TY - JOUR
T1 - Tropospheric Emission Spectrometer
T2 - Retrieval method and error analysis
AU - Bowman, Kevin W.
AU - Rodgers, Clive D.
AU - Kulawik, Susan Sund
AU - Worden, John
AU - Sarkissian, Edwin
AU - Osterman, Greg
AU - Steck, Tilman
AU - Lou, Ming
AU - Eldering, Annmarie
AU - Shephard, Mark
AU - Worden, Helen
AU - Lampel, Michael
AU - Clough, Shepard
AU - Brown, Pat
AU - Rinsland, Curtis
AU - Gunson, Michael
AU - Beer, Reinhard
PY - 2006/5
Y1 - 2006/5
N2 - We describe the approach for the estimation of the atmospheric state, e.g., temperature, water, ozone, from calibrated, spectral radiances measured from the Tropospheric Emission Spectrometer (TES) onboard the Aura spacecraft. The methodology is based on the maximum a posteriori estimate, which mathematically requires the minimization of the difference between observed spectral radiances and a nonlinear model of radiative transfer of the atmospheric state subject to the constraint that the estimated state must be consistent with an a priori probability distribution for that state. The minimization techniques employed here are based on the trust-region Levenberg-Marquardt algorithm. An analysis of the errors for this estimate include smoothing, random, spectroscopic, "cross-state," representation, and systematic errors. In addition, several metrics and diagnostics are introduced that assess the resolution, quality, and statistical significance of the retrievals. We illustrate this methodology for the retrieval of atmospheric and surface temperature, water vapor, and ozone over the Gulf of Mexico on November 3, 2004.
AB - We describe the approach for the estimation of the atmospheric state, e.g., temperature, water, ozone, from calibrated, spectral radiances measured from the Tropospheric Emission Spectrometer (TES) onboard the Aura spacecraft. The methodology is based on the maximum a posteriori estimate, which mathematically requires the minimization of the difference between observed spectral radiances and a nonlinear model of radiative transfer of the atmospheric state subject to the constraint that the estimated state must be consistent with an a priori probability distribution for that state. The minimization techniques employed here are based on the trust-region Levenberg-Marquardt algorithm. An analysis of the errors for this estimate include smoothing, random, spectroscopic, "cross-state," representation, and systematic errors. In addition, several metrics and diagnostics are introduced that assess the resolution, quality, and statistical significance of the retrievals. We illustrate this methodology for the retrieval of atmospheric and surface temperature, water vapor, and ozone over the Gulf of Mexico on November 3, 2004.
KW - Atmospheres
KW - Constituents
KW - Inverse methods
KW - Remote sounding
KW - Temperature
UR - https://www.scopus.com/pages/publications/33646428696
U2 - 10.1109/TGRS.2006.871234
DO - 10.1109/TGRS.2006.871234
M3 - Article
AN - SCOPUS:33646428696
SN - 0196-2892
VL - 44
SP - 1297
EP - 1306
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 5
ER -