Mixing layer height over Munich, Germany: Variability and comparisons of different methodologies

Transcription

1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 111,, doi: /2005jd006593, 2006 Mixing layer height over Munich, Germany: Variability and comparisons of different methodologies Matthias Wiegner, 1 Stefan Emeis, 2 Volker Freudenthaler, 1 Birgit Heese, 1 Wolfgang Junkermann, 2 Christoph Münkel, 3 Klaus Schäfer, 2 Meinhard Seefeldner, 1 and Siegfried Vogt 4 Received 17 August 2005; revised 23 November 2005; accepted 22 March 2006; published 1 July [1] On 4 days in summer and winter the mixing layer height over the municipal area of Munich, Germany, was determined by several remote sensing instruments and in situ probes. The main motivation was to obtain information on aerosols, and therefore we decided to understand the mixing layer as that layer where most of the locally produced aerosols are concentrated. In this paper we wanted to investigate the potential of the quite different methodologies which depend on measurements of aerosol properties and those which do not. The operation of two lidars, a ceilometer, a wind-temperatureradar, a sodar, radiosondes, and aerosol probes onboard of a microlight aircraft allowed such a thorough intercomparison. As the instruments were located at different sites, the horizontal homogeneity of the mixing layer could also be observed. It was found that the agreement between the different methodologies is very good as long as the mixing layer height does not exceed approximately 1 km, which is the common measurement range of all instruments. In summer, however, the mixing layer can reach 2 km and more, so that the lidar turns out to be the most capable remote sensing technique. Another advantage of the lidar is the possibility to clearly derive the internal structure of the mixing layer. The latter is important in cases when simple parameterizations assume vertical homogeneity of aerosol properties within the mixing layer. On the other hand, lidars are quite expensive and require a trained operator. As a conclusion, the development of unattended working lidars including automated data evaluation should be fostered. From the limited data set it was found that the mixing layer height in Munich did not change more than approximately 100 m over a horizontal distance of around 50 km. If this finding can be confirmed by further measurements, the area of Munich is a good test bed for the validation of aerosol retrievals from satellite data with medium spatial resolution and for the validation of the numerical treatment of aerosols in mesoscale chemistry transport models. Citation: Wiegner, M., S. Emeis, V. Freudenthaler, B. Heese, W. Junkermann, C. Münkel, K. Schäfer, M. Seefeldner, and S. Vogt (2006), Mixing layer height over Munich, Germany: Variability and comparisons of different methodologies, J. Geophys. Res., 111,, doi: /2005jd Introduction [2] Aerosol particles are one of the key constituents of the Earth s atmosphere as they influence atmospheric processes 1 Meteorologisches Institut, Ludwig-Maximilians-Universität, Munich, Germany. 2 Institut für Meteorologie und Klimaforschung, Atmosphärische Umweltforschung (IMK-IFU), Forschungszentrum Karlsruhe GmbH, Garmisch-Partenkirchen, Germany. 3 Vaisala GmbH, Hamburg, Germany. 4 Institut für Meteorologie und Klimaforschung, Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF), Forschungszentrum Karlsruhe GmbH, Karlsruhe, Germany. Copyright 2006 by the American Geophysical Union /06/2005JD in many aspects: They modify the atmospheric radiation budget by scattering and absorption, the water cycle by changing cloud formation and lifetime, and they govern heterogeneous chemistry [e.g., Intergovernmental Panel on Climate Change, 2001; Anderson et al., 2003a; Hauck et al., 2004]. Recently, aerosols also came into the focus of studies of air quality and health issues [e.g., Li et al., 2003; Gertler, 2005]. [3] The impact of aerosols is controlled by their macrophysical properties (e.g., spatial distribution), their optical properties (e.g., extinction coefficient, single scattering albedo) and microphysical properties (e.g., size distribution, mass concentration). The situation is in particular complicated because all these parameters vary in different scales of time and space [e.g., Hess et al., 1998; Dubovik et al., 1of17

2 2002]. As a conclusion, it is only possible to obtain a complete set of aerosol information by applying different observation systems and model calculations [see also, e.g., Anderson et al., 2003b]. [4] Observations are based on several contributions: Ground-based observations include highly sophisticated and specialized in situ or remote sensing instruments that measure one or another parameter with very high accuracy and temporal resolution. In most cases they are quite expensive with respect to manpower, so they are only operated during limited field campaigns or in small networks. Automatically operating stations [e.g., Chen et al., 2001; Lagrosas et al., 2004)], e.g., for air quality surveillance, run continuously but provide only point measurements and are often limited in their scientific output. Progress is achieved by ground based networks such as AERONET [e.g., Holben et al., 1998] or EARLINET [e.g., Bösenberg et al., 2003; Papayannis et al., 2003] and the homogenization of data sets (e.g., EMEP [see Lazaridis, 2001]). Supplementary, aerosol information is obtained from satellite sensors that can provide quasi-continuous and quasi-global observations, but they are, due to physical and instrumental restrictions, limited to a relatively poor characterization of aerosols: The main product of satellite retrievals is the aerosol optical depth [e.g., Stowe et al., 1997; Kaufman et al., 2002]. As the retrievals rely on several assumptions on aerosols, the Earth s surface, and atmospheric properties, their accuracy is limited especially over land surfaces, and consequently, validation of these products is indispensable. [5] In parallel to observations, chemistry transport models and general circulation models are used to describe aerosol interactions with the atmosphere [e.g., Bessagnet et al., 2004; Grell et al., 2005]. In the present state, aerosol parameterization is, however, relatively simple and