Search results

The purpose of this paper is to assess the spatial and temporal variations of extreme hot days (H*) and heat wave frequencies across Iran.

The authors used daily maximum temperature (T_max) data of 27 synoptic stations in Iran. These data were standardized using the mean and the standard deviation of each day of the year. An extreme hot day was defined when the Z score of daily maximum temperature of that day was equal or more than a given threshold fixed at 1.7, while a heat wave event was considered to occur when the Z score exceeds the threshold for at least three continuous days. According to these criteria, the annual frequency of extreme hot days and the number of heat waves were determined for all stations.

The trend analysis of H* shows a positive trend during the past two decades in Iran, with the maximum number of H* (110 cases) observed in 2010. A significant trend of the number of heat waves per year was also detected during 1991-2013 in all the stations. Overall, results indicate that Iran has experienced heat waves in recent years more often than its long-term average. There will be more frequent and intense hot days and heat waves across Iran until 2050, due to estimated increase of mean air temperature between 0.5-1.1 and 0.8-1.6 degree centigrade for Rcp2.6 and Rcp8.8 scenarios, respectively.

The trend analysis of hot days and heat wave frequencies is a particularly original aspect of this paper. It is very important for policy- and decision-makers especially in agriculture and health sectors of Iran to make some adaptation strategies for future frequent and intense hot days over Iran.

The purpose of this paper is to demonstrate a spatial model of population vulnerability (VI) capable of identifying areas of high emergency service demand (ESD) during extreme heat events (EHE).

An index of population vulnerability to EHE was developed from a literature review. Threshold temperatures for EHE were defined using local temperatures, and indicators of increased morbidity. Spearman correlations determined the strength of the relationship between the VI and morbidity during EHE. The VI was mapped providing a visual guide of risk during EHE. Future changes in population vulnerability based on future population projections (2020-2030) were mapped.

The VI can be used to explain the spatial distribution of ESD during EHE. Mapping future changes in population density/demography indicated several areas currently showing high risk will continue to show increased risk.

The limitations include using outdoor temperatures to determine health-related thresholds. Due to data restrictions three different measures of morbidity were used and aggregated to postal areas.

Identifying areas of increased service demand during EHE allows the development of proactive as-well-as reactive responses to heat. The model uses readily available data, is replicable in larger urban areas.

The model allows emergency service providers to work with high risk communities to build resilience to heat exposure and subsequently save lives.

To the authors’ knowledge this triangulated approach using heat thresholds, ESD and projected changes in risk in a spatial framework has not been presented to date.

The purpose of this paper is to develop a geographic information system (GIS)‐based risk assessment tool for visualising climate change impacts in agricultural industries and evaluating eventual adaptation strategies.

A climate change adaptation strategy tool (CCAST) with built‐in GIS capability has been developed for agricultural industries. Development of the GIS functionality within CCAST includes the implementation of map projection, boundary allocation, interpolation and a graphical display of spatial data. In total, 20 climatic and crop indices are computed alongside basic climate variables (rainfall and temperature) from downscaled global climate models at 1,062 sites across the state of New South Wales (NSW) located in eastern Australia.

A case study in Australia is used to demonstrate use of this tool. This shows selecting suitable genotypes of wheat is a key adaptation strategy to mitigate the impacts of climate change on wheat cropping. It shows that spring wheat genotypes will become predominate, while the winter genotypes will only be viable in clearly defined areas where sufficient days of cool temperature exist for completion of vernalisation in a future warmer climate.

CCAST integrates knowledge relevant to climate impact management in a stand‐alone environment. It benefits from statistical analysis and GIS functionalities and provides many user‐friendly GIS features to make it suitable for practitioners on the ground.

Purpose – To investigate the potential impacts of future climate change in the United Kingdom on its road and rail networks.

Methodology/approach – The climate change impacts of increasing summer temperatures, decreasing winter temperatures, increased heavy precipitation, greater numbers of extreme weather events and rises in sea level are reviewed.

Findings – Surface transportation is the most exposed element to the localised impacts of climate change. High summer temperatures will result in road rutting, rail buckling and decreased thermal comfort, whereas more intense winter precipitation will cause flooding, landslips and bridge scour across all modes. For all impacts, it is the extreme events (e.g. heat waves and storms) that are potentially the most devastating. As shown, there are some positive climate change impacts. For example, in the case of winter maintenance, all transport networks stand to benefit.

Originality/value – In order for transport to react appropriately to the potential changes in climate, it is essential to understand how the road and rail networks may be affected and to build strategies for both adaptation and mitigation into plans for future developments for both modes.

Over the last two decades the average floor area of new houses in Australia has increased significantly. This has coincided with greater expectations of thermal comfort in homes. In certain locations, the result has been an escalation of the use of large mechanical air conditioning systems in houses. Since it is predicted that climate change will lead to an increase in the frequency and severity of extreme weather events such as heatwaves, the future maintenance of thermal comfort in houses in an affordable manner is likely to be challenging. This will have implications not only for the health and comfort of the occupants but also for peak energy loads. A compounding factor is the likelihood of increased energy prices caused, in part, by financial mechanisms aimed at minimising greenhouse gas emissions. There will be sections of the community, such as the elderly and the less well off, that will be particularly vulnerable to these combined factors.

