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Multi-hazard events, characterized by the simultaneous, cascading, or cumulative occurrence of multiple natural hazards, pose a significant threat to human lives and assets. This is primarily due to the cumulative and cascading effects arising from the interplay of various natural hazards across space and time. However, their identification is challenging, which is attributable to the complex nature of natural hazard interactions and the limited availability of multi-hazard observations. This study presents an approach for identifying multi-hazard events during the past 123 years (1900-2023) using the EM-DAT global disaster database. Leveraging the 'associated hazard' information in EM-DAT, multi-hazard events are detected and assessed in relation to their frequency, impact on human lives and assets, and reporting trends. The interactions between various combinations of natural hazard pairs are explored, reclassifying them into four categories: preconditioned/triggering, multivariate, temporally compounding, and spatially compounding multi-hazard events. The results show, globally, approximately 19 % of the 16,535 disasters recorded in EM-DAT can be classified as multi-hazard events. However, the multi-hazard events recorded in EM-DAT are disproportionately responsible for nearly 59 % of the estimated global economic losses. Conversely, single hazard events resulted in higher fatalities compared to multi-hazard events. The largest proportion of multi-hazard events are associated with floods, storms, and earthquakes. Landslides emerge as the predominant secondary hazards within multi-hazard pairs, primarily triggered by floods, storms, and earthquakes, with the majority of multi-hazard events exhibiting preconditioned/triggering and multivariate characteristics. There is a higher prevalence of multi-hazard events in Asia and North America, whilst temporal overlaps of multiple hazards predominate in Europe. These results can be used to increase the integration of multi-hazard thinking in risk assessments, emergency management response plans and mitigation policies at both national and international levels.
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Nearly half of the natural disasters in the world are due to hydro-geomorphological hazards. Therefore, rainfall forecast is a key parameter for the implementation of landslides and flash-floods early warning systems. In this work we developed a routine in R software that enables the validation of a 3-day rainfall forecast by comparison with the daily rainfall data recorded in 101 automatic meteorological stations available in mainland Portugal. The routine integrates the pre-processing of base data, the matching between the 3-day rainfall forecast and the daily rainfall registered in the automatic meteorological stations based on sequence of days, the estimation of the difference between the forecasted and the real rainfall values and the computation of error measures, such as the bias, the mean absolute error, the mean absolute percentage error and the root mean square error. The results from the error measures, estimated for the 101 automatic meteorological stations, are then exported to an excel file. The routine is implemented for mainland Portugal and tested using data from February 2015, however, the spatial and temporal data can be easily updated for other regions.â¢A routine to validate the rainfall forecast at the regional scale using R programming language is implemented.â¢The automated routine can be easily updated and adapted with different spatial and temporal scales.
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Portugal is regularly affected by destructive wildfires that have severe social, economic, and ecological impacts. The total burnt area in 2017 (â¼540,000 ha) marked the all-time record value since 1980 with a tragic toll of 114 fatalities that occurred in June and October events. The local insurance sector declared it was the costliest natural disaster in Portugal with payouts exceeding USD295 million. Here, the 2017 October event, responsible for more than 200,000 ha of burnt area and 50 fatalities is analyzed from a compound perspective. A prolonged drought led to preconditioned cumulative hydric stress of vegetation in October 2017. In addition, on 15 October 2017, two other major drivers played a critical role: 1) the passage of hurricane Ophelia off the Coast of Portugal, responsible for exceptional meteorological conditions and 2) the human agent, responsible for an extremely elevated number of negligent ignitions. This disastrous combination of natural and anthropogenic drivers led to the uncontrolled wildfires observed on 15 October.
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Consideration of compound drivers and impacts are often missing from applications within the Disaster Risk Reduction (DRR) cycle, leading to poorer understanding of risk and benefits of actions. The need to include compound considerations is known, but lack of guidance is prohibiting practitioners from including these considerations. This article makes a step toward practitioner guidance by providing examples where consideration of compound drivers, hazards, and impacts may affect different application domains within disaster risk management. We discern five DRR categories and provide illustrative examples of studies that highlight the role of "compound thinking" in early warning, emergency response, infrastructure management, long-term planning, and capacity building. We conclude with a number of common elements that may contribute to the development of practical guidelines to develop appropriate applications for risk management.
