The substorm is a repeatable earthquake-like disturbance to near-Earth Space, which, apparently unpredictably, recurs after anything from 2 hours to a day or more and dumps typically one thousand million million Joules of energy into the upper atmosphere equivalent to ten Oklahoma tornados or the largest nuclear weapon in the US arsenal. The substorm's intermittency and variable size makes it arguably the greatest source of uncertainty in predicting the state of the upper atmosphere. Its most obvious effect is the aurora, which would be nice to know when its happening so that we could plan our Arctic holidays, but substorm prediction is also important for mitigating the effects of natural changes in the upper atmosphere on geostationary satellite communications and navigation, low-altitude satellite orbits and remote sensing, electricity power grids, and oil and mineral prospecting. Prediction is also the ultimate test for our scientific understanding. Progress requires measuring and analysing substorm variability in order to test and develop models based on maths and physics. We already know the statistics of substorm timing and have explained this with a simple mathematical model (that has also been used for understanding neuron firing in the brain!). However, knowing and understanding the variability of substorm size is much harder because it requires to measure simultaneously over large regions of the polar upper atmosphere and out into Space. In this project, we propose to attempt this by examining lots of substorms over more than a decade using spacecraft together with networks of magnetometers (sophisticated scientific compasses) and radars in both the Arctic and Antarctic. The resulting stats will be compared with what we already know from much more limited observations and with the predictions of new and existing substorm theories and models. The outcomes will be knowing things like how likely a really big substorm is that could mess things up, as well as models to explain why and hopefully when that might occur.

Background: The Problem With the current state of the art, it is possible to limit the access privileges of a third-party program running on a computer system. The addition of architectural capabilities such as provided by CHERI enable unprecedented fine-grained memory protection and isolation. These mechanisms are however not sufficient to control the behaviour of a program so that it follows the intended specification. For example, if a program performs network access, it is not possible to ensure that the network location accessed is intended by the developer, or the result of a backdoor in the system. In general, this is the case for any system call performed by the program. As a result, malicious programs can e.g. participate in DDoS attacks, or send information about the system to a Command and Control server, etc. It is also the case for library calls, which could perform unspecified actions within the memory space of a process. Project Aim The aim of this project is to enhance the provision of Digital Security By Design for mission-critical Systems-on-Chip through Capability hardware-enabled Design-by-Specification. What this means is that the Systems-on-Chip has a formal, executable specification (typically created by the system architect), and every software component of the SoC is forced to adhere to this specification. Programs with incompatible specifications cannot run; unspecified run-time behaviour will raise an exception. For the above example, the specification could govern the network access and also the access to system information. The practical realisation of this aim is through the extension of programming languages to supports expressive specifications and a toolchain which ensures that the specifications are enforced at run time on Capability hardware. Key Ideas in a Nutshell Our vision of how to achieve this goal is through the use of behavioural type systems, i.e. the specification of the SoC and each of its individual components are expressed as a type, which effectively and formally describes the allowed interfaces and interactions of each component. This type-based specification will be an integral component of the program executable, and be validated against an overall system specification by the operating system. This proposal focuses on software components, and will build on the capability hardware for enforcement of the type-based specifications. The type-based Design-by-Specification of hardware components is the topic of the EPSRC Border Patrol project (EP/N028201/1), which will run until 2023 and therefore present great potential for synergies with the current proposal. Prior Work In our current EPSRC project Border Patrol (EP/N028201/1) we investigate digital security by design for the design of hardware IP-core based SoCs. The key mechanism is the use of type-driven design-by-specification. A design's specification is encoded in the type system, so that the implementation must follow the specification. Adherence to the spec can be enforced at design time for trusted modules, and at run time for untrusted modules by patrolling the untrusted module's borders with FSM-based run-time type checkers.

Single-photon detection is the ability to capture the single quantum of light and is rapidly emerging as the critical capability for numerous emerging quantum technologies, as well as a range of new low-light sensing applications. This International Centre-to-Centre Collaboration proposal links three centres of excellence in quantum photonics to produce a collaboration designed to yield sustained world-class research in the field by combining their complementary expertise. The teams at the Jet Propulsion Laboratory (JPL) working with academic partners at the California Institute of Technology (Caltech) have made significant advances in the field of superconducting nanowire optical detectors in recent years, providing world-class temporal performance (> 5 times better than previously) and the largest format detector arrays yet demonstrated. The link to Heriot-Watt University offers a unique opportunity to use these state-of-the-art detectors in emerging quantum technology application areas such as single-photon and quantum-enhanced LIDAR, free-space and satellite-based quantum communications and in the use of quantum entanglement in ultra-high dimensional quantum imaging and communications. This EPSRC International Centre-to-Centre Collaboration affords a rare opportunity to enhance several world-leading research strands at Heriot-Watt, and make a significant, complementary and sustained contribution to major UK collaborative research initiatives, particularly the EPSRC SPEXS Programme Grant and the EPSRC Quantum Technology Hub network, strongly in line with UK research priorities.

