Observations of the morning development of the urban boundary layer over London, UK, taken during the ACTUAL project

The study of the boundary layer can be most difficult when it is in transition and forced by a complex surface, such as an urban area. Here, a novel combination of ground-based remote sensing and in situ instrumentation in central London, UK, is deployed, aiming to capture the full evolution of the urban boundary layer (UBL) from night-time until the fully-developed convective phase. In contrast with the night-time stable boundary layer observed over rural areas, the night-time UBL is weakly convective. Therefore, a new approach for the detection of the morning-transition and rapid-growth phases is introduced, based on the sharp, quasi-linear increase of the mixing height. The urban morning-transition phase varied in duration between 0.5 and 4 h and the growth rate of the mixing layer during the rapid-growth phase had a strong positive relationship with the convective velocity scale, and a weaker, negative relationship with wind speed. Wind shear was found to be higher during the night-time and morning-transition phases than the rapid-growth phase and the shear production of turbulent kinetic energy near the mixing-layer top was around six times larger than surface shear production in summer, and around 1.5 times larger in winter. In summer under low winds, low-level jets dominated the UBL, and shear production was greater than buoyant production during the night-time and the morning-transition phase near the mixing-layer top. Within the rapid-growth phase, buoyant production dominated at the surface, but shear production dominated in the upper half of the UBL. These results imply that regional flows such as low-level jets play an important role alongside surface forcing in determining UBL structure and growth

Evaluating single-sided natural ventilation models against full-scale idealised measurements: impact of wind direction and turbulence

Commonly single-sided natural ventilation is used in temperate climates to provide comfortable and healthy indoor environments. However, within built-up areas it is difficult to predict natural ventilation rates for buildings as they depend on many flow factors and opening type. Here, existing models are evaluated using the nine-month Refresh Cube Campaign (RCC). Pressure-based ventilation rates were determined for a small opening (1% porosity) in a cubical test building (side=6 m). The building was isolated and then sheltered in a limited staggered building array to simulate turbulent flows in dense urban areas. Internal and external flow, temperature and pressure measurements captured a wide range of scales of variability. Although the Warren and Parkins (1985, WP85) model performed best for 30-minute mean ventilation rates, all four models tested underestimated ventilation rates by a factor of 10. As wind dominated the stack effect, new coefficients were derived for the WP85 wind-driven model as a function of wind angle. Predictions were mostly improved, except for directions with complex flow patterns during the sheltered case. For the first time, the relation between ventilation rate and turbulence intensity (TI) around a full-scale building was tested. Results indicate that the wind-driven model for single-sided ventilation in highly turbulent flows (0.5<TI<4) can be improved by including TI as a multiplicative factor. Although small window openings with highly turbulent flows are common for sheltered buildings in urban areas, future model development should include a variety of configurations to assess the generality of these results

A sodar for profiling in a spatially inhomogeneous urban environment

The urban boundary layer, above the canopy, is still poorly understood. One of the challenges is obtaining data by sampling more than a few meters above the rooftops, given the spatial and temporal inhomogeneities in both horizontal and vertical. Sodars are generally useful tools for ground-based remote sensing of winds and turbulence, but rely on horizontal homogeneity (as do lidars) in building up 3-component wind vectors from sampling three or more spatially separated volumes. The time taken for sound to travel to a typical range of 200 m and back is also a limitation. A sodar of radically different design is investigated, aimed at addressing these problems. It has a single vertical transmitted sound pulse. Doppler shifted signals are received from a number of volumes around the periphery of the transmitted beam with microphones which each having tight angular sensitivity at zenith angles slightly off-vertical. The spatial spread of sampled volumes is therefore smaller. By having more receiver microphones than a conventional sodar, the effect of smaller zenith angle is offset. More rapid profiling is also possible with a single vertical transmitted beam, instead of the usual multiple beams.A prototype design is described, together with initial field measurements. It is found that the beam forming using a single dish antenna and the drift of the sound pulse downwind both give rise to reduced performance compared with expectations. It is concluded that, while the new sodar works in principle, the compromises arising in the design mean that the expected advantages have not been realize

The impact of spin up and resolution on the representation of a clear convective boundary layer over London in order 100m grid-length versions of the Met Office Unified Model

