Windowed region-of-interest non-uniformity correction and range walk error correction of a 3D flash LiDAR camera
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Andrew Reinhardt↗
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Ozone and Water Vapor Measurements by Raman Lidar in the Planetary Boundary Layer: Error Sources and Field Measurements
Why do we need time series of ozone and water vapor profiles at low altitude? The degradation of air quality is a very serious environmental problem that affects urban and industrial areas worldwide. Air pollution injures human health and ecosystems, diminishes crop yield, and spoils patrimony and materials. The phenomena involved in air pollution are very complex. Once emitted into the atmosphere, (primary) pollutants are transported, dispersed, transformed by gas/solid phase change and chemical reaction, and finally removed by dry and wet deposition. Most challenging is the fact that the health and environmental impacts of secondary pollutants (formed in the atmosphere) are frequently more severe than those of their precursors (primary pollutants). This is the case of ozone and other photochemical pollutants, such as peroxyacetil nitrate (PAN) and secondary particles, produced in the atmosphere by the photo-oxidation volatile organic compounds (VOC) catalyzed by nitrogen oxides (NO(sub x)). Photochemical air pollution is a complex science because of the non-linearity of its response to changes in primary emission.
Lazzarotto, Benoit↗
The Uncertainty of Biomass Estimates from LiDAR and SAR Across a Boreal Forest Structure Gradient
In this study, weexamined the uncertainty of aboveground live biomass (AGB) estimates based on light detection and ranging (LiDAR) and synthetic aperture radar (SAR) measurements distributed across a low-biomass vegetation structure gradient fromforest to non-forest in boreal-like ecosystems. The conifer-dominant structure gradient was compiled from ground data amassed from multiple field expeditions in central Maine (USA), Aurskog (Norway), and across central Siberia (Russia). Single variable empirical models were built tomodel AGB fromremote sensingmetrics. Using thesemodels, we calculated a rootmean square error (RMSE) and a 95% confidence interval (CI) of the RMSE fromthe difference between the remote sensing AGB predictions and the ground reference AGB estimates within AGB intervals across a 0-100 Mg ha(exp.−1) boreal forest structure gradient. The results show that the error in AGB predictions (RMSE) and the error uncertainty (the CI) from LiDAR and SAR change across a forest gradient. The errors of airborne LiDAR and SAR metrics and spaceborne LiDAR platforms show a general trend of reduced relative errors as AGBmagnitudes increase, particularly from0 to 60 Mg ha (exp.−1). Empirical models relating spaceborne metrics to AGB and estimates of spaceborne LiDAR error uncertainty demonstrate the difficulty of characterizing differences in AGB at the site-level with current spaceborne sensors, particularly below 80 Mg ha (exp.−1) with less than 50-100% error.
Taiga↗
A comparison of vertical velocity in cirrus obtained from aircraft and lidar divergence measurements during FIRE
Techniques are presented to obtain vertical velocity in cirrus clouds from in situ aircraft lateral wind measurements and from ground-based remote Doppler lidar measurements. The approach used is to calculate w from the integral of the divergence of the horizontal velocity around a closed path. Divergence measurements from both aircraft and Doppler lidar are discussed. The principal errors in the calculation of w from aircraft lateral wind measurements are bias in the lateral wind, ground speed errors, and error due to vertical shear of the horizontal wind. For Doppler lidar measurements the principal errors are in the estimate of mean terminal velocity and the zeroth order coefficients of the Fourier series that is fitted to the data. The technique is applied to a cirrus cloud investigated during the FIRE (First International Satellite Cloud Climatology Regional Experiment) Cirrus Intensive Field Observation Program. The results indicate that the error in w is about + or - 14 cm/s from the aircraft technique; this can be reduced to about + or - 2 to 3 cm/s with technical improvements in both ground speed and lateral velocity measurements. The error in w from Doppler lidar measurements, which is about + or - 8 cm/s, can be reduced to about + or - 5 cm/s by improvements in the Doppler velocity measurements with technology that is currently available.
Gultepe, Ismail↗
Accuracy of Lidar Measurements of the Atmosphere
Report reviews sources of systematic error in laser radar (lidar) measurements of particles in atmosphere. Report applies particularly to stationary pulsed carbon dioxide lidars of type used to measure backscatter from aerosols in troposphere. Provides information for calibrating such systems accurately and consistently and interpreting their data correctly. Also useful in calibrating mobile and airborne lidars, lidars operating at wavelengths other than those of carbon dioxide lasers, and continuouswave lidars.
