Key Research Findings Key Messages

Annual average air temperature in China has risen slightly faster than the average rate of global warming. The warming has led in places to a lengthening of the growing season and has affected cropping systems and management practices Droughts are responsible for the largest direct economic losses due to natural hazards in China. Average annual grain losses were 14 million tons between 1949 and 2001 accounting for 4.6% of average grain production over the same period. Flood events also disrupt agriculture and accounted for 28% of the total economic losses due to meteorological disasters during There is a tendency for wheat, rice, and maize yields to decrease in the southern parts of China, where crops are already grown close to their temperature tolerance and warmer conditions speed up crop maturation; yields tend to increase in central, north, and north-eastern China benefitting from the longer growing season. The effects of recent climate trends and extremes highlight the challenge they pose for agriculture in China. Improved understanding of their impacts an help the design of adaptation strategies Preliminary studies show there is good potential to increase food production if the right strategies and technologies can be identified. Climate Change: Impacts on Agriculture Understanding Past and Future Impacts of Climate Change in Agriculture: Implications for Adaptation Planning

The research on climate change and health conducted in Guangdong province indicates that extreme climate events, such as heat waves and cold spells, increase the risk of mortality and infectious diseases. Vulnerability to heat waves is higher in economically undeveloped regions; there is much room to improve public awareness on the health risk and appropriate responses in dealing with heat waves. Meteorological and health departments should cooperate to build up and improve the monitoring systems on climate change and public health through Guangdong province. Establishing a multi-sectorial cooperation mechanism to develop and implement temperature early warning systems will substantially help to minimize adverse health impacts of climate change. Risk communication strategies, education, and awareness projects and adaptation policies should be developed at a provincial authority level to improve risk perception and further reduce the adverse health impacts of climate change. Climate Change and Population Health

With water supplies per capita only 25% of the global average, and uneven rainfall already causing frequent floods and droughts, China must prepare for shifting water regimes under climate change. The Adapting to Climate Change in China (ACCC) research policy project shows how the latest climate change modeling can be linked with impact assessment and decision-making across different sectors, including water. Climate change is one of a number of pressures affecting water resources in China. Population growth, urbanisation, and industrialisation are increasing demand and polluting sources. At the same time, climate change is making flows more variable and amplifying existing drought and flood patterns. Although climate models agree warming will continue, rainfall projects are less certain. However, the prevailing pattern of ‘north dry, south wet’ looks set to persist; exacerbating water scarcity in some northern regions, which are important for agriculture. As China’s economy grows and competition for water intensifies, China will need to develop robust systems for managing water in an uncertain but increasingly volatile climate, particularly in the water-scarce north. This may require a new style of adaptive management, combining use of non- traditional sources such as urban waste water with better management of existing storage, and much more emphasis on water conservation and reallocation. Water Management as Climate Changes

Given the variety of contexts and the fact that climate change is a global phenomenon with highly differential and localized impacts, there are no standardized methods for conducting vulnerability and risk assessments. Which method is selected depends on spatial and temporal scales, resources available, data availability, and accessibility and requirements of decision makers. This is well supported by the evidence emerging from the experience of the ACCC project in China. Conducting comprehensive climate change vulnerability assessments requires interdisciplinary research collaboration. The process of establishing partnerships and building a common methodological research framework is challenging and adequate time should be allocated for this step. Developing a common language and agreeing on definitions of key concepts, such as risk and vulnerability, is essential to ensure effective collaboration. This should be done at the start of the research process. Quantitative models of vulnerability and risk can be difficult to construct if appropriate data for indicators are missing or are of low quality. Furthermore, quantitative models can be cumbersome to apply to simulate information on how rules, policies, culture, and social norms influence behavior and vulnerability to multiple stressors beyond climate change. These factors need to be evaluated through qualitative vulnerability assessments. Using such methods in an interdisciplinary research context in China is challenging, as most researchers are more familiar with quantitative methods. Vulnerability and risk assessments become more meaningful and are likely to lead ot change when they are linked to real-life governance and policy processes, and to community interests. This requires researchers conducting vulnerability and risk assessments to engage with stakeholders before the assessments begin and ensure their involvement in the assessment processes. Policy: Challenges and Lessons from China

The end-users of climate data are growing in number and becoming more diverse as more countries commit to take action on climate change. To produce policy-relevant data, scientists have to understand decision-makers’ need for specific kinds of evidence—providing that data in an easy-to-use format. User-friendly climate science starts with an awareness of key policy questions, focuses on that data which will reveal relevant impacts, and interprets the results in terms of the decisions to be made. Governments not only need access to climate data, but technical support on how to apply it. This support should include clear statements of what is available, its scientific pedigree, its underlying assumptions and limitations, and guidance on how to use it—and how not to use it. User-Friendly Data Sharing

Decision-makers need specific information about the range of climate futures we should prepare for. Since climate models agree on global trends, but disagree on just how fast and intense the changes will be, combining multiple models gives a fuller picture, deals with uncertainty, and enables adaptation responses. Vulnerability assessments and adaptation planning also require spatially detailed data—which means ‘downscaling’ global climate models to show future changes at higher resolution. Downscaling doesn’t come cheaply. But by using a carefully chosen sample of available models, researchers can produce detailed climate projections covering a wide range of scenarios while keeping computing costs relatively low. Policy-ready Climate Model Projections