Triple Collocation of Ground-, Satellite- and Land Surface Model-Based Surface Soil Moisture Products in Oklahoma Part II: New Multi-Sensor Soil Moisture (MSSM) Product

Round 1

Reviewer 1 Report

Based on the method of blending multisource soil moisture products in Oklahoma, this study identified the importance of incorporating in-situ soil moisture into soil moisture blending, and quantified the impact of different weighting schemes on soil moisture blending. There are some concerns that the authors should address before it can be considered for publication.

(1) I suggest the authors further clarify the significance of this study in the introduction. For example, the cons of in-situ measurements and their inter (and extra-) polations, remote sensing observations, and land surface model should be briefly described in this study.

(2) In order to evaluate the performance of multi-sensor surface soil moisture over different land cover types, the national land cover dataset (2016) product was used in this study. However, the land use/cover is dynamic, especially for a long study period. How the author considers the impact of land cover change on the results?

(3) For the methodology part (3.1), the authors should focus on describing the main methods and steps, rather than describing the shortcomings of the research methods they used. The deficiencies should be described in the introduction.

(4) Some references are suggested to be added in the MSSM product assessment (3.3) part.

(5) For the daily time series intercomparison part (4.2.3), "Figure 8 displays a daily time series intercomparison of the four study products for an example period (August of 2016) intentionally selected to include several storm and inter-storm events". What is the basis for the selection of this time period, and whether the results obtained in this way are accurate？

(6) In order to further highlight the innovation of this article, it is better to compare the results of this study with other studies.

(7) In the limitation discussion part, the authors should clarify the limitation or uncertainty of data and methods in this study. For example, the land cover change may affect surface soil moisture (Jiang et al., 2015; Shen et al., 2020) in this study.

Assessing the impacts of urbanization-associated land use/cover change on land surface temperature and surface moisture: A case study in the midwestern United States. Remote Sensing, 2015, 7: 4880-4898.

Marshland loss warms local land surface temperature in China Geophysical research letters, 2020, 47: e2020GL087648.

Author Response

Please see attached document.

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Authors,

The publication is pleasant to read, the introduction to the subject is sufficient and the data employed are interesting and very important from the point of view of possible hydroclimatic analyzes that can be carried out in the study area in the future. Such a large and valuable set of data collected within the operating observation network offers much more opportunities than presented in the publication. I have two main remarks:
Line 92: Do the Authors know what made a given station stand in a given place? If so, I think it's worth mentioning. The map suggests the stations are in different land cover types but the map resolution do not allow to check it. Please provide a very short description.
Figure 2 and 7. Unfortunately, I perceive a certain problem with this map and Figure 7 because it does not correspond to the spatial variability of the climate in the state of Oklahoma. Thus, I don't think it's a good choice for analysis.The map represents counties and not the actual variability of climate conditions affecting soil moisture. Therefore, it is difficult to evaluate the results with this in mind. Rather, I suggest using/checking (additionally) at least products like a multi-year average annual precipitation map and a digital terrain model or even combine them in next step with vegetation and/or soil map variability.
One quick look at the maps on the web (Oklahoma Meteorological Survey) was enough to see that precipitation has clear spatial pattern and follows the DEM. I think it is worth and important to take into account spatial distribution of precipitation in analysis not or not only county borders. I think Authors should enhance the research and perform such additional analysis. The results combined with the variability of vegetation and soil types will allow to better assess the accuracy of the models and conclude on the causes of larger/smaller errors within the analyzed area. In my opinion the analysis, description of the results, discussion and final conclusions need to be enhanced. 

Kind regards,
Reviewer

Author Response

Please see attached document

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The authors have addressed all my concerns. I suggest accept this paper in its present form.