scholarly journals Modelling forest ruin due to climate hazards

2021 ◽  
Vol 12 (3) ◽  
pp. 997-1013
Author(s):  
Pascal Yiou ◽  
Nicolas Viovy
Keyword(s):  
Climate Change ◽  
Insurance Industry ◽  
Probability Distributions ◽  
Physiological Parameters ◽  
Proof Of Concept ◽  
Average Growth ◽  
Monte Carlo Experiments ◽  
Climate Hazards ◽  
Hazard Parameters ◽  
Climate Events

Abstract. Estimating the risk of forest collapse due to extreme climate events is one of the challenges of adapting to climate change. We adapt a concept from ruin theory, which is widely used in econometrics and the insurance industry, to design a growth–ruin model for trees which accounts for climate hazards that can jeopardize tree growth. This model is an elaboration of a classical Cramer–Lundberg ruin model that is used in the insurance industry. The model accounts for the interactions between physiological parameters of trees and the occurrence of climate hazards. The physiological parameters describe interannual growth rates and how trees react to hazards. The hazard parameters describe the probability distributions of the occurrence and intensity of climate events. We focus on a drought–heatwave hazard. The goal of the paper is to determine the dependence of the forest ruin and average growth probability distributions on physiological and hazard parameters. Using extensive Monte Carlo experiments, we show the existence of a threshold in the frequency of hazards beyond which forest ruin becomes certain to occur within a centennial horizon. We also detect a small effect of the strategies used to cope with hazards. This paper is a proof of concept for the quantification of forest collapse under climate change.

scholarly journals Modelling the Ruin of Forests under Climate Hazards

2020 ◽  
Author(s):  
Pascal Yiou ◽  
Nicolas Viovy
Keyword(s):  
Climate Change ◽  
Insurance Industry ◽  
Probability Distributions ◽  
Physiological Parameters ◽  
Adaptation To Climate Change ◽  
Average Growth ◽  
Monte Carlo Experiments ◽  
Climate Hazards ◽  
Hazard Parameters ◽  
Climate Events

Abstract. Estimating the risk of collapse of forests due to extreme climate events is one of the challenges of adaptation to climate change. We adapt a concept from ruin theory, which is widespread in econometrics or the insurance industry, to design a growth/ruin model for trees, under climate hazards that can jeopardize their growth. This model is an elaboration of a classical Cramer-Lundberg ruin model that is used in the insurance industry. The model accounts for the interactions between physiological parameters of trees and the occurrence of climate hazards. The physiological parameters describe interannual growth rates and how trees react to hazards. The hazard parameters describe the probability distributions of occurrence and intensity of climate events. We focus on a drought/heatwave hazard. The goal of the paper is to determine the dependence of ruin and average growth probability distributions as a function of physiological and hazard parameters. From extensive Monte Carlo experiments, we show the existence of a threshold on the frequency of hazards beyond which forest ruin becomes certain in a centennial horizon. We also detect a small effect of strategies to cope with hazards. This paper is a proof-of-concept to quantify collapse (of forests) under climate change.

Climate Change-Related Temperature Impacts on Warm Season Heat Mortality: A Proof-of-Concept Methodology Using BenMAP

2011 ◽  
Vol 45 (4) ◽  
pp. 1450-1457 ◽  
Author(s):  
A. Scott Voorhees ◽  
Neal Fann ◽  
Charles Fulcher ◽  
Patrick Dolwick ◽  
Bryan Hubbell ◽  
...  
Keyword(s):  
Climate Change ◽  
Warm Season ◽  
Proof Of Concept ◽  
Temperature Impacts

scholarly journals Impact of recent climate extremes on mosquito-borne disease transmission in Kenya

2021 ◽  
Vol 15 (3) ◽  
pp. e0009182
Author(s):  
Cameron Nosrat ◽  
Jonathan Altamirano ◽  
Assaf Anyamba ◽  
Jamie M. Caldwell ◽  
Richard Damoah ◽  
...  
Keyword(s):  
Climate Change ◽  
Disease Transmission ◽  
Enzyme Linked Immunosorbent Assay ◽  
Mosquito Abundance ◽  
Targeted Interventions ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Recent Climate ◽  
Climate Events ◽  
The Impact

Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983–2019 for rainfall, 2000–2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission.

scholarly journals Paesaggi d’acqua in territori fragili

2021 ◽  
Author(s):  
Giovanni Maria Biddau ◽  
Gianfranco Sanna ◽  
Silvia Serreli
Keyword(s):  
Climate Change ◽  
Climate Adaptation ◽  
Landscape Design ◽  
Environmental Disasters ◽  
Weather And Climate ◽  
Close Relationship ◽  
Urban Transformations ◽  
High Degree ◽  
Climate Events

Environmental disasters and the high degree of exposure of cities to these risks are well known. What is evident is the close relationship between these disasters and urban transformations generated by sectoral approaches to landscape design that have made territories more vulnerable to extreme weather and climate events. With the aim of creating an open and sustainable spatial plan, the case study outlined in this article is intended as an approach to climate adaptation, even though in Sardinia the connection between climate change and flood risk has not been studied in depth and the evidence of this connection has not yet emerged.

When the unprecedented becomes precedented: Lessons from Cyclones Idai and Kenneth

2021 ◽  
Author(s):  
Karen MacClune ◽  
Rachel Norton
Keyword(s):  
Climate Change ◽  
Risk Reduction ◽  
Disaster Risk Reduction ◽  
Early Warning Systems ◽  
Disaster Risk ◽  
Climate Services ◽  
Humanitarian Response ◽  
Early Action ◽  
Future Events ◽  
Climate Hazards

<p>Learning from global disasters — understanding what happened, the successes that prevented impacts from being worse, and the opportunities to reduce risk to future events — is critical if we are to protect people from increasingly extreme weather. Population growth is overtaxing ecosystems and climate change is creating new and intensifying existing climate hazards. Proactive and collaborative efforts are needed between all levels, from local to international, and across sectors connecting social science, economics, policy, infrastructure and the environment, to address these challenges. Perhaps most urgently, however, is the need to harness humanitarian response, development, disaster risk reduction, and climate change adaptation to work in concert – we can no longer afford to deliver these needs in isolation.</p><p>In March and April 2019 Cyclones Idai and Kenneth – two of the most destructive and powerful cyclones to ever hit southeast Africa – resulted in a widespread humanitarian disaster in Malawi, Mozambique and Zimbabwe, the impacts of which continue today in terms of livelihoods lost, food insecurity, and loss of permanent shelter for thousands. Damages were intensified by the novel nature of the impacts – the storms brought with them climate threats that were new to the areas and people impacted, leading to greater failure of existing preparedness and response mechanisms than might have been expected.</p><p>This talk will present learnings from a study conducted by members of the Zurich Flood Resilience Alliance on the impacts of Cyclones Idai and Kenneth, highlighting opportunities for building multi-hazard resilience to future events. In particular, we will highlight the opportunities we found for strengthening resilience, even when challenged by entirely new climate hazards, through strengthening early warning systems and climate services, building capacity and resourcing for early action, supporting the construction of resistant homes and development of more diverse farming practices, and, most crucially, by better connecting humanitarian response and Disaster Risk Reduction (DRR) efforts.</p><p>These lessons are part of a series of Post-event Review Capability (PERC) learnings conducted by Zurich since 2013. The PERC methodology (available at: https://www.floodresilience.net/perc) supports broad, multi-sectoral resilience learning from global disaster events and identifies key actions for reducing future harm.</p><div></div><div></div><div></div><div></div>

Impacts of farmers' adaptation to drought and salinity intrusion on rice yield in Vietnam's Mekong Delta

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khoi Kim Dang ◽  
Thiep Huy Do ◽  
Thi Ha Lien Le ◽  
Thi Thu Hang Le ◽  
Thinh Duc Pham
Keyword(s):  
Climate Change ◽  
Design Methodology ◽  
Rice Yield ◽  
Mekong Delta ◽  
Future Research ◽  
Adaptation Measures ◽  
Content Type ◽  
Rice Farmers ◽  
Study Sites ◽  
Climate Events