IPCC stresses that limiting warming to 1.5 oC requires "reaching net zero CO2 emission globally around 2050". Aviation is one of the most important economic sectors, and is expected to steadily grow by 4-5% per year. If aviation emissions growth is unmitigated, it could contribute 4-15% of emission budget in 2050 for a 2 oC target. UK has committed to Jet-Zero by decarbonizing aviation until 2050, however, aviation's climate warming and uncertainty are both dominated (> 50%) by contrail cirrus. Therefore, it is vital to "quantify and reduce aviation contrail radiative forcing (QR-CODE)". This will enable the design of mitigation strategies via trade-offs: reduce large non-CO2 warming but with a subtle increase in CO2 emissions, such as flights diversion to avoid contrails. Contrails, or condensation trails, are cirrus clouds created by aircraft when flying through cold and humid regions. Fresh contrails are line-shaped and usually short-lived in dry ambient air; but under humid and cold conditions, contrails can persist for up to tens of hours and spread out as contrail cirrus (CC) covering up to thousands of km2. These contrail and CC can reflect shortwave sunlight back to space (cooling), but also trap longwave terrestrial radiation as CO2 does (warming). The net forcing of aviation cirrus (including contrail and CC) has been assessed to be the largest component of aviation-induced warming forcing but also with the largest uncertainty. One key challenge is the lack of observational evidence to constrain and improve aviation-induced cirrus prediction in numerical models, particularly because CC often merges with natural cirrus making it indistinguishable neither to quantify the associated radiative forcing. Recent developments mean that the lack of constraints are now changing, it is timely and ripe to overcome the challenge and achieve QR-CODE ambitions. The developments include: 1) The COVID global lockdown grounded more than 80% flights, which provides unprecedented large-scale natural experiments for deriving aviation fingerprints on cirrus. 2) The availability of 20+ years continuous observations of cirrus clouds from satellites enables advance application of machine-learning to develop natural experiments for disentangling aviation fingerprints. 3) The recent advance in computer vision enables automatic detection of line-shaped young contrails from satellite images during 2001-2022, which was almost an impossible task using manual techniques. Google led a recent innovation in applying computer vision in successful detecting line-shaped contrails from satellite images (similar to ship-tracks in liquid-clouds). Another our recent innovation in applying machine-learning to develop natural experiments has demonstrated its fidelity in unambiguously quantifying aerosol fingerprints on different types of natural clouds and the associated radiative forcing. These natural experiments use long-term satellite observations-based machine-learning to predict how clouds would look if they were unperturbed under the same meteorology, and therefore enabling discerning the fingerprints of large perturbations (including aviation during COVID) on cirrus (similar to liquid-clouds impacted by plumes, e.g., ship emission to marine boundary-layer clouds). QR-CODE will further develop and apply the above two modern innovations to aviation line-shaped contrails and CC to generate the first ever large ensemble of observation-based constraints for developing aviation cirrus predictors (Theme 1.3). This will allow us to improve aviation cirrus prediction and quantify its climate effects (Theme 1.1), hence enabling the optimization and implement of trade-off mitigation strategies via contrail avoidance through the Met Office Civil Aviation Authority to support the UK Jet Zero strategy (Themes 2.1-2.3).

The Earth's climate sensitivity / how much it warms as greenhouses gases increase, is arguably the most important 'unknown' in predictions of climate change. Models give a range of approximately 1.5 - 4.5 K for the increase in equilibrium global mean temperature expected when carbon dioxide is doubled. Recently scientists have attempted to use combinations of observations and models to constrain this range / but if anything the range has increased. Uncertainties, mainly in the cloud feedback but also in other feedbacks such as water vapour and ice, account for these large differences between the climate models. These climate feedbacks act to either amplify or reduce the initial effects of the climate change mechanism. Water vapour is the largest positive feedback and acting alone is believed to increase by an amount which roughly doubles the effectiveness of the initial greenhouse gas perturbation. Prime objective: - To evaluate the four main feedback terms in the climate system using observed varaibles. The feedbacks evaluated will be 1) water vapour, 2) clouds (specifically cloud amount, cloud height and cloud optical depth), 3) lapse-rate and 4) surface albedo. A variety of global-scale observations will be combined from many sources and these will be incorporated into offline radiative transfer calculations to gauge the role of these feedbacks in modifying the global energy balance. Uncertainty assessment: - Both the proposed methodology and other more conventional methodologies of calculating climate feedbacks will be assessed in climate model simulations from project partners at the Hadley Centre. These feedback calculations with their model output will be of direct benefit to the Centre who to date have not calculated these feedback terms within their model. These model and data comparisons will be used to: test and assess assumptions used in the proposed methodology, and to quantify realistic uncertainties for each of the feedback terms. - A parallel energy budget calculation by project partners at the NASA Goddard Institute for Space Studies (GISS) will also be used to gauge uncertainty estimates from our analyses. Secondary objectives: - The second aim of the project employs similar methodologies to those of the prime aim to analyse feedbacks on both shorter timescales and on regional scales, and will also analyse feedbacks for different regimes. This work will be used to design diagnostic tests of feedback mechanisms in climate models. Here we will make use of the regime analysis of feedbacks already undertaken by the Hadley Centre. - The third aim of the study is to test the linear model of climate feedbacks: here we will use two different methodologies to evaluate the linear and non linear components of these feeback terms, testing assumptions of non-linearity. Additional output: - We will produce a synthetic dataset of the top-of-atmosphere fluxes, which we will make available to the wider community for their own model evaluation exercises. In summary the project will attempt to quantify some of the largest 'unknowns' in our predictions of global climate change. It will also develop diagnostic tests for feedback analysis in climate models. Overall it will lead to better and more trustworthy climate model predictions, which would not only be of great benefit to the climate modelling community, it would also benefit policy makers who need to rely on the accuracy of such climate model predictions.