1,721,040 research outputs found
Projecting changes in Tanzania rainfall for the 21st century
No full textA non-homogeneous hidden Markov model (NHMM) is developed using a 40-year record (1950–1990) of
daily rainfall at 11 stations in Tanzania and National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) re-analysis atmospheric fields of a number of meteorological variables. The following atmospheric fields, temperature at 1000 hPa, geo-potential height at 1000 hPa, meridional winds and zonal winds at 850 hPa, and zonal winds at the equator from 10 to 1000 hPa, in a region defined by 25∘S–25∘N and 25∘–75∘E are identified as appropriate predictors for the downscaling of the seasonal regime of daily rainfall in Tanzania. The NHMM is used to predict future rainfall patterns under a comparatively high greenhouse gas emissions scenario [Representative Concentration Pathway 8.5 (RCP8.5)], using predictors from the CMCC-CMS (Centro Mediterraneo sui Cambiamenti Climatici) simulations from 1950 to 2100. Instead of pre-specifying a fixed rainy season, the model considers seasonality of precipitation to be determined by the 21st century simulations of the atmospheric variables used as predictors. The future downscaled precipitation simulations for the RCP8.5 scenario indicate that in the 21st century Tanzania may experience: (1) a slight decrease in the number of wet days and seasonal rainfall inMAMand JJAS, but not in OND; (2) a reduction of annual total rainfall; and (3) an intensification of the frequency and intensity of extreme rainfall, as identified by 90th, 95th, and 99th percentiles
A Flood Risk Management Model to Identify Optimal Defence Policies in Coastal Areas Considering Uncertainties in Climate Projections
Full text linkCoastal areas are particularly vulnerable to flooding from heavy rainfall, sea storm surge, or a combination of the two. Recent studies project higher intensity and frequency of heavy rains, and progressive sea level rise continuing over the next decades. Pre-emptive and optimal flood defense policies that adaptively address climate change are needed. However, future climate projections have significant uncertainty due to multiple factors: (a) future CO2 emission scenarios; (b) uncertainties in climate modelling; (c) discount factor changes due to market fluctuations; (d) uncertain migration and population growth dynamics. Here, a methodology is proposed to identify the optimal design and timing of flood defense structures in which uncertainties in 21st century climate projections are explicitly considered probabilistically. A multi-objective optimization model is developed to minimize both the cost of the flood defence infrastructure system and the flooding hydraulic risk expressed by Expected Annual Damage (EAD). The decision variables of the multi-objective optimization problem are the size of defence system and the timing of implementation. The model accounts for the joint probability density functions of extreme rainfall, storm surge and sea level rise, as well as the damages, which are determined dynamically by the defence system state considering the probability and consequences of system failure, using a water depth–damage curve related to the land use (Corine Land Cover); water depth due to flooding are calculated by hydraulic model. A new dominant sorting genetic algorithm (NSGAII) is used to solve the multi-objective problem optimization. A case study is presented for the Pontina Plain (Lazio Italy), a coastal region, originally a swamp reclaimed about a hundred years ago, that is rich in urban centers and farms. A set of optimal adaptation policies, quantifying size and timing of flood defence constructions for different climate scenarios and belonging to the Pareto curve obtained by the NSGAII are identified for such a case study to mitigate the risk of flooding and to aid decision makers
A non-homogeneous Markov model for the definition of climate change scenarios for coastal areas: the case of Agro-Pontina plain
No full textThis study addresses to the possible changes in Agro-Pontino rainfall under different global warming scenarios for the 21st century. The Agro-Pontino-plain is a reclamation region and presents the
typical hydro-geological features of Mediterranean coastal environments. It is densely populated and productive, therefore, climate changes could adversely affect the socio-economic development of
the area. Currently, due to the coarse resolution of Global-Circulation-Models, local climate variables simulations for limited size area are not accurate. Nonetheless, GCMs simulations of large-scale
