First results of compact coherent Doppler wind lidar and its validation at IITM, Pune, India

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1 METEOROLOGICAL APPLICATIONS Meteorol. Appl. : 15 1 (15) Published online 1 August 13 in Wiley Online Library (wileyonlinelibrary.com) DOI: 1./met. First results of compact coherent Doppler wind lidar and its validation at IITM, Pune, India P. C. S. Devara,* Y. Jaya Rao, S. M. Sonbawne, M. G. Manoj, K. K. Dani and S. K. Saha Indian Institute of Tropical Meteorology, Physical Meteorology and Aerology Division, Pune, India ABSTRACT: A coherent Doppler wind lidar was installed in July 9 at the Indian Institute of Tropical Meteorology (IITM), Pune (1 3 N, E, 559 m AMSL), India, to map the daily three-dimensional wind fields in the atmospheric boundary layer (ABL). The aim was to provide a more in-depth understanding of weather, climate and air quality over Pune initially and later to be extended to other suitable sites in the country. The excellent performance of the system led to the deployment of next generation (extended) wind lidar with higher pulse power ( 1 μj) in July 1 to probe winds in clear-air (aerosol particles as tracers) as well as in cloud-air (cloud particles as tracers) up to about km AMSL. In this communication, a brief description of these two lidar versions together with some salient results, including comparison with co-located in situ techniques is presented. Sample data obtained on some typical experimental days with extended lidar and its calibration with co-located AWS and GPS Radiosonde are also presented. This comparison shows a reasonable agreement within the measurement accuracies. The spectral analysis of data reveals short-period, propagating-type gravity waves of about 5 min periodicity, exchanging energy between lower and upper altitude levels. In addition to the ABL evolution and Low Level Jet (LLJ) features, the data can be used to establish cirrus cloud structures and associated circulation. KEY WORDS Doppler lidar; atmospheric winds; clouds; waves; GPS radiosonde Received June ; Revised 11 May 13; Accepted 3 June Introduction Lack of reliable wind data is one of the main deficiencies in the current meteorological global observing network. Albeit better parameterization schemes are incorporated in climate models and improved data assimilation techniques provide better analyses for Numerical Weather Prediction (NWP) models, there is a great need for wind profile measurements. While surface-level data do not provide atmospheric profiles, single-level as well as multi-level upper-air wind data do not have a dense and even geographical distribution. In addition, the complementary observations from satellite sounding instruments miss smaller-scale features, particularly at low latitudes. Therefore, new insights into the atmosphere, through the provision of high-resolution, well-distributed and continuous wind profiles are essential (WMO, 199). Doppler Wind Lidar (DWL) is considered to be one of the most promising active remote sensors to obtain wind profiles from ground-level up to stratospheric altitudes and beyond (Chanin et al., 199; Gentry et al., ; Baumgarten, 1). This is the only potential instrument that provides three-dimensional coverage of global wind data from satellites. Generally, two classes of DWL are used: coherent (heterodyne) systems operating from 1 to 1 μm wavelengths, and incoherent (direct detection) interferometric systems operating at shorter wavelength down to.3 μm. The former systems have been found to be more advantageous for the * Correspondence: P. C. S. Devara, Indian Institute of Tropical Meteorology, Pune 11, India. devara@tropmet.res.in Laser Atmospheric Wind Sounder to be flown on the Earth Observing System (Menzies, 19). The latter systems use atomic absorption line, the edge filters, and fringe-imaging techniques to discriminate or analyse the frequency or spectrum of the return lidar signals (Korb et al., 199). These lidars also have the capability to provide ancillary information on cloud macro-physical parameters/aerosol properties (through backscatter) and wind variability as by-products. Technology improvements in the form of high-energy pulsed lasers, lownoise detectors and high optical quality telescopes are being evaluated to make wind measurements to long