This paper explores design strategies that could be incorporated in new and existing houses to improve thermal comfort for residents during heatwaves. It is shown that during such periods, behaviour change, thermal comfort requirements and extra energy consumption have a strong influence on devising solutions for this challenge. The results of a pilot study are given that indicate opportunities for creating cool refuges in the existing dwelling stock.

This article discusses the basics of computer‐room air conditioning, an important component of the special environment required by mainframe computers and many mini‐computers as well. Computer room air conditioners differ in some significant ways from “comfort” air‐conditioners, which are designed for the comfort of people rather than machines. These differences make it less than ideal to use air conditioning systems designed for human comfort for computer cooling. The author describes several different types of air‐conditioners, considerations related to the construction of a computer room, and factors that determine air‐conditioning requirements.

This paper aims to explore the local knowledge on climate change, its impacts and the responses they are making at the household or community level to deal with the changes on the basis of their experiences and perceptions.

The study was based on household survey conducted with one male and one female respondent in 202 households. Alongside, series of focused group discussions were conducted with local people to capture the perception on about climate change, its impacts and adaptation strategies applied to enhance their resilience capacity to changing climate. Rainfall and temperature data were collected from Department of Hydrology and Meteorology (DHM) for seven and four different stations, respectively, within Kathmandu Valley and analyzed to understand the climatic trend.

The perception of most of the local people on changes in temperature was almost in line with the recorded long-term climatic trend both showing an increasing trend, whereas the perception of decreasing both monsoon and non-monsoon rainfall did not match with the recorded data as the rainfall data analysis did not reflect any clear long-term pattern. People have been facing several impacts such as decrease in water sources, decrease in agricultural crop production, increase in new crop pest and weeds in agricultural crops. Local people are responding to these impacts as per their own skills and traditional knowledge.

This is totally original research article and the impacts and adaptations measures documented in this article may represent the case of peri-urban areas of least developed countries like Nepal.

Climate change presents potential increased threats to the comfort and health of urban populations as a result of higher summer temperatures. This paper reviews recent research on the climate change adaptation potential of urban environments and focuses on a major conurbation, London. Recent work relating to the impact of exposure to heat on population health is also noted. Data obtained from a pilot monitoring study carried out in a subset of 36 dwellings (from a total of 110 dwellings in the overall study) across London during the summer of 2009 is then discussed. Preliminary results illustrate the need to quantify the net impacts of individual building characteristics and the location of each dwelling within the London heat island. During a hot period, more than 40% of the monitored bedrooms failed the recommended overheating criteria during the night time. There was some indication of purpose built flats being more prone to overheating. The potential use of such data as the basis of a heat-related health risk epidemiological model for London is discussed. Such a tool would help health policy makers to target the most vulnerable building types and areas.

The paper aims to investigate the possible changes in mean temperature in the Mongolian Plateau associated with the 1.5 and 2°C global warming targets and how snow changes in the Mongolian Plateau when the mean global warming is well below 2°C or limited to 1.5°C.

In total, 30 model simulations of consecutive temperature and precipitation days from Coupled Model Inter-comparison Project Phase 5 (CMIP5) are assessed in comparison with the 111 meteorological monitoring stations from 1961–2005. Multi-model ensemble and model relative error were used to evaluate the performance of CMIP5 models. Slope and the Mann–Kendall test were used to analyze the magnitude of the trends and evaluate the significance of trends of snow depth (SD) from 1981 to 2014 in the Mongolian Plateau.

Some models perform well, even better than the majority (80%) of the models over the Mongolian Plateau, particularly HadGEM2-CC, CMCC-CM, BNU-ESM and GFDL-ESM2M, which simulate best in consecutive dry days (CDD), consecutive wet days (CWD), cold spell duration indicator (CSDI) and warm spell duration indicator (WSDI), respectively. Emphasis zones of WSDI on SD were deeply analysed in the 1.5 and 2 °C global warming period above pre-industrial conditions, because it alone has a significant negative relation with SD among the four indices. It is warmer than before in the Mongolian Plateau, particularly in the southern part of the Mongolian Plateau, indicating less SD.

Providing climate extremes and SD data sets with different spatial-temporal scales over the Mongolian Plateau. Zoning SD potential risk areas and proposing adaptations to promote regional sustainable development.

This is a companion paper to our previous study in Cao and Wei (2005) on stock market temperature anomaly for eight international stock markets. The temperature anomaly is characterized by a negative relationship between stock market returns and temperature. This line of work relies on the impact of environmental variables, such as temperature, on mood and behavior changes. In this paper, we expand the sample in Cao and Wei (2005) to include 19 additional financial markets. Our evidence confirms the identified negative relationship for the expanded sample. More importantly, our nonparametric tests, as opposite to the parametric or semi-parametric approaches used by previous related studies, demonstrate that this negative relationship is robust to distributional assumptions. Based on the sub-sample analysis, we find that this negative relationship is stable over time. Furthermore, we consider temperature deviation and demonstrate that this negative relationship is not just a level effect.