Retrieval of Temperature From a Multiple Channel Rayleigh-Scatter Lidar Using an Optimal Estimation Method
19 Dec 2014-Vol. 2014
TL;DR: In this paper, the authors used an optimal estimation method (OEM) to estimate the temperature in the middle atmosphere with Rayleigh-scatter lidars, which allows a full uncertainty budget to be obtained on a per profile basis that includes, in addition to the statistical uncertainties, the smoothing error and uncertainties due to Rayleigh extinction, ozone absorption, lidar constant, nonlinearity in the counting system, variation of the Rayleigh scatter cross section with altitude, pressure, acceleration due to gravity, and the variation of mean molecular mass with altitude.
Abstract: The measurement of temperature in the middle atmosphere with Rayleigh-scatter lidars is an important technique for assessing atmospheric change. Current retrieval schemes for this temperature have several shortcomings, which can be overcome by using an optimal estimation method (OEM). Forward models are presented that completely characterize the measurement and allow the simultaneous retrieval of temperature, dead time, and background. The method allows a full uncertainty budget to be obtained on a per profile basis that includes, in addition to the statistical uncertainties, the smoothing error and uncertainties due to Rayleigh extinction, ozone absorption, lidar constant, nonlinearity in the counting system, variation of the Rayleigh-scatter cross section with altitude, pressure, acceleration due to gravity, and the variation of mean molecular mass with altitude. The vertical resolution of the temperature profile is found at each height, and a quantitative determination is made of the maximum height to which the retrieval is valid. A single temperature profile can be retrieved from measurements with multiple channels that cover different height ranges, vertical resolutions, and even different detection methods. The OEM employed is shown to give robust estimates of temperature, which are consistent with previous methods, while requiring minimal computational time. This demonstrated success of lidar temperature retrievals using an OEM opens new possibilities in atmospheric science for measurement integration between active and passive remote sensing instruments.
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TL;DR: In this article, the authors evaluate commonly used methods of extracting gravity-wave-induced temperature perturbations from lidar measurements and find that the Butterworth filter performs best if gravity waves over a wide range of periods are extracted from LIDAR temperature measurements, while the running mean method gives good results if only gravity waves with short periods are analyzed.
Abstract: . This study evaluates commonly used methods of extracting gravity-wave-induced temperature perturbations from lidar measurements. The spectral response of these methods is characterized with the help of a synthetic data set with known temperature perturbations added to a realistic background temperature profile. The simulations are carried out with the background temperature being either constant or varying in time to evaluate the sensitivity to temperature perturbations not caused by gravity waves. The different methods are applied to lidar measurements over New Zealand, and the performance of the algorithms is evaluated. We find that the Butterworth filter performs best if gravity waves over a wide range of periods are to be extracted from lidar temperature measurements. The running mean method gives good results if only gravity waves with short periods are to be analyzed.
60 citations
TL;DR: In this paper, a standardized approach for the definition, propagation, and reporting of uncertainty in the ozone differential absorption lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed.
Abstract: . A standardized approach for the definition, propagation, and reporting of uncertainty in the ozone differential absorption lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. One essential aspect of the proposed approach is the propagation in parallel of all independent uncertainty components through the data processing chain before they are combined together to form the ozone combined standard uncertainty. The independent uncertainty components contributing to the overall budget include random noise associated with signal detection, uncertainty due to saturation correction, background noise extraction, the absorption cross sections of O3, NO2, SO2, and O2, the molecular extinction cross sections, and the number densities of the air, NO2, and SO2. The expression of the individual uncertainty components and their step-by-step propagation through the ozone differential absorption lidar (DIAL) processing chain are thoroughly estimated. All sources of uncertainty except detection noise imply correlated terms in the vertical dimension, which requires knowledge of the covariance matrix when the lidar signal is vertically filtered. In addition, the covariance terms must be taken into account if the same detection hardware is shared by the lidar receiver channels at the absorbed and non-absorbed wavelengths. The ozone uncertainty budget is presented as much as possible in a generic form (i.e., as a function of instrument performance and wavelength) so that all NDACC ozone DIAL investigators across the network can estimate, for their own instrument and in a straightforward manner, the expected impact of each reviewed uncertainty component. In addition, two actual examples of full uncertainty budget are provided, using nighttime measurements from the tropospheric ozone DIAL located at the Jet Propulsion Laboratory (JPL) Table Mountain Facility, California, and nighttime measurements from the JPL stratospheric ozone DIAL located at Mauna Loa Observatory, Hawai'i.