ranges or low aerosol/cloud droplet concentrations. Thus, wind measurement using the lidar technique has many advantages when compared to the conventional and other remote sensing techniques such as acoustic sounders, mainly because of its higher altitude coverage with super spatial and temporal resolution (Devara, 199; Singh and Kavaya, ; Wandiger et al., ). Since a Doppler wind technique measures the velocity along the lidar beam, it needs radial velocity measurements from at least three independent Line-Of-Sight (LOS) directions to obtain all the three components (u, v and w) of the wind vector. Thus, the lidar beams from three different directions (e.g., zenith, south and west) to a given point in space, which means viewing the same point from three or more LOS directions. So far, lidar probing of the atmospheric winds is restricted to a limited number of locations in India and more in general in the world (Devara, 199; 199). Because of paucity of suitable tracers, which these systems basically make use of in deriving the vertical profiles of winds over different environments, not many wind lidars have been put into operation for routine use. For the first time, high resolution measurements of threedimensional wind (U, V, W corresponding to zonal, meridional 13 Royal Meteorological Society

2 Coherent Doppler wind lidar measurements 157 and vertical components) have been carried out at Pune (1 3 N, E, 559 m AMSL) using a portable Doppler Wind Lidar (Leosphere Model WindCube7). Subsequently, a similar but high-power wind lidar (WindCube) that can routinely measure all the three components to higher altitude (up to km) during the day and night under all-weather conditions was installed. These systems are active remote sensors based on laser detection and range finding techniques. The heterodyne lidar principle relies on the measurement of the Doppler shift of laser radiation backscattered by the particles in the air (such as dust, water droplets from clouds and fog, pollution aerosols, salt crystals, biomass burning aerosols). This paper is organized as follows: chief technical specifications of the DWL are presented in Section, measurement principle and analysis technique are given in Section 3, some possible applications of DWL to climate change studies are highlighted in Section, some sample results, obtained with the above-mentioned lidar systems and calibration/comparison with co-located, AWS and GPS radiosonde (Vaisala-DigiCORA- MW31), planetary boundary-layer dynamics and cloud structures are presented in Section 5, and finally a brief summary is given in Section.. WindCube7/ specification The lidar operates with an eye-safety pulsed fibre laser radiation at 1.5 μm. These specifications facilitate the complete system highly portable so as to operate very easily from different platforms and at locations associated with diverse environmental conditions. The IP5 waterproof and dustproof housing protects the system from harsh weather conditions. The accuracy of the system has been proven in rain, snow and cold climates. Unlike conventional systems, these lidars are equipped with window de-icing and an automatic wiper assembly which allows the systems to operate during rain and snow. The performance and functional parameters of both WindCube7 and are presented in Table 1. It may be noted that the range capability of the systems depends on the pulse length, laser power and weather conditions. The capabilities of the system operated at IITM include: (1) measurement of winds with ultra-high time interval (up to 1 s) and with range resolution of m, and () automatic data filter to maintain data quality by adopting a criterion of threshold carrier-to-noise ratio (CNR), which can be specified according to the experimental requirements. The noise level decreases as the square root of the number of averaged pulses. It is a compact, plug and play, self protecting and unattended system. Figure 1 illustrates functional diagram and explains the principle of operation. The heterodyne lidar scheme adopted in the system relies on the measurement of Doppler shift of laser radiation backscattered by the particles in the air (dust, water/ice droplets from clouds and fog, aerosol pollutants, salt crystals). The wiper assembly facilitates operation of the DWL even during rainy and dusty