input data are insufficient. Therefore validation is also required [e.g., Adams et al., 1999; Chin et al., 2002; Holtslag, 2003; Hodzic et al., 2004; Cuxart et al., 2006]. [6] In this context, two issues are important. First, it should be stressed that the merging of the different sources of information requires a strict assessment of their accuracy. Second, investigations of sampling errors are required: For example, if ground-based point measurements are compared with a satellite pixel of several tens of square kilometers or model results averaged over typical grid sizes, one has to know about the spatial homogeneity and the temporal variability of the observed quantity. [7] In this paper we want to contribute to both topics. We investigate the homogeneity of the aerosol distribution in terms of a quantity that can be assessed by satellites, models, and ground-based instruments of different complexity. We decided to identify the aerosol distribution as the height of the mixing layer. As test bed we have selected the municipal area of Munich and its surroundings. In the framework of the campaign ICAROS-NET [Sarigiannis et al., 2002; Schäfer et al., 2004] several instruments and observation techniques were implemented at different sites in and around Munich: This concept allows intercomparison of different observation methods and investigation of the variability of the aerosol distribution. The large set of deployed instruments including lidars, sodar, radar, ceilometer, radiosondes, and different in situ aerosol probes on board a microlight aircraft is an excellent opportunity for intercomparisons and the assessment of the potential and the limitations that reach far beyond already existing studies. This intercomparison and the discussion of the structure of the mixing layer over Munich for a limited set of days are the focus of this paper (section 4). Before this, we briefly describe the instruments (section 2) and the different methodologies to determine the mixing layer height (section 3). A summary concludes this paper. 2. Observations [8] Our investigations are based on data sets from the ICAROS-NET campaign. This campaign was conducted in two periods, one in summer 2003 (10 May till 30 May) and one in winter 2003 (27 November till 15 December). In this paper, we focus on 2 days, namely, 16 and 23 May, of the summer campaign, and 2 days of the winter campaign (8 and 9 December). With this selection we cover the typical meteorological conditions relevant for aerosol remote sensing: sunny days in summer and winter and a partly cloudy situation. A survey of the used systems is given in Table 1. Note that all distances are given with respect to the site of the Meteorological Institute (MIM) in central Munich. In addition to the ICAROS-NET instrumentation, the regular radiosonde ascents by the German Weather Service (DWD) at Oberschleißheim were also made available. [9] For clarification, the measurement sites are indicated in Figure 1. The flight tracks of the microlight aircraft of 8 December (solid line) and 9 December (dashed line) are also included together with circles of 10 to 40 km around the MIM. The whole area of investigation is characterized by flat terrain, the altitude gradually increases from north (Frankendorf, 450 m above mean sea level) to south (Oberpfaffenhofen, 580 m). The city limits of Munich have a diameter of roughly 10 km, outside there are smaller towns and mostly agricultural areas or forests (south of Munich), extended industrial areas do not exist. [10] The physical basis of the deployed instruments is quite different: The lidars and the ceilometer are based on backscattering of light pulses from aerosols (and air molecules) in the shortwave spectral region. The sodar and the wind-temperature-radar (WTR) exploit the backscattering of acoustic waves on inhomogeneities of the refractive index of air. The WTR also uses backscattering of radio frequencies. In contrast to these remote sensing techniques, the microlight aircraft carries in situ instrumentation to measure the vertical profiles of aerosol properties, and the radiosondes provide profiles of temperature and humidity at a predefined location. This diversity of methods provides a unique chance to compare methodologies to derive the mixing layer height, henceforward referred to as z ml. [11] A brief description of the instruments in view of the z ml measurement is given below. The potential to determine further meteorological relevant parameters, e.g., wind velocity, humidity fields or trace gas concentrations is not considered in this context Lidars [12] The aerosol lidar systems, MULIS and POLIS, were set up by the MIM [Wiegner et al., 1995; Heese et al., 2002]. 2of17

3 Table 1. Instruments and Their Sites Used in This Study a System Operator Site Coordinates Distance/Direction Lidar MULIS MIM Munich N, E 0 km Lidar POLIS MIM from Maisach to Ebersberg N, E 24.5 km/west N, E 30.0 km, east Ceilometer IMK-IFU Frankendorf N, E 37.3 km/northeast Wind-temperature-radar IMK-ASF Lohkirchen N, E 36.3 km/northeast Sodar IMK-IFU Fürstenfeldbruck N, E 23.0 km/west Airborne in situ IMK-IFU Fürstenfeldbruck N, E 23.0 km/west Ismaning N, E 13.9 km/northeast Radiosonde DWD Oberschleißheim N, E 10.8 km/northwest a MIM is Meteorological Institute of the Ludwig-Maximilians-University; IMK-IFU is Institute for Meteorology and Climate Research, Atmospheric Environmental Research; IMK-ASF is Institute for Meteorology and Climate Research, Atmospheric Trace Compounds and Remote Sensing; and DWD is German Weather Service. [13] MULIS is a scanning backscatter lidar emitting pulses at three wavelengths, namely, 1064, 532, and 355 nm. The raw data have a temporal resolution of 0.1 s and a spatial resolution of 3.75 m. Time averaging and smoothing along the line of sight can be adjusted individually by the user according to the meteorological condition. Data are typically averaged over 500 shots or less, resulting in a temporal resolution of less than a minute. Of special advantage for observations of the mixing layer is the potential of MULIS to scan: It allows measurements at different elevation angles including quasihorizontal measurements. With a measuring range along the line of sight starting at about 250 m, these measurements can be combined to