Retrieval Of Atmospheric Parameters Research Articles

In-orbit verification of microwave humidity sounder spectral channels coregistration using the moon

In-orbit verification of the coregistration of channels in a scanning microwave or infrared radiometer can in principle be done during normal in-orbit operation, using the regular events of lunar intrusion in the instrument cold space calibration view. A technique of data analysis based on best fit of data across lunar intrusions has been used to check the mutual alignment of the spectral channels of the microwave humidity sounder (MHS) instrument. MHS is a cross-track scanning radiometer in the millimeter-wave range flying on EUMETSAT and NOAA polar satellites, used operationally for the retrieval of atmospheric parameters in numerical weather prediction and nowcasting. This technique does not require any special operation or maneuver and only relies on the analysis of data from the nominal scanning operation. The coalignment of sounding channels and window channels can be evaluated by this technique, which would not be possible using Earth landmarks, due to the absorption effect of the atmosphere. The analysis reported shows an achievable accuracy below 0.5 mrad against a beam width at 3 dB and spatial sampling interval of about 20 mrad. In-orbit results for the MHS instrument on Metop-B are also compared with the prelaunch instrument characterization, showing a good correlation.

Real-Time Precise Point Positioning (RTPPP) with raw observations and its application in real-time regional ionospheric VTEC modeling

Precise Point Positioning (PPP) is an absolute positioning technology mainly used in post data processing. With the continuously increasing demand for real-time high-precision applications in positioning, timing, retrieval of atmospheric parameters, etc., Real-Time PPP (RTPPP) and its applications have drawn more and more research attention in recent years. This study focuses on the models, algorithms and ionospheric applications of RTPPP on the basis of raw observations, in which high-precision slant ionospheric delays are estimated among others in real time. For this purpose, a robust processing strategy for multi-station RTPPP with raw observations has been proposed and realized, in which real-time data streams and State-Space-Representative (SSR) satellite orbit and clock corrections are used. With the RTPPP-derived slant ionospheric delays from a regional network, a real-time regional ionospheric Vertical Total Electron Content (VTEC) modeling method is proposed based on Adjusted Spherical Harmonic Functions and a Moving-Window Filter. SSR satellite orbit and clock corrections from different IGS analysis centers are evaluated. Ten globally distributed real-time stations are used to evaluate the positioning performances of the proposed RTPPP algorithms in both static and kinematic modes. RMS values of positioning errors in static/kinematic mode are 5.2/15.5, 4.7/17.4 and 12.8/46.6 mm, for north, east and up components, respectively. Real-time slant ionospheric delays from RTPPP are compared with those from the traditional Carrier-to-Code Leveling (CCL) method, in terms of function model, formal precision and between-receiver differences of short baseline. Results show that slant ionospheric delays from RTPPP are more precise and have a much better convergence performance than those from the CCL method in real-time processing. 30 real-time stations from the Asia-Pacific Reference Frame network are used to model the ionospheric VTECs over Australia in real time, with slant ionospheric delays from both RTPPP and CCL methods for comparison. RMS of the VTEC differences between RTPPP/CCL method and CODE final products is 0.91/1.09 TECU, and RMS of the VTEC differences between RTPPP and CCL methods is 0.67 TECU. Slant Total Electron Contents retrieved from different VTEC models are also validated with epoch-differenced Geometry-Free combinations of dual-frequency phase observations, and mean RMS values are 2.14, 2.33 and 2.07 TECU for RTPPP method, CCL method and CODE final products, respectively. This shows the superiority of RTPPP-derived slant ionospheric delays in real-time ionospheric VTEC modeling.

