R. Magno

ABSTRACT Drought is a recurrent feature of climate and can affect areas with different climate regimes and human activities. Its impacts depend on the duration, intensity and extent of precipitation deficiency and water demand for several purposes. Due to the complexity of this phenomenon, it is crucial to analyze both current conditions and evolution of a drought event in order to provide accurate, timely and affordable support for policy setting and impacts management. In this perspective the LaMMA Consortium and the IBIMET-CNR Institute are developing a comprehensive operational tool for quasi-real time drought monitoring and medium-long time forecasts in the Tuscany region (Central Italy), with the aim to deliver periodical, geo-referenced information about areas affected by an increasing reduction of available water resources. A coupled rainfall based and satellite derived monitoring system consists of a set of indices suitable for our region and selected taking into account data availability. This system allows the assessment of vegetation moisture and temperature conditions at different spatio-temporal scales. An analysis of vegetation performances related to temperature and moisture stress is made throughout Normalized Difference Vegetation Index (NDVI) anomalies and Vegetation Health Index (VHI), derived from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) products, available since 2000 and updated each 16 days. These indices are selected in order to enhance the climate-based Standardized Precipitation Index (SPI) and Effective Drought Index (EDI), which provide multiple time scale drought occurrence and duration. Moreover, multi-temporal NDVI profiles of main Tuscan cultivations are used to monitor variations of seasonal growth in order to forecast possible crop yield reductions due to prolonged drought conditions. Data of SPI and EDI elaborated from long time series, starting from 1960, of a single rain gauge station or gridded over the whole region provide the base for seasonal outlooks of drought evolution. Forecasts of the next 1-3 months follow a physically-based statistical approach based on an “adaptive multi-regressive method” that takes into account potential predictors among a list of physical atmospheric indices and Sea Surface Temperature (SST) anomalies. Information about current condition related to the last 16 days available is delivered on the Consortium web site and uploaded on a WebGIS platform. Finally, monthly bulletins furnish a more detailed description of drought evolution throughout an analysis of the indices in the last 30 days and a forecast of the next 3 months. This comprehensive framework, composed by the monitoring and forecast systems, can become a timely and stand-alone multi-purpose tool for several final users, potentially able to give information useful for managing drought-related emergencies as crop yields losses, forest fires and water resources reduction.

ABSTRACT An analysis has been conducted on the hourly data of three different pluviometric stations in the central part of Italy, for the period 1948-2005. The number of rainfall events (daily rainfall amount higher than 0.2 mm) is analysed for each station, revealing an increasing of intensity while a frequency’s decrease is observed throughout the time series. For each station, the evolution of the hourly pluviometric regime with particular regard with extreme rainfall events is investigated. The attention is focussed on the overcomes of the higher percentiles’ values (90th and 99th) both for summer and winter periods. An increasing number of extreme rainfall events is observed. Furthermore the data are detrended and decycling, and the two-parameter General Pareto Distribution (GPD) is used to study the frequency of all the rainfall events over a chosen threshold (peaks over threshold). We evaluate the ad-hoc values for the shape and scale parameters, in order to correctly represent the distribution and the variability of these events.

ABSTRACT Drought is a recurrent feature of climate and its impacts on human activities depend on the interaction between this natural event and water demand for several purposes, from agriculture to civil and industrial needs. The aim of this study is to analyze long time series of rainfall data for evaluating variability, tendencies and intensity of drought events in three different geographical contexts of Tuscany region (coast, hill and mountain) and for analyzing their trends along with Mediterranean SST long term variability. The drought analysis is carried out using daily records from three central Italy rain gauges, covering, respectively, the periods 1945-2005, 1928-2003 and 1930-2005. The first step of our study is to define the dry spells and its characteristics. The rain threshold is computed taking in to account the minimum amount of water needed for the vegetation growth; number and duration of the spells are considered at seasonal and yearly level. Furthermore a two-parameter General Pareto Distribution (GPD) is applied to study the frequency of all the dry spell events over a chosen threshold (peaks over threshold) for their duration. Afterward we use the Standardized Precipitation Index (SPI) to quantify the precipitation deficit for multiple time scale (3, 6, 12, 24 months) and, consequently, to assess the effects of a drought event on different water-resources components: soil moisture, streamflow, reservoir storage, groundwater. The standardization of the values permits a comparison between meteorological stations climatically and geographically different. The frequency analysis of the negative values of the SPI classification gives information on the extreme event increasing or decreasing. The results obtained from the two investigations show a general increase of drought events in the last decades. The SPI highlights, in particular, a negative trend for the long time scale (hydrological drought). Moreover, thanks to the seasonal analysis, we detect an intensification of the phenomenon during the winter period.

