HIWAVES3 facilitates a dialogue between climate modelers, impact modelers and partners in different geographical regions with knowledge of local societal relevant meteorological events to construct stories of selected high-impact extreme events, simulated for present-day and future climate conditions. The story includes the origin of the extreme event from a meteorological perspective, its inter-regional linkages, its predictability, its societal impact and how climate change affects its magnitude and probability. Such stories, made available for schools, the general public and governments, are effective communication means, more so than bare numbers about the expected mean temperature increase, precipitation changes in percentages and such. Based on surveys, extreme summer events with large societal impacts, like droughts and floods, will be selected from the recent past for China, India and Europe. Similar events will be identified in large ensembles of global climate simulations. The size of the ensembles allows an analysis of the inter-regional linkages between the Arctic, the Midlatitudes and the Indian Monsoon region through large-scale Rossby waves and other meteorological factors leading to the extreme, like soil-moisture and sea-surface temperature conditions. In addition, a one in a thousand year event in China, India and Europe, although not witnessed in the recent past, will be analysed. The predictability of the event, weeks to months in advance will be assessed through additional simulations. Using empirical methods and process-based models, the impact on crop yields and economy will be estimated as well as the number of premature deaths. Using large ensembles under projected 2050 conditions the effect of climate change on these extremes and their impacts will be analysed. This research material is translated into powerful stories about concrete events that illustrate how climate affects man, man affects climate, how different geographical regions are connected and how extreme the weather might get. The meteorological data of these events will be made available for further impact studies.

Local and global consequences of climate change (enhanced urban heat islands, worsening environmental conditions) affect most of the world's urban population, but only recently have cities been represented, albeit crudely, in weather forecast models. To manage and develop sustainable, resilient and healthy cities requires improved forecasting and observations that cross neighbourhood-influenced scales which the next generation weather forecast models need to resolve. ASSURE addresses the critical issue of which processes need to be parameterised, and which resolved, to capture urban heterogeneity in space and time. We will advance understanding to develop new approaches and parameterisations for larger-scale urban meteorological and dispersion models by combining the results of field observations, high-resolution numerical simulations and wind tunnel experiments. Field work and modelling will focus on Bristol, as its physical geography provides suitably high levels of complexity and allows whole-city approaches. With mid-sized cities being large sources of greenhouse gases, and where large numbers of people live, it is critical agencies can provide predictions of weather and climate variability across cities of this scale as they need this information to manage and provide their services. ASSURE will include idealised simulations and theoretical analyses to ensure generic applicability. The ASSURE objectives are: * To understand how sources of urban heterogeneity (physical setting, layout of buildings and neighbourhoods, human activities) combine to influence the urban atmosphere in space and time. * To quantify effects of urban heterogeneity at different scales (street to neighbourhood, to city and beyond) on flow, temperature, moisture and air quality controlling processes and to determine how these processes interact. * To develop a theoretical framework that captures key processes and feedbacks with reduced complexity to aid mesoscale and larger model parameterisations. * To inform the development priorities of current weather and climate models that have meso-scale capabilities and are used in decision-making processes (e.g. integrated urban services). The ASSURE high-fidelity simulations and carefully designed experiments will allow us to explore implications of urban heterogeneity in isolated and combined configurations; interpret and integrate field observations (e.g. 3D meteorological and city-scale tracer dispersion experiments); integrate different approaches to understand the magnitude, source, and geographical extent of uncertainties in process models at different scales; synthesize the new knowledge to conduct theoretical analyses; develop algorithms reflecting this analysis. Novel in ASSURE are simulations resolving street to city-scale features that are linked to mesoscale models; field observations capturing vertical and horizontal variations in the urban boundary- and canopy-layers, including novel multi-source gas tracer experiments; and wind tunnel simulations across atmospheric stabilities and model resolution. New insights will be gained on the role of variations in the building morphology (or form), local topography, and human activities (e.g. waste heat, and AQ emissions). ASSURE will produce detailed datasets; in-depth understanding across the scale of atmospheric processes involved; high-fidelity multiscale urban modelling tools; theoretical models taking account of multiscale effects; improved assessment of current meso-scale model skill and the data used by practitioners to explore future urban scenarios as city form and function change. We will work with local and international organisations and companies to ensure the project benefits a broad range of society. They include: Avon Longitudinal Study of Parents and Children, CERC, COWI, ECMWF, Met Office, Delft University of Technology, Stanford University, University Hannover, RWDI, Surrey Sensors and UKCRIC.

