the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
16 Mar 2021
16 Mar 2021
An observing system simulation experiment (OSSE)-based assessment of the retrieval of above-cloud temperature and water vapor using hyperspectral infrared sounder
- 1Department of Atmospheric and Oceanic Sciences, McGill University
- 2Observations-Based Research Section, Environment and Climate Change Canada
- 1Department of Atmospheric and Oceanic Sciences, McGill University
- 2Observations-Based Research Section, Environment and Climate Change Canada
Abstract. Measuring atmospheric conditions above convective storms is challenging. This study finds that the uncertainties in cloud properties near the top of deep convective clouds have a non-negligible impact on the TOA infrared radiances which cannot be fully eliminated by adopting a slab-cloud assumption. To overcome this issue, a synergetic retrieval method is developed. This method integrates the infrared hyperspectral observations with cloud measurements from active sensors to retrieve atmospheric temperature, water vapor, and cloud properties simultaneously. Using an observation system simulation experiment (OSSE), we found that the retrieval method is capable of detecting the spatial distribution of temperature and humidity anomalies above convective storms and reducing the root-mean-square-errors in temperature and column integrated water vapor by more than half.
Jing Feng et al.
Status: closed
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RC1: 'Comment on amt-2020-518', Quentin Libois, 31 Mar 2021
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2020-518/amt-2020-518-RC1-supplement.pdf
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AC2: 'Reply on RC1', Jing Feng, 14 Jul 2021
Thank you, Quentin Libois, for your detailed and thoughtful comments. Following your comment, we have greatly expanded the abstract and introduction, added necessary description about the forward model, and expanded the discussion on cloud-induced uncertainties.Â
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AC2: 'Reply on RC1', Jing Feng, 14 Jul 2021
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CC1: 'Comment on amt-2020-518', S.G. DeSouza-Machado, 07 Apr 2021
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2020-518/amt-2020-518-CC1-supplement.pdf
- AC1: 'Reply on CC1', Jing Feng, 14 Jul 2021
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RC2: 'Comment on amt-2020-518', Anonymous Referee #3, 02 Jul 2021
This paper describes a method of improving the retrieval of temperatures and ice specific humidy using hyperspectral infrared measurements with added synergetic measurements of cloud effective radius and ice water content (IWC). A cloud resolving NWP model is used to generate a scene which acts as the "truth", which is input to MODTRAN for simulating the infrared radiances. The retrieval algorithm used two assumptions. One is the slab assumption which use the simulated radiances as inputs and the other uses synegetic dataset including IWC and cloud effective radius as synthetic measurements. Improvements have been found by adding these synergetic inputs.
The paper is well written except that there are minor typos here and there. For example, Fig. 6 refers "row" as column. Line 216 use um instead of μm for micron. I suggest that the authors do a thorough proof-reading and eliminate these typos.
The abstract is not as informative as I would see from a high quality paper. It merely mentioned that the algorithm is able to detect the spatial distribution of temperature and humidity anomalies above convective storms. Some more quatative results should be summarized here.
Overall, I recommend the publication of this paper with the minor revision incoporated.
- AC3: 'Reply on RC2', Jing Feng, 14 Jul 2021
Status: closed
-
RC1: 'Comment on amt-2020-518', Quentin Libois, 31 Mar 2021
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2020-518/amt-2020-518-RC1-supplement.pdf
-
AC2: 'Reply on RC1', Jing Feng, 14 Jul 2021
Thank you, Quentin Libois, for your detailed and thoughtful comments. Following your comment, we have greatly expanded the abstract and introduction, added necessary description about the forward model, and expanded the discussion on cloud-induced uncertainties.Â
-
AC2: 'Reply on RC1', Jing Feng, 14 Jul 2021
-
CC1: 'Comment on amt-2020-518', S.G. DeSouza-Machado, 07 Apr 2021
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2020-518/amt-2020-518-CC1-supplement.pdf
- AC1: 'Reply on CC1', Jing Feng, 14 Jul 2021
-
RC2: 'Comment on amt-2020-518', Anonymous Referee #3, 02 Jul 2021
This paper describes a method of improving the retrieval of temperatures and ice specific humidy using hyperspectral infrared measurements with added synergetic measurements of cloud effective radius and ice water content (IWC). A cloud resolving NWP model is used to generate a scene which acts as the "truth", which is input to MODTRAN for simulating the infrared radiances. The retrieval algorithm used two assumptions. One is the slab assumption which use the simulated radiances as inputs and the other uses synegetic dataset including IWC and cloud effective radius as synthetic measurements. Improvements have been found by adding these synergetic inputs.
The paper is well written except that there are minor typos here and there. For example, Fig. 6 refers "row" as column. Line 216 use um instead of μm for micron. I suggest that the authors do a thorough proof-reading and eliminate these typos.
The abstract is not as informative as I would see from a high quality paper. It merely mentioned that the algorithm is able to detect the spatial distribution of temperature and humidity anomalies above convective storms. Some more quatative results should be summarized here.
Overall, I recommend the publication of this paper with the minor revision incoporated.
- AC3: 'Reply on RC2', Jing Feng, 14 Jul 2021
Jing Feng et al.
Jing Feng et al.
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