Randomized kernels for large scale Earth observation applications

Current remote sensing applications of bio-geophysical parameter estimation and image classification have to deal with an unprecedented big amount of heterogeneous and complex data sources. New satellite sensors involving a high number of improved time, space and wavelength resolutions give rise to challenging computational problems. Standard physical inversion techniques cannot cope efficiently with this new scenario. Dealing with land cover classification of the new image sources has also turned to be a complex problem requiring large amount of memory and processing time. In order to cope with these problems, statistical learning has greatly helped in the last years to develop statistical retrieval and classification models that can ingest large amounts of Earth observation data. Kernel methods constitute a family of powerful machine learning algorithms, which have found wide use in remote sensing and geosciences. However, kernel methods are still not widely adopted because of the high computational cost when dealing with large scale problems, such as the inversion of radiative transfer models or the classification of high spatial-spectral-temporal resolution data. This paper introduces to the remote sensing community an efficient kernel method for fast statistical retrieval of atmospheric and biophysical parameters and image classification problems. We rely on a recently presented approximation to shift-invariant kernels using projections on random Fourier features. The method proposes an explicit mapping function defined through a set of projections randomly sampled from the Fourier domain. It is proved to approximate the implicit mapping of a kernel function. This allows to deal with large-scale data but taking advantage of kernel methods. The method is simple, computationally very efficient in both memory and processing costs, and easily parallelizable. We show that kernel regression and classification is now possible for datasets with millions of samples. Examples on atmospheric parameter retrieval from hyperspectral infrared sounders like IASI/Metop; large scale emulation and inversion of the familiar PROSAIL radiative transfer model on Sentinel-2 data; and the identification of clouds over landmarks in time series of MSG/Seviri images show the efficiency and effectiveness of the proposed technique.

Land Surface Temperature and Emissivity Separation from Cross-Track Infrared Sounder Data with Atmospheric Reanalysis Data and ISSTES Algorithm

The Cross-track Infrared Sounder (CrIS) is one of the most advanced hyperspectral instruments and has been used for various atmospheric applications such as atmospheric retrievals and weather forecast modeling. However, because of the specific design purpose of CrIS, little attention has been paid to retrieving land surface parameters from CrIS data. To take full advantage of the rich spectral information in CrIS data to improve the land surface retrievals, particularly the acquisition of a continuous Land Surface Emissivity (LSE) spectrum, this paper attempts to simultaneously retrieve a continuous LSE spectrum and the Land Surface Temperature (LST) from CrIS data with the atmospheric reanalysis data and the Iterative Spectrally Smooth Temperature and Emissivity Separation (ISSTES) algorithm. The results show that the accuracy of the retrieved LSEs and LST is comparable with the current land products. The overall differences of the LST and LSE retrievals are approximately 1.3 K and 1.48%, respectively. However, the LSEs in our study can be provided as a continuum spectrum instead of the single-channel values in traditional products. The retrieved LST and LSEs now can be better used to further analyze the surface properties or improve the retrieval of atmospheric parameters.

Retrieving of atmospheric parameters from multi‐GNSS in real time: Validation with water vapor radiometer and numerical weather model

AbstractThe multiconstellation Global Navigation Satellite Systems (GNSS) (e.g., GPS, GLObal NAvigation Satellite System (GLONASS), Galileo, and BeiDou) offers great opportunities for real‐time retrieval of atmospheric parameters for supporting numerical weather prediction nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined to retrieve atmospheric parameters based on the real‐time precise point positioning technique. The atmospheric parameters, retrieved from multi‐GNSS observations of a 180 day period from about 100 globally distributed stations, including zenith total delay, integrated water vapor, horizontal gradient, and slant total delay (STD), are analyzed and evaluated. The water vapor radiometer data and a numerical weather model, the operational analysis of the European Centre for Medium‐Range Weather Forecasts (ECMWF), are used to independently validate the performance of individual GNSS and also demonstrate the benefits of multiconstellation GNSS for real‐time atmospheric monitoring. Our results show that the GLONASS and BeiDou have the potential capability for real‐time atmospheric parameter retrieval for time‐critical meteorological applications as GPS does, and the combination of multi‐GNSS observations can improve the performance of a single‐system solution in meteorological applications with higher accuracy and robustness. The multi‐GNSS processing greatly increases the number of STDs. The mean and standard deviation of STDs between each GNSS and ECMWF exhibit a good stability as function of the elevation angle, the azimuth angle, and time, in general. An obvious latitude dependence is confirmed by a map of station specific mean and standard deviations. Such real‐time atmospheric products, provided by multi‐GNSS processing with higher accuracy, stronger reliability, and better distribution, might be highly valuable for atmospheric sounding systems, especially for nowcasting of extreme weather.

