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Estimation of the mixing layer height over a high altitude site in Central Himalayan region by using Doppler lidar
Journal of Atmospheric and Solar-Terrestrial Physics 109 (2014) 48–53
Contents lists available at ScienceDirect
Journal of Atmospheric and Solar-Terrestrial Physics journal homepage: www.elsevier.com/locate/jastp
Estimation of the mixing layer height over a high altitude site in Central Himalayan region by using Doppler lidar K.K. Shukla a,b,n, D.V. Phanikumar a, Rob K. Newsom c, K. Niranjan Kumar d, M. Venkat Ratnam e, M. Naja a, Narendra Singh a a
Aryabhatta Research Institute of Observational Sciences, Nainital 263002, Uttrakhand, India Pt. Ravishankar Shukla University, Raipur, Chhatisgarh, India c Pacific Northwest National Laboratory, Richland, WA, USA d Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates e National Atmospheric Research Laboratory, Tirupati, India b
art ic l e i nf o
a b s t r a c t
Article history: Received 8 November 2013 Received in revised form 6 January 2014 Accepted 7 January 2014 Available online 17 January 2014
A Doppler lidar was installed at Manora Peak, Nainital (29.41N; 79.21E; 1958 amsl) to estimate mixing layer height for the first time by using vertical velocity variance as basic measurement parameter for the period September–November 2011. Mixing layer height is found to be located 0.57 7 0.1 and 0.45 70.05 km AGL during day and nighttime, respectively. The estimation of mixing layer height shows good correlation (R2 4 0.8) between different instruments and with different methods. Our results show that wavelet co-variance transform is a robust method for mixing layer height estimation. & 2014 Elsevier Ltd. All rights reserved.
Keywords: Doppler lidar Mixing layer height GVAX
1. Introduction The atmospheric boundary layer (ABL) is the lower most part of the troposphere. This layer of the atmosphere is directly influenced by the earth0 s surface and responds to surface forcing on a timescale of about an hour or less (Stull, 1988). The depth of the ABL is a parameter that varies daily in accordance with the thermal and frictional influence of the earth0 s surface. ABL evolution is mainly governed by thermal (solar heating) and mechanical (wind shear) turbulence. Surface fluxes of sensible and latent heat play a major role in the diurnal growth of the ABL. It is evident from previous reports that the ABL dynamics play a key role in the vertical transport and mixing of aerosols and chemical species from the surface to the free troposphere (Pearson et al., 2010; Ouwersloot et al., 2012). The rural ABL depth has been found to be shallower than the ABL depth over nearby urban areas (Dupont et al., 1999). Hilly and mountainous terrain exerts an important influence on the Earth0 s atmosphere. Terrain affects atmospheric transport and mixing at a wide range of spatial and temporal scales. Hence, accurate determination of the boundary layer height (BLH) and its diurnal
n
Corresponding author. E-mail addresses: [email protected], [email protected] (K.K. Shukla). 1364-6826/$ - see front matter & 2014 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jastp.2014.01.006
variation at high altitude sites are of great importance for understanding observed asymmetries in day and nighttime aerosol mass concentration. Previous studies have hypothesized the observed asymmetry to be associated with ABL dynamics (for e.g. Dumka et al. (2006)). However, there are no reports till date on the determination of BLH to corroborate the plausible mechanism responsible for the asymmetric behavior of aerosol mass concentration. Estimates of BLH have been obtained using observations from various instruments, including light detection and ranging (Lidar), sound detection and ranging (SODAR), radio acoustic sounding system (RASS), and radiosonde (RS), constellation observing system for meteorology, ionosphere, and climate (COSMIC) refractivity profiles have also been used to estimate BLH (Seibert et al., 2000; Basha et al., 2009; Barlow et al., 2011). However, these various methods often produce different BLH estimates depending on the observed parameters and the performance characteristics of the instruments (Seibert et al., 2000). Previous studies show that BLH estimates vary from 2 to 3 km over a tropical station Gadanki (13.51N; 79.21E; 375 above mean sea level (amsl)) (Basha and Ratnam, 2009) to 0.5–0.7 km over Kharagpur (22.321N, 87.321E, 40 m amsl) and the Danum valley region of Sabah, Borneo (4.91N; 117.81E; 198 amsl) (Alappattu et al., 2009; Pearson et al., 2010). Additionally, a few reports even show that BLH is invariant ( 1 km) at Westminster (51.41N, 0.11W) (Barlow et al., 2011). These results show the large spatial heterogeneity in the nature of
K.K. Shukla et al. / Journal of Atmospheric and Solar-Terrestrial Physics 109 (2014) 48–53
the ABL around the globe. Therefore, the study of ABL dynamics over land, sea and complex terrain (including buildings, forests, hills and mountains) is imperative for air pollution models, atmospheric flow models and for climate models. The present study aims to investigate ABL characteristics over a high altitude mountainous site. Specifically, we examine the diurnal and seasonal pattern of the mixing layer height (MLH) over Manora Peak, Nainital, India using observations from a collocated Doppler lidar, ceilometer and radiosonde. Comparisons are made between MLH estimates obtained from these three observational systems using three different data analysis methods (e.g. threshold, gradient and wavelet covariance transform (WCT)). The results are discussed in the light of current understanding of ABL variation over the site.
