Sección Especial / Special Section: V Workshop on Lidar Measurements in Latin America
On
the
use
cirrus
clouds
for
ground
‐
based
elastic
lidar
calibration
Calibrado
de
un
lidar
elástico
operado
desde
tierra
con
nubes
tipo
cirro
F. Navas‐Guzmán
(*), J. L. Guerrero‐Rascado, J. A. Bravo‐Aranda,
L. Alados‐Arboledas
Atmospheric Physics Group, Andalusian Center for Environmental Research (CEAMA), and Science Faculty, University of Granada, 18071, Granada, Spain
(*) Email: [email protected] S: miembro de SEDOPTICA / SEDOPTICA member
Recibido / Received: 16/11/2010. Versión revisada / revised versión: 16/02/2011. Aceptado / Accepted: 18/02/2011
REFERENCES AND LINKS
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The Scientific Basis, contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press, Cambridge (2001).
[3] P. Forster, V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D. W. Fahey, J. Haywood, J. Lean, D.C. Lowe, G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulz, R. Van Dorland, “Changes in Atmospheric constituents and in radiative forcing”, in Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press, Cambridge (2007).
[4] C. Pilinis, S. N. Pandis, J. H. Seinfeld, “Sensitivity of direct climate forcing by atmospheric aerosols to aerosol size and composition”, J. Geophys. Res. 100, 18739–19754 (1995).
ABSTRACT:
A key parameter to retrieve backscatter coefficient from elastic lidar signals is the backscatter coefficient at a reference height. Traditionally, such a calibration height must fulfil the criterion that at this altitude the particle backscatter coefficient is negligible compared to the molecular backscatter value. Such clean‐air conditions are normally given in the upper troposphere. This procedure cannot be applied for those channels that present low signal‐to‐noise ratio (SNR) at the reference height. To solve this problem an alternative calibration method using cirrus clouds is presented.
Key words: Lidar, Reference Height, Cirrus Clouds, Backscatter Coefficient, Klett’s Inversion.
RESUMEN:
Un parámetro clave para la obtención del coeficiente de retrodispersión a partir de señales elásticas lidar es la altura de referencia. Tradicionalmente, esta altura de calibración es tal que el coeficiente de retrodispersión de aerosol es despreciable comparado con el valor de retrodispersión molecular en dicha altura. Tales condiciones de aire limpio suelen ser dadas en la troposfera superior. Este criterio no puede ser aplicado para aquellos canales que presentan una baja razón señal ruido en la altura de referencia. Para solucionar este problema se presenta un método alternativo de calibración con nubes tipo cirro.
Palabras clave: Lidar, Altura de Referencia, Nubes Tipo Cirro, Coeficiente de Retrodispersión,
[5] J. L. Guerrero‐Rascado, B. Ruiz, L. Alados‐Arboledas, “Multi‐spectral lidar characterization of the vertical structure of Saharan dust aerosol over southern Spain”, Atmos. Environ. 42, 2668–2681 (2008).
[6] J.A. Reagan, X. Wang, M. T. Osborn, “Spaceborne lidar calibration from cirrus and molecular backscatter returns”, IEEE T. Geosci. Remote 40, 2285‐2290 (2002).
[7] F. G. Fernald, B. M. Herman, J. A. Reagan, “Determination of aerosol height distribution by lidar”, J.
Appl. Meteorol. 11, 482‐489, (1972).
[8] J. D. Klett, “Stable analytical inversion solution for processing lidar returns”, Appl. Opt. 20, 211–220 (1981).
[9] J. D. Klett, “Lidar inversion with variable backscatter/extinction ratios”, Appl. Opt. 24, 1638–1643 (1985).
[10] F. G. Fernald, “Analysis of atmospheric lidar observations: some comments”, Appl. Opt. 23, 652–653, (1984).
[11] Y. Sasano, E. V. Browell, S. Ismail, “Error caused by using a constant extinction/backscattering ratio in lidar solution”, Appl. Opt. 24, 3929‐3932 (1985).