Optical processes for middle atmospheric Doppler lidars: Cabannes scattering and laser-induced resonance fluorescence

The problem of light scattering from a monochromatic laser beam by an ensemble of atmospheric atoms or molecules in thermal equilibrium under ambient wind and temperature is revisited with two emphases. First, the essence of and difference between laser Cabannes scattering (CS) and laser-induced resonance fluorescence (LIF), which permit atmospheric temperature and wind measurements, are simply presented. A classical model is shown to yield the same angular distribution in scattered power for both, a factor of two larger Doppler shift for the former (CS), in the backward direction with the same line-of-sight (LOS) wind, and a dramatic 17 order larger backscattering cross section for the latter (LIF). Second, the LIF process is developed from first principles, and we present the relations between absorption cross section, differential scattering cross sections, and LIF emission spectrum for atoms with hyperfine structure. By doing this, we (1) equate the decoherence rate among the mixed excited substates to half of the Einstein coefficient to comply with energy conservation, and (2) present a clear physical insight into the origin of the Hanle effect, whose quantitative evaluation for these atoms requires quantum mechanical treatment. We then derive LIF emission rates for each of the eight and 10 pathways associated with the D1 and D2 transitions, and deduce the temperature and LOS wind dependence in differential backscattering cross sections of atmospheric sodium and potassium atoms. Using these cross sections allows retrieval of atmospheric parameters in the mesopause region (80–110 km in altitude) by a metal resonance lidar.

Thermal structure of Venus׳ nightside mesosphere as observed by infrared heterodyne spectroscopy at 10 μm

Ground-based heterodyne spectroscopy is used to observe the night side of Venus by probing single pressure broadened CO2 absorption lines. From the pressure induced line broadening, the predominant temperature at different altitude layers can be deduced. It is found, that heterodyne spectroscopy is sensitive to probe the mesosphere between ~60km and 90km with an altitude resolution of ~4.5km.During two observing campaigns in March and May 2012, four different locations on the planet were investigated. Herein, we report on the retrieval of vertical temperature profiles in the nightside atmosphere of Venus. Retrieval of atmospheric parameters is based on a Levenberg–Marquard χ2 optimization that iteratively compares observed data to telluric transmittance corrected Venus׳ top-of-atmosphere spectra calculated using a radiative transfer algorithm. The deduced profiles are compared to the Venus International Reference Atmosphere and some found to be in satisfactory agreement. Sub-Doppler resolution Infrared heterodyne observations can provide temperature measurements that complement existing sub-mm and space based observations.

Diurnal variation in Sahara desert sand emissivity during the dry season from IASI observations

The problem of diurnal variation in surface emissivity over the Sahara Desert during non‐raining days is studied and assessed with observations from the Infrared Atmospheric Sounding Interferometer (IASI). The analysis has been performed over a Sahara Desert dune target area during July 2010. Spinning Enhanced Visible and Infrared Imager observations from the European geostationary platform Meteosat‐9 (Meteorological Satellite 9) have been also used to characterize the target area. Although the amplitude of this daily cycle has been shown to be very small, we argue that suitable nighttime meteorological conditions and the strong contrast of the reststrahlen absorption bands of quartz (8–14 μm) can amplify its effect over the surface spectral emissivity. The retrieval of atmospheric parameters show that, at nighttime, an atmospheric temperature inversion occurs close to the surface yielding a thin boundary layer which acts like a lid, keeping normal convective overturning of the atmosphere from penetrating through the inversion. This mechanism traps water vapor close to the land and drives the direct adsorption of water vapor at the surface during the night. The diurnal variation in emissivity at 8.7 μm has been found to be as large as 0.03 with high values at night and low values during the day. At 10.8 μm and 12 μm, the variation has the same sign as that at 8.7 μm, but with a smaller amplitude, 0.019 and 0.014, respectively. The impact of these diurnal variations on the retrieval of surface temperature and atmospheric parameters has been analyzed.