2. Observational site and general meteorology Fig. 1(a) shows the map of Indian sub-continent highlighting the observational site. The Manora Peak, Nainital site located in the Central Himalayan region at an altitude of 1958 m amsl is shown in Fig. 1(b). The plains of the Ganges Valley lie approximately 50 km to the south, and higher altitude mountains (4 1500 m amsl) of the Himalaya Range lie to the north. The site is located well away from large industrial and population centers, and the air is relatively clean. The town of Nainital is approximately 2 km north of the site, and the nearest cities with small-
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scale industries are located approximately 20 to 40 km south of the site, including the cities of Haldwani at (423 m amsl), Pantnagar (231 m amsl), and Rudrapur (209 m amsl). The mega city of Delhi, capital of India, is located about 225 km to the southwest. A detailed description of the topography and general meteorology of the observational site is discussed elsewhere (Sagar et al., 2004; Kumar et al., 2010).
3. Instrumentation and methodology The US Department of Energy0 s Atmospheric Radiation Measurement (ARM) program (Mather and Voyles, 2013) deployed the first ARM Mobile Facility (AMF1) at Manora Peak, Nainital as part of the Indo-US collaborative project Ganga Valley Aerosol Experiment (GVAX). The AMF1 contains a large number of ground-based in situ and remote sensing instruments for atmospheric measurement, including a Doppler lidar (DL), laser ceilometer (CM), and radiosonde (RS). 3.1. Doppler lidar The AMF1 DL is a scanning coherent DL that operates at a wavelength of 1.548 μm, a low pulse energy ( 100 μJ), and a high pulse repetition frequency of 15 kHz (Pearson et al., 2009). The DL is sensitive to scattering from aerosol, and provides measurements of radial (line-of-sight) velocity, signal-to-noise ratio (SNR), and attenuated aerosol backscatter. During the GVAX campaign, the DL was operated with a range resolution of 30 m (320 range bins covering a maximum height of 9.6 km) and a 1-s pulse integration time. The instrument was configured to perform planposition-indicator (PPI) scans once every hour, and range-heightindicator (RHI) scans once every 2 h. The vast majority of the time ( 90%), however, was spent with the beam pointing vertically in order to profile vertical velocities over the site. For this study, we use the vertical pointing observations from the DL to estimate MLH during the post-monsoon period from September through November 2011. Five-min averaged profiles of vertical velocity variance were computed from 1-s DL measurements, and the effects of noise were minimized by using only those velocity measurements such that SNR4 20 dB. The vertical velocity variance field was then used to estimate MLH (Tucker et al., 2009; Barlow et al., 2011). 3.2. Laser ceilometer Measurements of cloud base height and backscatter are provided by the Väisälä CT25K laser ceilometer (CM). The instrument provides backscatter measurements with vertical and temporal resolutions of 30 m and 16 s, respectively. Other technical details and specifications of the CM can be found at www.arm.gov or in Väisälä Oyj (2002). The backscatter data from the CM can be used to estimate MLH by identifying the height where the backscatter decreases abruptly. For this study, 5-min averaged profiles were computed from the 16-s backscatter measurements. These profiles were then used to estimate the MLH with the gradient and WCT methods as described in Sections 3.5 and 3.6. 3.3. Radiosonde
Fig. 1. (a) Altitude–topography map of Indian sub-continent and (b) zoomed version of latitude–longitude altitude display of central Himalayan region described in Section 2. Coordinates of the observational site (Manora Peak, Nainital (NTL)) are shown in the plot.
During the GVAX campaign, high resolutions radiosondes (RS92 Väisälä) were launched four-times daily from the Manora Peak site. The launch times were 00, 06, 12 and 18 GMT. The RS provided measurements of temperature, relative humidity, pressure, and winds with a vertical resolution of the RS measurements
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K.K. Shukla et al. / Journal of Atmospheric and Solar-Terrestrial Physics 109 (2014) 48–53
of about 10 m. Other technical details and specifications of RS-92 Väisälä (RS) can be found in www.arm.gov. For this study, potential temperature (PT) profiles were computed from the RS data, and used to estimate the inversion layer height (ILH) with the gradient and WCT methods, as described in Sections 3.5 and 3.6, respectively. Quality checks were performed on the RS data using the method described in Tsuda et al. (2006). The RS PT profiles were interpolated to a height resolution of 30 m in order to match the vertical resolution of the DL and CM. 3.4. Threshold method The threshold method was used to estimate the MLH from DL vertical velocity variance profiles. In this method, the MLH is estimated by locating the minimum height where the vertical velocity variance (sw2) exceeds a prescribed threshold value (Tucker et al., 2009). Tucker et al. (2009), Pearson et al. (2010) and Barlow et al. (2011); used the threshold values between 0.1 and 0.3 m2 s 2 depending on location and meteorological conditions. For this study, the observational site is located at high altitude and the meteorological conditions are quite different from urban locations (Sagar et al., 2004; Kumar et al., 2010). Therefore, we varied the threshold value from 0.1 to 0.5 m2 s 2 to obtain a reasonably realistic MLH in comparison with the previous reports and we found that an optimum threshold value of 0.25 m2 s 2 during the post-monsoon season (SON). However, it should be noted that this threshold value have seasonal variability.
3.6. Wavelet covariance transform method The wavelet covariance transform (WCT) was used to estimate the BLH from the DL, CM and RS measurements. The WCT is defined as Z 1 Zu zb W f ða; bÞ ¼ dz; ð1Þ f ðzÞh a Zl a where z is the altitude, f(z) is either the DL vertical velocity variance, CM backscatter, or the RS potential temperature profile, and Zl and Zu are the lower and upper altitude limits of the profile, respectively. For this study, we used the Haar function (i.e. step function) to detect changes in the profile (Gamage and Hagelberg, 1993). The Haar function is given by 8 a > < þ 1; b 2 r z r b zb h ¼ 1; b rz r b þ 2a ð2Þ > a : 0; elsewhere where b is the location at which the Haar function is centered, and a is the width or dilation of the function. The optimum value of the dilation a is determined from the depth of the transition zone. The main challenge is in choosing the appropriate dilation (Brooks, 2003; Baars et al., 2008). The identification of the MLH is done by varying a between 60 and 360 m and locating the height, z ¼b, which maximizes Wf.
