Articles | Volume 9, issue 6
https://doi.org/10.5194/acp-9-1883-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-9-1883-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
17 Mar 2009
A self-adapting and altitude-dependent regularization method for atmospheric profile retrievals
M. Ridolfi
Dipartimento di Chimica Fisica e Inorganica, Università di Bologna, Italy
L. Sgheri
Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, Firenze, Italy
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Cited
17 citations as recorded by crossref.
- Technical Note: Variance-covariance matrix and averaging kernels for the Levenberg-Marquardt solution of the retrieval of atmospheric vertical profiles S. Ceccherini & M. Ridolfi https://doi.org/10.5194/acp-10-3131-2010
- Jupiter’s hot spots: Quantitative assessment of the retrieval capabilities of future IR spectro-imagers D. Grassi et al. https://doi.org/10.1016/j.pss.2010.05.003
- Iterative approach to self-adapting and altitude-dependent regularization for atmospheric profile retrievals M. Ridolfi & L. Sgheri https://doi.org/10.1364/OE.19.026696
- On the choice of retrieval variables in the inversion of remotely sensed atmospheric measurements M. Ridolfi & L. Sgheri https://doi.org/10.1364/OE.21.011465
- Tropospheric ozone retrieval from thermal infrared nadir satellite measurements: Towards more adaptability of the constraint using a self-adapting regularization M. Eremenko et al. https://doi.org/10.1016/j.jqsrt.2019.106577
- The ESA MIPAS/Envisat level2-v8 dataset: 10 years of measurements retrieved with ORM v8.22 B. Dinelli et al. https://doi.org/10.5194/amt-14-7975-2021
- A Deterministic Method for Profile Retrievals From Hyperspectral Satellite Measurements P. Koner et al. https://doi.org/10.1109/TGRS.2016.2565722
- Measurement of the Arctic UTLS composition in presence of clouds using millimetre-wave heterodyne spectroscopy E. Castelli et al. https://doi.org/10.5194/amt-6-2683-2013
- Ten years of MIPAS measurements with ESA Level 2 processor V6 – Part 1: Retrieval algorithm and diagnostics of the products P. Raspollini et al. https://doi.org/10.5194/amt-6-2419-2013
- Insight into Construction of Tikhonov-Type Regularization for Atmospheric Retrievals J. Xu et al. https://doi.org/10.3390/atmos11101052
- A new approach to crystal habit retrieval from far-infrared spectral radiance measurements G. Di Natale et al. https://doi.org/10.5194/amt-17-3171-2024
- CCl4 distribution derived from MIPAS ESA v7 data: intercomparisons, trend, and lifetime estimation M. Valeri et al. https://doi.org/10.5194/acp-17-10143-2017
- Auto-adaptive Tikhonov regularization of water vapor profiles: application to FORUM measurements L. Sgheri et al. https://doi.org/10.1080/00036811.2020.1751825
- Application of the Complete Data Fusion algorithm to the ozone profiles measured by geostationary and low-Earth-orbit satellites: a feasibility study N. Zoppetti et al. https://doi.org/10.5194/amt-14-2041-2021
- A Vertically Structured Machine Learning Approach for Cloud Liquid and Ice Water Content Profiling Z. Pan et al. https://doi.org/10.3390/rs18132177
- Phosgene distribution derived from MIPAS ESA v8 data: intercomparisons and trends P. Pettinari et al. https://doi.org/10.5194/amt-14-7959-2021
- The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) A. Laeng et al. https://doi.org/10.1016/j.rse.2014.12.013
17 citations as recorded by crossref.
- Technical Note: Variance-covariance matrix and averaging kernels for the Levenberg-Marquardt solution of the retrieval of atmospheric vertical profiles S. Ceccherini & M. Ridolfi https://doi.org/10.5194/acp-10-3131-2010
- Jupiter’s hot spots: Quantitative assessment of the retrieval capabilities of future IR spectro-imagers D. Grassi et al. https://doi.org/10.1016/j.pss.2010.05.003
- Iterative approach to self-adapting and altitude-dependent regularization for atmospheric profile retrievals M. Ridolfi & L. Sgheri https://doi.org/10.1364/OE.19.026696
- On the choice of retrieval variables in the inversion of remotely sensed atmospheric measurements M. Ridolfi & L. Sgheri https://doi.org/10.1364/OE.21.011465
- Tropospheric ozone retrieval from thermal infrared nadir satellite measurements: Towards more adaptability of the constraint using a self-adapting regularization M. Eremenko et al. https://doi.org/10.1016/j.jqsrt.2019.106577
- The ESA MIPAS/Envisat level2-v8 dataset: 10 years of measurements retrieved with ORM v8.22 B. Dinelli et al. https://doi.org/10.5194/amt-14-7975-2021
- A Deterministic Method for Profile Retrievals From Hyperspectral Satellite Measurements P. Koner et al. https://doi.org/10.1109/TGRS.2016.2565722
- Measurement of the Arctic UTLS composition in presence of clouds using millimetre-wave heterodyne spectroscopy E. Castelli et al. https://doi.org/10.5194/amt-6-2683-2013
- Ten years of MIPAS measurements with ESA Level 2 processor V6 – Part 1: Retrieval algorithm and diagnostics of the products P. Raspollini et al. https://doi.org/10.5194/amt-6-2419-2013
- Insight into Construction of Tikhonov-Type Regularization for Atmospheric Retrievals J. Xu et al. https://doi.org/10.3390/atmos11101052
- A new approach to crystal habit retrieval from far-infrared spectral radiance measurements G. Di Natale et al. https://doi.org/10.5194/amt-17-3171-2024
- CCl4 distribution derived from MIPAS ESA v7 data: intercomparisons, trend, and lifetime estimation M. Valeri et al. https://doi.org/10.5194/acp-17-10143-2017
- Auto-adaptive Tikhonov regularization of water vapor profiles: application to FORUM measurements L. Sgheri et al. https://doi.org/10.1080/00036811.2020.1751825
- Application of the Complete Data Fusion algorithm to the ozone profiles measured by geostationary and low-Earth-orbit satellites: a feasibility study N. Zoppetti et al. https://doi.org/10.5194/amt-14-2041-2021
- A Vertically Structured Machine Learning Approach for Cloud Liquid and Ice Water Content Profiling Z. Pan et al. https://doi.org/10.3390/rs18132177
- Phosgene distribution derived from MIPAS ESA v8 data: intercomparisons and trends P. Pettinari et al. https://doi.org/10.5194/amt-14-7959-2021
- The ozone climate change initiative: Comparison of four Level-2 processors for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) A. Laeng et al. https://doi.org/10.1016/j.rse.2014.12.013
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