scholarly journals Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy)

2017 ◽  
Vol 21 (6) ◽  
pp. 2701-2723 ◽  
Author(s):  
Emanuele Bevacqua ◽  
Douglas Maraun ◽  
Ingrid Hobæk Haff ◽  
Martin Widmann ◽  
Mathieu Vrac
Keyword(s):  
Risk Analysis ◽  
Climate Models ◽  
Statistical Modelling ◽  
Future Climate ◽  
Accurate Information ◽  
Multivariate Statistical ◽  
The Past ◽  
Uncertainty Estimates ◽  
Compound Events ◽  
The Impact

Abstract. Compound events (CEs) are multivariate extreme events in which the individual contributing variables may not be extreme themselves, but their joint – dependent – occurrence causes an extreme impact. Conventional univariate statistical analysis cannot give accurate information regarding the multivariate nature of these events. We develop a conceptual model, implemented via pair-copula constructions, which allows for the quantification of the risk associated with compound events in present-day and future climate, as well as the uncertainty estimates around such risk. The model includes predictors, which could represent for instance meteorological processes that provide insight into both the involved physical mechanisms and the temporal variability of compound events. Moreover, this model enables multivariate statistical downscaling of compound events. Downscaling is required to extend the compound events' risk assessment to the past or future climate, where climate models either do not simulate realistic values of the local variables driving the events or do not simulate them at all. Based on the developed model, we study compound floods, i.e. joint storm surge and high river runoff, in Ravenna (Italy). To explicitly quantify the risk, we define the impact of compound floods as a function of sea and river levels. We use meteorological predictors to extend the analysis to the past, and get a more robust risk analysis. We quantify the uncertainties of the risk analysis, observing that they are very large due to the shortness of the available data, though this may also be the case in other studies where they have not been estimated. Ignoring the dependence between sea and river levels would result in an underestimation of risk; in particular, the expected return period of the highest compound flood observed increases from about 20 to 32 years when switching from the dependent to the independent case.

scholarly journals Multivariate Statistical Modelling of Compound Events via Pair-Copula Constructions: Analysis of Floods in Ravenna

2017 ◽  
Author(s):  
Emanuele Bevacqua ◽  
Douglas Maraun ◽  
Ingrid Hobæk Haff ◽  
Martin Widmann ◽  
Mathieu Vrac
Keyword(s):  
Risk Analysis ◽  
Climate Models ◽  
Statistical Modelling ◽  
Future Climate ◽  
Accurate Information ◽  
Multivariate Statistical ◽  
The Past ◽  
Uncertainty Estimates ◽  
Compound Events ◽  
The Impact

Abstract. Compound events are multivariate extreme events in which the individual contributing variables may not be extreme themselves, but their joint – dependent – occurrence causes an extreme impact. The conventional univariate statistical analysis cannot give accurate information regarding the multivariate nature of these events. We develop a conceptual model, implemented via pair-copula constructions, which allows for the quantification of the risk associated with compound events in present day and future climate, as well as the uncertainty estimates around such risk. The model includes meteorological predictors which provide insight into both the involved physical processes, and the temporal variability of CEs. Moreover, this model provides multivariate statistical downscaling of compound events. Downscaling of compound events is required to extend their risk assessment to the past or future climate, where climate models either do not simulate realistic values of the local variables driving the events, or do not simulate them at all. Based on the developed model, we study compound floods, i.e. joint storm surge and high river runoff, in Ravenna (Italy). To explicitly quantify the risk, we define the impact of compound floods as a function of sea and river levels. We use meteorological predictors to extend the analysis to the past, and get a more robust risk analysis. We quantify the uncertainties of the risk analysis observing that they are very large due to the shortness of the available data, though this may also be the case in other studies where they have not been estimated. Ignoring the dependence between sea and river levels would result in an underestimation of risk, in particular the expected return period of the highest compound flood observed increases from about 20 to 32 years when switching from the dependent to the independent case.

scholarly journals Predicted Future Benefits for an Endemic Rodent in the Irano-Turanian Region

Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Suzanna Meeussen ◽  
Anouschka Hof
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Species Distribution Modelling ◽  
Geographic Range ◽  
Future Climate ◽  
Future Climate Change ◽  
Distribution Ranges ◽  
Bioclimatic Variables ◽  
Suitable Area ◽  
The Impact

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.

scholarly journals Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes (Normandy, France)

2013 ◽  
Vol 1 (2) ◽  
pp. 957-1000 ◽  
Author(s):  
M. Fressard ◽  
Y. Thiery ◽  
O. Maquaire
Keyword(s):  
Landslide Susceptibility ◽  
Roc Curves ◽  
Statistical Modelling ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Statistical Accuracy ◽  
Multivariate Statistical ◽  
The Impact ◽  
Modelling Methods

Abstract. The objective of this paper is to assess the impact of the datasets quality for the landslide susceptibility mapping using multivariate statistical modelling methods at detailed scale. This research is conducted in the Pays d'Auge plateau (Normandy, France) with a scale objective of 1/10000, in order to fit the French guidelines on risk assessment. Five sets of data of increasing quality (considering accuracy, scale fitting, geomophological significance) and cost of acquisition are used to map the landslide susceptibility using logistic regression. The best maps obtained with each set of data are compared on the basis of different statistical accuracy indicators (ROC curves and relative error calculation), linear cross correlation and expert opinion. The results highlights that only high quality sets of data supplied with detailed geomorphological variables (i.e. field inventory and surficial formations maps) can predict a satisfying proportion of landslides on the study area.

scholarly journals Evaluation of Future Climate and Potential Impact on Streamflow in the Upper Nan River Basin of Northern Thailand

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Miyuru B. Gunathilake ◽  
Yasasna V. Amaratunga ◽  
Anushka Perera ◽  
Imiya M. Chathuranika ◽  
Anura S. Gunathilake ◽  
...  
Keyword(s):  
River Basin ◽  
Minimum Temperature ◽  
Climate Models ◽  
Hydrological Modeling ◽  
Winter Season ◽  
Future Climate ◽  
Maximum Temperature ◽  
Monthly Precipitation ◽  
Northern Thailand ◽  
The Impact

Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.

Tsunami on Mars: Implications for the duration and timing of a northern ocean

2020 ◽  
Author(s):  
Francois Costard ◽  
José Alexis Palmero Rodriguez ◽  
Antoine Séjourné ◽  
Anthony Lagain ◽  
Steve Clifford ◽  
...  
Keyword(s):  
Climate Models ◽  
Northern Plains ◽  
The Past ◽  
Time Period ◽  
Total Inventory ◽  
Climatic Evolution ◽  
Global Inventory ◽  
The Impact ◽  
Equivalent Layer ◽  
Potential Origin

<p>The duration and timing of a northern ocean is a key issue in understanding the past geological and climatic evolution of Mars. Mars experienced its greatest loss of H<sub>2</sub>O between the Noachian and Late Hesperian (~10 m Global Equivalent Layer, Jakosky et al., 2017) roughly the same amount that is thought to have been added to the global inventory by extrusive volcanism over the same time period (Carr and Head, 2015). Thus, the total inventory of water was probably similar during these two epochs. But, the ocean during the Late Hesperian was smaller in extension than the ocean during the Noachian– with significant implications for the potential origin and survival of life. Here we examine the implications of the existence of a Late Hesperian/ Early Amazonian ocean on the planet’s inventory of water (and especially liquid water) and its variation with time. Our previous work (Rodriguez et al., 2016; Costard et al., 2017) concluded that the most plausible explanation for the origin of the Thumbprint Terrain (TT) lobate deposits, with run-ups, found along the dichotomy boundary, especially in Arabia Terra, was tsunami deposits. This supports the hypothesis that an ocean occupied the northern plains of Mars as recently as ~3 billion years ago. Furthermore, Costard et al (2017) produced a tsunami numerical model showing that the TT deposits exhibit fine-scale textural patterns due to the wave’s interference patterns resulting from interactions with the coastal topography. More recently, we suggested that the unusual characteristics of Lomonosov crater (50.52°N/16.39°E ) in the northern plains are best explained by the presence of a shallow ocean at the time of the impact (Costard et al., 2019). Interestingly, the apparent agreement between the age of the Lomonosov impact and that of the TT unit (~3 Ga), strongly suggests that it was the source of the tsunami (Costard et al., 2019). Our preliminary assessment indicates that this impact-generated tsunami required a mostly liquid ocean and because of the high latitude location of the Lomonosov crater site, our results strongly imply relatively warm paleoclimatic conditions. Our conclusions highlight the need for more sophisticated climate models.</p>

