen approach, the intensity of this cell decreases and its extinction stage was reached. On the surface, in parallel with the mentioned period, a low-pressure core with a central pressure of 995 hPa formed on the southeast of the Arabian Sea and the creation of a very strong positive rotation indicates the occurrence of hurricanes in the region. The central pressure of the storm reached less than 993 hPa on days 9 and 10, which was the peak of the storm. As it approached the shores, the intensity of this cyclone was greatly reduced, turning it from a tropical storm into a tropical turbulence. Examination of the water surface temperature showed that the average water surface temperature in these 6 days in most parts of the Arabian Sea was more than 29 degrees Celsius. Inspection of water surface temperature anomalies also disclosed that the maximum positive anomalies corresponded to several places in the sea, including the southern coasts of Pakistan to western India, eastern Oman and a very strong core corresponding to the southwest of the Arabian Sea with an average temperature of more than 5° C. The maximum rainfall inside the cyclone indicated that on the first day of the storm, the maximum rainfall in the southwest was 240 mm. In the following days, with the transfer of this core to the south, southeast and finally to the east, the maximum rainfall would be on the west side of the Indian coast. Only in the last days it was observed that while the maximum rainfall occured in India near the eastern part of the eye of the storm, a maximum precipitation center with an average of 100 mm has been created. In this study, two indicators, CAPE and SWEAT, were used to assess the location of storm formation. The results showed that these two indicators well showed the formation and severity and weakness of the storm during different stages. Thus, on the first day in the south of the Arabian Sea, the amount of CAPE was more than 5000 Jules/kg, which indicates the amount of convective energy available. On the other hand, the values ​​of the SWEAT index have reached more than 380, which specify that the probability of a hurricane in this region is very high. Also, with the increase of water surface temperature in the region and the increase of anomalies in it, the necessary energy is provided for the production of cyclones in the region, which with the increase of energy within the air mass system and the presence of buoyancy energy in it, and on the other hand, instability indicators in monitoring and tracking these types of storms showed that they are a suitable tool for tracking and are able to navigate it while being aware of the intensity of the storm.

Tropical storms (TS) are important drivers of short-term changes and affects the coastal and marine environment. Based on in situ observational data from four locations in the coastal area of the northern Beibu Gulf and satellite data, we analyzed the changes in temperature, salinity, and turbidity during the transit of TS “Wipha” in 2019 and assessed the environmental factors controlling chlorophyll a concenteation (Chl-a) increases in the coastal area. Our results showed that in the coastal area, the growth of phytoplankton after the TS was mainly controlled by the nutrient and light availability. The increased input of freshwater by TS, including direct inputs from rainfall and increased river discharge, reduced the salinity. The decrease in salinity may indicate an increased input of nutrient-rich freshwater at all four stations (nutrients input: S1>S2>S3>S4). Nutrient concentration at S1, S2, and S3 implied by salinity was high, but that at S4 was limited. The shorter recovery time of turbidity after TS indicated the faster improvement of light conditions in this area [recovery time: S4 (2 days)< S1 (3 days)< S3 (5 days)< S2 (10 days)]. The high turbidity associated with poor light penetration was an important factor limiting phytoplankton growth at station 2, with a slow recovery of the turbidity to pre-TS levels. The rapid recovery of the turbidity to the pre-TS levels at S1, S3, and S4 suggested good light conditions soon after the TS, and probably led to a significant increase in Chl-a after the TS ([Chl-a]: S1>S3>S4). The less of an increase of Chl-a at S4 was not only related to nutrient restriction but also related to weak mixing of the water column, while the least significant decrease in the SST at S4 implied that the enhancing mixing after TS was limited.

After the tropical storm Cristobal, we performed special adult entomological collections in the peri-domicile of 35 houses from 25 neighborhoods of Mérida, Yucatan, Mexico in response to complaints from the community about an increased nuisance due to an abundance of mosquitoes. A total of 1,275 specimens from four genera and 13 species were collected: Aedes taeniorhynchus (92%), Culex quinquefasciatus (72%), Aedes aegypti (72%), Psorophora mexicana (36%), Psorophora cyanescens (32%), Aedes scapularis (24%), Culex nigripalpus (24%), Aedes albopictus (8%), Psorophora ferox (4%), Haemagogus equinus (4%), Aedes trivittatus (4%), Culex coronator (4%), Culex iolambdis (4%). From these collections, the increased mosquito nuisance was mainly the result of invasive species such as Aedes taeniorhynchus and Psorophora. City wide, vehicle mounted ULV spraying was performed by the MoH and the municipality of Merida to control adult mosquito populations. We report Culex iolambdis for the first time in Merida and Psorophora mexicana for the state of Yucatan. [ABSTRACT FROM AUTHOR]

