RTTOV-gb – adapting the fast radiative transfer model RTTOV for the
assimilation of ground-based microwave radiometer observations

De Angelis, Francesco; Cimini, Domenico; Hocking, James; Martinet, Pauline; Kneifel, Stefan

doi:https://doi.org/10.5194/gmd-9-2721-2016

Articles | Volume 9, issue 8

https://doi.org/10.5194/gmd-9-2721-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-9-2721-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 8

Development and technical paper

|

19 Aug 2016

Development and technical paper |

| 19 Aug 2016

RTTOV-gb – adapting the fast radiative transfer model RTTOV for the assimilation of ground-based microwave radiometer observations

Francesco De Angelis, Domenico Cimini, James Hocking, Pauline Martinet, and Stefan Kneifel

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Final revised paper (published on 19 Aug 2016)
Preprint (discussion started on 09 May 2016)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Review of "RTTOV-gb - Adapting the fast radiative transfer model RTTOV for the assimilation of groung-based microwave radiometer observations" by De Angelis et al.', Anonymous Referee #1, 27 Jun 2016
- AC1: 'Reply to Referee #1', Francesco De Angelis, 30 Jun 2016
  - AC3: 'Modification to "Reply to Referee #1"', Francesco De Angelis, 14 Jul 2016
RC2: 'Review of RTTOV-gb', Anonymous Referee #2, 04 Jul 2016
- AC2: 'Reply to Referee #2', Francesco De Angelis, 14 Jul 2016

Peer-review completion

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

AR by Francesco De Angelis on behalf of the Authors (14 Jul 2016) Author's response Manuscript

ED: Publish subject to technical corrections (27 Jul 2016) by Klaus Gierens

AR by Francesco De Angelis on behalf of the Authors (28 Jul 2016) Author's response Manuscript

Short summary

Ground-based microwave radiometers (MWRs) offer to bridge the observational gap in the atmospheric boundary layer. Currently MWRs are operational at many sites worldwide. However, their potential is largely under-exploited, partly due to the lack of a fast radiative transfer model (RTM) suited for data assimilation into numerical weather prediction models. Here we propose and test an RTM, building on satellite heritage and adapting for ground-based MWRs, which addresses this shortage.