upper-air fields are generally considered reliable, therefore to bridge the gap between GCMs and local-scale processes different downscaling techniques are carried out. Here, a Hidden Markov Model
and a Non-homogeneous Hidden Markov Model are developed using a 54-years record (1951-2004) of daily rainfall amount at 9 stations in Agro-Pontino-plain and re-analysis fields of atmospheric
variables. In HMM and NHMM runs, we directly consider the entire year, rather than an a priori demarcation of seasons. The idea is to identify, directly using the HMM, the seasonal precipitation
characteristics which may be related to the temporal sequence of ‘hidden states’ of atmosphere, subsequently modeled as dependent on appropriate fields of selected atmospheric variables. Daily
rainfall variability is described in terms of occurrence of 5 ‘hidden weather states’ identified by the HMM and associated to variables representing the main characteristics of large-scale atmospheric
circulation as obtained by re-analysis data, then, using NHMM, calibration and validation tests are made to identify the optimal predictors - GeoPotential Height and Temperature at 1000 hPa,
Meridional & Zonal Wind at 850 hPa and Precipitable Water - to reproduce better the observed rainfall features on Agro-Pontino-plain
5th International Conference on Meteorology and Climatology of the Mediterranean
No full textThis study regards an analysis of the possible changes in Agro-Pontino rainfall under different global warming scenarios for the 21st century. The Agro-Pontino plain (southern Lazio,Italy) is a reclamation region with the typical hydro-geological features of Mediterranean coastal environments. It is an important agricultural-industrial activities, densely populated, so that, climate changes could adversely affect the socio-economic development of the area. Currently, due to the coarse resolution of Global-Circulation-Models (GCMs), local climate variables simulations for limited size area are not accurate. Nonetheless, GCMs simulations of large-scale upper-air fields are generally considered reliable, therefore to bridge the gap between GCMs and local-scale processes different downscaling techniques are carried out. Here, a Hidden-Markov-Model (HMM) and a Non-Homogeneous-Markov-Model (NHMM) are developed using a 54-years record (1951-2004) of daily rainfall amount at 9stations in Agro-Pontino-plain and re-analysis fields of atmospheric variables. In HMM and NHMM runs, we directly consider the entire year, rather than an a priori demarcation of seasons. The idea is to identify, directly using the HMM, the seasonal precipitation characteristics which may be related to the temporal sequence of ‘hidden states’ of atmosphere, subsequently modeled as dependent on appropriate fields of selected atmospheric variables. Daily rainfall variability is described in terms of occurrence of 5 ‘hidden weather states’ identified by the HMM and associated to variables representing the main characteristics of large-scale atmospheric circulation as obtained by re-analysis data, then, using NHMM, calibration and validation tests are made to identify the optimal predictors - GeoPotential Height and Temperature at 1000 hPa, Meridional and Zonal Wind at 850 hPa and Precipitable Water - to reproduce better the observed rainfall features on Agro-Pontino-plain. Then, the fitted NHMM is used for predicting future rainfall patterns (RCP8.5 scenario), using GCM predictors and simulations (CMCC- CM/ 1951-2100)
Un modello markoviano non omogeneo per la definizione di scenari di cambiamento climatico delle aree costiere: il caso della Piana Pontina
No full textQuesto studio è finalizzato alla valutazione dei possibili cambiamenti del regime pluviometrico nella Pianura dell’Agro-Pontino che si determinano nei differenti scenari di riscaldamento globale ipotizzati per il 21°secolo. L’ area oggetto dello studio, fascia costiera compresa fra il Mar Tirreno e la dorsale Lepino-Ausona, ubicata nel Lazio meridionale, costituisce un rilevante esempio di regione di bonifica e presenta le tipiche caratteristiche idro-geologiche degli ambienti costieri del Mediterraneo. È densamente popolata ed è sede di importanti attività agricole e industriali che dipendono in modo determinante dalla disponibilità di acqua da fonti superficiali e sotterranee, quindi le modifiche climatiche e le possibili conseguenti alterazioni del ciclo idrologico hanno una diretta influenza sullo sviluppo socio-economico