4. Results and discussion 3.5. Gradient or derivative method The gradient method was used to estimate the MLH from the CM backscatter profiles, and from the RS potential temperature profiles. For the CM, the MLH is found by locating the height corresponding to the minimum in the first derivative (dβ/dz) of the range corrected and sensitivity normalized backscatter (β) (srad 1 km 1 10 4) profile (Emeis et al., 2008). For the RS, the inversion layer height is found by locating the height corresponding to the maximum in the first derivative of the potential temperature profile (Seibert et al., 2000).
Fig. 2(a) shows the diurnal variation of the vertical velocity variance from the DL and Fig. 2(c) shows a time series of MLH estimates on a typical day (16 October 2011).The MLH estimated by using WCT for DL is plotted over the time-height display with black solid line. Dotted green line represent DL MLH estimates using the threshold method and the blue solid line represents the DL MLH estimated by the WCT method, as described in Section 3.6. The diurnal variation in the MLH is clearly evident, with larger values during the daytime ( 0.8 km above ground level (AGL))
Fig. 2. Range-time intensity (RTI) plot showing the mixed layer evolution on 16 October 2011 using (a) DL MLH with WCT plotted with black solid line and (b) CM MLH with WCT plotted with black solid line (c) diurnal variation of the MLH obtained using DL (threshold/WCT), CM (gradient/WCT) and RS (PT gradient/WCT) on the same day. (d) Identification of inversion layer height from Radiosonde Potential temperature profile at 12 UT by using WCT method at different dilations. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
K.K. Shukla et al. / Journal of Atmospheric and Solar-Terrestrial Physics 109 (2014) 48–53
and lower values during the nighttime ( 0.35 km AGL). The increase in the MLH during the morning hours is expected due to surface heating and the subsequent buildup of convection and this results in the vertical transport of aerosols from the nearby valley region and local sources over the Manora Peak. Velocity variance shows that the maximum height of the mixing layer occurring on 08 UT corresponding to the period around solar noon, and the period when thermally driven upslope flow occurs. During the nighttime, with the absence of surface heating, the depth of the mixed layer decreases and the boundary layer becomes increasingly more stably stratified. Winds also play an important role in maintaining a stable NBL. It is generally found that the nighttime wind pattern is dominated by down slope flow over the site. Fig. 2(b) shows the diurnal variation of the aerosol backscatter from the CM on 16 October 2011. The MLH estimated by using WCT for CM is plotted over the time–height display with black solid line. The dotted red line and black solid line in Fig. 2(c) represent CM MLH estimates using the gradient and WCT methods, respectively. The MLH increases after sunrise and reaches a maximum of 0.8 km AGL at about solar noon (08:00 UT). After sunset the boundary layer becomes more stably stratified and the MLH decreases to 0.35 km AGL at about 12:00 UT. Also after sunset a periodic oscillation is observed in the DL and CM data. This may be due to topographically forced waves. The inversion layer height is estimated from RS PT profiles using the gradient and WCT methods. We found an appropriate dilation to be 120 m for the WCT method when applied to the RS PT profiles (see Fig. 2(d)). Fig. 2(c) shows RS inversion layer height estimates at the sounding times of 00, 12, and 18 UT. The open blue triangles represent inversion layer height estimates using the WCT method, and the solid black squares represent estimates using the gradient method. Both methods give nearly identical results, with values of 0.165, 0.705 and 0.375 km AGL, at 00, 12 and 18 UT, respectively. In general, a close match in the estimation of MLH among the different methods and different instruments can be noticed and the differences whatever small can be attributed to measuring technique which is sensitive to the measured parameter. Fig. 3 shows the post-monsoon (September–November 2011) seasonal mean diurnal variation in the MLH using the (i) threshold and WCT method for DL (dotted green line and solid black line), (ii) gradient and WCT method for CM (dotted magenta line and solid blue line), and (iii) PT gradient and WCT method for RS (red
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open circle and red open square). The diurnal mean of the MLH from the DL and CM observations were obtained by dividing the 24-h cycle into 30-min bins and then computing a seasonal average within each bin. Larger values of vertical velocity variance during the daytime can be attributed to vertical mixing of air (convective mixing). The MLH estimates from the DL and CM data show a maximum during the day time of about 0.57 km AGL, and a minimum during the night time of 0.35 km AGL. The DL MLH reaches a maximum at 06:00 UT during daytime. The DL MLH and the CM MLH are varying between 0.35 and 0.44 km AGL during night time and is also consistent with RS observations. The minimum and maximum RS inversion layer height values were found to be 0.44 and 0.57 km AGL, respectively. The above observed height of the BL ranging between 0.3 and 0.6 km AGL during the day and nighttime can be attributed to the topography of the site. Correlation diagrams between the various instruments and methods are shown in Fig. 4. These correlation diagrams include MLH estimates obtained at 00, 06, 12 and 18 UT during the postmonsoon period in 2011. Fig. 4(a) shows correlation diagrams between the RS WCT and DL WCT MLH estimates, and between the CM WCT and DL WCT MLH estimates. Fig. 4(b) shows correlation diagrams between the RS gradient and DL threshold MLH estimates, and between the CM gradient and DL threshold MLH estimates. Overall, there is good agreement between the various MLH estimates. Correlation (R2) coefficients between the DL with RS and CM are 0.8 and 0.6 with WCT method. Similarly, the correlations between the DL with RS and CM are 0.6 and 0.5 with threshold method (values of correlations with different instruments and methods for 00, 06, 12 and 18 UT are given in Table 1). The plausible reason for the observed discrepancies in correlation could be attributed to response of different instruments to BL differently keeping in view of the sensitivity of each instrument. For example, near BL altitude, it is not always possible to see temperature inversion and sharp reduction in the RH simultaneously (Basha et al., 2009). Thus, it is expected that correlation between different parameters may not be very high. It should be noted that the RS shows more consistent behavior as compared to CM with all the methods during post-monsoon season. In our present results, the correlation between different methods and instruments are consistent with earlier reports Tucker et al. (2009). Noteworthy is that the present analysis shows the potential of estimation of the MLH by different instruments and also by different methods giving consistent results in diurnal and seasonal patterns. In the current report, it is noted that the WCT method could be the robust and appropriate method for the estimation of BLH over the site than other methods and is less affected by the signal noise than the threshold and gradient methods.
