Preparation of future weather data to study the impact of climate change on buildings

The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of climate change on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since most of building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. In this paper, the methods used to prepare future weather data for the study of the impact of climate change are reviewed. The advantages and disadvantages of each method are discussed. The inherent relationship between these methods is also illustrated. Based on these discussions and the analysis of Australian historic climatic data, an effective framework and procedure to generate future hourly weather data is presented. It is shown that this method is not only able to deal with different levels of available information regarding the climate change, but also can retain the key characters of a “typical” year weather data for a desired period.

Examining the impact of climate change on dengue transmission in the Asia-Pacific region

Dengue fever (DF) is a serious public health concern in many parts of the world. An increase in DF incidence has been observed globally over the past decades. Multiple factors including urbanisation, increased international travels and global climate change are thought to be responsible for increased DF. However, little research has been conducted in the Asia-Pacific region about the impact of these changes on dengue transmission. The overarching aim of this thesis is to explore the spatiotemporal pattern of DF transmission in the Asia-Pacific region and project the future risk of DF attributable to climate change. Annual data of DF outbreaks for sixteen countries in the Asia-Pacific region over the last fifty years were used in this study. The results show that the geographic range of DF in this region increased significantly over the study period. Thailand, Vietnam and Laos were identified as the highest risk areas and there was a southward expansion observed in the transmission pattern of DF which might have originated from Philippines or Thailand. Additionally, the detailed DF data were obtained and the space-time clustering of DF transmission was examined in Bangladesh. Monthly DF data were used for the entire country at the district level during 2000-2009. Dhaka district was identified as the most likely DF cluster in Bangladesh and several districts of the southern part of Bangladesh were identified as secondary clusters in the years 2000-2002. In order to examine the association between meteorological factors and DF transmission and to project the future risk of DF using different climate change scenarios, the climate-DF relationship was examined in Dhaka, Bangladesh. The results show that climate variability (particularly maximum temperature and relative humidity) was positively associated with DF transmission in Dhaka. The effects of climate variability were observed at a lag of four months which might help to potentially control and prevent DF outbreaks through effective vector management and community education. Based on the quantitative assessment of the climate-DF relationship, projected climate change will likely increase mosquito abundance and activity and DF in this area. Assuming a temperature increase of 3.3oC without any adaptation measures and significant changes in socio-economic conditions, the consequence will be devastating, with a projected annual increase of 16,030 cases in Dhaka, Bangladesh by the end of this century. Therefore, public health authorities need to be prepared for likely increase of DF transmission in this region. This study adds to the literature on the recent trends of DF and impacts of climate change on DF transmission. These findings may have significant public health implications for the control and prevention of DF, particularly in the Asia- Pacific region.

Projecting the impact of climate change on dengue transmission in Dhaka, Bangladesh

Weather variables, mainly temperature and humidity influence vectors, viruses, human biology, ecology and consequently the intensity and distribution of the vector-borne diseases. There is evidence that warmer temperature due to climate change will influence the dengue transmission. However, long term scenario-based projections are yet to be developed. Here, we assessed the impact of weather variability on dengue transmission in a megacity of Dhaka, Bangladesh and projected the future dengue risk attributable to climate change. Our results show that weather variables particularly temperature and humidity were positively associated with dengue transmission. The effects of weather variables were observed at a lag of four months. We projected that assuming a temperature increase of 3.3 °C without any adaptation measure and changes in socio-economic condition, there will be a projected increase of 16,030 dengue cases in Dhaka by the end of this century. This information might be helpful for the public health authorities to prepare for the likely increase of dengue due to climate change. The modelling framework used in this study may be applicable to dengue projection in other cities.

