Extreme weather events and climate variability

One of the main consequences of climate change in Brazil is the increase in the occurrence of extreme rainfall, which in turn trigger Hydrometeorological disasters; the Brazilian continental dimension, the regional characteristics of biomes and socioeconomic inequality are conditioning factors for the impacts of extreme events in the country. This work analyzes Brazil's socioeconomic and urban infrastructure vulnerability, combined with the regional exposure of the population, based on disasters observed and future scenarios for the occurrence of rainfall extremes. As a result, it points out that climate change impact differently on large Brazilian regions, due to population density and the poor quality of urban infrastructure services. RESUMO Uma das principais consequências das mudanças climáticas no Brasil é o aumento dos extremos de chuva, que causa desastres hidrometeorológicos. A dimensão continental brasileira, as características regionais dos biomas e a desigualdade soci...

This chapter examines avenues for realizing effective responses to mounting 'climate refugee' justice issues through UN refugee and climate policy mechanisms and institutions. It begins with a discussion of key normative justice issues that are unique to climate refugee cases, and explanation of the legal reasons climate refugees are not currently extended rights to non-refoulement, asylum, and relief, available to other sorts of refugees under the UN Refugee Convention. Subsequently, I assess five complementary proposals for addressing climate refugee issues and consider how the five proposals could be co-implemented to realize effective international responses to emerging climate refugee issues.

Growing scientific evidence suggests that human-induced climate change will bring about large-scale environmental changes such as sea-level rise and coastal flooding, extreme weather events and agricultural disruptions. The speed and extent of these changes and the expected impacts on social and corresponding economic and industrial systems are now moving to the forefront of debates. In this paper, we argue that climate change will lead to significant disruptions to firms which might ultimately create the necessity of a geographical shift of firm and industrial activities away from regions highly affected by climate change. Such a shift might become necessary due to (1) direct disruptions through climate change impacts on firm operations, for instance through droughts, floods, or sea level rise, and due to (2) disruptions in a firm’s supplier, buyer or resource base that lead to flow-on effects and adverse consequences for a firm. We propose a framework for integrating firm relocation decisions into firm adaptive responses to climate change. The framework consists of three assessment steps: the level of risk from climate change impacts at a firm’s location, the feasibility of relocation, and associated costs and benefits. We apply the framework to two case examples. The first case of electricity distribution firms in Victoria/Australia illustrates how the relocation (undergrounding) of cables could decrease the vulnerability of distribution networks to bushfires and the risk of electricity-caused fires, but would require significant investments. The second case of firms in the Australian pastoral industry points to geographic diversification of pastoral land holdings as possible adaptation option, but also to constraints in form of availability of suitable properties, ties to local communities, and adverse impacts on biodiversity. Implications for adaptation research and practice are outlined.

ABSTRACT
Weather Forecast stations are used for the prediction of future weather conditions.
These systems require intensive human efforts and are sometimes inaccurate in its
prediction. Wireless weather monitoring stations are created to monitor weather
virtually or remotely without the requirement of direct human efforts. The system is
designed to implement sensors which accurately acquire analog or digital data passed
to a microcontroller for the storage and processing of these data. This project is focused
on the construction of wireless weather monitoring system able to sense temperature,
humidity and light intensity for normal use by regular users, application in agriculture,
science laboratories, industries and creation of weather reports.

This book is intended as a commented summary of some of the major trends and most important features that can be encountered when analysing ancient Egyptian society of the Old Kingdom. We have to bear in mind that around 3000 BCE one of the first centralised states in our recorded history rose, and the Old Kingdom represents certainly one of its apogees. Moreover, there is hardly any comparable society that left behind such a wealth of archaeological and literary evidence, a welcome companion for our journey back in time. The goal for writing this book was to outline general trends in the history of the non-royal tomb development of the period. The reason is rather simple and straightforward: ancient Egyptians considered the tomb to be their afterlife residence for eternity. In the afterlife they replicated the life they experienced during the lifetime. Thus the tomb architecture, decoration, inscriptions and equipment paradoxically represent a major tool for our understanding of the everyday life of the ancient Egyptians and enable a better comprehension of the development and dynamics of the Old Kingdom. The book is divided into nine chapters covering, step by step, the development of the Egyptian tomb and society from the Predynastic Period to the end of the first six Egyptian dynasties, a lengthy period of time which covers the Early Dynastic and the Old Kingdom periods. These six chapters are accompanied by three additional chapters on religious aspects of the Old Kingdom society, its economy and environment.

