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Atmospheric boundary-layer structure from simultaneous SODAR, RASS, and ceilometer measurements
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Atmospheric boundary-layer structure from simultaneous SODAR, RASS, and ceilometer measurements b Stefan Emeisa,*, Christoph Munkel . , Siegfried Vogtc, Wolfgang J. Muller . d, Klaus Sch.afera a
Institut fur Umweltforschung (IMK-IFU), Forschungszentrum Karlsruhe GmbH, . Meteorologie und Klimaforschung, Atmospharische . Kreuzeckbahnstr 19, Garmisch-Partenkirchen D-82467, Germany b Vaisala GmbH, Schnackenburgallee 41d, Hamburg D-22525, Germany c Institut fur Spurenstoffe und Fernerkundung (IMK-ASF), Forschungszentrum . Meteorologie und Klimaforschung, Atmospharische . Karlsruhe GmbH, Postfach 3640, Karlsruhe D-76021, Germany d . Niedersachsisches Landesamt fur Hannover, Gottinger Str. 14, Hannover D-30449, Germany . . Okologie, . Received 17 February 2003; received in revised form 11 August 2003; accepted 15 September 2003
Abstract A comparison of the determination of boundary-layer structures by a SODAR, by a RASS, and by a ceilometer is presented. One important structure is the mixing-layer height (MLH). The comparison is focused on 3 days with an evolution of a convective boundary layer over a larger city in Germany. The three instruments give information that partly agree and partly complement each other. By this, a picture of the diurnal evolution of the vertical structure of this urban boundary layer is presented. The ceilometer gives information on the aerosol content of the air and the RASS provides a direct measurement of the vertical temperature distribution in the boundary layer. The RASS and the ceilometer add information on the moisture structure of the boundary layer that is not detected by the SODAR. On the other hand this comparison validates known techniques by which the MLH is derived from SODAR data. Especially the temperature information from the RASS agrees well with lifted inversions derived from the analysis of the SODAR data. The ceilometer, being the smallest instrument, has a potential to be used in future MLH studies. r 2003 Elsevier Ltd. All rights reserved. Keywords: SODAR; RASS; Ceilometer; Remote sensing; Urban boundary layer; Mixing-layer height
Abbreviations: ABL, Atmospheric boundary-layer; CBL, Convective boundary-layer; MLH, Mixing-layer height; PM2.5, Particulate matter smaller than 2.5 mm in diameter; PM10, Particulate matter smaller than 10 mm in diameter (includes PM2.5); SBL, Stable boundary-layer; FM-CW, Frequency-modulated continuous-wave; FTIR, Fourier-transform infrared spectroscopy; LIDAR, Light detection and ranging; MWR, Microwave radiometer; RADAR, Radio detection and ranging; RASS, Radio acoustic sounding system; SODAR, Sound detection and ranging; WTR, Wind-temperature-radar; AFO2000, Atmospheric research programme of BMBF; BMBF, German Federal Ministry of Education and Research, Bonn, Germany; IMK-ASF, Institute for Meteorology and Climate Research—Atmospheric trace substances and remote sensing, Karlsruhe, Germany; IMK-IFU, Institute for Meteorology and Climate Research—Atmospheric Environmental Research, Garmisch-Partenkirchen, Germany; METEK, Meteorologische Mes. Lower Saxony Agency for Ecology, Hannover, Germany. stechnik GmbH, Elmshorn, Germany; NLO, *Corresponding author. E-mail addresses: [email protected] (S. Emeis), [email protected] (C. Munkel), . [email protected] (S. Vogt), [email protected] (W.J. Muller). . 1352-2310/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2003.09.054
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1. Introduction The vertical structure of the atmospheric boundarylayer (ABL) has considerable influence on meteorological and environmental issues. It affects, e.g. near-surface pollutant concentrations, the vertical profiles of mean wind velocity, and the turbulent vertical exchange of momentum, heat, moisture, and other admixtures. Key parameters in describing the ABL are its depth and its dynamical and thermal structure. The top of the daytime ABL is frequently marked by an inversion, the nighttime ABL is often stably stratified over its full depth. Thus, their tops can be found by analysing the vertical temperature profile. In case of windy and cloudy weather neutral thermal stratification prevails and we have a more smooth transition from the boundary-layer to the free atmosphere. This latter condition is usually not connected with critical air pollution episodes. The depth of the usually well-mixed ABL (mixinglayer height, MLH) is needed in a variety of applications. Among these are the use of mass-consistent wind field models that determine the flow field from a few selected wind measurements, dispersion models that calculate the dilution of emitted substances in the ABL, prognostic models for the forecast of fog and clouds, advanced numerical flow models that need MLH for the scaling of ABL-quantities, and retrieval schemes that compute atmospheric and chemical parameters from satellite measurements. Also the conversion of atmospheric aerosol optical thicknesses from remote sensing into local air quality information needs the knowledge of MLH (Dandou et al., 2002). Albeit information on MLH is frequently needed no unique procedure for the determination of this height exists (Seibert et al., 2000). Because it is very difficult to yield a sufficient temporal capture of atmospheric variables that indicate MLH by air-borne instruments (balloons, aircraft, etc.) the use of ground-based remote sensing instrumentation is challenging. The use of data from satellites is hampered by their low vertical resolution, by visitation frequency, and by potential influences from cloud cover. Relying on ground-based remote sensing on the other hand limits the choice of the parameters that can be monitored. Fig. 1 indicates working frequencies and possible targets for ground-based remote sensing devices (see list of abbreviations). Acoustic remote sensing with a SODAR yields the vertical wind profile from a Doppler shift analysis of the returned signal and the vertical profile of the temperature structure parameter from the strength of the returned acoustic signal. Optical remote sensing with a LIDAR or a ceilometer allows a calculation of an aerosol profile from the strength of the returned laser signal. A RASS can detect the speed of a sound wave and thus the temperature profile after a possibly necessary correction for the (vertical) wind
speed. Additionally, the strength of the returned electromagnetic signal from this instrument depends mainly on the humidity structure parameter. Height allocation is done by analysing the travel time of the signal for the SODAR, the LIDAR, and the ceilometer or by analysing the frequency shift between the transmitted and the received signal for the RASS. Considerable experience already exists in measuring MLH with a SODAR (for a summary, e.g., see Beyrich, 1997). Main deficiency of this instrument is its limited range and the reduced data availability in special weather situations (especially in near-perfectly adiabatically stratified boundary layers in the afternoon). Here, in this study, acoustic remote sensing with a SODAR will be compared to optical remote sensing with a ceilometer and radio-acoustic remote sensing with a RASS. The objectives of the study are a contribution to the validation of SODAR measurements by using other remote sensing information, a better temporal coverage of ABL structure information, and a comparison of the instruments to determine which instrument is most suited to detect which ABL structures.
2. Determining the vertical layering of the ABL by remote sensing Beyrich (1997) and Seibert et al. (2000) give an overview over means to determine one of the key parameters of the ABL, the MLH. The derivation of MLH from radiosonde temperature profile data is the oldest method. Starting with Holzworth (1964) various schemes have been proposed. An actual example, the monitoring of the annual variation of MLH from daily lateafternoon radiosonde ascents is presented in Freedman et al. (2001). They find the maximum MLH in the northeastern US in late spring just before the growing season starts. But this method is only appropriate to find MLH for the time of the sounding but not to detect the diurnal course of MLH. Further, the method is limited mainly to convective conditions. A critical discussion of this approach can be found in Lokoshchenko (2002). Remote sensing can fill this gap. But the interpretation of remote sensing data may be ambiguous because other features than the thermal stratification of the air . influence the data, too (Bosenberg and Linn!e, 2002). Therefore the comparison to radiosonde data or the intercomparison of different remote sensing techniques may help to identify the relevant structures of the ABL. Lokoshchenko (2002) has recently compared MLH from SODAR and radiosonde data using Holzworth’s method, which revealed the difficulties of determining and comparing MLH from these two types of data. He therefore proposes to use the instability energy as an alternative parameter for the characterisation of the convective boundary layer. A likewise study has been
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Fig. 1. Working frequencies of ground-based remote sensing techniques for atmospheric sounding (first line: active devices, second line: passive devices). Upper bars: electromagnetic spectrum, lower bar: acoustic spectrum. Visible light is indicated by the inserted rainbow colours. Vertical grey bars give typical size range of atmospheric aerosol, rain drops, and (near-surface) turbulent motion (modified from Emeis, 2000).
made by Keder (1999) who compared radiosonde data evaluated following Myrick et al. (1994) with the built-in MLH-determining routine of a REMTECH SODAR. Here the comparison was even more disappointing, but mainly due to errors in the automatic routine supplied by the SODAR manufacturer. Coulter (1979) has compared the temperature profile method with LIDAR and SODAR measurements. In early morning and late afternoon hours the LIDAR data systematically yielded higher CBL tops than the SODAR data. The data from both remote sensing methods always delivered higher CBL tops than the evaluation of the temperature profile. Due to Coulter (1979), this is because particulates mix to larger heights than the top of the adiabatic temperature profile, while temperature fluctuations exhibit an increase in the entrainment zone above the top of the adiabatic temperature profile but below the maximum height of particulate mixing. Devara et al. (1995) have compared a LIDAR and a SODAR in a study on the nocturnal SBL. They found a principal agreement in the results. Beyrich . and Gorsdorf (1995) have used two instruments, a SODAR and a wind profiler simultaneously for 5 weeks in order to determine the MLH. They found that on days with the development of a convective boundarylayer both instruments yielded comparable results during the morning hours. A RASS and two LIDARs have been compared with radiosonde data in Marsik et al. (1995). They found strong deviations between the MLH from the three instruments around 8:00 local time, a better coincidence around noon, and again increasing deviations in the afternoon.