[12] D. Müller, A. Ansmann, V. Freudenthaler, K. Kandler, C. Toledano, A. Hiebsch, J. Gasteiger, M. Esselborn, M. Tesche, B. Heese, D. Althausen, B. Weinzierl, A. Petzold, W. von Hoyningen‐Huene, “Mineral dust observed with AERONET sun photometer, Raman lidar, and in situ instruments during SAMUM 2006: Shape‐dependent particle properties”, J. Geophys. Res. 115, D11207 (2010).
[13] A. Ansmann, U. Wandinger, M. Riebesell, C. Weitkamp, W. Michaelis, “Independent measurement of extinction and backscatter profiles in cirrus clouds by using a combined Raman elastic‐backscatter lidar”, Appl. Opt. 31, 7113‐7131 (1992).
[14] R. R. Draxler, G. D. Rolph, “HYSPLIT (HYbrid Single‐Particle Lagrangian Integrated Trajectory) model” access via NOAA ARL READY Website: http://www.arl.noaa.gov/ ready/hysplit4.htmlS. NOAA Air Resources Laboratory, Silver Spring, MD, 2003.
1.
Introduction
Atmospheric aerosols, which originate both form natural sources and from human intervention, play an important role in many atmospheric processes. Although they are only a minor constituent of the atmosphere, they have appreciable influence on the Earth’s radiation budget [1,2], air quality and visibility, clouds, precipitation, and chemical processes in the troposphere and stratosphere. The largest source of uncertainty in predicting climate change is due to uncertainties involved in the estimation of aerosol radiative forcing [3]. This uncertainty arises mainly because of the lack of adequate information on the temporal and spatial distribution of aerosols and their associated properties across the globe [4]. Therefore, vertically resolved measurements of physical and optical properties of particles are of great interest.
Multiwavelength Raman lidar observations have matured into a powerful tool for the vertical resolved characterization of optical and microphysical properties of atmospheric aerosol particles. Raman lidar systems that operate with
laser pulses at three wavelengths are the minimum requirement for a comprehensive particle characterization. The Raman lidar model LR331D400 system operated at EARLINET Granada station (37.16oN, 3.60oW, 680 m a.s.l.) is configured in a monostatic biaxial alignment arrangement based on a Nd:YAG laser (1064 nm) equipped with second and third harmonic generators (532 and 355 nm, respectively). A complete description is given by Guerrero‐ Rascado et al. [5]. Parameters that are derived by such systems are particle backscatter and extinction coefficients, particle lidar ratios (extinction‐to‐backscatter ratio) and Ångström exponents.
the backscatter coefficient. In the case of multiwavelength systems the SNR of the various channels are different and the calibration in the molecular region could be feasible in some channels, and impossible in others. For the last ones it could be possible to look for a different reference. The procedure here presented consists in choosing cases with cirrus clouds and to use the cloud base for calibration. Calibration with cirrus clouds have been used previously for satellite lidar measurements [6], achieving uncertainties within 5%. The backscatter coefficient in cirrus clouds is independent on the spectral range, so it is possible to use the backscatter coefficient in the cirrus base obtained for a channel calibrated above cirrus cloud and calibrate the problematic one.
2.