Automated Forecasting System have been shown to be highly effective in providing a wide range of integrated capabilities for time series analysis and forecasting, econometrics and systems modeling and financial analysis and reporting. We have presented a platform for the practical development and design of a Rainfall Prediction System for the Kano City Metropolitan Area. The system automatically makes future forecasts of rainfall using the rainfall forecasting model derived from the inputted rainfall time series data.  The system when fully implemented will ensure accurate analysis and forecasting processes that takes place over time in Kano. The language of implementation is Visual Basic. NET

The Expert Team on Sector-specific Climate Indices (ET-SCI) for daily temperature and precipitation were analyzed for Mt Makulu (Latitude: 15.550° S, Longitude: 28.250° E, Elevation: 1200 meter) in Zambia. The study objective was to evaluate the ET-SCI climate indices for extreme weather conditions on temperature and precipitation from 1963 to 2012. Quality and homogeneity of the time series data were checked using RHtestsV4 and RHtests_dlyPrcp while ClimPACT2 software package was used to compute the ET-SCI indices. The Mann-Kendall for annual maximum and mean temperature were statistically significant with a positive linear trend (p<0.05). Additionally, results showed a significant increase in absolute indices as a function of temperature. The maximum warmest daily temperature (TXx) index showed a predominant increase in the monthly and annual maximum value of daily maximum temperature at Mt Makulu. The minimum warmest daily temperature (TXn) showed a similar trend for the annual value. Results also showed that the daily mean temperature (TMm) and mean daily maximum temperature (TXm) had increased from 1963-2012. The Daily Temperature Range (DTR) significantly increased annually and monthly resulting in a linear slope of 0.031 and 0.003, respectively. SU (Number of days when Original Research Article

RESUMEN: Estudios recientes indican que las motillas –asentamientos de la Edad del Bronce en La Mancha (España)– constituyen uno de los más antiguos sistemas de captación de agua subterránea en Europa. Se presenta la primera investigación de los contextos hidrogeoarqueológicos de cuatro motillas. El estudio incluye la perforación de sondeos de investigación y el análisis hidrogeológico del territorio sobre el cual se asentaron. Los datos resultantes desde esta perspectiva verifican una relación entre el sustrato geológico y la distribución espacial de las motillas, emplazadas allí donde el agua subterránea era accesible con la tecnología prehistórica. Las motillas fueron construidas durante el evento climático 4.2 ka cal BP, en un momento de estrés ambiental debido a un período de prolongada aridez. ABSTRACT: Recent studies indicate that the 'motillas' –Chalcolithic and Bronze Age settlements in La Mancha (Spain)– are one of the most ancient groundwater collection system in Europe. We present here the first hydrogeoarchaeological research at the regional level in La Mancha. The study includes borehole drilling and hydrogeological analysis of the territory on which the 'motillas' are settled. The resulting data confirm a relationship between the geological substrate and the spatial distribution of the 'motillas', sited where groundwater was accessible by means of prehistoric technology. The 'motillas' were built during the 4.2 ka cal BP event in a time of environmental stress after a period of prolonged aridity.

This study is motivated by the sharp contrast between physical and probabilistic models of civil engineering. The current practice focuses on physical models while probabilistic ones are relatively underdeveloped. This unbalance can even hinder advances in physical models. Moreover, this rarely acknowledged asymmetry creates the illusion that our deterministic models accurately capture all or at least the main aspects of reality. Thus, this thesis aspires to subtly adjust this imbalance by focusing on probabilistic models.

The main contribution is that it explores often neglected or oversimplified aspects of probabilistic analysis in civil engineering. These distinct but related issues are: (i ) selection of an appropriate distribution type; (ii ) effect of statistical uncertainty; (iii ) measurement uncertainty; (iv) long-term trends; and (v) dependence structure. These are demonstrated through analyzing extreme ground snow loads, although they are inevitably present for most random variables. Snow action, which has recently led to numerous structural failures in Central Europe, is treated as a vehicle of illustration to give a sharp focus to the study.

