scholarly journals Statistical modelling of extreme precipitation indices for the Mediterranean area under future climate change

2013 ◽  
Vol 34 (4) ◽  
pp. 1132-1156 ◽  
Author(s):  
E. Hertig ◽  
S. Seubert ◽  
A. Paxian ◽  
G. Vogt ◽  
H. Paeth ◽  
...  
2012 ◽  
Vol 7 (1) ◽  
pp. 7 ◽  
Author(s):  
Stella Lovelli ◽  
Michele Perniola ◽  
Emanuele Scalcione ◽  
Antonio Troccoli ◽  
Lewis H. Ziska

2021 ◽  
Author(s):  
◽  
Jacob Pastor Paz

<p><b>Three manuscripts form the basis of this dissertation exploring the effect of extreme precipitation and climate change on residential property in New Zealand. The first manuscript investigates the public insurer’s expected future liabilities, given future climate projections. Specifically, it examines the effect of extreme precipitation on direct property damage associated with rainfall-induced landslides, storms and floods. This study applies a fixed-effects panel regression model using claim data linked to extreme precipitation data over 2000-2017 and future climate change scenarios until 2100. The results show that liabilities will increase more if future greenhouse gasses emissions are higher. At the aggregate level, the percent change between past and future liabilities ranges between an increase of 7 to 8% higher in the next 20 years, and an increase between 9 to 25% increase by the end of the century, depending on the greenhouse gases emissions scenario.</b></p> <p>The second manuscript examines the risk of property damage from landslides associated with extreme precipitation. The focus is on the Nelson region as it displays the highest number of claims and pay-outs relative to its population and residential stock asset, and two thirds of the pay-outs come from a single event. The focus is on this event. This research combines past insurance claim data with geographic and sociodemographic data to estimate probability of damage, which is then combined with property replacement values and damage-ratio information to calculate the expected loses and map the spatial distribution of risk. The study integrates into the risk estimates the impact of climate change on precipitation based on an ‘attribution’ study. The analysis shows that slope and social deprivation play a significant role in the probability of damage. Furthermore, higher expected losses are associated with higher property values. </p> <p>The third manuscript studies the current and future risk of property damage from floods associated with extreme precipitation and climate change. The focus is on the most expensive event on record. This study applies a logistic cross-sectional regression model that exploits spatial variation of rainfall intensity-duration-frequency (with and without the effect of climate change), while controlling for other factors that might make a property more or less likely to experience damage. The expected monetary losses are calculated by factoring in the likelihood of flood damage derived from the regression model, property replacement values, and property vulnerability (based on flood-depth fragility functions). The results show that highest losses are associated with lowest annual exceedance probabilities (AEPs), still, sizeable losses are associated with higher AEPs. In this case, the effect of climate change for different emissions scenarios is too small to cause an economically meaningful increase in risk levels in the next 80 years (2100).</p>


2021 ◽  
Author(s):  
Jacob Pastor Paz

<p><b>Three manuscripts form the basis of this dissertation exploring the effect of extreme precipitation and climate change on residential property in New Zealand. The first manuscript investigates the public insurer’s expected future liabilities, given future climate projections. Specifically, it examines the effect of extreme precipitation on direct property damage associated with rainfall-induced landslides, storms and floods. This study applies a fixed-effects panel regression model using claim data linked to extreme precipitation data over 2000-2017 and future climate change scenarios until 2100. The results show that liabilities will increase more if future greenhouse gasses emissions are higher. At the aggregate level, the percent change between past and future liabilities ranges between an increase of 7 to 8% higher in the next 20 years, and an increase between 9 to 25% increase by the end of the century, depending on the greenhouse gases emissions scenario.</b></p> <p>The second manuscript examines the risk of property damage from landslides associated with extreme precipitation. The focus is on the Nelson region as it displays the highest number of claims and pay-outs relative to its population and residential stock asset, and two thirds of the pay-outs come from a single event. The focus is on this event. This research combines past insurance claim data with geographic and sociodemographic data to estimate probability of damage, which is then combined with property replacement values and damage-ratio information to calculate the expected loses and map the spatial distribution of risk. The study integrates into the risk estimates the impact of climate change on precipitation based on an ‘attribution’ study. The analysis shows that slope and social deprivation play a significant role in the probability of damage. Furthermore, higher expected losses are associated with higher property values. </p> <p>The third manuscript studies the current and future risk of property damage from floods associated with extreme precipitation and climate change. The focus is on the most expensive event on record. This study applies a logistic cross-sectional regression model that exploits spatial variation of rainfall intensity-duration-frequency (with and without the effect of climate change), while controlling for other factors that might make a property more or less likely to experience damage. The expected monetary losses are calculated by factoring in the likelihood of flood damage derived from the regression model, property replacement values, and property vulnerability (based on flood-depth fragility functions). The results show that highest losses are associated with lowest annual exceedance probabilities (AEPs), still, sizeable losses are associated with higher AEPs. In this case, the effect of climate change for different emissions scenarios is too small to cause an economically meaningful increase in risk levels in the next 80 years (2100).</p>


Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 120
Author(s):  
Dao Nguyen Khoi ◽  
Nguyen Trong Quan ◽  
Pham Thi Thao Nhi ◽  
Van Thinh Nguyen

