Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation

Abstract. Solar-induced fluorescence (SIF) data from satellites are increasingly used as a proxy for photosynthetic activity by vegetation, and as a constraint on gross primary production. Here we develop an improved retrieval algorithm to retrieve mid-morning (09:30 hrs local time) SIF estimates on the global scale from GOME-2 sensor on the Metop-A satellite (GOME-2A) for the period 2007–2019. Our new SIFTER v2 algorithm improves over a previous version by using a narrower spectral window that avoids strong oxygen absorption and is less sensitive to water vapour absorption, by constructing stable reference spectra from a 6-year period (2007–2012) of atmospheric spectra over the Sahara, and by applying a latitude-dependent zero-level adjustment that accounts for biases in the data product. We generated stable, good-quality SIF retrievals between January 2007 and June 2013, when GOME-2A degradation in the near infrared was still limited. After the narrowing of the GOME-2A swath in July 2013, we characterized the throughput degradation of the level-1 data in order to derive reflectance corrections and apply these for the SIF retrievals between July 2013 and December 2018. SIFTER v2 data compares well with the independent NASA v2.8 data product. Especially in the evergreen tropics, SIFTER v2 no longer shows the underestimates against other satellite products that were seen in SIFTER v1. The new data product includes uncertainty estimates for individual observations, and is best used for mostly clear-sky scenes, and when spectral residuals remain below a certain spectral autocorrelation threshold. Our results support the use of SIFTER v2 data to be used as an independent constraint on photosynthetic activity on regional to global scales.

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Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation

Atmospheric Measurement Techniques ◽

10.5194/amt-13-4295-2020 ◽

2020 ◽

Vol 13 (8) ◽

pp. 4295-4315

Author(s):

Erik van Schaik ◽

Maurits L. Kooreman ◽

Piet Stammes ◽

L. Gijsbert Tilstra ◽

Olaf N. E. Tuinder ◽

...

Keyword(s):

Near Infrared ◽

Photosynthetic Activity ◽

Gross Primary Production ◽

Terrestrial Ecosystems ◽

Global Scale ◽

Oxygen Absorption ◽

Spectral Window ◽

Data Product ◽

Uncertainty Estimates ◽

Water Vapour Absorption

Abstract. Solar-induced fluorescence (SIF) data from satellites are increasingly used as a proxy for photosynthetic activity by vegetation and as a constraint on gross primary production. Here we report on improvements in the algorithm to retrieve mid-morning (09:30 LT) SIF estimates on the global scale from the GOME-2 sensor on the MetOp-A satellite (GOME-2A) for the period 2007–2019. Our new SIFTER (Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval) v2 algorithm improves over a previous version by using a narrower spectral window that avoids strong oxygen absorption and being less sensitive to water vapour absorption, by constructing stable reference spectra from a 6-year period (2007–2012) of atmospheric spectra over the Sahara and by applying a latitude-dependent zero-level adjustment that accounts for biases in the data product. We generated stable, good-quality SIF retrievals between January 2007 and June 2013, when GOME-2A degradation in the near infrared was still limited. After the narrowing of the GOME-2A swath in July 2013, we characterised the throughput degradation of the level-1 data in order to derive reflectance corrections and apply these for the SIF retrievals between July 2013 and December 2018. SIFTER v2 data compare well with the independent NASA v2.8 data product. Especially in the evergreen tropics, SIFTER v2 no longer shows the underestimates against other satellite products that were seen in SIFTER v1. The new data product includes uncertainty estimates for individual observations and is best used for mostly clear-sky scenes and when spectral residuals remain below a certain spectral autocorrelation threshold. Our results support the use of SIFTER v2 data being used as an independent constraint on photosynthetic activity on regional to global scales.

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Twelve years of SIFTER Sun-Induced Fluorescence retrievals from GOME-2 as an independent constraint on photosynthesis across continents and biomes

10.5194/egusphere-egu2020-5421 ◽

2020 ◽

Author(s):

Maurits L. Kooreman ◽

K. Folkert Boersma ◽

Erik van Schaik ◽

Anteneh G. Mengistu ◽

Olaf N. E. Tuinder ◽

...

