Retrieval of temperature from a multiple channel pure rotational Raman backscatter lidar using an optimal estimation method
TL;DR: In this paper, a new method for retrieving temperature from pure rotational Raman (PRR) lidar measurements is presented, which uses the full physics of PRR scattering and does not require any assumption of the form for a calibration function nor does it require fitting of calibration factors over a large range of temperatures.
Abstract: . We present a new method for retrieving temperature from pure rotational Raman (PRR) lidar measurements. Our optimal estimation method (OEM) used in this study uses the full physics of PRR scattering and does not require any assumption of the form for a calibration function nor does it require fitting of calibration factors over a large range of temperatures. The only calibration required is the estimation of the ratio of the lidar constants of the two PRR channels (coupling constant) that can be evaluated at a single or multiple height bins using a simple analytic expression. The uncertainty budget of our OEM retrieval includes both statistical and systematic uncertainties, including the uncertainty in the determination of the coupling constant on the temperature. We show that the error due to calibration can be reduced significantly using our method, in particular in the upper troposphere when calibration is only possible over a limited temperature range. Some other advantages of our OEM over the traditional Raman lidar temperature retrieval algorithm include not requiring correction or gluing to the raw lidar measurements, providing a cutoff height for the temperature retrievals that specifies the height to which the retrieved profile is independent of the a priori temperature profile, and the retrieval's vertical resolution as a function of height. The new method is tested on PRR temperature measurements from the MeteoSwiss RAman Lidar for Meteorological Observations system in clear and cloudy sky conditions, compared to temperature calculated using the traditional PRR calibration formulas, and validated with coincident radiosonde temperature measurements in clear and cloudy conditions during both daytime and nighttime.
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TL;DR: In this paper, ground-based lidar and drone observations can fill this gap and improve high-impact high-resolution data in the planetary boundary layer, where the current operational observing systems are lacking data.
Abstract: Capsule SummaryThe current operational observing systems are lacking data in the planetary boundary layer. Novel ground based lidar and drone observations can fill this gap and improve high-impact ...
45 citations
19 Dec 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.
36 citations
TL;DR: In this paper, the authors calculated an 11.5-year water vapour climatology using RALMO measurements in the troposphere, which is consistent with a 1.38°C per decade surface temperature trend.
Abstract: . Water vapour is the strongest greenhouse gas in our atmosphere, and its strength and its dependence on temperature lead to a strong feedback mechanism in both the troposphere and the stratosphere. Raman water vapour lidars can be used to make high-vertical-resolution measurements on the order of tens of metres, making height-resolved trend analyses possible. Raman water vapour lidars have not typically been used for trend analyses, primarily due to the lack of long-enough time series. However, the Raman Lidar for Meteorological Observations (RALMO), located in Payerne, Switzerland, is capable of making operational water vapour measurements and has one of the longest ground-based and well-characterized data sets available.
We have calculated an 11.5-year water vapour climatology using RALMO measurements in the troposphere. Our study uses nighttime measurements during mostly clear conditions, which creates a natural selection bias. The climatology shows that the highest water vapour specific-humidity concentrations are in the summer months and the lowest in the winter months. We have also calculated the geophysical variability of water vapour. The percentage of variability of water vapour in the free troposphere is larger than in the boundary layer. We have also determined water vapour trends from 2009 to 2019. We first calculate precipitable water vapour (PWV) trends for comparison with the majority of water vapour trend studies. We detect a nighttime precipitable water vapour trend of 1.3 mm per decade using RALMO measurements, which is significant at the 90 % level. The trend is consistent with a 1.38 ∘ C per decade surface temperature trend detected by coincident radiosonde measurements under the assumption that relative humidity remains constant; however, it is larger than previous water vapour trend values. We compare the nighttime RALMO PWV trend to daytime and nighttime PWV trends using operational radiosonde measurements and find them to agree with each other. We cannot detect a bias between the daytime and nighttime trends due to the large uncertainties in the trends. For the first time, we show height-resolved increases in water vapour through the troposphere. We detect positive tropospheric water vapour trends ranging from a 5 % change in specific humidity per decade to 15 % specific humidity per decade depending on the altitude. The water vapour trends at five layers are statistically significant at or above the 90 % level.
12 citations
TL;DR: In this article, a one-dimensional variational (1D Var) retrieval of 5G European Centre for Medium-Range Weather Forecast reanalysis (ERA5) temperature and relative humidity profiles above Payerne, Switzerland, assimilating raw backscatter measurements from the MeteoSwiss Raman Lidar for Meteorological Observations (RALMO), is presented.