51 citations
TL;DR: This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors.
Abstract: . Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land–water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques.
48 citations
TL;DR: In this paper, a standardized approach for the definition and reporting of vertical resolution of the ozone and temperature lidar profiles contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed.
Abstract: A standardized approach for the definition and reporting of vertical resolution of the ozone and temperature lidar profiles contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. Two standardized definitions describing homogeneously and unequivocally the impact of vertical filtering are recommended.
The first proposed definition is based on the width of the response to a Finite Impulse-type perturbation. The response is computed by convolving the filter coefficients with an impulse function, namely, a Kronecker Delta function for smoothing filters, and a Heaviside Step function for derivative filters. Once the response has been computed, the proposed standardized definition of vertical resolution is given by Δz = δz * HFWHM, where δz is the lidar’s sampling resolution and HFWHM is the full-width at half-maximum (FWHM) of the response, measured in sampling intervals.
The second proposed definition relates to digital filtering theory. After applying a Laplace Transform to a set of filter coefficients, the filter’s gain characterizing the effect of the filter on the signal in the frequency-domain is computed, from which the cut-off frequency fC, defined as the frequency at which the gain equals 0.5, is computed. Vertical resolution is then defined by Δz = δz ⁄ (2fC). Unlike common practice in the field of spectral analysis, a factor 2fC instead of fC is constrained here to yield vertical resolution values nearly equal to the values obtained with the impulse response definition using the same filter coefficients. When using either of the proposed definitions, unsmoothed signals yield the best possible vertical resolution Δz = δz (one sampling bin).
Numerical tools were developed to support the implementation of these definitions across all NDACC lidar groups. The tools consist of ready-to-use “plug-in” routines written in several programming languages that can be inserted into any lidar data processing software and called each time a filtering operation occurs in the data processing chain.
41 citations
TL;DR: In this paper, a general approach to quantify absorption model uncertainty due to uncertainty in the underlying spectroscopic parameters is presented, which is applied to a widely used microwave absorption model (Rosenkranz, 2017) and radiative transfer calculations in the 20-60 GHz range.
Abstract: . This paper presents a general approach to quantify absorption model
uncertainty due to uncertainty in the underlying spectroscopic parameters. The
approach is applied to a widely used microwave absorption model (Rosenkranz,
2017) and radiative transfer calculations in the 20–60 GHz range, which are
commonly exploited for atmospheric sounding by microwave radiometer (MWR).
The approach, however, is not limited to any frequency range, observing
geometry, or particular instrument. In the considered frequency range,
relevant uncertainties come from water vapor and oxygen spectroscopic
parameters. The uncertainty of the following parameters is found to dominate:
(for water vapor) self- and foreign-continuum absorption coefficients, line
broadening by dry air, line intensity, the temperature-dependence exponent for
foreign-continuum absorption, and the line shift-to-broadening ratio; (for
oxygen) line intensity, line broadening by dry air, line mixing,
the temperature-dependence exponent for broadening, zero-frequency line
broadening in air, and the temperature-dependence coefficient for line mixing. The
full uncertainty covariance matrix is then computed for the set of
spectroscopic parameters with significant impact. The impact of the
spectroscopic parameter uncertainty covariance matrix on simulated
downwelling microwave brightness temperatures ( TB ) in the 20–60 GHz
range is calculated for six atmospheric climatology conditions. The
uncertainty contribution to simulated TB ranges from 0.30 K (subarctic
winter) to 0.92 K (tropical) at 22.2 GHz and from 2.73 K (tropical) to 3.31 K
(subarctic winter) at 52.28 GHz. The uncertainty contribution is nearly
zero at 55–60 GHz frequencies. Finally, the impact of spectroscopic
parameter uncertainty on ground-based MWR retrievals of temperature and
humidity profiles is discussed.
36 citations
References
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Book•
17 Jul 2000
TL;DR: This book treats the inverse problem of remote sounding comprehensively, and discusses a wide range of retrieval methods for extracting atmospheric parameters of interest from the quantities such as thermal emission that can be measured remotely.
