988 resultados para heavy rainfall events
Resumo:
The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.
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There are many natural events that can negatively affect the urban ecosystem, but weather-climate variations are certainly among the most significant. The history of settlements has been characterized by extreme events like earthquakes and floods, which repeat themselves at different times, causing extensive damage to the built heritage on a structural and urban scale. Changes in climate also alter various climatic subsystems, changing rainfall regimes and hydrological cycles, increasing the frequency and intensity of extreme precipitation events (heavy rainfall). From an hydrological risk perspective, it is crucial to understand future events that could occur and their magnitude in order to design safer infrastructures. Unfortunately, it is not easy to understand future scenarios as the complexity of climate is enormous. For this thesis, precipitation and discharge extremes were primarily used as data sources. It is important to underline that the two data sets are not separated: changes in rainfall regime, due to climate change, could significantly affect overflows into receiving water bodies. It is imperative that we understand and model climate change effects on water structures to support the development of adaptation strategies. The main purpose of this thesis is to search for suitable water structures for a road located along the Tione River. Therefore, through the analysis of the area from a hydrological point of view, we aim to guarantee the safety of the infrastructure over time. The observations made have the purpose to underline how models such as a stochastic one can improve the quality of an analysis for design purposes, and influence choices.
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Traffic and tillage effects on runoff and crop performance on a heavy clay soil were investigated over a period of 4 years. Tillage treatments and the cropping program were representative of broadacre grain production practice in northern Australia, and a split-plot design used to isolate traffic effects. Treatments subject to zero, minimum, and stubble mulch tillage each comprised pairs of 90-m 2 plots, from which runoff was recorded. A 3-m-wide controlled traffic system allowed one of each pair to be maintained as a non-wheeled plot, while the total surface area of the other received a single annual wheeling treatment from a working 100-kW tractor. Rainfall/runoff hydrographs demonstrate that wheeling produced a large and consistent increase in runoff, whereas tillage produced a smaller increase. Treatment effects were greater on dry soil, but were still maintained in large and intense rainfall events on wet soil. Mean annual runoff from wheeled plots was 63 mm (44%) greater than that from controlled traffic plots, whereas runoff from stubble mulch tillage plots was 38 mm (24%) greater than that from zero tillage plots. Traffic and tillage effects appeared to be cumulative, so the mean annual runoff from wheeled stubble mulch tilled plots, representing conventional cropping practice, was more than 100 mm greater than that from controlled traffic zero tilled plots, representing best practice. This increased infiltration was reflected in an increased yield of 16% compared with wheeled stubble mulch. Minimum tilled plots demonstrated a characteristic midway between that of zero and stubble mulch tillage. The results confirm that unnecessary energy dissipation in the soil during the traction process that normally accompanies tillage has a major negative effect on infiltration and crop productivity. Controlled traffic farming systems appear to be the only practicable solution to this problem.
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The NW Mediterranean region experiences every year heavy rainfall and flash floods that occasionally produce catastrophic damages. Less frequent are floods that affect large regions. Although a large number of databases devoted exclusively to floods or considering all kind of natural hazards do exist, usually they only record catastrophic flood events. This paper deals with the new flood database that is being developed within the framework of HYMEX project. Results are focused on four regions representative of the NW sector of Mediterranean Europe: Catalonia, Spain; the Balearic Islands, Spain; Calabria, Italy; and Languedoc-Roussillon, Midi-Pyrenées and PACA, France. The common available 30-yr period starts in 1981 and ends in 2010. The paper shows the database structure and criteria, the comparison with other flood databases, some statistics on spatial and temporal distribution, and an identification of the most important events. The paper also provides a table that includes the date and affected region of all the catastrophic events identified in the regions of study, in order to make this information available for all audiences.