Methods developed in mathematical statistics, probability theory, information theory, and structural reliability are applied to tackle these issues. Fully statistical analysis of snow extremes is undertaken in conjunction with structural reliability analysis. The popular civil engineering approaches are compared with more advanced techniques that are able to capture the neglected effects in the former approaches. Snow water equivalent data of the Carpathian Region from more than 600 meteorological stations are analyzed, thus the results are representative for lowlands, for highlands, and for mountains as well. Furthermore, extensive parametric analyses are performed to extend the investigations to random variables other than ground snow intensity.

Based on the analysis of the above-listed issues the following main conclusions are drawn:

(i) It is demonstrated that mountains and highlands are better represented by Weibull, while lowlands by Fréchet distribution. In comparison, the currently standardized Gumbel model recommended in Eurocode often appreciably underestimates the snow maxima of lowlands and thus leads to overestimation of structural reliability.

(ii) It is shown that current practice, which neglects statistical uncertainties (parameter estimation and model selection uncertainties), can yield to even multiple orders of magnitude underestimation of failure probability. Bayesian posterior predictive distribution and Bayesian model averaging is proposed to account for parameter estimation and model selection uncertainties, respectively.

(iii) Statistical and interval based approaches are used to explore the effect of prevalently neglected measurement uncertainty on structural reliability. It is demonstrated that such simplification can lead to an order of magnitude underestimation of failure probability. If sufficient data are available to infer the probabilistic model of measurement uncertainty, then the statistical approach is recommended. Otherwise, the interval approach is advocated.

(iv) Using non-stationary extreme value analysis, statistically significant decreasing trend is found in annual ground snow extremes for most of the Carpathian Region. For some locations the effect of the trend on structural reliability is practically significant. This change is favorable from safety point of view as it increases reliability. Hence, revision of current regulations due to long-term trends is not needed from safety reasons, though it might be desirable from economic considerations. However, record lengths are insufficient to draw strong conclusions and to include trends in predicting extreme values with return periods of hundreds of years.

(v) Study of the widely used Gauss (normal, or Gaussian) copula assumption of time-continuous stochastic processes is performed. It reveals that Gauss copula can four times underestimate or even ten times overestimate time-variant failure probabilities obtained by other adopted copulas (t, Gumbel, rotated Gumbel, and rotated Clayton). Model averaging is proposed as a viable approach to rigorously account for copula function uncertainty.

Based on these findings, practical recommendations are made for normal and safety critical structures. The effects and proposed approaches are illustrated through real life examples. Reliability of the more than 130 years old wrought iron structure of Eiffel-hall and a steel hall of Paks Nuclear Power Plant is analyzed. The tackled challenges are general and relevant for most random variables such as wind, traffic, and earthquake actions. Therefore, the findings can be applied for these as well and they can help to draft more consistent standards and to build safer structures.

The date palm scale (DPS) Parlatoria blanchardi is a serious pest due to the damage it inflicts on its host tree (Phoenix dactylifera). To develop an effective control against DPS in arid regions, it is essential to know its bio-ecology including population dynamics and climatic factors influencing the duration and timing of life history and also the densities of different phenological stages (crawlers, first and second instars nymphs, adult males, and adult females). Monitoring of biological cycle and population dynamics of the pest were achieved through weekly counts of DPS densities on leaflets sampled at different position of date palm trees in an oasis of Ouargla region (Algerian Sahara Desert). Within this hyper-arid region, DPS established four generations per year, the most important was the spring generation. Two overlapping generations occurred in spring–early summer, and two in autumn–early winter; these two pairs of generations were interspersed by two phases of high-mortality rates, the first corresponds to winter cold, the second refers to the extreme heat of summer. Statistical analysis of the effects of the studied climatic conditions (minimum, maximum and mean temperatures, precipitation, humidity, wind, rain days, and climatic indices) on the DPS densities at different phenological stages showed great variability from one stage to another. Among these, adult females were the most affected by climate factors. For the total DPS population, high values of minimum temperatures negatively affected population density, while high maximum temperatures, hygrometry, and De Martonne aridity index showed a positive influence.

