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Peer-Review Record

A New 32-Day Average-Difference Method for Calculating Inter-Sensor Calibration Radiometric Biases between SNPP and NOAA-20 Instruments within ICVS Framework

Remote Sens. 2021, 13(16), 3079; https://doi.org/10.3390/rs13163079
by Banghua Yan 1,*, Mitch Goldberg 2, Xin Jin 3,4, Ding Liang 3, Jingfeng Huang 3,4, Warren Porter 3,4, Ninghai Sun 3, Lihang Zhou 5, Chunhui Pan 6, Flavio Iturbide-Sanchez 1, Quanhua Liu 1 and Kun Zhang 3
Reviewer 1: Anonymous
Reviewer 2:
Remote Sens. 2021, 13(16), 3079; https://doi.org/10.3390/rs13163079
Submission received: 23 June 2021 / Revised: 16 July 2021 / Accepted: 19 July 2021 / Published: 5 August 2021

Round 1

Reviewer 1 Report

A new statistical method for estimating the calibration biases by calculating a 32-day average difference (32D-AD) of radiometric measurements between the same instrument onboard two satellites is proposed in this paper. This method establishes a control scheme using thresholds to remove high daily emissions, and carries out Radiative Transfer Modeling. The efficiency of the method is shown when applied to assess calibration radiometric biases between sensors for four instruments on board SNPP and NOAA-20. Interesting results were obtained on the detection of solar invasion anomalies, on the features of the zonal mean deviations of the calibration between the sensors.

There are comments on the article.

As presented, the manuscript is more consistent with the report on the grant than the scientific article. The manuscript is large in volume and overloaded with insignificant or known details. For example, Figure 1 can be found from other sources. In the opinion of the reviewer, without prejudice to understanding, the text of the article can be shortened.

The article presents new significant results. Undoubtedly, it will be of interest to specialists in remote sensing and, after minor revision, can be published in the Remote Sensing MDPI.

Author Response

Thank the reviewer’ great comments. We agree that the manuscript is large in volume. One reason is that the principle of the method has to be validated against Sensor Data Record data from four sensors. The validation of the new method is also conducted by several existing methods. The old version of Figure 1 was provided in a few conference presentations and in the ICVS web site, although the new version is not shown in the web site or presentation. However, neither the old or the new version of Fig. 1 has not been given in an official document or peer-reviewed manuscript so far, which causes a difficulty to cite the ICVS in a peer-reviewed manuscript. The operational monitoring of the 32D-AD results for the selected sensors is being implemented into the ICVS. Due to this significance, we think it is reasonable to keep this figure in the manuscript.  However, we do agree with that it is necessary to remove some insignificant or known details. Therefore, in the revised version, ‘Appendix B’ is removed and the equations beyond the diagrams in Appendix C (Appendix B in the revised version) are removed too. Thanks a lot.

Reviewer 2 Report

The authors discuss a new statistical method based on the 32-day averaged difference of radiometric measurements to assess globally and zonally averaged inter-sensor calibration radiometric biases. The procedure has been applied to SNPP and NOAA-20 instruments. The technique extends the well-known double-difference (DD) method, whose application is limited mainly to polar regions because of the need to exploit almost simultaneous measurements. I have found the manuscript well written and presented and informative; therefore, I think it can be published as-is.

Author Response

 Thank the reviewer’s great comments!

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