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In the summer of 2008, the state of Iowa suffered from a series of severe storms that produced tornadoes and heavy rainfall, which resulted in widespread flooding. The Summer Storms1 lasted from late May through mid-August, with the most intense storms occurring over a month-long period from May 25 to June 25. The Summer Storms exacted a major human and economic toll on Iowa, resulting in 18 fatalities and 106 injuries, forcing the evacuation of approximately 38,000 Iowans, and impacting 21,000 housing units. Iowa’s public and private sectors suffered significant monetary damages. Eighty-six of the ninety-nine counties in the state were included in the Governor’s disaster declarations. Presidential disaster declarations made residents in 84 counties eligible for Public Assistance and 78 counties for Individual Assistance. The Rebuild Iowa Advisory Commission estimated $798.3 million in damages to publicly owned buildings and infrastructure, including damages of $53 million to public transportation and $342 million to public utilities. The 2008 Summer Storms presented unique coordination challenges for the Iowa Homeland Security and Emergency Management Division (HSEMD) and the State Emergency Operations Center (SEOC). These challenges arose from three interrelated factors: the large number of local jurisdictions and areas impacted, the prolonged period of time that response operations were conducted, and the increasing complexity of overall response operations. These events caused the SEOC to coordinate response, mitigation, recovery, and preparedness operations simultaneously. HSEMD and the SEOC implemented a variety of measures to enhance their ability to coordinate operations and assistance to localities. The SEOC expanded its organizational structure, implemented innovative techniques, and incorporated new partners into its activities. These steps enabled HSEMD and SEOC to coordinate operations more effectively, which undoubtedly helped save lives and property, while mitigating the effects of the 2008 Summer Storms.
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The soil surface roughness increases water retention and infiltration, reduces the runoff volume and speed and influences soil losses by water erosion. Similarly to other parameters, soil roughness is affected by the tillage system and rainfall volume. Based on these assumptions, the main purpose of this study was to evaluate the effect of tillage treatments on soil surface roughness (RR) and tortuosity (T) and to investigate the relationship with soil and water losses in a series of simulated rainfall events. The field study was carried out at the experimental station of EMBRAPA Southeastern Cattle Research Center in São Carlos (Fazenda Canchim), in São Paulo State, Brazil. Experimental plots of 33 m² were treated with two tillage practices in three replications, consisting of: untilled (no-tillage) soil (NTS) and conventionally tilled (plowing plus double disking) soil (CTS). Three successive simulated rain tests were applied in 24 h intervals. The three tests consisted of a first rain of 30 mm/h, a second of 30 mm/h and a third rain of 70 mm/h. Immediately after tilling and each rain simulation test, the surface roughness was measured, using a laser profile meter. The tillage treatments induced significant changes in soil surface roughness and tortuosity, demonstrating the importance of the tillage system for the physical surface conditions, favoring water retention and infiltration in the soil. The increase in surface roughness by the tillage treatments was considerably greater than its reduction by rain action. The surface roughness and tortuosity had more influence on the soil volume lost by surface runoff than in the conventional treatment. Possibly, other variables influenced soil and water losses from the no-tillage treatments, e.g., soil type, declivity, slope length, among others not analyzed in this study.
Resumo:
Rainfall erosivity is one of the main factors related to water erosion in the tropics. This work focused on relating soil loss from a typic dystrophic Tb Haplic Cambisol (CXbd) and a typic dystrophic Red Latosol (LVdf) to different patterns of natural erosive rainfall. The experimental plots of approximately 26 m² (3 x 8.67 m) consisted of a CXbd area with a 0.15 m m-1 slope and a LVdf area with 0.12 m m-1 slope, both delimited by galvanized plates. Drainpipes were installed at the lower part of these plots to collect runoff, interconnected with a Geib or multislot divisor. To calculate erosivity (EI30), rainfall data, recorded continuously at a weather station in Lavras, were used. The data of erosive rainfall events were measured (10 mm precipitation intervals, accuracy 0.2 mm, 24 h period, 20 min intervals), characterized as rainfall events with more than 10 mm precipitation, maximum intensity > 24 mm h-1 within 15 min, or kinetic energy > 3.6 MJ, which were used in this study to calculate the rainfall erosivity parameter, were classified according to the moment of peak precipitation intensity in advanced, intermediate and delayed patterns. Among the 139 erosive rainfall events with CXbd soil loss, 60 % were attributed to the advanced pattern, with a loss of 415.9 Mg ha-1, and total losses of 776.0 Mg ha-1. As for the LVdf, of the 93 erosive rainfall events with soil loss, 58 % were listed in the advanced pattern, with 37.8 Mg ha-1 soil loss and 50.9 Mg ha-1 of total soil loss. The greatest soil losses were observed in the advanced rain pattern, especially for the CXbd. From the Cambisol, the soil loss per rainfall event was greatest for the advanced pattern, being influenced by the low soil permeability.