Timothy yield and nutritive value with a three-harvest system under the projected future climate in Canada

2014 ◽  
Vol 94 (2) ◽  
pp. 213-222 ◽  
Author(s):  
Qi Jing ◽  
Gilles Bélanger ◽  
Budong Qian ◽  
Vern Baron
Keyword(s):  
Climate Change ◽  
Nutritive Value ◽  
Climate Models ◽  
Phleum Pratense ◽  
Global Climate Models ◽  
Future Climate ◽  
Climate Scenarios ◽  
Intergovernmental Panel ◽  
Stochastic Weather Generator ◽  
The Impact

Jing, Q., Bélanger, G., Qian, B. and Baron, V. 2014. Timothy yield and nutritive value with a three-harvest system under the projected future climate in Canada. Can. J. Plant Sci. 94: 213–222. Timothy (Phleum pratense L.) is harvested twice annually in Canada but with projected climate change, an additional harvest may be possible. Our objective was to evaluate the impact on timothy dry matter (DM) yield and key nutritive value attributes of shifting from a two- to a three-harvest system under projected future climate conditions at 10 sites across Canada. Future climate scenarios were generated with a stochastic weather generator (AAFC-WG) using two global climate models under the forcing of two Intergovernmental Panel on Climate Change emission scenarios and, then, used by the CATIMO (Canadian Timothy Model) grass model to simulate DM yield and key nutritive value attributes. Under future climate scenarios (2040–2069), the additional harvest and the resulting three-harvest system are expected to increase annual DM yield (+0.46 to +2.47 Mg DM ha−1) compared with a two-harvest system across Canada but the yield increment will on average be greater in eastern Canada (1.88 Mg DM ha−1) and Agassiz (2.02 Mg DM ha−1) than in the prairie provinces of Canada (0.84 Mg DM ha−1). The DM yield of the first harvest in a three-harvest system is expected to be less than in the two-harvest system, while that of the second harvest would be greater. Decreases in average neutral detergent fibre (NDF) concentration (−19 g kg−1 DM) and digestibility (dNDF, −5 g kg−1 NDF) are also expected with the three-harvest system under future conditions. Our results indicate that timothy will take advantage of projected climate change, through taking a third harvest, thereby increasing annual DM production.

scholarly journals Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes

2017 ◽  
Vol 21 (1) ◽  
pp. 345-355 ◽  
Author(s):  
Hjalte Jomo Danielsen Sørup ◽  
Stylianos Georgiadis ◽  
Ida Bülow Gregersen ◽  
Karsten Arnbjerg-Nielsen
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Future Climate ◽  
High Temporal Resolution ◽  
Urban Water ◽  
Precipitation Time Series ◽  
Event Scale ◽  
The Impact

Abstract. Urban water infrastructure has very long planning horizons, and planning is thus very dependent on reliable estimates of the impacts of climate change. Many urban water systems are designed using time series with a high temporal resolution. To assess the impact of climate change on these systems, similarly high-resolution precipitation time series for future climate are necessary. Climate models cannot at their current resolutions provide these time series at the relevant scales. Known methods for stochastic downscaling of climate change to urban hydrological scales have known shortcomings in constructing realistic climate-changed precipitation time series at the sub-hourly scale. In the present study we present a deterministic methodology to perturb historical precipitation time series at the minute scale to reflect non-linear expectations to climate change. The methodology shows good skill in meeting the expectations to climate change in extremes at the event scale when evaluated at different timescales from the minute to the daily scale. The methodology also shows good skill with respect to representing expected changes of seasonal precipitation. The methodology is very robust against the actual magnitude of the expected changes as well as the direction of the changes (increase or decrease), even for situations where the extremes are increasing for seasons that in general should have a decreasing trend in precipitation. The methodology can provide planners with valuable time series representing future climate that can be used as input to urban hydrological models and give better estimates of climate change impacts on these systems.

