基于菲索干涉仪的边界层测风激光雷达研究

分析了多光束菲索(Fizeau)干涉仪的光学特性，以及影响干涉光谱性能的参数，并研究了激光雷达系统接收信号能力，提出了一套基于Fizeau干涉仪和CCD探测器的边界层测风激光雷达系统。利用标准大气参数和切合实际的激光雷达系统参数，对干涉仪进行优化设计模拟计算，得到了合理的参数，满足边界层1m／s风速测量精度要求。

车载直接探测多普勒测风激光雷达光学鉴频器

基于建立的车载直接探测激光雷达系统，对接收光学鉴频器进行了研究。针对边界层、对流层和平流层不同的气溶胶和大气分子浓度以及风速动态范围，同时采用直接探测的两种主要技术。利用多光束菲索（Fizeau）干涉仪（MFI）和阵列光电倍增管（PMT），接收气溶胶散射信号，获得边界层风速。采用双法布里-珀罗（Fabry-Perot）干涉仪（DFP）和光电倍增管探测器，分析分子散射信号，得到对流层风场。使用实际的激光雷达系统参数和大气模型参数，对两个鉴频器进行了优化设计，分析了它们的风速测量灵敏度和精度。多光束菲索干涉仪

光谱稳定性对直接探测多普勒测风激光雷达的影响研究

The wind error of the double-edge technique Doppler lidar due to the instability of injection-seeding solid laser and the drift of interferometer s spectrum was analyzed. Corresponding numerical simulation indicated that if the wind error of 1 m/s was achieved, the unsuccessful injection-seeding pulses should be less than 0.06% in integration time of 5 min. (30000 pulses). In the respect of spectrum drift of the interferometer, double temperature control systems were used and the accuracy of minus or plus 0.002°C was obtained, corresponding to the wind error of minus or plus 0.226 m/s. Monitoring of buildup time of the injection-seeding laser and temperature of the interferometer was significantly to improve the invertion accuracy of wind error by rejecting the data with frequency jumping and drifting. Researches of injection-seeding and spectrum stability of the interferometer were practical for the development of double-edge wind lidar.}

用于多普勒测风雷达的单频全固态激光器稳频

采用Pound-Drever-Hall技术，对用于多普勒测风雷达的种子注入激光器的主动激光器进行稳频，将其频率锁定在一个特殊设计的法珀腔上。该法珀腔总体采用零膨胀微晶玻璃材料制成，具有极高的温度稳定性。使用计算机采集鉴频信号并且进行处理。锁定后，1秒内激光器的相对频率漂移为±25kHz，一小时内的相对频率漂移为±55kHz，满足多普勒测风雷达的要求。

基于菲佐干涉仪与多通道光电倍增管阵列的多普勒频移检测技术

提出了基于菲佐干涉仪和多通道光电倍增管(PMT)阵列探测器组合的多普勒频移检测的方案, 适用于风速测量的直接探测多普勒激光雷达。首先介绍了工作原理, 再根据菲佐干涉仪光谱特征对频移检测用干涉仪进行了优化设计, 优化设计的菲佐干涉仪腔长150mm、平板反射率0.755。对提出的菲佐干涉仪和多通道光电倍增管阵列探测器组合的方案进行了数值模拟, 以分子散射作为背景噪声, 计算了该方法的风速测量误差。模拟结果表明, 设计的基于菲佐干涉仪的直接探测多普勒测风激光雷达, 在30 s的积分时间内、探测高度5 km以下,

First continuous ground-based observations of long period oscillations in strato-/mesospheric wind profiles

Direct measurements of middle-atmospheric wind oscillations with periods between 5 and 50 days in the altitude range between mid-stratosphere (5 hPa) and upper mesosphere (0.02 hPa) have been made using a novel ground-based Doppler wind radiometer. The oscillations were not inferred from measurements of tracers, as the radiometer offers the unique capability of near-continuous horizontal wind profile measurements. Observations from four campaigns at high, mid and low latitudes with an average duration of 10 months have been analyzed. The dominant oscillation has mostly been found to lie in the extra-long period range (20–40 days), while the well-known atmospheric normal modes around 5, 10 and 16 days have also been observed. Comparisons of our results with ECMWF operational analysis model data revealed remarkably good agreement below 0.3 hPa but discrepancies above.

Aerosol impacts on drizzle properties in warm clouds from ARM Mobile Facility maritime and continental deployments

We have extensively evaluated the response of cloud-base drizzle rate (Rcb; mm day–1) in warm clouds to liquid water path (LWP; g m–2) and to cloud condensation nuclei (CCN) number concentration (NCCN; cm–3), an aerosol proxy. This evaluation is based on a 19-month long dataset of Doppler radar, lidar, microwave radiometers and aerosol observing systems from the Atmospheric Radiation Measurement (ARM) Mobile Facility deployments at the Azores and in Germany. Assuming 0.55% supersaturation to calculate NCCN, we found a power law , indicating that Rcb decreases by a factor of 2–3 as NCCN increases from 200 to 1000 cm–3 for fixed LWP. Additionally, the precipitation susceptibility to NCCN ranges between 0.5 and 0.9, in agreement with values from simulations and aircraft measurements. Surprisingly, the susceptibility of the probability of precipitation from our analysis is much higher than that from CloudSat estimates, but agrees well with simulations from a multi-scale high-resolution aerosol-climate model. Although scale issues are not completely resolved in the intercomparisons, our results are encouraging, suggesting that it is possible for multi-scale models to accurately simulate the response of LWP to aerosol perturbations.

