A high-level cloud detection method utilizing the GOSAT TANSO-FTS water vapor saturated band

Eguchi, Nawo; Yoshida, Yukio

doi:https://doi.org/10.5194/amt-12-389-2019

Articles | Volume 12, issue 1

https://doi.org/10.5194/amt-12-389-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-12-389-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 1

Research article

|

18 Jan 2019

Research article |

| 18 Jan 2019

A high-level cloud detection method utilizing the GOSAT TANSO-FTS water vapor saturated band

Nawo Eguchi and Yukio Yoshida

Download

Final revised paper (published on 18 Jan 2019)
Preprint (discussion started on 12 Jun 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Severe lack of clarity.', Anonymous Referee #1, 09 Jul 2018
- AC1: 'Reply for comments of Anonymous Reviewer #1', Nawo Eguchi, 14 Nov 2018
RC2: 'Major revisions are needed', Anonymous Referee #2, 30 Jul 2018
- AC2: 'Reply for comments of Anonymous Reviewer #2', Nawo Eguchi, 14 Nov 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Nawo Eguchi on behalf of the Authors (14 Nov 2018) Manuscript

ED: Referee Nomination & Report Request started (20 Nov 2018) by Piet Stammes

RR by Anonymous Referee #1 (05 Dec 2018)

Suggestions for revision or reasons for rejection

The quality of the paper improved considerably after revision. I recommend publishing subject to technical corrections:

P1,L1: cloud -> clouds
P1,L5: with -> with the
P1,L6: cycle -> repeat cycle for a pointwise geolocation pattern
P1,L11: providing -> enabling
P1,L12: retrieval -> retrievals
P1,L16: the optical thickness of cirrus clouds -> the optical thickness of regularly observed cirrus clouds
P1,L16: Despite … clouds, -> (remove)
P1,L17-20: Phrase 2 somehow contradicts phrase 1.

P2,L4: cloud -> clouds
P2,L10: but has -> but it has
P2,L16: signal of -> signal oft he
P2,L17: channel -> channels
P2,L18: test -> tests
P2,L21: TANSO-FTS constructed by the cluster analysis and to validate
the detected clouds against the -> TANSO-FTS. The method is based on cluster analysis and it is validated by comparison against the

P4,L31(?strange line numbering): is absent -> are absent
P4,L4: is observed -> is indicative
P4,L29: meanl -> mean

P5,L35: at the out of the band-pass filter-> in the out-of-band-pass range
P5,L5: 10{-5} Is there units missing?

P6,L1: (2x) shorted -> sorted
P6,L9: middle latitudes -> mid-latitudes
P6,L24+25: Table1-> Table 1

P7,L14: observation has -> observations have

P8,L29: avoid error contamination -> avoid contamination
P8,L32: covers to detect -> covers

P9,L32: retrieval value -> retrieval
P9,second paragraph: I do not understand what you say. Do you mean that the present study helps the gas retrievals by providing an estimate for a priori cirrus optical thickness?
P9,third paragraph: Remove. OCO-2 does not cover the saturated water vapor bands. So, the method is not applicable.

Fig 1: schematics of spectral shape -> schematics of the radiative transfer effects
Fig 2: mention selected regions (black bars) in the caption
Fig 3: mention ordering in the caption

Hide

RR by Anonymous Referee #3 (13 Dec 2018)

ED: Publish subject to technical corrections (21 Dec 2018) by Piet Stammes

AR by Nawo Eguchi on behalf of the Authors (28 Dec 2018) Author's response Manuscript

Short summary

A detection method for high-level cloud, such as ice clouds, is developed using the water vapor saturated channels (2 μm) of the solar reflected spectrum observed by the TANSO-FTS on board GOSAT. The clouds detected by this method are optically relatively thin (0.01 or less) and located at high altitudes. Approximately 85 % of the results from this method for clouds with a cloud-top altitude above 5 km agree with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud classification.