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Landslides are among the most dangerous natural processes. Debris avalanches and debris flows in particular have often caused casualties and severe damage to infrastructures in a wide range of environments. The assessment of susceptibility to these phenomena may help policy makers in mitigating the associated risk and thus it has attracted special attention in the last decades. In this experiment, we assessed susceptibility to debris-avalanche and -flow landslides by using a stochastic approach. Two different modeling techniques were employed: i) Multivariate Adaptive Regression Splines (MARS) and ii) Logistic Regression (LR). Both MARS and LR allow for calculating the probability of landslide occurrence by building statistical relationships between a set of environmental variables and the target variable, i.e. presence/absence of the landslide event. The target variable was extracted from an inventory of debris-avalanche and - flow landslides which were triggered by the tropical storm that hit the area of Mocoa (Colombia) on 1 April 2017. As predictor variables, we employed nine terrain attributes derived from a 5-m resolution DEM (i.e. elevation, slope angle, northness, eastness, upslope slope angle, convergence index, topographic position index, valley depth and topographic wetness index), in addition to lithology, distance from faults and presence/absence of soil creep processes. In our experiment, we used three different landslide datasets which contain i) the highest point of each recognized landslide crown-lines (dataset LIP), ii) the highest 10% of cells of each landslide area (dataset SOURCE), and iii) the entire landslide areas, which include initiation and accumulation zones (dataset MASS). In order to evaluate their predictive ability, LR and MARS models were submitted to k-fold spatial cross-validation strategy, which consists in extracting random training and test subsets from k spatially disjoint sub-areas. The results of model validation, expressed in terms of Area Under the ROC Curve (AUC), demonstrate better predictive performance of MARS models with respect to LR models, for all the three landslide datasets. The mean AUC values calculated for the datasets LIP, SOURCE and MASS of the MARS models are 0.776, 0.788 and 0.768, respectively, whereas AUC values of the LR models are 0.748, 0.751 and 0.703, respectively. Model validation also shows that the predictive skill of the models is better when landslide data are sampled from the highest portions of the landslides (dataset SOURCE). Maps of susceptibility to debris-avalanche and -flow landslides for the Mocoa area were produced by using both LR and MARS and the three landslide datasets. The analysis of the distribution of events versus the susceptibility classes of the maps confirm that MARS and the dataset SOURCE provide the best ability to discriminate between event and non-event cells.

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.

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.

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 paper identifies the negative consequences of the strongest tropical storm ever to strike Guatemala on household welfare. Per capita consumption fell in urban areas, raising poverty substantially. Households cut back on food consumption and basic durables, and attempted to cope by increasing their adult and child labour supply. The mechanisms at play include the intensity of the shock, food prices and the timing of Agatha with respect to local harvest cycles. The results are robust to placebo treatments, migration and measurement error, and partly explain the increase in poverty in the country previously attributed solely to the collateral effects of the global financial crisis.

This article provides raw datasets of the coral reefs status in Pulau Bidong, southern of South China Sea before and after being strike by the tropical storm Pabuk on January 2019. Data were collected using a rapid coral survey method called Coral Video Transect (CVT) technique. The data were collected along a 100 m transect line set up parallel to the shoreline and at a constant depth. In total, eight transects were surveyed during both periods (pre – August 2016, post – March 2019). Back in laboratory, the footage was then extracted into non-overlapping frames or still images prior to image analysis using Coral Point Count with Excel Extension (CPCe) software. The benthic coral reefs relative percentage cover was automatically generated after the image analysis and represented by five major categories; live coral (C), algae (ALG), other invertebrates (OT), dead coral (DC), and sand silt and rock (SR). Live coral cover was identified up to the genus level. This raw dataset was used in this article. The data provided in this article could be of significant use for future studies especially on coral recovery after the natural disturbances. It can provide a baseline assessment especially for coral reefs management as well as to comprehend changes in coral health status in the face of natural and anthropogenic disturbances. The data presented here support the information in the article Safuan et al. (2020).