5. Summary and conclusions
Fig. 3. Diurnal variation of mean MLH obtained using DL, CM and RS for the postmonsoon season (September–November 2011) over Manora Peak, Nainital. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Precise measurement of the BLH over a complex terrain (e.g. central Himalayan region) is extremely important for developing accurate weather models. In this current report, DL observations in post-monsoon are used to show the MLH characteristics over the Manora Peak, Nainital, a high altitude site in central Himalayan region by using different methods and different instruments. On a typical day, the MLH rises ( 0.8 km, AGL) in the daytime due to the convective vertical mixing and upslope wind which carries the aerosols over the site. In night a SBL ( 0.5 km, AGL) is formed due to the mechanical turbulence and down slope winds play significant role in maintaining nighttime BL dynamics. Similar diurnal pattern of the MLH has been observed by other ground based instruments like CM and RS. The estimated MLH by DL over the Manora Peak in the post monsoon season shows variability
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K.K. Shukla et al. / Journal of Atmospheric and Solar-Terrestrial Physics 109 (2014) 48–53
Fig. 4. Co-relation plot (R2) of MLH between DL–RS (left y-axis, solid circles) and DL–CM (right y-axis, open circles) for WCT and threshold/gradient method for 00, 06, 12 and 18 UT, respectively, observed during post-monsoon season (September–November 2011). Table 1 Correlation-coefficient of the different instruments and methods. Method/instruments
WCT DL–WCT RS WCT DL–WCT CM Threshold DL–PT gradient of RS Threshold DL–gradient CM
2
Correlation coefficient (R ) 00 UT
06 UT
12 UT
18 UT
0.85 0.66 0.65 0.42
0.84 0.65 0.62 0.56
0.78 0.51 0.73 0.43
0.81 0.66 0.64 0.44
between 0.57 70.1 and 0.45 70.05 km AGL in day and nighttime, respectively. The estimated MLH showed a good agreement, considering the differences among the various methods involving different instruments. A good consistency ( R2 40.8) between WCT DL–WCT RS and WCT DL–WCT CM has been observed by using different instruments and different methods. Therefore, our present study on the behavior of the MLH variation over a high altitude site in the Himalayan region could provide valuable insights into the dynamical aspects over the region.
K.K. Shukla et al. / Journal of Atmospheric and Solar-Terrestrial Physics 109 (2014) 48–53
Acknowledgements This work has been carried out as a part of GVAX campaign in joint collaboration among Atmospheric Radiation Measurement (ARM), Department of Energy (US), Indian institute of Science (IISC) and Indian Space Research Organization (ISRO), India. We thank Director, ARIES for providing the necessary support. We thank Prof. Rao Kotamurthi for his valuable suggestions for the improvement of the manuscript. We also acknowledge Dr. Baars for fruitful discussions regarding WCT method. One of the authors acknowledges Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates, for providing the fellowship. References Alappattu, Denny, P., Kunhikrishnan, P.K., Aloysius, Marina, Mohan, M., 2009. A case study of atmospheric boundary layer features during winter over a tropical inland station—Kharagpur. J. Earth Syst. Sci. 118, 281–293. Baars, H., Ansmann, A., Engelmann, R., Althausen, D., 2008. Continuous monitoring of the boundary-layer top with lidar. Atmos. Chem. Phys. 8, 7281–7296. Barlow, J.F., Dunbar, T.M., Nemitz, E.G., Wood, C.R., Gallagher, M.W., Davies, F., O0 Connor, E., Harrison, R.M., 2011. Boundary layer dynamics over London, UK, as observed using Doppler lidar during REPARTEE-II. Atmos. Chem. Phys. 11, 2111–2125, http://dx.doi.org/10.5194/acp-11-2111-2011. Basha Ghouse, Venkat, Ratnam M, 2009. Identification of atmospheric boundary layer height over a tropical station using high-resolution radiosonde refractivity profiles: comparison with GPS radio occultation measurements. J. Geophys. Res. 114, D16101, http://dx.doi.org/10.1029/2008JD011692. Brooks, I.M., 2003. Finding boundary layer top: application of a wavelet covariance transform to lidar backscatter profiles. J. Atmos. Oceanic Technol. 20, 1092–1105. Dumka, U.C., Satheesh, S.K., Pant, P., Hegde, P., Krishna, Moorthy K., 2006. Surface changes in solar irradiance due to aerosols over central Himalayas. Geophys. Res. Lett. 33, L20809, http://dx.doi.org/10.1029/2006GL027814. Dupont, E., Menut, L., Carissim, B., Pelon, J., Flamant, P., 1999. Comparison between the atmospheric boundary layer in Paris and its rural suburbs during the ECLAP experiment. Atmos. Environ. 33, 979–994.