conditions. Continuous wave (CW) Doppler lidar systems, developed in the past, provide better CNR and useful for wind measurements up to the boundarylayer altitudes (Devara, 199). Moreover, they have been extensively applied in telecommunication studies (for example, Karlsson et al., ). The pulsed laser source employed in the present system allows simultaneous measurements with Table 1. Main characteristics of the DWRs at IITM, Pune. Performance/function parameter WindCube7 WindCubeS Optics and electronics Laser wavelength 1.5 μm pulsed fibre laser 1.5 μm pulsed fibre laser Eye safety ICE/EN 5-1 compliant ANSI-Z13, 1-7 compliant Wind measurement (min max 1 15 m 1 1 m range) Averaging time 1.5 s to 1 min 1 1 s Vertical range resolution 5 m Selectable:, 5, 1 m Number of programmable gates >, Wind speed accuracy.3 ms 1. m s 1 below 1.5 km range Radial wind speed range m s m s 1 Cloud detection > m 15 m Output data 1 s or 1 s/1 min horizontal and vertical; wind speed, min and max, direction; signal-to-noise ratio; horizontal and vertical wind speed; standard deviation FPS location/time; defined range gates, scanner positioning; radial wind speed averaged over selected periods; carrier-to-noise ratio; spectral bandwidth and wind speed dispersions; radial wind gradient; wind field reconstruction; relative backscatter; optional: raw signal data Data Operating system Windows Windows 7 OEM bits Data format ASCII and BUFR ASCII and BUFR Environmental Temperature range 15 to + C 15 to + C Relative humidity 1 1% 1 1% Environmental protection IP 5-water proof and dust proof IP 5-water proof and dust proof Electrical Power supply 11/ V AC to 7 V DC 11/ V AC to 7 V DC Power consumption W (max.) W Dimensions Size mm mm Weight 5 kg 1 kg 13 Royal Meteorological Society Meteorol. Appl. : 15 1 (15)

3 15 P. C. S. Devara et al. Zenith North West East South W N V φ φ U E Figure. DBS Technique for deriving wind components. Thick lines indicate four lines of sight. V LOS is: V LOS (r) = U (z) sin (θ) cos (γ ) + V (z) cos (θ) cos (γ ) + W (z) sin (γ ) () Figure 1. Block diagram of the DWL system. similar resolution and accuracy at any height. The extended system provides 1 vertical wind profiles in 1 s. The system is also equipped with real-time data processing software that provides final products for each beam position. The description, method of analysis and first results of winds from the DWL observations, and their comparison with in situ measurements, carried out in the IITM campus, Pune, India in 9 and 1 are presented in the next section. 3. Principle of measurement and analysis The lidar system s basic principle is the Doppler method, whereby the Doppler shift is measured as the apparent frequency change of radiation perceived or emitted by a particle moving relative to the source or receiver of the radiation, compared to the particle at rest. The heterodyne (coherent) technique was followed in the detection process. The calculation of vector wind velocity is based on the assumption of horizontal homogeneity of the wind field over the sensed volume, scanning lidar techniques such as Velocity-Azimuth-Display, VAD (conical scan lidar beam at a fixed elevation angle), Doppler- Beam-Swinging, DBS (pointing lidar beam to vertical, tilted north, east, south and west directions). In the case of VAD, the Doppler frequency f directly determines the LOS component (V LOS ) of the wind vector as: V LOS (r) = [ f (r) λ L / ] (1) where r is range from the lidar to the target atmosphere, and λ L is The radial LOS component V LOS depends on the wind vectors, U (zonal), V (meridional), and W (vertical); where θ is azimuth angle, clockwise from the north, γ is an elevation angle, and z (r sin γ ) is an altitude above the observational point. Thus the Doppler shift observed for different beam positions has been used to derive the three components of Zonal (or east west), Meridional (or north south), and vertical wind. In the present study, an improved DBS technique has been followed for the data archive and analysis. Observations are carried out by pointing the lidar beam to vertical, tilted north, east and west directions. A schematic of the analysis technique is depicted in Figure. As shown in the figure, the four lines of sight (pointing lidar beam to vertical, tilted north, tilted east, tilted south, and