Methods
The basis of any lidar signal analysis is the lidar equation that describes the received signal as a function of atmospheric and system parameters. The lidar equation for return signals due to elastic backscattering by air molecules and aerosol particles can, in the simplest form, be written as [7]:
RLO R R r dr
R E R P 0 2
0 ( ) ( ) exp 2 ( ) )
( , (1)
where P(R) is the signal owing to Rayleigh and particle scattering received from distance R, E0 is the transmitted laser pulse energy, ηL contains
lidar parameters describing the efficiencies of the optical and detection units, and O(R)
describes the overlap between the outgoing laser beam and the receiver field of view. β(R) (in m‐1 sr‐1) and α(R) (in m‐1) are the total backscatter and extinction coefficients, respectively. Backscattering and extinction processes are both caused by aerosol particles (index “aer”) and molecules (index “mol”): (R)aer(R)mol(R), (2) (R)aer(R)mol(R). (3) Molecular absorption effects are ignored for the used wavelengths. Equations (1)‐(3) can be summarized to:
( ) ( )
. 2 exp ) ( ) ( ) ( 0 0
R aer molmol aer L dr r r R R E R S (4)
with the range‐corrected lidar signal
S(R)=R2P(R). The full overlap is assumed [O(R)=1]. Assuming that the molecular part of (2) and (3) can be calculated by means of standard atmosphere conditions or using an atmospheric density profile derived from atmospheric soundings performed in a nearby station, αaer(R) and βaer(R) remain as two height‐
dependent unknowns while only one signal has been measured.
One usually solves this problem by assuming a (“a priori” unknown) relationship between aerosol backscatter and extinction, usually called lidar ratio (Laer(R)=αaer(R)/βaer(R)). The
determination of βaer(R) at one wavelength from
Eq. (4) requires the additional assumption of an unknown constant that represents the height‐ independent system parameters. To solve the equation for βaer(R), usually a calibration or
reference value βaer(R0), representing the aerosol
backscatter at a certain height R0, is used.
Under these assumptions, the equation for βaer(R) can be solved following the studies of
Klett, Fernald and Sasano [7‐11]:
, ) , ( ) ( ) ( 2 ) ( ) ( ) ( ) ( ) ( 2 exp ) ( ) ( ) ( 0 0 0 0 0 0
R R aer mol aer mol RR aer mol mol aer dr R r T r S r L R R R S dr r L r L R S R R (5)
rR aer mol mol dr r L r L R r T 0 ' ) ' ( ) ' ( 2 exp ) ,
( 0 ,(6)
where Lmol(R)=αmol(R)/βmol(R)=8π/3.
sunphotometer data available simultaneously with the lidar measurements. For this reason ancillary information, like those obtained from backward trajectories analyses and/or sunphotometer measurements available at other times of this day, can be used to select a lidar ratio appropriated to the aerosol type.
The selection of the reference range R0 in Eqs. (5) and (6) is usually done looking for a R0 where the particle backscatter coefficient is negligible compared to the known molecular backscatter value. Such clean‐air conditions are normally given in the upper troposphere. The problem appears when at these altitudes the signal shows a low signal‐to‐noise ratio (SNR) for the wavelength considered. In these situations, it is not possible to choose the reference range R0 in the altitude with clean‐air conditions to retrieve the aerosol backscatter coefficient.
Therefore, in order to determine the particle backscatter‐coefficient profile from Eqs. (5) and (6), we need to know the particle backscatter coefficient at a suitable reference height R0’, where the signal‐to‐noise ratio (SNR) of the problematic channel would be appropriate. If the use of a reference height at molecular conditions is not possible, we can use cirrus clouds to calibrate the problematic signal. It is known that cirrus clouds show an independent behaviour with the wavelength, and thus the aerosol backscatter coefficient at all wavelengths must be the same. The idea is calibrating with a good (from the signal‐to‐noise ratio point of view) channel in the far range (above cirrus cloud), where the aerosol component is negligible, and to retrieve the aerosol backscatter profile at this wavelength. After that, we use the aerosol backscatter coefficient at the cloud base to calibrate the problematic channel. Finally, we can retrieve the aerosol backscatter profile from Eqs. (5) and (6).
An important parameter that describes the spectral slope of the backscatter coefficients βλ(R) is the so‐called backscatter‐related Angström exponent. This parameter is known to be strongly dependent on particle size and shape.
1064 532 ln
) , 1064 (
) , 532 ( ln ) ( 1064 532
R R
R
a aer
aer o
. (7)
Inside the cirrus clouds this parameter must be close to zero.
3.