Keyword(s):

Photosynthetic Activity ◽

Gross Primary Production ◽

Global Scale ◽

Retrieval Algorithm ◽

Oxygen Absorption ◽

Water Vapor Absorption ◽

Zonal Distribution ◽

Spectral Window ◽

Tropical Regions ◽

Uncertainty Estimates

<p>Solar-Induced Fluorescence (SIF) data from satellites are increasingly used as a proxy for photosynthetic activity by vegetation, and as a constraint on gross primary production. The Royal Netherlands Meteorological Institute has developed an improved retrieval algorithm called SIFTER, to retrieve mid-morning (09:30 hrs local time) SIF estimates on the global scale from GOME-2 sensors on the Metop satellite series. The product is developed within the ACSAF network of EUMETSAT and a beta version is publicly available on www.temis.nl. The SIFTER algorithm improves over a previous version by using a narrower spectral window that avoids strong oxygen absorption and is less sensitive to water vapor absorption, by constructing stable reference spectra from a 6-year period (2007-2012) of atmospheric spectra over the Sahara, and by applying a latitude-dependent zero-level adjustment that accounts for biases in the product data. With SIFTER, we generate stable, good-quality SIF retrievals also in tropical regions that are known to suffer from high noise in other SIF products. Uncertainty estimates are included for individual observations, and the product is best used for mostly clear-sky scenes, and when spectral residuals remain below a certain threshold. The strength of SIFTER in the tropical regions was exploited to quantify the 2015/2016 drought in the Amazon, related to El Ni&#241;o. We found that SIF was strongly suppressed over areas with anomalously high temperatures and decreased levels of soil moisture. SIF went below its climatological range starting from the end of the 2015 dry season and returned to normal levels by February 2016. A validation study is performed to assess the SIFTER quality against independent SIF and GPP products from other platforms, including SIF from OCO-2 and GOSAT, modeled GPP from MPI-BGC and eddy covariance derived, in-situ GPP measurements. SIFTER shows strong correlations (0.70 &#8211; 0.94) in the zonal distribution for each continent and in capturing seasonal patterns of SIF and GPP over different regions across the globe (0.62-0.99) when comparing to OCO-2 SIF and GPP from MPI-BGC. At ecosystem level, SIFTER was evaluated against OCO-2 SIF and EC GPP for five flux tower sites with varying biomes and geolocations. Regions with a homogeneous vegetation distribution show a higher correlation than heterogeneous regions. Overall, the results support the use of SIFTER data to be used as an independent constraint on photosynthetic activity on global and regional scales.</p>

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Remote sensing of near-infrared chlorophyll fluorescence from space in scattering atmospheres: implications for its retrieval and interferences with atmospheric CO<sub>2</sub> retrievals

Atmospheric Measurement Techniques ◽

10.5194/amt-5-2081-2012 ◽

2012 ◽

Vol 5 (8) ◽

pp. 2081-2094 ◽

Cited By ~ 90

Author(s):

C. Frankenberg ◽

C. O'Dell ◽

L. Guanter ◽

J. McDuffie

Keyword(s):

