scholarly journals Improved OSIRIS NO<sub>2</sub> retrieval algorithm: description and validation

2017 ◽  
Vol 10 (3) ◽  
pp. 1155-1168 ◽  
Author(s):  
Christopher E. Sioris ◽  
Landon A. Rieger ◽  
Nicholas D. Lloyd ◽  
Adam E. Bourassa ◽  
Chris Z. Roth ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Polar Vortex ◽  
Bias Reduction ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Reconstruction Technique ◽  
Spectral Fitting ◽  
Infrared Imager ◽  
First Time

Abstract. A new retrieval algorithm for OSIRIS (Optical Spectrograph and Infrared Imager System) nitrogen dioxide (NO2) profiles is described and validated. The algorithm relies on spectral fitting to obtain slant column densities of NO2, followed by inversion using an algebraic reconstruction technique and the SaskTran spherical radiative transfer model (RTM) to obtain vertical profiles of local number density. The validation covers different latitudes (tropical to polar), years (2002–2012), all seasons (winter, spring, summer, and autumn), different concentrations of nitrogen dioxide (from denoxified polar vortex to polar summer), a range of solar zenith angles (68.6–90.5°), and altitudes between 10.5 and 39 km, thereby covering the full retrieval range of a typical OSIRIS NO2 profile. The use of a larger spectral fitting window than used in previous retrievals reduces retrieval uncertainties and the scatter in the retrieved profiles due to noisy radiances. Improvements are also demonstrated through the validation in terms of bias reduction at 15–17 km relative to the OSIRIS operational v3.0 algorithm. The diurnal variation of NO2 along the line of sight is included in a fully spherical multiple scattering RTM for the first time. Using this forward model with built-in photochemistry, the scatter of the differences relative to the correlative balloon NO2 profile data is reduced.

scholarly journals Improved OSIRIS NO<sub>2</sub> retrieval algorithm: Description and validation

2016 ◽  
Author(s):  
Christopher E. Sioris ◽  
Landon A. Rieger ◽  
Nicholas D. Lloyd ◽  
Adam E. Bourassa ◽  
Chris Z. Roth ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Nitrogen Dioxide ◽  
Polar Vortex ◽  
Bias Reduction ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Reconstruction Technique ◽  
Spectral Fitting ◽  
Infrared Imager

Abstract. A new retrieval algorithm for OSIRIS (Optical Spectrograph and Infrared Imager System) nitrogen dioxide (NO2) profiles is described and validated. The algorithm relies on spectral fitting to obtain line-of-sight (LOS) column densities of NO2 followed by inversion using an algebraic reconstruction technique and the SaskTran spherical radiative transfer model to obtain vertical profiles of local number density. The validation covers different latitudes (tropical to polar), years (2002–2012), all seasons (winter, spring, summer, and autumn), different concentrations of nitrogen dioxide (from deNOxified polar vortex to polar summer), a large range of solar zenith angles (68.6 to 90.5°) and altitudes between 10.5 and 39 km, thereby covering the full retrieval range of a typical OSIRIS NO2 profile. The use of a larger spectral fitting window than used in previous retrievals reduces retrieval uncertainties and the scatter in the retrieved profiles due to noisy radiances. Improvements are also demonstrated through the validation in terms of bias reduction at 15–17 km relative to the OSIRIS operational v3.0 algorithm. By accounting for the diurnal variation along the LOS in the two-dimensional radiative transfer model, the scatter of the differences relative to the correlative balloon NO2 profile data is reduced.

scholarly journals Odin/OSIRIS observations of stratospheric NO<sub>3</sub> through sunrise and sunset

2008 ◽  
Vol 8 (2) ◽  
pp. 5901-5917
Author(s):  
C. A. McLinden ◽  
C. S. Haley
Keyword(s):  
Radiative Transfer ◽  
Strong Dependence ◽  
Rapid Evolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Nitrate Radical ◽  
Signal To Noise ◽  
Spectral Fitting ◽  
Infrared Imager ◽  
Fitting In

Abstract. The nitrate radical (NO3) has been detected in visible limb-scattered spectra measured by the Optical Spectrograph and InfraRed Imager System (OSIRIS) on-board the Odin satellite when observing at large solar zenith angles (91–97°). Apparent slant column densities of NO3 at tangent heights between 10 and 45 km are derived via spectral fitting in the 590–680 nm window. Using observations from multiple scans spanning solar zenith angles of 91–97°, the rapid evolution of NO3 through sunrise and sunset can be traced. Slant column densities are found to be consistent with those simulated using a radiative transfer model with coupled photochemistry. In addition, a strong dependence of NO3 with temperature is observed. These results indicate that OSIRIS possesses signal-to-noise sufficient to make useful measurements of scattered sunlight out to solar zenith angles of 96–97° and suggests the possibility of retrieving profile information for NO3 and other species at large solar zenith angles.

scholarly journals Odin/OSIRIS observations of stratospheric NO<sub>3</sub> through sunrise and sunset