The Eastern Mediterranean is one of the most prominent hot spots of climate change in the world and extreme climatic phenomena in this region such as drought or extreme rainfall events are expected to become more frequent and intense. In this study climate extreme indices recommended by the joint World Meteorological Organization Expert Team on Climate Change Detection and Indices are calculated for daily precipitation data in 70 weather stations during 1961-2012. Observed trends and changes in daily precipitation extremes over the EM basin were analysed using the RClimDex package, which was developed by the Climate Research Branch of the Meteorological Service of Canada. Extreme and heavy precipitation events showed globally a statistically significant decrease in the Eastern Mediterranean and, in the southern parts, a significant decrease in total precipitation. The overall analysis of extreme precipitation indices reveals that decreasing trends are generally more frequent than increasing trends. We found statistically significant decreasing trends (reaching 74% of stations for extremely wet days) and increasing trends (reaching 36% of stations for number of very heavy precipitation days). Finally, most of the extreme precipitation indices have a statistically significant positive correlation with annual precipitation, particularly the number of heavy and very heavy precipitation days.

In this study, changes in the spatial and temporal patterns of climate extreme indices were analyzed. Daily maximum and minimum air temperature, precipitation, and their association with climate change were used as the basis for tracking changes at 50 meteorological stations in Iran over the period 1975–2010. Sixteen indices of extreme temperature and 11 indices of extreme precipitation, which have been quality controlled and tested for homogeneity and missing data, are examined. Temperature extremes show a warming trend, with a large proportion of stations having statistically significant trends for all temperature indices. Over the last 15 years (1995–2010), the annual frequency of warm days and nights has increased by 12 and 14 days/decade, respectively. The number of cold days and nights has decreased by 4 and 3 days/decade, respectively. The annual mean maximum and minimum temperatures averaged across Iran both increased by 0.031 and 0.059 °C/decade. The probability of cold nights has gradually decreased from more than 20 % in 1975–1986 to less than 15 % in 1999–2010, whereas the mean frequency of warm days has increased abruptly between the first 12-year period (1975–1986) and the recent 12-year period (1999–2010) from 18 to 40 %, respectively. There are no systematic regional trends over the study period in total precipitation or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at less than 15 % of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 85 % of all weather stations, forming strongly coherent spatial patterns.

Month by month analysis of precipitation in England and Wales 1766-2016 is carried out at an annual time scale for all twelve calendar months. No evidence of dependence, long term memory, or persistence is found. All twelve of the observed Hurst exponents of precipitation are found to be H≈0.5 indicative of Gaussian randomness. Therefore, non-periodic clusters of flood years observed in this area are more likely to be irregular cyclical phenomena of nature than effects of the Hurst phenomenon 1 .

The Hindu Kush-Himalayan (HKH) region epitomizes a geographic region where cryospheric processes coupled with hydrological regimes are under threat owing to a warming climate and shifts in climate extremes. In this study, we analyse global climate models in the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) archives to investigate the qualitative aspects of change and trends in temperature and precipitation indices. Specifically, we examine and evaluate multi-model, multi-scenario climate change projections and seven extreme temperature and precipitation indices over the eastern Himalaya (EH) and western Himalaya-Karakoram (WH) regions for the 21st century. Density distribution plots of observed climate indices for meteorological stations and gridded indices are also analysed, which indicate significant negative trends in the annual number of frost days and significant increasing trends in warm nights in the EH region over the 1960–2000 period. Multi-model average (MMA) projections additionally indicate continued trends towards more extreme conditions consistent with a warmer, wetter climate. Precipitation projections indicate increased mean precipitation with more frequent extreme rainfall during monsoon season in the EH region, and a wetter cold season in the WH region. Time series of all MMA precipitation indices exhibit significant increasing trends over the 1901–2099 period. By comparison, time series of temperature indices show decreases in the intra-annual extreme temperature range and total number of frost days, as well as increases in warm nights. In general, these future projections point towards increases in summertime temperatures and modifications in precipitation across both regions.