tilted west directions i.e., ZNEZSW), achieved by sequential scanning, allow geometrical computation of 3D wind vector components (horizontal and vertical wind speeds and direction). Let φ be the off-zenith angle. The radial wind velocity (i.e. in the direction of lidar beam) components in the east (RE), west (RW), north (RN), south (RS) and vertical (RZ) are given as: V RE = U (z) sin φ + W (z) cos φ (3) V RW = U (z) sin φ + W (z) cos φ () V RN = V (z) sin φ + W (z) cos φ (5) V RS = V (z) sin φ + W (z) cos φ () V RZ = W (z) (7) From the above Equations (3) (7), the zonal (U ), meridional (V ) and vertical (W ) wind components can be written as: U (z) = (V RE V RZ cos φ) / sin φ () V (z) = (V RN V RZ cos φ) / sin φ (9) W (z) = V RZ (1) 13 Royal Meteorological Society Meteorol. Appl. : 15 1 (15)

4 Coherent Doppler wind lidar measurements 159 In the middle atmosphere, W is generally less than 1 m s 1 with a radial wind velocity error of + 1ms 1. So it is reasonable to ignore the contribution from vertical wind to off-zenith radial wind. Thus, the Equations (3) (7) can be simplified as follows: U (z) = V RE / sin φ (11) U (z) = V RW / sin φ () V (z) = V RN / sin φ (13) Wind profile data have been used at IITM for studies on: (1) composition, structure and dynamics of atmospheric boundary layer (ABL), () land-atmosphere-ocean interactions, (3) mapping and evaluation of air pollution/quality, and () local/regional/global climate analysis (including atmospheric aerosols, trace gases, electricity, clouds, radiation, convection and precipitation). The present state-of-the-art, ultra-high resolution Doppler wind lidar is believed to enrich the understanding of the above phenomena and bridge some of the gaps in the field, as briefly summarized in the next section. V (z) = V RS / sin φ (1) W (z) = V RZ (15). Applications Climate-change issues have received substantial attention in recent years due to increasing evidence that human activities may significantly modify the future climate of the Earth. Hence improvements in global climate analysis, its variability, predictability and change, require measurements of winds throughout the atmosphere. Numerical Weather Prediction (NWP) models and associated parameterization and data assimilation schemes also rely on accurate wind measurements. The World Meteorological Organization (WMO) states in its evaluation of user requirements and satellite capabilities that, for global meteorological analyses, measurement of wind profiles remains most challenging and most important (WMO, 199). Hence, it is essential to devote significant effort to the development of not only ground-based wind measuring systems in network mode but also the development of space-based wind monitoring systems. 5. Results and discussion 5.1. Comparison between DWL and AWS wind Continuous wind measurements were made, covering an altitude range of 1 1 m, on some typical days in July 9. Simultaneous observations of winds were carried out at the surface using an Automatic Weather Station (AWS). DWL wind speeds measured at 1 m level and the AWS values at the surface on 3 July 9 are compared in Figure 3 for two periods, h (DWL time series in solid line and AWS time series in dashed line) and h (DWL time series in solid line and AWS time series in dashed line). These two measurement series show reasonably good agreement within the measurement accuracies except for a small deviation (in space and time), which is considered to be mainly due to differences in the measurement height and sensitivity of the two experimental techniques. Moreover, both time series exhibit significant variability and short-period wavy structures. Time elapsed in minutes (AWS) WInd speed (ms -1 ) July 9 3July IST IST Time elapsed (X1) in seconds (DWL) Figure 3. Affinity between wind speed recorded with DWL (solid line) and AWS (dashed line). 13 Royal Meteorological Society Meteorol. Appl. : 15 1 (15)

