This project will result in methods to detect boreal recruitment failure (RF) due to fire, an explanatory model of RF, and quantification of climate feedbacks from RF that are not currently accounted for in any climate or vegetation model. The associated data collection and research outputs will benefit models of climate-fire-vegetation feedbacks. Presently all models that incorporate fire disturbance assume forest recovery. Research Questions 1. When and where does boreal RF occur? 2. What are the factors that cause boreal RF? 3. What climate feedbacks are likely to result from boreal RF? Forest loss due to the failure of new trees to survive (recruitment failure) post-fire occurs in boreal forests in Eurasia and North America. The existence of ecological thresholds, or "tipping points" that cause abrupt ecological shifts, is well-known in ecosystems theory but where and when ecosystems are approaching such dramatic changes is difficult to predict. One such extreme ecological shift has been observed in boreal forests that fail to recover after multiple fires within a short time interval (< 10 years). These areas are dominated by grass and are similar to steppe vegetation. Transition from forest to steppe is consistent with predicted changes in vegetation composition in response to regional climate change, and is consistent with global observations of forest loss in response to climate. Preliminary analyses of these sites indicate causes related to changing fire regimes effected by climate. Firstly, although vegetation indices have been used to identify forest loss, there is currently no method to detect RF using remotely sensed data. We address here the likelihood that RF produces a unique signature that can be detected remotely. The total area affected by RF in Eurasia and North America is at present unknown. Using RF locations provided by the Sukachev Institute (see letter of support), we have developed preliminary methods to differentiate between successfully recovery from fire and RF using remotely-sensed vegetation indices. The proposed research would refine these methods and develop an automated approach to detect RF. The lengthening satellite data record permits a new focus on the impact of climate change on boreal forests (the largest terrestrial biome) and its potential consequences. Remotely sensed imagery to date have yielded "snapshots" of ecosystems and disturbance events. With more than a decade of daily imagery from the MODIS sensors, we can begin to monitor processes like disturbance-recovery cycles. This new focus is critically important to the study of climate-ecosystem interactions and climatic "tipping points". Secondly, the causes of RF have not been identified. RF has been observed in areas of Siberia where the length of time between fire disturbances was extremely low. Initial field observations of RF sites indicate that high soil temperature and low moisture create a seedbed unsuitable for recruitment of trees following a fire. Additional field data will provide the inputs for an explanatory model of RF that includes characteristics of the fire (such as intensity and fire weather), pre-fire vegetation (e.g., stand age and density), and post-fire environment (e.g., soil temperature and moisture). Thirdly, the effect of RF on carbon, water and energy fluxes that impact climate has not been quantified. The replacement of forests with steppe vegetation results in carbon losses to the atmosphere from combustion and post-fire decomposition. The net climate impact of RF is presently unknown. Albedo is initially low following a fire and then may become higher due to the higher albedo of replacement vegetation. Changes in evapotranspiration rates affect latent and sensible heat fluxes. The area of RF is likely to grow in response to increasing fire frequency and severity, but the dynamics of recovery from wildfire and RF have not been incorporated into any coupled climate-vegetation models.

An eruption of Fuego volcano, Guatemala, on 3rd June 2018, had tragic outcomes when an entire village was inundated by pyroclastic flows. The eruption has prompted evacuations of around 12,000 people. This event resulted in changes to hazard, exposure and vulnerability, demonstrating the complex and dynamic nature of ongoing and future risk. This proposal seeks to characterise this dynamic risk observed in the natural environment, and understand the interactions between dynamic risk and society. Following the 3rd June eruption of Fuego, evacuations have resulted in reduced exposure in some regions, however, vulnerability (physical, systemic, functional, social, economic and political) remains high and is a key component of the evolving risk. In particular, systemic and functional vulnerability are believed to be highly dynamic. This provides an opportunity to investigate how the evolving hazard situation at Fuego, combined with changes in exposure and highly dynamic systemic and functional vulnerability, play out to affect risk in a context where both recovery and continued eruption risk management are ongoing. This opportunity is urgent: we must characterise changing hazard, exposure and vulnerability through time. Although the nature of the hazard can be investigated retrospectively, documenting changes to exposure (evacuations and reoccupations) and vulnerability as they respond to changing hazard and socio-economic conditions needs to be done as it occurs. For example, it is important to document physical vulnerability on buildings already impacted by the pyroclastic flows before further damage by weather or heavy machinery occurs, or document road closures next to affected drainages which can constitute a major element of the systemic vulnerability to lahars or pyroclastic flows of a community isolated by that road closure. Information on systemic vulnerability at this level of granularity is not normally documented in Guatemala, thus will not be available for later study. Through this proposed work, we will collect an unprecedented dataset on vulnerability, documenting physical vulnerability of buildings impacted by pyroclastic flows before any further damage. When considering risk to life by volcanic flow hazards and lahars however, physical vulnerability of infrastructure can be reduced to a binary effect (impacted or not. It is actually systemic and functional vulnerability that are the more important, and harder to ascertain, unknowns. A key research component, therefore, is to test the hypothesis that for volcanic flow related hazards, in contrast to tephra hazards, it is widespread systemic vulnerability and not physical vulnerability of the footprint of potential impact that is the root cause of risk. This is important because much of the work currently undertaken on risk in volcanology is led by frameworks used for tephra fall hazards, yet flow impacts and risk are very different. The project is will-aligned with the UN Sendai Framework for Disaster Risk Reduction, as well as recent initiatives in the wider volcanology community to engage and improve our capacity to do risk well. We will use a combination of volcanology field approaches, forensic approaches, and interviews to gather the information.