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This study presents a catalogue of synoptic patterns of torrential rainfall in northeast of the Iberian Peninsula (IP). These circulation patterns were obtained by applying a T-mode Principal Component Analysis (PCA) to a daily data grid (NCEP/NCAR reanalysis) at sea level pressure (SLP). The analysis made use of 304 days which recorded >100 mm in one or more stations in provinces of Barcelona, Girona and Tarragona (coastland area of Catalonia) throughout the 1950-2005 period. The catalogue comprises 7 circulation patterns showing a great variety of atmospheric conditions and seasonal or monthly distribution. Likewise, we computed the mean index value of the Western Mediterranean Oscillation index (WeMOi) for the synoptic patterns obtained by averaging all days grouped in each pattern. The results showed a clear association between the negative values of this teleconnection index and torrential rainfall in northeast of the IP. We therefore put forward the WeMO as an essential tool for forecasting heavy rainfall in northeast of Spain
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The main objective of the of present study are to study the intraseasonal variability of LLJ and its relation with convective heating of the atmosphere, to establish whether LLJ splits into two branches over the Arabian sea as widely believed, the role of horizonatal wind shear of LLJ in the episodes of intense rainfall events observed over the west coast of India, to perform atmospheric modeling work to test whether small (meso) scale vortices form during intense rainfall events along the west coast; and to study the relation between LLJ and monsoon depression genesis. The results of a study on the evolution of Low Level Jetstream (LLJ) prior to the formation of monsoon depressions are presented. A synoptic model of the temporal evolution of monsoon depression has been produced. There is a systematic temporal evolution of the field of deep convection strength and position of the LLJ axis leading to the genesis of monsoon depression. One of the significant outcomes of the present thesis is that the LLJ plays an important role in the intraseasonal and the interannual variability of Indian monsoon activity. Convection and rainfall are dependent mainly on the cyclonic vorticity in the boundary layer associated with LLJ. Monsoon depression genesis and the episodes of very heavy rainfall along the west coast of India are closely related to the cyclonic shear of the LLJ in the boundary layer and the associated deep convection. Case studies by a mesoscale numerical model (MM5) have shown that the heavy rainfall episodes along the west coast of India are associated with generation of mesoscale cyclonic vortices in the boundary layer.
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TRMM Microwave Imager (TMI) is reported to be a useful sensor to measure the atmospheric and oceanic parameters even in cloudy conditions. Vertically integrated specific humidity, Total Precipitable Water (TPW) retrieved from the water vapour absorption channel (22GHz.) along with 10m wind speed and rain rate derived from TMI is used to investigate the moisture variation over North Indian Ocean. Intraseasonal Oscillations (ISO) of TPW during the summer monsoon seasons 1998, 1999, and 2000 over North Indian Ocean is explored using wavelet analysis. The dominant waves in TPW during the monsoon periods and the differences in ISO over Arabian Sea and Bay of Bengal are investigated. The northward propagation of TPW anomaly and its coherence with the coastal rainfall is also studied. For the diagnostic study of heavy rainfall spells over the west coast, the intrusion of TPW over the North Arabian Sea is seen to be a useful tool.
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Climate models suggest that extreme precipitation events will become more common in an anthropogenically warmed climate. However, observational limitations have hindered a direct evaluation of model-projected changes in extreme precipitation. We used satellite observations and model simulations to examine the response of tropical precipitation events to naturally driven changes in surface temperature and atmospheric moisture content. These observations reveal a distinct link between rainfall extremes and temperature, with heavy rain events increasing during warm periods and decreasing during cold periods. Furthermore, the observed amplification of rainfall extremes is found to be larger than that predicted by models, implying that projections of future changes in rainfall extremes in response to anthropogenic global warming may be underestimated.