2008 ◽  
Vol 8 (18) ◽  
pp. 5529-5534 ◽  
Author(s):  
C. A. McLinden ◽  
C. S. Haley
Keyword(s):  
Radiative Transfer ◽  
Current Knowledge ◽  
Strong Dependence ◽  
Rapid Evolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Spectral Fitting ◽  
Infrared Imager ◽  
Fitting In ◽  
Radiative Transfer Modeling

Abstract. The nitrate radical (NO3) has been detected in visible limb-scattered spectra measured by the Optical Spectrograph and InfraRed Imager System (OSIRIS) on-board the Odin satellite when observing at large solar zenith angles (91–97°). Apparent slant column densities of NO3 at tangent heights between 10 and 45 km are derived via spectral fitting in the 610–680 nm window. Using observations from multiple scans spanning solar zenith angles of 91–97°, the rapid evolution of NO3 through sunrise and sunset can be traced. Slant column densities are found to be generally consistent with those simulated using a radiative transfer model with coupled photochemistry. In addition, a strong dependence of NO3 with temperature is observed. These results indicate that our current knowledge of NO3 photochemistry is generally consistent with OSIRIS observations to within the limitations of the radiative transfer modeling. Furthermore, they reveal that OSIRIS possesses signal-to-noise sufficient to make useful measurements of scattered sunlight out to solar zenith angles of 91–97° and suggest the possibility of retrieving profile information for NO3 and other species at large solar zenith angles.

scholarly journals Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

2020 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Lucie Leonarski ◽  
Laurent C.-Labonnote ◽  
Mathieu Compiègne ◽  
Jérôme Vidot ◽  
Anthony J. Baran ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Signal To Noise Ratio ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Water Path ◽  
Ice Cloud ◽  
Ice Water Path ◽  
Ice Water

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

scholarly journals Differences in ozone retrieval in MIPAS channels A and AB: a spectroscopic issue

2018 ◽  
Vol 11 (8) ◽  
pp. 4707-4723 ◽  
Author(s):  
Norbert Glatthor ◽  
Thomas von Clarmann ◽  
Gabriele P. Stiller ◽  
Michael Kiefer ◽  
Alexandra Laeng ◽  
...  
Keyword(s):  
Spectroscopic Data ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Forward Modelling ◽  
Hitran Database ◽  
Processing Scheme ◽  
Mixing Ratios ◽  
Level 1 ◽  
Standing Problem

Abstract. Discrepancies in ozone retrievals in MIPAS channels A (685–970 cm−1) and AB (1020–1170 cm−1) have been a long-standing problem in MIPAS data analysis, amounting to an interchannel bias (AB–A) of up to 8 % between ozone volume mixing ratios in the altitude range 30–40 km. We discuss various candidate explanations, among them forward model and retrieval algorithm errors, interchannel calibration inconsistencies and spectroscopic data inconsistencies. We show that forward-modelling errors as well as errors in the retrieval algorithm can be ruled out as an explanation because the bias can be reproduced with an entirely independent retrieval algorithm (GEOFIT), relying on a different forward radiative transfer model. Instrumental and calibration issues can also be refuted as an explanation because ozone retrievals based on balloon-borne measurements with a different instrument (MIPAS-B) and an independent level-1 data processing scheme produce a rather similar interchannel bias. Thus, spectroscopic inconsistencies in the MIPAS database used for ozone retrieval are practically the only reason left. To further investigate this issue, we performed retrievals using additional spectroscopic databases. Various versions of the HITRAN database generally produced rather similar channel AB–A differences. Use of a different database, namely GEISA-2015, led to similar results in channel AB, but to even higher ozone volume mixing ratios for channel A retrievals, i.e. to a reversal of the bias. We show that the differences in MIPAS channel A retrievals result from about 13 % lower air-broadening coefficients of the strongest lines in the GEISA-2015 database. Since the errors in line intensity of the major lines used in MIPAS channels A and AB are reported to be considerably lower than the observed bias, we posit that a major part of the channel AB–A differences can be attributed to inconsistent air-broadening coefficients as well. To corroborate this assumption we show some clearly inconsistent air-broadening coefficients in the HITRAN-2008 database. The interchannel bias in retrieved ozone amounts can be reduced by increasing the air-broadening coefficients of the lines in MIPAS channel AB in the HITRAN-2008 database by 6 %–8 %.

scholarly journals Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

2015 ◽  
Vol 12 (12) ◽  
pp. 13019-13067
Author(s):  
A. Barella-Ortiz ◽  
J. Polcher ◽  
P. de Rosnay ◽  
M. Piles ◽  
E. Gelati
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Function Analysis ◽  
Microwave Emission ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Brightness Temperatures

Abstract. L-Band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm. The work exposed compares brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The latter were estimated using a radiative transfer model and state variables from two land surface models: (i) ORganising Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and (ii) Hydrology – Tiled ECMWF Scheme for Surface Exchanges over Land (H-TESSEL). The radiative transfer model used is the Community Microwave Emission Model (CMEM). A good agreement in the temporal evolution of measured and modelled brightness temperatures is observed. However, their spatial structures are not consistent between them. An Empirical Orthogonal Function analysis of the brightness temperature's error identifies a dominant structure over the South-West of the Iberian Peninsula which evolves during the year and is maximum in Fall and Winter. Hypotheses concerning forcing induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for it at the moment. Further hypotheses are proposed at the end of the paper.