Seibert et al. (2000) only considered active remote sensing devices. Westwater (1997) describes also passive microwave radiometers (MWR) that yield temperature profiles and inversion heights for the lowest 1000 m of the atmosphere with reasonable accuracy. Solheim and Godwin (1998) present temperature profiles from MWR up to 10 km above ground. Elevated inversions are not represented very well in their retrievals. Since the preparation of the review by Seibert et al. (2000) optical remote sensing has made considerable progress. Ceilometers originally designed just to report cloud base heights have become available also for atmospheric profiling (Rogers et al., 1997; R.as.anen et al., 2000; Munkel . et al., 2003). They have an improved vertical resolution (now about 15 m) and a much smaller lower detection range limit (now about 30 m above ground). They are eye-safe and can be operated automatically. The availability of a RASS like the WTR of IMK-ASF allows the direct measurement of the vertical temperature profile. Therefore the determination of ABL structure with SODAR and other remote sensing techniques is reconsidered here.
3. Experimental set-up 3.1. Site In the framework of the project Validation of instruments for environmental policies (VALIUM) within the program AFO2000 (Atmospheric Research 2000) of the German Federal Ministry of Education and
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Research (BMBF) long-term meteorological and air quality measurements have been made in the street . canyon ‘‘Gottinger Strasse’’ in the town of Hannover in Northern Germany. This street canyon runs in front of the main building of the Lower Saxony Agency for . At the highest part of the roof of this Ecology (NLO). building (about 43 m above ground level) an automatic . is available that meteorological station, run by the NLO, delivers wind and temperature information at roof level above the street canyon. The horizontally averaged roughness length of the more or less urban area within a radius of 10 km is about 1 m. In order to monitor the ambient flow conditions (wind profile and MLH) near this street canyon a SODAR has been placed about 550 m upstream (with respect to the most frequent wind direction, which is Southwest) of the street canyon and the roof-top station on the grounds of a larger factory away from housing areas. The ceilometer has been placed about 20 m above ground level . building that is connected to the on the roof of a NLO one adjacent to the street canyon. The distance to the roof-top station is about 30 m. The RASS has been operated 150 m away from the roof-top station in the . buildings. The intensity of the backyard of the NLO acoustic sound emission by the RASS had to be limited due to the people working in a near-by office building. SODAR, RASS, ceilometer, and roof-top station were positioned along an almost straight line that is running from southwest to northeast. The first campaign during that all three remote sensing instruments were available was from 26 April to 12 May 2002. A second campaign was from 19 October to 1 November 2002. 3.2. Instrumentation 3.2.1. SODAR The METEK DSD3 7 mono-static Doppler SODAR (Reitebuch and Emeis, 1998) has three antennas (see Fig. 2a) with seven sound transducers (i.e. a device that serves both as a loudspeaker and as a microphone, depending on the phase of the measurement cycle) each, working at about 1500 Hz. The instrument is optimised for long-range detection up to 1300 m above ground in ideal conditions without external noise sources. The SODAR records the intensity of acoustic backscatter of the air S; that is proportional to the structure parameter of the acoustic refractive index CN2 ; which in turn mainly depends on the temperature structure parameter CT2 (Tatarskii, 1961). The measurement fails in case of stronger rain or snow, perfect adiabatic conditions due to strong thermal mixing, and large noise from the surroundings. Only inhomogeneities in the temperature field in the order of Dx ¼ lsound =2 contribute to S: Normally this is within the ‘inertial subrange’ of the turbulence spectrum. Therefore S contains
information on the structure of the turbulence in the boundary-layer, but not on the sign of the vertical temperature gradient. In case of a vanishing vertical gradient of potential temperature the backscatter intensity of the air is low even if there is still turbulent motion (see explanation for code ‘7’ in Maughan et al., 1982). During weather situations with weak winds and strong thermal inversions the contribution of the mean vertical temperature gradient to S can be at least as large as the contribution from the turbulent motion (Beyrich, 1997). This allows the detection of stable layers at night. The range of the instrument with respect to sound reflectivity is usually larger than with respect to the identification of a Doppler shift.
3.2.2. RASS The RASS used here is called a wind-temperatureradar (WTR) because it works in the RASS mode and the clear-air mode. It is a prototype instrument designed and built by Dr. G. Peters from the Max-Planck Institute for Meteorology and the Meteorological Institute of the University of Hamburg, Germany (see Figs. 2b and 3). All measurements are based on the backscattering of electromagnetic decimetre waves in the atmosphere. Waves are scattered either at microturbulent fluctuations of the atmospheric refraction index associated with fluctuations of temperature and humidity, or at artificial fluctuations of the refraction index, which are generated by the transmission of appropriate sound pulses. The WTR measures the air temperature by detecting the propagation of sound pulses with a RADAR. The temperature calculation from the sound speed is corrected for the vertical wind speed. In the clear-airmode the WTR observes the electromagnetic structure parameter of the refractive index CN2 ; which in contrast to its acoustic counterpart is mainly dominated by moisture fluctuations but much less by temperature fluctuations. The WTR has a five-beam geometry with two bistatic radiofrequency (rf) and one acoustic (ac) antenna. The ac antenna is a 1:2 scaled copy of the rf-array to match the rf-beam at the Bragg-wavelength. The rf antenna emits continuous waves that are frequency-shifted with a saw tooth modulation (FM-CW Doppler Radar) in order to provide a high average transmitted power and a fine range gate resolution. Contrary to a conventional pulse Radar the height resolution is not calculated from the travel time of the rf waves but is taken proportional to the frequency shift between the transmitted and received signal. The sound source is also used to estimate the wind components in the so-called RASSmode. This is possible because the ac beam is simultaneously shifted in the same four oblique beam directions like the rf beam. The combination of the
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Fig. 2. (a) METEK DSDR3 7 SODAR. Instrument height is about 4 m. (b) METEK WTR. Instrument height is about 4 m. (c) Vaisala CT25K ceilometer. Instrument height is about 1 m.
RASS mode and the clear air mode allows the derivation of two independent and redundant wind profiles. The sound speed wa depends on the virtual acoustic temperature Tvs ¼ Tð1 þ 0:51qÞ with the specific moisture q (Kaimal and Businger, 1963). The virtual acoustic temperature is defined as the temperature of dry air in which the sound speed is equal to the sound speed in the real (moist) air Tvs ¼ ðM=gRÞw2a ;
where M is the molecular weight of the air, g is the ratio of the specific heats and R is the universal gas constant. Technical data are shown in Table 1. As can be seen in Fig. 3 the WTR can be rotated on its trailer, and the distance separating the acoustic antenna from the rf antennas can be varied by means of a sliding boom, allowing the acoustic source to be positioned for maximum efficiency upwind of the rf antennas in dependence on wind speed and wind direction.
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Fig. 3. Schematic bird’s eye view of the WTR. Table 1 Technical data of the WTR (left column: electromagnetic waves, right column: acoustic waves) Frequency Power Antenna aperture Antenna gain Beam direction Antenna type Number of range gates Width of range gate Averaging time per beam Averaging time for wind and temperature
1290 MHz 6400 W 3.2 m 3.2 m 33.5 dB 78.5 off zenith in N–S–W–O 8 8 pyramidal horns 78 60 m (variable) 10 s (variable) 30 min (variable)
3.2.3. Ceilometer The Vaisala single-lens ceilometer CT25K (see Fig. 2c, R.as.anen et al., 2000) measures the optical backscatter intensity of the air at a wavelength of 0.9 mm (near infrared). Its InGaAs laser diodes are pulsed with a repetition rate of 5.57 kHz. The pulse energy is 1.6 mJ, the 50% pulse width is 100 ns. The lens has a focal length of 377 mm and an effective diameter of 145 mm. Laser beam full divergence and field-of-view divergence of the receiver are 1.4 mrad each. Because of the monostatic optical system and the small divergence multiple scattering effects are negligible, Mie scattering with scattering angles between 179.9 and 180.1 is dominant and the following simplified form of the lidar equation can be used for interpreting the backscatter profiles: cDt AZOðxÞ Pðx; lÞ ¼ bðx; lÞt2 ðx; lÞ; P0 2 x2
2700–3000 Hz 320 W 1.6 m 1.6 m 33.5 dB 78.5 off zenith in N–S–W–O 8 8 exponential horns 24 60 m (variable) 10 s (variable) 30 min (variable)
where Pðx; lÞ is the power recorded by the receiver detector, c is the speed of light, Dt is the laser pulse duration, P0 is the power of emitted laser pulse, A is the area of the receiver, Z is the efficiency of the receiver, OðxÞ is the range-dependent overlap integral between the transmitted beam and the field of view of the receiver (0pOðxÞp1), bðx; l) is the backscatter coefficient, tðx; lÞ is the transmittance of the atmosphere between the measuring system and the scattering volume, l is the wavelength, x is the range from the measuring system to the scattering volume. The ceilometer does not report raw signals, but preprocessed backscatter intensity profiles representing the last two terms in the lidar equation, bðx; lÞt2 ðx; lÞ; with a range of 2 km and a vertical resolution of 15 m. Every 15 s a profile accumulated over 65,536 laser pulses is reported. Automatic laser power control and
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temperature compensation of the receiver detector provide a long-term stability of the factor P0 Z of 715%. The backscatter intensity depends mainly on the particulate concentration in the air. As the size of many particles varies with their moisture content, the reflectivity is influenced by atmospheric humidity, too. Clouds and precipitation inhibit measurements. Enhanced particulate concentrations can be either due to horizontal advection, due to strong thermal convection, or due to local chemical reactions forming secondary particles. In case of chemical reactions this usually points at a stable stratification of the air because otherwise mixing would dilute the chemically produced particles. The performance of the CT25K ceilometer is sufficient for analysing boundary-layer structures. Compared to more sophisticated LIDAR systems commonly used for these investigations it has several special features. Some of these are favourable when long-term studies involving several stations are considered. These features include the low first range gate (15 m, due to the identity of the optical axes of transmitter and receiver and due to relatively low emitted power), its low maximum range (around 2000 m, due to the low emitted power), its ability to operate eye-safe and maintenance-free for several years in any climatic environment with just some regular window cleaning, and its comparably low price.