ABSTRACT In the last decades changes in precipitation pattern were registered at global level as a consequence of temperature rise, with an increase in the intensity of precipitation events in many regions of the world. but also more intense and longer drought in others, and in particular in the Mediterranean basin. Climate changes can have direct influence on biological phenomena, like the earlier onset of spring and the lengthening of the growing season, playing a key role for the carbon fixation and for the amount of CO2 exchanged by the biosphere with the atmosphere. The impact of water availability variation on ecosystem functioning and carbon fluxes differs from species to species and depends on the period of occurrence. Mediterranean-type ecosystems (MTEs), which are mostly water and temperature-limited biomes and suffered prolonged and exacerbated human pressure, are particularly sensitive to changes in climate, as suggested by the observed decrease in plant productivity following recent heat waves and droughts events. Water availability for this region seems to be a crucial constraint for the net carbon assimilation, and biomes evolving in particularly negative soil and climatic conditions could be the most affected by changes in rainfall pattern. In this view a comparison between carbon uptake of two Holm oak (Quercus ilex L.) forests of Central Italy (Castelporziano-Rome and Lecceto-Siena), measured by eddy covariance technique, was done to analyze the possible adaptation to rainfall decrease. The two ecosystems are characterized by different soil water content of the upper soil layers, by the occurrence of a shallow water table in Castelporziano forest and by a strongly different net ecosystem exchange rate (NEE), with -360 gCm-2year-1 for Lecceto and -875 gCm-2year-1 for Castelporziano. The water supply of Lecceto was mostly driven by rainfall, reaching minimum values under 5% in particularly dry periods and increasing the carbon sink of the ecosystem after sufficiently prolonged or high precipitation events; on the contrary in Castelporziano the presence of the underground water allowed to keep lower level of soil water content around 10%, guaranteeing a more regular photosynthetic activity and favouring, at the end of the year, a greater carbon uptake. The comparison of the net carbon exchange for medium and high values of photosynthetically active radiation shown a correlation with the soil water content and indicated that, keeping constant soil moisture classes, Lecceto ecosystem resulted more efficient than Castelporziano, but became a source of CO2 in drought conditions, confirming the importance of water in favouring plant functions and indicates an influence on carbon exchange in terms of water stress.

<div> <p><span>Water management received increasing attention in the last decades since it is a key to coping with climate change and global warming. Within this framework, water scarcity will be one of the main issues to be addressed by humans, mainly because of its subsequent effects on, but not limited to, the agricultural sector. To tackle this challenge, the Drought Observatory (DO) of CNR-IBE developed an operational climate service to provide seasonal forecasting, of the Standardized Precipitation Index (SPI) to support drought risk management over the Mediterranean area.</span><span> </span></p> </div><div> <p><span>The forecast tool stands on the most recent and evolute version of the ECMWF numerical seasonal forecast system, named SEAS, (5 and 5.1). Each month, from 2017 onwards, SEAS5 provides an ensemble of 51 members of daily simulations, lasting seven months each; these simulations are freely accessible from the Copernicus Data Store (CDS). In addition, from 1981 to 2016, CDS provided a hindcast of 25 members simulation runs (named System 4). SEAS daily precipitation seasonal forecasts, with a horizontal resolution of 1°x1°, are then bias adjusted using the Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset (version 2.8). MSWEP is a global precipitation product with an original 3-hourly, 0.1° resolution available from 1979 to the present; it merges gauges, satellite, and reanalysis data to obtain high-quality precipitation estimates at every location. The bias adjustment is computed using the CSTools R Package (CSTools: Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales) applying a quantile-quantile mapping algorithm. This algorithm adjusts/corrects the quantiles of the modelled distribution (the raw SEAS5 daily precipitation distribution) by using an observed distribution set as a reference (the MSWEP daily precipitation distribution). Thus each SEAS5 grid-points of each ensemble member is 1) reprojected onto the highest resolution MSWEP dataset, and then 2) the resulting high-resolution daily time-series precipitation distribution is adjusted using a quantile transformation. A 1981 – 2016 period is selected to adjust and train the quantile mapping algorithm. From the resulting high resolution and bias-adjusted daily rainfall forecast dataset, we then compute the SPI index for a series of timescales: 1, 3 and 6 months, for the period 1981 onwards. </span><span> </span></p> </div><div> <p><span>From the verification analysis seasonal forecast skills vary on time and geographical areas. It is thus possible to identify windows of opportunity for specific tasks in cooperation with users. Within this framework, bias-corrected seasonal forecasts are valuable supporting information for water resources management and decision-making processes. During the drought that occurred in the summer of 2022, the DO was widely used by national and international media to deliver accurate information on the drought trend. This fact underlines the need for timely and science-based data to inform also the wider public.</span><span> </span></p> </div><div> <p><span>These new bias-adjusted forecasts, along with the empirical seasonal forecasts and other monitoring drought and vegetation indices, will be freely accessible through the Drought Observatory Climate Service (</span><span>https://drought.climateservices.it</span><span>).</span><span> </span></p> </div>