With a number of operational centres looking forward to the possibilities of “city scale” NWP and climate modelling it is important to understand the behaviour of order 100m models over cities. A key issue is how to handle the representation of partially resolved turbulence in these models. In this paper we compare the representation of a clear convective boundary layer case in London in 100m and 50m grid-length versions of the Unified Model (MetUM) with observations. Comparison of Doppler lidar observations of the vertical velocity shows that convective overturning in the boundary layer is broadly well represented in terms of its depth and magnitude. The role of model resolution was investigated by comparing a 50m grid-length model with the 100m one. It is found that, although going to 50m grid-length does not greatly change many of the bulk properties (mixing height, heat flux profiles, etc.) the spatial structure of the overturning is significantly different. This is confirmed with spectral analysis which shows that the 50m model resolves significantly more of the energetic eddies, and a length scale analysis that shows the 50m and 100m models produce convective structures 2-3 times larger than observed. We conclude that, for the MetUM, model grid-lengths of order 100m may well be sufficient for predicting many bulk and statistical properties of convective boundary layers however the details of the spatial structures around convective overturning in these situations are likely to be still under-resolved. Spin up artefacts emanating from the inflow boundary of the model are investigated by comparing with a smaller 100m grid-length domain which is more dominated by such effects. These manifest themselves as along wind boundary layer rolls which produce a less realistic comparison with the lidar observations. A stability analysis is presented in order to better understand the formation of these rolls

Observations of urban boundary layer structure during a strong urban heat island event

It has long been known that the urban surface energy balance is different to that of a rural surface, and that heating of the urban surface after sunset gives rise to the Urban Heat Island (UHI). Less well known is how flow and turbulence structure above the urban surface are changed during different phases of the urban boundary layer (UBL). This paper presents new observations above both an urban and rural surface and investigates how much UBL structure deviates from classical behaviour. A 5-day, low wind, cloudless, high pressure period over London, UK, was chosen for analysis, during which there was a strong UHI. Boundary layer evolution for both sites was determined by the diurnal cycle in sensible heat flux, with an extended decay period of approximately 4 h for the convective UBL. This is referred to as the “Urban Convective Island” as the surrounding rural area was already stable at this time. Mixing height magnitude depended on the combination of regional temperature profiles and surface temperature. Given the daytime UHI intensity of 1.5∘C, combined with multiple inversions in the temperature profile, urban and rural mixing heights underwent opposite trends over the period, resulting in a factor of three height difference by the fifth day. Nocturnal jets undergoing inertial oscillations were observed aloft in the urban wind profile as soon as the rural boundary layer became stable: clear jet maxima over the urban surface only emerged once the UBL had become stable. This was due to mixing during the Urban Convective Island reducing shear. Analysis of turbulent moments (variance, skewness and kurtosis) showed “upside-down” boundary layer characteristics on some mornings during initial rapid growth of the convective UBL. During the “Urban Convective Island” phase, turbulence structure still resembled a classical convective boundary layer but with some influence from shear aloft, depending on jet strength. These results demonstrate that appropriate choice of Doppler lidar scan patterns can give detailed profiles of UBL flow. Insights drawn from the observations have implications for accuracy of boundary conditions when simulating urban flow and dispersion, as the UBL is clearly the result of processes driven not only by local surface conditions but also regional atmospheric structure

Volume for pollution dispersion: London’s atmospheric boundary layer during ClearfLo observed with two ground-based lidar types

In urban areas with high air pollution emissions, the boundary layer volume within which gases and particles are diluted is critical to air quality impacts. With advances in ground-based remote sensing technologies and data processing algorithms, observations of layers forming the atmospheric boundary layer (ABL) are becoming increasingly available at high temporal resolution. Here, mixing height (MH) estimates determined from turbulence measurements of Doppler lidars and aerosol derived mixed layer height (MLH) based on automatic lidar and ceilometer (ALC) observations within the centre of London are assessed. While MH uncertainty increases with shorter duration of vertical stare sampling within the Doppler lidar scan pattern, instrument-related noise of the ALC may result in large MLH errors due to the challenging task of layer attribution. However, when long time series are assessed most of the algorithm- and instrument-related uncertainties average out and therefore become less critical to overall climatological analyses. Systematic differences occur in nocturnal MH from two nearby (3-4 km) sites but MLH estimates at both sites generally agree with MH obtained at the denser urban setting. During daytime, most spatial variations in ABL structure induced by synoptic conditions or land cover heterogeneity at this scale do not exceed measurement uncertainty. Agreement between MH and MLH is clearly affected by ABL aerosol content and cloud 28 conditions. Discrepancies increase with cloud complexity. On average, MH rises ahead of MLH during the morning growth period and peaks earlier in the day. There is a faster afternoon decay of MLH so that MLH and MH converge again around sunset and often have similar nocturnal values. Results demonstrate that turbulence-derived MH and aerosol-derived MLH should not be used inter32 changeably for purposes of model evaluation, interpretation of surface air quality observations or 33 initialisation of chemical transport models