4. Comparison of SODAR, WTR, and ceilometer measurements Seventeen days in spring and 14 days in autumn are principally available for comparison. From the days in spring only the last six showed an enhanced convective activity. The first 11 days were dominated by cyclonic activity over the British Isles and the North Sea and very windy weather. The longest dry period (a prerequisite for the evaluation of the ceilometer data) was from 8 to 10 May 2002. Inspecting the SODAR data lifted inversions were observed on 6, 9, and 10 May and very marginally on 2 May. From the 14 days in autumn 12 days were at least partly rainy so that the ceilometer data are not usable. Only two single days, 20 and 31 October remain for a complete comparison. The first of these days showed only weak convective activity, the second one had the passage of a weak cold front without rain in the afternoon. On 21 October and 1 November lifted inversions are clearly visible from the SODAR backscatter data although the ceilometer data indicate that it was continuously raining. On both days the height of the lifted inversions decreased during the day until they reached the ground. Warm fronts passed the measuring site on these days (also obvious from the WTR temperature time-height cross sections). Thus, these structures were no inversions but the frontal surfaces of
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the warm fronts. A lifted inversion with rain not connected to a warm front occurred in the first half of 8 May. We have chosen the period from 8 to 10 May 2002 for presentation because these three consecutive days reveal all relevant boundary layer structures and inversions. During these days all instruments operated reliably. This period also includes the above-mentioned case with a lifted inversion during rain. Fig. 4 shows the meteorological readings from the roof-top station. At these days the wind came from southeasterly directions, the wind speed varied between 2 and 3 m/s at night and 5 and 6 m/s in the afternoons. On the evening of 10 May, a weak cold front passed the measurement site. After the passage of the front the wind turned to northwesterly directions. At these days sunrise was around 3:00 UTC, sunset around 19:41 UTC. The following discussion will be illustrated by coloured pictures of the backscatter and the temperature distribution (Figs. 5–7) seen by the three instruments in order to demonstrate the different abilities of these instruments to detect ABL structures. The displayed backscatter intensity is corrected for distance but for the SODAR and the WTR it is given in arbitrary units only. The ceilometer data is calibrated (see Section 3.2.3). It is not the purpose of the present investigation to give statistics of MLH for a longer period. These will be published elsewhere later. The following investigation extends only to a height of 1000 m above ground. This choice has been made because the range of the WTR temperature measurements and the range of the SODAR are limited to this height. The ceilometer and the WTR (in the clear-air mode) return meaningful signals from heights of more than 2000 m. The comparison is based on 30 min averages in the case of the SODAR and the WTR (computed from 12 s data for the WTR) and 15 s
. at 43 m above Fig. 4. Data from the roof-top station of NLO ground level for 8–10 May 2002. Thick black line: temperature in C (left-hand scale), thin black line: wind speed in m/s (lefthand scale), dotted line: wind direction in degrees (right-hand scale).
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Fig. 5. Upper frame: SODAR acoustic backscatter and horizontal winds (scale in the third frame), second frame: WTR temperature in C, third frame: WTR electromagnetic backscatter and horizontal winds, lowest frame: ceilometer optical backscatter in 104/sr km for 8 May 2002. Y-axis: height above ground in m, X-axis: time in UTC. Sunrise is at 03:00 UTC, sun set at 19:41 UTC.
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Fig. 6. Upper frame: SODAR acoustic backscatter and horizontal winds (scale in the third frame), second frame: WTR temperature in C, third frame: WTR electromagnetic backscatter and horizontal winds, lowest frame: ceilometer optical backscatter in 104/sr km for 9 May 2002. Y-axis: height above ground in m, X-axis: time in UTC. Sunrise is at 03:00 UTC, sun set at 19:41 UTC.
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Fig. 7. Upper frame: SODAR acoustic backscatter and horizontal winds (scale in the third frame), second frame: WTR temperature in C, third frame: WTR electromagnetic backscatter and horizontal winds, lowest frame: ceilometer optical backscatter in 104/sr km for 10 May 2002. Y-axis: height above ground in m, X-axis: time in UTC. Sunrise is at 03:00 UTC, sun set at 19:41 UTC.
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averages in the case of the ceilometer data. The vertical resolution is 15 m with the ceilometer data, 25 m with the SODAR data, and 60 m with the WTR data. Due to fixed echoes from near-by buildings the lowest reliable measurement height is 60 m above ground for the SODAR and 160 m above ground for the WTR in case of backscatter. As the measurements in the RASS mode are not affected by ground clutter the WTR can measure wind and temperature down to 100 m height. The ceilometer with its well-focussed beam has also no ground-clutter problems. The ragged top of the SODAR data in Figs. 5–7 is due to a regular switching between two vertical resolutions (12.5 and 25 m) and thus two different ranges (600 and 1200 m) every half hour. The uppermost image in each of the Figs. 5–7 displays the acoustic backscatter intensity (corrected for distance) and the horizontal wind vector measured by the SODAR (for a scale see the third frame below). Wind vectors can be determined only when the acoustic backscatter intensity exceeds a certain threshold, because otherwise the signal-to-noise ratio for a determination of the Doppler shift is too low. The second image shows the virtual acoustic temperature (in C) measured by the WTR in the RASS mode. This image also contains in the lowest row the virtual temperature that has been recorded at the roof-top station 43 m above ground level. Temperature rather than potential temperature is shown here because temperature inversions can be seen more clearly. Potential temperature would have been better in order to diagnose whether a layer is really well mixed or not. The third image presents the backscatter seen by the WTR in the clear-air mode and the horizontal wind vector measured by this instrument. The lowermost image shows the optical backscatter intensity obtained with the ceilometer. Dark blue areas above dark red areas indicate missing data because in this case the light beam has been totally absorbed in the cloud layer in between. Each figure presents data for 1 day. ABL structures analysed from the SODAR data have been entered into the plots as full lines. Dotted lines represent sharp gradients in the optical backscatter recorded by the ceilometer that match with echoes from the clear-air mode of the WTR. The analysis of the structures in the SODAR data has been made according to the MLH criteria given in Beyrich (1997) and Seibert et al. (2000). At daytime the MLH has been marked at the lower edge of a lifted secondary backscatter maximum. At night-times the upper edge of the surface-based backscatter maximum is marked as the top of the SBL. If a backscatter maximum appears adjacent to the ground during daytimes, it was not marked because in this case the high backscatter indicates a super-adiabatic surface layer due to the heating of the ground by incoming solar radiation.