Exchange flows between estuaries and the coastal ocean are important for land-ocean interactions and ecosystem health. This study is aimed at resolving severe weather-induced exchange flows between the Calcasieu Lake Estuary and Gulf of Mexico. For that purpose, we use data from a long-term deployment of side-looking acoustic Doppler current profilers (ADCPs) and conductivity-temperature-depth sensors (CTDs) as well as flow velocity data from a boat operated survey. Regression between the transport measured from a boat mounted ADCP and the velocity data from a fixed side-looking ADCP is done to calculate a long-term transport along the Calcasieu Pass. Analyses have been done for the hydrodynamic response to 16 cold fronts passing the study area. Effects of six strongest cold fronts are discussed in more detail. Results have confirmed that the hydrodynamics is highly correlated with the frequent cold fronts. The highest correlation coefficient is r ~0.75 between the north wind and along channel transport. In general, winds from the southern quadrants push water into the estuary before each frontal passage, after the passage of the front, a rapid change of wind direction to the northern quadrants produces strong outward flows. A quasi-steady state balance between the wind stress and water level difference proposed in recent studies for different systems is further confirmed and discussed in this system. The quasi-steady state balance leads to a relatively high R2 value of greater than 0.8 between the modeled water level gradient and actual observed gradient. We have also applied a regression model, derived from the momentum balance requirement, for the subtidal exchange flow as a function of wind components and their squares which yield an R2 value greater than 0.7. With a confidence in the regression model, we further implement it for twelve years from 26 February 2007 to 10 April 2019. Four extreme events during this 12-year period of time are discussed&ndash, they include the Hurricane Ike (2008), Tropical Storm Lee (2011), a warm front, and a cold front. This hindcast of the exchange flows over multiple years can provide a useful tool for coastal management and research for estuarine channels where continuous observations of velocity are not always available.

The article of record as published may be found at https://doi.org/10.1117/1.JRS.13.047502. Optical detection systems have the potential to get around some limitations of acous- tic detection systems, especially with increased fleet and port security in noisy littoral waters. Identification of environmental effects especially tropical storms on underwater optical detection is a key to the success. A typhoon-influenced area is chosen in the western North Pacific Ocean with high ocean transparency and low seasonal optical variability. Underwater inherent optical properties (IOPs) such as the beam attenuation coefficient for 470 nm light are measured in the selected region from the U.S. Naval Oceanographic Office sea gliders deployed after super typhoon Guchol’s (June 7 to 20, 2012) passage from June 25 to 30, 2012, and with no typhoon activity from January 9 to February 28, 2014. The observed two sets (with and without typhoon) of IOPs are taken as the input into the Navy’s electro-optical detection simulator. The simulation shows low detection after the super typhoon Guchol-2012’s passage and high detection without typhoon passage.

Based on moored observations and remote sensing data in July and August 2005, energy sources for enhancing turbulent mixing and possible mechanisms of phytoplankton bloom in the continental shelf southeast of Hainan Island under the influence of Washi, a fast-moving and weak tropical storm, are analyzed in this paper. Observations show that strong near-inertial internal waves were generated by the rapidly changing wind stress and the near-inertial energy was dissipated quickly across the thermocline. The strong turbulent mixing associated with the near-inertial barodinic shear instability occurred with maximum eddy diffusivity above 3.2 x 10(-4) m(2) s(-1), and the surface chlorophyll-a (Chl-a) concentration after the storm increased by 22.2%. The Chl-a concentration augment was inferred to be an upper ocean biophysical response to the enhanced near-inertial turbulent mixing which could increase the upward nutrient flux into the surface low eutrophic zone during the passage of Washi. (C) 2013 The Authors. Published by Elsevier B.V. All rights reserved.

International audience; We deployed five broadband three-components seismic stations in the Iles Eparses in the south-west Indian Ocean and on Mayotte Island, between April 2011 and January 2014. These small and remote oceanic islands suffer the effects of strong ocean swells that affect their coastal environments but most islands are not instrumented by wave gauges to characterize the swells. However, wave action on the coast causes high levels of ground vibrations in the solid earth, so-called microseismic noise. We use this link between the solid earth and ocean wave activity to quantify the swells locally. Spectral analyses of the continuous seismic data show clear peaks in the 0.05e0.10 Hz frequency band (periods between 10 and 20 s), corresponding to the ocean wave periods of the local swells. We analyze an example of austral swell occurring in August 2013 and a cyclonic event (Felleng) that developed in January 2013, and quantify the ground motion at each station induced by these events. In both cases, we find a linear polarization in the horizontal plane with microseismic amplitude directly correlated to the swell height (as predicted by the global swell model WaveWatchIII), and a direction of polarization close to the predicted swell propagation direction. Although this analysis has not been performed in real time, it demonstrates that terrestrial seismic stations can be efficiently used as wave gauges, and are particularly well suited for quantifying extreme swell events. This approach may therefore provide useful and cheaper alternatives to wave buoys for monitoring swells and the related environmental processes such as beach erosion or coral reef damages.

