Suchergebnisse

Rainfall-induced landslides number among the most devastating natural hazards in the world and early warning models are urgently needed to reduce losses and fatalities. Most landslide early warning systems are based on rainfall thresholds defined on the regional scale, regardless of the different landslide susceptibilities of various slopes. Here we divided slope units in southern Taiwan into three categories (high, moderate and low) according to their susceptibility. For each category, we established separate rainfall thresholds so as to provide differentiated thresholds for different degrees of susceptibility. Logistic regression (LR) analysis was performed to evaluate landslide susceptibility by using event-based landslide inventories and predisposing factors. Analysis of rainfall patterns of 941 landslide cases gathered from field investigation led to the recognition that 3 h mean rainfall intensity ( I 3 ) is a key rainfall index for rainfall of short duration but high intensity; in contrast, 24 h accumulated rainfall ( R 24 ) was recognized as a key rainfall index for rainfall of long duration but low intensity. Thus, the I 3 – R 24 rainfall index was used to establish rainfall thresholds in this study. Finally, an early warning model is proposed by setting alert levels including yellow (advisory), orange (watch) and red (warning) according to a hazard matrix. These differentiated thresholds and alert levels can provide essential information for local governments to use in deciding whether to evacuate residents.

All aspects of human life are, directly or indirectly, affected by climatic processes. This effect is especially noticeable in such fields as agriculture, irrigation, economy, telecommunications, transportation, traffic, air pollution and military industries (Haltiner & Williams 1980). A number of researchers have studied the possibility of forecasting rainfall several months in advance using climate indices such as SOI, PDOI and NPI (e.g. Silverman and Dracup 2000). A well-known atmospheric phenomenon is the Southern Oscillation (SO). The SO is an atmospheric see-saw process in the tropical Pacific sea level pressure between the eastern and western hemispheres associated with the El Niño and La Niña oceanographic features. The oscillation can be characterized by a simple index, the Southern Oscillation Index (SOI). (Kawamura et al., 1998). The Pacific Decadal Oscillation index (PDOI) is the leading principal component of monthly sea surface temperature (SST) anomalies in the North Pacific Ocean north of 20°N (Zhang et al., 1997; Mantua et al., 1997). Trenberth and Hurrell (1994) have defined the North Pacific Index (NPI) as the area-weighted sea level pressure over the region 30°N to 65°N, 160°E to 140°W to measure the decadal variations of atmosphere and ocean in the north Pacific. ; https://digitalcommons.usu.edu/modern_climatology/1013/thumbnail.jpg

Abstract. This study investigates the atmospheric pattern circulations associated with heavy rainfall (HR) days in Calabria, southern Italy, and contributes to the understanding of the dynamical mechanisms that produce those events. Heavy rainfall days are extracted from the raingauge database of the "Protezione Civile Regionale", which has more than a hundred pluviometric stations for the period 1999–2007 (eight years). To study the synoptic atmospheric circulations associated with HR we use the Regional Atmospheric Modeling System (RAMS) gridded data field of 925 hPa and 500 hPa geopotential height. First the number of variables is reduced by principal component analysis (PCA), then a cluster analysis (CA) is applied on those new atmospheric variables and eleven atmospheric patterns are obtained. Clear associations emerged between each of the circulation types and rainfall patterns over Calabria for HR days. These associations can be explained by the interaction between the complex orography of the region, the sea and the synoptic scale flow.

Climate change is attributed indirectly or directly to anthropogenic activities that has led to subsequent changes in the global atmospheric composition and hence the observed climate variability over period of time. Maize crop is very sensitive to climatic change conditions such as rainfalls patterns and onset. These changes have potentially compromised agricultural production systems and hence having a negative effect on the food supply in the country, it is therefore imperative to understand the effect of seasonal annual variability of rainfall among the small-scale farmers in Endebess Sub-County, Trans Nzoia County, Kenya between 2008- 2018. The study was based on 150 maize farmers in wards namely; Chepchoina, Matumbei and Endebess. Primary data was obtained from randomly selected farmers through questionnaires, while secondary data on rainfalls and maize production yields was collected from Kitale Meteorological Departments and Endebess Sub-County Ministry of Agriculture offices respectively between 2008-2018. The data collected was analyzed using Statistical Package for Social Sciences version 22 and Precipitations Concentration Index (PCI) values. The study findings on analysis of annual rainfall between 2008–2018 in PCI was 9.3 and seasonal variability was PCI 16 which means uniform distributions of rainfalls between the years. However, the finding found that there was a positive relationship between rainfall and maize yields r = 0.625 while annual rainfall variable index is significant to seasonal months' variability. This study recommends that both National Government and County Government of Trans Nzoia should create awareness on climate change and adaptations measures to rainfall variability in the study area.

AbstractThere is growing evidence that early life conditions are important for outcomes during adolescence, including cognitive development and education. Economic conditions at the time children enter school are also important. We examine these relationships for young adolescents living in a low-income drought-prone pastoral setting in Kenya using historical rainfall patterns captured by remote sensing as exogenous shocks. Past rainfall shocks measured as deviations from local long-term averages have substantial negative effects on the cognitive development and educational achievement of girls. Results for the effects of rainfall shocks on grades attained, available for both girls and boys, support that finding. Consideration of additional outcomes suggests the effects of rainfall shocks on education are due to multiple underlying mechanisms including persistent effects on the health of children and the wealth of their households, underscoring the potential value of contemporaneous program and policy responses to such shocks.