Effects of spectral resolution and signal-to-noise ratio of hyperspectral sensors on retrieving atmospheric parameters

Space-borne Fourier Transform Infrared (FTIR) spectroscopy has been operationalized to obtain atmospheric parameters. The spectral resolution and signal-to-noise ratio (SNR) of FTIR spectroscopy are its two key parameters. Given fixed costs and technical limitations, one has to choose between less information (low spectral resolution) and low noise (high SNR), or high information and high noise. This study illustrates one important, although not well realized fact: Downgrading from a high to a low spectral resolution measurement cannot achieve the same SNR as the latter. By comparing the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-track Infrared Sounder (CrIS) data at operational mode (low spectral resolution) and at experimental high spectral resolution, it is found that full CrIS resolution is required to accurately detect trace gases in the atmosphere. This study investigated three approaches for spectral data reduction, and compared their effects on the retrieval of atmospheric parameters.

Multispectral information from TANSO-FTS instrument – Part 2: Application to aerosol effect on greenhouse gas retrievals

Abstract. This article is the second in a series of studies investigating the benefits of multispectral measurements to improve the atmospheric parameter retrievals. In the first paper, we presented an information content (IC) analysis from the thermal infrared (TIR) and shortwave infrared (SWIR) bands of Thermal And Near infrared Sensor for carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument dedicated to greenhouse gas retrieval in clear sky conditions. This second paper presents the potential of the spectral synergy from TIR to visible for aerosol characterization, and their impact on the retrieved CO2 and CH4 column concentrations. The IC is then used to determine the most informative spectral channels for the simultaneous retrieval of greenhouse gas total columns and aerosol parameters. The results show that a channel selection spanning the four bands can improve the computation time and retrieval accuracy. Therefore, the spectral synergy allows obtaining up to almost seven different aerosol parameters, which is comparable to the most informative dedicated instruments. Moreover, a channel selection from the TIR to visible bands allows retrieving CO2 and CH4 total columns simultaneously in the presence of one aerosol layer with a similar accuracy to using all channels together to retrieve each gas separately in clear sky conditions.

Infrared Radiation in the Mesosphere and Lower Thermosphere: Energetic Effects and Remote Sensing

This paper discusses the formation mechanisms of infrared radiation in the mesosphere and lower thermosphere (MLT), the energetic effects of the radiative absorption/emission processes, and the retrieval of atmospheric parameters from infrared radiation measurements. In the MLT and above, the vibrational levels of the molecules involved in radiative transitions are not in local thermodynamic equilibrium (LTE) with the surrounding medium, and this then requires specific theoretical treatment. The non-LTE models for CO2, O3, and H2O molecules are presented, and the radiative cooling/heating rates estimated for five typical atmospheric scenarios, from polar winter to polar summer, are shown. An optimization strategy for calculating the cooling/heating rates in general circulation models is proposed, and its accuracy is estimated for CO2. The sensitivity of the atmospheric quantities retrieved from infrared observations made from satellites to the non-LTE model parameters is shown.

MIPAS-STR measurements in the Arctic UTLS in winter/spring 2010: instrument characterization, retrieval and validation