determine aerosol profiles reaching down to almost surface values. The lidar was located at the roof platform of the MIM (539 m altitude). [14] In the framework of the summer campaign of ICAROS-NET the second backscatter lidar, POLIS, was operated at 355 nm only; the line of sight was vertically oriented. The design of the optical receiver of POLIS allows the retrieval of aerosol profiles down to approximately 100 m altitude. The raw data s resolution is 7.5 m and 0.05 s, respectively. Because of its small size, low weight, and low power consumption, POLIS could easily be integrated in a van to perform measurements at different sites in and around Munich: On both days in May, profiles were measured at eight stations within a few hours. The sites were selected to provide cross sections from 25 km west of Munich (Maisach) and 30 km east of Munich (Ebersberg). At each site, measurements were taken for about 15 min. POLIS was not available during the winter campaign Ceilometer [15] The Vaisala double lens ceilometer LD-40 [Münkel et al., 2004] is based on the same physical principles as the above mentioned lidars. It measures the backscattered Figure 1. Measurement sites during ICAROS-NET and flight tracks of the microlight aircraft on 8 December (solid line) and 9 December (dashed line). Munich Airport is shown for orientation only. 3of17

4 intensity of aerosols and air molecules at a wavelength of 855 nm. Its InGaAs laser diodes are pulsed with a repetition rate of 6.5 khz. Pulse energies are limited to 1 mj to allow eye-safe operation and long diode life cycles. The minimum lifetime of a laser diode is 17,500 hours. The data records cover the range from 7.5 m to 15 km with a nominal vertical resolution of 7.5 m. Every 15 s a mean profile is stored; the number of laser pulses accumulated for each profile varies with signal amplitude and is in the order of 60,000. Typical signal-to-noise ratios are in the order of 7 for z = 0.2 km. The geometric overlap factor of the optical system increases from 0.45 at z = 0.18 km to 0.9 at z = 0.55 km. Data are corrected for this overlap, variations in the laser output and for spurious wave pattern in the signals. [16] The ceilometer can operate unattended for several years in any climatic environment, and only requires some regular window cleaning. Thus it is favorable for long-term studies and implementation in networks. However, the range and the signal-to-noise ratio is significantly lower compared to more sophisticated lidar systems Sodar [17] In contrast to the previously mentioned instruments, the sodar technique relies on the emission of acoustic pulses and the time resolved detection of its backscatter [e.g., Kalogiros et al., 1998]. We used the METEK DSD 3 7 monostatic Doppler sodar as described by Reitebuch and Emeis [1998]. It has three antennas, each with seven sound transducers, i.e., the same device serves both as a loudspeaker and as a microphone, depending on the phase of the measurement cycle. In the framework of ICAROS-NET a frequency of 1674 Hz was used and the instrument s range was under ideal conditions without external noise sources from 55 m to 1285 m with a raw range resolution of 30 m. Smoothing of the data along the line of sights is not provided, so that the final resolution is not reduced. Data include the acoustic backscatter intensity, the three components of the wind, and the variance of the vertical velocity component s w. A calibration of the signals is not required. The accuracy of the wind velocity is ±0.5 m s 1, if measurements are averaged over 10 min. In a monostatic configuration the backscatter intensity depends only on temperature gradients caused by turbulent fluctuations and by strong vertical temperature gradients such as inversions [Tatarskii, 1961]. This information can be used for the determination of the mixing layer height Wind-Temperature-Radar [18] The wind-temperature-radar (WTR) was another mobile, ground-based remote sensing system for probing the lower atmosphere during ICAROS-NET. The WTR is a so-called frequency modulated continuous wave (FMCW) radar, more details are given by Bauer-Pfundstein [1999]. The measurements are based on the backscattering of electromagnetic decimeter waves in the atmosphere. Waves are scattered either on turbulent fluctuations of the atmospheric refractive index which are caused by fluctuations of the temperature and humidity, or at fluctuations of the refractive index, which are generated by the transmission of an appropriate artificial sound source. [19] The WTR operates simultaneously in the RASS mode (Radio Acoustic Sounding System) and the clear-air mode. In the RASS mode, the air temperature is derived from measurements of the propagation of sound pulses by means of the Doppler shift of the radio frequency waves. The temperature calculation from the sound speed is corrected for the vertical wind speed. In the clear-air mode the WTR observes the electromagnetic structure parameter of the refractive index, which is mainly dominated by moisture fluctuations but much less by temperature fluctuations. [20] The raw spatial and temporal resolution of the radial velocities of the WTR is 1 min and 60 m, respectively. Wind and temperature data for the assessment of mixing layer heights are determined by consensus averaging over 30 min, and a 1:2:1 weighting function for the three adjacent range gates is applied Airborne In Situ Measurements [21] In addition to the derivation of profiles of aerosol parameters, temperature or humidity from remote sensing techniques, profiles were also determined directly by airborne in situ measurements. The three dimensional characterization of the mixing layer was achieved by a microlight aircraft equipped with sensors for meteorological parameters and aerosol particles. The microlight aircraft, due to its slow horizontal speed, high climb rate, and low minimum altitude, serves as very flexible platform for profiling the planetary boundary layer up to about 4.5 km on a regional scale [Junkermann, 2001]. [22] The horizontal speed of about 20 m s 1 allows a good spatial resolution and coverage. Local profiles can be performed within a column of less than 500 m in diameter with a climb rate of more than 4 m s 1. As a consequence, a vertical profile of the mixing layer