5 1 P. C. S. Devara et al. Speed (m s 1 ) Direction ( ) V (m s 1 ) W (m s 1 ) July IST U (m s 1 ) IST Time elapsed (s) Figure. Time variation of wind components, direction and carrier-to-noise ratio (CNR) observed on 17 July 9. Speed (m s 1 ) Direction ( ) V (m s 1 ) W (m s 1 ) U (m s 1 ) July IST IST Time elapsed (s) Figure 5. Same as Figure 7, but observed on July Time variation of total wind and components Figures show time series of total wind magnitude and direction, zonal (U ), meridional (V ) and vertical (W ) components of wind computed, as explained in the previous section, on 17, and 3 July 9, respectively. The five panels of the figures display variations in wind speed, direction and all the three components of wind during the period 17 1 IST. It can be observed from these figures that the measurement of wind components is sensitive to the detectability of the lidar signal. The magnitude of vertical velocity is found to be less reliable when the CNR falls below certain threshold value i.e. db in the present system. Moreover, the magnitude of this component varies between positive (updraft) and negative (downdraft) during the study period. On all three experimental days, the magnitude of zonal wind component is found to be stronger compared to the meridional wind component, which is primarily due to Coriolis force. In addition, the total wind direction is found to lie between 1 and 3,whichis consistent Spectral analysis of wind variations Atmospheric gravity waves are essential parts of the dynamics of the atmosphere on all meteorological scales (Nappo, ). Since these waves occur at all altitudes in the atmosphere, 13 Royal Meteorological Society Meteorol. Appl. : 15 1 (15)

6 Coherent Doppler wind lidar measurements 11 Speed (m s 1 ) Direction ( ) V (m s 1 ) W (m s 1 ) U (m s 1 ) Juyl IST IST Time elapsed (s) Figure. Same as Figure 7, but observed on 3 July July IST Amplitude (arb. units) m m 7 m Period (s) Figure 7. Multi-altitude amplitude spectra of zonal wind variations observed on 3 July 9. Note the shifting of Y-axis by.5 for each spectrum, for clarity. they can transport energy and momentum from one region to another. Roach (197) reported oscillations in wind speed with a period of 1 15 min associated with gravity waves. In order to study these aspects, a power spectral analysis has been applied to the ultra-high time resolution measurements of DWL. The analysis shows the dominance of small-scale gravity waves with characteristic periodicities extending up to about 5 min. Such spectra obtained at three altitudes, 1, and 7 m, are depicted in Figure 7. These spectra exhibit prominent periodicities ranging from 1.5 to 5 min at all three altitudes at the 5% level of statistical significance. This feature further reveals vertical propagation of these waves, exchanging their energy between lower and higher height levels. Such oscillations are favoured by stable atmospheric background conditions. Study of such short-period waves, induced by wind turbulence, plays a pivotal role in energy exchange mechanisms involved in the land-surface interaction processes. 5.. Sample results from WindCube and inter-comparison Figure depicts a comparison between the zonal and meridional wind components obtained from co-located, simultaneous profile data archived with the extended DWL and GPS Radiosonde on 15 September 1. The agreement between the altitude profiles of wind from both techniques appears to be reasonably good, particularly at the altitudes ( and 1 m in the case of U and V components, respectively) where the wind magnitudes are large. The small vertical shifts in the peaks between the two techniques are considered to be 13 Royal Meteorological Society Meteorol. Appl. : 15 1 (15)

7 1 P. C. S. Devara et al. Height (m) Sept 1 1 Wind profiler U Radiosonde U Wind profiler V Radiosonde V Zonal wind (m/s) 1 3 Meridional wind (m/s) Figure. Comparison between EW and NS winds from DWL and GP radiosonde on 15 September 1. 11:37:3 7/15/1 :37:3 7/15/1 13:37:3 7/15/1 1:37:3 7/15/1 15:37:3 7/15/1 1:37:3 7/15/1 17:53:3 7/15/1 Figure 9. Height-time cross-section of carrier-to-noise ratio (CNR in db) observed on 15 July 1. Boundary-layer evolution, and wind structures within the cloud can be noted up to km from the figure. due to lack of exact time synchronization and sensitivity of DWL and GPS techniques. As with the surface-level winds, the zonal (U ) component shows larger magnitude as compared to that of meridional (V ). Moreover, the low level jet (LLJ) between and 1 m, captured by both the sensors, can be noted from the figure. The LLJ profoundly influences the ABL mixing process and the associated strengthening/dilution of cloud activity aloft during the study period (south west monsoon) over the experimental station. The height-time evolution of CNR (db) and horizontal wind (m s 1 ) observed on 15 July 1 is shown in Figures 9 and 1, respectively. These figures clearly show the LLJ, characterized by strong updrafts in the ABL, diurnal variation of ABL-induced cloud clusters and high-level cirrus cloud structures in the upper tropospheric region. Added, in Figure 9, the strong CNR values up to about 15 m indicate well-mixed boundary layer until 133 IST and thereafter the shallow boundary layer continuation up till 17 IST. It can also be 13 Royal Meteorological Society Meteorol. Appl. : 15 1 (15)