Kavaya, M. J.↗
Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization
In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.
vertical profiles↗
Measurements of Stratospheric Pinatubo Aerosol Extinction Profiles by a Raman Lidar
The Raman lidar has been used for remote measurements of water vapor, ozone and atmospheric temperature in the lower troposphere because the Raman cross section is three orders smaller than the Rayleigh cross section. We estimated the extinction coefficients of the Pinatubo volcanic aerosol in the stratosphere using a Raman lidar. If the precise aerosol extinction coefficients are derived, the backscatter coefficient of a Mie scattering lidar will be more accurately estimated. The Raman lidar has performed to measure density profiles of some species using Raman scattering. Here we used a frequency-doubled Nd:YAG laser for transmitter and received nitrogen vibrational Q-branch Raman scattering signal. Ansmann et al. (1990) derived tropospherical aerosol extinction profiles with a Raman lidar. We think that this method can apply to dense stratospheric aerosols such as Pinatubo volcanic aerosols. As dense aerosols are now accumulated in the stratosphere by Pinatubo volcanic eruption, the error of Ramen lidar signal regarding the fluctuation of air density can be ignored.
Abo, Makoto↗
Assessment of measurement error due to sampling perspective in the space-based Doppler lidar wind profiler
A Multipair Algorithm (MPA) has been developed to minimize the contribution of the sampling error in the simulated Doppler lidar wind profiler measurements (due to angular and spatial separation between shots in a shot pair) to the total measurement uncertainty. Idealized wind fields are used as input to the profiling model, and radial wind estimates are passed through the MPA to yield a wind measurement for 300 x 300 sq km areas. The derived divergence fields illustrate the gradient patterns that are particular to the Doppler lidar sampling strategy and perspective.
Houston, S. H.↗
Temperature retrievals by Rayleigh backscatter lidar signals
Differences between retrieved temperatures from lidar and atmospheric model temperatures are calculated for four problems: (1) the effect of a transient thin aerosol layer at any altitude on temperature retrieved by a single-wavelength lidar; (2) the effect of residual aerosols on temperature retrieved by a two-wavelength lidar; (3) the errors due to splicing two backscatter signals which are obtained separately; and (4) the effect of multiple scattering. The results show that temperatures can be retrieved for + or - 3 K if Rayleigh backscatter can be measured for + or - 1.5 percent. The LITE lidar in a 240 km orbit aboard the Shuttle should be able to make a + or -3 K measurements from 10-40 km with vertical resolutions of 1 km and horizontal resolutions of 300 km.
Uchino, O.↗
Lidar windshear detection for commercial aircraft
As part of the NASA/FAA National Integrated Windshear Program, a measurable windshear hazard index that can be remotely sensed from an aircraft is presented. This will provide a pilot information about the wind conditions he will experience at some later time if he continues along the present flight path. The technology analysis and end-to-end performance simulation, which measured S/N and resulting wind velocity errors for competing lidar systems, demonstrated that a Ho:YAG lidar at a wavelength of 2.1 microns and a CO2 lidar at 10.6 microns can give the pilot data about the line-of-sight component of a windshear threat in an area extending from his present position to two to four km in front of the aircraft.
Targ, Russell↗
Retrieving the Vertical Structure of the Effective Aerosol Complex Index of Refraction from a Combination of Aerosol in Situ and Remote Sensing Measurements During TARFOX
The largest uncertainty in estimates of the effects of atmospheric aerosols on climate stems from uncertainties in the determination of their microphysical properties, including the aerosol complex index of refraction, which in turn determines their optical properties. A novel technique is used to estimate the aerosol complex index of refraction in distinct vertical layers from a combination of aerosol in situ size distribution and remote sensing measurements during the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX). In particular, aerosol backscatter measurements using the NASA Langley LASE (Lidar Atmospheric Sensing Experiment) instrument and in situ aerosol size distribution data are utilized to derive vertical profiles of the "effective" aerosol complex index of refraction at 815 nm (i.e., the refractive index that would provide the same backscatter signal in a forward calculation on the basis of the measured in situ particle size distributions for homogeneous, spherical aerosols). A sensitivity study shows that this method yields small errors in the retrieved aerosol refractive indices, provided the errors in the lidar-derived aerosol backscatter are less than 30% and random in nature. Absolute errors in the estimated aerosol refractive indices are generally less than 0.04 for the real part and can be as much as 0.042 for the imaginary part in the case of a 30% error in the lidar-derived aerosol backscatter. The measurements of aerosol optical depth from the NASA Ames Airborne Tracking Sunphotometer (AATS-6) are successfully incorporated into the new technique and help constrain the retrieved aerosol refractive indices. An application of the technique to two TARFOX case studies yields the occurrence of vertical layers of distinct aerosol refractive indices. Values of the estimated complex aerosol refractive index range from 1.33 to 1.45 for the real part and 0.001 to 0.008 for the imaginary part. The methodology devised in this study provides, for the first time, a complete set of vertically resolved aerosol size distribution and refractive index data. yielding the vertical distribution of aerosol optical properties required for the determination of aerosol-induced radiative flux changes.