can be obtained in less than 10 min. During ICAROS-NET the instrumentation included a Grimm aerosol spectrometer (type 1.108) with 15 size bins for diameters d from 0.3 to 20 mm for the measurements of the size distribution of large particles. The total number of particles with d > 10 nm was determined by a TSI 3010 condensation particle counter (CPC). While the CPC runs without any inlet system, a 15 cm long electrical conducting tube with an inner diameter of 1.5 mm is used as inlet for the particle spectrometer. The diameter of the forward pointing tube is matched to the average true air speed. The vertical resolution of the raw data of the spectrometer and the CPC is 20 and 3 m, respectively. For the discussion in section 4, this resolution is reduced by a sliding average over 60 m. [23] The Grimm aerosol counter is factory calibrated once per year. Prior and after each field campaign the size sensitivity is calibrated in the institute using a TSI 3080 DMA-Aerosol classifier system. A noise check for the lowest size range can be performed during the flight each time the planetary boundary layer is left. In this case the CPC signal goes down to approximately 300 cm 3 and the Grimm spectrometer reads typically less than 10 cm 3. [24] Temperature and dewpoint are measured with a fast chilled mirror (Meteolab). All data are stored together with GPS position and altitude with a temporal resolution of 2 s Radiosondes [25] Radiosonde ascents, using the Vaisala RS 80 system, are performed routinely by the German Weather Service at Oberschleißheim at 0000 and 1200 UTC. Note that all times 4of17

5 are given in UTC (Coordinated Universal Time; 1200 UTC corresponds to 1247 mean local time in Munich) throughout the paper. Data of temperature and humidity are given in intervals of 10 s, the sounding of the lowermost 2 km of the atmosphere takes about 5 to 6 min. 3. Determination of the Mixing Layer Height [26] The determination of the height of the top of the mixing layer z ml is difficult per se because there is no unique definition for this quantity [e.g., Stull, 1988; Seibert et al., 2000]. As the term mixing layer is associated with vertical exchange leading to a (more or less) homogeneous distribution of atmospheric constituents which have their sources at the surface, z ml can be described by means of the abundance of such a constituent, e.g., aerosols, or by atmospheric dynamics. If we use the first approach and rely on aerosol as a tracer, it is obvious that all residual layers should be included. If the definition is based on aerosol properties, the extinction or backscatter coefficient, or the number density may be used. However, the identification by means of the water vapor concentration, temperature inversions or turbulence parameters is also possible. It is obvious that the choice of a suitable definition depends on the available data sets: A backscatter lidar certainly will use an aerosol parameter and not a feature of the temperature profile, radiosondes have to refer to temperature and humidity profiles and cannot use aerosol properties, and so on. In the following, the different methodologies to retrieve the mixing layer height are briefly outlined Lidar [27] The identification of the mixing layer from lidar data is based on aerosol information and a widely used approach [e.g., Endlich et al., 1979; Ferrare et al., 1991; Cooper et al., 1994]. The basic idea is that aerosols are mainly confined to the mixing layer, because the most significant aerosol sources are at the surface and vertical exchange is prohibited at the top of the mixing layer under many meteorological conditions (e.g., temperature inversions). As a first approach, z ml can therefore directly be determined from the averaged and smoothed lidar signal P: the range corrected signal, Pr 2 Pr ðþr 2 / bðþt r 2 can be taken as attenuated backscatter and is a good indicator of the mixing layer, as the transmission T of the atmosphere is only slowly decreasing with height. Thus Pr 2 quite well reflects the structure of the backscatter coefficient b, which is dominated by aerosol backscatter, and thus is a suitable and widely applied means for the assessment of the top of the mixing layer [e.g., Johansson et al., 2005]. It is marked by a strong decrease of Pr 2 with r: We take z ml as that height where the absolute value of the first derivative of ln Pr 2 has its maximum (i.e., where the steepest decrease occurs). Note that above this height, the signal further decreases to a background value or to a value corresponding to the actual aerosol load of the free troposphere. In other words, above the so defined mixing layer height the aerosol load does not immediately drop to zero. [28] Alternatively, the aerosol backscatter or the extinction coefficient a p can be used to identify the mixing layer. Then, however, an inversion of the lidar data is required. It was shown during the European Aerosol Research Lidar Network EARLINET [Bösenberg et al., 2003] that the corresponding computational effort is not justified if one only wants to determine z ml [Wiegner et al., 2002]. Therefore we exploit the range corrected signal as described above. Note that the signal below 2.5 km is typically two to 3 orders of magnitude larger than the background noise. [29] In case of MULIS the procedure to derive z ml is semiautomatical. This approach has the disadvantage to be more time consuming by requiring input from the user, but it has the big advantage that it is possible to reliably identify multilayered aerosol distributions and to distinguish more than one aerosol layer. The user input concerns the selection (from visual inspection) of adequate regions where the local minimum of the derivative is calculated, and the selection of the width of the Gaussian filter for the smoothing of the profiles. The latter depends on the signal-to-noise ratio and is typically 37.5 m (FWHM) Ceilometer [30] The underlying physical concept of a commercially available ceilometer and a lidar is the same, consequently, the determination of z ml is similar; it is based on the slope of the range corrected signal. However, compared to the lidar, longer averaging times are required (10 min) and a sliding average over 25 range bins (of 7.5 m each) is provided. The detection of mixing layer