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Figure 5.2: Data preparation scheme.
Conversion to MATLAB, Data Averaging and Background Correction
After being transferred from Ny-Ålesund to Potsdam, data files are present as zip-files containing all raw data profiles of one hour. These files are unpacked and merged to integration blocks, aiming at a sufficiently large SNR with as much small scale information as possible. The standard spatial resolution is set to 60 m, occasionally a 30-m resolution is used. The temporal resolution is varied over a wider range. Data acquisition is usually carried out with 2 min integration time but can be shorter when looking at phenomena which vary on smaller time scales like clouds. For aerosol data analysis, the standard temporal resolution is set to 10 min, for stable aerosol layers it can be increased to 30 or 60 min (see examples in Fig. 5.3a). Raman signals, which suffer from weaker intensities due to a smaller scattering cross section, sometimes also require broader averaging of up to 60 min. Optionally, data can be averaged individually after analyzing the meteorological and atmospheric conditions. The signal background is a superposition of "electronic noise", i.e., the detector’s counting rate in darkness and the background signal from the atmosphere, which increases with the elevation angle of the sun (cf. Fig. 5.3b). The data profiles are averaged between 60 and 120 km ASL and then corrected by this background value. The signals obtained in the PC mode of the transient recorders further need to be corrected for dead time intervals, which means that after detecting one single photon, there is a time interval, in which no other photon can be detected. Tests have shown that cross-talk between the detectors can be neglected.
Signal Assembly
Necessity of signal assembly occurs due to two different reasons. First, some wave-lengths are detected in two different transient recorder detection modes: AN and PC (cf. Sec. 4.4.2). While the AN mode can be used for the near field as photons can be detected continuously, single photons can be detected in the PC mode and hence
1013 1014
(a)Profiles of the 532-nm channel with different temporal averaging (data from 1 April 2009, 10:30 UTC).
1013 1014
(b) Profiles of the 532-nm channel at 10:30 UTC and 22:30 UTC (data from 1 April 2009).
Figure 5.3: Raw PC profiles of the 532-nm channel.
it is more suitable for the weaker far field signal. Second, in the 2007/2008 KARL configuration, the profiles of the small and large telescope have to be mounted for the wavelengths detected by both mirrors. In both cases, the assembly follows the same scheme: An altitude interval of several hundred meters in which both signals are supposed to be correct is chosen with nb being the number of bins within the chosen altitude interval. This interval depends on the signal strength, e.g., lower altitudes are chosen for the weaker Raman channels. The AN signal is then scaled to the PC signal, subtracting a constant backgroundC and dividing it by a constantk:
IANnew = IAN−C
k . (5.1)
The constants are obtained from the requirement that the deviation of both signals is minimal within the interval:
nb is the number of bins within the chosen altitude interval. Assembly is done at the height step with minimal difference between the two signals, using a weighted adaption function over the altitude interval. Occasionally, if the altitude interval of interest can be fully covered by one of the signals, the original AN or PC profiles are used. The prepared signal profiles are labeled asPel and Pram.
5.1. KARL DATA PREPARATION
5.1.2. Backscatter Coefficient Calculations
Klett Method
Vertical profiles of the aerosol backscatter coefficient βaer(z,λ) at 532 and 355 nm in parallel and perpendicular polarization as well as at 1064 nm are retrieved using the Klett algorithm [Klett, 1981]. Equation 3.19 relates the elastic LIDAR signals to the scattering and extinction coefficients of the molecules and particles in the atmosphere:
• βaer(z,λ) - aerosol backscatter coefficient,
• βray(z,λ) - molecular backscatter coefficient,
• αaer(z,λ) - aerosol extinction coefficient,
• αray(z,λ) - molecular extinction coefficient.
