Charting the Realms of Mesoscale Cloud Organisation using Unsupervised Learning

Quantifying the driving mechanisms and effect on Earth's energy budget, of mesoscale shallow cloud organisation, remains difficult. Partly because quantifying the atmosphere's organisational state through objective means remains challenging. We present the first map of the full continuum of convective organisation states by extracting the manifold within an unsupervised neural networks's internal representation. On the manifold distinct organisational regimes, defined in prior work, sit as waymarkers in this continuum. Composition of reanalysis and observations onto the manifold, shows wind-speed and water vapour concentration as key environmental characteristics varying with organisation. We show, for the first time, that mesoscale shallow cloud organisation produces $\pm 1.4\%$ variations in albedo in addition to variations from cloud-fraction changes alone. We further demonstrate how the manifold's continuum representation captures the temporal evolution of organisation. By enabling study of states and transitions in organisation (in simulations and observations) the presented technique paves the way for better representation of shallow clouds in simulations of Earth's future climate

Using high-resolution modelling to improve the parameterisation of convection in a climate model

In this work high-resolution numerical simulation (Large-Eddie Simulation, LES) has been used to study the characteristic factors causing and influencing the development of moist convective clouds. Through this work a 1D cloud-model was derived from first principles to represent the vertical profile of individual convective clouds. A microphysics framework was implemented to ensure identical behaviour in LES and cloud-model integration where the microphysical processes represented are numerically integrated using a novel adaptive step microphysics integration which uses the physical speed at which a process takes place to adjust the integration step size (in space and time). This work also introduces a simple representation of cloud-droplet formation which allows for super-saturation to exist in-cloud and through this provide more physical representation of the in-cloud state. Together with high-resolution simulation of isolated individual and interacting multiple clouds in environmental conditions leading to shallow convection, the 1D cloud-model was used to infer that the principal influence on moist convective clouds is the entrainment of air from a cloud’s immediate environment which is significantly different from the environmental mean state. This suggests that convection parameterisations must represent the influence of moist convective downdrafts to properly predict the vertical structure of convective clouds so as to correctly predict the cloud-top height and vertical transport. Finally it was found that cloud-base radius is not in itself adequate as a means of classification for defining cloud-types as clouds with the same cloud-base radius showed large variation (≈ 600m) in cloud-top height. Based on simulations of individual convective clouds it was found that 3D simulations are necessary to capture the full dynamic behaviour of convective clouds (2D axisymmetric simulations have too little entrainment) and that agreement with the 1D cloud-model could only be found when entrainment was diagnosed from simulation instead of being parameterised by the traditional Morton-Turner model and only for 2D axisymmetric simulations, suggesting that the 1D cloud-model will require further extension or the diagnosis of entrainment improved

leifdenby/synthetic-gravity-waves: v0.1.0

Initial releas

Text entry performance of state of the art unconstrained handwriting recognition: a longitudinal user study

We report on a longitudinal study of unconstrained handwriting recognition performance. After 250 minutes of practice, participants had a mean text entry rate of 24.1 wpm. For the first four hours of usage, entry and error rates of handwriting recognition are about the same as for a baseline QWERTY software keyboard. Our results reveal that unconstrained handwriting is faster than what was previously assumed in the text entry literature. Author Keywords Handwriting, handwriting recognition, software keyboar

Continuous recognition and visualization of pen strokes and touch-screen gestures

We present a technique that enables continuous recognition and visualization of pen strokes and touch-screen gestures. We describe an incremental recognition algorithm that provides probability distributions over template classes as a function of users ’ partial or complete stroke articulations. We show that this algorithm can predict users ’ intended template classes with high accuracy on several different datasets. We use the algorithm to design two new visualizations that reveal various aspects of the recognition process to users. We then demonstrate how these visualizations can help users to understand how the recognition process interprets their input and how interactions between different template classes affect recognition outcomes

EUREC⁴A

The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic - eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air-sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored - from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation - are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at 10.25326/165 , and a film documenting the campaign is provided as a video supplement.ISSN:1866-3516ISSN:1866-350