della zona. Allo stato attuale dell’arte nè i modelli di circolazione generale dell’atmosfera (GCM), nè quelli regionali (RCM), consentono una riproduzione del regime pluviometrico giornaliero sufficientemente accurata per zone di relativamente limitata estensione, quale la regione suddetta. Ciò nonostante, essi riproducono con sufficiente fedeltà i campi alla grande scala delle variabili rappresentanti la circolazione atmosferica globale. Pertanto è necessario ricorrere a tecniche di downscaling per ottenere simulazioni sufficientemente accurate delle precipitazioni locali, basate sull’individuazione di relazioni statistiche fra le suddette variabili alla grande scala e le precipitazioni locali. Nel presente lavoro, sono state applicate le tecniche di downscaling statistico, ‘Hidden Markov Model’ (HMM) e ‘Non-homogeneous Hidden Markov Model’ (NHMM), a 54 anni (1951-2004) di dati delle precipitazioni giornaliere di 9 stazioni dell’Istituto Idrografico e Mareografico di Roma e dell’ Aeronautica Militare ricadenti nell’area di studio. L’HMM e l’NHMM sono utilizzati sull’intero hanno solare piuttosto che su stagioni delineate a-priori per riprodurre le attuali caratteristiche di piovosità giornaliera e quelle future sulla Piana dell’Agro-Pontino, con particolare riferimento alle caratteristiche di stagionalità, che vengono catturate attraverso un’opportuna scelta delle variabili atmosferiche, descriventi le caratteristiche metereologiche e climatiche alla grande scala, influenzanti il regime di precipitazione locale. L’idea consiste nell’identificare, direttamente utilizzando l’HMM, le caratteristiche stagionali di piovosità associate agli ‘stati nascosti’ (HS) e descrivere la variabilità giornaliera delle precipitazioni; successivamente selezionare le variabili atmosferiche (predictors) che più influenzano il regime pluviometrico e analizzare le distribuzioni spaziali associate ai differenti stati piovosi; infine, mediante l’NHMM si sono effettuate prove di calibrazione (1951-1994) e validazione (1995-2004) per individuare l’insieme ottimale di predittori atmosferici (“Mean Sea Level Pressure (MSL)”, “Temperature at 1000 hPa (T)”, “Meridional Wind (MW)” e “Zonal Wind (ZW) at 850 hPa” e “Precipitable Water (P)” (IRI Library – NOAA-NCAR) ) che meglio consentono di riprodurre le caratteristiche stagionali delle precipitazioni osservate.This study addresses to the possible changes in Agro-Pontino rainfall under different global warming scenarios for the 21st century. The Agro-Pontino-plain is a reclamation region and presents the
typical hydro-geological features of Mediterranean coastal environments. It is densely populated and productive, therefore, climate changes could adversely affect the socio-economic development of
the area. Currently, due to the coarse resolution of Global-Circulation-Models, local climate variables simulations for limited size area are not accurate. Nonetheless, GCMs simulations of large-scale
upper-air fields are generally considered reliable, therefore to bridge the gap between GCMs and local-scale processes different downscaling techniques are carried out. Here, a Hidden Markov Model
and a Non-homogeneous Hidden Markov Model are developed using a 54-years record (1951-2004) of daily rainfall amount at 9 stations in Agro-Pontino-plain and re-analysis fields of atmospheric
variables. In HMM and NHMM runs, we directly consider the entire year, rather than an a priori demarcation of seasons. The idea is to identify, directly using the HMM, the seasonal precipitation
characteristics which may be related to the temporal sequence of ‘hidden states’ of atmosphere, subsequently modeled as dependent on appropriate fields of selected atmospheric variables. Daily
rainfall variability is described in terms of occurrence of 5 ‘hidden weather states’ identified by the HMM and associated to variables representing the main characteristics of large-scale atmospheric
circulation as obtained by re-analysis data, then, using NHMM, calibration and validation tests are made to identify the optimal predictors - GeoPotential Height and Temperature at 1000 hPa,
Meridional & Zonal Wind at 850 hPa and Precipitable Water - to reproduce better the observed rainfall features on Agro-Pontino-plain
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Willingness of farmers to pay for satellite-based irrigation advisory services: a southern Italy experience
No full textVariations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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