Optimal Estimation Method Research Articles

Integrate Uncertainty in the Process of Prognostics for Electronics

Elements of uncertainty in the electronics Prognostics process were studied. A method for electronics Dynamic Damage Optimal Estimation and prognostics based on Particle Filtering were proposed. Under the effect of time stress, the electronics cumulative damage is the result of the continuous effect of the stress, as a result, a HMM based electronics dynamic damage model was built at first place, analytical results of uncertainties in the process of prognostics were given and thus a Bayesian based filter system was built. Bayesian Filter change the problem of uncertainty into an optimal estimation processes as a result, the optimal estimation was fetched by applying the particle filtering into the estimation. The experiment case study proved that the proposed method can eliminate the uncertainties caused by measurement and the system effectively and improve the RUL prediction accuracy.

Simultaneous trace gas measurements using two Fourier transform spectrometers at Eureka, Canada during spring 2006, and comparisons with the ACE-FTS

Abstract. The 2006 Canadian Arctic ACE (Atmospheric Chemistry Experiment) Validation Campaign collected measurements at the Polar Environment Atmospheric Research Laboratory (PEARL, 86.42° W, 80.05° N, 610 m a.s.l.) at Eureka, Canada from 17 February to 31 March 2006. Two of the ten instruments involved in the campaign, both Fourier transform spectrometers (FTSs), were operated simultaneously, recording atmospheric solar absorption spectra. The first instrument was an ABB Bomem DA8 high-resolution infrared FTS. The second instrument was the Portable Atmospheric Research Interferometric Spectrometer for the Infrared (PARIS-IR), the ground-based version of the satellite-borne FTS on the ACE satellite (ACE-FTS). From the measurements collected by these two ground-based instruments, total column densities of seven stratospheric trace gases (O3, HCl, ClONO2, HF, HNO3, NO2, and NO) were retrieved using the optimal estimation method and these results were compared. Since the two instruments sampled the same portions of atmosphere by synchronizing observations during the campaign and used consistent retrieval parameters, the biases in retrieved columns from the two spectrometers represent the instrumental differences. Mean differences in total column densities of O3, HCl, ClONO2, HF, HNO3, and NO2 from the observations between PARIS-IR and the DA8 FTS are 2.8 %, −3.2 %, −4.3 %, −1.5 %, −1.9 %, and −0.1 %, respectively. Partial column results from the ground-based spectrometers were also compared with partial columns derived from ACE-FTS version 2.2 (including updates for O3) profiles. Mean differences in partial column densities of O3, HCl, ClONO2, HF, HNO3, NO2, and NO from the measurements between ACE-FTS and the DA8 FTS are −5.9 %, −8.5 %, −11.8 %, −0.9 %, −6.6 %, −21.6 % and −7.6 % respectively. Mean differences in partial column densities of O3, HCl, ClONO2, HF, HNO3, NO2 from the measurements between ACE-FTS and the PARIS-IR are −5.2 %, −4.6 %, −2.3 %, −4.7 %, 5.7 % and −11.9 %, respectively. This work provides further evidence of the reliability of ACE-FTS measurements from the first three years of on-orbit observations. Column densities of O3, HCl, ClONO2, and HNO3 from the three FTSs were normalized with respect to HF and used to compare the time evolution of the chemical constituents in the atmosphere over Eureka during spring 2006.

Retrieval algorithm for CO<sub>2</sub> and CH<sub>4</sub> column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite

Abstract. The Greenhouse gases Observing SATellite (GOSAT) was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here, we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS). The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from instrumental noise. The interferences due to auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and temporal variation patterns of the retrieved column abundances show features similar to those of an atmospheric transport model.