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The marking of the structures and inversions in the Figs. 5–7 has mainly been done for an easier intercomparison between the four frames within one figure. The figures demonstrate clearly that backscatter intensities for acoustic, electromagnetic, and optical waves differ considerably. The WTR detects in its clearair mode several structures that do not appear in the SODAR data. While the maximum acoustic backscatter intensity is nearly always close to the ground (except for lifted inversions), the maximum electromagnetic backscatter is most frequently between 500 and 1000 m above ground. The most intense backscatter is observed here during daytime unstable stratification of the atmosphere extending over a quite large height range of several hundreds of meters. In the following several boundarylayer features detected by the three instruments are described in more detail: 4.1. Lifted temperature inversions Elevated secondary maxima in the acoustic backscatter are interpreted as lifted inversion. Such features, lasting for at least a few hours, occurred during this instrument intercomparison campaign on 2, 6, 8, 9, and 10 May, on 19 and 21 October and on 1 November 2002. In Figs. 5–7 they can clearly be identified from the acoustic backscatter and the WTR temperature on 8 May from 0:00 to 14:00 UTC, on 9 May from 1:00 to 9:00 UTC (although there is a second inversion at about 300 m until 6:00 UTC that is detectable only from the temperature distribution), and on 10 May at 2:00–7:00 UTC. During most of the time the lifted inversion is visible from a wind shear, too. Below this inversion the wind is weaker and has backed due to the surface friction. On 9 and 10 May the layer below this inversion is additionally characterised by an enhanced aerosol content as seen from the ceilometer data. On 8 May low clouds inhibit the ceilometer to have a look at this inversion. The electromagnetic backscatter intensity also depicts these inversions. But here, the increased backscatter extends several hundreds meters above the inversion while the elevated maximum of the acoustic backscatter is usually o100 m deep. Especially noteworthy is the decoupling of the winds below and above the temperature inversion between 6:00 and 7:00 UTC on 10 May. During this short episode a temperature inversion starts at 200 m above ground with an increase of the air temperature from 15 C to 19 C within the next 100 m above this level. Above this inversion at 6:30 and 7:00 UTC the wind has turned to near southerly directions compared to the more southeasterly wind direction before and after this episode. This turning is due to the reduced turbulent momentum transport through this strong inversion. Due to the higher vertical resolution this phenomenon is more
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clearly to be seen from the SODAR winds than from the WTR winds. 4.2. Convective boundary-layers The development of a deeper daytime convective boundary-layer during the instrument intercomparison was observed on 7, 8, 9, 10, and 12 May only. During the autumn period, convection was generally weak because of the season and the rainy weather. At all 3 days considered in Figs. 5–7 a well-mixed convective boundary layer (CBL) is developing. This CBL erodes the existing—above mentioned—temperature inversions and grows beyond 1000 m on 8 May at 14 UTC and on 10 May around noon. On 9 May the CBL top maximum height is between 700 and 800 m above ground. The secondary acoustic backscatter intensity maxima marking the CBL top are weaker than the ones that indicated the lifted temperature inversion discussed in the previous subsection. On the other hand, the electromagnetic backscatter from the CBL top is stronger than from the lifted temperature inversions. On 9 and 10 May this CBL can also be detected from an increased aerosol content. On 8 May mist and clouds prevent a clear identification of aerosol concentrations from the ceilometer data. Close to the ground high acoustic backscatter intensities can be found during well-developed CBLs. This high reflectivity obviously marks an over-adiabatic layer due to the strong radiative heating of the surface. Above this over-adiabatic layer the backscatter intensity is decreasing considerably before it increases again near the top of the CBL. The electromagnetic backscatter intensity in a CBL increases well with height. The maximum intensity is reached just above the inversion in the same height where the acoustic backscatter has its weak secondary maximum, too. Above this maximum the electromagnetic backscatter is decreasing only slowly. The most striking difference to the acoustic backscatter is that the high intensity of the electromagnetic backscatter in the upper part of the CBL and at the inversion can be traced until the evening whereas the acoustic backscatter vanishes nearly completely after 15 or 16 UTC. This happens also on 9 May where the CBL top is definitely below 1000 m. The reason for this fading of the acoustic backscatter is the vanishing vertical potential temperature gradient in a well-mixed CBL in the later afternoon (Maughan et al., 1982) when the heating from below stops. The daily maxima of sigma w (not shown) are detected in an interval between 2 h before and 2 h after this fading out near the top of the CBL. These maxima indicate turbulence and are responsible for the near adiabatic profile without any larger temperature fluctuations in this range.
4.3. Nocturnal surface inversions An intensity maximum of the acoustic backscatter close to the surface during the night is interpreted as an indication of a nocturnal stable surface inversion layer with some mechanically induced turbulence. This feature appeared in the nights to 1, 2, 9, and 10 May and in some nights of the autumn period. It can be seen in both nights covered in Figs. 5–7 from about 19 UTC in the evening to about 4–5 UTC the next morning. The wind speed at the roof-top station at 43 m above ground level never falls below 2 m/s during these two nights (Fig. 4). A temperature increase reaches up to about 500 m in both nights, as can be seen from the WTR data. In a height between 300 and 400 m a further layering of the air can be deduced from a further reduction of the intensity of the acoustic backscatter and a related turn of the wind direction. Within this surface inversion also the ceilometer detects high optical backscatter. This may be due to an increased aerosol content, but it could also be moist dust as well. On the evenings of 8 and 10 May the increases in relative humidity and in the particulate matter fractions PM2.5 and PM10 (measured at stations in the vicinity, Munkel . et al., 2003) coincide. Thus, it may be that the increase in aerosol mass is at least partially due to a humidification of pre-existing aerosol. On the evening of 9 May no such correlation can be found between relative humidity and aerosol concentrations. In the second half of the night in the stable layer between the surface inversion and the second inversion at about 300–400 m height distinct layers of enhanced aerosol content can be seen from the ceilometer data. Probably these aerosol layers have been advected. One to two hours after sun rise at 03 UTC these aerosol layers disappeared.
5. Conclusions Three different instruments that deliver five types of vertical profiles (wind and acoustic backscatter from a SODAR, wind, temperature, and electromagnetic backscatter from a WTR and optical backscatter from a ceilometer) have been brought together at one site. Lifted temperature inversions can be detected best from the intensity of the acoustic backscatter and the vertical temperature distribution. These inversions form an upper bound for the dispersion of near-surface aerosol. The SODAR can follow the CBL top only in the first half of a day. Later in the afternoon the CBL top is either out of the vertical range of the SODAR or the gradients in potential temperature become too low in order to reflect sound waves. The upper part of the CBL and the CBL top can be detected best from the
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electromagnetic backscatter. This indicates considerable moisture fluctuations in the upper half of the CBL also in the later afternoon. A considerably enhanced aerosol concentration inside the CBL can be derived from the ceilometer data. The results from the ceilometer give no indication for higher MLH than the SODAR or the WTR as had been reported by Coulter (1979) for a LIDAR. During nights a surface inversion can be identified from the SODAR data in the lowest 100 m as a maximum of acoustic backscatter intensity. This surface inversion is also clearly identifiable from an intensity maximum of optical backscatter in the ceilometer data. In the nearly isothermal layer above the surface inversion filament-like structures can be observed in the ceilometer data. In case of cloud cover and rain the ceilometer does not yield useful data on the boundary layer structure. During the other periods the ceilometer gives direct information on the vertical aerosol distribution, a quantity which is otherwise only indirectly derived from mixing conditions measured with SODAR or WTR. The comparison for the period discussed in this paper shows especially at night when mixing due to thermal instability is absent that there are considerable differences between the vertical aerosol distribution and the induced vertical structure of the ABL. This is an indication that advection of aerosol and the formation of moist haze can be important at these times. SODAR measurements afford less expense than WTR measurements. The great advantage of the WTR on the other hand is the direct observation of the vertical temperature profile. The ceilometer is the most easiest remote sensing device of the instruments considered here. The potential of a ceilometer is comparable to a single-frequency LIDAR. It has a height range of a few thousand meters, only bounded by cloud bases and precipitation. The progress in remote sensing instrumentation is bringing us closer to a more continuous observation of parts of the atmosphere that are not directly adjacent to the ground.
Acknowledgements The SODAR measurements were financed within the project VALIUM of the German Ministry of Education and Research (BMBF) under the framework program AFO2000. The ceilometer measurements were funded by Vaisala GmbH, Hamburg, the WTR by IMK-ASF of the Forschungszentrum Karlsruhe GmbH. The measurements would not have been possible without the technical and scientific support from the Nieder. . Hanns.achsische Landesanstalt fur . Okologie (NLO), over, and METEK GmbH, Elmshorn. Special thanks go . We thank Komatsu, . from NLO. to Mr. Drunkenmolle
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Germany GmbH, for the permission to use their grounds for the SODAR measurements.
References Beyrich, F., 1997. Mixing height estimation from sodar data—a critical discussion. Atmospheric Environment 31, 3941–3953. . Beyrich, F., Gorsdorf, U., 1995. Composing the diurnal cycle of mixing height from simultaneous SODAR and wind profiler measurements. Boundary-Layer Meteorology 76, 387–394. . Bosenberg, J., Linn!e, H., 2002. Laser remote sensing of the planetary boundary layer. Meteorologische Zeitschrift 11, 233–240. Coulter, R.L., 1979. A comparison of three methods for measuring mixing layer height. Journal of Applied Meteorology 18, 1495–1499. Dandou, A., Bossioli, E., Tombrou, M., Sifakis, N., Paronis, D., Soulakellis, N., Sarigiannis, D., 2002. The importance of mixing height in characterising pollution levels from aerosol optical thickness derived by satellite. Water, Air and Soil Pollution: Focus 2 (5–6), 17–28. Devara, P.C.S., Ernest Ray, P., Murthy, B.S., Pandithurai, G., Sharma, S., Vernekar, K.G., 1995. Intercomparison of nocturnal lower-atmospheric structure observed with LIDAR and SODAR techniques at Pune. Indian Journal of Applied Meteorology 34, 1375–1383. Emeis, S., 2000. Meteorologie in Stichworten. Borntraeger, Stuttgart, 199pp. Freedman, J.M., Fitzjarrald, D.R., Moore, K.E., Sakai, R.K., 2001. Boundary layer clouds and vegetation-atmosphere feedbacks. Journal of Climatology 14, 180–197. Holzworth, C.G., 1964. Estimates of mean maximum mixing depths in the continguous United States. Monthly Weather Review 92, 235–242. Kaimal, J.C., Businger, J.A., 1963. A continuous wave sonic anemometer-thermometer. Journal of Applied Meteorology 2, 156–164. Keder, J., 1999. Detection of inversions and mixing height by REMTECH PA2 Sodar in comparison with collocated radiosonde measurements. Meteorology and Atmospheric Physics 71, 133–138. Lokoshchenko, M.A., 2002. Long-term sodar observations in Moscow and a new approach to potential mixing determination by radiosonde data. Journal of Atmospheric and Oceanic Technology 19, 1151–1162. Marsik, F.J., Fischer, K.W., McDonald, T.D., Samson, P.J., 1995. Comparison of methods for estimating mixing layer height used during the 1992 Atlanta field initiative. Journal of Applied Meteorology 34, 1802–1814. Maughan, R.A., Spanton, A.M., Williams, M.L., 1982. An analysis of the frequency distribution of SODAR derived mixing heights classified by atmospheric stability. Atmospheric Environment 16, 1209–1218. Munkel, . C., Emeis, S., Muller, . W.J., Sch.afer, K., 2003. Observation of aerosol in the mixing layer by a groundbased LIDAR ceilometer. In: Sch.afer, K., Lado-Bordowsky, O., Comeron, A., Picard, R.H. (Eds.), Remote Sensing of Clouds and the Atmosphere, Vol. VII. SPIE, Vol. 4882, SPIE Bellingham, WA, USA, pp. 344–352; Proceedings of
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the Ninth International Symposium on Remote Sensing, Agia Pelagia, Crete, Greece, 24–27 September, 2002. Myrick, R.H., Sakiyama, S.K., Angle, R.P., Sandhu, H.S., 1994. Seasonal mixing heights and inversions at Edmonton, Alberta. Atmospheric Environment 28, 723–729. . R.as.anen, J., Lonnqvist, J., Piironen, A.K., 2000. Urban boundary layer measurements with a commercial ceilometer. Proceedings of the Third Symposium on Urban Environment, 15–18 August 2000, Davis, CA. American Meteorological Society, Boston, pp. 34–35. Reitebuch, O., Emeis, S., 1998. SODAR-measurements for atmospheric research and environmental monitoring. Meteorologische Zeitschrift, N.F. 7, 11–14. Rogers, R.R., Lamoureux, M.-F., Bissonnette, L., Peters, R.M., 1997. Quantitative interpretation of laser ceilometer intensity profiles. Journal of Atmospheric and Oceanic Technology 14, 396–411.
