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In this study, the crosswind (wind component perpendicular to a path, U⊥) is measured by a scintillometer and estimated with Doppler lidar above the urban environment of Helsinki, Finland, for 15 days. The scintillometer allows acquisition of a path-averaged value of U⊥ (U⊥), while the lidar allows acquisition of path-resolved U⊥ (U⊥ (x), where x is the position along the path). The goal of this study is to evaluate the performance of scintillometer U⊥ estimates for conditions under which U⊥ (x) is variable. Two methods are applied to estimate U⊥ from the scintillometer signal: the cumulative-spectrum method (relies on scintillation spectra) and the look-up-table method (relies on time-lagged correlation functions). The values of U⊥ of both methods compare well with the lidar estimates, with root-mean-square deviations of 0.71 and 0.73 m s−1. This indicates that, given the data treatment applied in this study, both measurement technologies are able to obtain estimates of U⊥ in the complex urban environment. The detailed investigation of four cases indicates that the cumulative-spectrum method is less susceptible to a variable U⊥ (x) than the look-up-table method. However, the look-up-table method can be adjusted to improve its capabilities for estimating U⊥ under conditions under for which U⊥ (x) is variable.

Airflow along rivers might provide a key mechanism for ventilation in cities: important for air quality and thermal comfort. Airflow varies in space and time in the vicinity of rivers. Consequently, there is limited utility in point measurements. Ground-based remote sensing offers the opportunity to study 3D airflow in locations which are difficult to observe with conventional approaches. For three months in the winter and spring of 2011, the airflow above the River Thames in central London was observed using a scanning Doppler lidar, a scintillometer and sonic anemometers. First, an inter-comparison showed that lidar-derived mean wind-speed estimates compare almost as well to sonic anemometers (root-mean-square error (rmse) 0.65-0.68 m s− 1) as comparisons between sonic anemometers (0.35-0.73 m s− 1). Second, the lidar duo-beam operating strategy provided horizontal transects of wind vectors (comparison with scintillometer rmse 1.12-1.63 m s− 1) which revealed mean and turbulent airflow across the river and surrounds; in particular, channelled airflow along the river and changes in turbulence quantities consistent with the roughness changes between built and river environments. The results have important consequences for air quality and dispersion around urban rivers, especially given that many cities have high traffic rates on roads located on riverbanks.

Relative humidity (RH) measurements, as derived from wet-bulb and dry-bulb thermometers operated as a psychrometer within a thermometer screen, have limited accuracy because of natural ventilation variations. Standard RH calculations generally assume a fixed screen psychrometer coefficient, but this is too small during poor ventilation. By comparing a reference humidity probe—exposed within a screen containing a psychrometer—with wind-speed measurements under controlled conditions, a wind-speed correction for the screen psychrometer coefficient has been derived and applicable when 2-metre wind speeds fall below 3 ms–1. Applying this to hourly-averaged data reduced the mean moist RH bias of the psychrometer (over the reference probe) from 1.2% to 0.4%, and reduced the inter-quartile range of the RH differences from 2.0% to 0.8%. This correction is particularly amenable to automatic measurement systems.

The Finnish Meteorological Institute, in collaboration with the University of Helsinki, has established a new ground-based remote-sensing network in Finland. The network consists of five topographically, ecologically and climatically different sites distributed from southern to northern Finland. The main goal of the network is to monitor air pollution and boundary layer properties in near real time, with a Doppler lidar and ceilometer at each site. In addition to these operational tasks, two sites are members of the Aerosols, Clouds and Trace gases Research InfraStructure Network (ACTRIS); a Ka band cloud radar at Sodankylä will provide cloud retrievals within CloudNet, and a multi-wavelength Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended), in Kuopio provides optical and microphysical aerosol properties through EARLINET (the European Aerosol Research Lidar Network). Three C-band weather radars are located in the Helsinki metropolitan area and are deployed for operational and research applications. We performed two inter-comparison campaigns to investigate the Doppler lidar performance, compare the backscatter signal and wind profiles, and to optimize the lidar sensitivity through adjusting the telescope focus length and data-integration time to ensure sufficient signal-to-noise ratio (SNR) in low-aerosol-content environments. In terms of statistical characterization, the wind-profile comparison showed good agreement between different lidars. Initially, there was a discrepancy in the SNR and attenuated backscatter coefficient profiles which arose from an incorrectly reported telescope focus setting from one instrument, together with the need to calibrate. After diagnosing the true telescope focus length, calculating a new attenuated backscatter coefficient profile with the new telescope function and taking into account calibration, the resulting attenuated backscatter profiles all showed good agreement with each other. It was thought that harsh Finnish winters could pose problems, but, due to the built-in heating systems, low ambient temperatures had no, or only a minor, impact on the lidar operation – including scanning-head motion. However, accumulation of snow and ice on the lens has been observed, which can lead to the formation of a water/ice layer thus attenuating the signal inconsistently. Thus, care must be taken to ensure continuous snow removal.

Insects migrating at high altitude over southern Britain have been continuously monitored by automatically operating, vertical-looking radars over a period of several years. During some occasions in the summer months, the migrants were observed to form well-defined layer concentrations, typically at heights of 200–400 m, in the stable night-time atmosphere. Under these conditions, insects are likely to have control over their vertical movements and are selecting flight heights that are favourable for long-range migration. We therefore investigated the factors influencing the formation of these insect layers by comparing radar measurements of the vertical distribution of insect density with meteorological profiles generated by the UK Meteorological Office’s (UKMO) Unified Model (UM). Radar-derived measurements of mass and displacement speed, along with data from Rothamsted Insect Survey light traps, provided information on the identity of the migrants. We present here three case studies where noctuid and pyralid moths contributed substantially to the observed layers. The major meteorological factors influencing the layer concentrations appeared to be: (a) the altitude of the warmest air, (b) heights corresponding to temperature preferences or thresholds for sustained migration and, (c) on nights when air temperatures are relatively high, wind-speed maxima associated with the nocturnal jet. Back-trajectories indicated that layer duration may have been determined by the distance to the coast. Overall, the unique combination of meteorological data from the UM and insect data from entomological radar described here show considerable promise for systematic studies of high-altitude insect layering.

Radar has been applied to the study of insect migration for almost 40 years, but most entomological radars operate at X-band (9.4 GHz, 3.2 cm wavelength), and can only detect individuals of relatively large species, such as migratory gras shoppers and noctuid moths, over all of their flight altitudes. Many insec ts (including economically important species) are much smaller than this, but development of the requisite higher power and/or higher frequency radar systems to detect these species is often prohibitively expensive. In this paper, attention is focussed upon the uses of some recently-deployed meteorological sensing devices to investigate insect migratory flight behaviour, and especially its inter actions with boundary layer processes. Records were examined from the vertically-pointing 35 GHz 'Copernicus' and 94 GHz ' Galileo' cloud radars at Chilbolton (Hampshire, England) for 12 clo udless and convective occasions in summer 2003, and one of these occasions (13 July) is presented in detail. Insects were freque ntly found at heights above aerosol particles, which represent passiv e tracers, indicating active insect movement. It was found that insect flight above the convective boundary layer occurs most often during the morning. The maximum radar-reflectivity (an indicator of aerial insect biomass) was found to be positively correlated with maximum screen temperature. Copyright c 0000 Royal Meteorological Society