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The Mediterranean region is an area potentially vulnerable to climatic changes. In fact, it is characterized by a significant precipitation variability resulting from synoptic dynamics of hazardous events moving and evolving along the Mediterranean basin. In this paper, the results of an investigation on rainfall trend in the Sardinia region are presented. The trend analysis has been performed by means of the Mann–Kendall test and of the Theil–Sen estimator applied on annual, seasonal, and monthly scales. To this aim, a monthly database of precipitation registered at 158 rain gauges, with an average observation of 84 years, was used for the analyses. The results mainly evidenced a rainfall amount reduction in the winter months and an increase during the summer months. The monthly rainfall distribution throughout the year was also investigated by means of the precipitation concentration index (PCI). A negative trend emerged and, more specifically, a tendency towards a more uniform rainfall distribution on the Sardinia region throughout the year. [ABSTRACT FROM AUTHOR]

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

Summer precipitation anomalies over eastern China are characterized spatially by meridionally banded structures fluctuating on interannual and interdecadal timescales, leading to regional droughts and floods. In addition to long-term trends, how these patterns may change under global warming has important implications for agricultural planning and water resources over this densely populated area. Using the latest Hadley Centre climate model, HadGEM3-GC2, this paper investigates the potential response of summer precipitation patterns over this region, by comparing the leading modes between a 4×CO2 simulation and the model’s pre-industrial control simulation. Empirical Orthogonal Function (EOF) analyses show that the first two leading modes account for about 20% of summer rainfall variability. EOF1 is a monopole mode associated with the developing phase of ENSO events and EOF2 is a dipole mode associated with the decaying phase of ENSO. Under 4×CO2 forcing, the dipole mode with a south-north orientation becomes dominant because of a strengthened influence from excessive warming of the Indian Ocean. On interdecadal time scales, the first EOF looks very different from the control simulation, showing a dipole mode of east-west contrast with enhanced influence from high latitudes. [ABSTRACT FROM AUTHOR]

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Niño to Yangtze River basin rainfall meant that the strong El Niño in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements. [ABSTRACT FROM AUTHOR]

Global Climate Models (GCMs) have been extensively used in many climate change impact studies. However, the coarser resolution of these GCM outputs is not adequate to assess the potential effects of climate change on local scale. Downscaling techniques have thus been proposed to resolve this problem either by dynamical or statistical approaches. The statistical downscaling (SD) methods are widely privileged because of their simplicity of implementation and use. However, many of them ignore the observed spatial dependence between different locations, which significantly affects the impact study results. An improved multi-site SD approach is thus presented in this paper to downscaling of daily precipitation at many sites concurrently. This approach is based on a combination of multiple regression models for rainfall occurrences and amounts and the Singular Value Decomposition technique, which models the stochastic components of these regression models to preserve accurately the space-time statistical properties of the daily precipitation. Furthermore, this method was able to describe adequately the intermittency property of the precipitation processes. The proposed approach has been assessed using 10 rain gauges located in the southwest region of Quebec and southeast region of Ontario in Canada, and climate predictors from the National Centers for Environmental Prediction/National Centre for Atmospheric Research re-analysis data set. The results have indicated the ability of the proposed approach to reproduce accurately multiple observed statistical properties of the precipitation occurrences and amounts, the at-site temporal persistence, the spatial dependence between sites and the temporal variability and spatial intermittency of the precipitation processes. [ABSTRACT FROM AUTHOR]

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern. [ABSTRACT FROM AUTHOR]