Seibert, P., Beyrich, F., Gryning, S.-E., Joffre, S., Rasmussen, A., Tercier, P., 2000. Review and intercomparison of operational methods for the determination of the mixing height. Atmospheric Environment 34, 1001–1027. Solheim, F., Godwin, J.R., 1998. Passive ground-based remote sensing of atmospheric temperature, water vapor, and cloud liquid water profiles by a frequency synthesized microwave radiometer. Meteorologische Zeitschrift 7, 370–376. Tatarskii, V.I., 1961. Wave Propagation in a Turbulent Medium. McGraw-Hill, New York, 285pp. (English translation). Westwater, R.E., 1997. Remote sensing of tropospheric temperature and water vapor by integrated observing systems. Bulletin of the American Meteorological Society 78, 1991–2006.
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Atmospheric boundary-layer structure from simultaneous SODAR, RASS, and ceilometer measurements b Stefan Emeisa,*, Christoph Munkel . , Siegfried Vogtc, Wolfgang J. Muller . d, Klaus Sch.afera a
Institut fur Umweltforschung (IMK-IFU), Forschungszentrum Karlsruhe GmbH, . Meteorologie und Klimaforschung, Atmospharische . Kreuzeckbahnstr 19, Garmisch-Partenkirchen D-82467, Germany b Vaisala GmbH, Schnackenburgallee 41d, Hamburg D-22525, Germany c Institut fur Spurenstoffe und Fernerkundung (IMK-ASF), Forschungszentrum . Meteorologie und Klimaforschung, Atmospharische . Karlsruhe GmbH, Postfach 3640, Karlsruhe D-76021, Germany d . Niedersachsisches Landesamt fur Hannover, Gottinger Str. 14, Hannover D-30449, Germany . . Okologie, . Received 17 February 2003; received in revised form 11 August 2003; accepted 15 September 2003
Abstract A comparison of the determination of boundary-layer structures by a SODAR, by a RASS, and by a ceilometer is presented. One important structure is the mixing-layer height (MLH). The comparison is focused on 3 days with an evolution of a convective boundary layer over a larger city in Germany. The three instruments give information that partly agree and partly complement each other. By this, a picture of the diurnal evolution of the vertical structure of this urban boundary layer is presented. The ceilometer gives information on the aerosol content of the air and the RASS provides a direct measurement of the vertical temperature distribution in the boundary layer. The RASS and the ceilometer add information on the moisture structure of the boundary layer that is not detected by the SODAR. On the other hand this comparison validates known techniques by which the MLH is derived from SODAR data. Especially the temperature information from the RASS agrees well with lifted inversions derived from the analysis of the SODAR data. The ceilometer, being the smallest instrument, has a potential to be used in future MLH studies. r 2003 Elsevier Ltd. All rights reserved. Keywords: SODAR; RASS; Ceilometer; Remote sensing; Urban boundary layer; Mixing-layer height
Abbreviations: ABL, Atmospheric boundary-layer; CBL, Convective boundary-layer; MLH, Mixing-layer height; PM2.5, Particulate matter smaller than 2.5 mm in diameter; PM10, Particulate matter smaller than 10 mm in diameter (includes PM2.5); SBL, Stable boundary-layer; FM-CW, Frequency-modulated continuous-wave; FTIR, Fourier-transform infrared spectroscopy; LIDAR, Light detection and ranging; MWR, Microwave radiometer; RADAR, Radio detection and ranging; RASS, Radio acoustic sounding system; SODAR, Sound detection and ranging; WTR, Wind-temperature-radar; AFO2000, Atmospheric research programme of BMBF; BMBF, German Federal Ministry of Education and Research, Bonn, Germany; IMK-ASF, Institute for Meteorology and Climate Research—Atmospheric trace substances and remote sensing, Karlsruhe, Germany; IMK-IFU, Institute for Meteorology and Climate Research—Atmospheric Environmental Research, Garmisch-Partenkirchen, Germany; METEK, Meteorologische Mes. Lower Saxony Agency for Ecology, Hannover, Germany. stechnik GmbH, Elmshorn, Germany; NLO, *Corresponding author. E-mail addresses: [email protected] (S. Emeis), [email protected] (C. Munkel), . [email protected] (S. Vogt), [email protected] (W.J. Muller). . 1352-2310/$ - see front matter r 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2003.09.054
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1. Introduction The vertical structure of the atmospheric boundarylayer (ABL) has considerable influence on meteorological and environmental issues. It affects, e.g. near-surface pollutant concentrations, the vertical profiles of mean wind velocity, and the turbulent vertical exchange of momentum, heat, moisture, and other admixtures. Key parameters in describing the ABL are its depth and its dynamical and thermal structure. The top of the daytime ABL is frequently marked by an inversion, the nighttime ABL is often stably stratified over its full depth. Thus, their tops can be found by analysing the vertical temperature profile. In case of windy and cloudy weather neutral thermal stratification prevails and we have a more smooth transition from the boundary-layer to the free atmosphere. This latter condition is usually not connected with critical air pollution episodes. The depth of the usually well-mixed ABL (mixinglayer height, MLH) is needed in a variety of applications. Among these are the use of mass-consistent wind field models that determine the flow field from a few selected wind measurements, dispersion models that calculate the dilution of emitted substances in the ABL, prognostic models for the forecast of fog and clouds, advanced numerical flow models that need MLH for the scaling of ABL-quantities, and retrieval schemes that compute atmospheric and chemical parameters from satellite measurements. Also the conversion of atmospheric aerosol optical thicknesses from remote sensing into local air quality information needs the knowledge of MLH (Dandou et al., 2002). Albeit information on MLH is frequently needed no unique procedure for the determination of this height exists (Seibert et al., 2000). Because it is very difficult to yield a sufficient temporal capture of atmospheric variables that indicate MLH by air-borne instruments (balloons, aircraft, etc.) the use of ground-based remote sensing instrumentation is challenging. The use of data from satellites is hampered by their low vertical resolution, by visitation frequency, and by potential influences from cloud cover. Relying on ground-based remote sensing on the other hand limits the choice of the parameters that can be monitored. Fig. 1 indicates working frequencies and possible targets for ground-based remote sensing devices (see list of abbreviations). Acoustic remote sensing with a SODAR yields the vertical wind profile from a Doppler shift analysis of the returned signal and the vertical profile of the temperature structure parameter from the strength of the returned acoustic signal. Optical remote sensing with a LIDAR or a ceilometer allows a calculation of an aerosol profile from the strength of the returned laser signal. A RASS can detect the speed of a sound wave and thus the temperature profile after a possibly necessary correction for the (vertical) wind
speed. Additionally, the strength of the returned electromagnetic signal from this instrument depends mainly on the humidity structure parameter. Height allocation is done by analysing the travel time of the signal for the SODAR, the LIDAR, and the ceilometer or by analysing the frequency shift between the transmitted and the received signal for the RASS. Considerable experience already exists in measuring MLH with a SODAR (for a summary, e.g., see Beyrich, 1997). Main deficiency of this instrument is its limited range and the reduced data availability in special weather situations (especially in near-perfectly adiabatically stratified boundary layers in the afternoon). Here, in this study, acoustic remote sensing with a SODAR will be compared to optical remote sensing with a ceilometer and radio-acoustic remote sensing with a RASS. The objectives of the study are a contribution to the validation of SODAR measurements by using other remote sensing information, a better temporal coverage of ABL structure information, and a comparison of the instruments to determine which instrument is most suited to detect which ABL structures.