heights in about 2 km requires averaging over 30 min and 50 range bins. [31] As mentioned in section 2.3, the optical design of the ceilometer provides insufficient overlap for the first few hundred meters, and, due to the low pulse energy, the signal-to-noise ratio from distances of more than 3 km is generally too low for this analysis. As a consequence, we choose in this paper an upper range for the determination for z ml of 2.1 km. The lower range was set to 0.18 km; from that range an overlap correction is applied until full overlap is reached. Note that possible uncertainties in the overlap correction do not affect the retrieval of z ml and that calibration is not necessary. However, because of the low signalto-noise ratio the derivation of backscatter and extinction coefficients is prohibited Sodar [32] The z ml from the sodar data, averaged over 10 min, is determined by evaluating two criteria as described in Emeis and Türk [2004]. As the signal-to-noise ratio of the acoustic backscatter intensity is in the order of 50 in the lowermost 400 m, the first criterion is the search for the height z 1 where the decrease of the intensity exceeds system specific thresholds. The second criterion accounts for surface temperature inversions and elevated inversions by diagnosing (secondary) maxima of the backscatter intensity that are not related to high turbulence intensities, i.e., the variance of the wind velocity must be low. This restriction is necessary to avoid cases of superadiabatic temperature profiles. Note that the consideration of the wind velocity requires a signal-to-noise ratio of more than 5. For elevated inversions we stipulate an increase in the backscatter intensity below a certain height, z 2, and a decrease above. For (usually nocturnal) surface 5of17

6 inversions, again, the backscatter intensity must exceed a threshold. [33] z 1 and z 2 are determined separately. In both cases the algorithm starts with small z and stops at that z when the corresponding criterion is fulfilled the first time. The mixing layer height z ml is then defined as the minimum of z 1 and z 2. In case neither z 1 nor z 2 is found, z ml cannot be determined from the sodar data. This happens, e.g., during the afternoon of warm and sunny days when the convective boundary layer top is higher than the range of the sodar. However, this does not necessarily mean that there is no inversion at all Wind-Temperature-Radar [34] As the WTR determines vertical profiles of temperature as well as the wind vector and turbulence parameters, there are several options to derive the mixing layer height: z ml can be associated to temperature inversions, regions of strong turbulence gradients or regions of strong echoes of the backscattered intensity. [35] The derivation of z ml from temperature profile data is one of the oldest methods [Holzworth, 1964] and straight forward. It is called TG here. Turbulence data can also be used in several ways for the determination of z ml [Beyrich, 1994]. Under convective conditions the vertical profile of the wind speed w is related to the extension of convective plumes. The standard deviation of w, s w, is then used for the estimation of z ml and is referred to as S0 approach. Finally, small-scale fluctuations of water vapor concentration can be used as an indicator of z ml [Bösenberg and Linné, 2002]. Such fluctuations are seen as maxima in the backscattered intensity of the radio frequency waves; this approach is referred to as P0. [36] Note that the evaluation of the data cannot be automatized as it requires expert knowledge. Thus it is difficult to give a general order of preference of the different approaches: The TG approach is quite reliable in cases of elevated temperature inversions and adiabatic lapse rates below, however, the maximum vertical range is between 0.8 and 1.2 km depending on the wind speed. The S0 approach fails if the wind is weak. The advantage of the third approach is that the measurement range normally exceeds 1 km; however, it must be assumed that the water vapor distribution reflects the extent of the mixing layer. The relative errors of the individual z ml retrievals is typically 10 15%. Comparison of the three approaches is therefore used to increase the confidence in the z ml retrieval Airborne in Situ Measurements [37] The measurements onboard of the microlight aircraft offers a suite of physical parameters which can serve to determine the height and the structure of the mixing layer. As we are primarily interested in aerosols, the measurements of the number concentrations of particles are the most obvious data set to assess z ml. Moreover, the potential temperature reflects the mixing layer for thermodynamical reasons. The rapid decrease of the dew point at the transition from the mixing layer to the free troposphere is another parameter to determine the mixing layer height Radiosondes [38] Radiosonde profiles of the relative humidity and temperature can be used to search for moist layers and temperature inversions. They constitute an independent way to support the interpretation of the findings from the other instruments, in particular of these methods, which are based on aerosol parameters. 4. Results [39] The above mentioned techniques have been widely used to determine the mixing layer height. The spatial aerosol distribution over some tens of kilometers was investigated by, e.g., Dupont et al. [1999] or Menut et al. [1999]. The strengths of certain techniques, e.g., the unattended operation for continuous monitoring, and their weaknesses, e.g., the limited vertical coverage, as well as mutual comparisons of different instruments have in part been discussed in previous studies [e.g., Coulter, 1979; Devara et al., 1995; De Tomasi and Perrone, 2006; Zéphoris et al., 2005]. Comparisons between retrievals from ceilometer, RASS and sodar were published recently [Emeis et al., 2004] and showed good agreement provided that the mixing layer heights are within the measurement range of the instruments (about 1 km). In this paper we extend the set of instruments by lidars and in situ measurements from a microlight aircraft. [40] The second purpose is the investigation of the development of the mixing layer over a flat terrain like the Munich area, which is not uncommon for Germany. We