Projecting the impact of climate change on the transmission of Ross River virus : methodological challenges and research needs

Ross River virus (RRV) is the most common vector-borne disease in Australia. It is vitally important to make appropriate projections on the future spread of RRV under various climate change scenarios because such information is essential for policy-makers to identify vulnerable communities and to better manage RRV epidemics. However, there are many methodological challenges in projecting the impact of climate change on the transmission of RRV disease. This study critically examined the methodological issues and proposed possible solutions. A literature search was conducted between January and October 2012, using the electronic databases Medline, Web of Science and PubMed. Nineteen relevant papers were identified. These studies demonstrate that key challenges for projecting future climate change on RRV disease include: (1) a complex ecology (e.g. many mosquito vectors, immunity, heterogeneous in both time and space); (2) unclear interactions between social and environmental factors; and (3) uncertainty in climate change modelling and socioeconomic development scenarios. Future risk assessments of climate change will ultimately need to better understand the ecology of RRV disease and to integrate climate change scenarios with local socioeconomic and environmental factors, in order to develop effective adaptation strategies to prevent or reduce RRV transmission.

The potential impact of climate change and ultraviolet radiation on vaccine preventable infectious diseases and immunisation service delivery system

Climate change and solar ultraviolet radiation may affect vaccine-preventable infectious diseases (VPID), the human immune response process and the immunization service delivery system. We systematically reviewed the scientific literature and identified 37 relevant publications. Our study shows that climate variability and ultraviolet radiation may potentially affect VPID and the immunization delivery system through modulating vector reproduction and vaccination effectiveness, possibly influencing human immune response systems to the vaccination, and disturbing immunization service delivery. Further research is needed to determine these affects on climate-sensitive VPID and on human immune response to common vaccines. Such research will facilitate the development and delivery of optimal vaccination programs for target populations, to meet the goal of disease control and elimination.

Using a process-based model, ParopSys, to predict the impact of climate change on the eucalypt plantation pest Paropsis atomaria.

The eucalypt leaf beetle, Paropsis atomaria Olivier, is an increasingly important pest of eucalypt plantations in subtropical eastern Australia. A process-based model, ParopSys, was developed using DYMEXTM and was found to accurately predict the beetle populations. Climate change scenarios within the latest Australian climate model forecast range were run in ParopSys at three locations to predict changes in beetle performance. Relative population peaks of early generations did not change but shifted to earlier in the season. Temperature increases of 1.0 to 1.5 ºC or greater predicted an extra generation of adults at Gympie and Canberra, but not for Lowmead, where increased populations of late season adults were observed under all scenarios. Furthermore, an additional generation of late-larval stages was predicted at temperature increases of greater than 1.0 ºC at Lowmead. Management strategies to address these changes are discussed, as are requirements to improve the predictive capacity of the model.

Impact of climate change on Indian forests: a dynamic vegetation modeling approach

We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.

Impact of climate change at species level: a case study of teak in India

In this study, we model the long-term effect of climate change on commercially important teak (Tectona grandis) and its productivity in India. This modelling assessment is based on climate projections of the regional climate model of the Hadley Center (HadRM3) and the dynamic vegetation model, IBIS. According to the model projections, 30% of teak grids in India are vulnerable to climate change under both A2 and B2 SRES scenarios because the future climate may not be optimal for teak at these grids. However, the net primary productivity and biomass are expected to increase because of elevated levels of CO2. Given these directions of likely impacts, it is crucial to further investigate the climate change impacts on teak and incorporate such findings into long-term teak plantation programs. This study also demonstrates the feasibility and limitations of assessing the impact of projected climate change at the species level in the tropics.

Impact of climate change on marine pelagic phenology and trophic mismatch

Phenology, the study of annually recurring life cycle events such as the timing of migrations and flowering, can provide particularly sensitive indicators of climate change. Changes in phenology may be important to ecosystem function because the level of response to climate change may vary across functional groups and multiple trophic levels. The decoupling of phenological relationships will have important ramifications for trophic interactions, altering food-web structures and leading to eventual ecosystem-level changes. Temperate marine environments may be particularly vulnerable to these changes because the recruitment success of higher trophic levels is highly dependent on synchronization with pulsed planktonic production. Using long-term data of 66 plankton taxa during the period from 1958 to 2002, we investigated whether climate warming signals are emergent across all trophic levels and functional groups within an ecological community. Here we show that not only is the marine pelagic community responding to climate changes, but also that the level of response differs throughout the community and the seasonal cycle, leading to a mismatch between trophic levels and functional groups.