2. Determining the vertical layering of the ABL by remote sensing Beyrich (1997) and Seibert et al. (2000) give an overview over means to determine one of the key parameters of the ABL, the MLH. The derivation of MLH from radiosonde temperature profile data is the oldest method. Starting with Holzworth (1964) various schemes have been proposed. An actual example, the monitoring of the annual variation of MLH from daily lateafternoon radiosonde ascents is presented in Freedman et al. (2001). They find the maximum MLH in the northeastern US in late spring just before the growing season starts. But this method is only appropriate to find MLH for the time of the sounding but not to detect the diurnal course of MLH. Further, the method is limited mainly to convective conditions. A critical discussion of this approach can be found in Lokoshchenko (2002). Remote sensing can fill this gap. But the interpretation of remote sensing data may be ambiguous because other features than the thermal stratification of the air . influence the data, too (Bosenberg and Linn!e, 2002). Therefore the comparison to radiosonde data or the intercomparison of different remote sensing techniques may help to identify the relevant structures of the ABL. Lokoshchenko (2002) has recently compared MLH from SODAR and radiosonde data using Holzworth’s method, which revealed the difficulties of determining and comparing MLH from these two types of data. He therefore proposes to use the instability energy as an alternative parameter for the characterisation of the convective boundary layer. A likewise study has been
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Fig. 1. Working frequencies of ground-based remote sensing techniques for atmospheric sounding (first line: active devices, second line: passive devices). Upper bars: electromagnetic spectrum, lower bar: acoustic spectrum. Visible light is indicated by the inserted rainbow colours. Vertical grey bars give typical size range of atmospheric aerosol, rain drops, and (near-surface) turbulent motion (modified from Emeis, 2000).
made by Keder (1999) who compared radiosonde data evaluated following Myrick et al. (1994) with the built-in MLH-determining routine of a REMTECH SODAR. Here the comparison was even more disappointing, but mainly due to errors in the automatic routine supplied by the SODAR manufacturer. Coulter (1979) has compared the temperature profile method with LIDAR and SODAR measurements. In early morning and late afternoon hours the LIDAR data systematically yielded higher CBL tops than the SODAR data. The data from both remote sensing methods always delivered higher CBL tops than the evaluation of the temperature profile. Due to Coulter (1979), this is because particulates mix to larger heights than the top of the adiabatic temperature profile, while temperature fluctuations exhibit an increase in the entrainment zone above the top of the adiabatic temperature profile but below the maximum height of particulate mixing. Devara et al. (1995) have compared a LIDAR and a SODAR in a study on the nocturnal SBL. They found a principal agreement in the results. Beyrich . and Gorsdorf (1995) have used two instruments, a SODAR and a wind profiler simultaneously for 5 weeks in order to determine the MLH. They found that on days with the development of a convective boundarylayer both instruments yielded comparable results during the morning hours. A RASS and two LIDARs have been compared with radiosonde data in Marsik et al. (1995). They found strong deviations between the MLH from the three instruments around 8:00 local time, a better coincidence around noon, and again increasing deviations in the afternoon.
Seibert et al. (2000) only considered active remote sensing devices. Westwater (1997) describes also passive microwave radiometers (MWR) that yield temperature profiles and inversion heights for the lowest 1000 m of the atmosphere with reasonable accuracy. Solheim and Godwin (1998) present temperature profiles from MWR up to 10 km above ground. Elevated inversions are not represented very well in their retrievals. Since the preparation of the review by Seibert et al. (2000) optical remote sensing has made considerable progress. Ceilometers originally designed just to report cloud base heights have become available also for atmospheric profiling (Rogers et al., 1997; R.as.anen et al., 2000; Munkel . et al., 2003). They have an improved vertical resolution (now about 15 m) and a much smaller lower detection range limit (now about 30 m above ground). They are eye-safe and can be operated automatically. The availability of a RASS like the WTR of IMK-ASF allows the direct measurement of the vertical temperature profile. Therefore the determination of ABL structure with SODAR and other remote sensing techniques is reconsidered here.
3. Experimental set-up 3.1. Site In the framework of the project Validation of instruments for environmental policies (VALIUM) within the program AFO2000 (Atmospheric Research 2000) of the German Federal Ministry of Education and
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Research (BMBF) long-term meteorological and air quality measurements have been made in the street . canyon ‘‘Gottinger Strasse’’ in the town of Hannover in Northern Germany. This street canyon runs in front of the main building of the Lower Saxony Agency for . At the highest part of the roof of this Ecology (NLO). building (about 43 m above ground level) an automatic . is available that meteorological station, run by the NLO, delivers wind and temperature information at roof level above the street canyon. The horizontally averaged roughness length of the more or less urban area within a radius of 10 km is about 1 m. In order to monitor the ambient flow conditions (wind profile and MLH) near this street canyon a SODAR has been placed about 550 m upstream (with respect to the most frequent wind direction, which is Southwest) of the street canyon and the roof-top station on the grounds of a larger factory away from housing areas. The ceilometer has been placed about 20 m above ground level . building that is connected to the on the roof of a NLO one adjacent to the street canyon. The distance to the roof-top station is about 30 m. The RASS has been operated 150 m away from the roof-top station in the . buildings. The intensity of the backyard of the NLO acoustic sound emission by the RASS had to be limited due to the people working in a near-by office building. SODAR, RASS, ceilometer, and roof-top station were positioned along an almost straight line that is running from southwest to northeast. The first campaign during that all three remote sensing instruments were available was from 26 April to 12 May 2002. A second campaign was from 19 October to 1 November 2002. 3.2. Instrumentation 3.2.1. SODAR The METEK DSD3 7 mono-static Doppler SODAR (Reitebuch and Emeis, 1998) has three antennas (see Fig. 2a) with seven sound transducers (i.e. a device that serves both as a loudspeaker and as a microphone, depending on the phase of the measurement cycle) each, working at about 1500 Hz. The instrument is optimised for long-range detection up to 1300 m above ground in ideal conditions without external noise sources. The SODAR records the intensity of acoustic backscatter of the air S; that is proportional to the structure parameter of the acoustic refractive index CN2 ; which in turn mainly depends on the temperature structure parameter CT2 (Tatarskii, 1961). The measurement fails in case of stronger rain or snow, perfect adiabatic conditions due to strong thermal mixing, and large noise from the surroundings. Only inhomogeneities in the temperature field in the order of Dx ¼ lsound =2 contribute to S: Normally this is within the ‘inertial subrange’ of the turbulence spectrum. Therefore S contains
information on the structure of the turbulence in the boundary-layer, but not on the sign of the vertical temperature gradient. In case of a vanishing vertical gradient of potential temperature the backscatter intensity of the air is low even if there is still turbulent motion (see explanation for code ‘7’ in Maughan et al., 1982). During weather situations with weak winds and strong thermal inversions the contribution of the mean vertical temperature gradient to S can be at least as large as the contribution from the turbulent motion (Beyrich, 1997). This allows the detection of stable layers at night. The range of the instrument with respect to sound reflectivity is usually larger than with respect to the identification of a Doppler shift.
3.2.2. RASS The RASS used here is called a wind-temperatureradar (WTR) because it works in the RASS mode and the clear-air mode. It is a prototype instrument designed and built by Dr. G. Peters from the Max-Planck Institute for Meteorology and the Meteorological Institute of the University of Hamburg, Germany (see Figs. 2b and 3). All measurements are based on the backscattering of electromagnetic decimetre waves in the atmosphere. Waves are scattered either at microturbulent fluctuations of the atmospheric refraction index associated with fluctuations of temperature and humidity, or at artificial fluctuations of the refraction index, which are generated by the transmission of appropriate sound pulses. The WTR measures the air temperature by detecting the propagation of sound pulses with a RADAR. The temperature calculation from the sound speed is corrected for the vertical wind speed. In the clear-airmode the WTR observes the electromagnetic structure parameter of the refractive index CN2 ; which in contrast to its acoustic counterpart is mainly dominated by moisture fluctuations but much less by temperature fluctuations. The WTR has a five-beam geometry with two bistatic radiofrequency (rf) and one acoustic (ac) antenna. The ac antenna is a 1:2 scaled copy of the rf-array to match the rf-beam at the Bragg-wavelength. The rf antenna emits continuous waves that are frequency-shifted with a saw tooth modulation (FM-CW Doppler Radar) in order to provide a high average transmitted power and a fine range gate resolution. Contrary to a conventional pulse Radar the height resolution is not calculated from the travel time of the rf waves but is taken proportional to the frequency shift between the transmitted and received signal. The sound source is also used to estimate the wind components in the so-called RASSmode. This is possible because the ac beam is simultaneously shifted in the same four oblique beam directions like the rf beam. The combination of the
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Fig. 2. (a) METEK DSDR3 7 SODAR. Instrument height is about 4 m. (b) METEK WTR. Instrument height is about 4 m. (c) Vaisala CT25K ceilometer. Instrument height is about 1 m.
RASS mode and the clear air mode allows the derivation of two independent and redundant wind profiles. The sound speed wa depends on the virtual acoustic temperature Tvs ¼ Tð1 þ 0:51qÞ with the specific moisture q (Kaimal and Businger, 1963). The virtual acoustic temperature is defined as the temperature of dry air in which the sound speed is equal to the sound speed in the real (moist) air Tvs ¼ ðM=gRÞw2a ;
where M is the molecular weight of the air, g is the ratio of the specific heats and R is the universal gas constant. Technical data are shown in Table 1. As can be seen in Fig. 3 the WTR can be rotated on its trailer, and the distance separating the acoustic antenna from the rf antennas can be varied by means of a sliding boom, allowing the acoustic source to be positioned for maximum efficiency upwind of the rf antennas in dependence on wind speed and wind direction.