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Emeis, S., Schäfer, K., Münkel, C., 2008. Surface-based remote sensing of the mixing-layer height—a review. Meteorol. Z. 17, 621–630. Gamage, N., Hagelberg, C., 1993. Detection and analysis of micro fronts and associated coherent events using localized transforms. J. Atmos. Sci. 50, 750–756. Kumar, R., Naja, M., Venkataramani, S., Wild, O., 2010. Variations in surface ozone at Nainital: a high altitude site in the central Himalayas. J. Geophys. Res. 115, D16302, http://dx.doi.org/10.1029/2009JD013715. Mather, J.H., Voyles, J.W., 2013. The ARM climate research facility: a review of structure and capabilities. Bull. Am. Meteorol. Soc. 94, 377–392. Ouwersloot, H.G., Vila-Guerau de Arellano, J., Nolscher, A.C., Krol, M.C., Ganzeveld, L.N., Breitenberger, C., Mammarella, I., Williams, J., Lelieveld, J., 2012. Characterization of a boreal convective boundary layer and its impact on atmospheric chemistry during HUMPPA-COPEC-2010. Atmos. Chem. Phys. 12, 9335–9353. Pearson, G.N., Davies, F., Collier, C., 2009. An analysis of the performance of the UFAM pulsed Doppler lidar for observing the boundary layer. J. Atmos. Oceanic Technol. 26, 240–250. Pearson, G., Davies, F., Collier, C., 2010. Remote sensing of the tropical rain forest boundary layer using pulsed Doppler lidar. Atmos. Chem. Phys. 10, 5891–5901, http://dx.doi.org/10.5194/acp-10-5891-2010. Sagar, R., Kumar, B., Dumka, U.C., Moorthy, K.K., Pant, P., 2004. Characteristics of aerosol spectral optical depths over Manora Peak: a high-altitude station in the central Himalayas. J. Geophys. Res. 109, D06207, http://dx.doi.org/10.1029/ 2003JD003954. Seibert, P., Beyrich, F., Gryning, S.E., Joffre, S., Rasmussen, A., Tercier, P., 2000. Review and inter comparison of operational methods for the determination of the mixing height. Atmos. Environ. 34, 1001–1027. Stull, R.B., 1988. An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, Dordrecht, Germany Tsuda, T., Ratnam, M.V., Kozu, T., Mori, S., 2006. Characteristics of 10-day Kelvin wave observed with radiosondes and CHAMP/GPS occultation during CPEA campaign (April–May 2004). J. Meteorol. Soc. Jpn. 84A, 277–293, http://dx.doi. org/10.2151/jmsj.84A.277. Tucker, S.C., Brewer, W.A., Banta, R.M., Senff, C.J., Sandberg, S.P., Law, D.C., Weickmann, A., Hardesty, R.M., 2009. Doppler lidar estimation of mixing height using turbulence, shear, and aerosol profiles. J. Atmos. Oceanic Technol. 26, 673–688. Väisälä Oyj, 2002. Ceilometer CT25K: User0 s guide, Väisälä Oyj, Vantaa.
Contents lists available at ScienceDirect
Journal of Atmospheric and Solar-Terrestrial Physics journal homepage: www.elsevier.com/locate/jastp
Estimation of the mixing layer height over a high altitude site in Central Himalayan region by using Doppler lidar K.K. Shukla a,b,n, D.V. Phanikumar a, Rob K. Newsom c, K. Niranjan Kumar d, M. Venkat Ratnam e, M. Naja a, Narendra Singh a a
Aryabhatta Research Institute of Observational Sciences, Nainital 263002, Uttrakhand, India Pt. Ravishankar Shukla University, Raipur, Chhatisgarh, India c Pacific Northwest National Laboratory, Richland, WA, USA d Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates e National Atmospheric Research Laboratory, Tirupati, India b
art ic l e i nf o
a b s t r a c t
Article history: Received 8 November 2013 Received in revised form 6 January 2014 Accepted 7 January 2014 Available online 17 January 2014
A Doppler lidar was installed at Manora Peak, Nainital (29.41N; 79.21E; 1958 amsl) to estimate mixing layer height for the first time by using vertical velocity variance as basic measurement parameter for the period September–November 2011. Mixing layer height is found to be located 0.57 7 0.1 and 0.45 70.05 km AGL during day and nighttime, respectively. The estimation of mixing layer height shows good correlation (R2 4 0.8) between different instruments and with different methods. Our results show that wavelet co-variance transform is a robust method for mixing layer height estimation. & 2014 Elsevier Ltd. All rights reserved.