scholarly journals Gauss–Seidel limb scattering (GSLS) radiative transfer model development in support of the Ozone Mapping and Profiler Suite (OMPS) limb profiler mission

2015 ◽  
Vol 15 (6) ◽  
pp. 3007-3020 ◽  
Author(s):  
R. Loughman ◽  
D. Flittner ◽  
E. Nyaku ◽  
P. K. Bhartia
Keyword(s):  
Radiative Transfer ◽  
Model Development ◽  
Model Atmosphere ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Process Data ◽  
Variable Surface ◽  
Height Dependence ◽  
Minimal Effort

Abstract. The Gauss–Seidel limb scattering (GSLS) radiative transfer (RT) model simulates the transfer of solar radiation through the atmosphere and is imbedded in the retrieval algorithm used to process data from the Ozone Mapping and Profiler Suite (OMPS) limb profiler (LP), which was launched on the Suomi NPP satellite in October 2011. A previous version of this model has been compared with several other limb scattering RT models in previous studies, including Siro, MCC++, CDIPI, LIMBTRAN, SASKTRAN, VECTOR, and McSCIA. To address deficiencies in the GSLS radiance calculations revealed in earlier comparisons, several recent changes have been added that improve the accuracy and flexibility of the GSLS model, including 1. improved treatment of the variation of the extinction coefficient with altitude, both within atmospheric layers and above the nominal top of the atmosphere; 2. addition of multiple-scattering source function calculations at multiple solar zenith angles along the line of sight (LOS); 3. introduction of variable surface properties along the limb LOS, with minimal effort required to add variable atmospheric properties along the LOS as well; 4. addition of the ability to model multiple aerosol types within the model atmosphere. The model improvements 1 and 2 are verified by comparison to previously published results (using standard radiance tables whenever possible), demonstrating significant improvement in cases for which previous versions of the GSLS model performed poorly. The single-scattered radiance errors that were as high as 4% in earlier studies are now generally reduced to 0.3%, while total radiance errors generally decline from 10% to 1–3%. In all cases, the tangent height dependence of the GSLS radiance error is greatly reduced.

scholarly journals Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1225
Author(s):  
Lanka Karthikeyan ◽  
Ming Pan ◽  
Dasika Nagesh Kumar ◽  
Eric F. Wood
Keyword(s):  
Soil Moisture ◽  
Global Scale ◽  
Passive Microwave ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Structural Uncertainty ◽  
Three Solutions ◽  
Brightness Temperatures ◽  
Retrieval Algorithms

Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that is inherent in all τ-ω types of models in passive microwave SM retrieval algorithms. In the process, a new analytical solution for concurrent VOD and SM retrieval is presented, along with two widely used existing analytical solutions. All three solutions are applied to a fixed framework of RTM to retrieve VOD and SM on a global scale, using X-band Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) TB data. Results indicate that, with structural uncertainty, there ensues a noticeable impact on the VOD and SM retrievals. In an era where the sensitivity of retrieval algorithms is still being researched, we believe the structural indeterminacy of RTM identified here would contribute to uncertainty in the soil moisture retrievals.

scholarly journals Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

2016 ◽  
Vol 9 (6) ◽  
pp. 2647-2668 ◽  
Author(s):  
Caroline R. Nowlan ◽  
Xiong Liu ◽  
James W. Leitch ◽  
Kelly Chance ◽  
Gonzalo González Abad ◽  
...  
Keyword(s):  
Air Quality ◽  
Near Infrared ◽  
Infrared Light ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Test Bed ◽  
Mixing Ratios ◽  
Sensor Optimization

Abstract. The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m  ×  250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

scholarly journals The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm: theoretical basis

2018 ◽  
Vol 11 (5) ◽  
pp. 2633-2651 ◽  
Author(s):  
Robert Loughman ◽  
Pawan K. Bhartia ◽  
Zhong Chen ◽  
Philippe Xu ◽  
Ernest Nyaku ◽  
...  
Keyword(s):  
Spherical Shell ◽  
Theoretical Basis ◽  
Relaxation Method ◽  
Radiative Transfer Model ◽  
Aerosol Size Distribution ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Extinction ◽  
Horizontal Variations

Abstract. The theoretical basis of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm is presented. The algorithm uses an assumed bimodal lognormal aerosol size distribution to retrieve aerosol extinction profiles at 675 nm from OMPS LP radiance measurements. A first-guess aerosol extinction profile is updated by iteration using the Chahine nonlinear relaxation method, based on comparisons between the measured radiance profile at 675 nm and the radiance profile calculated by the Gauss–Seidel limb-scattering (GSLS) radiative transfer model for a spherical-shell atmosphere. This algorithm is discussed in the context of previous limb-scattering aerosol extinction retrieval algorithms, and the most significant error sources are enumerated. The retrieval algorithm is limited primarily by uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction, which violate the spherical-shell atmosphere assumed in the version 1 algorithm, may also limit the quality of the retrieved aerosol extinction profiles significantly.

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