Diego Lange

Stratospheric AOD after the 2011 eruption of Nabro volcano measured by lidars over the Northern Hemisphere

Nabro volcano (13.37°N, 41.70°E) in Eritrea erupted on 13 June 2011 generating a layer of sulfate aerosols that persisted in the stratosphere for months. For the first time we report on ground-based lidar observations of the same event from every continent in the Northern Hemisphere, taking advantage of the synergy between global lidar networks such as EARLINET, MPLNET and NDACC with independent lidar groups and satellite CALIPSO to track the evolution of the stratospheric aerosol layer in various parts of the globe. The globally averaged aerosol optical depth (AOD) due to the stratospheric volcanic aerosol layers was of the order of 0.018 ± 0.009 at 532 nm, ranging from 0.003 to 0.04. Compared to the total column AOD from the available collocated AERONET stations, the stratospheric contribution varied from 2% to 23% at 532 nm.

Atmospheric Boundary Layer Height Monitoring Using a Kalman Filter and Backscatter Lidar Returns

A solution based on a Kalman filter to trace the evolution of the atmospheric boundary layer (ABL) sensed by a ground-based elastic-backscatter tropospheric lidar is presented. An erf-like profile is used to model the mixing-layer top and the entrainment-zone thickness. The extended Kalman filter (EKF) enables to retrieve and track the ABL parameters based on simplified statistics of the ABL dynamics and of the observation noise present in the lidar signal. This adaptive feature permits to analyze atmospheric scenes with low signal-to-noise ratios (SNRs) without the need to resort to long-time averages or range-smoothing techniques, as well as to pave the way for future automated detection solutions. First, EKF results based on oversimplified synthetic and experimental lidar profiles are presented and compared with classic ABL estimation quantifiers for a case study with different SNR scenarios.

Atmospheric Boundary Layer Height Estimation Using a Kalman Filter and a Frequency‐Modulated Continuous‐Wave Radar

An adaptive solution based on an extended Kalman filter (EKF) is proposed to estimate the atmospheric boundarylayer height (ABLH) from frequency-modulated continuous-wave S-band weather-radar returns. The EKF estimator departs from previous works, in which the transition interface between the mixing layer (ML) and the free troposphere (FT) is modeled by means of an erf-like parametric function. In contrast to lidar remote sensing, where aerosols give strong backscatter returns over the whole ML, clear-air radar reflectivity returns (Bragg scattering from refractive turbulence) shows strongest returns from the ML-FT interface. In addition, they are corrupted by “insect” noise (impulsive noise associated with Rayleigh scattering from insects and birds), all of which requires a specific treatment of the problem and the measurement noise for the clear-air radar case. The proposed radar-ABLH estimation method uses: 1) a first preprocessing of the reflectivity returns based on median filtering and threshold-limited decision to obtain “clean” reflectivity signal; 2) a modified EKF with adaptive range intervals as time tracking estimator; and 3) ad hoc modeling of the observation noise covariance. The method has successfully been implemented in clear-air, single-layer, and convective boundary-layer conditions. ABLH estimates from the proposed radar-EKF method have been cross examined with those from a collocated lidar ceilometer yielding a correlation coefficient as high as ρ = 0.93 (mean signal-to-noise ratio, SNR = 18 (linear units), at the ABLH) and in relation to the classic THM.

Six-channel polychromator design and implementation for the UPC elastic/Raman LIDAR

A 6-channel dichroic-based polychromator is presented as the spectrally selective unit for the U.P.C. elastic/Raman lidar. Light emission is made at 355-nm (ultraviolet, UV), 532-nm (visible, VIS) and 1064-nm (near infrared, NIR) wavelengths. In reception, the polychromator is the spectral separation unit that separates the laser backscattered composite return into 3 elastic (355, 532, 1064-nm wavelengths) and 3 Raman channels (386.7, 607.4 and 407.5-nm (water-vapor) wavelengths). The polychromator houses photo-multiplier tubes (PMT) for all the channels except for the NIR one, which is avalanche photodiode (APD) based. The optomechanical design uses 1-inch optics and Eurorack standards. The APD-based receiver uses a XY-axis translation/elevation micro-positioning stage due to its comparatively small active area and motorised neutral density filters are used in all PMT-based channels to avoid detector saturation. The design has been specially optimized to provide homogeneous spatial light distribution onto the photodetectors and good mechanical repeatability. All channels are acquired in mixed analog and photon-counting mode using Licel® transient recorders, which are controlled by means of a user friendly LabVIEWTM interface. The paper focuses on the main polychromator optical design parameters, that is, light collimation trade-offs, end-to-end transmissivity, net channel responsivity, light distribution and spot size onto the photodetectors. The polychromator along with the rest of the U.P.C. lidar system has successfully been tested during a recent lidar system intercomparison campaign carried out in Madrid (Spain) during Oct. 2010.

Power budget and performance assessment for the RSLAB multispectral elastic/raman lidar system

The need of a multi-spectral lidar has widely been experienced in last few years with a view to invert the optical and microphysical properties of aerosols and their impact on the climate change. As a part of the EARLINET-GALION objectives, a joint effort has already been made by the European Aerosol Research Lidar Network (EARLINET). The EARLINET advanced standard of 3+2-channel configuration for lidar instruments (3+2 standing for 3 elastic channels and 2 respective Raman channels) enables retrieval of aerosol microphysical properties. An overview of the new RSLAB 3+2+1 multispectral lidar system, therefore, is presented in terms of power budget estimation for all the reception channels and overall system performance, that is, signal-to-noise ratio (SNR) and maximum sounding range achieved.

Backscatter Error Bounds for the Elastic Lidar Two-Component Inversion Algorithm

Total backscatter-coefficient inversion error bounds for the two-component lidar inversion algorithm (so-called Fernalds or Klett-Fernald-Sasanos method) are derived in analytical form in response to the following three error sources: 1) the measurement noise; 2) the user uncertainty in the backscatter-coefficient calibration; and 3) the aerosol extinction-to-backscatter ratio. The following two different types of error bounds are presented: 1) approximate error bounds using first-order error propagation and 2) exact error bounds using a total-increment method. Both error bounds are formulated in explicit analytical form, which is of advantage for practical physical sensitivity analysis and computational implementation. A Monte Carlo approach is used to validate the error bounds at 355-, 532-, and 1064-nm wavelengths.

Backscattered signal level and SNR validation methodology for tropospheric elastic lidars

A methodology aimed at validating elastic-channel optical power return and signal-to-noise ratio (SNR) levels estimated at the link-budget design stage of a tropospheric lidar against the measured ones is presented. A Rayleigh fit along with knowledge of the atmospheric aerosol transmittance and emission energy is used to theoretically estimate the net voltage responsivity. As a further refinement, when simultaneous analog and photon-counting acquisition is available, the method formulates a rough estimate of the optical losses in the receiving chain. Preliminary validation of the link-budget-assessed optical power and SNR levels for the 1064-nm channel of the Remote Sensing Lab. (RSLab) lidar is discussed.