Ground-based aerosol optical depth trends at three high-altitude sites in Switzerland and Southern Germany from 1995–2010

Ground-based aerosol optical depth (AOD) climatologies at three high-altitude sites in Switzerland (Jungfraujoch and Davos) and Southern Germany (Hohenpeissenberg) are updated and re-calibrated for the period 1995 – 2010. In addition, AOD time-series are augmented with previously unreported data, and are homogenized for the first time. Trend analysis revealed weak AOD trends (λ = 500 nm) at Jungfraujoch (JFJ; +0.007 decade-1), Davos (DAV; +0.002 decade-1) and Hohenpeissenberg (HPB; -0.011 decade-1) where the JFJ and HPB trends were statistically significant at the 95% and 90% confidence levels. However, a linear trend for the JFJ 1995 – 2005 period was found to be more appropriate than for 1995 – 2010 due to the influence of stratospheric AOD which gave a trend -0.003 decade-1 (significant at 95% level). When correcting for a recently available stratospheric AOD time-series, accounting for Pinatubo (1991) and more recent volcanic eruptions, the 1995 – 2010 AOD trends decreased slightly at DAV and HPB but remained weak at +0.000 decade-1 and -0.013 decade-1 (significant at 95% level). The JFJ 1995 – 2005 AOD time-series similarly decreased to -0.003 decade-1 (significant at 95% level). We conclude that despite a more detailed re40 analysis of these three time-series, which have been extended by five years to the end of 2010, a significant decrease in AOD at these three high-altitude sites has still not been observed

Concept and methodology of characterising infrared radiative performance of urban trees using tree crown spectroscopy

Urban trees play an important role in cooling urban microclimates and regulating outdoor thermal comfort. To better understand their contribution to these processes, it is crucial to elucidate urban trees’ radiative thermal performance, especially in the infrared (IR) region (approximately 50% of solar radiation). Yet, owing to significant conceptual and methodological challenges, studies on the radiative performance of trees have mainly focused on individual leaves rather than crown-level characteristics. Here we applied a novel conceptual and methodological framework to characterise the crown-level IR radiative performance of 10 lime trees (Tilia cordata), a common urban tree in the UK and Europe. Our results show that reflected and transmitted solar energy from leaves is dominated (>70%) by IR radiation. At the leaf level, transmission and reflection spectra are similar between trees (differences typically 40% in IR region) were found between trees. These variations were largely due to crown structural differences (leaf number, density, angles), rather than leaf solar interaction character (leaf-level transmittance or reflectance, leaf colour). Crown transflectance measured from the four cardinal directions was significantly different in the IR region (maximum differences circa 30%), and changed substantially with solar time. Hence, a tree’s surroundings received very different, and time dependent, levels of solar IR radiation. These findings have significant implications for species selection and control of environmental stress factors in urban microclimates

30 minute averaged overview data from the Silsoe Refresh Cube Campaign (RCC)

All 30 minute averaged data taken during the Refresh Cube Campaign (RCC) at Silsoe using the 6 m^3 test structure at the site and eight other 6 m^3 straw cubes undertaken as part of the PhD work of Gough (2017) and forms the full-scale experiments of the REFRESH project. The data-set is split into two sections: an isolated cube and the array case with three different opening set-ups being undertaken for both array and isolated. The array was in place October 2014 to April 2015, and the cube was isolated from May 2015 to July 2015. Details of the experimental set-ups are available in publications. The data contained within this document are 30 minute averaged and quality controlled using code previously used for the ACTUAL project. The data set contains wind speeds, wind directions, internal and external temperatures, surface pressures, CO_2 concentrations and ventilation rates calculated from the pressure difference methods. Internal and external measurements are included for the flow