In this study, we have analysed seasonal and annual trends in rainfall and rainy days over Himachal Pradesh, an Indian state located in Western Himalayas. Based upon rainfall data of 37 stations for the period 1951-2005, it is found that the contribution of monsoon rainfall for the lower southwest part of the state is in the range of 60 to 80% of the annual total, while it is only around 35% for the higher elevation stations in the northern parts of the state. State averaged rainfall is decreasing significantly at 95% level for January (-0.61 mm/year), July (-1.83 mm/year), August (-1.49 mm/year) and October (-0.90 mm/year). On seasonal scale, rainfall and rainy days are showing significantly decreasing trends for monsoon (-3.68 mm/year and -0.09 days/year respectively) and post monsoon (-0.98 mm/year and -0.03 days/year respectively). Annual rainfall and rainy days are showing significantly decreasing trends by -4.58 mm/year and -0.13 days/year respectively. Spatial patterns of mon...

Alternatively, to other studies that used parametric distributions (e.g. Gamma) in the estimation of the Standardized Precipitation Index (SPI), this study aims to apply a nonparametric method based on Kernel Density Estimator (KDE) for calculating the SPI. Results of the proposed method were compared with the ones from the most widely used parametric distribution, using a long dataset of monthly precipitation of four meteorological stations in Iran (including Bushehr, Mashhad, Tehran and Esfahan) over a period of 107 water years (1895-2002). The capability of KDE-based SPI was compared with the Gamma-based SPI at four-time scales of 3, 6, 9 and 12 months. The frequencies of the drought classes of SPI were calculated and compared with corresponding expected frequencies. The results revealed that the KDE is more consistent with the expected values of the SPI drought/wet classes frequencies (especially in the extreme classes) at all stations as well as at the four-time scales, compared to the Gamma distribution. The greatest deviation from the expected frequencies for KDE and Gamma distribution were about 10% and 150%, respectively. This study proposes a new analytical approach in modeling SPI that provides more accurate results pertaining frequency of occurrences of extreme drought events. The output of the study can be used in many fields (e.g. tourism, agriculture, insurance, etc.) that are influenced by severe droughts.

It was the objective of this study to characterize erosional and depositional sedimentary features caused by overwash events at barrier islands. Investigations took place at the East Frisian Island of Norderney as well as at the North Frisian Island of Amrum, which both are part of a barrier system that belongs to an island chain lining the Southern North Sea. Coring data of Northern Amrum show a washover-sequence caused by several storm surge induced overwash flooding of the last century. Today, overwash processes are prevented by coastal protection arrangements that preserve the entire sedimentary sequence. The eastern part of Norderney is currently affected by storm surge events and represents a vivid example for studying today’s overwash dynamics of a young barrier island. A variety of different erosional and depositional sedimentary features like washover channel and washover fans can be recognised straight next to each other.

Coral reefs have largely declined across multiple spatial scales due to a combination of local-scale anthropogenic impacts, and due to regional-global climate change. This has resulted in a significant loss of entire coral functional groups, including western Atlantic Staghorn coral (Acropora cervicornis) biotopes, and in a net decline of coral reef ecosystem resilience, ecological functions, services and benefits. Low-tech coral farming has become one of the most important tools to help restore depleted coral reefs across the Wider Caribbean Region. We tested a community-based, low-tech coral farming approach in Culebra Island, Puerto Rico, aimed at adapting to climate change-related impacts through a two-year project to propagate A. cervicornis under two contrasting fishing management conditions, in coastal areas experimenting significant land use changes. Extreme rainfall events and recurrent tropical storms and hurricanes had major site-and method-specific impacts on project outcome, particularly in areas adjacent to deforested lands and subjected to recurrent impacts from land-based source pollution (LBSP) and runoff. Overall, coral survival rate in “A frame” units improved from 73% during 2011-2012 to 81% during 2012-2013. Coral survival rate improved to 97% in horizontal line nurseries (HLN) incorporated during 2012-2013. Percent tissue cover ranged from 86% to 91% in “A frames”, but reached 98% in HLN. Mean coral skeletal extension was 27 cm/y in “A frames” and 40 cm/y in HLN. These growth rates were up to 545% to 857% faster than previous reports from coral farms from other parts of the Caribbean, and up to 438% faster than wild colonies. Branch production and branchiness index (no. harvestable branches > 6 cm) increased by several orders of magnitude in comparison to the original colonies at the beginning of the project. Coral mortality was associated to hurricane physical impacts and sediment-laden runoff impacts associated to extreme rainfall and deforestation of adjacent lands. This raises a challenging question regarding the impact of chronic high sea surface temperature (SST), in combination with recurrent high nutrient pulses, in fostering increased coral growth at the expense of coral physiological conditions which may compromise corals resistance to disturbance. Achieving successful local management of reefs and adjacent lands is vital to maintain the sustained net production in coral farms and of reef structure, and the provision of the important ecosystem services that they provide. These measures are vital for buying time for reefs while global action on climate change is implemented. Adaptive community-based strategies are critical to strengthen institutional management efforts. But government agencies need to transparently build local trust, empower local stakeholders, and foster co-management to be fully successful. Failing to achieve that could make community-based coral reef rehabilitation more challenging, and could potentially drive rapidly declining, transient coral reefs into the slippery slope to slime.