PurposeThe Vietnamese Mekong River Delta (VMD) is one of the most affected deltas by climate change in the world. Several studies have investigated factors influencing farmers' climate change adaptation behaviors in the region; however, little is known about the effectiveness of such measures. This paper examines the determinants of adaptation strategies among VMD rice farmers and assesses the impacts of such practices on rice yield.Design/methodology/approachEndogenous switching regressions were employed using a survey data of 300 rice-producing households in An Giang and Tra Vinh provinces in 2016.FindingsThe results show that farmers receiving early disaster warnings are more likely to adopt adaptation measures to climate change. If nonadaptors had chosen to respond, their rice yield would have increased by 0.932 tons/ha/season.Research limitations/implicationsThe data sample is small and collected from two provinces in the VMD only; therefore, the results may be specific for the study sites. However, future research can adopt the proposed method for other regions.Originality/valueThe study estimates the production impacts of farmers' decisions on whether or not to adapt to extreme climate events. The proposed approach allows for capturing both observed and unobserved behaviors.

scholarly journals Analysis of changes in daily temperature and precipitation extreme in Jakarta on period of 1986-2014

2018 ◽  
Vol 229 ◽  
pp. 02017
Author(s):  
Aulia N. Khoir ◽  
R. Mamlu’atur ◽  
Agus Safril ◽  
Akhmad Fadholi
Keyword(s):  
Climate Change ◽  
Maximum Temperature ◽  
Temperature Index ◽  
Extreme Climate ◽  
Rainfall Index ◽  
Temperature And Precipitation ◽  
Precipitation Characteristics ◽  
Expert Team ◽  
Weather Stations ◽  
Climate Events

Climate change due to an increase in greenhouse gas concentrations has led to changes in extreme climate events. IPCC 2007 already predicted that average global temperatures would reach 0.74⁰ C in the last 100 years (1906-2005). A study on the temperature index trends and extreme precipitation in the period of 1986-2014 in Jakarta are represented by 5 weather stations. Daily of maximum temperature, minimum temperature, and precipitation data are calculated using RClimDex Software so that temperature and rainfall index data are obtained. The indexes are extreme climate indexes defined by ETCCDMI (Expert Team for Climate Change Detection Monitoring and Indices). The indexes consist of TN10p, TN90p, TX10p, TX90p, TNn, TNx, TXn, TXx, DTR, RX1day, RX5day, RCPTOT, CDD, CWD, and R95p. The purpose of this research is to know the change of temperature and precipitation characteristics from observation result in Jakarta by using index calculation. The results show that Jakarta has number of hot days according to the trends which are generally increasing. It can cause the temperature in Jakarta to get hotter. However, for the rainfall, the upward or downward trend is not significant, so it can be said there is no change in precipitation in Jakarta during 1986-2014.

Why Is Climate Sensitivity So Unpredictable?

Science ◽  
2007 ◽  
Vol 318 (5850) ◽  
pp. 629-632 ◽  
Author(s):  
Gerard H. Roe ◽  
Marcia B. Baker
Keyword(s):  
Climate Change ◽  
Atmospheric Carbon Dioxide ◽  
Probability Distributions ◽  
Analytic Form ◽  
Future Climate Change ◽  
Large Temperature ◽  
Global Mean Temperature ◽  
Simple Analytic Form ◽  
Global Mean

Uncertainties in projections of future climate change have not lessened substantially in past decades. Both models and observations yield broad probability distributions for long-term increases in global mean temperature expected from the doubling of atmospheric carbon dioxide, with small but finite probabilities of very large increases. We show that the shape of these probability distributions is an inevitable and general consequence of the nature of the climate system, and we derive a simple analytic form for the shape that fits recent published distributions very well. We show that the breadth of the distribution and, in particular, the probability of large temperature increases are relatively insensitive to decreases in uncertainties associated with the underlying climate processes.

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