Firenze, Italy
Firenze, Italy

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Maselli F.,CNR Institute for Biometeorology | Vaccari F.P.,CNR Institute for Biometeorology | Chiesi M.,CNR Institute for Biometeorology | Romanelli S.,LaMMA Consortium | D'Acqui L.P.,CNR Institute of Ecosystem Study
Ecological Modelling | Year: 2017

Mediterranean ecosystems are particularly vulnerable to the environmental changes which have occurred in the last decades. Evaluating the ecosystem response to these changes is therefore a top priority, particularly concerning water and carbon dynamics. The Pianosa Island is a well known test site where numerous environmental surveys have been performed to fully characterize the most typical vegetation type, Mediterranean macchia. A first measurement campaign concerning both vegetation and soil properties was performed in 2001, and was repeated in 2010 only for soil properties. Vegetation cover was characterized again by means of an aircraft high resolution LiDAR dataset taken in 2009. Additional medium and low spatial resolution satellite images (Landsat OLI and MODIS) and aircraft photos were recovered from various sources. The availability of these datasets offers a unique opportunity to develop and test a methodology capable of modelling and analyzing the water and carbon dynamics of Mediterranean macchia during the 2001–2010 decade. To this aim, simulation procedures integrating remotely sensed and ancillary data were first tuned towards the available observations of vegetation biomass and soil carbon content. These procedures were then applied to produce daily estimates of macchia actual evapotranspiration (AET), gross primary production (GPP) and net ecosystem exchange (NEE), whose accuracy was assessed against corresponding eddy covariance flux tower observations taken in two years (2007–2008). The results obtained are satisfactory and support the capability of the modelling approach to reproduce both the water and carbon dynamics of macchia during the study decade. From an ecological viewpoint, both fluxes are increasing in this time period, mainly depending on similarly increasing spring rainfall. The macchia ecosystem behaves as a net sink of carbon, which is stored primarily in soil (≅90%) and secondarily in vegetation. © 2017 Elsevier B.V.


Mazza A.,LaMMA Consortium | Mazza A.,National Research Council Italy
Water (Switzerland) | Year: 2017

Precipitation during the period 2001-2016 over the northern and central part of Tuscany was studied in order to characterize the rainfall regime. The dataset consisted of hourly cumulative rainfall series recorded by a network of 801 rain gauges. The territory was divided into 30 × 30 km2 square areas where the annual and seasonal Average Cumulative Rainfall (ACR) and its uncertainty were estimated using the Non-Parametric Ordinary Block Kriging (NPOBK) technique. The choice of area size was a compromise that allows a satisfactory spatial resolution and an acceptable uncertainty of ACR estimates. The daily ACR was estimated using a less computationally expensive technique, averaging the cumulative rainfall measurements in the area. The trend analysis of annual and seasonal ACR time series was performed by means of the Mann-Kendall test. Four climatic zones were identified: the north-western was the rainiest, followed by the north-eastern, north-central and south-central. An overall increase in precipitation was identified, more intense in the north-west, and determined mostly by the increase in winter precipitation. On the entire territory, the number of rainy days, mean precipitation intensity and sum of daily ACR in four intensity groups were evaluated at annual and seasonal scale. The main result was a magnitude of the ACR trend evaluated as 35 mm/year, due mainly to an increase in light and extreme precipitations. This result is in contrast with the decreasing rainfall detected in the past decades. © 2017 by the authors.


Ferretti R.,University of L'Aquila | Pichelli E.,University of L'Aquila | Gentile S.,University of L'Aquila | Maiello I.,University of L'Aquila | And 20 more authors.
Hydrology and Earth System Sciences | Year: 2014

The Special Observation Period (SOP1), part of the HyMeX campaign (Hydrological cycle in the Mediterranean Experiments, 5 September-6 November 2012), was dedicated to heavy precipitation events and flash floods in the western Mediterranean, and three Italian hydro-meteorological monitoring sites were identified: Liguria-Tuscany, northeastern Italy and central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models, including hydrological models and marine models, allowed an unprecedented monitoring and analysis of high-impact weather events around the Italian hydro-meteorological sites. This activity has seen strong collaboration between the Italian scientific and operational communities. In this paper an overview of the Italian organization during SOP1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12-13 September 2012) in northeastern Italy, IOP13 (15-16 October 2012) in central Italy and IOP19 (3-5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems, including the hydrological impacts. The usefulness of having different weather forecast operational chains characterized by different numerical weather prediction models and/or different model set up or initial conditions is finally shown for one of the events (IOP19). © Author(s) 2014.


