Estimation of a lidar’s overlap function and its calibration by nonlinear regression

Povey, Adam C.; Grainger, Roy G.; Peters, Daniel M.; Agnew, Judith L.; Rees, D.

doi:10.1364/ao.51.005130

Cited by 19 publications

(13 citation statements)

References 32 publications

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“…Wandinger and Ansmann [51] introduced an experimental approach to determine O(R), which requires a pure molecular backscatter channel (Raman signal) in addition to the usual elastic backscatter signal. This method works well for the 355 and the 532 nm channels using Raman signals under both homogeneous and inhomogeneous conditions without any critical assumption, unlike some theoretical approaches (e.g., slope method, polynomial regression, non-linear regression) illustrated by Tomine et al [52], Dho et al [53], Povey et al [54], among others. However, Guerrero-Rascado et al [55] found poor performance of Raman-signal approach for 1064 nm-channel of a LiDAR system due to the low intensity for the Raman shifted signal in the infrared range.…”

Section: Theoretical and Experimental Approaches To Correct Lidar Sigmentioning

confidence: 91%

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

Pal

2014

Remote Sensing

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Abstract:There is compelling evidence that the incomplete laser beam receiver field-of-view overlap (i.e., partial overlap) of ground-based vertically-pointing aerosol LiDAR restricts the observational range for detecting aerosol layer boundaries to a certain height above the LiDAR. This height varies from one to few hundreds of meters, depending on the transceiver geometry. The range, or height of full overlap, is defined as the minimum distance at which the laser beam is completely imaged onto the detector through the field stop in the receiver optics. Thus, the LiDAR signal below the height of full overlap remains erroneous. In effect, it is not possible to derive the atmospheric boundary layer (ABL) top (z i ) below the height of full overlap using lidar measurements alone. This problem makes determination of the nocturnal z i almost impossible, as the nocturnal z i is often lower than the minimum possible retrieved height due to incomplete overlap of lidar. Detailed studies of the nocturnal boundary layer or of variability of low z i would require changes in the LiDAR configuration such that a complete transceiver overlap could be achieved at a much lower height. Otherwise, improvements in the system configuration or deployment (e.g., scanning LiDAR) are needed. However, these improvements are challenging due to the instrument configuration and the need for Raman channel signal, eye-safe laser transmitter for scanning deployment, etc. This paper presents a brief review of some of the challenges and opportunities in overcoming the partial overlap of the LiDAR transceiver to determine z i below the height of full-overlap using complementary approaches to derive low z i . A comprehensive discussion focusing on four different techniques is presented. These are based on the combined (1) ceilometer and LiDAR; (2) tower-based trace gas (e.g., CO 2 ) concentration profiles and LiDAR measurements; (3) 222 Rn budget approach and LiDAR-derived results; and (4) encroachment model and LiDAR observations.

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Section: Theoretical and Experimental Approaches To Correct Lidar Sigmentioning

confidence: 91%

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

Pal

2014

Remote Sensing

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“…Aerosol and cloud layers are modelled by Gaussian peaks (G. Biavati, personal communication, 2011). An analytic model outlined in Povey et al (2012) is used to generate the calibration function and detector nonlinearity. Once simulated, Poisson noise is added to the profiles.…”

Section: Simulationsmentioning

confidence: 99%

“…Radiosonde launches are available twice daily from Larkhill, 30 km northwest (UK Meteorological Office, 2006Office, -2011. Six profiles were selected from March 2010 for which the instrument's calibration has been thoroughly investigated using the techniques of Povey et al (2012). Figure 13 compares the retrieved profiles to those given by the Fernald-Klett and Ansmann methods.…”

Section: Individual Profilesmentioning

confidence: 99%

Retrieval of aerosol backscatter, extinction, and lidar ratio from Raman lidar with optimal estimation

et al. 2014

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Abstract.Optimal estimation retrieval is a form of nonlinear regression which determines the most probable circumstances that produced a given observation, weighted against any prior knowledge of the system. This paper applies the technique to the estimation of aerosol backscatter and extinction (or lidar ratio) from two-channel Raman lidar observations. It produces results from simulated and real data consistent with existing Raman lidar analyses and additionally returns a more rigorous estimate of its uncertainties while automatically selecting an appropriate resolution without the imposition of artificial constraints. Backscatter is retrieved at the instrument's native resolution with an uncertainty between 2 and 20 %. Extinction is less well constrained, retrieved at a resolution of 0.1-1 km depending on the quality of the data. The uncertainty in extinction is > 15 %, in part due to the consideration of short 1 min integrations, but is comparable to fair estimates of the error when using the standard Raman lidar technique.The retrieval is then applied to several hours of observation on 19 April 2010 of ash from the Eyjafjallajökull eruption. A depolarising ash layer is found with a lidar ratio of 20-30 sr, much lower values than observed by previous studies. This potentially indicates a growth of the particles after 12-24 h within the planetary boundary layer. A lower concentration of ash within a residual layer exhibited a backscatter of 10 Mm −1 sr −1 and lidar ratio of 40 sr.

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“…The overlap function of lidar defines the efficiency with which the laser beam is coupled with the receiver FOV as a function of height (Povey et al, 2012, and references therein). Accurate estimation of the overlap function describes the accuracy with which the lidar can be used to study the PBL, where the aerosol distribution is inhomogeneous.…”

Section: Determination Of Overlap Function With a Scanning Lidarmentioning

confidence: 99%

A new mobile and portable scanning lidar for profiling the lower troposphere

Chiang

Das

Chiang

et al. 2015

Geosci. Instrum. Method. Data Syst.

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Abstract. An in-house developed mobile and portable threedimensional scanning lidar system is discussed in this work. The system uses a stimulated Raman-scattering technique for the continuous observation of atmospheric aerosols, clouds and trace gases. This system has a fast scanning technique with a high-speed data acquisition, and permits the real-time measurement of atmospheric pollutants with the temporal resolution of 1 min. This scanning lidar system provides typical horizontal coverage of about 8-10 km while scanning; however, in zenith mode, good quality backscattered signals can be from 20 km, depending upon the laser power and sky conditions. This versatile lidar system has also overcome the drawbacks which are popular in the traditional scanning lidar systems such as complicated operation, overlap height between laser beam and telescope field of view In this system, the optical damage is reduced by using an integral coaxial transmitter and receiver. Some of the initial results obtained from the scanning lidar system are also presented. This study shows that boundary-layer structure and land-sea breeze circulation can be resolved from the developed scanning lidar system. The application of this lidar system to measure the pollutants over an industrial area is also discussed.

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Estimation of a lidar’s overlap function and its calibration by nonlinear regression

Cited by 19 publications

References 32 publications

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

Monitoring Depth of Shallow Atmospheric Boundary Layer to Complement LiDAR Measurements Affected by Partial Overlap

Retrieval of aerosol backscatter, extinction, and lidar ratio from Raman lidar with optimal estimation

A new mobile and portable scanning lidar for profiling the lower troposphere

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