The Hub will reduce disaster risk for the poor in tomorrow's cities. The failure to integrate disaster risk resilience into urban planning and decision-making is a persistent intractable challenge that condemns hundreds of millions of the World's poor to continued cyclical destruction of their lives and livelihoods. It presents a major barrier to the delivery of the Sustainable Development Goals in expanding urban systems. Science and technology can help, but only against complex multi-hazard context of urban life and the social and cultural background to decision-making in developing countries. Science-informed urbanisation, co-produced and properly integrated with decision support for city authorities, offers the possibility of risk-sensitive development for millions of the global poor. This is a major opportunity - some 60% of the area expected to be urban by 2030 is yet to be built. Our aim is to catalyse a transition from crisis management to risk-informed planning in four partner cities and globally through collaborating International governance organisations. The Hub, co-designed with local and international stakeholders from the start, will deliver this agenda through integrated research across four urban systems - Istanbul, Kathmandu, Nairobi and Quito - chosen for their multi-hazard exposure, and variety of urban form, development status and governance. Trusted core partnerships from previous Global Challenge Research Fund, Newton Fund and UK Research Council projects provide solid foundations on which city based research projects have been built around identified, existing, policy interventions to provide research solutions to specific current development problems. We have developed innovative, strategic research and impact funds and capable management processes constantly to monitor progress and to reinforce successful research directions and impact pathways. In each urban system, the Hub will reduce risk for 1-4 million people by (1) Co-producing forensic examinations of risk root causes, drivers of vulnerability and trend analysis of decision-making culture for key, historic multi-hazard events. (2) Combining quantitative, multi-hazard intensity, exposure and vulnerability analysis using advances in earth observation, citizen science, low cost sensors and high-resolution surveys with institutional and power analysis to allow multi-hazard risk assessment to interface with urban planning culture and engineering. (3) Convene diverse stakeholder groups-communities, schools, municipalities private enterprise, national agencies- around new understanding of multi-hazard urban disaster risk stimulating engagement and innovation in making risk-sensitive development choices to help meet the SDGs and Sendai Framework. Impact will occur both within and beyond the life of the Hub and will raise the visibility of cities in global risk analysis and policy making. City Partnerships, integrating city authorities, researchers, community leaders and the private sector, will develop and own initiatives including high-resolution validated models of multi-hazard risk to reflect individual experience and inform urban development planning, tools and methods for monitoring, evaluation and audit of disaster risk, and recommendations for planning policy to mitigate risks in future development. City partnerships will collaborate with national and regional city networks, policy champions and UN agencies using research outputs to structure city and community plans responding to the Sendai Framework and targeted SDG indicators, and build methods and capacity for reporting and wider critique of the SDG and Sendai reporting process. Legacy will be enabled through the ownership of risk assessment and resilience building tools by city and international partners who will identify need, own, modify and deploy tools beyond the life of the Hub.

