Orbiting Carbon Observatory: Inverse method and prospective error analysis
By Brian J. Connor, H. Boesch, Geoffrey C. Toon, Bhaswar Sen, Charles E. Miller, David Crisp. 2008
293 citations recorded by the source corpus.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/40204b1b797768f720e7d5f24d2722945eda8f3c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atmospheric Science
- David Crisp
- Paul O. Wennberg
- Heinrich Bovensmann
- Oliver Schneising
- Charles E. Miller
- John P. Burrows
- Christian Frankenberg
- Michael Buchwitz
In Global and Planetary Change
- David Crisp
- Paul O. Wennberg
- H. Bösch
- Paul I. Palmer
- Liang Feng
- Heinrich Bovensmann
- Oliver Schneising
- Charles E. Miller
Citations in the corpus
- Methane observations from the Greenhouse Gases Observing SATellite: Comparison to ground‐based TCCON data and model calculations (2011, methodology): “[9] The retrieval algorithm uses an iterative retrieval scheme basedonBayesian optimal estimation to retrieve aset of atmospheric/surface/instrument parameters, referred to as the state vector, from measured spectral radiances [Boesch et al., 2011; Connor et al., 2008 ].”
- Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm (2018, methodology): “2 of Connor et al., 2008).”
- Carbon source/sink information provided by column CO 2 measurements from the Orbiting Carbon Observatory (2008, background): “Biases due the representation errors were found to be small in Corbin et al. (2008) and are not added here at all.”
- How bias correction goes wrong: measurement of XCO2 affected by erroneous surface pressure estimates (2019, methodology): “For all data sets a correction was applied using the OCO-2 averaging kernels based on Connor et al. (2008). We convolve the CO2 profiles from the truth proxies with the OCO-2 column averaging kernel before we compare it to OCO-2 XCO2 .”
- Retrieval of atmospheric CO2 with enhanced accuracy and precision from SCIAMACHY: validation with FTS measurements and comparison with model results (2011, methodology): “[8] For the high spectral resolution instruments TANSO and OCO, algorithms have been developed that correct for scattering effects [Kuang et al., 2002; Bril et al., 2007; Connor et al., 2008; Butz et al., 2009].”
- Disentangling chlorophyll fluorescence from atmospheric scattering effects in O2 A‐band spectra of reflected sun‐light (2011, background): “…the atmosphere and thereby minimize the impact of aerosols and thin clouds on the retrieval of CO2, which is performed in additional channels covering CO2 absorption bands at 1.61 and 2.06 mm [Bösch et al., 2006; Connor et al., 2008; Oshchepkov et al., 2008; Butz et al., 2009; Reuter et al., 2010].”
- The ACOS CO 2 retrieval algorithm – Part 1: Description and validation against synthetic observations (2011, methodology): “For instance, Connor et al.(2008) weights CO2 concentration by pressure, and Reuter et al.”