Fiorella Acquaotta

Climate variations in a high altitude Alpine basin and their effects on a glacial environment (Italian Western Alps)

The main objective of this study is to evaluate the variations of climatic parameters (temperature, rain and snow) measured by two weather stations (Formazza and Sabbione) that have never been analyzed before, located in a high glacial catchment (the Sabbione basin in the Italian Western Alps). The study highlights the climatic evolution of the Alpine basin during the last 60 years (1950-2012): climate change has caused a pronounced glacial decline originated by ablation augmentation, due mainly to increasing air temperatures and to reduced alimentation caused by a fresh snow decrease. The cross-correlation test shows that temperatures affect the glacial retreat dynamics more than snowfall. Periglacial and permafrost landforms (e.g., patterned grounds, rock glaciers) have been identified within the Little Ice Age (LIA) glacial deposits, which indicate the ongoing transition from glacial/proglacial to periglacial environments. Furthermore, in order to better identify the periglacial domain in the basin, a map of mean annual air temperature (MAAT) was produced based on climatic analysis.

The evolution of temperature extremes in the Gaspé Peninsula, Quebec, Canada (1974–2013)

The majority of natural hazards that affect Canadian territory are the result of extreme climate and weather conditions. Among these weather hazards, some can be calculated from the application of thresholds for minimum and maximum temperatures at a daily or monthly timescale. These thermal indices allowed the prediction of extreme conditions that may have an impact on the human population by affecting, for example, health, agriculture, and water resources. In this article, we discuss the methods used (RHtestsV4, SPLIDHOM, ClimPACT) then describe the steps followed to calculate the indices, including how we dealt with the problem of missing data and the necessity to identify a common methodology to analyze the time series. We also present possible solutions for ensuring the quality of meteorological data. We then present an overview of the results, namely the main trends and variability of extreme temperature for seven stations located in the Gaspé Peninsula from 1974 to 2013. Our results indicate some break points in time series and positive trends for most indices related to the rise of the temperatures but indicate a negative trend for the indices related to low temperatures for most stations during the study period.

The association between ambient temperature and mortality in South Africa: A time-series analysis

Background: There is an extensive literature describing temperature‐mortality associations in developed regions, but research from developing countries, and Africa in particular, is limited. Methods: We conducted a time‐series analysis using daily temperature data and a national dataset of all 8.8 million recorded deaths in South Africa between 1997 and 2013. Mortality and temperature data were linked at the district municipality level and relationships were estimated with a distributed lag non‐linear model with 21 days of lag, and pooled in a multivariate meta‐analysis. Results: We found an association between daily maximum temperature and mortality. The relative risk for all‐age all‐cause mortality on very cold and hot days (1st and 99th percentile of the temperature distribution) was 1.14 (1.10,1.17) and 1.06 (1.03,1.09), respectively, when compared to the minimum mortality temperature. This “U” shaped relationship was evident for every age and cause group investigated, except among 25–44 year olds. The strongest associations were in the youngest (< 5) and oldest (> 64) age groups and for cardiorespiratory causes. Heat effects occurred immediately after exposure but diminished quickly whereas cold effects were delayed but persistent. Overall, 3.4% of deaths (˜ 290,000) in South Africa were attributable to non‐optimum temperatures over the study period. We also present results for the 52 district municipalities individually. Conclusions: An assessment of the largest‐ever dataset for analyzing temperature‐mortality associations in (South) Africa indicates mortality burdens associated with cold and heat, and identifies the young and elderly as particularly vulnerable. HIGHLIGHTSCountry‐wide epidemiology study of temperature‐mortality association in S. Africa.Strongest associations were in children/elderly and from cardiorespiratory causes.Total attributable mortality was 3.4%, mostly from cold (3.0%) rather than heat (0.4%).Attributable mortality of 3.4% is on the low end of what is reported in other areas.Results can help estimate future burdens from climate change and inform adaptation.

The Climate of Italy

The chapter highlights the main features of the climate of Italy. In particular, it identifies and defines the main climatic regions and the local factors that control the type of climate according to the Koppen classification. Furthermore, it shows the distribution of the main meteorological variables, temperature and precipitation, and the climatic variations that affected Italy in the last decades. The Italian climate displays remarkably varied features due to the complexity of its territory. Climatic variations recently observed show some common elements throughout the country, i.e. a gradual increase in temperature and a change in the annual distribution of precipitation. These changes are more remarkable in the Alpine region.

CoRain: A free and open source software for rain series comparison

A good climatic analysis requires accurate and homogeneous daily precipitation series; unluckily, inhomogeneity is frequently found and have to be considered, especially when it is due to non-climatic parameters. CoRain is a free and open source software written in R language that could greatly help analyzing inhomogeneity caused by rainfall measuring instruments. CoRain compares two parallel rain series (with an overlapping period) and tries to highlight overestimations and underestimations due to rain gauges in a specific condition, so that the user can consider it for future analysis. CoRain offers many information on the two analyzed series, starting with cleaning input data, comparing them and classifying rainy days by severity. CoRain is a cross-platform software, easily adaptable to different needs, that takes in input a single text file with daily information of the two rain series and outputs tables (in CSV format) and plots (as PNG images) that help in the interpretation of the data. Use of the program is very simple: the execution can be either interactive or non-interactive. CoRain code has been tested on different rain series in the Piedmont region (northwestern Italy), showing its importance in identifying climate variations and instrumentation errors.

