scholarly journals Measuring atmospheric CO<sub>2</sub> from space using Full Spectral Initiation (FSI) WFM-DOAS

2006 ◽  
Vol 6 (11) ◽  
pp. 3517-3534 ◽  
Author(s):  
M. P. Barkley ◽  
U. Frieß ◽  
P. S. Monks
Keyword(s):  
Near Infrared ◽  
Weighting Function ◽  
A Priori ◽  
Measurement Techniques ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Reference Spectrum ◽  
Retrieval Technique ◽  
Priori Information ◽  
Atmospheric Co2 Concentrations

Abstract. Satellite measurements of atmospheric CO2 concentrations are a rapidly evolving area of scientific research which can help reduce the uncertainties in the global carbon cycle fluxes and provide insight into surface sources and sinks. One of the emerging CO2 measurement techniques is a relatively new retrieval algorithm called Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) that has been developed by Buchwitz et al. (2000). This algorithm is designed to measure the total columns of CO2 (and other greenhouse gases) through the application to spectral measurements in the near infrared (NIR), made by the SCIAMACHY instrument on-board ENVISAT. The algorithm itself is based on fitting the logarithm of a model reference spectrum and its derivatives to the logarithm of the ratio of a measured nadir radiance and solar irradiance spectrum. In this work, a detailed error assessment of this technique has been conducted and it has been found necessary to include suitable a priori information within the retrieval in order to minimize the errors on the retrieved CO2 columns. Hence, a more flexible implementation of the retrieval technique, called Full Spectral Initiation (FSI) WFM-DOAS, has been developed which generates a reference spectrum for each individual SCIAMACHY observation using the estimated properties of the atmosphere and surface at the time of the measurement. Initial retrievals over Siberia during the summer of 2003 show that the measured CO2 columns are not biased from the input a priori data and that whilst the monthly averaged CO2 distributions contain a high degree of variability, they also contain interesting spatial features.

scholarly journals Measuring atmospheric CO<sub>2</sub> from space using Full Spectral Initiation (FSI) WFM-DOAS

2006 ◽  
Vol 6 (2) ◽  
pp. 2765-2807 ◽  
Author(s):  
M. P. Barkley ◽  
U. Frieß ◽  
P. S. Monks
Keyword(s):  
Near Infrared ◽  
Weighting Function ◽  
A Priori ◽  
Measurement Techniques ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Reference Spectrum ◽  
Priori Information ◽  
Atmospheric Co2 Concentrations ◽  
High Degree

Abstract. Satellite measurements of atmospheric CO2 concentrations are a rapidly evolving area of scientific research which can help reduce the uncertainties in the global carbon cycle fluxes and provide insight into surface sources and sinks. One of the emerging CO2 measurement techniques is a relatively new retrieval algorithm called Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) that has been developed by Buchwitz et al. (2000). This algorithm is designed to measure the total columns of CO2 (and other greenhouse gases) through the application to spectral measurements in the near infrared (NIR), made by the SCIAMACHY instrument on-board ENVISAT. The algorithm itself is based on fitting the logarithm of a model reference spectrum and its derivatives to the logarithm of the ratio of a measured nadir radiance and solar irradiance spectrum. In this work, a detailed error assessment of this technique has been conducted and it has been found necessary to include suitable a priori information within the retrieval in order to minimize the errors on the retrieved CO2 columns. Hence, a new CO2 retrieval algorithm called Full Spectral Initiation (FSI) WFM-DOAS has been developed which generates a reference spectrum for each individual SCIAMACHY observation using the known properties of the atmosphere and surface at the time of the measurement. Initial retrievals over Siberia during the summer of 2003 show that the measured CO2 columns are not biased from the input a priori data and that whilst the monthly averaged CO2 distributions contain a high degree of variability, they also contain significant spatial features.

scholarly journals Comparisons between SCIAMACHY atmospheric CO<sub>2</sub> retrieved using (FSI) WFM-DOAS to ground based FTIR data and the TM3 chemistry transport model

2006 ◽  
Vol 6 (3) ◽  
pp. 5387-5425 ◽  
Author(s):  
M. P. Barkley ◽  
P. S. Monks ◽  
U. Frieß ◽  
R. L. Mittermeier ◽  
H. Fast ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Weighting Function ◽  
Unknown Origin ◽  
Optical Absorption Spectroscopy ◽  
Vertical Column ◽  
Chemistry Transport Model ◽  
Relative Scatter ◽  
Atmospheric Co2 Concentrations ◽  
Good Agreement

