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Book ; Online: Climate Adaptation Modelling

Kondrup, Claus / Mercogliano, Paola / Bosello, Francesco / Mysiak, Jaroslav / Scoccimarro, Enrico / Rizzo, Angela / Ebrey, Rhian / Ruiter, Marleen de / Jeuken, Ad / Watkiss, Paul

(Springer Climate)

2022

Author's details	edited by Claus Kondrup, Paola Mercogliano, Francesco Bosello, Jaroslav Mysiak, Enrico Scoccimarro, Angela Rizzo, Rhian Ebrey, Marleen de Ruiter, Ad Jeuken, Paul Watkiss
Series title	Springer Climate
Keywords	Climatology ; Natural disasters ; Ecology—Methodology ; Bioclimatology ; Earth sciences ; Geography
Subject code	551.6
Language	English
Size	1 Online-Ressource (XVII, 238 p. 49 illus., 46 illus. in color)
Edition	1st ed. 2022
Publisher	Springer International Publishing ; Imprint: Springer
Publishing place	Cham
Document type	Book ; Online
HBZ-ID	HT021216945
ISBN	978-3-030-86211-4 ; 9783030862107 ; 9783030862121 ; 9783030862138 ; 3-030-86211-9 ; 3030862100 ; 3030862127 ; 3030862135
DOI	10.1007/978-3-030-86211-4
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Book ; Online: Climate Adaptation Modelling

Kondrup, Claus / Mercogliano, Paola / Bosello, Francesco / Mysiak, Jaroslav / Scoccimarro, Enrico / Rizzo, Angela / Ebrey, Rhian / Ruiter, Marleen de / Jeuken, Ad / Watkiss, Paul

(Springer Climate)

2022

Series title	Springer Climate
Keywords	Meteorology & climatology ; Natural disasters ; Ecological science, the Biosphere ; Mathematics & science ; Climate change ; Climate adaptation ; Climate modelling ; Hazard assessment ; Rapid analysis ; Climate-Change Policy ; Climate-Change Adaptation ; Climate-Change Impacts ; Climate Change Management
Language	English
Size	1 electronic resource (238 pages)
Publisher	Springer Nature
Publishing place	Cham
Document type	Book ; Online
Note	English
HBZ-ID	HT030379277
ISBN	9783030862114 ; 3030862119
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Spatio-Temporal Pattern and Meteo-Climatic Determinants of Visceral Leishmaniasis in Italy.

Moirano, Giovenale / Ellena, Marta / Mercogliano, Paola / Richiardi, Lorenzo / Maule, Milena

Tropical medicine and infectious disease

2022 Volume 7, Issue 11

Abstract: Historically, visceral leishmaniasis (VL) in Italy was constrained to Mediterranean areas. However, in the last 20 years, sand fly vectors and human cases of VL have been detected in northern Italy, traditionally classified as a cold area unsuitable for ... ...

Abstract	Historically, visceral leishmaniasis (VL) in Italy was constrained to Mediterranean areas. However, in the last 20 years, sand fly vectors and human cases of VL have been detected in northern Italy, traditionally classified as a cold area unsuitable for sand fly survival. We aim to study the spatio-temporal pattern and climatic determinants of VL incidence in Italy. National Hospital Discharge Register records were used to identify incident cases of VL between 2009 and 2016. Incident rates were computed for each year (N = 8) and for each province (N = 110). Data on mean temperature and cumulative precipitation were obtained from the ERA5-Land re-analysis. Age- and sex-standardized incidence rates were modeled with Bayesian spatial and spatio-temporal conditional autoregressive Poisson models in relation to the meteo-climatic parameters. Statistical inference was based on Monte Carlo−Markov chains. We identified 1123 VL cases (incidence rate: 2.4 cases/1,000,000 person-years). The highest incidence rates were observed in southern Italy, even though some areas of northern Italy experienced high incidence rates. Overall, in the spatial analysis, VL incidence rates were positively associated with average air temperatures (β for 1 °C increase in average mean average temperature: 0.14; 95% credible intervals (CrI): 0.01, 0.27) and inversely associated with average precipitation (β for 20 mm increase in average summer cumulative precipitation: −0.28, 95% CrI: −0.42, −0.13). In the spatio-temporal analysis, no association between VL cases and season-year specific temperature and precipitation anomalies was detected. Our findings indicate that VL is endemic in the whole Italian peninsula and that climatic factors, such as air temperature and precipitation, might play a relevant role in shaping the geographical distribution of VL cases. These results support that climate change might affect leishmaniasis distribution in the future.
Language	English
Publishing date	2022-10-29
Publishing country	Switzerland
Document type	Journal Article
ISSN	2414-6366
ISSN (online)	2414-6366
DOI	10.3390/tropicalmed7110337
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Very High Resolution Projections over Italy under different CMIP5 IPCC scenarios.

