The manuscript by Mirones et. al., focuses on the methodology for calibrating the TRMM precipitation data. The authors used Multi-method approach for data from five observational stations. The major concerns from my perspective include: while the results showed better effects of the adaptive calibration method based on five station, the limited representation of the five stations is not enough to support the generalization of method to entire low-middle latitudes. Second, what are the deficiencies of TRMM precipitation data, and how the adaptive method resoled the problem targeted to those deficiencies. Third, how the method performs over the entire low and middle latitudes.

A minor commend:

Fig. 3, Do the horizontal axes represent RF scores?

An “adaptive calibration method”, which is based on five weather types to take advantage of the complementary strengths for four methods (i.e., scaling, empirical quantile mapping (eQM), parametric quantile mapping (pQM), and generalized Pareto distribution quantile mapping (gpQM)), was proposed in this paper for calibrating the TMPA product. The validation of the “adaptive calibration method” was executed according to comparison with eQM, pQM, gpQM, scaling, and unweighted method. Although TMPA is a good precipitation product and has been widely used in various fields, it has stopped updating and its successor IMERG has higher spatiotemporal resolution and accuracy. I believe that choosing TMPA as a calibration object does not make much sense. In addition, the primary drawback of this manuscript is that the “adaptive calibration approach” was not clearly explained in the manuscript, such as how to classify the weather types, why selecting those 10 metrics and how to obtain their optimal weights. More importantly, the novelty of the manuscript was not well represented. Therefore, I cannot suggest the acceptance of this manuscript at the current stage.

Major comments:

1. The TMPA product was used as a calibration object. The reasons for choosing TMPA should be provided. In particular, its successor. i.e., IMERG, has been released to the public and is better than TMPA in multiple aspects such as resolution, covering period, and quality. Moreover, the TMPA products have stopped updating. I am confused that this study selected TMPA instead of IMERG.
2. Methodology: the method section is one of the important content, but the current descriptions are too concise. Based on five weather types, the paper proposed an “adaptive calibration approach” to take advantage of the complementary strengths for four methods and further improve the accuracy of the TMPA product. However, the weighting method was not described well, especially its standards and rules. In addition, could the weighting method used in this paper provide optimal weights? In other words, whether this weighting method can maximize the advantages of different error adjustment methods. In addition, the classification of weather types was not provided. I understand the authors gave the related literature, but this is not enough. A detailed classification scheme should be provided as it is an important component for the “adaptive calibration approach”.
3. Results and discussion: The analysis has many subjective descriptions, which is not recommended for scientific writing. I suggest the analysis provides some specific metric values and strengthens in-depth interpretations on the results.

Other comments

1. Lines 36-37: this conclusion is true only in some areas, not all regions. I suggest revising this sentence to avoid misleading the readers.
2. The differences between the four methods (i.e., scaling, eQM, pQM, and gpQM) should be provided and discussed, especially for their advantages and limitations. Due to their respective advantages, the adaptive calibration approach, which could consider their advantages, is necessary. Meanwhile, the adaptive calibration approach is not the best in all cases, which is worth analyzing.
3. Weather typing is important in this study. So, which five types? The description lacks detail.
4. Lines 159-161: could the authors provide some literature to support this point?
5. Lines 161-162: can the authors provide some study results (e.g., specific metric values) to support this point？
6. Lines 166-167: what results?
7. Why did the adaptive calibration method not improve the accuracy at the Rarotonga and Nu’uuli stations?