18 Pags.- 14 Figs. © 2016 The Authors. Published by Elsevier B.V. This is an open access article under a CC BY license (http://creativecommons.org/licenses/by/4.0/). ; Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315 MJ mm ha− 1 h− 1) compared to winter (87 MJ mm ha− 1 h− 1). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year. ; Peer reviewed

Yield variability in Ethiopian agriculture can be partly explained by
rainfall. The degree of yield variability over time is changed not only by
the amount of rainfall, but also by the pattern and frequency of the
rainfall cycle. Mean annual rainfall is often the only index of rainfall
quoted for a place for the purpose of rainfall-yield relationship analysis.
For agriculture, however, the critical question is how often a place
receives too little, enough or too much rain for a particular form of crop
production to be carried out successfully. Using station level rainfall
data from 1954-1994 and agricultural production data of major cereal
crops from 1980-1994 for four provinces of Ethiopia, this study
attempts to show patterns of rainfall and provide insight into the
preparation of an early warning system in the country. Time series
analysis techniques, Auto-Regressive Moving Average (ARMA) and
Vector Auto-Regressive (VAR) models are used to see the pattern of
rainfall and response of yield to rainfall as well as to previous yield
shocks. The results of this study show that rainfall cycle can be
determined only for BELG rain in Gojjam (thirty-five years) and total
rain in Harar (eleven years) and Jima (seventeen years). All other series
have no cyclical component; however, drought-prone provinces show
some deterministic component in the rainfall process. Results from
estimation of VAR show that current levels of yield respond to previous
levels of yield even more than responses to rainfall in most provinces.

PR ; IFPRI1; CRP5; The Water Energy Food Nexus; ISI; 1 Fostering Climate-Resilient and Sustainable Food Supply ; EPTD ; CGIAR Research Program on Water, Land and Ecosystems (WLE)

Abstract. An accurate knowledge of the weather patterns causing winter rainfall over the Scorff watershed in western Brittany (W. France) was developed prior to studies of the impact of the climate factor on land use management, and of the hydrological reponses to rain-producing weather patterns. These two studies are carried out in the context of the climate change. The identification of rainy air-circulation types was realized using the objective computational version of the 29-type Hess and Brezowsky Grosswetterlagen system of classifying European synoptic regimes, for the cold season (November-March) of the 1958–2005 period at the reference weather station of Lorient, and 13 other stations located in western and southern Brittany, including a more detailed study for the wet 2000–2001 cold season for three reference stations of the Scorff watershed (Lorient, Plouay and Plouray). The precipitation proportion (including the days with rainfall ≥20 mm) was calculated by major air-circulation type (GWT: see Appendix A) and by individual air-circulation subtype (GWL: see Appendix A) for the studied time-period. The most frequently occurrence of rainy days associated with westerly and southerly GWL confirmed well-known observations in western Europe and so justify the use of the Hess-Brezowsky classification in other areas outside Central Europe. The southern or south-western exposure of the watershed with a hilly inland area enhanced the heavy rainfall generated by the SW and S circulation types, and increased the difference between the rainfall amounts of coastal and inland stations during the wettest days.

Abstract. This brief communication introduces a new quality-controlled precipitation database for Calabria, shows the precipitation trend for the period considered, and correlates daily rainfall with some common teleconnection patterns. The database consists of daily accumulated precipitation collected by 61 rain gauges from 1 January 1970 to 31 December 2006. The 37-year trend in yearly rainfall shows a decrease of 4.7 mm/y, with a 17% reduction in the yearly mean value. The correlation of the daily rainfall with large-scale patterns shows that the Mediterranean Oscillation Index (MOI a/c) is a useful predictor of daily precipitation over Calabria.

Abstract. In the face of climate change, the assessment of land transport infrastructure exposure towards adverse climate events is of major importance for Europe's economic prosperity and social wellbeing. In this study, a climate index estimating rainfall patterns which trigger landslides in central Europe is analysed until the end of this century and compared to present-day conditions. The analysis of the potential future development of landslide risk is based on an ensemble of dynamically downscaled climate projections which are driven by the SRES A1B socio-economic scenario. Resulting regional-scale climate change projections across central Europe are concatenated with Europe's road and railway network. Results indicate overall increases of landslide occurrence. While flat terrain at low altitudes exhibits an increase of about 1 more potentially landslide-inducing rainfall period per year until the end of this century, higher elevated regions are more affected and show increases of up to 14 additional periods. This general spatial distribution emerges in the near future (2021–2050) but becomes more pronounced in the remote future (2071–2100). Since largest increases are to be found in Alsace, potential impacts of an increasing amount of landslides are discussed using the example of a case study covering the Black Forest mountain range in Baden-Württemberg by further enriching the climate information with additional geodata. The findings derived are suitable to support political decision makers and European authorities in transport, freight and logistics by offering detailed information on which parts of Europe's ground transport network are at particularly high risk concerning landslide activity.

AbstractThe flood and drought cycles suffered of old by the province of Malaga, the variability in the distribution of rainfall throughout the province and the reduced length of the data series make it of interest to carry out a regional analysis (RA) of the yearly maximum daily precipitation data to obtain appropriate rainfall quantiles. By taking these maximum precipitations values from 72 weather stations, and their physiographic parameters latitude and altitude, four regions with similar rainfall patterns have been determined by the principal component analysis statistical technique. Then, carrying out an RA of the yearly maximum daily precipitations for each of the regions discriminated, it was observed that three of them were homogeneous for the parameter being studied. In those homogeneous regions that grouped data of different stations but close rainfall pattern, frequency curves could be calculated for several return periods by means of the functions that best fit the data of each region. With these regional curves, it has been possible to obtain more accurate values of the maximum daily quantiles for each of the stations analysed than through the conventional local frequency analysis.