Tropical islands, including many in island arcs, are subjected to recurring disturbances from extreme storms such as tropical cyclones. To test whether such storms influence cosmogenic nuclide concentrations such that they do not reflect long‐term rates of erosion, we measured meteoric and in situ10Be in river sediment samples from Dominica, an andesitic island in the Caribbean, before and after category five Hurricane Maria (in 2017). Populations of before‐ and after‐storm concentrations are statistically indistinguishable (n = 7 pairs for in‐situ10Be, n = 11 pairs for meteoric 10Be). 10Be concentrations vary from −138% to +73% within before–after sample pairs relative to the mean of the pair. These new data suggest that the effects of extreme storms on the depth and amount of near‐surface erosion on Dominica vary spatially. Our data support the calculations of Niemi et al. (2005) and Yanites et al. (2009) suggesting that basin‐by‐basin comparisons of erosion rates based on cosmogenic nuclides should be approached with caution in small (<~100 km2) watersheds affected by mass movements and extreme storms. Erosion rates determined from in‐situ10Be on Dominica (geometric mean = 0.102 mm y−1, n = 12) are low compared to similarly steep and wet areas globally and correlate positively with the spatial density of mass movements. [ABSTRACT FROM AUTHOR]

Hurricanes and tropical storms (TS) are infrequent but disastrous events to human lives, social activities, and terrestrial ecosystems in coastal regions. Using the Environmental Protection Agency (US-EPA)'s Hydrologic and Water Quality System (HAWQS) model, principal component analysis (PCA), and principal factor analysis (PFA), we estimated impacts of multiple hurricanes and TS on hydrological processes in agricultural and forested watersheds. Five hurricanes and four TS that passed near or through the Apalachicola–Chattahoochee–Flint River basin (ACFRB) of the Florida panhandle from 1966 to 2018 were selected to estimate their impacts on rainfall, potential evapotranspiration (PET), evapotranspiration (ET), soil water percolation, surface runoff, stream discharge, groundwater recharge, and water yield (WYLD). Simulations showed that the category of hurricanes was not highly related to the amounts of rainfall, runoff, discharge, and WYLD. Based on PCA and PFA, PET and ET were highly and negatively, rainfall and discharge were highly and positively, and percolation, runoff, groundwater recharge and WYLD were moderately and positively affected by the hurricanes and TS at the ACFRB in the recent 50 years. This study provides water resource managers with critical insights into how multiple hurricanes and TS affected hydrological processes in agricultural and forested watersheds of the coastal region. [ABSTRACT FROM AUTHOR]

Hurricanes and tropical storms can significantly alter forested and non-forested areas, creating unique hazards and considerations for wildland firefighters and prescribed burners. Prior to responding to wildfires and planning prescribed fires, fire managers should anticipate how these changes will affect fire behavior, smoke, hazards, and access to the fire.

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During a behavioural survey of a tagged whale shark (Rhincodon typus) conducted in 2019 in the waters off Kagoshima, Japan, a typhoon passed close to the area under surveillance. As the typhoon approached, monitoring of the shark's movements indicated that it dived to depths of up to 90 m, and during this period, the authors recorded the effects of the typhoon‐induced waves. They also detected changes in the vertical thermal structure of the waters, possibly due to the disturbance caused by the typhoon. [ABSTRACT FROM AUTHOR]