Keywords: Doppler lidar Mixing layer height GVAX
1. Introduction The atmospheric boundary layer (ABL) is the lower most part of the troposphere. This layer of the atmosphere is directly influenced by the earth0 s surface and responds to surface forcing on a timescale of about an hour or less (Stull, 1988). The depth of the ABL is a parameter that varies daily in accordance with the thermal and frictional influence of the earth0 s surface. ABL evolution is mainly governed by thermal (solar heating) and mechanical (wind shear) turbulence. Surface fluxes of sensible and latent heat play a major role in the diurnal growth of the ABL. It is evident from previous reports that the ABL dynamics play a key role in the vertical transport and mixing of aerosols and chemical species from the surface to the free troposphere (Pearson et al., 2010; Ouwersloot et al., 2012). The rural ABL depth has been found to be shallower than the ABL depth over nearby urban areas (Dupont et al., 1999). Hilly and mountainous terrain exerts an important influence on the Earth0 s atmosphere. Terrain affects atmospheric transport and mixing at a wide range of spatial and temporal scales. Hence, accurate determination of the boundary layer height (BLH) and its diurnal
n
Corresponding author. E-mail addresses: [email protected], [email protected] (K.K. Shukla). 1364-6826/$ - see front matter & 2014 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jastp.2014.01.006
variation at high altitude sites are of great importance for understanding observed asymmetries in day and nighttime aerosol mass concentration. Previous studies have hypothesized the observed asymmetry to be associated with ABL dynamics (for e.g. Dumka et al. (2006)). However, there are no reports till date on the determination of BLH to corroborate the plausible mechanism responsible for the asymmetric behavior of aerosol mass concentration. Estimates of BLH have been obtained using observations from various instruments, including light detection and ranging (Lidar), sound detection and ranging (SODAR), radio acoustic sounding system (RASS), and radiosonde (RS), constellation observing system for meteorology, ionosphere, and climate (COSMIC) refractivity profiles have also been used to estimate BLH (Seibert et al., 2000; Basha et al., 2009; Barlow et al., 2011). However, these various methods often produce different BLH estimates depending on the observed parameters and the performance characteristics of the instruments (Seibert et al., 2000). Previous studies show that BLH estimates vary from 2 to 3 km over a tropical station Gadanki (13.51N; 79.21E; 375 above mean sea level (amsl)) (Basha and Ratnam, 2009) to 0.5–0.7 km over Kharagpur (22.321N, 87.321E, 40 m amsl) and the Danum valley region of Sabah, Borneo (4.91N; 117.81E; 198 amsl) (Alappattu et al., 2009; Pearson et al., 2010). Additionally, a few reports even show that BLH is invariant ( 1 km) at Westminster (51.41N, 0.11W) (Barlow et al., 2011). These results show the large spatial heterogeneity in the nature of
K.K. Shukla et al. / Journal of Atmospheric and Solar-Terrestrial Physics 109 (2014) 48–53
the ABL around the globe. Therefore, the study of ABL dynamics over land, sea and complex terrain (including buildings, forests, hills and mountains) is imperative for air pollution models, atmospheric flow models and for climate models. The present study aims to investigate ABL characteristics over a high altitude mountainous site. Specifically, we examine the diurnal and seasonal pattern of the mixing layer height (MLH) over Manora Peak, Nainital, India using observations from a collocated Doppler lidar, ceilometer and radiosonde. Comparisons are made between MLH estimates obtained from these three observational systems using three different data analysis methods (e.g. threshold, gradient and wavelet covariance transform (WCT)). The results are discussed in the light of current understanding of ABL variation over the site.
2. Observational site and general meteorology Fig. 1(a) shows the map of Indian sub-continent highlighting the observational site. The Manora Peak, Nainital site located in the Central Himalayan region at an altitude of 1958 m amsl is shown in Fig. 1(b). The plains of the Ganges Valley lie approximately 50 km to the south, and higher altitude mountains (4 1500 m amsl) of the Himalaya Range lie to the north. The site is located well away from large industrial and population centers, and the air is relatively clean. The town of Nainital is approximately 2 km north of the site, and the nearest cities with small-
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scale industries are located approximately 20 to 40 km south of the site, including the cities of Haldwani at (423 m amsl), Pantnagar (231 m amsl), and Rudrapur (209 m amsl). The mega city of Delhi, capital of India, is located about 225 km to the southwest. A detailed description of the topography and general meteorology of the observational site is discussed elsewhere (Sagar et al., 2004; Kumar et al., 2010).
3. Instrumentation and methodology The US Department of Energy0 s Atmospheric Radiation Measurement (ARM) program (Mather and Voyles, 2013) deployed the first ARM Mobile Facility (AMF1) at Manora Peak, Nainital as part of the Indo-US collaborative project Ganga Valley Aerosol Experiment (GVAX). The AMF1 contains a large number of ground-based in situ and remote sensing instruments for atmospheric measurement, including a Doppler lidar (DL), laser ceilometer (CM), and radiosonde (RS). 3.1. Doppler lidar The AMF1 DL is a scanning coherent DL that operates at a wavelength of 1.548 μm, a low pulse energy ( 100 μJ), and a high pulse repetition frequency of 15 kHz (Pearson et al., 2009). The DL is sensitive to scattering from aerosol, and provides measurements of radial (line-of-sight) velocity, signal-to-noise ratio (SNR), and attenuated aerosol backscatter. During the GVAX campaign, the DL was operated with a range resolution of 30 m (320 range bins covering a maximum height of 9.6 km) and a 1-s pulse integration time. The instrument was configured to perform planposition-indicator (PPI) scans once every hour, and range-heightindicator (RHI) scans once every 2 h. The vast majority of the time ( 90%), however, was spent with the beam pointing vertically in order to profile vertical velocities over the site. For this study, we use the vertical pointing observations from the DL to estimate MLH during the post-monsoon period from September through November 2011. Five-min averaged profiles of vertical velocity variance were computed from 1-s DL measurements, and the effects of noise were minimized by using only those velocity measurements such that SNR4 20 dB. The vertical velocity variance field was then used to estimate MLH (Tucker et al., 2009; Barlow et al., 2011). 3.2. Laser ceilometer Measurements of cloud base height and backscatter are provided by the Väisälä CT25K laser ceilometer (CM). The instrument provides backscatter measurements with vertical and temporal resolutions of 30 m and 16 s, respectively. Other technical details and specifications of the CM can be found at www.arm.gov or in Väisälä Oyj (2002). The backscatter data from the CM can be used to estimate MLH by identifying the height where the backscatter decreases abruptly. For this study, 5-min averaged profiles were computed from the 16-s backscatter measurements. These profiles were then used to estimate the MLH with the gradient and WCT methods as described in Sections 3.5 and 3.6. 3.3. Radiosonde
Fig. 1. (a) Altitude–topography map of Indian sub-continent and (b) zoomed version of latitude–longitude altitude display of central Himalayan region described in Section 2. Coordinates of the observational site (Manora Peak, Nainital (NTL)) are shown in the plot.
