Search

O sistema costeiro consiste em um conjunto de fatores sujeito às marés, ventos, ondas, correntes oceânicas e o impacto das tempestades. Nesse sentido, o município de Jaguaruna (SC), situado em uma zona costeira, encontra-se sujeito aos impactos decorrentes das marés de tempestade. Assim, o presente estudo tem por objetivo analisar a amplitude das inundações costeiras oriundas dos eventos meteorológicos extremos, apresentando resultados de cotas de inundação extrema e a área urbana exposta aos eventos de inundação. A cota de inundação foi obtida a partir da soma da maré astronômica, maré meteorológica e do runup. Para tanto, a metodologia empregada consistiu em calcular valores de cota de inundação, utilizando a modelagem numérica SMC-Brasil, com uma base de dados de 60 anos (1948 a 2008) de ondas e marés, além da batimetria disponível na modelagem. A partir deste cálculo foram obtidos os valores de cota de inundação associados a regimes extremos de período de retorno de 5, 10, 25, 50 e 100 anos. Posteriormente, foi delimitado os regimes extremos de cotas de inundação para os respectivos anos, para tal foram utilizados dados topográficos de um Modelo Digital do Terreno (MDT), considerando os limites da inundação as áreas com valores topográficos menores que a cota de inundação. A análise da área urbana exposta a inundação se deu por meio da sobreposição da área urbana e da mancha de inundação, com o uso da ferramenta Intersect, disponível no Software ArcGis 10.6, tornando possível mensurar a área urbana atingida pelos regimes extremos de inundação. Também foi realizada apuração da área urbana atingida por um evento meteorológico extremo, com a busca de informações sobre inundações costeiras ocorridas na área de estudo, com isso, constatou-se que durante o evento meteorológico ocorrido em outubro de 2016, a amplitude da maré de tempestade alcançou a cota de inundação referente ao PR de 10 anos. Os resultados mostraram diferentes valores de cota de inundação ao longo da área, na porção norte os valores foram de 2,9 m e na porção sul os valores ficaram em 3,4 m, tomando como base o PR de 5 anos. Esses valores aumentaram gradativamente para os demais PR. A delimitação da mancha de inundação e posterior mensuração da área atingida demonstrou que o Balneário Campo Bom é o mais exposto a inundação costeira, em todos os períodos de retorno analisado. A metodologia empregada neste estudo se mostrou eficaz para realizar análise da amplitude das inundações costeiras. Por fim, consistem em ferramentas viáveis para auxiliar a gestão pública na tomada de decisões e no planejamento urbano, de forma que apontam as áreas atingidas por eventos extremos de inundação costeira, contribuindo assim, para o gerenciamento costeiro. The coastal system is a combination of factors susceptible to tides, winds, waves, ocean currents and the impact of storms. Since the city of Jaguaruna (SC) is located in a coastal zone, it is subjected to the impact caused by storm tides. This study aims at analysing the extension of coastal floods caused by extreme weather events and indicating the extreme flooding rates and the urban area exposed to such flooding events. The flooding rate was calculated by adding up high tides, storm surge, and the run-up. The methodology used consisted of calculating the flooding rate values by using the SMC-Brazil numerical modeling, a database of 60 years (1948-2008) of information on waves and tides and the bathymetry available in the model. From this estimate, we got the rates of flooding prompted by extreme regime in the return period of 5, 10, 25, 50 and 100 years. After that, we narrowed the flooding rates of extreme regime for the respective years, using a Digital Terrain Model (DTM) that equalled the flooding limits to the areas with topographic figures lower than the flooding rate. The analysis of the urban area exposed to the flood occurred through the overlapping of the urban area and the flooded spot, using the Intersect tool, available in the ArcGIS 10.6 Software, making it possible to measure the urban area affected by extreme flood regimes. It was also verified the urban area reached by an extreme meteorological event, with the search for information about coastal floods occurred in the study area, with that, it was verified that during the meteorological event occurred and October 2016, the amplitude of the storm surge reached the flood quota for the 10-year RP.The results have shown different values for the flooding rate throughout the area: in the north, the values were 2.9 m, and in the south, 3.4 m, considering a 5 year RP. These values rise gradually according to the RPs. The demarcation of the flooded spot and further measurement of the stricken area showed that Campo Bom Beach is the more susceptible one to coastal flood in all the RP assessed. The methodology used in this research has proven effective in analysing the range of coastal floodings. They are viable tools to help public administration in the decision-making and urban planning by pointing out the areas stricken by extreme events of coastal flood and helping in the management of coastal areas.