Machine Learning-driven EEG Analysis towards brain-controlled vehicle

Με τη ραγδαία ανάπτυξη της τεχνολογίας, ο ανθρώπινος εγκέφαλος και οι υπολογιστές μπορούν να συνεργαστούν με τη βοήθεια βιοηλεκτρονικών συσκευών που χρησιμοποιούν βιο-σήματα, τα οποία ανιχνεύονται από μια συγκεκριμένη κατηγορία αισθητήρων που ονομάζονται βιο-αισθητήρες. Ένας νέος τομέας έρευνας που σχετίζεται με τη μελέτη των βιο-σημάτων έχει επικεντρωθεί ιδιαίτερα στην τεχνολογία ελεγχόμενη από το μυαλό. Πιο συγκεκριμένα, ο άμεσος έλεγχος ενός οχήματος με χρήση εγκεφαλικών κυμάτων μπορεί να βοηθήσει τα άτομα με αναπηρίες να ανακτήσουν τις οδηγικές τους ικανότητες, καθώς και να προσφέρει μια νέα επιλογή για υγιή άτομα να χειριστούν ένα όχημα. Η παρούσα πτυχιακή εργασία περιγράφει ένα όχημα ελεγχόμενο με το μυαλό (BCV) που χρησιμοποιεί την τεχνολογία Brain Computer Interface (BCI) για να ερμηνεύσει δεδομένα Ηλεκτροεγκεφαλογραφίας (EEG), να χειριστεί μια συσκευή και να αξιολογήσει τα εγκεφαλικά κύματα, προκειμένου να παραμείνει όσο το δυνατόν πιο κοντά στην ανθρώπινη φύση. Το σύστημα, το οποίο βασίζεται σε τεχνικές Μηχανικής Μάθησης, περιλαμβάνει τα ακόλουθα χαρακτηριστικά: (α) Επεξεργασία δεδομένων EEG για την ανάπτυξη διαφόρων μεθόδων εξαγωγής χαρακτηριστικών (β) χρήση κατάλληλων μηχανισμών μείωσης των διαστάσεων των δεδομένων, οι οποίοι στοχεύουν στην εύρεση συσχετισμών στα δεδομένα με σκοπό την απομάκρυνση μη κρίσιμων πληροφορίων, (γ) εφαρμογή μεθόδων ταξινόμησης που είναι σε θέση να προβλέψουν τις επιθυμητές ετικέτες που σχετίζονται με την κίνηση (αριστερό χέρι, δεξί χέρι, και τα δύο πόδια, γλώσσα), (δ) αντιστοίχηση των προβλεπόμενων σχετικά με την οδήγηση ετικετών σε πραγματικές κινήσεις (στροφή αριστερά, στροφή δεξιά, αύξηση ταχύτητας, μείωση ταχύτητας) και (ε) ενσωμάτωση των καλύτερων μοντέλων, με τη χρήση της μεθόδου ψηφοφορίας, σε ένα τελικό σύστημα BCV.Due to the rapid development of technology, the Human Brain and Computers are interfered with by Bio-Electronic devices employing bio-signals, which are detected by a particular class of sensors called bio-sensors. A new emerging research, the study of bio-signals has focused particularly on mind-controlled technology. More specifically, directly controlling a vehicle using brain waves might assist people with impairments regain their driving abilities as well as offer a fresh option for healthy people to operate a vehicle. The current thesis describes a Brain Controlled Vehicle (BCV) that uses Brain Computer Interface (BCI) technology to interpret Electroencephalography (EEG) data, operate a device, and evaluate brain waves, in order to stay as close as possible to the human nature. The system, which is based on Machine Learning techniques, comprises the following features: (a) Processing of EEG data in order to perform various feature extraction methods; (b) make use of a proper dimensionality reduction method that will find correlations in the data and discard non-critical information; (c) implement classification methods that are able to predict the desired motion related labels (left hand, right hand, both feet, tongue); (d) map the predicted motion related labels into real motions (turn left, turn right, accelerate, slow down) and (e) integrate the best models, with the use of a voting method, into a final BCV system