Abstract. Atmospheric CO2 concentrations, retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using Full Spectral Initiation Weighting Function Modified Differential Optical Absorption Spectroscopy (FSI WFM-DOAS), are compared to ground based Fourier Transform Infrared (FTIR) data and to the output from a global chemistry-transport model. Analysis of the FSI WFM-DOAS retrievals with respect to the ground based FTIR instrument, located at Egbert, Canada, show good agreement with an average negative bias of approximately −4.0% with a standard deviation of ~3.0%. This bias which exhibits an apparent seasonal trend, is of unknown origin, though slight differences between the averaging kernels of the instruments and the limited temporal coverage of the FTIR data may be the cause. The relative scatter of the retrieved vertical column densities is comparable to the spread of the FTIR measurements themselves. Normalizing the CO2 columns using the surface pressure does not affect the magnitude of this bias although it slightly increases the scatter of the FSI data. Comparisons of the FSI retrievals to the TM3 global chemistry-transport model, performed over four selected Northern Hemisphere scenes show good agreement. The correlation, between the time series of the SCIAMACHY and model monthly scene averages, are ~0.7 or greater, demonstrating the ability of SCIAMACHY to detect seasonal changes in the CO2 distribution. The amplitude of the seasonal cycle, peak to peak, observed by SCIAMACHY however, is overestimated by a factor of 2–3, which cannot be explained. The yearly means detected by SCIAMACHY are within 2% of those of the model with the mean difference between the CO2 distributions also approximately 2.0%. Additionally, analysis of the retrieved CO2 distributions reveals structure not evident in the model fields which correlates well with land classification type. From these comparisons, the overall precision and bias of the CO2 columns retrieved by the FSI algorithm are estimated to be close to 1.0% and <4.0% respectively.

scholarly journals Comparisons between SCIAMACHY atmospheric CO<sub>2</sub> retrieved using (FSI) WFM-DOAS to ground based FTIR data and the TM3 chemistry transport model

2006 ◽  
Vol 6 (12) ◽  
pp. 4483-4498 ◽  
Author(s):  
M. P. Barkley ◽  
P. S. Monks ◽  
U. Frieß ◽  
R. L. Mittermeier ◽  
H. Fast ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
Weighting Function ◽  
Unknown Origin ◽  
Optical Absorption Spectroscopy ◽  
Spectral Measurements ◽  
Vertical Column ◽  
Chemistry Transport Model ◽  
Relative Scatter ◽  
Atmospheric Co2 Concentrations

Abstract. Atmospheric CO2 concentrations, retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using Full Spectral Initiation Weighting Function Modified Differential Optical Absorption Spectroscopy (FSI WFM-DOAS), are compared to ground based Fourier Transform Infrared (FTIR) data and to the output from a global chemistry-transport model. Analysis of the FSI WFM-DOAS retrievals with respect to the ground based FTIR instrument, located at Egbert, Canada, show good agreement with an average negative bias of approximately −4.0% with a standard deviation of  3.0%. This bias which exhibits an apparent seasonal trend, is of unknown origin, though slight differences between the averaging kernels of the instruments and the limited temporal coverage of the FTIR data may be the cause. The relative scatter of the retrieved vertical column densities is larger than the spread of the FTIR measurements. Normalizing the CO2 columns using the surface pressure does not affect the magnitude of this bias although it slightly decreases the scatter of the FSI data. Comparisons of the FSI retrievals to the TM3 global chemistry-transport model, performed over four selected Northern Hemisphere scenes show reasonable agreement. The correlation, between the time series of the SCIAMACHY and model monthly scene averages, are  0.7 or greater, demonstrating the ability of SCIAMACHY to detect seasonal changes in the CO2 distribution. The amplitude of the seasonal cycle, peak to peak, observed by SCIAMACHY however, is larger by a factor of 2–3 with respect to the model, which cannot be explained. The yearly means detected by SCIAMACHY are within 2% of those of the model with the mean difference between the CO2 distributions also approximately 2.0%. Additionally, analysis of the retrieved CO2 distributions reveals structure not evident in the model fields which correlates well with land classification type. From these comparisons, it is estimated that the overall bias of the CO2 columns retrieved by the FSI algorithm is <4.0% with the precision of monthly 1°×1° gridded data close to 1.0%.

