108 research outputs found
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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
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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
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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
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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
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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
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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
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Persistent cloud cover over mega-cities linked to surface heat release
Urban areas are a hotspot for the interactions between the built environment, its inhabitants, and weather. Unlike the impact of temperatures through the well-known urban heat island effect, urban effects on cloud formation remain unknown. In this study we show observational evidence of a systematic enhancement of cloud cover in the afternoon and evening over two large metropolitan areas in Europe (Paris and London). Long-term measurements in and around London show that during late-spring and summer, even though less moisture is available at the surface and the atmosphere is drier, low clouds can persist longer over the urban area as vertical mixing of the available moisture is maintained for a longer period of time, into the evening transition. Our findings show that urban impacts on weather extend beyond temperature effects. These prolonged clouds over the city might enhance the urban heat island via night-time radiative forcing
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