Maritime radar display unit based on PC for safe ship navigation

A prototype radar display unit was implemented using inexpensive off-the-shelf components, including a nonlinear estimation algorithm for the target tracking in a clutter environment. Two custom designed boards; an analog signal processing board and a DSP board, can be plugged into an expansion slot of a personal computer (PC) to form a maritime radar display unit. Our system provided all the functionality specified in the International Maritime Organization (IMO) resolution A422(XI). The analog signal processing board was used for A/D conversion as well as rain and sea clutter suppression. The main functions of the DSP board were scan conversion and video overlay operations. A host PC was used to run the tracking algorithm of targets in clutter, using the discrete-time Bayes optimal (nonlinear, and non-Gaussian) estimation method, and the graphic user interface (GUI) software for Automatic Radar Plotting Aid (ARPA). The proposed tracking method recursively found the entire probability density function of the target position and velocity by converting into linear convolution operations.

Modeling data revisions: Measurement error and dynamics of “true” values

Policy makers must base their decisions on preliminary and partially revised data of varying reliability. Realistic modeling of data revisions is required to guide decision makers in their assessment of current and future conditions. This paper provides a new framework with which to model data revisions. Recent empirical work suggests that measurement errors typically have much more complex dynamics than existing models of data revisions allow. This paper describes a state-space model that allows for richer dynamics in these measurement errors, including the noise, news and spillover effects documented in this literature. We also show how to relax the common assumption that “true” values are observed after a few revisions. The result is a unified and flexible framework that allows for more realistic data revision properties, and allows the use of standard methods for optimal real-time estimation of trends and cycles. We illustrate the application of this framework with real-time data on US real output growth.

Densities and temperatures in the Venus mesosphere and lower thermosphere retrieved from SOIR on board Venus Express: Retrieval technique

The SOIR instrument, flying on board Venus Express, operates in the infrared spectral domain and uses the solar occultation technique to determine the vertical profiles of several key constituents of the Venus atmosphere. The retrieval algorithm is based on the optimal estimation method, and solves the problem simultaneously on all spectra belonging to one occultation sequence. Vertical profiles of H2O, CO, HCl, and HF, as well as some of their isotopologues, are routinely obtained for altitudes ranging typically from 70 to 120 km, depending on the species and the spectral region recorded. In the case of CO2, a vertical profile from 70 up to 150 km can be obtained by combining different spectral intervals. Rotational temperature is also retrieved directly from the CO2 signature in the spectra. The present paper describes the method used to derive the above mentioned atmospheric quantities and temperature profiles. The method is applied on some retrieval cases illustrating the capabilities of the technique. More examples of results will be presented and discussed in a following companion paper which will focus on the CO2 vertical profiles of the whole data set.

Hydrogen fluoride total and partial column time series above the Jungfraujoch from long‐term FTIR measurements: Impact of the line‐shape model, characterization of the error budget and seasonal cycle, and comparison with satellite and model data

Time series of hydrogen fluoride (HF) total columns have been derived from ground‐based Fourier transform infrared (FTIR) solar spectra recorded between March 1984 and December 2009 at the International Scientific Station of the Jungfraujoch (Swiss Alps, 46.5°N, 8.0°E, 3580 m asl) with two high‐resolution spectrometers (one homemade and one Bruker 120‐HR). Solar spectra have been inverted with the PROFFIT 9.5 algorithm, using the optimal estimation method. An intercomparison of HF total columns retrieved with PROFFIT and SFIT‐2–the other reference algorithm in the FTIR community–is performed for the first time. The effect of a Galatry line shape model on HF retrieved total columns and vertical profiles, on the residuals of the fits and on the error budget is also quantified. Information content analysis indicates that in addition to HF total vertical abundance, three independent stratospheric HF partial columns can be derived from our Bruker spectra. A complete error budget has been established and indicates that the main source of systematic error is linked to HF spectroscopy and that the random error affecting our HF total columns does not exceed 2.5%. Ground‐based middle and upper stratospheric HF amounts have been compared to satellite data collected by the HALOE or ACE‐FTS instruments. Comparisons of our FTIR HF total and partial columns with runs performed by two three‐dimensional numerical models (SLIMCAT and KASIMA) are also included. Finally, FTIR and model HF total and partial columns time series have been analyzed to derive the main characteristics of their seasonal cycles.