scholarly journals Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms; validation against collocated MODIS and CALIOP data

2015 ◽  
Vol 8 (12) ◽  
pp. 12663-12707 ◽  
Author(s):  
T. E. Taylor ◽  
C. W. O'Dell ◽  
C. Frankenberg ◽  
P. Partain ◽  
H. Q. Cronk ◽  
...  
Keyword(s):  
Surface Pressure ◽  
Near Infrared ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Screening Methods ◽  
Data Set ◽  
Atmospheric Scattering ◽  
Carbon Dioxide Co2 ◽  
Cloud Screening

Abstract. The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols within the instrument's field of view (FOV). Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 μm O2 A-band, neglecting scattering by clouds and aerosols, which introduce photon path-length (PPL) differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 μm (weak CO2 band) and 2.06 μm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which key off of different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning to allow throughputs of &amp;simeq; 30 %, agreement between the OCO-2 and MODIS cloud screening methods is found to be &amp;simeq; 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April–May) for OCO-2 nadir-land, glint-land and glint-water observations. No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

scholarly journals Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis

2017 ◽  
Vol 10 (1) ◽  
pp. 119-153 ◽  
Author(s):  
Nicolas Theys ◽  
Isabelle De Smedt ◽  
Huan Yu ◽  
Thomas Danckaert ◽  
Jeroen van Gent ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Theoretical Basis ◽  
Large Range ◽  
A Priori ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Pixel Size ◽  
Vertical Column ◽  
Spectral Fitting ◽  
Correction Scheme

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S-5P) platform will measure ultraviolet earthshine radiances at high spectral and improved spatial resolution (pixel size of 7 km  ×  3.5 km at nadir) compared to its predecessors OMI and GOME-2. This paper presents the sulfur dioxide (SO2) vertical column retrieval algorithm implemented in the S-5P operational processor UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) and comprehensively describes its various retrieval steps. The spectral fitting is performed using the differential optical absorption spectroscopy (DOAS) method including multiple fitting windows to cope with the large range of atmospheric SO2 columns encountered. It is followed by a slant column background correction scheme to reduce possible biases or across-track-dependent artifacts in the data. The SO2 vertical columns are obtained by applying air mass factors (AMFs) calculated for a set of representative a priori profiles and accounting for various parameters influencing the retrieval sensitivity to SO2. Finally, the algorithm includes an error analysis module which is fully described here. We also discuss verification results (as part of the algorithm development) and future validation needs of the TROPOMI SO2 algorithm.

scholarly journals Tropospheric nitrogen dioxide column retrieval from ground-based zenith–sky DOAS observations

2015 ◽  
Vol 8 (6) ◽  
pp. 2417-2435 ◽  
Author(s):  
F. Tack ◽  
F. Hendrick ◽  
F. Goutail ◽  
C. Fayt ◽  
A. Merlaud ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Atmospheric Composition ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Measuring Instruments ◽  
Reference Spectrum ◽  
Vertical Column ◽  
Data Set ◽  
Residual Amount

Abstract. We present an algorithm for retrieving tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) from ground-based zenith–sky (ZS) measurements of scattered sunlight. The method is based on a four-step approach consisting of (1) the differential optical absorption spectroscopy (DOAS) analysis of ZS radiance spectra using a fixed reference spectrum corresponding to low NO2 absorption, (2) the determination of the residual amount in the reference spectrum using a Langley-plot-type method, (3) the removal of the stratospheric content from the daytime total measured slant column based on stratospheric VCDs measured at sunrise and sunset, and simulation of the rapid NO2 diurnal variation, (4) the retrieval of tropospheric VCDs by dividing the resulting tropospheric slant columns by appropriate air mass factors (AMFs). These steps are fully characterized and recommendations are given for each of them. The retrieval algorithm is applied on a ZS data set acquired with a multi-axis (MAX-) DOAS instrument during the Cabauw (51.97° N, 4.93° E, sea level) Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI) held from 10 June to 21 July 2009 in the Netherlands. A median value of 7.9 × 1015 molec cm−2 is found for the retrieved tropospheric NO2 VCDs, with maxima up to 6.0 × 1016 molec cm−2. The error budget assessment indicates that the overall error σTVCD on the column values is less than 28%. In the case of low tropospheric contribution, σTVCD is estimated to be around 39% and is dominated by uncertainties in the determination of the residual amount in the reference spectrum. For strong tropospheric pollution events, σTVCD drops to approximately 22% with the largest uncertainties on the determination of the stratospheric NO2 abundance and tropospheric AMFs. The tropospheric VCD amounts derived from ZS observations are compared to VCDs retrieved from off-axis and direct-sun measurements of the same MAX-DOAS instrument as well as to data from a co-located Système d'Analyse par Observations Zénithales (SAOZ) spectrometer. The retrieved tropospheric VCDs are in good agreement with the different data sets with correlation coefficients and slopes close to or larger than 0.9. The potential of the presented ZS retrieval algorithm is further demonstrated by its successful application on a 2-year data set, acquired at the NDACC (Network for the Detection of Atmospheric Composition Change) station Observatoire de Haute Provence (OHP; Southern France).