Redemann, J.↗
Correction function in the Lidar equation and the solution techniques for CO2 Lidar date reduction
For lidar systems with long laser pulses the unusual behavior of the near-range signals causes serious difficulties and large errors in reduction. The commonly used lidar equation is no longer applicable since the convolution of the laser pulse with the atmospheric parameter distributions should be taken into account. It is important to give more insight into this problem and find the solution techniques. Starting from the original equation, a general form is suggested for the single scattering lidar equation where a correction function Cr is introduced. The correction Function Cr(R) derived from the original equation indicates the departure from the normal lidar equation. Examples of Cr(R) for a coaxial CO2 lidar system are presented. The Differential Absorption Lidar (DIAL) errors caused by the differences of Cr(R) for H2O measurements are plotted against height.
Zhao, Y.↗
Results from 1984 airborne Doppler lidar wind measurement program. Flight 6: Analysis of line-of-sight elevation angle errors and apparent Doppler velocities
During the summer of 1984 the Marshall Space Flight Center's Airborne Doppler Lidar System (ADLS) made a series of wind measurements in the California Central Valley. This study quantifies the lidar beam angle errors and velocity errors through analysis of ground return signals. Line-of-sight elevation (LOSE) angle errors are under 1 deg. Apparent Doppler ground velocities, as large as 2m/s, are considerably less than in a previous flight experiment in 1981. No evidence was found of a Schuler resonance phenomenon common to inertial navigation systems (INS), however the aperiodic nature of the apparent velocities implies an error in the INS-derived ground speeds. Certain features and subtleties in the ground returns are explained in terms of atmospheric structure and characteristics of the ADLS hardware and software. Finally, least squares and low-pass filtering techniques are suggested for eliminating errors during post-processing.
Rothermel, Jeffry↗
Error caused by using a constant extinction/backscattering ratio in the lidar solution
The Bernoulli solution of the lidar equation with the assumption of a constant extinction/backscattering ratio can lead to errors in the derived aerosol extinction and backscattering profiles. This paper presents a general theoretical analysis of the errors that result from differences between the assumed and actual extinction/backscattering ratio profiles. Examples of the influence of the constant extinction/backscattering ratio assumption on the lidar derived aerosol extinction profile are presented for various laser wavelengths.
Sasano, Y.↗
Accuracy of wind measurements using an airborne Doppler lidar
Simulated wind fields and lidar data are used to evaluate two sources of airborne wind measurement error. The system is sensitive to ground speed and track angle errors, with accuracy required of the angle to within 0.2 degrees and of the speed to within 1 knot, if the recovered wind field is to be within five percent of the correct direction and 10 percent of the correct speed. It is found that errors in recovered wind speed and direction are dependent on wind direction relative to the flight path. Recovery of accurate wind fields from nonsimultaneous sampling errors requires that the lidar data be displaced to account for advection so that the intersections are defined by air parcels rather than fixed points in space.