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One of the most robust signals of climate change is the relentless rise in global mean surface temperature, which is linked closely with the water-holding capacity of the atmosphere. A more humid atmosphere will lead to enhanced moisture transport due to, among other factors, an intensification of atmospheric rivers (ARs) activity, which are an important mechanism of moisture advection from subtropical to extra-tropical regions. Here we show an enhanced evapotranspiration rates in association with landfalling atmospheric river events. These anomalous moisture uptake (AMU) locations are identified on a global scale. The interannual variability of AMU displays a significant increase over the period 1980-2017, close to the Clausius-Clapeyron (CC) scaling, at 7 % per degree of surface temperature rise. These findings are consistent with an intensification of AR predicted by future projections. Our results also reveal generalized significant increases in AMU at the regional scale and an asymmetric supply of oceanic moisture, in which the maximum values are located over the region known as the Western Hemisphere Warm Pool (WHWP) centred on the Gulf of Mexico and the Caribbean Sea.
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A Lagrangian analysis is applied to identify the main moisture source areas associated with atmospheric rivers (ARs) making landfall along the west coast of South Africa during the extended austral winter months from 1980 to 2014. The results show that areas that provide the anomalous uptake of moisture can be categorized into four regions: (1) the South Atlantic Ocean between 10°S and 30°S, (2) a clear local maximum in the eastern South Atlantic, (3) a continental source of anomalous uptake to the north of the Western Cape, and (4) over South America at a distance of more than 7000 km from the target region. It emerges that the South American moisture source can be linked to a particular phase of the South American low-level jet, known as a no Chaco jet event (NCJE), which transports moisture to the western and central South Atlantic basin. Concisely, we provide strong evidence that the two margins of the South Atlantic Ocean appear connected by two meteorological structures, with the NCJE playing a key role of transporting moisture from South America to the western and central South Atlantic basin, feeding the AR that transports some of the moisture to the west coast of South Africa.
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Modelos Teóricos , Estaciones del Año , Temperatura , África Austral , Océano Atlántico , América del SurRESUMEN
The aim of the work described herein was to study projection scenarios in order to find changes in the synoptic variability of the northwest Iberian Peninsula in the 21st century. To this end, we investigated the changes in the frequency of the different circulation types computed for the study area using three different models used in the IPCC 4(th) assessment report. The circulation types were computed using the procedure known as Lamb circulation types. The control simulation for the late 20th century was evaluated objectively from the results obtained using data from the NCEP/NCAR reanalysis, as to evaluate the ability of the model to reproduce the present climate. We have compared not only seasonal mean sea level pressure fields but also the mean seasonal frequency of circulation types. The results for the end of the 21st century show a decrease in the frequency of cyclonic, W, and SW circulation types in the spring and summer months. This trend also appears in the autumn, with a concomitant increase in the anticyclonic types.
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Procesos Climáticos , Simulación por Computador , Movimientos del Aire , Presión del Aire , Clima , Tormentas Ciclónicas , Europa (Continente) , Predicción , Estaciones del AñoRESUMEN
An analysis of the frequency of cyclones and surface wind velocity for the Euro-Atlantic sector is performed by means of an objective methodology. Monthly and seasonal trends of cyclones and wind speed magnitude are computed and trends between 1960 and 2000 evaluated. Results reveal a significant frequency decrease (increase) in the western Mediterranean (Greenland and Scandinavia), particularly in December, February, and March. Seasonal and monthly analysis of wind magnitude trends shows similar spatial patterns. We show that these changes in the frequency of low-pressure centers and the associated wind patterns are partially responsible for trends in the significant height of waves. Throughout the extended winter months (October-March), regions with positive (negative) wind magnitude trends, of up to 5 cm/s/year, often correspond to regions of positive (negative) significant wave height trends. The cyclone and wind speed trends computed for January-March are well matched by the corresponding trends in significant wave height, with February being the month with the highest trends (negative south of lat 50 degrees N up to -3 cm/year, and positive up to 5 cm/year just north of Scotland). Trends in European precipitation are assessed using the Climatic Research Unit data set. The results of the assessment emphasize the link with the corresponding tendencies of cyclone frequencies. Finally, it is shown that these changes are associated, to a large extent, with the preferred phases of major large-scale atmospheric circulation modes, particularly with the North Atlantic Oscillation, the eastern Atlantic pattern, and the Scandinavian pattern.