Tropical forests play a critical role in global water, carbon and nutrient cycles, and currently absorb billions of tonnes of carbon, thus reducing rates of climate change. For this reason, computer models that are used to predict future climate change and the impacts of climate on plants and ecosystems, need to be able to represent tropical forest very well. In fact, the response of tropical forests to changes in temperature is one of the greatest uncertainties in climate change prediction. However, currently, scientists do not understand how these forests will respond to increasing temperatures. This is worrying because temperatures are increasing faster today than in the past, forcing forests to respond to unprecedented rates of warming. Critically, the lack of seasonal changes in temperature may mean that trees growing in these regions have a reduced capacity to deal with rapid climate change compared with more temperate and high-latitude species. If this is the case, then global warming may represent a considerable threat to these forests, the amazing amounts of biodiversity that they contain, and their role in reducing current rates of climate change. However, this suggestion is yet to be tested formally. The lack of understanding is even more worrying for tropical forest growing in mountains, as in these areas temperatures are increasing faster than in the lowlands. For example, scientists studying Andean forest in Colombia and Peru have observed that some tree species native to high elevations are dying out while others are moving to higher elevations. These scientists have suggested that these observations may be explained by the fact that trees are already seeing the impacts of climate change and are not able to withstand current temperatures. However, this explanation remains controversial and has not been tested formally. The major goal of this project is to determine if tropical Andean species can tolerate current temperatures and adjust to withstand the higher temperatures expected for the future. To answer this question, we will plant trees from high elevations in the Colombian Andes in their home environment but also at two lower elevations where temperatures are 5oC and 9oC higher, respectively. Our trees will be all planted in common soils and will have access to plenty of water, eliminating potential differences in water and nutrient access. We will monitor photosynthesis, respiration and growth at the three locations in other to understand how they respond to temperature. Compared to other experiments, our study is unique as it will: i) be the first to investigate the ability of large 3 - 4m tall trees planted in a common soil to respond to long-term (3 year) changes in temperature, ii) investigate a much greater number of species than all other field studies on this subject, and iii) measure a more complete set of key physiological and growth responses than in any other experiment. The measurements taken will be used to the derive mathematical equations that can represent the response of these tree montane species to elevated temperatures. Furthermore, to predict the response of tropical forest everywhere in the world to higher temperatures, we need data from high and low elevations in as many locations as possible. Scientists around the world are now starting to collect some of these measurements in forests from Costa Rica, Puerto Rico, Panama, Brazil, Peru, Rwanda and Australia. Although, no one of these investigations is as detailed as our study, by teaming up with all these groups we can use their data to test and extrapolate our equations across all tropics globally. We will then introduce these mathematical equations into a computer model to predict future behavior of the tropical forest under warming conditions. The outcome will represent a step change in our ability to accurately predict how this critically important biome will respond to global warming.

