the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 31 May 2024
An Improved Geolocation Methodology for Spaceborne Radar and Lidar Systems
Abstract. Geolocation and co-registration methodologies are essential for the accurate interpretation of observations from spaceborne remote sensors. In preparations for EarthCARE, here, we refine the definition of these techniques and present various examples of geolocation assessments. The geolocation methods build upon earlier work, however, introduces several improvements that have increased the reliability of the geolocation accuracy. The EarthCARE active sensors geolocation methods use coastlines and significant elevation gradients, in both statistical and numerical ways. The effectiveness of the proposed geolocation methods was tested using the extensive record of CloudSat and CALIPSO observations. The EarthCARE active sensors geolocation methods were effective in identifying and correcting a short period of CloudSat observations when the star tracker was not operating properly. In addition, the geolocation methods were able to reproduce the excellent geolocation record of the CloudSat and CALIPSO missions.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(2498 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2498 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1546', Anonymous Referee #1, 09 Aug 2024
General Comments:
This preprint introduces a geolocation method, occasionally referred to as a tool, designed for application to EarthCARE. This method draws upon the experience gained from the observations and methods developed for CloudSat and CALIPSO. The geolocation method previously applied to CloudSat was based on a Digital Terrain Model (DTM) that was coarser than the ASTER DEM/WBD products used in this preprint. When applied to the CloudSat/CALIPSO datasets, the proposed method demonstrates strong performance, and the quantification of the pointing error is more precise. Examples of the application for EarthCARE geolocation are provided, though a more stringent performance indication likely requires actual data. Nevertheless, optimal areas for applying the geolocation methods within EarthCARE are defined. The manuscript is well-written and easy to understand, though some points require clarification.
Specific Comments:
- Fig. 1: It would be beneficial to include a comparison with the Digital Elevation Model (without convolution) in Fig. 1c.
- Line 175: Figure 3 displays the points suitable for applying EarthCARE geolocation. The selection criteria are vaguely described in the manuscript. A more detailed description of the criteria used for selecting these points, along with their quantity, is recommended.
- Line 281: Please provide the number of overpasses that will be available during the 3-month period.
- Line 400: Please specify the name of the processors in the EarthCARE processing system that utilize the geolocation tool.
- Line 404: The text mentions the application of EarthCARE co-registration, which is not described in the preprint. Is there a reference that describes the co-registration to be used in EarthCARE?
Citation: https://doi.org/10.5194/egusphere-2024-1546-RC1 - AC2: 'Reply on RC1', Bernat Puigdomènech Treserras, 30 Aug 2024
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RC2: 'Comment on egusphere-2024-1546', Anonymous Referee #2, 18 Aug 2024
- AC1: 'Reply on RC2', Bernat Puigdomènech Treserras, 30 Aug 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1546', Anonymous Referee #1, 09 Aug 2024
General Comments:
This preprint introduces a geolocation method, occasionally referred to as a tool, designed for application to EarthCARE. This method draws upon the experience gained from the observations and methods developed for CloudSat and CALIPSO. The geolocation method previously applied to CloudSat was based on a Digital Terrain Model (DTM) that was coarser than the ASTER DEM/WBD products used in this preprint. When applied to the CloudSat/CALIPSO datasets, the proposed method demonstrates strong performance, and the quantification of the pointing error is more precise. Examples of the application for EarthCARE geolocation are provided, though a more stringent performance indication likely requires actual data. Nevertheless, optimal areas for applying the geolocation methods within EarthCARE are defined. The manuscript is well-written and easy to understand, though some points require clarification.
Specific Comments:
- Fig. 1: It would be beneficial to include a comparison with the Digital Elevation Model (without convolution) in Fig. 1c.
- Line 175: Figure 3 displays the points suitable for applying EarthCARE geolocation. The selection criteria are vaguely described in the manuscript. A more detailed description of the criteria used for selecting these points, along with their quantity, is recommended.
- Line 281: Please provide the number of overpasses that will be available during the 3-month period.
- Line 400: Please specify the name of the processors in the EarthCARE processing system that utilize the geolocation tool.
- Line 404: The text mentions the application of EarthCARE co-registration, which is not described in the preprint. Is there a reference that describes the co-registration to be used in EarthCARE?
Citation: https://doi.org/10.5194/egusphere-2024-1546-RC1 - AC2: 'Reply on RC1', Bernat Puigdomènech Treserras, 30 Aug 2024
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RC2: 'Comment on egusphere-2024-1546', Anonymous Referee #2, 18 Aug 2024
- AC1: 'Reply on RC2', Bernat Puigdomènech Treserras, 30 Aug 2024
Peer review completion
Journal article(s) based on this preprint
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Bernat Puigdomènech Treserras
Pavlos Kollias
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2498 KB) - Metadata XML