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Fig. 3. Schematic bird’s eye view of the WTR. Table 1 Technical data of the WTR (left column: electromagnetic waves, right column: acoustic waves) Frequency Power Antenna aperture Antenna gain Beam direction Antenna type Number of range gates Width of range gate Averaging time per beam Averaging time for wind and temperature
1290 MHz 6400 W 3.2 m 3.2 m 33.5 dB 78.5 off zenith in N–S–W–O 8 8 pyramidal horns 78 60 m (variable) 10 s (variable) 30 min (variable)
3.2.3. Ceilometer The Vaisala single-lens ceilometer CT25K (see Fig. 2c, R.as.anen et al., 2000) measures the optical backscatter intensity of the air at a wavelength of 0.9 mm (near infrared). Its InGaAs laser diodes are pulsed with a repetition rate of 5.57 kHz. The pulse energy is 1.6 mJ, the 50% pulse width is 100 ns. The lens has a focal length of 377 mm and an effective diameter of 145 mm. Laser beam full divergence and field-of-view divergence of the receiver are 1.4 mrad each. Because of the monostatic optical system and the small divergence multiple scattering effects are negligible, Mie scattering with scattering angles between 179.9 and 180.1 is dominant and the following simplified form of the lidar equation can be used for interpreting the backscatter profiles: cDt AZOðxÞ Pðx; lÞ ¼ bðx; lÞt2 ðx; lÞ; P0 2 x2
2700–3000 Hz 320 W 1.6 m 1.6 m 33.5 dB 78.5 off zenith in N–S–W–O 8 8 exponential horns 24 60 m (variable) 10 s (variable) 30 min (variable)
where Pðx; lÞ is the power recorded by the receiver detector, c is the speed of light, Dt is the laser pulse duration, P0 is the power of emitted laser pulse, A is the area of the receiver, Z is the efficiency of the receiver, OðxÞ is the range-dependent overlap integral between the transmitted beam and the field of view of the receiver (0pOðxÞp1), bðx; l) is the backscatter coefficient, tðx; lÞ is the transmittance of the atmosphere between the measuring system and the scattering volume, l is the wavelength, x is the range from the measuring system to the scattering volume. The ceilometer does not report raw signals, but preprocessed backscatter intensity profiles representing the last two terms in the lidar equation, bðx; lÞt2 ðx; lÞ; with a range of 2 km and a vertical resolution of 15 m. Every 15 s a profile accumulated over 65,536 laser pulses is reported. Automatic laser power control and
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temperature compensation of the receiver detector provide a long-term stability of the factor P0 Z of 715%. The backscatter intensity depends mainly on the particulate concentration in the air. As the size of many particles varies with their moisture content, the reflectivity is influenced by atmospheric humidity, too. Clouds and precipitation inhibit measurements. Enhanced particulate concentrations can be either due to horizontal advection, due to strong thermal convection, or due to local chemical reactions forming secondary particles. In case of chemical reactions this usually points at a stable stratification of the air because otherwise mixing would dilute the chemically produced particles. The performance of the CT25K ceilometer is sufficient for analysing boundary-layer structures. Compared to more sophisticated LIDAR systems commonly used for these investigations it has several special features. Some of these are favourable when long-term studies involving several stations are considered. These features include the low first range gate (15 m, due to the identity of the optical axes of transmitter and receiver and due to relatively low emitted power), its low maximum range (around 2000 m, due to the low emitted power), its ability to operate eye-safe and maintenance-free for several years in any climatic environment with just some regular window cleaning, and its comparably low price.
4. Comparison of SODAR, WTR, and ceilometer measurements Seventeen days in spring and 14 days in autumn are principally available for comparison. From the days in spring only the last six showed an enhanced convective activity. The first 11 days were dominated by cyclonic activity over the British Isles and the North Sea and very windy weather. The longest dry period (a prerequisite for the evaluation of the ceilometer data) was from 8 to 10 May 2002. Inspecting the SODAR data lifted inversions were observed on 6, 9, and 10 May and very marginally on 2 May. From the 14 days in autumn 12 days were at least partly rainy so that the ceilometer data are not usable. Only two single days, 20 and 31 October remain for a complete comparison. The first of these days showed only weak convective activity, the second one had the passage of a weak cold front without rain in the afternoon. On 21 October and 1 November lifted inversions are clearly visible from the SODAR backscatter data although the ceilometer data indicate that it was continuously raining. On both days the height of the lifted inversions decreased during the day until they reached the ground. Warm fronts passed the measuring site on these days (also obvious from the WTR temperature time-height cross sections). Thus, these structures were no inversions but the frontal surfaces of
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the warm fronts. A lifted inversion with rain not connected to a warm front occurred in the first half of 8 May. We have chosen the period from 8 to 10 May 2002 for presentation because these three consecutive days reveal all relevant boundary layer structures and inversions. During these days all instruments operated reliably. This period also includes the above-mentioned case with a lifted inversion during rain. Fig. 4 shows the meteorological readings from the roof-top station. At these days the wind came from southeasterly directions, the wind speed varied between 2 and 3 m/s at night and 5 and 6 m/s in the afternoons. On the evening of 10 May, a weak cold front passed the measurement site. After the passage of the front the wind turned to northwesterly directions. At these days sunrise was around 3:00 UTC, sunset around 19:41 UTC. The following discussion will be illustrated by coloured pictures of the backscatter and the temperature distribution (Figs. 5–7) seen by the three instruments in order to demonstrate the different abilities of these instruments to detect ABL structures. The displayed backscatter intensity is corrected for distance but for the SODAR and the WTR it is given in arbitrary units only. The ceilometer data is calibrated (see Section 3.2.3). It is not the purpose of the present investigation to give statistics of MLH for a longer period. These will be published elsewhere later. The following investigation extends only to a height of 1000 m above ground. This choice has been made because the range of the WTR temperature measurements and the range of the SODAR are limited to this height. The ceilometer and the WTR (in the clear-air mode) return meaningful signals from heights of more than 2000 m. The comparison is based on 30 min averages in the case of the SODAR and the WTR (computed from 12 s data for the WTR) and 15 s
. at 43 m above Fig. 4. Data from the roof-top station of NLO ground level for 8–10 May 2002. Thick black line: temperature in C (left-hand scale), thin black line: wind speed in m/s (lefthand scale), dotted line: wind direction in degrees (right-hand scale).
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Fig. 5. Upper frame: SODAR acoustic backscatter and horizontal winds (scale in the third frame), second frame: WTR temperature in C, third frame: WTR electromagnetic backscatter and horizontal winds, lowest frame: ceilometer optical backscatter in 104/sr km for 8 May 2002. Y-axis: height above ground in m, X-axis: time in UTC. Sunrise is at 03:00 UTC, sun set at 19:41 UTC.
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Fig. 6. Upper frame: SODAR acoustic backscatter and horizontal winds (scale in the third frame), second frame: WTR temperature in C, third frame: WTR electromagnetic backscatter and horizontal winds, lowest frame: ceilometer optical backscatter in 104/sr km for 9 May 2002. Y-axis: height above ground in m, X-axis: time in UTC. Sunrise is at 03:00 UTC, sun set at 19:41 UTC.
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Fig. 7. Upper frame: SODAR acoustic backscatter and horizontal winds (scale in the third frame), second frame: WTR temperature in C, third frame: WTR electromagnetic backscatter and horizontal winds, lowest frame: ceilometer optical backscatter in 104/sr km for 10 May 2002. Y-axis: height above ground in m, X-axis: time in UTC. Sunrise is at 03:00 UTC, sun set at 19:41 UTC.
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averages in the case of the ceilometer data. The vertical resolution is 15 m with the ceilometer data, 25 m with the SODAR data, and 60 m with the WTR data. Due to fixed echoes from near-by buildings the lowest reliable measurement height is 60 m above ground for the SODAR and 160 m above ground for the WTR in case of backscatter. As the measurements in the RASS mode are not affected by ground clutter the WTR can measure wind and temperature down to 100 m height. The ceilometer with its well-focussed beam has also no ground-clutter problems. The ragged top of the SODAR data in Figs. 5–7 is due to a regular switching between two vertical resolutions (12.5 and 25 m) and thus two different ranges (600 and 1200 m) every half hour. The uppermost image in each of the Figs. 5–7 displays the acoustic backscatter intensity (corrected for distance) and the horizontal wind vector measured by the SODAR (for a scale see the third frame below). Wind vectors can be determined only when the acoustic backscatter intensity exceeds a certain threshold, because otherwise the signal-to-noise ratio for a determination of the Doppler shift is too low. The second image shows the virtual acoustic temperature (in C) measured by the WTR in the RASS mode. This image also contains in the lowest row the virtual temperature that has been recorded at the roof-top station 43 m above ground level. Temperature rather than potential temperature is shown here because temperature inversions can be seen more clearly. Potential temperature would have been better in order to diagnose whether a layer is really well mixed or not. The third image presents the backscatter seen by the WTR in the clear-air mode and the horizontal wind vector measured by this instrument. The lowermost image shows the optical backscatter intensity obtained with the ceilometer. Dark blue areas above dark red areas indicate missing data because in this case the light beam has been totally absorbed in the cloud layer in between. Each figure presents data for 1 day. ABL structures analysed from the SODAR data have been entered into the plots as full lines. Dotted lines represent sharp gradients in the optical backscatter recorded by the ceilometer that match with echoes from the clear-air mode of the WTR. The analysis of the structures in the SODAR data has been made according to the MLH criteria given in Beyrich (1997) and Seibert et al. (2000). At daytime the MLH has been marked at the lower edge of a lifted secondary backscatter maximum. At night-times the upper edge of the surface-based backscatter maximum is marked as the top of the SBL. If a backscatter maximum appears adjacent to the ground during daytimes, it was not marked because in this case the high backscatter indicates a super-adiabatic surface layer due to the heating of the ground by incoming solar radiation.