have selected 4 typical days to study differences with season and cloud cover: 16 May is an example of sunny conditions, 23 May was a partly cloudy situation in the summer season, and 8 and 9 December are examples of winter days with Föhn conditions Mixing Layer Height Under Cloud-Free Conditions in Summer [41] To observe the aerosol distribution under clear and sunny conditions during a stable high-pressure period, we selected 16 May 2003 as an example. All instruments were in operation. [42] As lidars are certainly the most adequate instruments for aerosol detection, we start with the discussion of their results. The mixing layer height as derived from the lidar MULIS at central Munich is shown in Figure 2. The crosses show aerosol layer boundaries based on 100 shot averages (between 0945 and 1130) or 500 shot averages (elsewhere). Until 1100, clearly separated layers existed. The top of the lower layer raised from 0.45 km at 0730 to 1.2 km. The top of the second layer slowly descended from 2.3 km to about 1.9 km at It seems to be the residual layer from the previous day. After 1100, both layers began to merge, as a consequence, no significant changes in the slope of the range corrected lidar signal could be identified below the transition to the free troposphere. Additionally, we show the profile of the relative humidity derived from the radiosonde ascent at Oberschleißheim at 1200: The close correlation between aerosol and humidity is obvious. [43] To illustrate the aerosol distribution and its layering more clearly, we show as one example the aerosol extinction coefficient profile derived from lidar signals under different zenith angles. The profile shown in Figure 3 corresponds to the 355 nm wavelength and belongs to the beginning of the measurement sequence (0725). Error bars 6of17

7 Figure 2. Temporal development of the mixing layer height and the lowermost aerosol layer as derived from MULIS (16 May 2003) in central Munich (crosses), and the profile of the relative humidity of the radiosonde ascent of 1200 at Oberschleißheim. are shown for selected heights. It can be seen that both layers are clearly separated and show significant aerosol load. Seventy-five percent of the total aerosol optical depth is confined in the lowest 2.3 km, with both layers contributing almost the same to the optical depth: Whereas the lower layer shows the larger extinction coefficient, the elevated layer has the larger vertical extent. Consequently, an interpretation of the lower layer (below 0.9 km) as that part of the troposphere, where most of the aerosols are confined, would be erroneous. [44] In addition to the strong mixing layer there were two aerosol layers in the free troposphere: a double structure at 4.4 and 5.1 km and a small layer at about 3.2 km. These layers were slowly changing in height and width, however, were persistent during the whole measurement period. It is most probably that they origin from long-range transport and are not part of the mixing layer. [45] As already mentioned, POLIS measurements were conducted for the same time period as MULIS, but at different sites to assess the horizontal homogeneity of the aerosol distribution. At each site one mean range corrected profile corresponding to typically 15 min was determined and z ml was calculated as described in section 3. The pronounced planetary boundary layer consisting of two aerosol layers as seen in Figure 3 was observed at all sites across Munich. The altitudes of the top of these layers are shown in Figure 4 (POLIS, wide hatched) together with the corresponding MULIS measurements (narrow hatched), i.e., measurements made at roughly the same time but at different sites are compared. The derivative of the logarithm of the range corrected signal, which constitutes the criterion for the z ml search (see section 3.1), is shown (in arbitrary units) for MULIS at the MIM (solid line) and POLIS (dashed line) at different sites as indicated for different times of the day. Figures 4a, 4b, 4c, and 4d concern approximately 0800, 0900, 1030, and 1115, respectively, Figure 3. Aerosol extinction coefficient (l = 355 nm), in km 1 at central Munich derived from MULIS data (16 May, 0725). 7of17

8 Figure 4. Comparison of z ml determination based on the derivative of the range corrected lidar signal: MULIS (at central Munich, solid line) and POLIS (sites are indicated, dashed line) for 16 May 2003, quasi-simultaneous measurements. See text for details. when POLIS was in Maisach (24.5 km west of MIM; N, E), in Neuherberg (8.8 km north of MIM; N, E), in Ebersberg (30.0 km east of MIM; N, E), and Haar (13.0 km east of MIM; N, E). Note that the range resolution of MULIS and POLIS (3.75 m compared to 7.5 m) and the length of the temporal integration are different and that the times of observation differ by roughly 10 min. In spite of these differences, the pairs of measurements give a very good indication of the horizontal behavior of the aerosol distribution. [46] It is obvious that the vertical structure of the profiles at the outskirts of Munich is very similar to the observations at the Meteorological Institute in central Munich. As already mentioned, the two layers of the mixing layer can easily be detected in Figure 4. Comparison of the measurements at about 0800 (Figure 4a) shows that the top of the layer was quite similar for Munich and Maisach (approximately 2.2 km), but the lower layer was higher in Munich than outside (0.6 and 0.4 km, respectively). A similar situation occurred approximately 1 hour later (Figure 4b) north of Munich, when the top of this layer raised at both sites but the difference between Munich and the hinterland remains small. The comparison between central Munich and the easternmost site (Ebersberg) shows that the development of the lower layer continued. It has lifted 8of17