Raffa, Mario / Adinolfi, Marianna / Reder, Alfredo / Marras, Gian Franco / Mancini, Marco / Scipione, Gabriella / Santini, Monia / Mercogliano, Paola

Scientific data

2023 Volume 10, Issue 1, Page(s) 238

Abstract: This paper introduces VHR-PRO_IT (Very High-Resolution PROjections for ITaly), an open access hourly climate projection with a resolution of ≃2.2 km (i.e., Convection Permitting Scale) up to 2050, covering the Italian peninsula and some neighbouring ... ...

Abstract	This paper introduces VHR-PRO_IT (Very High-Resolution PROjections for ITaly), an open access hourly climate projection with a resolution of ≃2.2 km (i.e., Convection Permitting Scale) up to 2050, covering the Italian peninsula and some neighbouring areas. VHR-PRO_IT is produced within the Highlander project ( https://highlanderproject.eu/ ) by dynamically downscaling the Italy8km-CM climate projection (spatial resolution ≃8 km; output frequency = 6 h; driven CMIP5 GCM = CMCC-CM) with the Regional Climate Model COSMO-CLM under the IPCC RCP4.5 and RCP8.5 scenarios. It covers the 60-year period 1989-2050. VHR-PRO_IT is intended for research purposes in the field of climate studies. For example, it may be included in the ongoing activities to clarify the added value of running climate simulation at the convection-permitting scale.
Language	English
Publishing date	2023-04-26
Publishing country	England
Document type	Dataset ; Journal Article
ZDB-ID	2775191-0
ISSN	2052-4463 ; 2052-4463
ISSN (online)	2052-4463
ISSN	2052-4463
DOI	10.1038/s41597-023-02144-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Propagation of variability in climate projections within urban flood modelling: A multi-purpose impact analysis

Padulano, Roberta / Rianna, Guido / Costabile, Pierfranco / Costanzo, Carmelina / Del Giudice, Giuseppe / Mercogliano, Paola

Journal of hydrology. 2021 Nov., v. 602

2021

Abstract: Flooding is one of the most challenging weather-induced risks in urban areas. However, in a climate change perspective, significant gaps can still be observed in literature addressing the key role of rainfall input and related variability within urban ... ...

Abstract	Flooding is one of the most challenging weather-induced risks in urban areas. However, in a climate change perspective, significant gaps can still be observed in literature addressing the key role of rainfall input and related variability within urban flood impact models. The present research attempts to bridge this gap by investigating the effect of using a large ensemble of bias-corrected Euro-CORDEX climate projections on flood hazard estimations, with the goal of understanding the propagation of future climate variability in terms of flooding outputs for the urban environment. With this aim, a scenario analysis is performed for two return periods (10 and 200 years) building on nineteen climate projections for future horizon 2071–2100 under RCP 4.5 and 8.5 scenarios by means of CADDIES Caflood inundation model, using a test case in the City of Naples (Italy). Model outcomes are investigated and discussed in terms of relevant metrics and indicators available in literature targeting both general hazards, evaluated in terms of runoff volumes and flooded areas, and sectoral hazards, specified by a number of relevant literature hazard classifications. Modelling outcomes are analysed and normalised with respect to baseline values representing current climate conditions to emphasize potential impacts of climate change. Results show that flood features increase more slowly than rainfall, and the relationship between rainfall and flood increase is linear, with decreasing slope with increasing return period. Furthermore, the spread in rainfall input due to the use of different climate projections does not inflate through the impact modelling stages, albeit a dependence on the indicators used to model flood impacts can be observed. The outcomes of the research can be of aid to managers, designers and policy makers to understand the impacts of climate change in flood-prone urban areas and, in perspective, to adapt urban areas exploring the feasibility and effectiveness of solutions.
Keywords	climate change ; issues and policy ; models ; rain ; runoff ; urban areas ; Italy
Language	English
Dates of publication	2021-11
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1473173-3
ISSN	1879-2707 ; 0022-1694
ISSN (online)	1879-2707
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2021.126756
Database	NAL-Catalogue (AGRICOLA)

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Article: Using the present to estimate the future: A simplified approach for the quantification of climate change effects on urban flooding by scenario analysis

Padulano, Roberta / Costabile, Pierfranco / Costanzo, Carmelina / Rianna, Guido / Del Giudice, Giuseppe / Mercogliano, Paola

Hydrological processes. 2021 Dec., v. 35, no. 12

2021

Abstract: Understanding and modelling pluvial flood patterns is pivotal for the estimation of flood impacts in urban areas, especially in a climate change perspective. However, urban flood modelling under climate change conditions poses several challenges. On one ... ...

