This paper presents significant new material by introducing the SDUST2022GRA, a new 1 arcmin global marine gravity anomaly model, along with various comparisons to state-of-the-art global gravity field models and in situ observations. The authors leverage radar and laser altimetry to harness the strengths of individual missions enabled by advanced altimeter technologies. The beam pair configuration of ICESat-2, which allows for the determination of cross-track height slopes, offers an opportunity to enhance the precision and spatial resolution of the gravity anomaly model. This article provides valuable insights into gravity anomaly recovery using along-track and cross-track data. Overall, the paper introduces significant advancements in the field, but addressing the following concerns would enhance its clarity and impact.

Concerns:

Section 4.1 emphasizes the critical role of altimeter data downsampling in mitigating high-frequency noise, which is essential for ensuring data accuracy and reliability. For radar altimeter data, a 1 Hz sampling rate is typically employed. The authors note that ICESat-2 laser altimeter data exhibit varying length scales, ranging from 70 m to 7 km. However, the downsampling method applied to the ICESat-2 laser altimeter data is not specified. Clarification on this method is essential, as it significantly impacts the quality of the SDUST2022GAR model.

The geoid height is derived from SSH observations, with the dynamic topography removed as the non-geoidal signal. The authors use the MDT_CNES_CLS18 model with a grid resolution of 7.5 arcmin to remove this signal. Given that the average along-track ground distance of altimeter data is about 7 km (1 arcmin), it is crucial to understand how the removal value from MDT_CNES_CLS18 is determined. Detailed methodology on this aspect would enhance comprehension.

Filtering is crucial for the fusion of multi-altimeter data. The filter radius for along-track radar and laser altimeter data is noted as 7 km. However, details regarding the filter radius and its application are missing. Is the filtering applied in the along-track direction or in the spatial domain? Is the purpose to reduce spatial high-frequency error or to mitigate the temporal SSH signal? Clarification on these points is essential for a thorough understanding and accurate interpretation of the results.

Section 3.2 outlines the steps for determining cross-track geoid gradients. However, merely listing the processing steps can lead to ambiguity. For instance, the phrase “one track with good observation is selected as the reference altimeter data” is unclear. Does "good" refer to accuracy or the number of observations? Providing the corresponding formula or a detailed processing flowchart would greatly improve clarity.

The precision of the gravity anomaly model is assessed by comparing it to shipborne gravity anomalies. While the RMS is 4-5 mGal in global oceans and low-middle latitudes, it approaches 10 mGal in high-latitude regions. An explanation for the lower precision in high-latitude regions is necessary to understand this discrepancy.

Spatial resolution is a crucial index of the gravity anomaly model. Cross-spectral analysis is typically used to determine the wavelength of the model by comparing it to shipborne gravity. The paper derives three results from shipborne gravity, yet the wavelengths from the gravity anomaly model differ. An explanation for this variance and what determines the spatial resolution of the model would be beneficial.

Minor edits:

I recommend that the authors improve the clarity and readability of the manuscript by refining the English language usage

Line 17: “across-track direction” should be “cross-track direction”.

Line 115: SARAL/Altika is operate in Ka-band not Ku-band, please correct it.

Line 146: “a quadratic polynomial was used to correct long wavelength system error”. This statement is not accurate. The quadratic polynomial is used for shipborne gravity from each cruise in order to correct system bias relative to the gravity reference field.

Line 252: “the maximum distance of along-track …”, what is the maximum distance?

Line 265: In Table 5, please specify the unit of geoid gradients?

Line 369: The percentage contribution formula is not explained clearly about the use of the variable RMS. Please add an description.

Line 385: In Table 14, the regions A, B, C, D, E, F are not mentioned in the text. please specify the used region.

This paper derived the global marine gravity model, SDUST2022GRA, by combining altimeter data from nadir-looking satellites and from ICESat-2. The cross-track geoid gradients were determined using the three-pair laser beams of  ICESat-2,  a capability not available from nadir-looking altimeters. These cross-track geoid gradients, which are primarily oriented in the east-west direction, are instrumental in improving the accuracy of the east-wast components of geoid gradients, thereby enhancing the marine gravity model.  This paper is interesting and worth publishing after addressing the key points identified herein.



I have some main questions regarding the determination of cross-track geoid gradients from ICESat-2:

(1) Lines 210-215: When determining the cross-track geoid gradients, the authors only used the data with 'the closest time'. Although time-related signals affect ICESat-2 SSHs, the time for the SSHs from the ICESat-2's three-pair beams is close. Ignoring the time factor may yield more results.



(2) Figure 3 and Table 5: Three types of cross-track geoid gradients (g12, g23, and g13) were obtained (Fig. 3). The accuracy of g13 was much higher than that of g12 and g23 (Table 5). Therefore, only g13 was used to derive the marine gravity model. However, the differences in the STD for the three types of geoid gradients are due to the distance rather than the accuracy of ICESat-2 SSHs. A more reasonable explanation should be provided.



The detailed comments are provided in the attachment.