Abstract. The mid-infrared FTIR-limb-sounder Michelson Interferometer for Passive Atmospheric Sounding–STRatospheric aircraft (MIPAS-STR) was deployed onboard the research aircraft M55 Geophysica during the RECONCILE campaign (Reconciliation of Essential Process Parameters for an Enhanced Predictability of Arctic Stratospheric Ozone Loss and its Climate Interactions) in the Arctic winter/spring 2010. From the MIPAS-STR measurements, vertical profiles and 2-dimensional vertical cross-sections of temperature and trace gases are retrieved. Detailed mesoscale structures of polar vortex air, extra vortex air and vortex filaments are identified in the results at typical vertical resolutions of 1 to 2 km and typical horizontal sampling densities of 45 or 25 km, depending on the sampling programme. Results are shown for the RECONCILE flight 11 on 2 March 2010 and are validated with collocated in-situ measurements of temperature, O3, CFC-11, CFC-12 and H2O. Exceptional agreement is found for the in-situ comparisons of temperature and O3, with mean differences (vertical profile/along flight track) of 0.2/−0.2 K for temperature and −0.01/0.05 ppmv for O3 and corresponding sample standard deviations of the mean differences of 0.7/0.6 K and 0.1/0.3 ppmv. The comparison of the retrieved vertical cross-sections of HNO3 from MIPAS-STR and the infrared limb-sounder Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere–New Frontiers (CRISTA–NF) indicates a high degree of agreement. We discuss MIPAS-STR in its current configuration, the spectral and radiometric calibration of the measurements and the retrieval of atmospheric parameters from the spectra. The MIPAS-STR measurements are significantly affected by continuum-like contributions, which are attributed to background aerosol and broad spectral signatures from interfering trace gases, and are important for mid-infrared limb-sounding in the Upper Troposphere/Lower Stratosphere (UTLS) region. Taking into consideration continuum-like effects, we present a scheme suitable for accurate retrievals of temperature and an extended set of trace gases, including the correction of a systematic line-of-sight offset.

Sunglint impact on atmospheric soundings from hyperspectral resolution infrared radiances

The mid-wave infrared band (3–5 µm) has been widely used for atmospheric soundings. The sunglint impact on the atmospheric parameter retrieval using this band has been neglected because the reflected radiances in this band are significantly less than those in the visible band. In this study, an investigation of sunglint impact on the atmospheric soundings was conducted with Atmospheric InfraRed Sounder observation data from 1 July to 7 July 2007 over the Atlantic Ocean. The impact of sunglint can lead to a brightness temperature increase of 1.0 K for the surface sensitive sounding channels near 4.58 µm. This contamination can indirectly cause a positive bias of 4 g kg−1 in the water vapor retrieval near the ocean surface, and it can be corrected by simply excluding those contaminated channels.

Interferometric vs Spectral IASI Radiances: Effective Data-Reduction Approaches for the Satellite Sounding of Atmospheric Thermodynamical Parameters

Abstract: Two data-reduction approaches for the Infrared Atmospheric Sounder Interferometer satellite instrument are discussed and compared. The approaches are intended for the purpose of devising and implementing fast near real time retrievals of atmospheric thermodynamical parameters. One approach is based on the usual selection of sparse channels or portions of the spectrum. This approach may preserve the spectral resolution, but at the expense of the spectral coverage. The second approach considers a suitable truncation of the interferogram (the Fourier transform of the spectrum) at points below the nominal maximum optical path difference. This second approach is consistent with the Shannon-Whittaker sampling theorem, preserves the full spectral coverage, but at the expense of the spectral resolution. While the first data-reduction acts within the spectraldomain, the second can be performed within the interferogram domain and without any specific need to go back to the spectral domain for the purpose of retrieval. To assess the impact of these two different data-reduction strategies on retrieval of atmospheric parameters, we have used a statistical retrieval algorithm for skin temperature, temperature, water vapour and ozone profiles. The use of this retrieval algorithm is mostly intended for illustrative purposes and the user could choose a different inverse strategy. In fact, the interferogram-based data-reduction strategy is generic and independent of any inverse algorithm. It will be also shown that this strategy yields subset of interferometric radiances, which are less sensitive to potential interfering effects such as those possibly introduced by the day-night cycle (e.g., the solar component, and spectroscopic effect induced by sun energy) and unknown trace gases variability.