The authors are very grateful to the Uruguayan water supply company (OSE-UGD), the Uruguayan Institute of Meteorology (INUMET) and the Uruguayan National Water Directorate (DINAGUA) for providing long-term data on physicochemical, biological, hydrological and meteorological variables. We also thank to Dra. Carla Kruk for her comments on phytoplankton morphology-based functional groups dynamics, to MSc. Magdalena Crisci for her assistance in the digitalization of bathymetric data, to Dra.Valeria Durañona for her advice on the analysis of extreme wind events in Uruguay, and to Paula Santos for language revision.; International audience; A multi-model approach to predict phytoplankton biomass and composition was performed in a eutrophic Uruguayan shallow lake which is the second drinking water source of the country. We combined statistical (spectral analysis and Machine learning techniques) and physically based models to generate, for the first time in this system, a predictive tool of phytoplankton biomass (chlorophyll-a) and composition (morphology-based functional groups). The results, based on a 11-year time series, revealed two alternating phases in the temporal dynamics of phytoplankton biomass. One phase is characterized by high inorganic turbidity and low phytoplankton biomass, and the other by low inorganic turbidity and variable (low and high) phytoplankton biomass. A threshold of turbidity (29 TNU), above which phytoplankton remains with low biomass (

Newly developed approaches based on satellite altimetry and gravity measurements provide promising results on glacier dynamics in the Pamir-Himalaya but cannot resolve short-term natural variability at regional and finer scale. We contribute to the ongoing debate by upscaling a hydrological model that we calibrated for the central Pamir. The model resolves the spatiotemporal variability in runoff over the entire catchment domain with high efficiency. We provide relevant information about individual components of the hydrological cycle and quantify short-term hydrological variability. For validation, we compare the modeled total water storages (TWS) with GRACE (Gravity Recovery and Climate Experiment) data with a very good agreement where GRACE uncertainties are low. The approach exemplifies the potential of GRACE for validating even regional scale hydrological applications in remote and hard to access mountain regions. We use modeled time series of individual hydrological components to characterize the effect of climate variability on the hydrological cycle. We demonstrate that glaciers play a twofold role by providing roughly 35% of the annual runoff of the Panj River basin and by effectively buffering runoff both during very wet and very dry years. The modeled glacier mass balance (GMB) of -0.52 m w.e. / yr (2002–2013) for the entire catchment suggests significant reduction of most Pamiri glaciers by the end of this century. The loss of glaciers and their buffer functionality in wet and dry years could not only result in reduced water availability and increase the regional instability, but also increase flood and drought hazards.

Póster presentado en: 10th EUMETNET Data Management Workshop celebrado en St. Gallen, Suiza, del 28 al 30 de octubre de 2015. The CCS (Spanish Insurance Compensation Consortium) is the Spanish Agency that provides insurance coverage against weather events that involve an extraordinary risk. One of the extraordinary risks covered by the CCS refers to extraordinary wind, defined as those with wind gusts exceeding 120 km/h. The accurate delimitation of the areas in which this condition is met shows considerable difficulties in our country because of the lack of wind observations and the complexity of the terrain. The operational procedure performed at AEMET (Spanish Meteorological Agency) for estimating the areas with maximum wind gusts applies a geostatistical technique, the universal kriging, based on the observational data of maximum wind gust and drawing also on external variables: terrain elevation, distance from the shore, and the HIRLAM (High Resolution Limited Area Model) forecasting model output of maximum wind gust field. Extreme meteorological events sometimes go unnoticed but frequently become apparent due their impact on society with its corresponding consequences. Moreover, the catastrophic nature of a phenomenon depends not only on the extreme value that the climate element takes on, but also on other factors, such as population distribution or geomorphological features, among many others. In this work we present some preliminary steps in the development of a catastrophic model of extreme wind gust situations in peninsular Spain. The main aim of this model is to provide significant information for covering risk against future extreme wind situations, as well as assessing the liability owing to this risk on a year time-frame. The first steps in the development of this model are: a) the generation of climatology of the areas under extraordinary wind going back to 2010 and, b) the estimation of incurred covered loss in these years based on data from the insurer. The following step will be the estimation of a local (at municipality level at best) expected loss function from extraordinary winds depending on the intensity of the event. This project is being sponsored by CCS

The hypothesis is that yield variations due to an extreme event (cold temperature, high temperature or water deficit) is mediated by a change in Harvest Index (HI), while the main effect of weather on crop performance is already captured by existing crop models.

Soil temperature analysis is becoming more important in the climate change issue. In this paper, the focus is on the trend analysis of extreme soil temperatures, which are very important for the management of crops in agriculture. Maximal and minimal soil temperatures were analyzed on annual and seasonal scale for depths 2, 5, 10 and 20 cm for the period 1961–2010. Monthly, seasonal, and annual data were extracted from daily measurements at a standard climatological time (7 h, 14 h, 21 h CET) at 18 meteorological stations. The variability of detrended data is represented by interquartile range. Trends were determined by Theil Sen's estimator, and statistical significance on 5 % level was determined using the Mann-Kendall test.In general, variability decreases with depth in all seasons, and is larger for maximal soil temperature of surface layer. The results of trend analysis show a general increase of maximal soil temperature at almost all stations in spring and summer seasons, whilst the number of significant trends of minimal soil temperature is much smaller in all seasons. Trends of annual maximal soil temperature are almost equal to summer trends, and ranges from 1.0–2.3 °C/decade. Significant trends of minimal soil temperature are smaller for an order of magnitude (-0.4–0.7°C/decade), with few exceptions in the surface layer of spring and summer season. The analysis shows a significant increase of the maximum soil temperature in spring and summer seasons in agricultural areas and the results may suggest the necessary adjustments to farmers when choosing seeding varieties.