Pieri M.,CNR Institute for Biometeorology | Massi L.,University of Florence | Lazzara L.,University of Florence | Nuccio C.,University of Florence | And 2 more authors.
European Journal of Remote Sensing | Year: 2015

Three algorithms based on MODIS imagery were evaluated for the estimation of Chlorophyll-a concentration ([CHL]) in the Western Mediterranean Sea. The first algorithm (OC3M) is usually applied at global scale, while the second (MedOC3), has been used in the Mediterranean basin. The third algorithm (SAM_LT), specifically developed for the Ligurian and North Tyrrhenian Seas, is here described and applied, in its updated version. The three algorithms were assessed through comparison with 240 sea [CHL] samples collected during the 2002-2011 decade. The results obtained show that OC3M is the most accurate algorithm when used for the entire Western Mediterranean, but is outperformed by SAM_LT in the area where this was originally developed. The impact of different MODIS quality flags on the three algorithms has been finally evaluated, providing guidelines for their operational application in the study area. © 2015, Associazione Italiana di Telerilevamento. All rights reserved.


Mazza A.,National Research Council Italy | Antonini A.,LaMMA Consortium | Melani S.,National Research Council Italy | Ortolani A.,National Research Council Italy
Journal of Applied Remote Sensing | Year: 2015

The real-time measurement of rainfall is a primary information source for many purposes, such as weather forecasting, flood risk assessment, and landslide prediction and prevention. In this perspective, remote sensing techniques to monitor rainfall fields by means of radar measurements are very useful. In this work, a technique is proposed for the estimation of cumulative rainfall fields averaged over a large area, applied on the Tuscany region using the Italian weather radar network. In order to assess the accuracy of radar-based rainfall estimates, they are compared with coincident spatial rain gauge measurements. Observations are compared with average rainfall over areas as large as a few tens of kilometers. An ordinary block kriging method is applied for rain gauge data spatialization. The comparison between the two types of estimates is used for recalibrating the radar measurements. As a main result, this paper proposes a recalibrated relationship for retrieving precipitation from radar data. The accuracy of the estimate increases when considering larger areas: an area of 900 km2 has a standard deviation of less than few millimeters. This is of interest in particular for extending recalibrated radar relationships over areas where rain gauges are not available. Many applications could benefit from it, from nowcasting for civil protection activities, to hydrogeological risk mitigation or agriculture. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE).


Gioli B.,CNR Institute for Biometeorology | Gualtieri G.,CNR Institute for Biometeorology | Busillo C.,LaMMA Consortium | Calastrini F.,CNR Institute for Biometeorology | And 2 more authors.
Meteorological Applications | Year: 2014

Long term aircraft observations of wind magnitude along an ∼250km flight track in central Italy, performed over 1.5years, are compared with the output of an existing mesoscale prognostic-diagnostic (WRF-CALMET) model chain aimed at assessing wind potential maps at regional scale. Aircraft measurements are used to evaluate model performance along spatial and temporal transects at moderate altitude from the ground (∼75m), where observational frameworks are rarely available. Spatial wind analysis was capable of assessing overall model performance, while highlighting some limitations: the implemented models have better performance in inland areas with respect to coastal areas, while they are capable of representing diurnal variability in all regions correctly. Overall agreement is within 3% in the cold season and 16% in the warm season, while the greatest differences, above 30%, are obtained in coastal areas in the summer. The hypothesis supporting these results is that summer sea breeze regimes that develop consistently from the coast through the interior land are not entirely resolved from mesoscale modelling. Finally, the model performance and limitations related to complex orography are highlighted. This study demonstrates the added value that may derive from aircraft wind measurements as an additional observational framework for applied meteorology studies. © 2013 Royal Meteorological Society.


Mazza A.,National Research Council Italy | Antonini A.,LAMMA Consortium | Melani S.,National Research Council Italy | Ortolani A.,National Research Council Italy
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

In this work we propose a technique for 15-minutes cumulative rainfall mapping, applied over Tuscany, using Italian weather radar networks together with the regional rain gauge network. In order to assess the accuracy of the radar-based rainfall estimates, we have compared them with spatial coincident rain gauge measurements. Precipitation at ground is our target observable: rain gauge measurements of such parameter have a so small error that we consider it negligible (especially if compared from what retrievable from radars). In order to make comparable the observations given from these two types of sensors, we have collected cumulative rainfall over areas a few tens of kilometres wide. The method used to spatialise rain gauges data has been the Ordinary Block Kriging. In this case the comparison results have shown a good correlation between the cumulative rainfall obtained from the rain gauges and those obtained by the radar measurements. Such results are encouraging in the perspective of using the radar observations for near real time cumulative rainfall nowcasting purposes. In addition the joint use of satellite instruments as SEVIRI sensors on board of MSG-3 satellite can add relevant information on the nature, spatial distribution and temporal evolution of cloudiness over the area under study. For this issue we will analyse several MSG-3 channel images, which are related to cloud physical characteristics or ground features in case of clear sky. © 2014 SPIE.