The role of external drivers of climate change in mid-latitude weather events, particularly that of human influence on climate, arouses intense scientific, policy and public interest. In February 2014, the UK Prime Minister stated he "suspected a link" between the flooding at the time and anthropogenic climate change, but the scientific community was, and remains, frustratingly unable to provide a more quantitative assessment. Quantifying the role of climate change in extreme weather events has financial significance as well: at present, impact-relevant climate change will be primarily felt through changes in extreme events. While slow-onset processes can exacerbate (or ameliorate) the impact of individual weather events, any change in the probability of occurrence of these events themselves could overwhelm this effect. While this is known to be a problem, very little is known about the magnitude of such changes in occurrence probabilities, an important knowledge gap this project aims to address. The 2015 Paris Agreement of the UNFCCC has given renewed urgency to understanding relatively subtle changes in extreme weather through its call for research into the impacts of a 1.5oC versus 2oC increase in global temperatures, to contribute to an IPCC Special Report in 2018. Few, if any, mid-latitude weather events can be unambiguously attributed to external climate drivers in the sense that these events would not have happened at all without those drivers. Hence any comprehensive assessment of the cost of anthropogenic climate change and different levels of warming in the future must quantify the impact of changing risks of extreme weather, including subtle changes in the risks of relatively 'ordinary' events. The potential, and significance, of human influence on climate affecting the occupancy of the dynamical regimes that give rise to extreme weather in mid-latitudes has long been noted, but only recently have the first tentative reports of an attributable change in regime occupancy begun to emerge. A recent example is the 2014 floods in the Southern UK, which are thought to have occurred not because of individually heavy downpours, but because of a more persistent jet. Quantifying such changes presents a challenge because high atmospheric resolution is required for realistic simulation of the processes that give rise to weather regimes, while large ensembles are required to quantify subtle but potentially important changes in regime occupancy statistics and event frequency. Under this project we propose, for the first time, to apply a well-established large-ensemble methodology that allows explicit simulation of changing event probabilities to a global seasonal-forecast-resolution model. We aim to answer the following question: over Europe, does the dynamical response to human influence on climate, manifest through changing occupancy of circulation regimes and event frequency, exacerbate or counteract the thermodynamic response, which is primarily manifest through increased available moisture and energy in individual events? Our focus is on comparing present-day conditions with the counterfactual "world that might have been" without human influence on climate, and comparing 1.5 degree and 2 degree future scenarios. While higher forcing provides higher signal-to-noise, interpretation is complicated by changing drivers and the potential for a non-linear response. We compensate for a lower signal with unprecedentedly large ensembles. Event attribution has been recognised by the WCRP as a key component of any comprehensive package of climate services. NERC science has been instrumental in its development so far: this project will provide a long-overdue integration of attribution research into the broader agenda of understanding the dynamics of mid-latitude weather.

Trees in the Amazon are getting bigger absorbing large amounts of carbon dioxide from the atmosphere; equivalent to almost 10% of anthropogenic greenhouse gas emissions. This "carbon sink" slows the buildup of atmospheric carbon dioxide and therefore plays an important role in regulating climate change. At the moment we do not understand why the Amazon forest is behaving in this way. One potential reason is changes to the amount of tiny particles in the atmosphere called aerosols. We know that human activity has significantly changed the amount of aerosol over the Amazon: each dry season, humans start forest fires across southern parts of the Amazon basin (the so called "Arc of deforestation"). These fires emit large quantities of smoke aerosol into the atmosphere, scattering and absorbing radiation from the sun. This scattering of the sun's rays decreases the amount of direct radiation reaching the surface but increases the amount of diffuse radiation. It has been known for a long time that increases in diffuse radiation can increase plant productivity. For example, gardeners place "diffuser sheets" inside greenhouses that increase diffuse radiation in the similar way to atmospheric particles. The reason why diffuse radiation increases plant productivity is that it penetrates deeper into the canopy and illuminates leaves that would otherwise be in the shade. These previously shaded leaves can do more photosynthesis. A recent study showed that this effect can be very important, increasing the amount of carbon taken up by forests globally by 25%. It is therefore likely that deforestation fires (a major source of carbon dioxide emissions) are at least partly contributing to the sink of carbon dioxide in undisturbed forests in the Amazon basin. So far this effect has not been carefully studied for forests in the Amazon. Firstly, it is not well known exactly how much the amount of aerosol particles over the Amazon has changed. Second, no one has quantified how this change in aerosol particles has altered the amount of diffuse radiation. And finally we do not know whether these changes in diffuse radiation are sufficient to explain any of the observed changes in forest biomass across the Amazon. In this project we will use a suite of atmospheric aerosol, radiation and land-surface models to explore the problem. We will use a global model of atmospheric aerosol to simulate how aerosol distributions have changed over the Amazon over the last few decades. We will input these changes in aerosol into an atmospheric radiation model to quantify how amounts of diffuse radiation have changed. Finally, we will use these changes in diffuse radiation as input to a land-surface model to quantify how it impacts Amazon forests. At each step in the process we will use observations from ground-sites and satellite sensors to test how well the models explain observed changes. The project will lead to a much better understanding of how Amazon aerosol has changed and how this impacts diffuse radiation and the biosphere.