P24-26 A novel method for optimal estimation of cortico-muscular coherence based on multi-channel EEG/MEG recordings

P24-26 A novel method for optimal estimation of cortico-muscular coherence based on multi-channel EEG/MEG recordings

Optimal estimation retrieval of aerosol microphysical properties from SAGE~II satellite observations in the volcanically unperturbed lower stratosphere

Abstract. Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003). An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE) method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths) with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities), even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal) size distributions naturally differ from the correct bimodal values, the associated surface area (A) and volume densities (V) are, nevertheless, fairly accurately retrieved, except at values larger than 1.0 μm2 cm−3 (A) and 0.05 μm3 cm−3 (V), where they tend to underestimate the true bimodal values. Due to the limited information content in the SAGE II spectral extinction measurements this kind of forward model error cannot be avoided here. Nevertheless, the retrieved uncertainties are a good estimate of the true errors in the retrieved integrated properties, except where the surface area density exceeds the 1.0 μm2 cm−3 threshold. When applied to near-global SAGE II satellite extinction measured in 1999 the retrieved OE surface area and volume densities are observed to be larger by, respectively, 20–50% and 10–40% compared to those estimates obtained by the SAGE~II operational retrieval algorithm. An examination of the OE algorithm biases with in situ data indicates that the new OE aerosol property estimates tend to be more realistic than previous estimates obtained from remotely sensed data through other retrieval techniques. Based on the results of this study we therefore suggest that the new Optimal Estimation retrieval algorithm is able to contribute to an advancement in aerosol research by considerably improving current estimates of aerosol properties in the lower stratosphere under low aerosol loading conditions.

Numerical discretization of stationary random processes

The increasing interest of the research community to the probabilistic analysis concerning the civil structures with space-variant properties points out the problem of achieving a reliable discretization of random processes (or random fields in a multi-dimensional domain). Given a discretization method, a continuous random process is approximated by a finite set of random variables. Its dimension affects significantly the accuracy of the approximation, in terms of the relevant properties of the continuous random process under investigation. The paper presents a discretization procedure based on the truncated Karhunen–Loève series expansion and the finite element method. The objective is to link in a rational way the number of random variables involved in the approximation to a quantitative measure of the discretization accuracy. The finite element method is applied to evaluate the terms of the series expansion when a closed form expression is not available. An iterative refinement of the finite element mesh is proposed in this paper, leading to an accurate random process discretization. The technique is tested with respect to the exponential covariance function, that enables a comparison with analytical expressions of the approximated properties of the random process. Then, the procedure is applied to the square exponential covariance functions, which is one of the most used covariance models in the structural engineering field. The comparison of the adaptive refinement of the discretization with a non-adaptive procedure and with the wavelet Galerkin approach allows to demonstrate the computational efficiency of the proposal within the framework of the Karhunen–Loève series expansion. A comparison with the Expansion Optimal Linear Estimation (EOLE) method is performed in terms of efficiency of the discretization strategy.

A Rain-Rate Retrieval Algorithm for Attenuated Radar Measurements

Abstract A dynamic regularization scheme for rain-rate retrievals from attenuated radar measurements is presented. Most regularization techniques, including the optimal estimation method, use the state-space parameters to regularize the problem, which will always lead to a bias in the solution. To avoid this problem the authors introduce an evolutionary regularization technique, which is based on the spatial derivative of the measured reflectivity profile and allows for a bias-free global solution. The regularization strength is determined by the quadratic eigenvalue solution using the regularized total least squares method. With the new method, the authors perform a retrieval of rain-rate profiles from simulated measurements of a nadir-pointing W-band (94 GHz) radar, in a configuration similar to the cloud radar employed on CloudSat. The simulations assume that multiple scattering is negligible and only liquid hydrometeors are taken into account. The authors compare the results of this method with the outcome of an optimal estimation method and demonstrate that their method is superior in terms of reliability, correlation coefficient, and dispersion to the optimal estimation method for layers experiencing high values of attenuation; therefore, the a priori bias typical for optimal estimation solutions is avoided.