During the GVAX campaign, high resolutions radiosondes (RS92 Väisälä) were launched four-times daily from the Manora Peak site. The launch times were 00, 06, 12 and 18 GMT. The RS provided measurements of temperature, relative humidity, pressure, and winds with a vertical resolution of the RS measurements
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of about 10 m. Other technical details and specifications of RS-92 Väisälä (RS) can be found in www.arm.gov. For this study, potential temperature (PT) profiles were computed from the RS data, and used to estimate the inversion layer height (ILH) with the gradient and WCT methods, as described in Sections 3.5 and 3.6, respectively. Quality checks were performed on the RS data using the method described in Tsuda et al. (2006). The RS PT profiles were interpolated to a height resolution of 30 m in order to match the vertical resolution of the DL and CM. 3.4. Threshold method The threshold method was used to estimate the MLH from DL vertical velocity variance profiles. In this method, the MLH is estimated by locating the minimum height where the vertical velocity variance (sw2) exceeds a prescribed threshold value (Tucker et al., 2009). Tucker et al. (2009), Pearson et al. (2010) and Barlow et al. (2011); used the threshold values between 0.1 and 0.3 m2 s 2 depending on location and meteorological conditions. For this study, the observational site is located at high altitude and the meteorological conditions are quite different from urban locations (Sagar et al., 2004; Kumar et al., 2010). Therefore, we varied the threshold value from 0.1 to 0.5 m2 s 2 to obtain a reasonably realistic MLH in comparison with the previous reports and we found that an optimum threshold value of 0.25 m2 s 2 during the post-monsoon season (SON). However, it should be noted that this threshold value have seasonal variability.
3.6. Wavelet covariance transform method The wavelet covariance transform (WCT) was used to estimate the BLH from the DL, CM and RS measurements. The WCT is defined as Z 1 Zu zb W f ða; bÞ ¼ dz; ð1Þ f ðzÞh a Zl a where z is the altitude, f(z) is either the DL vertical velocity variance, CM backscatter, or the RS potential temperature profile, and Zl and Zu are the lower and upper altitude limits of the profile, respectively. For this study, we used the Haar function (i.e. step function) to detect changes in the profile (Gamage and Hagelberg, 1993). The Haar function is given by 8 a > < þ 1; b 2 r z r b zb h ¼ 1; b rz r b þ 2a ð2Þ > a : 0; elsewhere where b is the location at which the Haar function is centered, and a is the width or dilation of the function. The optimum value of the dilation a is determined from the depth of the transition zone. The main challenge is in choosing the appropriate dilation (Brooks, 2003; Baars et al., 2008). The identification of the MLH is done by varying a between 60 and 360 m and locating the height, z ¼b, which maximizes Wf.
4. Results and discussion 3.5. Gradient or derivative method The gradient method was used to estimate the MLH from the CM backscatter profiles, and from the RS potential temperature profiles. For the CM, the MLH is found by locating the height corresponding to the minimum in the first derivative (dβ/dz) of the range corrected and sensitivity normalized backscatter (β) (srad 1 km 1 10 4) profile (Emeis et al., 2008). For the RS, the inversion layer height is found by locating the height corresponding to the maximum in the first derivative of the potential temperature profile (Seibert et al., 2000).
Fig. 2(a) shows the diurnal variation of the vertical velocity variance from the DL and Fig. 2(c) shows a time series of MLH estimates on a typical day (16 October 2011).The MLH estimated by using WCT for DL is plotted over the time-height display with black solid line. Dotted green line represent DL MLH estimates using the threshold method and the blue solid line represents the DL MLH estimated by the WCT method, as described in Section 3.6. The diurnal variation in the MLH is clearly evident, with larger values during the daytime ( 0.8 km above ground level (AGL))
Fig. 2. Range-time intensity (RTI) plot showing the mixed layer evolution on 16 October 2011 using (a) DL MLH with WCT plotted with black solid line and (b) CM MLH with WCT plotted with black solid line (c) diurnal variation of the MLH obtained using DL (threshold/WCT), CM (gradient/WCT) and RS (PT gradient/WCT) on the same day. (d) Identification of inversion layer height from Radiosonde Potential temperature profile at 12 UT by using WCT method at different dilations. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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and lower values during the nighttime ( 0.35 km AGL). The increase in the MLH during the morning hours is expected due to surface heating and the subsequent buildup of convection and this results in the vertical transport of aerosols from the nearby valley region and local sources over the Manora Peak. Velocity variance shows that the maximum height of the mixing layer occurring on 08 UT corresponding to the period around solar noon, and the period when thermally driven upslope flow occurs. During the nighttime, with the absence of surface heating, the depth of the mixed layer decreases and the boundary layer becomes increasingly more stably stratified. Winds also play an important role in maintaining a stable NBL. It is generally found that the nighttime wind pattern is dominated by down slope flow over the site. Fig. 2(b) shows the diurnal variation of the aerosol backscatter from the CM on 16 October 2011. The MLH estimated by using WCT for CM is plotted over the time–height display with black solid line. The dotted red line and black solid line in Fig. 2(c) represent CM MLH estimates using the gradient and WCT methods, respectively. The MLH increases after sunrise and reaches a maximum of 0.8 km AGL at about solar noon (08:00 UT). After sunset the boundary layer becomes more stably stratified and the MLH decreases to 0.35 km AGL at about 12:00 UT. Also after sunset a periodic oscillation is observed in the DL and CM data. This may be due to topographically forced waves. The inversion layer height is estimated from RS PT profiles using the gradient and WCT methods. We found an appropriate dilation