Gioli B.,CNR Institute for Biometeorology | Gualtieri G.,CNR Institute for Biometeorology | Busillo C.,LaMMA Consortium | Calastrini F.,CNR Institute for Biometeorology | And 2 more authors.
Atmospheric Environment | Year: 2015

Emission inventories are the fundamental official data on atmospheric emissions of pollutants and greenhouse gases at a variety of spatial and temporal scales worldwide. This study makes use of direct CO2 emission measurements made with the eddy covariance technique over a completely urbanized area, with no confounding effect of vegetation, where emissions are mostly controlled by natural gas combustion processes and road traffic. Objectives are: i) to validate top-down spatially and temporally disaggregated emission inventories at yearly, monthly, weekly and hourly time scales; ii) to quantify the improvement achieved in official inventories when replacing built-in temporal disaggregation proxies with customized proxies based on local data of road traffic and natural gas consumption. We demonstrate that the overall performance of official inventory at yearly scale is rather good with an emission of 3.08gCO2m-2h-1 against a measured emission of 3.21±0.12gCO2m-2h-1. When temporally disaggregating annual emissions, the agreement between inventory and observations always significantly improves when using local proxies, by 47% (from 0.70 to 0.37gCO2m-2h-1 RMSE) at monthly scale, by 26% (from 0.58 to 0.43gCO2m-2h-1 RMSE) at weekly scale, and by 32% (from 1.26 to 0.85gCO2m-2h-1 RMSE), at hourly scale. The validity of this analysis goes beyond CO2 since the temporal proxies used by the inventories mimic the intensity of specific emission processes, therefore species emitted in the same processes as CO2, would benefit from the improved parameterization of temporal proxies shown here. These results indicate that effort should be put into developing improved temporal proxies based on local rather than national scale data, that can better mimic site dependent behaviors. © 2015 Elsevier Ltd.


Guarnieri F.,LAMMA Consortium | Guarnieri F.,National Research Council Italy | Calastrini F.,LAMMA Consortium | Calastrini F.,National Research Council Italy | And 3 more authors.
Scientific World Journal | Year: 2015

The mixing layer height (MLH) is a crucial parameter in order to investigate the near surface concentrations of air pollutants. The MLH can be estimated by measurements of some atmospheric variables, by indirect estimates based on trace gases concentration or aerosol, or by numerical models. Here, a modelling approach is proposed. The developed modelling system is based on the models WRF-ARW and CALMET. This system is applied on Firenze-Prato-Pistoia area (Central Italy), during 2010, and it is compared with in situ measurements. The aim of this work is to evaluate the use of MLH model estimates to characterize the critical episodes for PM10 in a limited area. In order to find out the meteorological conditions predisposing accumulation of PM10 in the atmosphere's lower level, some indicators are used: daily mean wind speed, cumulated rainfall, and mean MLH estimates from CALMET model. This indicator is linked to orography, which has important consequences on local weather dynamics. However, during critical events the local emission sources are crucial to the determination of threshold exceeding of PM10. Results show that the modelled MLH, together with cumulative rainfall and wind speed, can identify the meteorological conditions predisposing accumulation of air pollutant at ground level. © 2015 F. Guarnieri et al.


PubMed | National Research Council Italy and LAMMA Consortium
Type: | Journal: TheScientificWorldJournal | Year: 2015

The mixing layer height (MLH) is a crucial parameter in order to investigate the near surface concentrations of air pollutants. The MLH can be estimated by measurements of some atmospheric variables, by indirect estimates based on trace gases concentration or aerosol, or by numerical models. Here, a modelling approach is proposed. The developed modelling system is based on the models WRF-ARW and CALMET. This system is applied on Firenze-Prato-Pistoia area (Central Italy), during 2010, and it is compared with in situ measurements. The aim of this work is to evaluate the use of MLH model estimates to characterize the critical episodes for PM10 in a limited area. In order to find out the meteorological conditions predisposing accumulation of PM10 in the atmospheres lower level, some indicators are used: daily mean wind speed, cumulated rainfall, and mean MLH estimates from CALMET model. This indicator is linked to orography, which has important consequences on local weather dynamics. However, during critical events the local emission sources are crucial to the determination of threshold exceeding of PM10. Results show that the modelled MLH, together with cumulative rainfall and wind speed, can identify the meteorological conditions predisposing accumulation of air pollutant at ground level.

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