Simulation of Echo‐Photon Counts of a Sodium Doppler Lidar and Retrievals of Atmospheric Parameters

AbstractThe atmospheric winds and temperatures can be retrieved with the received resonance fluorescence scattering echo photons from Na atoms as a trace in the mesopause region. In this paper, the lidar principle and the retrieval method of atmospheric parameters are presented. The background temperature and density of the atmosphere is determined by the atmospheric model MSISE, the background wind is given by the HWM93 model, and the Na number density profile of the sodium layer is given with a Gaussian model. Then the lidar echo‐photon counts is simulated by using the lidar equations of Rayleigh scattering and sodium resonance fluorescence scattering. The retrieved winds and temperatures agree well with the background winds and temperatures, which shows that the retrieval method is reliable. The effects of laser frequency bias and variations of the laser linewidth on the accuracy of retrieval results are analyzed.

On the application of the MODTRAN4 atmospheric radiative transfer code to optical remote sensing

The quantification of atmospheric effects on the solar radiation measured by a spaceborne or airborne optical sensor is required for some key tasks in remote sensing, such as atmospheric correction, simulation of realistic scenarios or retrieval of atmospheric parameters. The MODTRAN4 code is an example of state‐of‐the‐art atmospheric radiative transfer code, as it provides very accurate calculations by means of a rigorous mathematical formulation and a very fine spectral resolution. However, the application of MODTRAN4 to remote sensing is not straightforward for the average user for a number of reasons: the provided output parameters do not exactly correspond to those necessary for the construction of the at‐sensor signal by combination with the surface reflectance, an advanced knowledge of radiative transfer theory and atmospheric physics is needed for the understanding of the input parameters and all their possible combinations, and the computation time may be too high for many practical applications. This work is intended to give explicit solutions to those problems. MODTRAN4 has been modified so that the proper atmospheric parameters are calculated and delivered as output. In addition, the most important execution options are investigated, and the compromise between accuracy and computation time is analysed. The performance of the proposed methodology is demonstrated by generating a look‐up table (LUT) enabling fast but accurate radiative transfer calculations for the atmospheric correction of data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) on board the Project for On‐Board Autonomy (PROBA).

SWAS observations of water vapor in the Venus mesosphere

We present the first detections of the ground-state H 2 16O ( 1 10 – 1 01 ) rotational transition (at 556.9 GHz) and the 13CO (5–4) rotational transition from the atmosphere of Venus, measured with the Submillimeter Wave Astronomy Satellite (SWAS). The observed spectral features of these submillimeter transitions originate primarily from the 70–100 km altitude range, within the Venus mesosphere. Observations were obtained in December 2002, and January, March, and July 2004, coarsely sampling one Venus diurnal period as seen from Earth. The measured water vapor absorption line depth shows large variability among the four observing periods, with strong detections of the line in December 2002 and July 2004, and no detections in January and March 2004. Retrieval of atmospheric parameters was performed using a multi-transition inversion algorithm, combining simultaneous retrievals of temperature, carbon monoxide, and water profiles under imposed constraints. Analysis of the SWAS spectra resulted in measurements or upper limits for the globally averaged mesospheric water vapor abundance for each of the four observation periods, finding variability over at least two orders of magnitude. The results are consistent with both temporal and diurnal variability, but with short-term fluctuations clearly dominating. These results are fully consistent with the long-term study of mesospheric water vapor from millimeter and submillimeter observations of HDO [Sandor, B.J., Clancy, R.T., 2005. Icarus 177, 129–143]. The December 2002 observations detected very rapid change in the mesospheric water abundance. Over five days, a deep water absorption feature consistent with a water vapor abundance of 4.5 ± 1.5 parts per million suddenly gave way to a significantly shallower absorption, implying a decrease in the water vapor abundance by a factor of nearly 50 in less that 48 h. In 2004, similar changes in the water vapor abundance were measured between the March and July SWAS observing periods, but variability on time scales of less than a week was not detected. The mesospheric water vapor is expected to be in equilibrium with aerosol particles, primarily composed of concentrated sulfuric acid, in the upper haze layers of the Venus atmosphere. If true, moderate amplitude (10–15 K) variability in mesospheric temperature, previously noted in millimeter spectroscopy observations of Venus, can explain the rapid water vapor variability detected by SWAS.