9 Figure 5. Aerosols number concentration in cm 3 of particles larger than 10 nm as derived from the particle counter data onboard the microlight aircraft (16 May 2003), solid line for Ismaning (0915), dashed lines for Fürstenfeldbruck (0833, 0957, or 1017 with one, two, or three dots, respectively). by another 200 m; still with a shallower aerosol distribution outside of Munich. At 1115 the separation between the both layers became smaller as can be seen in Figure 4d: As already inferred from Figure 2, the vertical exchange leads to a smoothing of the gradients so that the lower layer became less pronounced and began to merge with the upper layer. In Figure 4 it is obvious that larger differences in the lower layer exist which can be attributed to possible local sources, and different surface conditions which can lead to different vertical aerosol fluxes. [47] The general agreement of the vertical profiles determined from the lidars suggests horizontal homogeneity insofar that a layer of about 2 km thickness containing most of the aerosols (70% of the aerosol optical depth on average; l = 532 nm) was constant over a range of several tens of kilometers: The measurements show that the temporal development of the tropospheric aerosol distribution was similar at all stations in and around Munich. Furthermore, they confirm that the mixing layer consisted of two sublayers. However, the internal structure of the aerosol layer was different due to local effects. [48] Direct aerosol measurements were provided by the particle counter onboard of the microlight aircraft (see Figure 5). Three profiles from ground to approximately 2.3 km were provided at Fürstenfeldbruck ( , , and ; N, E) as indicated by the dashed lines with one, two, and three dots, respectively. The solid line shows the profile at Ismaning ( ; N, E) which is 33.3 km farther east. [49] In the morning, the lowermost layer was very pronounced with a concentration of up to 18,000 cm 3 below z = 0.5 km and between 3000 and 4000 cm 3 above. At an altitude of 2.2 km the number concentration dropped to approximately 1000 cm 3. Comparison with the POLIS profiles at Maisach (1 km from Fürstenfeldbruck) 30 min earlier (see Figure 4a) shows a close correlation. The second and third profile at Fürstenfeldbruck show how the onset of the vertical transport changes the aerosol distribution: Close to the surface the number density decreases, but between z = 0.5 and z = 1.0 km it increases significantly. This vertical mixing led to an extension of the aerosol layer to about 1.0 km around 1000, which is consistent with the MULIS measurements in central Munich (see Figure 2). The vertical structure of the aerosol distribution above the lowermost layer remained virtually constant with another sharp decrease between 2.0 and 2.2 km. The same conclusion with respect to the z ml can be drawn if only particles larger than 0.3 mm as measured by the Grimm spectrometer are considered (not shown here). However, the size distribution changes in the course of the day. [50] In the following we discuss results from the automatically running stations and compare them to the lidar data. [51] Most similar to the lidar concept is the ceilometer. Data were exploited between 0930 and 1730, Figure 6 shows the retrievals on the basis of 15 s averages. Before and after that period no data were recorded due to logging failures. According to the ceilometer data, the mixing layer continuously widened until 1200: z ml changed from about 0.7 km (0930) to 1.3 km at Before 1000 a few measurements from a cloud at 1.6 km were identified as the top of the mixing layer. Between 1100 and 1330 the ceilometer detected more clouds with bases rising from 1.2 to 1.9 km. They were also taken as z ml by the automated algorithm. Thereafter the retrieval of the mixing layer height became critical: It rapidly changed between 1.5 and 2.0 km. This finding can be attributed to one or a combination of the following reasons: the existence of different layers, the less pronounced transition between the mixing layer and the free troposphere, or the low signal-to-noise ratios which makes the calculation of the derivative of the range corrected signals unreliable. [52] Comparisons between the lidars and the ceilometer can be made from 0930 until While MULIS and the ceilometer show pronounced differences at 0930 with z ml = 0.7 km from the ceilometer and z ml = 1 km from the MULIS Figure 6. Mixing layer height (crosses) as derived from the slope of the range corrected backscatter profiles of the ceilometer at Frankendorf (16 May 2003). 9of17

10 Figure 7. Comparison of z ml derived from the WTR measurements at Lohkirchen using different approaches (16 May 2003): approach S0 (solid line), TG (longdashed), and P0 (short-dashed). retrieval, the agreement between POLIS and the ceilometer is excellent at 0900 when both retrievals show approximately 0.7 km. This seems to confirm the shallower aerosol distributions in the suburban areas, which was already seen in the MULIS/POLIS intercomparisons (see Figure 4). At 1100, the agreement between the three data sets is fairly good with approximately km. Before 1200, the second layer above 2 km was not identified by the ceilometer. When both layers have merged, the agreement is quite good showing values for z ml between 1.8 and 2.0 km. This situation began before 1200 according to MULIS, and after 1300 according to the ceilometer. This differences can be attributed to the existence of the clouds in the ceilometer s field of view that inhibit evaluation from higher levels. [53] The WTR was installed 3.4 km northwest of the site of the ceilometer. The temporal development of z ml between 0400 and 1100 as derived from the WTR is shown in Figure 7. The different curves correspond to the different retrievals: The solid line is based on the vertical wind ( S0 ), the long dashed line is based on the lapse rate ( TG ), and the short dashed is based on the backscatter intensity ( P0 ). As mentioned above, the three approaches were applied to increase the confidence in the determination of the mixing layer height. The differences between the three retrievals are quite small being in general below 100 m. It can be seen that all methods show a pronounced increase of z ml from morning to noon. After 1100 it is no longer possible to determine z ml because the signal-to-noise ratio of the transmitted and the received signals is too low. [54] Comparisons between the WTR and the ceilometer (Figures 6 and 7) are possible only during the short time period from 0930 to 1100 when common data sets are available. Here, the agreement is very good showing an increase of z ml from 0.7 to 1.0 km. Comparisons between MULIS and WTR can be made for the time period from 0730 to At the