scholarly journals A method for improved SCIAMACHY CO2 retrieval in the presence of optically thin clouds

2010 ◽  
Vol 3 (1) ◽  
pp. 209-232 ◽  
Author(s):  
M. Reuter ◽  
M. Buchwitz ◽  
O. Schneising ◽  
J. Heymann ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Absorption Band ◽  
Near Infrared ◽  
A Priori ◽  
Optimal Estimation ◽  
Surface Flux ◽  
Co2 Absorption ◽  
Retrieval Scheme ◽  
Priori Information ◽  
Transfer Of Information

Abstract. An optimal estimation based retrieval scheme for satellite based retrievals of XCO2 (the dry air column averaged mixing ratio of atmospheric CO2) is presented enabling accurate retrievals also in the presence of thin clouds. The proposed method is designed to analyze near-infrared nadir measurements of the SCIAMACHY instrument in the CO2 absorption band at 1580 nm and in the O2-A absorption band at around 760 nm. The algorithm accounts for scattering in an optically thin cirrus cloud layer and at aerosols of a default profile. The scattering information is mainly obtained from the O2-A band and a merged fit windows approach enables the transfer of information between the O2-A and the CO2 band. Via the optimal estimation technique, the algorithm is able to account for a priori information to further constrain the inversion. Test scenarios of simulated SCIAMACHY sun-normalized radiance measurements are analyzed in order to specify the quality of the proposed method. In contrast to existing algorithms for SCIAMACHY retrievals, the systematic errors due to cirrus clouds with optical thicknesses up to 1.0 are reduced to values below 4 ppm for most of the analyzed scenarios. This shows that the proposed method has the potential to reduce uncertainties of SCIAMACHY retrieved XCO2 making this data product potentially useful for surface flux inverse modeling.

scholarly journals Extending differential optical absorption spectroscopy for limb measurements in the UV

2010 ◽  
Vol 3 (3) ◽  
pp. 631-653 ◽  
Author(s):  
J. Puķīte ◽  
S. Kühl ◽  
T. Deutschmann ◽  
U. Platt ◽  
T. Wagner
Keyword(s):  
Optical Depth ◽  
Absorption Spectroscopy ◽  
Weighting Function ◽  
Scattered Light ◽  
A Priori ◽  
Optical Absorption Spectroscopy ◽  
A Priori Knowledge ◽  
Light Path ◽  
Air Mass ◽  
Mass Factor