A tsunami is a sea wave of local or distant origin that results from large-scale seafloor displacements associated with strong earthquakes, major submarine slides, or exploding volcanic islands. A tsunami can strike any coast at any time and we cannot predict exactly when or where they will occur. Undersea earthquakes most often cause tsunamis but submarine landslides or volcanic eruptions can also cause them. A tsunami can move as fast as a jet plane across the Open Ocean and can hit land with waves as high as 20 meters or more. The water may wash inland for several kilometers in flat lying areas, and can move up streams and rivers, destroying everything in its path. Waves may continue to strike the shoreline for many hours, and dangerous currents can continue for days following the event. Coastal areas endure Clear changes in response to ocean changes. The tsunami and tropical storms are among those changes. These changes should be note, Failure to pay attention to them makes opportunities become a threat. Tropical storms are one of the most dangerous hazards. In the first table some costs are mentioned. When a tropical storm occurs, the water level along the waves in the sea changes. In these storms, strong winds are generated that revolve around a central core.it can move from ocean to coastal areas. The Makran seduction is due to the mountain range from Iran to Pakistan. The most important of these are Taftan and Bazman in Iran and Sultan in Pakistan. In hence The coastal area and sea play an important role in the development of country. Tropical storms and tsunamis are one of the most destructive phenomena in the world.it occurred in1945 in Iran, Mokran. The reason for this phenomenon was the large earthquake of 8.25 on the Mokran fault. This tsunami caused a lot of damage That killed more than 4,000 people in Pakistan. Tropical storms are important phenomena in the ocean area. The proper investment in different sectors and special attention to marine hazards and tsunami and also implementation of prevention plans are so necessary. Coastal areas influence economy by the knowledge of the potential of energy, transport, fisheries and tourism in addition to their political, strategic and social importance in the countrychr('39')s economy. Some plans are designed to reduce costs. Some of these programs are for training and some are to prevent damage. Financial limitation causes the need of prioritizing plans based on the knowledge of economical engineering in different periods of time. . In this case we present a modeling for prioritizing plans in order to Reduce the amount of Economical losses .with use NPV index to do the task .we have to calculate the amount of cost reduction for each plan. To find the extent of the damage reduction, 100 experts and organizations are surveyed and the results are estimated and then the cost of implementation of plans was found. Historical accounts describe an earthquake and tsunami on 21 July AD 365 that destroyed cities and drowned thousands of people in coastal regions from the Nile Delta to modern-day Dubrovnik. The location and tectonic setting of this earthquake have been uncertain until now.

The unique tropical storm (TS) Deliwe (2014) occurred in the northern Mozambique Channel on 17 January 2014 and turned right during its whole life cycle, moving south along the west coast of Madagascar Island. During the development of the TS, the anticyclonic eddies in the Mozambique Channel had an important influence on the intensity and track of Deliwe, which existed for months. In this study, multisource reanalysis, conductivity temperature depth (CTD) and Argo buoy data were used to investigate the mechanism of dynamics. The results showed that the anticyclonic eddies in the Mozambique Channel were a major cause of Deliwe strengthening, weakening and then deflection to the right. On 17 January, the maximum latent heat flux of anticyclonic eddy W1 reached 103.1 w/m2. After Deliwe passed, the tropical cyclone heat potential (TCHP) of anticyclonic eddy W1 was significantly reduced by 3 kJ/cm2. The mixed layer of anticyclonic eddy W1 was deeper than the surrounding waters, supporting the development of Deliwe. As the TS intensity decreased, the low-pressure center of 500 hPa moved above anticyclonic eddy W2, and the westerly wind belt moved northward to form a westerly trough of low pressure, which caused the TS to keep turning right and formed a unique TS track. This study provides a new understanding of the influence of marine anticyclonic eddies on the development of tropical cyclones (TCs) in the Mozambique channel.

Tropical cyclones are the most powerful storms on earth, causing catastrophic damage to human lives and infrastructure. Hurricanes also cause wildlife mortality when they make landfall, but the severity of these effects is difficult to quantify because data collection is either logistically impossible or deprioritized in the wake of human tragedy. On August 27, 2020, Hurricane Laura made landfall in southwestern Louisiana with maximum sustained winds of 241 kph (150 mph), making it one of the most powerful storms to strike the mainland United States. Hurricane Laura passed directly over the core breeding range of the western Gulf Coast population of Mottled Duck (Anas fulvigula), during a time when many adult birds were undergoing a simultaneous wing feather molt and were flightless. We used GPS-GSM telemetry data to evaluate survival rates of adult female Mottled Ducks in late summer 2020 (bracketing August 27 by one month on either side) relative to the same period in 2018 and 2019. Mortality was lower in 2018 (12 out of 29; 41%) and 2019 (8 out of 28; 29%) than in 2020 (12 out of 18; 67%), and 7 out of 12 mortalities documented in 2020 occurred when Hurricane Laura made landfall. Survival analyses in program MARK confirmed lower survival probability in 2020, but there was overlap in 85% confidence intervals in all years. This single storm resulted in the death of ~40% of all marked birds in our sample, suggesting that hurricanes have the potential to influence population demographics. In addition, Hurricane Laura resulted in widespread habitat loss and degradation that has reduced available nesting habitat in 2021, and possibly for years to come. The acute and chronic effects of hurricanes may exacerbate Mottled Duck population declines, which may worsen in the face of increasingly frequent and more severe tropical storms. [ABSTRACT FROM AUTHOR]