Chlorophyll Fluorescence ◽

Greenhouse Gas ◽

Near Infrared ◽

Global Scale ◽

Oxygen Absorption ◽

Random Errors ◽

Solar Absorption ◽

Systematic Biases ◽

Gas Space ◽

Absorption Features

Abstract. With the advent of dedicated greenhouse gas space-borne spectrometers sporting high resolution spectra in the O2 A-band spectral region (755–774 nm), the retrieval of chlorophyll fluorescence has become feasible on a global scale. If unaccounted for, however, fluorescence can indirectly perturb the greenhouse gas retrievals as it perturbs the oxygen absorption features. As atmospheric CO2 measurements are used to invert net fluxes at the land–atmosphere interface, a bias caused by fluorescence can be crucial as it will spatially correlate with the fluxes to be inverted. Avoiding a bias and retrieving fluorescence accurately will provide additional constraints on both the net and gross fluxes in the global carbon cycle. We show that chlorophyll fluorescence, if neglected, systematically interferes with full-physics multi-band XCO2 retrievals using the O2 A-band. Systematic biases in XCO2 can amount to +1 ppm if fluorescence constitutes 1% to the continuum level radiance. We show that this bias can be largely eliminated by simultaneously fitting fluorescence in a full-physics based retrieval. If fluorescence is the primary target, a dedicated but very simple retrieval based purely on Fraunhofer lines is shown to be more accurate and very robust even in the presence of large scattering optical depths. We find that about 80% of the surface fluorescence is retained at the top-of-atmosphere, even for cloud optical thicknesses around 2–5. We further show that small instrument modifications to future O2 A-band spectrometer spectral ranges can result in largely reduced random errors in chlorophyll fluorescence, paving the way towards a more dedicated instrument exploiting solar absorption features only.

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Global carbon monoxide as retrieved from SCIAMACHY by WFM-DOAS

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-4-2805-2004 ◽

2004 ◽

Vol 4 (3) ◽

pp. 2805-2837 ◽

Cited By ~ 2

Author(s):

M. Buchwitz ◽

R. de Beek ◽

K. Bramstedt ◽

S. Noël ◽

H. Bovensmann ◽

...

Keyword(s):

Carbon Monoxide ◽

Near Infrared ◽

Weighting Function ◽

Lower Troposphere ◽

Quantitative Information ◽

Scaling Factor ◽

Retrieval Algorithm ◽

Absorption Bands ◽

Spectral Fitting ◽

Data Product

Abstract. Vertical columns of CO have been retrieved from SCIAMACHY/ENVISAT short wave/near infrared (~2.3µm) nadir spectra using the Weighting Function Modified (WFM) DOAS retrieval algorithm. WFM-DOAS has been applied to a small spectral fitting window located in SCIAMACHY's channel 8 (~2365 nm) covering four CO absorption lines. The focus of this paper is to demonstrate that quantitative information on carbon monoxide (CO) on a global scale can be retrieved from SCIAMACHY. It is shown that plumes of CO resulting from, e.g. biomass burning in Africa, are clearly detectable with SCIAMACHY. The SCIAMACHY CO columns are in good agreement with the CO column data product of MOPITT (V3). For example, the correlation between SCIAMACHY and MOPITT CO columns for cloud free pixels over land is typically in the range r=0.4–0.7, where r is the correlation coefficient. In order to retrieve good CO columns it was necessary to improve the calibration of the SCIAMACHY nadir spectra. Nevertheless, there is still room for significant improvement. The fit residuals, for example, are dominated by stable and systematic spectral artifacts on the order of the weak CO lines. These artifacts are most pronounced in spectral regions of strong overlapping methane and water vapour absorption bands. They might result from spectrometer slit function uncertainties. The CO columns of the WFM-DOAS Version 0.4 CO column data product presented in this paper have been multiplied by a constant and ground scene independent scaling factor of 0.5 to quantitatively adjust the WFM-DOAS retrieved CO columns to the MOPITT CO data. If and how this scaling factor is influenced by SCIAMACHYs much higher sensitivity to the lower troposphere and boundary layer CO and/or by the currently not perfect spectral fitting needs further investigation.