Temperature Analysis on the North-Western Italian Alps Through the Use of Satellite Images and Ground-Based Meteorological Stations

In the present study we have analyzed the temperature data of the stations of high altitude on the north-western Italian Alps. The data used are the daily series of temperature over the last 51 years. The data were digitized and subjected to quality control and finally to homogenization. To improve the quantity of the ground-data, we decided to use the remote sensing data. The availability of large scale reliable and consistent spatial data as those of the MODIS “land surface temperature” datasets from the satellites “Terra” and “Aqua” allows to evaluate the variation of temperature extent over Alps even where there are no stations on the ground. Finally for the ground-base data the climatic indices were calculated. The analysis of the series showed a positive trend in temperature that coincide on the rise in altitude. In fact, the stations located above 1,600 m asl show a rise in temperatures and a decrease in cold periods. For maximum temperatures were observed greater increases in trends spring and winter, minimum temperatures in summer trends. The trends confirm climate change in an environment is particularly sensitive to temperature changes especially during the season of snow accumulation and vegetative growth.

West Nile Virus infection in Northern Italy: Case-crossover study on the short-term effect of climatic parameters.

Background: Changes in climatic conditions are hypothesized to play a role in the increasing number of West Nile Virus (WNV) outbreaks observed in Europe in recent years. Objectives: We aimed to investigate the association between WNV infection and climatic parameters recorded in the 8 weeks before the diagnosis in Northern Italy. Methods: We collected epidemiological data about new infected cases for the period 2010–2015 from the European Center for Disease Control and Prevention (ECDC) and meteorological data from 25 stations throughout the study area. Analyses were performed using a conditional Poisson regression with a time‐stratified case‐crossover design, specifically modified to account for seasonal variations. Exposures included weekly average of maximum temperatures, weekly average of mean temperatures, weekly average of minimum temperatures and weekly total precipitation. Results: We found an association between incidence of WNV infection and temperatures recorded 5–6 weeks before diagnosis (Incidence Rate Ratio (IRR) for 1 °C increase in maximum temperatures at lag 6: 1.11; 95% CI 1.01–1.20). Increased weekly total precipitation, recorded 1–4 weeks before diagnosis, were associated with higher incidence of WNV infection, particularly for precipitation recorded 2 weeks before diagnosis (IRR for 5 mm increase of cumulative precipitation at lag 2: 1.16; 95% CI 1.08–1.25). Conclusions: Increased precipitation and temperatures might have a lagged direct effect on the incidence of WNV infection. Climatic parameters may be useful for detecting areas and periods of the year potentially characterized by a higher incidence of WNV infection. HighlightsTemperature and precipitation interact with the complex ecology of West Nile Virus.Climatic parameters have a delayed effect on the human West Nile Virus infection.Climatic parameters might be used to predict seasonal outbreaks of WNV.

ROLE OF CLIMATE IN THE SPREAD OF SHIGA TOXIN-PRODUCING ESCHERICHIA COLI INFECTION AMONG CHILDREN

Haemolytic-uraemic syndrome (HUS) is a rare disease mainly affecting children that develops as a complication of shiga toxin-producing Escherichia coli (STEC) infection. It is characterised by acute kidney injury, platelet consumption and mechanical destruction of red blood cells (haemolysis). In order to test the working hypothesis that the spread of the infection is influenced by specific climatic conditions, we analysed all of the identified cases of infection occurring between June 2010 and December 2013 in four provinces of Lombardy, Italy (Milano, Monza Brianza, Varese and Brescia), in which a STEC surveillance system has been developed as part of a preventive programme. In the selected provinces, we recorded in few days a great number of cases and clusters which are unrelated for spatially distant or for the disease are caused by different STEC serotypes. In order to investigate a common factor that favoured the onset of infection, we have analysed in detail the weather conditions of the areas. The daily series of temperature, rain and relative humidity were studied to show the common climate peculiarities whilst the correlation coefficient and the principal component analysis (PCA) were used to point out the meteorological variable, maximum temperature, as the principal climate element in the onset of the infection. The use of distributed lag non-linear models (DLNM) and the climate indices characterising heat waves (HWs) has allowed to identify the weather conditions associated with STEC infection. The study highlighted a close temporal correlation between STEC infection in children and the number, duration and frequency of heat waves. In particular, if the maximum temperature is greater than 90th percentile, days classified as very hot, for 3 or more consecutive days, the risk of infection is increasing.

Preliminary Results of a Comparison Study Between Two Independent Snow Networks in North-Western Italian Alps (Piemonte Region)

The snow represents a fundamental resource for hydro-power generation, irrigation, domestic and industrial water supply. The knowledge of behaviour and trends of this meteorological variable is very important for the human society and mountain system. Thus, climatologists are increasingly interested in studying changes in the intensity, frequency, duration and spatial distribution of snowfall and snow depth. Unfortunately, long instrumental climate records are usually affected by non-climatic changes (inhomogeneities), which compromise the quality of these studies. In order to analyse non-climatic biases, such as the influence of position or instrument changes due, for example, to the transition from manual to automatic measurements, we have compared the parallel measurements. The presence of two independent climate networks offers the opportunity to study the data inhomogeneity of snow records. The analyses highlight higher measured values in manned gauges respect to automatic stations. The major differences have been recorded at the beginning of the winter season, in October and April.