beginning of this period, the excellent agreement of the z ml of the lower layer (MULIS) and the mean height as derived of the WTR retrievals is obvious. In the following hours, the z ml from the WTR data is slightly lower than the z ml according to MULIS. However, differences in the order of 100 to 200 m have also been observed between POLIS and MULIS and can therefore been attributed to local effects: Comparison with POLIS measurements east of Munich in Ebersberg (see Figure 4) at 1030 shows indeed good agreement with the WTR results (Figure 7). [55] The third automatic station was the sodar, located at Fürstenfeldbruck. It was working continuously for 24 hours. The results of the z ml retrieval are shown in Figure 8. According to the definition in section 3.3, the thin line indicates z ml as the direct result of two criteria, whereas the smoothed thick line is shown for clarification. Between 1000 and 1800, z ml could not be retrieved because neither the method relying on the turbulence (z 1, squares in Figure 8) nor the second method which evaluates the slope of the backscatter intensity (z 2, crosses in Figure 8) worked reliably. It is known from the other measurements that z ml was larger than 1.25 km during this time period. [56] The sodar measurements show, similar to all other measurements, the general increase of z ml in the early morning, i.e., between 0600 and A direct comparison is possible with the microlight profiles at Fürstenfeldbruck and the POLIS measurements at Maisach. They agree fairly: The aerosol-based retrievals (lidar, in situ) show differences of approximately 0.1 km only Mixing Layer Height Under Partly Cloudy Conditions [57] The second day we want to discuss in this paper is 23 May. This day was quite different from the previous example because of significant cloud coverage. As a consequence, atmospheric radiation is clearly dominated by clouds and aerosols are of less importance. Furthermore, most remote sensing techniques of aerosol properties are more or less prohibited: Spaceborne remote sensing is impossible because of the high cloud reflectance, ground based sun photometry is virtually impossible because of the high probability of clouds in the line Figure 8. Mixing layer height z ml derived from the sodar measurements (16 May 2003) as the minimum of the retrieved z 1 (squares) and z 2 (crosses), respectively, as described in the text. The thick line is the smoothed z ml. 10 of 17

11 Figure 9. Range corrected lidar signal (532 nm) in logarithmic scale as measured by MULIS to illustrate the development of the lower troposphere on 23 May The lowest 200 m should be neglected due to incomplete overlap. of sight and even active ground based remote sensing by lidars or ceilometers is complicated as optically thick clouds cannot be fully penetrated. So, primarily for academic interests, we want briefly discuss the potential of the different sensors for assessing the mixing layer height. [58] An overview of the vertical distribution of the clouds and aerosols as derived from the lidar MULIS is shown in Figure 9 by means of the range corrected signal at 532 nm. As only measurements under a zenith angle of 20 are considered, there are gaps in the time series, when the lidar was scanning; 23 May was characterized by a high coverage of midlevel clouds in about 4 km. These clouds disappeared at 1000 over Munich, but east of Munich they were still observed at 1130 by POLIS. A second broken cloud field was present below 1.5 km throughout the observation period. Below this cloud, backscatter signals indicate no further aerosol layering. [59] If we assume that the lowermost cloud layer marks the top of the mixing layer, zml can be easily assessed from the lidar data. It coincides with the height range of high relative humidity which was measured by the radiosonde (not shown here). If we study lidar data with high temporal resolution during episodes when cloudy and cloud-free conditions rapidly changed, we found that clouds formed in the height of the upper part of the aerosol layer. To be consistent with the previous definition of zml, we can now interpret the top of the cloud as zml, provided that the cloud could be penetrated by the lidar. Accordingly, zml slowly raised from 0.6 km (0900) to about 1.4 km (1230). [60] This is in good agreement with the POLIS measurements taken at different stations around Munich (not shown here): At 0813 (Pasing) and 0900 (Maisach) zml = 0.4 km was found, whereas zml = 0.6 km at the eastern sites Neuherberg, Vaterstetten und Zorneding (between 0944 and 1051). At the most eastern station, Ebersberg, the cloud extended between 0.9 and 1.5 km. [61] Profiles of the particle number density at Fu rstenfeldbruck are available from the airborne in situ measurements between 1153 and 1215 (solid line in Figure 10, left) and 32 km east at Ismaning between 1234 and 1247 (dashed line in Figure 10, left). Both profiles were measured under cloud-free conditions or within large gaps between cumulus clouds. In Fu rstenfeldbruck the aerosol particles were confined to the lowest 1.4 km, whereas east of Munich, the height of the layer was slightly higher (1.6 km). However, the size distribution of the particles and their overall number have changed significantly: On the one hand, the total number of particles (d > 0.01 mm) was almost twice as large (9000 cm 3 versus 17,000 cm 3); on the other hand, the number of large particles (d > 0.3 mm; Figure 10, right) remains virtually constant. This profile is averaged over both sites; the small range between the dashed lines, showing the average plus/minus one standard deviation, indicates the small variability of the large particle fraction over Munich. [62] Though not directly related to the mixing layer height, we want to briefly discuss a special feature of the profile of the number density of large particles as shown in Figure 10. It is obvious that the aerosol number increases in Figure 10. Aerosol number density in cm 3 of particles (left) larger than 10 nm at Fu rstenfeldbruck (solid line; approximately 1200) and Ismaning (dashed; approximately 1240) and (right) larger than 300 nm as derived from the microlight aircraft data on 23 May Figure 10 (right) shows the averaged profile and the plus/minus one standard deviation. 11 of 17