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Changes to the behaviour of subseasonal precipitation extremes and active-break cycles of the Indian summer monsoon are assessed in this study using pre-industrial and 2 × CO2 integrations of the Hadley Centre coupled model HadCM3, which is able to simulate the monsoon seasonal cycle reasonably. At 2 × CO2, mean summer rainfall increases slightly, especially over central and northern India. The mean intensity of daily precipitation during the monsoon is found to increase, consistent with fewer wet days, and there are increases to heavy rain events beyond changes in the mean alone. The chance of reaching particular thresholds of heavy rainfall is found to approximately double over northern India, increasing the likelihood of damaging floods on a seasonal basis. The local distribution of such projections is uncertain, however, given the large spread in mean monsoon rainfall change and associated extremes amongst even the most recent coupled climate models. The measured increase of the heaviest precipitation events over India is found to be broadly in line with the degree of atmospheric warming and associated increases in specific humidity, lending a degree of predictability to changes in rainfall extremes. Active-break cycles of the Indian summer monsoon, important particularly due to their effect on agricultural output, are shown to be reasonably represented in HadCM3, in particular with some degree of northward propagation. We note an intensification of both active and break events, particularly when measured against the annual cycle, although there is no suggestion of any change to the duration or likelihood of monsoon breaks. Copyright © 2009 Royal Meteorological Society
Resumo:
It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.
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Many theories for the Madden-Julian oscillation (MJO) focus on diabatic processes, particularly the evolution of vertical heating and moistening. Poor MJO performance in weather and climate models is often blamed on biases in these processes and their interactions with the large-scale circulation. We introduce one of three components of a model-evaluation project, which aims to connect MJO fidelity in models to their representations of several physical processes, focusing on diabatic heating and moistening. This component consists of 20-day hindcasts, initialised daily during two MJO events in winter 2009-10. The 13 models exhibit a range of skill: several have accurate forecasts to 20 days' lead, while others perform similarly to statistical models (8-11 days). Models that maintain the observed MJO amplitude accurately predict propagation, but not vice versa. We find no link between hindcast fidelity and the precipitation-moisture relationship, in contrast to other recent studies. There is also no relationship between models' performance and the evolution of their diabatic-heating profiles with rain rate. A more robust association emerges between models' fidelity and net moistening: the highest-skill models show a clear transition from low-level moistening for light rainfall to mid-level moistening at moderate rainfall and upper-level moistening for heavy rainfall. The mid-level moistening, arising from both dynamics and physics, may be most important. Accurately representing many processes may be necessary, but not sufficient for capturing the MJO, which suggests that models fail to predict the MJO for a broad range of reasons and limits the possibility of finding a panacea.
Resumo:
The Castanhao reservoir was built in the state of Ceara, a dry region in Northeastern Brazil, to regulate the flow of the Jaguaribe River, for irrigation, and for power generation. It is an earth-filled dam, 60 m high, with a water capacity of 4.5 x 10(9) m(3). The seismicity in the area has been monitored since 1998, with a few interruptions, using one analog or one digital station and, during a few periods, a three-station network. The first earthquakes likely to be induced events were detected in 2003, when the water level was about 20 in high. In early 2004 a very heavy rainfall season quickly filled the reservoir. Shortly after, an increase in the seismic activity occurred and many micro-earthquakes were recorded. We suggest that this activity resulted from an increase in pore pressure due to undrained response. Therefore, we may classify this cluster of microearthquakes as ""initial seismicity."" We deployed a network with four analog stations in the area, following this activity, to determine the epicentral zone. At least three epicentral areas under the reservoir were detected. The spatio-temporal analysis of the available data revealed that the seismicity occurs in clusters and that these were activated at different periods. We identified four sets of faults (N-S-, E-W-, NW-SE-, and NE-SW-oriented), some of which moved in shallow crustal levels and as recently as the Quaternary (1.8 Ma). Under the present-day stress regime, the last two sets moved as strike-slip structures. We suggest a possible correlation between dormant faults and the observed induced seismicity. (c) 2008 Elsevier B.V. All rights reserved.