Anthropogenic emissions that affect climate are not just confined to greenhouse gases. Sulfur dioxide (SO2) and other pollutants form atmospheric aerosols that scatter and absorb sunlight, and influence the properties of clouds, modulating the Earth-atmosphere energy balance. Anthropogenic emissions of aerosols exert a significant, but poorly quantified, cooling of climate that acts to counterbalance the global warming from anthropogenic emissions of greenhouse gases. Uncertainties in aerosol-climate impacts are dominated by uncertainties in aerosol-cloud interactions (ACI) which operates through aerosols acting as cloud-condensation nuclei (CCN) which increases the cloud droplet number concentration (CDNC) while reducing the size of cloud droplets and subsequently impact rain formation which may change the overall physical properties of clouds. This consequently impacts the uncertainty in climate sensitivity (the climate response per unit climate forcing) because climate models with a strong/weak aerosol cooling effect and a high/low climate sensitivity respectively are both able to represent the historic record of global mean temperatures. On a global mean basis, the most significant anthropogenic aerosol by mass and number is sulphate aerosol resulting from the ~100Tg per year emissions of sulphur dioxide from burning of fossil fuels, but these plumes are emitted quasi-continuously owing to the nature of industrial processes, meaning that there is no simple 'control' state of the climate where sulphur dioxide is not present. On/off perturbation/control observations have, to date, been limited to observations of ship tracks but the spatial scales of such features are far less than the resolution of the weather forecast models or of the climate models that are used in future climate projections. This situation changed dramatically in 2014 with the occurrence of the huge fissure eruption at Holuhraun in 2014-2015 in Iceland, which was the largest effusive degassing event from Iceland since the eruption of Laki in 1783-17849. The eruption at Holuhraun emitted sulphur dioxide at a peak rate of up to 1/3 of global emissions, creating a massive plume of sulphur dioxide and sulphate aerosols across the entire North Atlantic. In effect, Iceland became a significant global/regional pollution source in an otherwise unpolluted environment where clouds should be most susceptible to aerosol emissions. Thus, the eruption at Holuhraun created an excellent analogy for studying the impacts of anthropogenic emissions of sulphur dioxide and the resulting sulphate aerosol on ACI. Our research will comprehensively evaluate impacts of the Holuhraun aerosol plume on clouds, precipitation, the energy balance, and key weather and climate variables. Observational analysis will be extended beyond that of our pilot study to include high quality surface sites. Two different climate models will be used; HadGEM3, which is the most up to date version of the Met Office Unified model and ECHAM6-HAM, developed by MPI Hamburg. These models are chosen because they produce radically different responses in terms of ACI; ECHAM6-HAM produces far stronger ACI impacts overall than HadGEM3. Additionally, the UK Met Office Unified Model framework means that the underlying physics is essentially identical in low-resolution climate models and high-resolution numerical weather predication models, a feature that is unique in weather/climate research. In the high resolution numerical weather prediction version, parameterisations of convection can be turned off and sub-gridscale processes can be explicitly represented. Thus the impacts of choices of parameterisation schemes and discrete values of variables within the schemes may be evaluated. The research promises new insights into ACI and climate sensitivity promising us great strides improving weather and climate models and simulations of the future.

The 2010 Eyjafjallajökull and 2011 Grimsvötn eruptions in Iceland were stark reminders that society is increasingly vulnerable to volcanic hazards. Since 2012, volcanic eruptions are listed in the UK National Risk Register for Civil Emergencies, recognising the high potential for societal disruption and economic loss. Volcano observatories and regulatory bodies, including the nine Volcanic Ash Advisory Centres (VAACs), use a variety of tools and data to mitigate the impacts of eruptions, and ensure aviation safety. Some of the most important tools are atmospheric models that simulate the atmospheric transport and removal of volcanic plume constituents and form the backbone of the regulatory response. The accuracy of these model predictions relies on: i) accurate input data, mainly derived from ground-based measurements and satellites; ii) the accuracy of the model representation of volcanic plume transport and plume processes. The overarching aims of V-PLUS are to transform our understanding of volcanic plumes and deliver methods and tools that enhance monitoring and forecasting capabilities in the UK and beyond. Our project partners and subcontractor include the Icelandic Met Office, the UK Met Office and Etna volcano observatory, which ensures that our new research breakthroughs will be used operationally by VAACs and volcano observatories. This will enhance our capabilities to mitigate the economic and societal hazards posed by volcanic eruptions. To achieve our aims, V-PLUS will exploit data from a recently launched satellite sensor called TROPOspheric Monitoring Instrument (TROPOMI). The exceptional spectral and spatial resolution of TROPOMI, 12 times better than the previous generation of instruments, is for the first time comparable to ground-based measurements, and will be a game-changer in volcanology, providing an unprecedented opportunity to characterise and track volcanic plumes. V-PLUS will combine this new data with ground-based and other satellite data, as well as atmospheric modelling to study volcanic plumes with unprecedented fidelity. To improve our ability to measure volcanic ash from satellite imagery we will conduct experiments on volcanoes, directly sampling volcanic ash during volcanic explosions using unmanned aerial vehicles, and test numerical models of volcanic activity. Aside from volcanic ash hazards, toxic volcanic sulphur species can degrade air quality, negatively affect human health, and potentially increase the cost of ownership of aircraft engines due to an increase in maintenance cycles. However, there is at present extremely limited knowledge of exposure thresholds and durations at which negative human health effects occur and the functioning of aircraft engines is compromised. While none of the VAACs are currently required to forecast the dispersion of volcanic sulphur, there is increasing recognition of the potential hazards from volcanic gases and their chemical conversion products. Thus, the requirement for VAACs could change in future. The chemical evolution of gases and aerosol particles controls the health and climatic impact of eruptions, and we will study this chemical evolution through experiments in accessible volcanic gas plumes. In summary, the new atmospheric models and tools created by the V-PLUS will be rigorously tested using case study eruptions and translated into tools for direct use by VAACs and volcano observatories. Therefore, the V-PLUS project will have societal and economic benefits primarily through creating enhanced national and international capability to predict the dispersion of volcanic ash and gas plumes including their impacts on air quality, human health, climate and aviation.