Detection of volcanic SO2, ash, and H2SO4 using the Infrared Atmospheric Sounding Interferometer (IASI)

In this work we use infrared spectra recorded by the Infrared Atmospheric Sounding Interferometer (IASI) to characterize the emissions from the Mount Kasatochi volcanic eruption on 7 and 8 August 2008. We first derive the total atmospheric load of sulfur dioxide (SO2) and its evolution over time. For the initial plume, we found values over 1.7 Tg of SO2, making it the largest eruption since the 1991 eruptions of Pinatubo and Hudson. Vertical profiles were retrieved using a line‐by‐line radiative transfer model and an inversion procedure based on the optimal estimation method (OEM). For the Kasatochi eruption, we found a plume altitude of 12.5 ± 4 km. Taking advantage of IASI's broad spectral coverage, we used the ν3 band (∼1362 cm−1) and, for the first time, the ν1 + ν3 band (∼2500 cm−1) of SO2 for the retrievals. While the ν3 band saturates easily for high SO2 concentrations, preventing accurate retrieval, the ν1 + ν3 band has a much higher saturation threshold. We also analyzed the broadband signature observed in the radiance spectra in the 1072–1215 cm−1 range associated with the presence of aerosols. In the initial volcanic plume the signature matches closely that of mineral ash, while by 10 August most mineral ash is undetectable, and the extinction is shown to match closely the absorption spectrum of liquid H2SO4 drops. The extinction by sulphuric acid particles was confirmed by comparing spectra before and a month after the eruption, providing the first spectral detection of such aerosols from nadir view radiance data.

Joint retrieval of surface reflectance and aerosol optical depth from MSG/SEVIRI observations with an optimal estimation approach: 1. Theory

An original method is presented in this paper for the joint retrieval of the mean daily total column aerosol optical depth and surface BRF from the daily accumulated Meteosat Second Generation–Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI) observations in the solar channels. The proposed algorithm is based on the optimal estimation (OE) theory, a one‐dimensional variational retrieval scheme that seeks an optimal balance between information that can be derived from the observations, and the one that is derived from prior knowledge of the system. The forward radiative transfer model explicitly accounts for the surface anisotropy and its coupling with the atmosphere. The low rate of change in the surface reflectance is used to derive the prior information on the surface state variables. The reliable estimation of the measurement system error is one of the most critical aspects of the OE method as it strongly determines the likelihood of the solution. An important effort in the proposed method has thus been dedicated to this issue, where the actual radiometric performances of SEVIRI are dynamically taken into account.

H<sub>2</sub><sup>16</sup>O and HDO measurements with IASI/MetOp

Abstract. In this paper we analyze distributions of water vapour isotopologues in the troposphere using infrared spectra recorded by the Infrared Atmospheric Sounding Interferometer (IASI), which operates onboard the Metop satellite in nadir geometry. The simultaneous uncorrelated retrievals of H216O and HDO are performed on radiance measurements using a line-by-line radiative transfer model and an inversion procedure based on the Optimal Estimation Method (OEM). The characterizations of the retrieved products in terms of vertical sensitivity and error budgets show that IASI measurements contain up to 6 independent pieces of information on the vertical distribution of H216O and up to 3.5 for HDO from the surface up to the upper troposphere (0–20 km). Although the purpose of the paper is not validation, a restricted comparison with sonde measurements shows that the retrieved H216O profiles capture the seasonal/latitudinal variations of the water content, with good accuracy in the lowest layer but with larger uncertainties higher in the free and upper troposphere. Our results then demonstrate the ability of the IASI instrument to monitor atmospheric isotopologic water vapour distributions and to provide information on the partitioning of HDO as compared to H216O. The derivation of the δD is challenging and associated with large errors in the uncorrelated retrieval approach chosen here. As a result averaging on the vertical to produce a column-averaged δD is required to produce meaningful results for geophysical interpretation. As a case study, we analyse concentration distributions and spatio-temporal variations of H216O and δD during the October 2007 Krosa super-typhoon over South-East Asia. We show that individual δD have uncertainties of 37‰ for the vertically averaged values. Using the latter, we suggest that the typhoon produces a so-called amount-effect, where the δD is negatively correlated to the water amounts as a result of intense depletion of the deuterated species.