The wind-sensitive long-span suspension bridge is a vital element in land transportation. Understanding the wind characteristics at the bridge site is thus of great significance to the wind- resistant analysis of such a flexible structure. In this study, a strong wind event from a landfall typhoon called Soudelor recorded at the Jiangyin Bridge site with the anemometer is taken as the research object. As inherent time-varying trends are frequently captured in typhoon events, the wind characteristics of Soudelor are analyzed in a non-stationary perspective. The time-varying mean is first extracted with the wavelet-based self-adaptive method. Then, the non-stationary turbulent wind characteristics, e.g.; turbulence intensity, gust factor, turbulence integral scale, and power spectral density, are investigated and compared with the results from the stationary analysis. The comparison highlights the importance of non-stationary considerations of typhoon events, and a transition from stationarity to non-stationarity for the analysis of wind effects. The analytical results could help enrich the database of non-stationary wind characteristics, and are expected to provide references for the wind-resistant analysis of engineering structures in similar areas.

The threatened status (both ecologically and legally) of Caribbean staghorn coral, Acropora cervicornis, has prompted rapidly expanding efforts in culture and restocking, although tissue loss diseases continue to affect populations. In this study, disease surveillance and histopathological characterization were used to compare disease dynamics and conditions in both restored and extant wild populations. Disease had devastating effects on both wild and restored populations, but dynamics were highly variable and appeared to be site-specific with no significant differences in disease prevalence between wild versus restored sites. A subset of 20 haphazardly selected colonies at each site observed over a four-month period revealed widely varying disease incidence, although not between restored and wild sites, and a case fatality rate of 8%. A tropical storm was the only discernable environmental trigger associated with a consistent spike in incidence across all sites. Lastly, two field mitigation techniques, (1) excision of apparently healthy branch tips from a diseased colony, and (2) placement of a band of epoxy fully enclosing the diseased margin, gave equivocal results with no significant benefit detected for either treatment compared to controls. Tissue condition of associated samples was fair to very poor; unsuccessful mitigation treatment samples had severe degeneration of mesenterial filament cnidoglandular bands. Polyp mucocytes in all samples were infected with suspect rickettsia-like organisms; however, no bacterial aggregates were found. No histological differences were found between disease lesions with gross signs fitting literature descriptions of white-band disease (WBD) and rapid tissue loss (RTL). Overall, our results do not support differing disease quality, quantity, dynamics, nor health management strategies between restored and wild colonies of A. cervicornis in the Florida Keys.

High-resolution climate models have been shown to improve the statistics of tropical storms (TCs) and hurricanes compared to low-resolution models. The impact of increasing horizontal resolution in the TC simulation is investigated exclusively using a series of Atmospheric Global Climate Model (AGCM) runs with idealized aquaplanet steady-state boundary conditions and a fixed operational storm-tracking algorithm. The results show that increasing horizontal resolution helps to detect more hurricanes, simulate stronger extreme rainfall, and emulate better storm structures in the models. However, increasing model resolution does not necessarily produce stronger hurricanes in terms of maximum wind speed, minimum sea-level pressure, and mean precipitation, as the increased number of storms simulated by high-resolution models is mainly associated with weaker storms. The spatial scale at which the analyses are conducted appears to have more important control on these meteorological statistics compared to horizontal resolution of the model grid. When the simulations are analyzed on common low-resolution grids, the statistics of the hurricanes, particularly the hurricane counts, show reduced sensitivity to the horizontal grid resolution and signs of scale invariance. ©2013. American Geophysical Union. All Rights Reserved.

Ponencia presentada en: VI Congreso Internacional de la Asociación Española de Climatología celebrado en Tarragona del 8 al 11 de octubre de 2008. Este trabajo ha sido posible gracias a la financiación otorgada por el Ministerio de Educación y Ciencia mediante los proyectos NUCLIER (CGL 2004-02325) y NUCLIEREX (CGL 2007- 62664).