scholarly journals Stratospheric Ozone Density Retrieval Using the Optimal Estimation Method (OEM)

2018 ◽  
Vol 176 ◽  
pp. 03006
Author(s):  
Ghazal Farhani ◽  
R. J. Sica ◽  
Sophie Godin-Beekmann ◽  
Alexander Haefele

We use an Optimal Estimation Method (OEM) to retrieve ozone profiles from the CANDAC Stratospheric Ozone Differential Absorption Lidar in Eureka, Canada. The OEM is a well known inverse method in which a forward model (FM) is used to describe the instrument and geophysical situation. We have developed a FM and are testing its validity using synthetic measurements. We will present the advantages of using OEM retrievals over the traditional method, including a full uncertainty budget.

2016 ◽  
Vol 9 (8) ◽  
pp. 4051-4078 ◽  
Author(s):  
Thierry Leblanc ◽  
Robert J. Sica ◽  
Joanna A. E. van Gijsel ◽  
Sophie Godin-Beekmann ◽  
Alexander Haefele ◽  
...  

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.


2018 ◽  
Author(s):  
Ghazal Farhani ◽  
Robert J. Sica ◽  
Sophie Godin-Beekmann ◽  
Alexander Haefele

Abstract. This paper provides a detailed description of the first principle Optimal Estimation Method (OEM) which is applied to ozone retrieval analysis using Differential Absorption Lidar (DIAL) measurements. The air density, detector dead times, background coefficients, and lidar constants are simultaneously retrieved along with ozone density profiles. Using an averaging kernel, the OEM provides the vertical resolution of the retrieval as a function of altitude. A maximum acceptable height at which the a priori has a small contribution to the retrieval is calculated for each profile as well. Moreover, a complete uncertainty budget including both systematic and statistical uncertainties is given for each individual retrieved profile. Long term stratospheric DIAL ozone measurements have been carried out at the Observatoire de Haute-Provence (OHP) since 1985. The OEM is applied to 3 nights of measurements at OHP during an intensive ozone campaign in July 2017 where coincident lidar-ozonesonde measurements are available. The retrieved ozone density profiles are in good agreement with both traditional analysis and the ozonesonde measurements. For the three nights of measurements, below 15 km the difference between the OEM and the sonde profiles is less than 25 %, at altitudes between 15 km to 25 km the difference is less than 10 %, and the OEM can successfully catch many variations of ozone which are detected in the sonde profiles due to its ability to adjust its vertical resolution as the signal varies. Above 25 km the difference between the OEM and the sonde profiles does not exceed 20 %.


2019 ◽  
Vol 12 (4) ◽  
pp. 2097-2111 ◽  
Author(s):  
Ghazal Farhani ◽  
Robert J. Sica ◽  
Sophie Godin-Beekmann ◽  
Alexander Haefele

Abstract. This paper provides a detailed description of a first-principle optimal estimation method (OEM) applied to ozone retrieval analysis using differential absorption lidar (DIAL) measurements. The air density, detector dead times, background coefficients, and lidar constants are simultaneously retrieved along with ozone density profiles. Using an averaging kernel, the OEM provides the vertical resolution of the retrieval as a function of altitude. A maximum acceptable height at which the a priori has a small contribution to the retrieval is calculated for each profile as well. Moreover, a complete uncertainty budget including both systematic and statistical uncertainties is given for each individual retrieved profile. Long-term stratospheric DIAL ozone measurements have been carried out at the Observatoire de Haute-Provence (OHP) since 1985. The OEM is applied to three nights of measurements at OHP during an intensive ozone campaign in July 2017 for which coincident lidar–ozonesonde measurements are available. The retrieved ozone density profiles are in good agreement with both traditional analysis and the ozonesonde measurements. For the three nights of measurements, below 15 km the difference between the OEM and the sonde profiles is less than 25 %, and at altitudes between 15 and 25 km the difference is less than 10 %; the OEM can successfully catch many variations in ozone, which are detected in the sonde profiles due to its ability to adjust its vertical resolution as the signal varies. Above 25 km the difference between the OEM and the sonde profiles does not exceed 20 %.


2018 ◽  
Vol 176 ◽  
pp. 01011
Author(s):  
S. Mahagammulla Gamage ◽  
A. Haefele ◽  
R.J. Sica

We present the application of the Optimal Estimation Method (OEM) to retrieve atmospheric temperatures from pure rotational Raman (PRR) backscatter lidar measurements. A forward model (FM) is developed to retrieve temperature and tested using synthetic measurements. The OEM offers many advantages for this analysis, including eliminating the need to determine temperature calibration coefficients.


2021 ◽  
Author(s):  
Arno Keppens ◽  
Jean-Christopher Lambert ◽  
Daan Hubert ◽  
Steven Compernolle ◽  
Tijl Verhoelst ◽  
...  