Abstract	Understanding and modelling pluvial flood patterns is pivotal for the estimation of flood impacts in urban areas, especially in a climate change perspective. However, urban flood modelling under climate change conditions poses several challenges. On one hand, the identification and collection of climate change data suitable for flood‐related evaluations requires consistent computational and scientific effort. On the other hand, large difficulties can arise in the reproduction of the rainfall‐runoff transformation process in cases when only little information about the subsurface processes is known. In this perspective, a simplified approach is proposed to address the challenges regarding the quantitative estimation of climate change effects on urban flooding for real case applications. The approach is defined as “bottom‐up” because climate change information is not included in flood modelling, but it is only invoked for the interpretation of results. In other words, the challenge faced in this work is the development of a modelling strategy that is expeditious, because it does not require flood simulations for future rainfall scenarios, but only under current climate conditions, thus reducing the overall computational effort; and it is flexible, because results can be easily updated once new climate change data, scenarios or methods become available, without the need of additional flood simulations. To simulate real case applications, the approach is tested for a scenario analysis, where different return periods and hyetograph shapes are used as input for urban inundation modelling in Naples, Italy. The approach can support public and private stakeholders, such as land administrators and water systems managers; moreover, it represents a valuable and effective basis for climate change risk communication strategies.
Keywords	climate change ; rain ; reproduction ; risk communication ; runoff ; stakeholders ; Italy
Language	English
Dates of publication	2021-12
Publishing place	John Wiley & Sons, Inc.
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	1479953-4
ISSN	1099-1085 ; 0885-6087
ISSN (online)	1099-1085
ISSN	0885-6087
DOI	10.1002/hyp.14436
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Improving the potential accuracy and usability of EURO-CORDEX estimates of future rainfall climate using frequentist model averaging

Jewson, Stephen / Barbato, Giuliana / Mercogliano, Paola / Mysiak, Jaroslav / Sassi, Maximiliano

eISSN: 1607-7946

2021

Abstract: Probabilities of future climate states can be estimated by fitting distributions to the members of an ensemble of climate model projections. The change in the ensemble mean can be used as an estimate of the change in the mean of the real climate. However, ...

Abstract	Probabilities of future climate states can be estimated by fitting distributions to the members of an ensemble of climate model projections. The change in the ensemble mean can be used as an estimate of the change in the mean of the real climate. However, the level of sampling uncertainty around the change in the ensemble mean varies from case to case and in some cases is large. We compare two model-averaging methods that take the uncertainty in the change in the ensemble mean into account in the distribution fitting process. They both involve fitting distributions to the ensemble using an uncertainty-adjusted value for the ensemble mean in an attempt to increase predictive skill relative to using the unadjusted ensemble mean. We use the two methods to make projections of future rainfall based on a large data set of high-resolution EURO-CORDEX simulations for different seasons, rainfall variables, representative concentration pathways (RCPs), and points in time. Cross-validation within the ensemble using both point and probabilistic validation methods shows that in most cases predictions based on the adjusted ensemble means show higher potential accuracy than those based on the unadjusted ensemble mean. They also perform better than predictions based on conventional Akaike model averaging and statistical testing. The adjustments to the ensemble mean vary continuously between situations that are statistically significant and those that are not. Of the two methods we test, one is very simple, and the other is more complex and involves averaging using a Bayesian posterior. The simpler method performs nearly as well as the more complex method.
Subject code	333
Language	English
Publishing date	2021-07-29
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Improving the Potential Accuracy and Usability of EURO-CORDEX Estimates of Future Rainfall Climate using Mean Squared Error Model Averaging

Jewson, Stephen / Barbato, Giuliana / Mercogliano, Paola / Mysiak, Jaroslav / Sassi, Maximiliano

eISSN: 1607-7946

2021

Abstract: Probabilities of future climate states can be estimated by fitting distributions to the members of an ensemble of climate model projections. The change in the ensemble mean can be used as an estimate of the unknown change in the mean of the distribution ... ...

Abstract	Probabilities of future climate states can be estimated by fitting distributions to the members of an ensemble of climate model projections. The change in the ensemble mean can be used as an estimate of the unknown change in the mean of the distribution of the climate variable being predicted. However, the level of sampling uncertainty around the change in the ensemble mean varies from case to case and in some cases is large. We compare two model averaging methods that take the uncertainty in the change in the ensemble mean into account in the distribution fitting process. They both involve fitting distributions to the ensemble using an uncertainty-adjusted value for the ensemble mean in an attempt to increase predictive skill relative to using the unadjusted ensemble mean. We use the two methods to make projections of future rainfall based on a large dataset of high resolution EURO-CORDEX simulations for different seasons, rainfall variables, RCPs and points in time. Cross-validation within the ensemble using both point and probabilistic validation methods shows that in most cases predictions based on the adjusted ensemble means show higher potential accuracy than those based on the unadjusted ensemble mean. They also perform better than predictions based on conventional Akaike model averaging and statistical testing. The adjustments to the ensemble mean vary continuously between situations that are statistically significant and those that are not. Of the two methods we test, one is very simple, and the other is more complex and involves averaging using a Bayesian posterior. The simpler method performs nearly as well as the more complex method.
Subject code	333
Language	English
Publishing date	2021-03-19
Publishing country	de
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Social inequalities in heat-attributable mortality in the city of Turin, northwest of Italy: a time series analysis from 1982 to 2018.