Application of active power sensitivity to frequency and voltage variations on load shedding

The occurrence of a large disturbance in a power system can lead to a decline in the system frequency and bus voltages due to a real and reactive power deficiency or due to the formation of islands with generation–load imbalance. Load shedding is an emergency control action that can prevent a blackout in the power system by relieving the overload in some parts of the system. This paper shows that rate of change of frequency can be utilized to determine the magnitude of generation–load imbalance, while the rate of change of voltage with respect to active power can be utilized to identify the sensitive bus for load shedding. The frequency, voltages and their rate of change can be obtained by means of measurements in real-time from various devices such as digital recorders or phasor measurement units or these parameters can be estimated from the voltage data by other means such as an optimal estimation method like Kalman filtering. The rate of change of system frequency, along with the equivalent system inertia may be used to estimate the magnitude of the disturbance prior to each load shedding step. The buses with a higher rate of change of voltage may be identified as the critical ones for load shedding and load can be first shed at these buses, depending on the change in the power flow at each bus. This application is tested on the IEEE 30 bus system and the preliminary results demonstrate that it is feasible to be used in load shedding to restore system voltage and frequency.

An evaluation of infrared microwindows for ozone retrievals using the Eureka Bruker 125HR Fourier transform spectrometer

Abstract A Bruker 125HR Fourier transform spectrometer was installed at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Nunavut, Canada in the summer of 2006 to study atmospheric composition. Using the optimal estimation method, typically over a limited spectral region called a microwindow, information about the vertical distribution of trace gas species that have absorption bands in the mid-infrared spectral range can be retrieved. Total and partial columns can also be determined to show the temporal evolution of the target gas. For ozone in particular, retrievals have been performed using several of its many mid-infrared absorption features, resulting in a lack of consistency in the literature in the microwindows chosen for retrievals. This work focuses on the optimization of the ozone retrieval, assessing a set of 22 microwindows between 780 and 3052 cm −1 to determine which is best suited to conditions at Eureka. The 1000–1004.5 cm −1 spectral interval is shown to be the most sensitive to both the stratosphere and troposphere. This microwindow gives the highest number of degrees of freedom for signal (∼7 for total column), and the smallest total error (4.3%) compared with 21 other spectral regions. Retrievals performed with this microwindow agree well with results obtained from other instruments on-site. Total column ozone measured by the Bruker 125HR in this microwindow agreed to 2% with two other Fourier transform spectrometers, to 0.7% with a Brewer spectrophotometer, to 8% with a SAOZ UV–VIS spectrometer, and to 7% with ozone sondes.

Global distributions of nitric acid from IASI/MetOP measurements

Abstract. This paper presents the first global distributions of HNO3 total columns acquired by the Infrared Atmospheric Sounding Interferometer (IASI) instrument, launched onboard the MetOp platform in October 2006. IASI is an infrared nadir-looking Fourier transform spectrometer providing atmospheric radiance spectra at 0.5 cm−1 spectral resolution, from which temperature and infrared absorbing gas concentration profiles are retrieved with global Earth coverage twice a day. A first analysis of the IASI measurements in terms of information content demonstrates the possibility of retrieving a total column for HNO3 at all latitudes with a maximal sensitivity in the middle stratosphere. The retrievals are performed from IASI spectra in the atmospheric window using a fast radiative transfer model and inversion software (FORLI) relying on the Optimal Estimation Method. The operational processing of HNO3 total columns is achieved since March 2008. We show that FORLI-HNO3 performs well at all latitudes (RMS of the spectral residuals around 2.3×10−6 W/m2 sr m−1) and provides HNO3 total columns with on average statistical errors of about 12%, reaching the threshold value of 32% at the equatorial belt. The global distributions of the retrieved total columns for one year (from March 2008 to February 2009) are presented and discussed with emphasis given to seasonal and interhemispheric variations. Local seasonal variations at 6 specific locations are also described and discussed in comparison with MLS volume mixing ratios at 46.5 hPa. The seasonal cycle observed in Polar regions is highlighted, with maxima observed in fall-winter and minima during spring-summer. The denitrification inside the Antarctic polar vortex during winter is clearly revealed with unprecedented horizontal resolution: HNO3 columns decreasing down to about 1×1016 molecules cm−2 are observed, which is consistent with the lower values of temperature observed between 50 and 15 hPa (~20–25 km) and the resulting formation and sedimentation of polar stratospheric clouds. During the same period, the collar region of high quantities of HNO3 at the vortex edge is also observed around 65–60° S latitude. Preliminary correlations between IASI derived HNO3 and O3 columns inside the polar vortex are presented and discussed.

