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.

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.

Earthquakes pose one of the greatest natural threats to vast populations. In the last century, earthquakes have caused 2.3 million deaths (1 million in the last 30 years alone) and US$820 billion of financial losses. Earthquakes are generated by movement along lines of geological weakness called "active faults" which, in some places, can be observed on the Earth's surface. Unlike other natural hazards, advances in scientific understanding have not yet led to a reduction in fatalities from earthquakes. Predicting the timing, location and magnitude of individual earthquakes is likely impossible, but estimating the spatial distribution of earthquake hazard is manageable, and of great importance to the global population and the insurance economy. However, there are difficulties in calculating the earthquake hazard because we are currently reliant on present-day measurements of the rates of movement of faults and historical records of past damaging earthquakes. We cannot simply observe earthquakes for longer, therefore we must develop 'geologically richer' numerical simulations to build synthetic earthquake records and seismic hazard models to improve our understanding of the fundamental processes that control earthquakes. This project will develop a new, geologically-rich, fully integrated physics-based approach to modelling all aspects of the earthquake cycle. The earthquake cycle is the cyclical nature of earthquakes occurring, with tectonic stress building up and then releasing in a series of earthquakes over time. The physical processes that control the earthquake cycle operate on different time-scales, from seconds during the earthquake to millennia between earthquakes recurring on the same fault. The shape and spacing of faults also affect how earthquakes are generated, but it is not always easy to see the true shape of faults at the Earth's surface. There are three stages of the earthquake cycle that are currently modelled separately. These are; 1. the dynamic process of fault slip occurring over seconds to minutes during the earthquake, 2. the resulting deformation and stress transfer onto surrounding faults and 3. the evolution and accumulation of tectonic stress between earthquakes. Each of these three stages can be modelled individually and are used to speculate on different aspects of the earthquake cycle. However, because they are presently not integrated, the effects of each one on the others are poorly understood. Several active and inactive systems of extensional faults will be studied. The seismically active central and southern Italian Apennines will be studied because there is a wealth of data available; the faults are well-exposed at the surface and there is a 700 years record of damaging earthquakes and therefore high seismic hazard. The inactive fault systems that will be studied are offshore Norway, Australia and New Zealand. These inactive systems are important to study because we can use seismic reflection (like echo-location of the ground under the sea bed) to image the faults, to see their 3D shape and study how that has evolved with time. The slip rate on these faults can be quantified by studying the age and offset across these faults. It's important to study a range of different systems to synthesise the different data sets available in these regions. In summary, earthquake hazard forecasting is currently lagging behind forecasting of other natural hazards. By combining three different physics-based modelling approaches and testing the resulting model on two data-rich natural fault systems, this project will generate a truly physical and geological model of a fault system - this has not been attempted before. These models will output synthetic earthquake catalogues that can be compared to historical records (hindcasting), used to speculate on the future locations of earthquakes (forecasting) and used to inform and understand uncertainty in seismic hazard mode

Tropical cyclones (TCs) are one of the most dangerous natural hazards on Earth. Known as hurricanes in the North Atlantic, TCs represent ~30% ($75bn) of global annual losses due to all natural hazards, to which all our societies are - at least economically - exposed. Understanding future changes in TC frequency and strength are active, challenging and critical research areas. The term 'tropical' suggests that the lifetime and impacts of TCs are confined to the tropics, but this is not the case. Some tropical cyclones (TCs) migrating into the mid-latitudes retain the physical characteristics of a hurricane, while others structurally evolve into post-tropical cyclones (PTCs). Both types (which we collectively call CTOs) can be extremely intense and their hazards set them apart from typical extratropical cyclones, the type of storm our societies are adapted to in mid-latitudes. Recent events, and ongoing research, have brought into sharp focus the dangers posed by CTOs to the North-East United States (NEUS), as well as the British Isles and Western Europe (BIWE). North of 30N, events in the last ten years have been the most costly on record, causing loss of life and widespread severe damage: Ophelia totalled $70m in Ireland; Sandy alone totalled US$17bn in New York City; Henri and Ida in autumn 2021 caused $31-44bn in losses around New York State. More generally, and despite uncertainty due to decadal variability, there are indications that the number of CTOs reaching the midlatitudes has increased, consistent with projections of CTOs making landfall in BIWE, in the future. Future projections, despite uncertainties, highlight the increasing likelihood of a CTO landfall over BIWE/NEUS. Even if such events should be rare, the potential consequences are alarming; for instance, our homes and infrastructure are not designed to resist hurricane-intensity winds, nor the associated flooding. Although our weather-forecasting centres surveil tropical weather, our early-warning systems remain largely untested against CTOs. Risk assessment is held back by a fundamental lack of information: while some UK and US records exist as far back as 1860, the US National Hurricane Center only began recording non-US landfalls in 1991 and a complete analysis of TCs east of 30W only in 2005. Very little research exists for the eastern side of the Atlantic. According to analysis of 7 reanalysis datasets since 1979, 3-5 CTOs reach NEUS and 1-2 CTOs reach BIWE each year. How can we address these shortcomings? Continued surveillance (e.g. with new satellite products) is key. Complementing observations are model data, for instance the climate 'reanalyses', typically spanning the last 50-100 years. Additionally, we need far more physically plausible evidence, and physical reasoning, for robust risk assessment. Huracán will: 1. make use of the latest developments in numerical simulation, with 1-3km grid-spacing (similar to the concept of pixel size in a digital camera) enabling us to fundamentally change how we simulate the processes leading to the birth (genesis) of CTOs. 2. tap into a wealth of potential case studies contained in ensembles of seasonal prediction model simulations, which offer multiple versions of 'could-have-been' CTOs and augment the sample size by a factor of order 100. 3. combine all the data products in 1) and 2) to construct plausible physical routes (storylines) for a CTO landfall and to identify what the worst-case scenarios could be in terms of wind, storm surge, precipitation (both leading to extreme flooding) and enable future planning. Huracán will leverage state-of-the-art capabilities (theory, simulation, process analysis) across leading institutions on both sides of the Atlantic, and harness international collaborations to address two pivotal issues: (i) the key factors that influence the formation and evolution of CTOs reaching the midlatitudes; (ii) what governs mid-latitude landfall of the most hazardous CTOs.