Worldwide climate is likely to become more variable or extreme with increases in intense precipitation. In Mediterranean areas, climate change will increase the risks of droughts, flash floods and soil erosion. Despite rainfall intensity being a key factor in erosive processes, in these areas information on extreme rainfall intensity and the associated erosivity, based on high-temporal resolution data, is either non homogeneous or scarce. These parameters thus need to be assessed in order to highlight suitable adaptation strategies. In this paper, an hourly rainfall intensity (RI) data series is analyzed together with the corresponding 1-min rainfall intensity maximum (RIm) of 23 rainfall gauges located in Tuscany, Italy, in an area highly vulnerable to erosion. The aim is to look for temporal trends (1989-2010) in extreme rainfall intensity and erosivity. Fixed effect logistic regression shows statistically significant temporal increases in the number of RI and RIm exceedances over the 95th percentile threshold. Winter is shown to be the season with the strongest increasing trend in coastal and inland rainfall gauge groups, followed by spring for the coastal group and autumn for the inland group. Linear regressions show that in the inland group there is a temporal increase in rainfall erosivity and on a seasonal basis, the highest increase is observed in autumn. By contrast, for the coastal group this increasing trend is only detectable for spring and winter. Such an increase in rainfall erosivity and its potential continuation could have a strong adverse effect on Mediterranean land conservation. [ABSTRACT FROM AUTHOR]

This paper analyses the temporal and spatial changes in the amount and variability of rainfall in Scotland. The sequential Mann-Kendall test reveals that total annual precipitation has increased across Scotland since the 1970s with increasing trends in variability beginning between the mid-1960s and the mid-1970s. Whilst temporally consistent increasing trends in precipitation totals prevail in the West, many weather stations in the East have experienced subsequent trend turning points in the following two decades, explaining the larger magnitude of the trends in western Scotland in recent decades. Trend analyses on six measures of rainfall variability indicate an increase in rainfall variability during the period 1961-2000, as measured by the intra-annual variance, the winter to summer precipitation ratio and the annual cumulative sum range, with decreasing trends observed in the number of dry days. Periodicities associated with the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation could explain the observed temporal variability of rainfall. [ABSTRACT FROM AUTHOR]

This paper addresses deficiencies of stochastic Weather Generators (WGs) in terms of reproduction of low-frequency variability and extremes, as well as the unanticipated effects of changes to precipitation occurrence under climate change scenarios on secondary variables. A new weather generator (named IWG) is developed in order to resolve such deficiencies and improve WGs performance. The proposed WG is composed of three major components, including a stochastic rainfall model able to reproduce realistic rainfall series containing extremes and inter-annual monthly variability, a multivariate daily temperature model conditioned to the rainfall occurrence, and a suitable multi-variate monthly generator to fit the low-frequency variability of daily maximum and minimum temperature series. The performance of IWG was tested by comparing statistical characteristics of the simulated and observed weather data, and by comparing statistical characteristics of the simulated runoff outputs by a daily rainfall-runoff model fed by the generated and observed weather data. Furthermore, IWG outputs are compared with those of the well-known LARS-WG weather generator. The tested characteristics are a variety of different daily statistics, low-frequency variability, and distribution of extremes. It is concluded that the performance of the IWG is acceptable, better than LARS-WG in the majority of tests, especially in reproduction of extremes and low-frequency variability of weather and runoff series. [ABSTRACT FROM AUTHOR]

Interannual variability is an important modulator of synoptic and intraseasonal variability in South America. This paper seeks to characterize the main modes of interannual variability of seasonal precipitation and some associated mechanisms. The impact of this variability on the frequency of extreme rainfall events and the possible effect of anthropogenic climate change on this variability are reviewed. The interannual oscillations of the annual total precipitation are mainly due to the variability in austral autumn and summer. While autumn is the dominant rainy season in the northern part of the continent, where the variability is highest (especially in the northeastern part), summer is the rainy season over most of the continent, thanks to a summer monsoon regime. In the monsoon season, the strongest variability occurs near the South Atlantic Convergence Zone (SACZ), which is one of the most important features of the South American monsoon system. In all seasons but summer, the most important source of variability is ENSO (El Niño Southern Oscillation), although ENSO shows a great contribution also in summer. The ENSO impact on the frequency of extreme precipitation events is also important in all seasons, being generally even more significant than the influence on seasonal rainfall totals. Climate change associated with increasing emission of greenhouse gases shows potential to impact seasonal amounts of precipitation in South America, but there is still great uncertainty associated with the projected changes, since there is not much agreement among the models' outputs for most regions in the continent, with the exception of southeastern South America and southern Andes. Climate change can also impact the natural variability modes of seasonal precipitation associated with ENSO. [ABSTRACT FROM AUTHOR]