An assessment of a three-beam Doppler lidar wind profiling method for use in urban areas

Currently there are few observations of the urban wind field at heights other than rooftop level. Remote sensing instruments such as Doppler lidars provide wind speed data at many heights, which would be useful in determining wind loadings of tall buildings, and predicting local air quality. Studies comparing remote sensing with traditional anemometers carried out in flat, homogeneous terrain often use scan patterns which take several minutes. In an urban context the flow changes quickly in space and time, so faster scans are required to ensure little change in the flow over the scan period. We compare 3993 h of wind speed data collected using a three-beam Doppler lidar wind profiling method with data from a sonic anemometer (190 m). Both instruments are located in central London, UK; a highly built-up area. Based on wind profile measurements every 2 min, the uncertainty in the hourly mean wind speed due to the sampling frequency is 0.05–0.11 m s−1. The lidar tended to overestimate the wind speed by ≈0.5 m s−1 for wind speeds below 20 m s−1. Accuracy may be improved by increasing the scanning frequency of the lidar. This method is considered suitable for use in urban areas.

Observations of wind speed profiles over Greater London, UK, using a Doppler lidar

To calculate the potential wind loading on a tall building in an urban area, an accurate representation of the wind speed profile is required. However, due to a lack of observations, wind engineers typically estimate the characteristics of the urban boundary layer by translating the measurements from a nearby reference rural site. This study presents wind speed profile data obtained from a Doppler lidar in central London, UK, during an 8 month observation period. Used in conjunction with wind speed data measured at a nearby airport, the data have been used to assess the accuracy of the predictions made by the wind engineering tools currently available. When applied to multiple changes in surface roughness identified from morphological parameters, the non-equilibrium wind speed profile model developed by Deaves (1981) provides a good representation of the urban wind speed profile. For heights below 500 m, the predicted wind speed remains within the 95% confidence interval of the measured data. However, when the surface roughness is estimated using land use as a proxy, the model tends to overestimate the wind speed, particularly for very high wind speed periods. These results highlight the importance of a detailed assessment of the nature of the surface when estimating the wind speed above an urban surface.

A method for estimating the turbulent kinetic energy dissipation rate from a vertically pointing Doppler lidar, and independent evaluation from balloon-borne in situ measurements

A method of estimating dissipation rates from a vertically pointing Doppler lidar with high temporal and spatial resolution has been evaluated by comparison with independent measurements derived from a balloon-borne sonic anemometer. This method utilizes the variance of the mean Doppler velocity from a number of sequential samples and requires an estimate of the horizontal wind speed. The noise contribution to the variance can be estimated from the observed signal-to-noise ratio and removed where appropriate. The relative size of the noise variance to the observed variance provides a measure of the confidence in the retrieval. Comparison with in situ dissipation rates derived from the balloon-borne sonic anemometer reveal that this particular Doppler lidar is capable of retrieving dissipation rates over a range of at least three orders of magnitude. This method is most suitable for retrieval of dissipation rates within the convective well-mixed boundary layer where the scales of motion that the Doppler lidar probes remain well within the inertial subrange. Caution must be applied when estimating dissipation rates in more quiescent conditions. For the particular Doppler lidar described here, the selection of suitably short integration times will permit this method to be applicable in such situations but at the expense of accuracy in the Doppler velocity estimates. The two case studies presented here suggest that, with profiles every 4 s, reliable estimates of ϵ can be derived to within at least an order of magnitude throughout almost all of the lowest 2 km and, in the convective boundary layer, to within 50%. Increasing the integration time for individual profiles to 30 s can improve the accuracy substantially but potentially confines retrievals to within the convective boundary layer. Therefore, optimization of certain instrument parameters may be required for specific implementations.

Wind observations above an urban river using a new lidar technique, scintillometry and anemometry

Flow along rivers, an integral part of many cities, might provide a key mechanism for ventilation – which is important for air quality and heat stress. Since the flow varies in space and time around rivers, there is limited utility in point measurements. Ground-based remote sensing offers the opportunity to study 3D flow in locations which are hard to observe. For three months in the winter and spring of 2011, the atmospheric flow above the River Thames in central London was observed using a scanning Doppler lidar, a dual-beam scintillometer and sonic anemometry. 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 scanning strategy provided horizontal transects of wind vectors comparison with scintillometer rmse 1.12–1.63 m s–1) which revealed mean and turbulent flow across the river and surrounds; in particular: chanelling flow along the river and turbulence changes consistent with the roughness changes between built to 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 bankside roads.