scholarly journals Comparative study of conceptual versus distributed hydrologic modelling to evaluate the impact of climate change on future runoff in unregulated catchments

2019 ◽  
Vol 11 (2) ◽  
pp. 341-366 ◽  
Author(s):  
Hashim Isam Jameel Al-Safi ◽  
Hamideh Kazemi ◽  
P. Ranjan Sarukkalige
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Distributed Model ◽  
Runoff Reduction ◽  
The Future ◽  
The Impact

Abstract The application of two distinctively different hydrologic models, (conceptual-HBV) and (distributed-BTOPMC), was compared to simulate the future runoff across three unregulated catchments of the Australian Hydrologic Reference Stations (HRSs), namely Harvey catchment in WA, and Beardy and Goulburn catchments in NSW. These catchments have experienced significant runoff reduction during the last decades due to climate change and human activities. The Budyko-elasticity method was employed to assign the influences of human activities and climate change on runoff variations. After estimating the contribution of climate change in runoff reduction from the past runoff regime, the downscaled future climate signals from a multi-model ensemble of eight global climate models (GCMs) of the Coupled Model Inter-comparison Project phase-5 (CMIP5) under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios were used to simulate the future daily runoff at the three HRSs for the mid-(2046–2065) and late-(2080–2099) 21st-century. Results show that the conceptual model performs better than the distributed model in capturing the observed streamflow across the three contributing catchments. The performance of the models was relatively compatible in the overall direction of future streamflow change, regardless of the magnitude, and incompatible regarding the change in the direction of high and low flows for both future climate scenarios. Both models predicted a decline in wet and dry season's streamflow across the three catchments.

scholarly journals Categorization of South Tyrolean Built Heritage with Consideration of the Impact of Climate

Climate ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 139 ◽  
Author(s):  
Lingjun Hao ◽  
Daniel Herrera-Avellanosa ◽  
Claudio Del Pero ◽  
Alexandra Troi
Keyword(s):  
Climate Change ◽  
Adaptation Strategies ◽  
Future Climate ◽  
Historic Buildings ◽  
Climate Scenarios ◽  
The Past ◽  
Built Heritage ◽  
Plan Adaptation ◽  
The Impact ◽  
Design Construction

Climate change imposes great challenges on the built heritage sector by increasing the risks of energy inefficiency, indoor overheating, and moisture-related damage to the envelope. Therefore, it is urgent to assess these risks and plan adaptation strategies for historic buildings. These activities must be based on a strong knowledge of the main building categories. Moreover, before adapting a historic building to future climate, it is necessary to understand how the past climate influenced its design, construction, and eventual categories. This knowledge will help when estimating the implication of climate change on historic buildings. This study aims at identifying building categories, which will be the basis for further risk assessment and adaptation plans, while at the same time analyzing the historical interaction between climate and human dwelling. The results show some correlations between building categories and climate. Therefore, it is necessary to use different archetypes to represent the typical buildings in different climate zones. Moreover, these correlations imply a need to investigate the capability of the climate-responsive features in future climate scenarios and to explore possible further risks and adaptation strategies.

scholarly journals Which climatic modeling to assess climate change impacts on vineyards?

OENO One ◽  
2017 ◽  
Vol 51 (2) ◽  
pp. 91 ◽  
Author(s):  
Hervé Quénol ◽  
Iñaki Garcia de Cortazar Atauri ◽  
Benjamin Bois ◽  
Andrew Sturman ◽  
Valérie Bonnardot ◽  
...  
Keyword(s):  
Climate Change ◽  
Climatic Change ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Future Climate ◽  
Phenological Stages ◽  
Different Types ◽  
Assess Climate Change ◽  
The Impact

The impact of climatic change on viticulture is significant: main phenological stages appear earlier, wine characteristics are changing,... This clearly illustrates the point that the adaptation of viticulture to climate change is crucial and should be based on simulations of future climate. Several types of models exist and are used to represent viticultural climates at various scales. In this paper, we propose a review of different types of climate models (methodology and uncertainties) and then few examples of its application at the scale of wine growing regions worldwide.

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