Three core questions bind this proposal together: how to foster growth; how to share growth and how to sustain growth 1 HOW CAN WE FOSTER GROWTH? We plan to develop a new Growth Programme focussing on bolstering innovation in its widest sense, both technological and organisational. It will co-ordinate the Centre's growth work agenda and follow up the LSE Growth Commission's policy proposals. Next, the Trade programme will analyse the impact of globalisation with a targeted focus on how to make a dramatic improvement in British export performance. A core policy question is what the UK's future relationship with other countries will be, in particular with the European Union (EU) and South-East Asia. Third, the Education and Skills programme will examine human capital investment by analysing the recent transformation of the educational system using new tools of competition and organisation theory. Two core questions are: have educational reforms worked - especially for the disadvantaged - and, what can be done to improve the intermediate skills base, a long-standing area of UK weakness. 2 HOW CAN WE SHARE THE BENEFITS OF GROWTH? A problem with growth in the decades prior to the global financial crisis was that prosperity was shared very unequally. To study the spatial dimensions of inequality, we propose a new Urban programme. This will emphasise cities as key economic units and address why so much UK growth is concentrated in the South East.This is a key policy issue in the light of the commitment to decentralise power within England by all main UK parties. Following the City Growth Commission, the policy focus will be how local policy makers can help their cities prosper. Alongside the large productivity fall since the crisis, there has been a big fall in real wages - something unique in post-war UK recessions. Some wage stagnation occurred also in the run-up to the crisis, as it has over a longer time in the US. The Labour programme will examine these changes and whether they are linked to the declining share of GDP going to employees across the world. We will look at earnings, income and wealth inequalities across individuals, but also on why women's progress has stalled. In all these aspects, we are interested not just in explaining why growth is unequally shared, but also how we could design institutions and policies that generate a "double dividend" of more growth and less inequality. 3 WHAT KIND OF GROWTH DO WE WANT? Increasing GDP per capita remains important as UK average incomes track this over the long run. But growth must be sustainable, it must deal with environmental challenges, it should expand not undermine people's happiness and it should not be at the expense of social cohesion. Dealing with climate change requires both containing demand for greenhouse gases and stimulating clean technologies and we propose a wide portfolio of green growth projects directed to this. Of course, it is not just technology that affects people's lives - it is also the beliefs and norms that regulate the interactions between people. Growth involves change that has significant impacts on people's lives and neighbourhoods, often causing great stress. Our Community programme will investigate the impact of economic changes (both direct and indirect through changes like immigration) on social cohesion, and will help to develop policies to ensure that growth benefits all communities. CEP has been at the forefront of looking beyond GDP and our Wellbeing programme will ambitiously develop a model of subjective well-being over the life-course, in order to show the quantitative causal impact of factors like parenting, schooling, employment, income and health. Without such knowledge it is impossible for policy-makers to aim effectively at greater wellbeing, even if that is their objective.

Our vision: To impel climate change mitigation action by motivating private investments in sustainably managed forest ecosystem services. Our contribution: To address a critical KE gap between expertise on the mapping, modelling and quantification of the risk of forest carbon loss, and investor's confidence in forest investments (including in REDD+). Our focus: To address 4 categories of risks (i) Climatic (ii) Fire (iii) Anthropogenic and (iv) Regulatory. Our aim: To stimulate the exploitation of UK's world-class knowledge base -NERC and elsewhere - in forest loss and risk mapping by the UK knowledge brokers and financial institutions. Our impacts: To deliver, as a consequence of this work, a more accurate and holistic understanding of the real risk represented by forest propositions around the world; a more stable and mainstream investment environment for forestry and; to bring forestry from the margins of business, to a business line as common as aviation, motor or life and pensions. We request funding for a period of 12 months to support the creation of a ForestRisks-for-Finance Network. Partners, including WillisRE Ltd., ForestRe Ltd., Ecometrica Ltd, Acclimatise Ltd. The Edinburgh Centre on Climate Change, and Forest Research will contribute more than £55,000 in-cash and in-kind to this KE initiative. A PDRA will be appointed to effectively bring together the NERC funded and UK research community (on forest-loss risks) as well as to proactively engage with potential users (Brokers & End users). This initiative stems from (a) recommendations made at the NERC-funded Long Finance symposia on "Forestry and Finance: Where's the data" (London, July 2010 and Sept 2010), to which the PI (Patenaude) was an invited panellist and (b) the wider KE activities led by Richard Max-Lino (NERC Knowledge and Innovation Manager, Financial Services) and the Long Finance initiative (http://www.zyen.com/long-finance.html).