TES level 1 algorithms: interferogram processing, geolocation, radiometric, and spectral calibration

The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite measures the infrared radiance emitted by the Earth's surface and atmosphere using Fourier transform spectrometry. The measured interferograms are converted into geolocated, calibrated radiance spectra by the L1 (Level 1) processing, and are the inputs to L2 (Level 2) retrievals of atmospheric parameters, such as vertical profiles of trace gas abundance. We describe the algorithmic components of TES Level 1 processing, giving examples of the intermediate results and diagnostics that are necessary for creating TES L1 products. An assessment of noise-equivalent spectral radiance levels and current systematic errors is provided. As an initial validation of our spectral radiances, TES data are compared to the Atmospheric Infrared Sounder (AIRS) (on EOS Aqua), after accounting for spectral resolution differences by applying the AIRS spectral response function to the TES spectra. For the TES L1 nadir data products currently available, the agreement with AIRS is 1 K or better.

Error analysis for GNSS radio occultation data based on ensembles of profiles from end‐to‐end simulations

Radio occultation (RO) observations using the Global Navigation Satellite System (GNSS) globally provide high quality atmospheric data which can support the advancement of climate monitoring and modeling as well as the improvement of numerical weather prediction. In order to make optimal use of the data, e.g., via data assimilation systems, the characterization of measurement errors is of importance. Within this context we present results of an empirical error analysis based on quasi‐realistically simulated GNSS RO data. The study is based on an end‐to‐end forward‐inverse simulation involving (1) modeling of the neutral atmosphere and ionosphere, (2) simulation of RO observations, (3) forward modeling of excess phase observables including realistic observation system error modeling, and (4) retrieval of atmospheric parameters. Occultation observations were simulated for one day from which an ensemble of 300 occultation events was chosen, with 100 events in each of three latitude bands (low, middle, high). Phase path profiles were computed showing a realistic rms error of the ionosphere corrected phase paths of 2–3 mm at mesospheric and stratospheric heights at 10 Hz sampling rate. Atmospheric profiles were retrieved by applying a dry air retrieval in the stratosphere and an optimal estimation retrieval in the troposphere. The retrieved profiles were referenced to the “true” co‐located ones of the analysis field of the European Centre for Medium‐range Weather Forecasts (ECMWF). We empirically estimated bias profiles and covariance matrices (standard deviations and correlation functions) for the retrieval products such as bending angle, refractivity, pressure, geopotential height, temperature, and specific humidity. Results include the refractivity error showing a relative standard deviation of 0.1–0.75% and a relative bias of <0.1% at 5–40 km height. Temperature exhibits a standard deviation of 0.2–1 K at 3–31 km height and a bias of <0.1–0.5 K below 33 km and of <0.1 K below 20 km. Simple analytical error covariance formulations are presented for refractivity, as deduced from the empirically estimated covariance matrices. The reasonably realistic error estimates presented are a good basis for further retrieval algorithm improvements and for proper specification of observational errors in data assimilation systems.

Effects of a Spectral Surface Reflectance on Measurements of Backscattered Solar Radiation: Application to the MOPITT Methane Retrieval

Abstract The amount of solar radiation emerging from the top of the atmosphere is strongly influenced by the reflectance of the underlying surface. For this reason, some information about the magnitude and the spectral variability of the surface reflectance typically has to be included in the retrieval of atmospheric parameters from reflected solar radiation measurements. Sufficient information about the surface reflectance properties is rarely available, and the integration of this effect in the retrieval might turn out to be a challenge, especially for broadband instruments. In this paper the focus is on the Measurements of Pollution in the Troposphere (MOPITT) remote sensing instrument. Theoretical studies are performed to investigate how a spectrally varying surface reflectance might impact the retrieval of the total column amount of methane from MOPITT radiance measurements, and the current findings are compared to observed biases. However, the findings present herein might be valuable and applicable for other remote sensing instruments that are sensitive to the amount of solar radiation reflected from the earth’s surface.