Semiautonomous FTS Observation System for Remote Sensing of Stratospheric and Tropospheric Gases

Abstract A solar-viewing Fourier transform spectrometer (FTS) at Thule, Greenland (76.5°N, 68.8°W, 225 m MSL), has been in operation as part of the Network for the Detection of Atmospheric Composition Change [NDACC; formerly the Network for the Detection of Stratospheric Change (NDSC)] since 1999. Observations have been made, on average, 77 days yr−1 during the 8 months, excluding polar night. The semiautonomous operation of the instrument, including its associated optical, cryogenic, and control systems, is of primary importance to acquiring long-term data records efficiently and is herein described. Discussed in this paper are the data processing and spectra analysis methodology that are used to convert the measured interferograms into geophysical data products. Vertical profile retrievals derived from the high-resolution solar absorption spectra use the optimal estimation method. Total column amounts then represent the integration of these vertical profiles. As an example of this process, results are presented for daily average total column amounts of HF, HCl, ClONO2, and CCl2F2 from 2001 through 2007. The means of unperturbed summertime observations are used in a preliminary study of their annual trends.

Inner-tropical ozone measurements at the Mérida Atmospheric Research Station (MARS) using ground-based microwave radiometry

Since March 2004 the ground-based 268–280 GHz radiometer MIRA 2 has been in quasi-continuous operation at the inner-tropical Mérida Atmospheric Research Station (MARS) on Pico Espejo (8.58°N, 71.15°W, 4765 m above sea level) in the Venezuelan Andes. Using the optimal estimation method concentration profiles of ozone have been retrieved in the stratosphere and mesosphere. In the middle stratosphere variations of ozone on a time scale of several months were revealed in the resulting time series that probably result from the turnaround of the Brewer–Dobson circulation. In the mesosphere photochemistry plays the most important role for the ozone concentration. Therefore a diurnal cycle is observed in the upper part of the retrieved ozone profiles. The measurements are used to verify model results of ozone in the mesosphere obtained by a photochemistry model, which reproduces the diurnal variation of ozone very well. Also an inter-annual variation of mesospheric ozone during the month of November in 2004–2007 was observed, primarily during the night. As the time series is still too short to clearly distinguish solar or QBO signals, the cause of this inter-annual variation cannot yet be related to one or the other. In November 2006 an unusual decrease of the ozone partial columns above 60 km was measured; the cause of this decrease is also not identified so far.

Improving spectroscopic line parameters by means of atmospheric spectra: Theory and example for water vapor and solar absorption spectra

Current atmospheric remote sensing experiments measuring high resolution spectra apply instruments of similar quality as the laboratory experiments that are especially equipped to derive spectroscopic parameters. We propose a method that uses high quality atmospheric spectra to improve the spectroscopic parameterization. It is an optimal estimation method that applies the uncertainty ranges given in current spectroscopic databases as a priori covariance and the residuals between the simulated and measured atmospheric spectra as new measurements. We test the method by updating the current HITRAN parameters of 49 mid-infrared water vapor lines (situated in 15 spectral windows between 795 and 1330 cm - 1 ) by the information present in high quality ground-based Fourier transform infra-red (FTIR) spectra. We show that the application of a speed dependent Voigt line shape model is important. The updated water vapor parameterization, compared to the original one, leads to lower residuals, larger measurement information content, and better agreement between remotely sensed and coincident in situ water vapor profiles. Using the new line parameterization, a state-of-the-art ground-based FTIR system is able to monitor upper tropospheric water vapor amounts and middle/upper tropospheric HDO / H 2 O ratios.