General comments:

This paper analyzes the spatiotemporal variations in snow phenology on the Tibetan Plateau and elucidates the comprehensive effects of various influencing factors. It provides crucial insights for addressing climate change, hydrological cycles, and ecological balance issues in the context of global warming. The experimental design is well-structured and the result is complete. However, several issues still need to be clarified before being published in The Cryosphere. Further consideration is necessary regarding the selection of influencing factors, as well as the resolution and time delay effects of meteorological factors. Details and suggestions are given below.

Special comments:

1. Section 2.1: it is essential to add detailed information on the spatiotemporal distribution of snow cover in the Tibetan Plateau, as well as temperature and precipitation patterns.

1. Section 2.2: clearly states that spatiotemporal analysis in SP extends until 2021, but due to limitations in the data for influencing factors, the analysis is based on data up to 2018.

1. The accumulation and melting of snow can be influenced by various factors. In addition to the 13 factors mentioned in the manuscript, land surface temperature, soil characteristics (such as soil moisture), frozen soil, human activities, and other relevant factors can also affect snow cover variation. It is suggested to provide the analysis for these factors.

1. As far as I know, meteorological data with a spatial resolution of approximately 3 km is now available for the Tibetan Plateau (https://data.tpdc.ac.cn/zh-hans/data/44a449ce-e660-44c3-bbf2-31ef7d716ec7). It is suggested to use this data to analyze the impact of meteorology.

1. Meteorological data can exhibit a time delay effect on SP. For instance, temperatures may rise for several days before the actual snowmelt process starts. Consequently, relying solely on the annual average temperature for analysis is not entirely reasonable. Please try to explain this delay effect in the given context.

1. The authors have considered the impact of black carbon and similar factors; however, their influence does not seem significant. Please explain the reasons behind this, especially in light of previous studies indicating the importance of black carbon.

1. It is suggested to discuss the limitations of the study.

Minor revisions:

1. Line 113: There is a missing space between "2002" and "to."

1. Line 194: There is an extra "d" between "by" and "resampling."

1. Line 234: There is a missing space between "2.07%" and "of."

1. The slope labels for Figure 3a and Figure 3b are the same, but they appear to be inconsistent. Please double-check.

In this paper, the authors examine the spatiotemporal variability of the snow phenology over the Tibetan Plateau, based on MODIS satellite observations. The period covers 2002 to 2021.

The study focuses on snow onset, snow end date and snow cover days. It relies on an improved MODIS dataset, filled for temporal and spatial data gaps.   Governing factors, which can have both direct and indirect effects on the snow phenology through the interplay of the different variables are extracted by a Structure Model. It is found that the meterorological factors (temperature, precipitation) play the leading roles. However, the relative importance of temperature and precipitation shifts with elevation.

The study is detailed and comprehensive, and the article clearly written. It should prove a valuable to understand the snow cover variability over the Tibetan Plateau. I recommend the paper for publication provided the three main comments (essentially, discussion points) are addressed.

Main comments:

• It is a bit surprising that the “darkening of the snow” plays such a minor role, given the attention given to this issue in recent years. [e.g., W. Lau et al, Atmosphere 2018, 9(11),https://doi.org/10.3390/atmos9110438] . Are the findings consistent with earlier studies about this point? Is the  global BC emission dataset really relevant here since it is mostly the BC transported and deposited on the Tibetan Plateau that would matter ? Is the AOD dataset of sufficient quality and resolution over the area of interest?
• The precipitation data is at high spatial resolution, which was deemed important and explaining differences with respect to earlier studies. Yet, the precipitation data consists of monthly means. Is this sufficient to elicit the daily snow evolution required to estimate snow onset and end dates ?   Is there daily precipitation dataset that the authors could have used and could they test if it affect the results?
• I am a bit unclear on the longitude dependence of the results is it merely elevation that is folded in this dependency (to explain that different longitudes receive different amount of radiation, precipitation and so forth).

Minor comments:

• L 162: It is a bit unclear how the number 56 is derived. Number of stations times years with sufficiently long records ? Please spell out the details.
• L191: “owing to its valuable for unstable factor weights”. Unclear sentence.
• L288: The wording “temperature gradient” is misleading (also caption of Fig 8). It is actually the correlation as a function of temperature that is shown, not the temperature vertical or spatial gradient (which would have different units)
• L326 Unclear sentence and wording for “essential”: “proved consistently as essential  as elevation” (Is that what is meant here?)