Hence, one single elastic backscatter signal depends on four different quantities. The molecular backscatter coefficientβray(z,λ) is linearly related to the density of N2molecules as they account for most of the atmosphere. It can be calculated using T(z) and p(z) obtained with radio soundings of the atmosphere:
βray(z,λ) = p(z) kBT(z)
dσraysca
dΩ (λ). (5.3)
αray(z,λ) can be calculated likewise according to Eq. 3.20. With βaer(z,λ) andαaer(z,λ) there are still two unknown variables. To be able to find an analytical solution, Klett assumes the quotient of the two coefficients - the LIDAR ratio (LR) - to be constant:
LR(z,λ) = Laer = α
aer(z,λ)
βaer(z,λ) =constant for each ∆z. (5.4) This assumption is a rough estimate, since LR is a function of composition, shape and size distribution of the scattering aerosol. It can be taken from tables [Müller et al., 2007] or from empirical studies. Aerosols, which strongly absorb incident radiation, are characterized by a large LR at the absorbed wavelengths. LR is one of the most critical input parameters, since it can strongly vary with height. After a first evaluation (assuming a constant LR), the Klett algorithm can be reapplied iteratively with a LR profile modified according to the results, e.g. with different values for individual cloud or aerosol layers. Additionally, co-located photometer measurements of the AOD can be used to estimate a column-related LR from the ratio of the photometer AOD, which equals the column-integrated aerosol extinction coefficient αaer (Eq. 3.21), and the column-integrated backscatter coefficient. However, if LR is obtained iteratively with the Klett algorithm or from photometer comparisons, it refers to a layer integrated mean LR:
LRlay(λ) = Rztop
zbottomαaer(z,λ)dz Rztop
zbottomβaer(z,λ)dz. (5.5)
Usually, the LR profile is initially set to 30 sr for all three wavelengths and at all altitudes.
Furthermore, the backscatter coefficient at a reference altitude zref at the far end of the LIDAR profile is needed. zref is chosen to be an altitude, at which the atmosphere is assumed to be aerosol free, such that Rayleigh scattering is the dominant scattering process. The LIDAR signal is fitted to the molecular profile and an aerosol background
value above all aerosol layers in the stratosphere around 18 km to 20 km ASL. A backscatter ratio (BSR) of 1.05 at 532 nm implies that the aerosol particle contribution to the backscatter is only 5 % of the molecular contribution of the Rayleigh atmosphere:
BSR(z,λ) = β
ray(z,λ) +βaer(z,λ)
βray(z,λ) . (5.6)
This is frequently referred to as "clear sky condition". The backscatter values for the other wavelengths can be derived assuming an aerosol backscatter dependency of 1/λ. This way, BSR = 1.05 at 532 nm corresponds to BSR = 1.015 at 355 nm and BSR = 1.4 at 1064 nm. According to a long term comparison with photometer AOD, a boundary condition of 1.4 for the IR is slightly too high, so this value is set to 1.25. Usually, the LR profile is initially set to 30 sr for all three wavelengths and altitudes. Following Klett, the LIDAR equation 3.19 can than be written as a differential equation [Klett, 1981; 1985]:
dS(z,λ)
dz = d
dzln[βray(z,λ) +βaer(z,λ)]−2[αray(z,λ) +αaer(z,λ)] (5.7) with S(z,λ) = ln(z2Pel(z,λ)).
Rewritten in an equation for βaer, this equation has the structure of a second order Bernoulli equation and is solved for the boundary condition:
βaer(zref, 532/355/1064 nm) =0.05/0.015/0.25βray(z, 532/355/1064 nm) (5.8) to obtain:
βray(z,λ) + βaer(z,λ)
=
S(z,λ)exp
−2Rz
zrefLR(z,λ)βray(z,λ)−αray(z,λ)dz
S(zref,λ)
βray(zref,λ)+βaer(zref,λ) −2Rz
zrefLR(z,λ)S(z,λ)T(z,zref,λ)dz (5.9) with
T(z,zref,λ) = exp −2 Z z0
zrefLR(z0,λ)βray(z0,λ)−αray(z0,λ)dz0
! .
This Equation can be integrated by setting the reference range zref either at the near or remote end of the measuring range, which equals forward or backward integration.
The backward integration was introduced by Klett, who stated that numerical stability is given only when choosing the boundary condition above the range of interest [Klett, 1981; 1985]. The profile of the particle extinction coefficient αaer can be estimated from the solution for βaer by Eq. 5.4.
Raman Method
The combination of elastic wavelengths detection and the detection of Raman scattering wavelengths allows vertical profiling of the aerosol extinction and backscatter coefficients without a LR assumption, at least throughout the troposphere [Ansmann et al., 1992].
From the Raman equation for vibrational Raman scattering (Eq. 3.22) the direct calcu-lation of the aerosol extinction coefficient is possible. The only particle effect on the signal strength is the attenuation on the way up to the backscatter region and back.
5.1. KARL DATA PREPARATION