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

Extreme climate events are becoming more frequent and severe due to climate change. Vulnerability to extremes is the result of three components: exposure to hazards, sensitivity of the system, and capacity to adapt. A large-scale qualitative study of rural vulnerability to climate extremes in Argentina, Canada, and Colombia demonstrates the political-economic root causes of vulnerability in each context. Structural causes are difficult to identify using quantitative indices and deductive metrics alone, but qualitative approaches can help identify key drivers of vulnerability at a deeper level. Technology and diversification are insufficient to address such structural or “deep” vulnerability.

As a continuation of the first paper from the late medieval drought series related to medieval Hungary, we present, analyse and compare further late medieval drought data, based on contemporary direct and indirect written sources. The evidence, derived from documentary sources referring to the droughts and dry spells in 1361, 1439, 1473, 1480, 1482(?), 1502-3 and 1506, is further compared to the recent tree-ring based hydroclimate reconstruction of the OWDA (Old World Drought Atlas), and similarities, differences and complementary information are discussed in more detail. Additionally, documentary evidence related to Danube low water-levels of 1443, 1444, 1455 and 1502 are as well presented in a broader context: these cases provide evidence on the hydrological conditions of the Upper-Danube catchment, and not on the Carpathian Basin. The OWDA evidence in most cases shows good agreement with the discussed documentary-based drought reports; some differences in the spatial extension and intensity of the droughts were only exceptionally detected (e.g. 1455, 1482-3, 1507). Most of the written documentation refer to droughts that covered more than one calendar years.

Extreme climate events are becoming more frequent and severe due to climate change. Vulnerability to extremes is the result of three components: exposure to hazards, sensitivity of the system, and capacity to adapt. A large-scale qualitative study of rural vulnerability to climate extremes in Argentina, Canada, and Colombia demonstrates the political-economic root causes of vulnerability in each context. Structural causes are difficult to identify using quantitative indices and deductive metrics alone, but qualitative approaches can help identify key drivers of vulnerability at a deeper level. Technology and diversification are insufficient to address such structural or “deep” vulnerability.

Bangladesh is highly vulnerable to climate change along with the adverse impacts of climate change. This paper aims to reveal the debates about climate change and extreme weather events. It considers Bangladesh as a case to understand the debates, the impacts of climate change on people's livelihoods. This paper used secondary sources to select and scrutunize recent literatures about climate change, extreme events, the impacts of climate change on livelihood patterns and future trends. Increase of minimum and maximum temperature and average rainfall are evident in this country along with the future projection regarding increase of temperature and precipitation. As a result sea level will rise and flood events will frequently occur in the future. The intensity, severity and extent of flooding will also be higher in the near future. It is evident that the negative impacts of extreme events will bring difficulties and challenges for people living in vulnerable areas and consequently will cause a lot of damage and loss of life. That demands paying more attention to climate change and context based adaptation strategies and integrative policy.

This paper offers insights for assessing organizational resilience to the effects of climate change, specifically to climate and weather extremes. The assessment of organizational resilience to climate and weather extremes brings about several challenges
due to (1) uncertainties about future climate change outcomes across temporal and spatial scales and (2) a lack of insight into what lead to organizational resilience, or which variables should be measured in a given study. We suggest methodological pathways for organizational managers to identify properties of future climate and weather extremes and to include them in resilience assessments. We also suggest approaches to identify factors that promote organizational resilience to selected climate and weather extremes. Findings are intended to help managers to understand how organizational resilience to climate and weather extremes can be enhanced.