The GODFIT algorithm: A direct fitting approach to improve the accuracy of total ozone measurements from GOME
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Authors
Lerot, C.
Van Roozendael, M.
Lambert, J.-C.
Granville, J.
Van Gent, J.
Loyola, D.
Spurr, R.
Discipline
Earth and related Environmental sciences
Subject
Back-scattered
Data processors
Discrete ordinates
Global ozone monitoring experiments
Ground based
Ground based measurement
Ozone monitoring instruments
Radiative transfer model
Spectral radiance
Total ozone
Total ozone measurements
Algorithms
Atmospheric composition
Ozone
Radiative transfer
Ultraviolet spectrometers
Monitoring
algorithm
correlation
GOME
ground-based measurement
nadir
radiative transfer
satellite data
satellite imagery
total ozone
Audience
Scientific
Date
2010Metadata
Show full item recordDescription
We present the total ozone retrieval algorithm GODFIT (GOME Direct-FITting). Applied to nadir backscattered measurements from the Global Ozone Monitoring Experiment (GOME), it is based on a direct-fitting approach by which spectral radiances simulated using the radiative transfer model LIDORT v3.3 (Linearized Discrete Ordinate Radiative Transfer) are adjusted to measurements in the 325-335 nm interval. Total O3 columns retrieved from GOME spectra have been compared not only to columns retrieved from Ozone Monitoring Instrument (OMI) measurements using the TOMS v8.5 algorithm, but also to correlative ground-based measurements from the GAW/NDACC networks (Global Atmosphere Watch/Network for the Detection of Atmospheric Composition Change). We show that GODFIT produces a significant reduction of the GOME ground-based differences and some of the associated dependencies, compared with the GOME Data Processor (GDP) 4.1 product. Version 5 of GDP, based on the GODFIT algorithm, will be released in spring 2010.
Citation
Lerot, C.; Van Roozendael, M.; Lambert, J.-C.; Granville, J.; Van Gent, J.; Loyola, D.; Spurr, R. (2010). The GODFIT algorithm: A direct fitting approach to improve the accuracy of total ozone measurements from GOME. , International Journal of Remote Sensing, Vol. 31, Issue 2, 543-550, DOI: 10.1080/01431160902893576.Identifiers
scopus: 2-s2.0-77649165357
Type
Article
Peer-Review
Yes
Language
eng