In the context of climate change, the impact of hydro-meteorological extremes, such as floods and droughts, has become one of the most severe issues for the governors of mega-cities. The main purpose of this study is to assess the spatiotemporal changes in extreme precipitation indices over Ho Chi Minh City, Vietnam, between the near (2021–2050) and intermediate (2051–2080) future periods with respect to the baseline period (1980–2009). The historical extreme indices were calculated through observed daily rainfall data at 11 selected meteorological stations across the study area. The future extreme indices were projected based on a stochastic weather generator, the Long Ashton Research Station Weather Generator (LARS-WG), which incorporates climate projections from the Coupled Model Intercomparison Project 5 (CMIP5) ensemble. Eight extreme precipitation indices, such as the consecutive dry days (CDDs), consecutive wet days (CWDs), number of very heavy precipitation days (R20mm), number of extremely heavy precipitation days (R25mm), maximum 1 d precipitation amount (RX1day), maximum 5 d precipitation amount (RX5day), very wet days (R95p), and simple daily intensity index (SDII) were selected to evaluate the multi-model ensemble mean changes of extreme indices in terms of intensity, duration, and frequency. The statistical significance, stability, and averaged magnitude of trends in these changes, thereby, were computed by the Mann-Kendall statistical techniques and Sen’s estimator, and applied to each extreme index. The results indicated a general increasing trend in most extreme indices for the future periods. In comparison with the near future period (2021–2050), the extreme intensity and frequency indices in the intermediate future period (2051–2080) present more statistically significant trends and higher growing rates. Furthermore, an increase in most extreme indices mainly occurs in some parts of the central and southern regions, while a decrease in those indices is often projected in the north of the study area.


Water ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 2848
Author(s):  
Wenfeng Hu ◽  
Junqiang Yao ◽  
Qing He ◽  
Jing Chen

The Tibetan Plateau (TP) are regions that are most sensitive to climate change, especially extreme precipitation changes with elevation, may increase the risk of natural disasters and have attracted attention for the study of extreme events in order to identify adaptive actions. Based on daily observed data from 113 meteorological stations in the Tibetan Plateau and the surrounding regions in China during 1971–2017, we calculated the annual total precipitation and extreme precipitation indices using the R ClimDex software package and explored elevation-dependent precipitation trends. The results demonstrate that the annual total precipitation increased at a rate of 6.7 mm/decade, and the contribution of extreme precipitation to total precipitation increased over time, and the climate extremes were enhanced. The annual total, seasonal precipitation, and precipitation extreme trends were observed in terms of elevation dependence in the Tibetan Plateau (TP) and the surrounding area of the Tibetan Plateau (TPS) during 1971–2017. There is growing evidence that the elevation-dependent wetting (EDWE) is complex over the TP. The trends in total precipitation have a strong dependence on elevation, and the EDWE is highlighted by the extreme precipitation indices, for example, the number of heavy precipitation days (R10) and consecutive wet days (CWD). The dependence of extreme precipitation on elevation is heterogeneous, as other extreme indices do not indicate EDWE. These findings highlight the precipitation complexity in the TP. The findings of this study will be helpful for improving our understanding of variabilities in precipitation and extreme precipitation in response to climate change and will provide support for water resource management and disaster prevention in plateaus and mountain ranges.


2021 ◽  
Vol 11 (3) ◽  
Author(s):  
W. R. Singh ◽  
S. Barman ◽  
S. K. Sharma ◽  
A. Taggu ◽  
A. Bandyopadhyay ◽  
...  

AbstractThe aim of this paper is to understand the historical and future climate change situation using 15 extreme precipitation indices in the Pare watershed of Arunachal Pradesh, India. Historical period (1981–2019) and future period (2021–2050) precipitation data are used to compute extreme precipitation indices in RClimDex software. The Pare watershed was divided into 13 subwatersheds; however, the results of the study showed no significant spatial variation. This study found that majority of the precipitation extreme indices are showing decreasing trends during the historical period and most of them are statistically insignificant at 95% confidence level. Only three indices such as SDII, CWD and MRI are found significant at 0.05 level in the Pare watershed. Though not significant, the annual precipitation amount in the Pare watershed was found decreasing at the rate of 3.3 mm per year during the study period. The trend analysis over the whole watershed indicated significant decreasing trends for CWD and MRI while indicating significant increasing trend for SDII. The representative concentration pathway (RCP) 4.5 and 8.5 projected the extreme precipitation indices in a very similar way. The results of the trend analysis under RCP 8.5 showed significant decreasing trend only at SW10 for the index-moderate rainfall index (MRI). Various cases of RX1DAY and RX5DAY not falling during the months of monsoon were observed in both the historical and future periods. The percentage departures of the monsoon from its annual total had increased in RCP 4.5 and RCP 8.5 scenarios as compared to the historical periods. The results of this climatic investigation suggest that the precipitation regime in the study area had been accompanied and also expected by overall reduction in precipitation amount, milder rainfall events, reduction in monsoon (June–September) rainfall and drier climatic conditions. With the prevalent historical scenario and future projected scenarios of the extreme precipitation indices, the water resource potential in the study area is expected to be greatly reduced, for which the authors seek the attention of various stakeholders in water and allied sectors to come together and discuss on the construction of water conservation structures so that agricultural activities can be expanded and remain sustainable.


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