Abstract: Remote sounding of the atmosphere has proved to be a fruitful method of obtaining global information about the atmospheres of the earth and planets. This book treats the inverse problem of remote sounding comprehensively, and discusses a wide range of retrieval methods for extracting atmospheric parameters of interest from the quantities such as thermal emission that can be measured remotely. Inverse theory is treated in depth from an estimation-theory point of view, but practical questions are also emphasized, for example designing observing systems to obtain the maximum quantity of information, efficient numerical implementation of algorithms for processing of large quantities of data, error analysis and approaches to the validation of the resulting retrievals, The book is targeted at both graduate students and working scientists.
4,052 citations
TL;DR: In this paper, the MSIS-86 empirical model has been extended into the mesosphere and lower atmosphere to provide a single analytic model for calculating temperature and density profiles representative of the climatological average for various geophysical conditions.
Abstract: The MSIS-86 empirical model has been revised in the lower thermosphere and extended into the mesosphere and lower atmosphere to provide a single analytic model for calculating temperature and density profiles representative of the climatological average for various geophysical conditions. Tabulations from the Handbook for MAP 16 are the primary guide for the lower atmosphere and are supplemented by historical rocket and incoherent scatter data in the upper mesosphere and lower thermosphere. Low-order spherical harmonics and Fourier series are used to describe the major variations throughout the atmosphere including latitude, annual, semiannual, and simplified local time and longitude variations. While month to month details cannot be completely represented, lower atmosphere temperature data are fit to an overall standard deviation of 3 K and pressure to 2%. Comparison with rocket and other data indicates that the model represents current knowledge of the climatological average reasonably well, although there is some conflict as to details near the mesopause.
2,359 citations
TL;DR: In this paper, a lidar system based at the Haute-Provence Observatory (44°N, 6°E) has been used to obtain night-time density and temperature profiles in the altitude range 35-70 km.
Abstract: A lidar system based at the Haute-Provence Observatory (44°N, 6°E) has been used to obtain night-time density and temperature profiles in the altitude range 35-70 km. If the lidar results are normalized to an in-situ rocket sounding from 35 to 40 km, the lidar and rocket profiles are in quite good agreement up to about 50 km. Differences are sometimes noted around 55 km, and these could possibly be caused by an aerosol layer.
434 citations
California Institute of Technology1, New Mexico Institute of Mining and Technology2, University of Waterloo3, University of York4, Leibniz Association5, Langley Research Center6, Goddard Space Flight Center7, Hampton University8, European Centre for Medium-Range Weather Forecasts9, University of Toronto10
TL;DR: In this article, the authors describe the retrievals algorithm used to determine temperature and height from radiance measurements by the Microwave Limb Sounder on EOS Aura, which is a "limbscanning" instrument, meaning that it views the atmosphere along paths that do not intersect the surface.
Abstract: This paper describes the retrievals algorithm used to determine temperature and height from radiance measurements by the Microwave Limb Sounder on EOS Aura. MLS is a "limbscanning" instrument, meaning that it views the atmosphere along paths that do not intersect the surface - it actually looks forwards from the Aura satellite. This means that the temperature retrievals are for a "profile" of the atmosphere somewhat ahead of the satellite. Because of the need to view a finite sample of the atmosphere, the sample spans a box about 1.5km deep and several tens of kilometers in width; the optical characteristics of the atmosphere mean that the sample is representative of a tube about 200-300km long in the direction of view. The retrievals use temperature analyses from NASA's Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system as a priori states. The temperature retrievals are somewhat deperrde~zt on these a priori states, especially in the lower stratosphere. An important part of the validation of any new dataset involves comparison with other, independent datasets. A large part of this study is concerned with such comparisons, using a number of independent space-based measurements obtained using different techniques, and with meteorological analyses. The MLS temperature data are shown to have biases that vary with height, but also depend on the validation dataset. MLS data are apparently biased slightly cold relative to correlative data in the upper troposphere and slightly warm in the middle stratosphere. A warm MLS bias in the upper stratosphere may be due to a cold bias in GEOS-5 temperatures.
412 citations
TL;DR: In this article, the absorption coefficients of ozone have been measured in the ultraviolet and visible regions using essentially 100% pure ozone, and the results confirm those of Inn and Tanaka in ultraviolet, and those of Vigroux in the visible region.
Abstract: The absorption coefficients of ozone have been measured in the ultraviolet and visible regions using essentially 100% pure ozone. The results confirm those of Inn and Tanaka in the ultraviolet, and those of Vigroux in the visible region.
391 citations