Carroll, J. J.↗
Lidar-Polarimeter Retrieval OSSEs in Support of NASA's Aerosols and Clouds-Convection-Precipitation (ACCP) Study
The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (A-CCP). The DS and the A-CCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those addressed by individual DOs.A critical element of the A-CCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. Central to this observing system design is the adoption of a Value Framework in which quantitative assessment of the science benefits of space-and air-borne assets is a key element. Given pre-defined A-CCP science objectives and geophysical variables with desired accuracies, A-CCP relies on a spectrum of Observing System Simulation Experiments (OSSEs) aimed at addressing pixel level retrieval uncertainties and sampling trade-offs. In this talk we will discuss a subset of Retrieval OSSEs being considered for A-CCP, namely, synergistic lidar-polarimeter retrievals of particular relevance for the A-CCP aerosol science objectives. Starting with aerosol states from the GEOS-5 Nature Run (G5NR) sampled along specific satellite orbits, we simulate polarized radiances at the desired polarimeter wavelengths with the Vector Linearized Direct Ordinate Radiative Transfer (VLIDORT) model, alongside the lidar signal for the relevant lidars with realistic error characterization. Next, inversions are performed with the Generalized Retrieval of Aerosol and Surface Properties (GRASP) system and the accuracy of the retrieved geophysical variables are assessed. In this presentation we will highlight results for key architectures being considered for A-CCP.
da Silva, Arlindo↗
Lidar-Polarimeter Retrieval OSSEs using a Nature Run in Support of NASA's Aerosols, Clouds, Convection and Precipitation (ACCP) Study
The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (ACCP). The DS and the ACCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those addressed by individual DOs. A critical element of the ACCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. Central to this observing system design is the adoption of a Value Framework in which quantitative assessment of the science benefits of space- and air-borne assets is a key element. Given pre-defined ACCP science objectives and geophysical variables with desired accuracies, ACCP relies on a spectrum of Observing System Simulation Experiments (OSSEs) aimed at addressing pixel level retrieval uncertainties and sampling trade-offs. In this talk we will discuss a subset of Retrieval OSSEs being considered for ACCP, namely, synergistic lidar-polarimeter retrievals based on observation simulations from the GEOS-5 Nature Run (G5NR). Starting with aerosol states from the GEOS-5 Nature Run (G5NR) sampled along specific satellite orbits, we simulate polarized radiances at the desired polarimeter wavelengths with the Vector Linearized Direct Ordinate Radiative Transfer (VLIDORT) model, alongside the lidar signal for the relevant lidars with realistic error characterization. Next, inversions are performed with the Generalized Retrieval of Aerosol and Surface Properties (GRASP) system and the accuracy of the retrieved geophysical variables are assessed. In this presentation we will highlight results for key architectures being considered for ACCP with emphasis on geophysical variables of particular relevance to ACCP’s aerosol science objectives.
A Da Silva↗
Quantifying the Observational Requirements of a Space-borne LiDAR Snow Mission
This study quantifies the level of observational accuracy required from a spaceborne light detection and ranging (LiDAR) snow depth retrieval mission for enabling beneficial impacts for snow estimation. The study is conducted over a region in Western Colorado using a suite of observing system simulation experiments(OSSEs).The Joint UK Land Environment Simulator, version 5.0 (JULES v5.0) is employed to simulate a suite of idealized LiDAR observations, considering a range of LiDAR snow depth retrieval errors, different hypothetical sensor swath widths, and the impact of cloud cover on observability. These simulated observations are then assimilated into the Noah land surface modelwith multi-parameterization options, version 3.6 (Noah-MP v3.6) model. This data assimilation setup is used to systematically evaluate the potential utility of LiDAR observations for improving modeled snow water equivalent (SWE)estimates and water budget variables such as runoff. Results from the OSSE runsshow that, in general, assimilation of synthetic LiDAR observations provide beneficial impacts when theLiDAR snow depth retrieval error standard deviation (σerror) is below 60 cm.Based on comparisons between the realistic (i.e., swath-limited and cloud-attenuated) case and the idealized (i.e., infinite swath width in the absence of cloud cover) case,this study concludes that observations with a conservative error standard deviation threshold of 40 cm (i.e., upper limit of the snow depth retrieval error that adds value to the SWE estimates viaassimilation) are needed for improving modeled snow estimates. More than a 33% reduction in SWEroot mean square errors and more than a 15% increase in correlation coefficientsare achieved when σ error ≤ 40 cmusing a 170-km sensor swath width in the presence of cloud attenuation effects. Further, the integrated hydrologic response, as represented by total (surface and subsurface) runoff estimates during the snow ablation season, are also enhanced when assimilating synthetic LiDAR snow depth retrievals with errors below this level.
Yonghwan Kwon↗