The abandonment of olive orchards is a phenomenon of great importance triggered mainly by economic and social causes. The aim of this study was to investigate some chemical, biochemical, and microbiological properties in a soil of a southern olive grove abandoned for 25 years. In order to define the effect of the long-term land abandonment on soil properties, an adjacent olive grove managed according to extensive practices was taken as reference (essentially minimum tillage and no fertilization). Soil organic matter, total nitrogen, and pH were significantly higher in the abandoned olive grove due to the absence of tillage and the natural inputs of organic matter at high C/N ratio which, inter alia, increased the number of cellulolytic bacteria and stimulated the activity of -glucosidase, an indicator of a more advanced stage of soil evolution. The soil of the abandoned olive orchard showed a lower number of total bacteria and fungi and a lower microbial diversity, measured by means...

... Bianchi CN, Peirano A (1995) Atlante delle fanerogame marine della Liguria: Posidonia oceanica e Cymodocea nodosa. ENEA, Centro Ricerche Ambiente Marino, La Spezia Bianchi CN, Boero F, Fonda Umani S, Morri C, Vacchi M (1998) Successione e cambiamento negli ...

ABSTRACT Spatial distributed climatological data are more and more required for characterizing a territory in different applications. Point datasets are generally the primary sources for meteo-climatic information. These points represent the location of the sensors that measure main climatic parameters. This leads to define a standard for a spatial representation using interpolation techniques. Different kinds of geostatistical algorithms are actually available, supplied by common standard software or in phase of development. The aim of the paper is to propose a standard methodology for meteoclimatic data processing based on the nature and the temporal variability of parameters that may be used to create climatic maps. In the context of DESERTNET project (Interreg III B), developed by IBIMET in collaboration with Tuscany Region, climatological maps of rainfall and thermometric data for the period 1961-2000 have been produced in order to evaluate the desertification sensibility of Tuscany regional territory. For this evaluation, a statistical validation of several geostatistical techniques has been developed for choosing the more performing spatialization of each parameter analyzed.

Abstract Optical and LiDAR datasets taken by airborne platforms are informative on important forest attributes, and particularly on growing stock volume (GSV), which is related to woody biomass and carbon storage. This paper presents the integration of such datasets with information collected on the ground for assessing the GSV variation that occurred in the Cascine urban park (Florence, Italy) mostly as a consequence of an extreme wind storm in March 2015. Two LiDAR acquisitions taken before and after the disastrous event (2007 and 2017) were combined with conventional forest observations derived from a complete inventory of the park area and from restricted ground surveys conducted around the first and second study dates. The dataset of the first period was used to evaluate the applicability of an area-based estimation approach to the second dataset and consequently assess the magnitude of the GSV change. In particular, the change was statistically characterized based only on the recently collected ground samples and on the combination of these with LiDAR data through a ratio estimator. The combination of the LiDAR and ground data increased the precision of the estimates obtained, highlighting a significant GSV decrease during the study decade (about 20%), that was concentrated in two of four park sectors. This GSV decrease, which can be mostly attributed to the effect of the 2015 wind storm, corresponds to a total loss of carbon stored in the park of around 2700 tons.

... Modellizzazione dell¶accumulo di carbonio in ecosistemi forestali: attività svolta nell¶ambitodell¶Osservatorio Kyoto della regione Toscana ... fondamentale per la loro potenziale capacità di assorbire carbonio nei suoli e nella vegetazione che li caratterizza (Waring and Running ...