Biomass burning aerosol (BBA) exerts a considerable impact on climate by impacting regional radiation budgets as it significantly reflects and absorbs sunlight, and its cloud nucleating properties perturb cloud microphysics and hence affect cloud radiative properties, precipitation and cloud lifetime. However, BBA is a complex and poorly understood aerosol species as it consists of a complex cocktail of organic carbon and inorganic compounds mixed with black carbon and hence large uncertainties exist in both the aerosol-radiation-interactions and aerosol-cloud-interactions, uncertainties that limit the ability of our current climate models to accurately reconstruct past climate and predict future climate change. The African continent is the largest global source of BBA (around 50% of global emissions) which is transported offshore over the underlying semi-permanent cloud decks making the SE Atlantic a regional hotspot for BBA concentrations. While global climate models agree that this is a regional hotspot, their results diverge dramatically when attempting to assess aerosol-radiation-interactions and aerosol-cloud-interactions. Hence the area presents a very stringent test for climate models which need to capture not only the aerosol geographic, vertical, absorption and scattering properties, but also the cloud geographic distribution, vertical extent and cloud reflectance properties. Similarly, in order to capture the aerosol-cloud-interactions adequately, the susceptibility of the clouds in background conditions; aerosol activation processes; uncertainty about where and when BBA aerosol is entrained into the marine bundary layer and the impact of such entrainment on the microphysical and radiative properties of the cloud result in a large uncertainty. BBA overlying cloud also causes biases in satellite retrievals of cloud properties which can cause erroneous representation of stratocumulus cloud brightness; this has been shown to cause biases in other areas of the word such as biases in precipitation in Brazil via poorly understood global teleconnection processes. It is timely to address these challenges as both measurement methods and high resolution model capabilities have developed rapidly over the last few years and are now sufficiently advanced that the processes and properties of BBA can be sufficiently constrained. This measurement/high resolution model combination can be used to challenge the representation of aerosol-radiation-interaction and aerosol-cloud-interaction in coarser resolution numerical weather prediction (NWP) and climate models. Previous measurements in the region are limited to the basic measurements made during SAFARI-2000 when the advanced measurements needed for constraining the complex cloud-aerosol-radiation had not been developed and high resolution modelling was in its infancy. We are therefore proposing a major consortium programme, CLARIFY-2016, a consortium of 5 university partners and the UK Met Office, which will deliver a suite of ground and aircraft measurements to measure, understand, evaluate and improve: a) the physical, chemical, optical and radiative properties of BBAs b) the physical properties of stratocumulus clouds c) the representation of aerosol-radiation interactions in weather and climate models d) the representation of aerosol-cloud interactions across a range of model scales. The main field experiment will take place during September 2016, based in Walvis Bay, Namibia. The UK large research aircraft (FAAM) will be used to measure in-situ and remotely sensed aerosol and cloud and properties while advanced radiometers on board the aircraft will measure aerosol and cloud radiative impacts. While the proposal has been written on a stand-alone basis, we are closely collaborating and coordinating with both the NASA ORACLES programme (5 NASA centres, 8 USA universities) and NSF-funded ONFIRE programme (22 USA institutes).