Abstract. Methods of UV/VIS absorption spectroscopy to determine the constituents in the Earth's atmosphere from measurements of scattered light are often based on the Beer-Lambert law, like e.g. Differential Optical Absorption Spectroscopy (DOAS). While the Beer-Lambert law is strictly valid for a single light path only, the relation between the optical depth and the concentration of any absorber can be approximated as linear also for scattered light observations at a single wavelength if the absorption is weak. If the light path distribution is approximated not to vary with wavelength, also linearity between the optical depth and the product of the cross-section and the concentration of an absorber can be assumed. These assumptions are widely made for DOAS applications for scattered light observations. For medium and strong absorption of scattered light (e.g. along very long light-paths like in limb geometry) the relation between the optical depth and the concentration of an absorber is no longer linear. In addition, for broad wavelength intervals the differences in the travelled light-paths at different wavelengths become important, especially in the UV, where the probability for scattering increases strongly with decreasing wavelength. However, the DOAS method can be extended to cases with medium to strong absorptions and for broader wavelength intervals by the so called air mass factor modified (or extended) DOAS and the weighting function modified DOAS. These approaches take into account the wavelength dependency of the slant column densities (SCDs), but also require a priori knowledge for the air mass factor or the weighting function from radiative transfer modelling. We describe an approach that considers the fitting results obtained from DOAS, the SCDs, as a function of wavelength and vertical optical depth and expands this function into a Taylor series of both quantities. The Taylor coefficients are then applied as additional fitting parameters in the DOAS analysis. Thus the variability of the SCD in the fit window is determined by the retrieval itself. This new approach provides a description of the SCD the exactness of which depends on the order of the Taylor expansion, and is independent from any assumptions or a priori knowledge of the considered absorbers. In case studies of simulated and measured spectra in the UV range (332–357 nm), we demonstrate the improvement by this approach for the retrieval of vertical profiles of BrO from the SCIAMACHY limb observations. The results for BrO obtained from the simulated spectra are closer to the true profiles, when applying the new method for the SCDs of ozone, than when the standard DOAS approach is used. For the measured spectra the agreement with validation measurements is also improved significantly, especially for cases with strong ozone absorption. While the focus of this article is on the improvement of the BrO profile retrieval from the SCIAMACHY limb measurements, the novel approach may be applied to a wide range of DOAS retrievals.

scholarly journals Atmospheric methane and carbon dioxide from SCIAMACHY satellite data: initial comparison with chemistry and transport models

2004 ◽  
Vol 4 (6) ◽  
pp. 7217-7279 ◽  
Author(s):  
M. Buchwitz ◽  
R. de Beek ◽  
J. P. Burrows ◽  
H. Bovensmann ◽  
T. Warneke ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Reasonable Agreement ◽  
Near Infrared ◽  
Weighting Function ◽  
Lower Surface ◽  
Retrieval Algorithm ◽  
Atmospheric Methane ◽  
Mixing Ratios ◽  
Data Products ◽  
Carbon Dioxide Co2

Abstract. The remote sensing of the atmospheric greenhouse gases methane (CH4) and carbon dioxide (CO2) in the troposphere from instrumentation aboard satellites is a new area of research. In this manuscript, results obtained from observations of the up-welling radiation in the near-infrared by SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY), which flies on board ENVISAT, are presented. Vertical columns of CH4, CO2 and oxygen (O2) have been retrieved and the (air or) O2-normalized CH4 and CO2 column amounts, the dry air column averaged mixing ratios XCH4 and XCO2 derived. In this manuscript the first results, obtained by using the version 0.4 of the Weighting Function Modified (WFM) DOAS retrieval algorithm applied to SCIAMACHY data, are described and compared with global models. This is an important step in assessing the quality and information content of the data products derived from SCIAMACHY observations. This study investigates the behaviour of CO2 and CH4 in the period from January to October 2003. The SCIAMACHY greenhouse gas column amounts and their mixing ratios for cloud free scenes over land are shown to be in reasonable agreement with models. Over the ocean, as a result of the lower surface spectral reflectance and resultant low signal to noise with the exception of sun glint conditions, the accuracy of the individual data products is poorer. The measured methane column amounts agree with the model columns within a few percent. The inter-hemispheric difference of the methane mixing ratios, determined from single day cloud free measurements over land, is in the range 30–110 ppbv and in reasonable agreement with the corresponding model data (48–71 ppbv). For the set of individual measurements the standard deviations of the difference with respect to the models are in the range ~100–200 ppbv (5–10%) and ±14.4 ppmv (3.9%) for XCH

scholarly journals Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

2016 ◽  
Vol 9 (3) ◽  
pp. 973-989 ◽  
Author(s):  
Thomas E. Taylor ◽  
Christopher W. O'Dell ◽  
Christian Frankenberg ◽  
Philip T. Partain ◽  
Heather Q. Cronk ◽  
...  
Keyword(s):  
Surface Pressure ◽  
Near Infrared ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Screening Methods ◽  
Atmospheric Scattering ◽  
Initial Comparison ◽  
Carbon Dioxide Co2 ◽  
Cloud Screening

Abstract. The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of  ≃ 20–25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be  ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April–May) for OCO-2 nadir-land, glint-land and glint-water observations.No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

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