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

Identifying and characterising large ramps in power output of offshore wind farms

Recently there has been a significant change in the distribution of wind farms in Great Britain with the construction of clusters of large offshore wind farms. These clusters can produce large ramping events (i.e. changes in power output) on temporal scales which are critical for managing the power system (30 minute, 60 minute and 4 hours). This study analyses generation data from the Thames Estuary cluster in conjunction with meteorological observations to determine the magnitude and frequency of ramping events and the meteorological mechanism. Over a 4 hour time window, the extreme ramping events of the Thames Estuary cluster were caused by the passage of a cyclone and associated weather fronts. On shorter time scales, the largest ramping events over 30 minute and 60 minute time windows are not associated with the passage of fronts. They are caused by three main meteorological mechanisms; (1) very high wind speeds associated with a cyclone causing turbine cut-out (2) gusts associated with thunderstorms and (3) organised band of convection following a front. Despite clustering offshore capacity, the addition of offshore wind farms has increased the mean separation between capacity and therefore reduced the variability in nationally aggregated generation on high frequency time scales

An optimal inverse method using Doppler lidar measurements to estimate the surface sensible heat flux

Inverse methods are widely used in various fields of atmospheric science. However, such methods are not commonly used within the boundary-layer community, where robust observations of surface fluxes are a particular concern. We present a new technique for deriving surface sensible heat fluxes from boundary-layer turbulence observations using an inverse method. Doppler lidar observations of vertical velocity variance are combined with two well-known mixed-layer scaling forward models for a convective boundary layer (CBL). The inverse method is validated using large-eddy simulations of a CBL with increasing wind speed. The majority of the estimated heat fluxes agree within error with the proscribed heat flux, across all wind speeds tested. The method is then applied to Doppler lidar data from the Chilbolton Observatory, UK. Heat fluxes are compared with those from a mast-mounted sonic anemometer. Errors in estimated heat fluxes are on average 18 %, an improvement on previous techniques. However, a significant negative bias is observed (on average −63%) that is more pronounced in the morning. Results are improved for the fully-developed CBL later in the day, which suggests that the bias is largely related to the choice of forward model, which is kept deliberately simple for this study. Overall, the inverse method provided reasonable flux estimates for the simple case of a CBL. Results shown here demonstrate that this method has promise in utilizing ground-based remote sensing to derive surface fluxes. Extension of the method is relatively straight-forward, and could include more complex forward models, or other measurements

Increasing thermal plant flexibility in a high renewables power system

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability. This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified

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

A wind-tunnel study of flow distortion at a meteorological sensor on top of the BT Tower, London, UK

High quality wind measurements in cities are needed for numerous applications including wind engineering. Such data-sets are rare and measurement platforms may not be optimal for meteorological observations. Two years' wind data were collected on the BT Tower, London, UK, showing an upward deflection on average for all wind directions. Wind tunnel simulations were performed to investigate flow distortion around two scale models of the Tower. Using a 1:160 scale model it was shown that the Tower causes a small deflection (ca. 0.5°) compared to the lattice on top on which the instruments were placed (ca. 0–4°). These deflections may have been underestimated due to wind tunnel blockage. Using a 1:40 model, the observed flow pattern was consistent with streamwise vortex pairs shed from the upstream lattice edge. Correction factors were derived for different wind directions and reduced deflection in the full-scale data-set by <3°. Instrumental tilt caused a sinusoidal variation in deflection of ca. 2°. The residual deflection (ca. 3°) was attributed to the Tower itself. Correction of the wind-speeds was small (average 1%) therefore it was deduced that flow distortion does not significantly affect the measured wind-speeds and the wind climate statistics are reliable

Assessing methods to extrapolate the vertical wind-speed profile from surface observations in a city centre during strong winds

Knowledge of the vertical wind-speed profile in cities is important for the construction and insurance industries, wind energy predictions, and simulations of pollutant and toxic gas release. Here, five methods to estimate the spatially- and temporally- averaged wind-speed profile are compared in London: the logarithmic wind law (LOG); the Deaves and Harris equilibrium (DHe) and non-equilibrium (DHv) models; an adaptation of the power law (PL) and the Gryning et al. (GR) profile. Using measurements at 2.5 times the average building height, a source area model is used to determine aerodynamic roughness parameters using two morphometric methods, which assume homogeneous and variable roughness-element heights, respectively. Hourly-averaged wind speeds are extrapolated to 200 m above the canopy during strong wind conditions, and compared to wind speeds observed with Doppler lidar. Wind speeds are consistently underestimated if roughness-element height variability is not considered during aerodynamic parameter determination. Considering height variability, the resulting estimations with the DHe and GR profiles are marginally more similar to observations than the DHv profile, which is more accurate than the LOG and PL methods. An exception is in directions with more homogeneous fetch and a gradual reduction in upwind roughness, where the LOG and PL profiles are more appropriate

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

The importance of forecasting regional wind power ramping: a case study for the UK

In recent years there has been a significant change in the distribution of wind farms in Great Britain, with a trend towards very large offshore farms clustered together in zones. However, there are concerns these clusters could produce large ramping events on time scales of less than 6 hours as local meteorological phenomena simultaneously impact the production of several farms. This paper presents generation data from the wind farms in the Thames Estuary (the largest cluster in the world) for 2014 and quantifies the high frequency power ramps. Based on a case study of a ramping event which occurred on 3rd November 2014, we show that due to the large capacity of the cluster, a localised ramp can have a significant impact on the cost of balancing the power system on a national level if it is not captured by the forecast of the system operator. The planned construction of larger offshore wind zones will exacerbate this problem. Consequently, there is a need for accurate regional wind power forecasts to minimise the costs of managing the system. This study shows that state-of-the-art high resolution forecast models have capacity to provide valuable information to mitigate this impact