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Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces

Remote Sensing ◽

10.3390/rs13050932 ◽

2021 ◽

Vol 13 (5) ◽

pp. 932

Author(s):

René Preusker ◽

Cintia Carbajal Henken ◽

Jürgen Fischer

Keyword(s):

Water Vapour ◽

Near Infrared ◽

Retrieval Algorithm ◽

Data Sets ◽

Data Set ◽

Uncertainty Estimates ◽

Resolution Imaging ◽

Retrieval Errors ◽

Mean Square Errors ◽

Total Column

A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One of the main advantages of the OLCI instrument regarding improved TCWV retrievals lies in the use of more than one absorbing band. Furthermore, the COWa retrieval algorithm is based on the full Optimal Estimation (OE) method, providing pixel-based uncertainty estimates, and transferable to other Near-Infrared (NIR) based TCWV observations. Three independent global TCWV data sets, i.e., Aerosol Robotic Network (AERONET), Atmospheric Radiation Measurement (ARM) and U.S. SuomiNet, and a German Global Navigation Satellite System (GNSS) TCWV data set, all obtained from ground-based observations, serve as reference data sets for the validation. Comparisons show an overall good agreement, with absolute biases between 0.07 and 1.31 kg/m2 and root mean square errors (RMSE) between 1.35 and 3.26 kg/m2. This is a clear improvement in comparison to the operational OLCI TCWV Level 2 product, for which the bias and RMSEs range between 1.10 and 2.55 kg/m2 and 2.08 and 3.70 kg/m2, respectively. A first evaluation of pixel-based uncertainties indicates good estimated uncertainties for lower retrieval errors, while the uncertainties seem to be overestimated for higher retrieval errors.

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Can vegetation index track the interannual variation in gross primary production of temperate deciduous forests?

Ecological Processes ◽

10.1186/s13717-021-00324-2 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Fan Liu ◽

Chuankuan Wang ◽

Xingchang Wang

Keyword(s):

Primary Production ◽

Vegetation Index ◽

Near Infrared ◽

Deciduous Forest ◽

Gross Primary Production ◽

Growing Season ◽

Temperate Deciduous Forest ◽

Near Infrared Reflectance ◽

Modis Ndvi ◽

Temperate Deciduous

Abstract Background Vegetation indices (VIs) by remote sensing are widely used as simple proxies of the gross primary production (GPP) of vegetation, but their performances in capturing the inter-annual variation (IAV) in GPP remain uncertain. Methods We evaluated the performances of various VIs in tracking the IAV in GPP estimated by eddy covariance in a temperate deciduous forest of Northeast China. The VIs assessed included the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), and the near-infrared reflectance of vegetation (NIRv) obtained from tower-radiometers (broadband) and the Moderate Resolution Imaging Spectroradiometer (MODIS), respectively. Results We found that 25%–35% amplitude of the broadband EVI tracked the start of growing season derived by GPP (R2: 0.56–0.60, bias < 4 d), while 45% (or 50%) amplitudes of broadband (or MODIS) NDVI represented the end of growing season estimated by GPP (R2: 0.58–0.67, bias < 3 d). However, all the VIs failed to characterize the summer peaks of GPP. The growing-season integrals but not averaged values of the broadband NDVI, MODIS NIRv and EVI were robust surrogates of the IAV in GPP (R2: 0.40–0.67). Conclusion These findings illustrate that specific VIs are effective only to capture the GPP phenology but not the GPP peak, while the integral VIs have the potential to mirror the IAV in GPP.

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Toward CO2 and CH4 measurements by ground-based observations of surface-scattered sunlight

10.5194/egusphere-egu21-7569 ◽

2021 ◽

Author(s):

Benedikt Hemmer ◽

Christin Proß ◽

Stanley P. Sander ◽

Thomas J. Pongetti ◽

Zhao-Cheng Zeng ◽

...

Keyword(s):