Ongoing global warming increases the frequency and severity of tropical typhoons and prolonged drought, leading to forest degradation. Simultaneous and/or successive masting events and climatic extremes may thus occur frequently in the near future. If these climatic extremes occur immediately after mass seed reproduction, their effects on individual trees are expected to be very severe because mass reproduction decreases carbohydrate reserves. While the effects of either a single climate extreme or masting alone on tree resilience/growth have received past research attention, understanding the cumulative effects of such multiple events remains challenging and is crucial for predicting future forest changes. Here, we report tree hazards compound by two successive climate extremes, a tropical typhoon and prolonged drought, after mass reproduction in an endemic tree species (Distylium lepidotum Nakai) on oceanic islands. Across individual trees, the starch stored within the sapwood of branchlets significantly decreased with reproductive efforts (fruit mass/shoot mass ratio). Typhoon damage significantly decreased not only the total leaf area of apical shoots but also the maximum photosynthetic rates. During the 5‐month period after the typhoon, the mortality of large branchlets (8–10‐mm diameter) increased with decreasing stored starch when the typhoon hit. During the prolonged summer drought in the next year, the recovery of total leaf area, stored starch, and hydraulic conductivity was negatively correlated with the stored starch at the typhoon. These data indicate that the level of stored starch within branchlets is the driving factor determining tree regrowth or dieback, and the restoration of carbohydrates after mass reproduction is synergistically delayed by such climate extremes. Stored carbohydrates are the major cumulative factor affecting individual tree resilience, resulting in their historical effects. Because of highly variable carbohydrate levels among individual trees, the resultant impacts of such successive events on forest dieback will be fundamentally different among trees. [ABSTRACT FROM AUTHOR]

Cyclones and tropical storms are important threats to public health faced by countries worldwide as they are associated with infectious disease outbreaks, unsafe food and water to mention a few. To help meet these challenges, the World Health Organization encourages countries to strengthen their capacities for health emergency and disaster risk management incorporating measures for prevention, mitigation, preparedness, response and recovery. In this letter, we unpack the case of Zimbabwe’s preparedness and response to cyclones and tropical storms. Zimbabwe has been hit by several cyclones and tropical storms in the past two decades of varying magnitude and public health impacts. While the state of readiness and nature of response has improved over the years, we discuss the preparedness for and response to the 2019 Cyclone Idai to highlight the gaps that remain.

This study investigated the impact of the assimilation of satellite radiance observations in a three-dimensional variational data assimilation system (3DVAR) that could improve the tracking and intensity forecasts of the Tropical Storm Dianmu in 2021, which occurred over parts of southeast mainland Asia. The weather research and forecasting (WRF) model was used to conduct the assimilation experiments of the storm. Four sets of numerical experiments were performed using the WRF. In the first, the control experiment, only conventional data in Binary Universal Form for the Representation of Meteorological Data (PREPBUFR) observations from the National Centers for Environmental Prediction (NCEP) were assimilated. The second experiment (RDA1) was performed with PREPBUFR observations and satellite radiance data from the Advanced Microwave Unit-A (AMSU-A), and the Advanced Technology Microwave Sounder (ATMS). PREPBUFR observations and the High-resolution Infrared Radiation Sounder (HIRS-4) were used in the third experiment (RDA2). The fourth experiment (ALL-OBS) used the assimilation of PREPBUFR observations and all satellite radiance data (AMSU-A, ATMS, and HIRS-4). The community radiative transfer model was used on the forward operator for the satellite radiance assimilation, along with quality control and bias correction procedures, before assimilating the radiance data. To evaluate the impact of the assimilation experiments, a forecast starting on 00 UTC 23 September 2021, was produced for 72 h. The results showed that the ALL-OBS experiment improved the short-term forecast up to ~24 h lead time, as compared to the assimilation considering only PREPBUFR observations. When all observations were assimilated into the model, the storm’s landfall position, intensity, and structure were accurately predicted. In the deterministic forecast, the tracking errors of the ALL-OBS experiment was consistently less than 40 km within 24 h. The case study of Tropical Storm Dianmu exhibited the significant positive impact of all observations in the numerical model, which could improve updates for initial conditions and storm forecasting.