Results
and
discussion
Raman lidar system at EARLINET Granada station shows in some circumstances a low SNR at 1064 nm in the molecular range, and therefore it is not possible to use this altitude for calibration. The above mentioned technique has been used to calibrate this channel. The 532nm‐ channel was used to retrieve the aerosol backscatter coefficient at the cloud base, because the calibration was possible in the molecular range (above cirrus cloud) using this channel.
The calibration method described previously has been used successfully for several cases in which cirrus clouds were present. The case showed in this work corresponds to a Saharan dust outbreak
.
A lidar ratio of 50 sr was chosen for this case for the different channels. This lidar ratio is coherent for this kind of particles [12]. A lidar ratio of 15 sr inside cirrus cloud [13] was used to retrieve the backscatter profile at 532 nm.The measurements were performed during the daytime on 27 February 2008 (12:00‐13:00 GMT). Figure 1 shows the lidar quicklook for this day. This plot shows the range‐corrected lidar signal
S(R) along the measurement session. The colour scale is related to the signal received. We can see cirrus clouds around 12 km (a.s.l.) during the measurement. In this plot it can be seen that the largest aerosol load is below 3 km (a.s.l.), although it is possible to see some aerosol layers between 3 and 4 km.
spectral range of 440‐1020 nm and medium‐ high aerosol optical depth (0.17 at 670 nm).
Fig. 1. Lidar quicklook on 27 February 2008 during the daytime measurement.
Figure 2(a) shows the aerosol backscatter profiles at 355, 532 and 1064 nm retrieved for this case. The blue and green lines correspond to the backscatter profile at 355 and 532 nm, respectively. The reference range used was 6 km at 355 nm channel. The reference height for the 532 nm channel was chosen above the cirrus clouds, 13 km, in order to calibrate the infrared channel. Two different calibration methods are shown for 1064 nm channel. The gray line corresponds to the calibration in the molecular range, whereas red line corresponds to the case when the calibration with cirrus cloud is used. The profile calibrated in the molecular range shows too low values.
Figure 2(b) shows backscatter‐related Angström exponents retrieved from the lidar signals. For the spectral range 355‐532 nm, the values are around 0.5 below 3 km. This is a typical value for mineral dust particles and it confirms the results expected. If we use the 1064nm‐channel calibrated in the molecular range, the Angström exponent for the spectral range 532‐1064 nm presents larger values, above 1.0 in the whole profile. In this sense we can see large discrepancies between Angström exponent determined for different spectral ranges. This behaviour improves significantly when the 1064 nm profile is calibrated using the cirrus cloud. In fact, the Angström exponent for 532‐1064 nm presents values around 0.5 in the near range and a good agreement with the Angström exponent for 355‐532 nm.
Fig. 2. (a) Aerosol backscatter profiles at 355, 532 nm (blue and green lines) and 1064 nm (gray line: calibration using the molecular range; red line: calibration using cirrus clouds). (b) Angström exponents derived from 355‐532 nm channels (blue line) and 532‐1064 channels (gray line: calibration using molecular range; red line: calibration using cirrus clouds).
4.
Conclusion
The 1064nm‐backscatter coefficient profile shows an important improvement when the new calibration with cirrus is used. This method has been performed to cases with a low signal‐to‐ noise ratio in the molecular range. The most important improvements are reached in planetary boundary layer, where the profiles of corrected backscatter coefficients and Ångström exponents show more reasonable values considering the typical load of particles under different atmospheric conditions.
Acknowledgements
This work was supported by the Spanish Ministry of Science and Technology through projects CGL‐2006‐27108‐E/CLI (DAMOCLES Aerosol Scientific Thematic Network), CGL2008‐ 01330‐E/CLI, CGL2009‐08031‐E/CLI, CGL2010‐ 09225‐E (Spanish Lidar Network), CGL2010‐ 18782 and CSD2007‐00067; by the Andalusian Regional Government through projects P10‐ RNM‐6299 and P08‐RNM‐3568; and by EU
through EARLINET‐ASOS project (EU