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The marking of the structures and inversions in the Figs. 5–7 has mainly been done for an easier intercomparison between the four frames within one figure. The figures demonstrate clearly that backscatter intensities for acoustic, electromagnetic, and optical waves differ considerably. The WTR detects in its clearair mode several structures that do not appear in the SODAR data. While the maximum acoustic backscatter intensity is nearly always close to the ground (except for lifted inversions), the maximum electromagnetic backscatter is most frequently between 500 and 1000 m above ground. The most intense backscatter is observed here during daytime unstable stratification of the atmosphere extending over a quite large height range of several hundreds of meters. In the following several boundarylayer features detected by the three instruments are described in more detail: 4.1. Lifted temperature inversions Elevated secondary maxima in the acoustic backscatter are interpreted as lifted inversion. Such features, lasting for at least a few hours, occurred during this instrument intercomparison campaign on 2, 6, 8, 9, and 10 May, on 19 and 21 October and on 1 November 2002. In Figs. 5–7 they can clearly be identified from the acoustic backscatter and the WTR temperature on 8 May from 0:00 to 14:00 UTC, on 9 May from 1:00 to 9:00 UTC (although there is a second inversion at about 300 m until 6:00 UTC that is detectable only from the temperature distribution), and on 10 May at 2:00–7:00 UTC. During most of the time the lifted inversion is visible from a wind shear, too. Below this inversion the wind is weaker and has backed due to the surface friction. On 9 and 10 May the layer below this inversion is additionally characterised by an enhanced aerosol content as seen from the ceilometer data. On 8 May low clouds inhibit the ceilometer to have a look at this inversion. The electromagnetic backscatter intensity also depicts these inversions. But here, the increased backscatter extends several hundreds meters above the inversion while the elevated maximum of the acoustic backscatter is usually o100 m deep. Especially noteworthy is the decoupling of the winds below and above the temperature inversion between 6:00 and 7:00 UTC on 10 May. During this short episode a temperature inversion starts at 200 m above ground with an increase of the air temperature from 15 C to 19 C within the next 100 m above this level. Above this inversion at 6:30 and 7:00 UTC the wind has turned to near southerly directions compared to the more southeasterly wind direction before and after this episode. This turning is due to the reduced turbulent momentum transport through this strong inversion. Due to the higher vertical resolution this phenomenon is more
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clearly to be seen from the SODAR winds than from the WTR winds. 4.2. Convective boundary-layers The development of a deeper daytime convective boundary-layer during the instrument intercomparison was observed on 7, 8, 9, 10, and 12 May only. During the autumn period, convection was generally weak because of the season and the rainy weather. At all 3 days considered in Figs. 5–7 a well-mixed convective boundary layer (CBL) is developing. This CBL erodes the existing—above mentioned—temperature inversions and grows beyond 1000 m on 8 May at 14 UTC and on 10 May around noon. On 9 May the CBL top maximum height is between 700 and 800 m above ground. The secondary acoustic backscatter intensity maxima marking the CBL top are weaker than the ones that indicated the lifted temperature inversion discussed in the previous subsection. On the other hand, the electromagnetic backscatter from the CBL top is stronger than from the lifted temperature inversions. On 9 and 10 May this CBL can also be detected from an increased aerosol content. On 8 May mist and clouds prevent a clear identification of aerosol concentrations from the ceilometer data. Close to the ground high acoustic backscatter intensities can be found during well-developed CBLs. This high reflectivity obviously marks an over-adiabatic layer due to the strong radiative heating of the surface. Above this over-adiabatic layer the backscatter intensity is decreasing considerably before it increases again near the top of the CBL. The electromagnetic backscatter intensity in a CBL increases well with height. The maximum intensity is reached just above the inversion in the same height where the acoustic backscatter has its weak secondary maximum, too. Above this maximum the electromagnetic backscatter is decreasing only slowly. The most striking difference to the acoustic backscatter is that the high intensity of the electromagnetic backscatter in the upper part of the CBL and at the inversion can be traced until the evening whereas the acoustic backscatter vanishes nearly completely after 15 or 16 UTC. This happens also on 9 May where the CBL top is definitely below 1000 m. The reason for this fading of the acoustic backscatter is the vanishing vertical potential temperature gradient in a well-mixed CBL in the later afternoon (Maughan et al., 1982) when the heating from below stops. The daily maxima of sigma w (not shown) are detected in an interval between 2 h before and 2 h after this fading out near the top of the CBL. These maxima indicate turbulence and are responsible for the near adiabatic profile without any larger temperature fluctuations in this range.
4.3. Nocturnal surface inversions An intensity maximum of the acoustic backscatter close to the surface during the night is interpreted as an indication of a nocturnal stable surface inversion layer with some mechanically induced turbulence. This feature appeared in the nights to 1, 2, 9, and 10 May and in some nights of the autumn period. It can be seen in both nights covered in Figs. 5–7 from about 19 UTC in the evening to about 4–5 UTC the next morning. The wind speed at the roof-top station at 43 m above ground level never falls below 2 m/s during these two nights (Fig. 4). A temperature increase reaches up to about 500 m in both nights, as can be seen from the WTR data. In a height between 300 and 400 m a further layering of the air can be deduced from a further reduction of the intensity of the acoustic backscatter and a related turn of the wind direction. Within this surface inversion also the ceilometer detects high optical backscatter. This may be due to an increased aerosol content, but it could also be moist dust as well. On the evenings of 8 and 10 May the increases in relative humidity and in the particulate matter fractions PM2.5 and PM10 (measured at stations in the vicinity, Munkel . et al., 2003) coincide. Thus, it may be that the increase in aerosol mass is at least partially due to a humidification of pre-existing aerosol. On the evening of 9 May no such correlation can be found between relative humidity and aerosol concentrations. In the second half of the night in the stable layer between the surface inversion and the second inversion at about 300–400 m height distinct layers of enhanced aerosol content can be seen from the ceilometer data. Probably these aerosol layers have been advected. One to two hours after sun rise at 03 UTC these aerosol layers disappeared.
5. Conclusions Three different instruments that deliver five types of vertical profiles (wind and acoustic backscatter from a SODAR, wind, temperature, and electromagnetic backscatter from a WTR and optical backscatter from a ceilometer) have been brought together at one site. Lifted temperature inversions can be detected best from the intensity of the acoustic backscatter and the vertical temperature distribution. These inversions form an upper bound for the dispersion of near-surface aerosol. The SODAR can follow the CBL top only in the first half of a day. Later in the afternoon the CBL top is either out of the vertical range of the SODAR or the gradients in potential temperature become too low in order to reflect sound waves. The upper part of the CBL and the CBL top can be detected best from the
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electromagnetic backscatter. This indicates considerable moisture fluctuations in the upper half of the CBL also in the later afternoon. A considerably enhanced aerosol concentration inside the CBL can be derived from the ceilometer data. The results from the ceilometer give no indication for higher MLH than the SODAR or the WTR as had been reported by Coulter (1979) for a LIDAR. During nights a surface inversion can be identified from the SODAR data in the lowest 100 m as a maximum of acoustic backscatter intensity. This surface inversion is also clearly identifiable from an intensity maximum of optical backscatter in the ceilometer data. In the nearly isothermal layer above the surface inversion filament-like structures can be observed in the ceilometer data. In case of cloud cover and rain the ceilometer does not yield useful data on the boundary layer structure. During the other periods the ceilometer gives direct information on the vertical aerosol distribution, a quantity which is otherwise only indirectly derived from mixing conditions measured with SODAR or WTR. The comparison for the period discussed in this paper shows especially at night when mixing due to thermal instability is absent that there are considerable differences between the vertical aerosol distribution and the induced vertical structure of the ABL. This is an indication that advection of aerosol and the formation of moist haze can be important at these times. SODAR measurements afford less expense than WTR measurements. The great advantage of the WTR on the other hand is the direct observation of the vertical temperature profile. The ceilometer is the most easiest remote sensing device of the instruments considered here. The potential of a ceilometer is comparable to a single-frequency LIDAR. It has a height range of a few thousand meters, only bounded by cloud bases and precipitation. The progress in remote sensing instrumentation is bringing us closer to a more continuous observation of parts of the atmosphere that are not directly adjacent to the ground.
Acknowledgements The SODAR measurements were financed within the project VALIUM of the German Ministry of Education and Research (BMBF) under the framework program AFO2000. The ceilometer measurements were funded by Vaisala GmbH, Hamburg, the WTR by IMK-ASF of the Forschungszentrum Karlsruhe GmbH. The measurements would not have been possible without the technical and scientific support from the Nieder. . Hanns.achsische Landesanstalt fur . Okologie (NLO), over, and METEK GmbH, Elmshorn. Special thanks go . We thank Komatsu, . from NLO. to Mr. Drunkenmolle
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Germany GmbH, for the permission to use their grounds for the SODAR measurements.
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