Abstract: We present a one-dimensional variational (1D Var) retrieval of fifth-generation European Centre for Medium-Range Weather Forecast reanalysis (ERA5) temperature and relative humidity profiles above Payerne, Switzerland, assimilating raw backscatter measurements from the MeteoSwiss Raman Lidar for Meteorological Observations (RALMO). Our reanalysis is called ERA5-reRH. We use an optimal estimation method to perform the 1D Var data retrieval. The forward model combines the Raman lidar equation with the Hyland and Wexler expression for water vapor saturation pressure. The error covariance matrix of ERA5 was derived from the differences between ERA5 and a set of 50 special radiosoundings that have not been assimilated into ERA5. We validate ERA5-reRH, ERA5, and RALMO temperature and relative humidity profiles against the same set of special radiosoundings and found the best agreement was with our reanalysis, with a bias of less than 2% relative humidity with respect to water (%RHw) and a spread of less than 8%RHw below 8 km in terms of relative humidity. Improvements for temperature in our reanalysis are only found in the boundary layer, as ERA5 assimilates a large number of upper-air temperature observations. Our retrieval also provides a full uncertainty budget of the reanalyzed temperature and relative humidity including both random and systematic uncertainties.
7 citations
TL;DR: A pure rotational Raman lidar for measuring the all-day temperature profiles in the lower troposphere with 1-σ statistical uncertainty <1K between altitudes ranging from 0.6 to ∼2.0km is described, indicating a possible seasonal dependence.
Abstract: We describe a pure rotational Raman lidar for measuring the all-day temperature profiles in the lower troposphere. The lidar is made up of a frequency-tripled Nd:YAG laser at 354.82 nm with ∼250mJ pulse energy at the 30 Hz repetition rate, a 200 mm receiving telescope, and narrow-band interference-filter-based detection optics. The lidar performance is shown by measured examples. Under clear sky conditions, with an integration time of 60 min and a vertical resolution of 90 m, the 1-σ statistical uncertainty does not exceed 1 K up to the altitude of ∼4.1km during nighttime, while the corresponding altitude is ∼2.3km at noon. The diurnal temperature variation characteristics have been revealed by the lidar measurements with the 1-σ statistical uncertainty 0.6km, the diurnal amplitude in the September period is less than that in the July period, but greater than that in the January period. The phase delays of the diurnal oscillations are ∼3h in the July period, 5-6 h in the September period, and 5-7 h in the January period compared to those at the surface, respectively. Both the diurnal amplitudes and phase delays indicate a possible seasonal dependence.
3 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: The dispersion of the depolarization factor is shown to affect the Rayleigh phase function slightly, by approximately 1% in the forward, backscattered, and 90° scattering-angle directions.
Abstract: Rayleigh-scattering cross sections and volume-scattering coefficients are computed for standard air; they incorporate the variation of the depolarization factor with wavelength. Rayleigh optical depths are then calculated for the 1962 U.S. Standard Atmosphere and for five supplementary models. Analytic formulas are derived for each of the parameters listed. The new optical depths can be 1.3% lower to 3% higher at midvisible wavelengths and up to 10% higher in the UV region compared with previous calculations, in which a constant or incorrect depolarization factor was used. The dispersion of the depolarization factor is also shown to affect the Rayleigh phase function slightly, by approximately 1% in the forward, backscattered, and 90° scattering-angle directions.
669 citations
TL;DR: Examples covering the measured range of extinction-to-backscatter ratios (lidar ratios) in ice clouds are presented and simple backscatter lidars can provide reliable information about the cloud optical depth and the mean cloud lidar ratio.
Abstract: Height profiles of the extinction and the backscatter coefficients in cirrus clouds are determined independently from elastic- and inelastic- (Raman) backscatter signals. An extended error analysis is given. Examples covering the measured range of extinction-to-backscatter ratios (lidar ratios) in ice clouds are presented. Lidar ratios between 5 and 15 sr are usually found. A strong variation between 2 and 20 sr can be observed within one cloud profile. Particle extinction coefficients determined from inelastic-backscatter signals and from elastic-backscatter signals by using the Klett method are compared. The Klett solution of the extinction profile can be highly erroneous if the lidar ratio varies along the measuring range. On the other hand, simple backscatter lidars can provide reliable information about the cloud optical depth and the mean cloud lidar ratio.
668 citations
TL;DR: In this paper, a combined Raman elastic-backscatter lidar has been developed, where a XeCl excimer laser is used as the radiation source and inelastic Raman backscatter signals are spectrally separated from the elastic signal with a filter or grating polychromator.
Abstract: A combined Raman elastic-backscatter lidar has been developed. A XeCl excimer laser is used as the radiation source. Inelastic Raman backscatter signals are spectrally separated from the elastic signal with a filter or grating polychromator. Raman channels can be chosen to register signals from CO2, O2, N2, and H2O. Algorithms for the calculation of the water-vapor mixing ratio from the Raman signals and the particle extinction and backscatter coefficients from both elastic and inelastic backscatter signals are given. Nighttime measurements of the vertical humidity distribution up to the tropopause and of particle extinction, backscatter, and lidar ratio profiles in the boundary layer, in high-altitude water and ice clouds, and in the stratospheric aerosol layer are presented. Daytime boundary-layer measurements of moisture and particle extinction are made possible by the improved daylight suppression of the grating polychromator. Test measurements of the CO2 mixing ratio indicate the problems for the Raman lidar technique in monitoring other trace gases than water vapor.
415 citations