Ellena, Marta / Ballester, Joan / Mercogliano, Paola / Ferracin, Elisa / Barbato, Giuliana / Costa, Giuseppe / Ingole, Vijendra

Environmental health : a global access science source

2020 Volume 19, Issue 1, Page(s) 116

Abstract: Background: Understanding context specific heat-health risks in urban areas is important, especially given anticipated severe increases in summer temperatures due to climate change effects. We investigate social inequalities in the association between ... ...

Abstract	Background: Understanding context specific heat-health risks in urban areas is important, especially given anticipated severe increases in summer temperatures due to climate change effects. We investigate social inequalities in the association between daily temperatures and mortality in summer in the city of Turin for the period 1982-2018 among different social and demographic groups such as sex, age, educational level, marital status and household occupants. Methods: Mortality data are represented by individual all-cause mortality counts for the summer months between 1982 and 2018. Socioeconomic level and daily mean temperature were assigned to each deceased. A time series Poisson regression with distributed lag non-linear models was fitted to capture the complex nonlinear dependency between daily mortality and temperature in summer. The mortality risk due to heat is represented by the Relative Risk (RR) at the 99th percentile of daily summer temperatures for each population subgroup. Results: All-cause mortality risk is higher among women (1.88; 95% CI = 1.77, 2.00) and the elderly (2.13; 95% CI = 1.94, 2.33). With regard to education, the highest significant effects for men is observed among higher education levels (1.66; 95% CI = 1.38, 1.99), while risks for women is higher for the lower educational level (1.93; 95% CI = 1.79, 2.08). Results on marital status highlighted a stronger association for widower in men (1.66; 95% CI = 1.38, 2.00) and for separated and divorced in women (2.11; 95% CI = 1.51, 2.94). The risk ratio of household occupants reveals a stronger association for men who lived alone (1.61; 95% CI = 1.39, 1.86), while for women results are almost equivalent between alone and not alone groups. Conclusions: The associations between heat and mortality is unequal across different aspects of social vulnerability, and, inter alia, factors influencing the population vulnerability to temperatures can be related to demographic, social, and economic aspects. A number of issues are identified and recommendations for the prioritisation of further research are provided. A better knowledge of these effect modifiers is needed to identify the axes of social inequality across the most vulnerable population sub-groups.
MeSH term(s)	Adolescent ; Adult ; Aged ; Aged, 80 and over ; Child ; Child, Preschool ; Cities/epidemiology ; Female ; Heat Stress Disorders/mortality ; Hot Temperature/adverse effects ; Humans ; Infant ; Infant, Newborn ; Italy/epidemiology ; Male ; Middle Aged ; Socioeconomic Factors ; Young Adult
Language	English
Publishing date	2020-11-16
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2092232-2
ISSN	1476-069X ; 1476-069X
ISSN (online)	1476-069X
ISSN	1476-069X
DOI	10.1186/s12940-020-00667-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Numerical Simulation of the Period 1971–2100 over the Mediterranean Area with a Regional Model, Scenario SRES-A1B

Bucchignani Edoardo / Mercogliano Paola / Montesarchio Myriam / Zollo Alessandra Lucia

Sustainability, Vol 9, Iss 12, p

2017 Volume 2192

Abstract: In this work, we discuss the results of numerical simulations performed with the regional model COSMO-CLM over the Mediterranean area at a spatial resolution of 14 km, employing an optimized model configuration. An assessment of model capabilities to ... ...

Abstract	In this work, we discuss the results of numerical simulations performed with the regional model COSMO-CLM over the Mediterranean area at a spatial resolution of 14 km, employing an optimized model configuration. An assessment of model capabilities to reproduce the main features of the recent and past climate has been performed, using two different simulations: The first simulation is driven by the ERA40 Reanalysis and the second, by the CMCC-MED global model. Validation is performed through a comparison with the E-OBS dataset. Climate projections, according to the SRES A1B emission scenario, have been further analyzed in terms of change of 2-m temperature and precipitation, and have shown a significant warming expected at the end of the 21st Century, along with a general reduction in precipitation, particularly evident in spring and summer.
Keywords	Mediterranean ; regional scenarios ; climate change ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2017-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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