8 Coherent Doppler wind lidar measurements 13 11:: 7/15/1 :: 7/15/1 13:: 7/15/1 1:: 7/15/1 15:: 7/15/1 1:: 7/15/1 17:59:11 7/15/1 Figure 1. Height-time cross-section of horizontal wind speed (m s 1 ) recorded on 15 July 1. The presence of the low level jet (LLJ) involving strong updrafts is evident up to 1 m. Cirrus cloud signatures and wind field inside the cloud from to 11 km can be noted from the figure. noted that the background residual layer continued around 3 m throughout the study period. Moreover, the descending cloud structures with moderate CNR values in the height range between and m are evident at different times of the day. Similarly in Figure 1, moderate to strong wind speeds are evident in the boundary layer and also in clouds formed between and 1 5 m. The exciting feature that can be seen in this figure is that, the within-cloud winds are stronger and they exhibit wide variability throughout its vertical extent. Measurement of such wind field variations inside clouds is possible only with these types of ultra-high sensitive active remote sensors such as DWLs.. Summary and conclusions First results from a compact coherent Doppler Wind Lidar (DWL) and its validation at Pune, a tropical urban station in India are presented. The comparison between co-located DWL, AWS and GPS radiosonde shows a good agreement within the measurement accuracies. Of all the three wind components, vertical wind measurements are found to be more sensitive to the carrier-to-noise ratio. The spectral analysis of data revealed short-period propagating-type gravity waves of about 5 min periodicity, exchanging energy between lower and higher altitude levels. Under the assumption of horizontal homogeneity of the wind field over the sensed volume, scanning lidar technique can be used to determine the vector wind. Two scanning lidar techniques, VAD and DBS, are explained. The latter technique, adopted in the present study, is briefly described. Some sample results relating to both horizontal and vertical wind components in clear-air (aerosol particles as tracers) and cloud-air (cloud droplets as tracers) environments, evolution and interactions between ABL, LLJ and clouds from the extended DWL version are also presented. It is hoped that the DWL system would be highly useful for studying the role of circulation phenomenon in monsoon on different spatial and temporal scales. Such systems would play a significant role in the understanding, attribution and prediction of weather and climate change. Acknowledgements The authors are highly indebted to the Editor and anonymous reviewers for their encouragement and insightful comments. The useful discussions with Laurent Sauvage, Sebastien Dubois, Matthieu Boquet of M/s Leosphere, France, and Anil Sood of Microcomm, India during the operation of the DWL at the Institute and thereafter are gratefully acknowledged. The IITM is fully functional under the Ministry of Earth Sciences, Government of India, and the authors would like to thank its Director for infrastructure support. Authors also appreciate the support from the members of Aerosol and Cloud Physics Laboratory for Weather and Climate Studies. One of the authors (MGM) thanks the CSIR, New Delhi. References Baumgarten G. 1. Doppler Rayleigh/Mie/Raman lidar for wind and temperature measurements in the middle atmosphere up to km. Atmos. Meas. Tech. 3: Chanin ML, Gariner A, Hauchecorne A, Porteneuve J A Doppler lidar for measuring winds in the middle atmosphere. Geophys. Res. Lett. 1: Devara PCS Active remote sensing of the atmosphere using lasers. J. Sci. Ind. Res. : Royal Meteorological Society Meteorol. Appl. : 15 1 (15)

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