Los Angeles ◽

Urban Areas ◽

Near Infrared ◽

Chem Phys ◽

Retrieval Algorithm ◽

Los Angeles Basin ◽

Satellite Measurements ◽

Precise Knowledge ◽

Extended Sources

<div> <div>Precise knowledge of sources and sinks in the carbon cycle is desired to understand its sensitivity to climate change and to account and verify man-made emissions. In this context, extended sources like urban areas play an important role. While in-situ measurements of carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) are highly accurate but localized, satellites measure column-integrated concentrations over an extended footprint. The CLARS-FTS [1, 2] stationed at the Mt. Wilson observatory looking downward into the Los Angeles basin has pioneered an innovative measurement technique that fills the sensitivity gap between in-situ and satellite measurements. The technique enables mapping the urban greenhouse gas concentration fields by collecting spectra of ground scattered sunlight and scanning through the region.</div> <div>&#160;</div> <div>Here, we report on progress developing a portable setup for a CLARS-FTS-like measurement geometry. The instrument is based on the EM27/SUN FTS with a modified pointing technique and a more sensitive detector. The retrieval algorithm is based on the RemoTeC software, previously employed for solar backscatter satellite measurements. We discuss first steps in terms of instrument performance and retrieval exercises. For the latter, we have carried out simulations on how the neglect of scattering by the retrieval affects the retrieved boundary layer concentrations of CO<sub>2</sub> and CH<sub>4</sub> for an ensemble of hypothetical scenes with variable complexity in aeorsol loadings and viewing geometry. We also report on a test to apply RemoTeC to a small set of CLARS-FTS spectra collected throughout the Los Angeles basin.</div> <div>&#160;</div> <div><em>References</em></div> <div>[1] Fu, D. et al., 2014: Near-infrared remote sensing of Los Angeles trace gas distributions from a mountaintop site, Atmos. Meas. Tech., 7, 713&#8211;729, https://doi.org/10.5194/amt-7-713-2014</div> [2] Wong, K. W. et al., 2015: Mapping CH4 : CO2 ratios in Los Angeles with CLARS-FTS from Mount Wilson, California, Atmos. Chem. Phys., 15, 241&#8211;252, https://doi.org/10.5194/acp-15-241-2015</div>

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Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project

Atmospheric Measurement Techniques ◽

10.5194/amt-11-2395-2018 ◽

2018 ◽

Vol 11 (4) ◽

pp. 2395-2426 ◽

Cited By ~ 33

Author(s):

Isabelle De Smedt ◽

Nicolas Theys ◽

Huan Yu ◽

Thomas Danckaert ◽

Christophe Lerot ◽

...

Keyword(s):

Near Infrared ◽

Horizontal Resolution ◽

Retrieval Algorithm ◽

User Requirements ◽

Vertical Column ◽

Ultraviolet Range ◽

Order Of Magnitude ◽

Shortwave Infrared ◽

Double Channel ◽

The Eu

Abstract. On board the Copernicus Sentinel-5 Precursor (S5P) platform, the TROPOspheric Monitoring Instrument (TROPOMI) is a double-channel, nadir-viewing grating spectrometer measuring solar back-scattered earthshine radiances in the ultraviolet, visible, near-infrared, and shortwave infrared with global daily coverage. In the ultraviolet range, its spectral resolution and radiometric performance are equivalent to those of its predecessor OMI, but its horizontal resolution at true nadir is improved by an order of magnitude. This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the S5P operational processor and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted. Finally, verification results based on the application of the algorithm to OMI measurements are presented, demonstrating the performances expected for TROPOMI.

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SIFSpec: Measuring Solar-Induced Chlorophyll Fluorescence Observations for Remote Sensing of Photosynthesis

Sensors ◽

10.3390/s19133009 ◽

2019 ◽

Vol 19 (13) ◽

pp. 3009 ◽

Cited By ~ 11

Author(s):

Shanshan Du ◽

Liangyun Liu ◽

Xinjie Liu ◽

Jian Guo ◽

Jiaochan Hu ◽

...

Keyword(s):

Remote Sensing ◽

Chlorophyll Fluorescence ◽

Seasonal Variations ◽

Photosynthetic Activity ◽

Gross Primary Production ◽

Atmospheric Correction ◽

Gansu Province ◽

Optical Measurements ◽

Calibration Data ◽

Flux Measurements

Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2–A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.

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

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-8-12663-2015 ◽

2015 ◽

Vol 8 (12) ◽

pp. 12663-12707 ◽

Cited By ~ 2

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 &simeq; 30 %, agreement between the OCO-2 and MODIS cloud screening methods is found to be &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.

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