<p>Part of the space segment of EU’s Copernicus Earth Observation programme, the Sentinel-5 Precursor (S5P) mission is dedicated to global and European atmospheric composition measurements of air quality, climate and the stratospheric ozone layer. On board of the S5P early afternoon polar satellite, the imaging spectrometer TROPOMI (TROPOspheric Monitoring Instrument) performs nadir measurements of the Earth radiance within the UV-visible and near-infrared spectral ranges, from which atmospheric ozone profile data are retrieved. Developed at the Royal Netherlands Meteorological Institute (KNMI) and based on the optimal estimation method, TROPOMI’s operational ozone profile retrieval algorithm has recently been upgraded. With respect to early retrieval attempts, accuracy is expected to have improved significantly, also thanks to recent updates of the TROPOMI Level-1b data product. This work reports on the initial validation of the improved TROPOMI height-resolved ozone data in the troposphere and stratosphere, as collected both from the operational S5P Mission Performance Centre/Validation Data Analysis Facility (MPC/VDAF) and from the S5PVT scientific project CHEOPS-5p. Based on the same validation best practices as developed for and applied to heritage sensors like GOME-2, OMI and IASI (Keppens et al., 2015, 2018), the validation methodology relies on the analysis of data retrieval diagnostics – like the averaging kernels’ information content – and on comparisons of TROPOMI data with reference ozone profile measurements. The latter are acquired by ozonesonde, stratospheric lidar, and tropospheric lidar stations performing network operation in the context of WMO's Global Atmosphere Watch and its contributing networks NDACC and SHADOZ. The dependence of TROPOMI’s ozone profile uncertainty on several influence quantities like cloud fraction and measurement parameters like sun and scan angles is examined and discussed. This work concludes with a set of quality indicators, enabling users to verify the fitness-for-purpose of the S5P data.</p>


2018 ◽  
Vol 11 (11) ◽  
pp. 6043-6058 ◽  
Author(s):  
Ali Jalali ◽  
Robert J. Sica ◽  
Alexander Haefele

Abstract. Hauchecorne and Chanin (1980) developed a robust method to calculate middle-atmosphere temperature profiles using measurements from Rayleigh-scatter lidars. This traditional method has been successfully used to greatly improve our understanding of middle-atmospheric dynamics, but the method has some shortcomings regarding the calculation of systematic uncertainties and the vertical resolution of the retrieval. Sica and Haefele (2015) have shown that the optimal estimation method (OEM) addresses these shortcomings and allows temperatures to be retrieved with confidence over a greater range of heights than the traditional method. We have calculated a temperature climatology from 519 nights of Purple Crow Lidar Rayleigh-scatter measurements using an OEM. Our OEM retrieval is a first-principle retrieval in which the forward model is the lidar equation and the measurements are the level-0 count returns. It includes a quantitative determination of the top altitude of the retrieved temperature profiles, the evaluation of nine systematic plus random uncertainties, and the vertical resolution of the retrieval on a profile-by-profile basis. Our OEM retrieval allows for the vertical resolution to vary with height, extending the retrieval in altitude 5 to 10 km higher than the traditional method. It also allows the comparison of the traditional method's sensitivity to two in-principle equivalent methods of specifying the seed pressure: using a model pressure seed versus using a model temperature combined with the lidar's density measurement to calculate the seed pressure. We found that the seed pressure method is superior to using a model temperature combined with the lidar-derived density. The increased altitude capability of our OEM retrievals allows for a comparison of the Rayleigh-scatter lidar temperatures throughout the entire altitude range of the sodium lidar temperature measurements. Our OEM-derived Rayleigh temperatures are shown to have improved agreement relative to our previous comparisons using the traditional method, and the agreement of the OEM-derived temperatures is the same as the agreement between existing sodium lidar temperature climatologies. This detailed study of the calculation of the new Purple Crow Lidar temperature climatology using the OEM establishes that it is both highly advantageous and practical to reprocess existing Rayleigh-scatter lidar measurements that cover long time periods, during which time the lidar may have undergone several significant equipment upgrades, while gaining an upper limit to useful temperature retrievals equivalent to an order of magnitude increase in power-aperture product due to the use of an OEM.


2019 ◽  
Vol 12 (11) ◽  
pp. 5801-5816 ◽  
Author(s):  
Shayamila Mahagammulla Gamage ◽  
Robert J. Sica ◽  
Giovanni Martucci ◽  
Alexander Haefele

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.


1995 ◽  
Vol 100 (D12) ◽  
pp. 25899 ◽  
Author(s):  
J. F. Hahn ◽  
C. T. McElroy ◽  
E. W. Hare ◽  
W. Steinbrecht ◽  
A. I. Carswell

2002 ◽  
Vol 80 (4) ◽  
pp. 341-356 ◽  
Author(s):  
Ph. Baron ◽  
Ph. Ricaud ◽  
J de la Noë ◽  
J EP Eriksson ◽  
F Merino ◽  
...  

This paper presents the first algorithm developed to retrieve atmospheric vertical profiles of trace gases from calibrated spectra measured by the sub-millimetre radiometer (SMR) onboard the Odin satellite. An estimation of atmospheric profiles is obtained by means of an inversion of the spectra using the Optimal Estimation Method. Great attention is paid to the study of the simultaneous retrieval of several species and nonlinearity effects. The measurement response is defined to give the altitude domain of a good retrieval. Main sources of measurement and forward model errors are characterized and separated into two categories: the fixed errors and the variable errors. We define a standard retrieval strategy that can be applied to theoretically investigate any frequency band of any observing Odin mode. For each frequency band, two categories of species are defined: the target species, i.e., the main species to be retrieved, and the interfering species, i.e., molecules emitting an interfering radiance in the observed band. The standard code is based upon an inversion of spectra using a linearized forward model and simultaneously estimates target species and interfering species. As an example, inversions of synthetic noise-free spectra of ozone and chlorine monoxide within an autocorrelator band ranging from 501.18 to 501.58 GHz are shown to behave as expected in the middle stratosphere and in the lower mesosphere. The error analysis shows retrieval limitations in the lower stratosphere that are mainly induced by the high sensitivity of the retrieval to parameters such as tangent height, accuracy in the vertical profile of the interfering species, and spectral parameters of both target lines and interfering lines. PACS Nos.: 42.68Ay, 07.07Df, 07.57Kp


Sign in / Sign up

Export Citation Format

Share Document