to be 120 m for the WCT method when applied to the RS PT profiles (see Fig. 2(d)). Fig. 2(c) shows RS inversion layer height estimates at the sounding times of 00, 12, and 18 UT. The open blue triangles represent inversion layer height estimates using the WCT method, and the solid black squares represent estimates using the gradient method. Both methods give nearly identical results, with values of 0.165, 0.705 and 0.375 km AGL, at 00, 12 and 18 UT, respectively. In general, a close match in the estimation of MLH among the different methods and different instruments can be noticed and the differences whatever small can be attributed to measuring technique which is sensitive to the measured parameter. Fig. 3 shows the post-monsoon (September–November 2011) seasonal mean diurnal variation in the MLH using the (i) threshold and WCT method for DL (dotted green line and solid black line), (ii) gradient and WCT method for CM (dotted magenta line and solid blue line), and (iii) PT gradient and WCT method for RS (red
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open circle and red open square). The diurnal mean of the MLH from the DL and CM observations were obtained by dividing the 24-h cycle into 30-min bins and then computing a seasonal average within each bin. Larger values of vertical velocity variance during the daytime can be attributed to vertical mixing of air (convective mixing). The MLH estimates from the DL and CM data show a maximum during the day time of about 0.57 km AGL, and a minimum during the night time of 0.35 km AGL. The DL MLH reaches a maximum at 06:00 UT during daytime. The DL MLH and the CM MLH are varying between 0.35 and 0.44 km AGL during night time and is also consistent with RS observations. The minimum and maximum RS inversion layer height values were found to be 0.44 and 0.57 km AGL, respectively. The above observed height of the BL ranging between 0.3 and 0.6 km AGL during the day and nighttime can be attributed to the topography of the site. Correlation diagrams between the various instruments and methods are shown in Fig. 4. These correlation diagrams include MLH estimates obtained at 00, 06, 12 and 18 UT during the postmonsoon period in 2011. Fig. 4(a) shows correlation diagrams between the RS WCT and DL WCT MLH estimates, and between the CM WCT and DL WCT MLH estimates. Fig. 4(b) shows correlation diagrams between the RS gradient and DL threshold MLH estimates, and between the CM gradient and DL threshold MLH estimates. Overall, there is good agreement between the various MLH estimates. Correlation (R2) coefficients between the DL with RS and CM are 0.8 and 0.6 with WCT method. Similarly, the correlations between the DL with RS and CM are 0.6 and 0.5 with threshold method (values of correlations with different instruments and methods for 00, 06, 12 and 18 UT are given in Table 1). The plausible reason for the observed discrepancies in correlation could be attributed to response of different instruments to BL differently keeping in view of the sensitivity of each instrument. For example, near BL altitude, it is not always possible to see temperature inversion and sharp reduction in the RH simultaneously (Basha et al., 2009). Thus, it is expected that correlation between different parameters may not be very high. It should be noted that the RS shows more consistent behavior as compared to CM with all the methods during post-monsoon season. In our present results, the correlation between different methods and instruments are consistent with earlier reports Tucker et al. (2009). Noteworthy is that the present analysis shows the potential of estimation of the MLH by different instruments and also by different methods giving consistent results in diurnal and seasonal patterns. In the current report, it is noted that the WCT method could be the robust and appropriate method for the estimation of BLH over the site than other methods and is less affected by the signal noise than the threshold and gradient methods.
5. Summary and conclusions
Fig. 3. Diurnal variation of mean MLH obtained using DL, CM and RS for the postmonsoon season (September–November 2011) over Manora Peak, Nainital. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Precise measurement of the BLH over a complex terrain (e.g. central Himalayan region) is extremely important for developing accurate weather models. In this current report, DL observations in post-monsoon are used to show the MLH characteristics over the Manora Peak, Nainital, a high altitude site in central Himalayan region by using different methods and different instruments. On a typical day, the MLH rises ( 0.8 km, AGL) in the daytime due to the convective vertical mixing and upslope wind which carries the aerosols over the site. In night a SBL ( 0.5 km, AGL) is formed due to the mechanical turbulence and down slope winds play significant role in maintaining nighttime BL dynamics. Similar diurnal pattern of the MLH has been observed by other ground based instruments like CM and RS. The estimated MLH by DL over the Manora Peak in the post monsoon season shows variability
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Fig. 4. Co-relation plot (R2) of MLH between DL–RS (left y-axis, solid circles) and DL–CM (right y-axis, open circles) for WCT and threshold/gradient method for 00, 06, 12 and 18 UT, respectively, observed during post-monsoon season (September–November 2011). Table 1 Correlation-coefficient of the different instruments and methods. Method/instruments
WCT DL–WCT RS WCT DL–WCT CM Threshold DL–PT gradient of RS Threshold DL–gradient CM
2
Correlation coefficient (R ) 00 UT
06 UT
12 UT
18 UT
0.85 0.66 0.65 0.42
0.84 0.65 0.62 0.56
0.78 0.51 0.73 0.43
0.81 0.66 0.64 0.44
between 0.57 70.1 and 0.45 70.05 km AGL in day and nighttime, respectively. The estimated MLH showed a good agreement, considering the differences among the various methods involving different instruments. A good consistency ( R2 40.8) between WCT DL–WCT RS and WCT DL–WCT CM has been observed by using different instruments and different methods. Therefore, our present study on the behavior of the MLH variation over a high altitude site in the Himalayan region could provide valuable insights into the dynamical aspects over the region.
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