Climate change is arguably the biggest challenge facing people this century, and changes to the intensity and frequency of climatic and hydrologic extremes will have large impacts on our communities. We use climate models to tell us about what weather in the future will be like and these computer models are based on fundamental physical laws and complicated mathematical equations which necessarily simplify real processes. One of the simplifications that really seems to matter is that of deep convection (imagine the type of processes that cause a thunderstorm). However, computers are so powerful now that we are able to produce models that work on smaller and smaller scales, and recently we have developed models which we call "convection-permitting" where we stop using these simplifications of deep convection. These "convection-permitting" models are not necessarily better at simulating mean rainfall or rainfall occurrence but they are much better at simulating heavy rainfall over short time periods (less than one day) which cause flooding, in particular flash-flood events. They are also better at simulating the increase in heavy rainfall with temperature rise that we can observe; therefore we are more confident in their projections of changes in heavy rainfall for the future. A few "convection-permitting" modelling experiments have now been run for different parts of the world but all of these have been over small regions, only the same size as the UK, or smaller. All of the experiments so far have concentrated on rainfall and none have examined how "convection-permitting" models might improve the simulation of other types of extreme weather such as hail, lightning or windstorms. In fact we know very little about how these types of extremes might change in the future. We also have no idea of the uncertainty in our experiments in terms of our predictions of future changes as we have only run one model simulation in each region - this is not useful for planning climate adaptation strategies where we really need to understand the uncertainties in our future predictions so we can plan for them. In FUTURE-STORMS we are running these "convection-permitting" models over a very large area (the whole of Europe) and we are comparing models from two different climate modelling teams at the UK Met Office and ETH Zurich in Switzerland. In addition to this we are now able to run a number of different climate models over the same region, which allows us to assess some of the uncertainties in future changes to heavy rainfall and other storm-related extreme weather. This will let us explore how heavy rainfall might change across Europe and what might be causing this. It will also allow us to look at whether these new models are able to simulate other types of extreme weather like hail, lightning and windstorms which have a huge impact on Europe, and how these might change in the future. Ultimately, we need better information on how extreme weather events might change in the future on which to make adaptation decisions and FUTURE-STORMS intends to provide this important advance, alongside translating this information into useful tools and metrics for use in climate change adaptation.

Wind storms can cause great damage to property and infrastructure. The windstorm footprint (a map of maximum wind gust speed over 3 days) is an important summary of the hazard of great relevance to the insurance industry and to infrastructure providers. Windstorm footprints are conventionally estimated from meteorological data and numerical weather model analyses. However there are several interesting less structured data sources that could contribute to the estimation of the wind storm footprints, and more importantly will raise the spatial resolution of our estimates. This is important as there are important small-scale meteorological phenomena, such as sting jets, that are currently not well resolved by the current methods. We propose to exploit three additional sources of data (and possibly others during the course of the project). The three sources so far identified identified are amateur observations available through the Met Office weather observations website (WOW), comments made on social media and video recorded on social media or CCTV. Amateur meteorological observations are currently collected by the Met Office but not used in producing the footprint estimates. We will investigate whether we can use them in the estimation of the storm footprint; a useful by-product will be estimates of the uncertainty for each WOW station. Social media, such as twitter or instagram, often contains comments on windstorms. These can range from comments on how windy it is, to reports of damage produced by storms. In some cases the geographical location of the message is provided by the device but in others it has to be inferred. There are very large numbers of messages posted on social media every day and it should be possible to used these to provide more detailed modelling of footprints. In addition to text, social media also records images and video. Video is also recorded extensively in the form of CCTV. Video recordings of trees, say, blowing in the wind include information on the strength of the windstorm. We will analyse such recordings to produce information on wind velocity and gust velocity. Bringing together large quantities of diverse data is a complex procedure. We will develop, test, and compare two approaches in modern data science: statistical process modelling and machine learning. Both methods will aim to synthesise all the data into an estimate of the windstorm footprint (and its associated uncertainty). The former will concentrate on producing a map more like the current estimates based on the maximum gust speed while the latter data based methods will concentrate more on mapping the damage caused by the storm. Once we have estimates of the windstorm footprint from both social media and the modelling we will compare these with the standard products and, in consultation with stakeholder, establish any improvements.