A number of general circulation model studies have assessed the impact of degradation of the land surface in the Sahel, mostly with idealized degradation scenarios. This paper builds on the previous research by testing the sensitivity of Mesoscale Convective Systems (MCS) and associated rainfall amounts to observed vegetation changes using a regional atmospheric model. Over the last 20 years, the vegetation in the Sahel has recovered from the drought in the 1980s and vegetation cover values have increased up to 20%. The sensitivity for both a vegetation increase and a decrease by these realistic amounts is investigated. The model simulations span 42 days of the rainy season and are centred over the region of the Hydrological and Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel), of which the data are used to evaluate model results. The model is able to correctly reproduce rainfall amounts and atmospheric profiles. Total precipitation is found to be insensitive to the applied vegetation changes, but the latter do have an impact on the rainfall patterns and the location of MCS. The model results indicate that the change in vegetation cover influences the MCS in two different ways: Firstly, the vegetation change is found to affect the surface fluxes and this in turn is found to affect the Convective Available Potential Energy (CAPE) and thereby the strength of the convective systems. The relation between vegetation cover and CAPE turns out to be affected by the time in-between precipitation events. Secondly, a change in atmospheric dynamics, especially the mid-tropospheric zonal flow, is modelled as response to a change in the spatial temperature and humidity distribution. Both mechanisms are likely to play a role in determining the characteristics of the rainfall pattern. [ABSTRACT FROM AUTHOR]

A revised 25-point Shuman-Shapiro Spatial Filter (RSSSF) has been applied to six atmospheric circulation models and multi-model ensemble (MME) predictions, and its effect on the improvement of model forecast skill scores of the Asian summer precipitation anomaly is discussed in this paper. On the basis of 21-yr model ensemble predictions, the RSSSF can remove the unpredictable ‘noise’ with respect to the 2-grid wavelength in the model precipitation anomaly fields and maintain the large-scale counterpart, which is related to the response of the model to large-scale boundary forcing. Therefore, this could possibly enhance the forecast skill of the Asian summer rainfall anomaly in the models and the MME. The potential improvement of model forecasting skill is found in the Asian summer monsoon region, where the anomaly correlation coefficient (ACC) has been improved by 7–40%, corresponding to the decreased root mean square error (RMSE) in the model and the MME precipitation anomaly forecasts. [ABSTRACT FROM AUTHOR]

The aim of the paper lies in the identification of possible significant linear trends at monthly, seasonal and annual timescales in the Mediterranean during the second half of the 20th century. Monthly and daily records of 63 stations have been used to elaborate several precipitation indices: sum of daily precipitation (SDP) for rainfall >0.1 mm, >10 mm and >95th percentile, of number of rainy days (RD) >0.1 mm and >10 mm and of mean daily precipitation (MDP) >0.1 mm and >10 mm. For each index the stations have been gathered together by Rotated Principal Component Analyses to determine 8 sub-areas which can be considered as identical for all the timescales at the spatial scale of the research. Trends have been estimated from the scores of each eigenvector retained in all RPCAs. They are mainly non existant or non significant decreasing, even if a few monthly trends appear to be significantly diminishing, primarily during winter months, March in the Atlantic region, October in the Mediterranean Spain, December in the Lions and Genoa Gulfs, January, winter and the year in Greece, winter and the year in Italy and winter in the Near East and increasing in April in the two gulfs. Correlation coefficients between SDP>0.1 mm and other indices have been computed: the significant trends seem mainly related to RD>10 mm, which represents a high percentage of the total rainfall amount. Greece is remarkable: SDP>0.1 mm and >10 mm decrease significantly during January, winter, the rainy season and the entire year whereas SDP>95th percentile increases significantly, in accordance with the climatic change scenarios for the end of this century as does the decreasing of the total monthly and seasonal rainfall. [ABSTRACT FROM AUTHOR]