Please see the attached pdf file for comments.

This study explores the variability of shallow convective clouds and precipitation in Houston, Texas, during the summer, utilizing data from the TRACER and ESCAPE field campaigns. Through a combination of geostationary satellite and ground-based radar observations over a 250x250 km domain, the authors identify four diurnal modes of shallow cloud fraction and analyze their spatial and temporal patterns. The study highlights the influence of land-ocean contrasts, sea breeze circulations, and local meteorology on shallow cloud properties, contributing to the understanding of cloud behavior in complex urban and coastal environments. Overall, while the study makes a contribution to understanding shallow cloud behavior in a complex urban and coastal environment, its impact is somewhat diminished by insufficient attention to physical mechanisms and scientific discussions. Addressing these issues would enhance the clarity and applicability of the findings.

Specific comments:

1. The physical meaning of the identified regimes of shallow cumulus clouds is insufficiently addressed. While the clustering analysis identifies distinct modes, there is a lack of detailed discussion on their underlying drivers or implications for broader meteorological processes. It should explain more about the underlying differences in terms of the formation and mechanisms of different regimes.

2. The variability of cloud fraction and precipitation is not thoroughly explained. Although the study presents statistical patterns, it does not adequately explore the mechanisms responsible for observed spatial and temporal differences, particularly in the context of different meteorological factors such as humidity, circulation, advection, etc.

3. Under high precipitable water conditions, radar signal attenuation may impact cloud and precipitation detection, introducing uncertainties not discussed in the study. For instance, ARSCL faces limitations such as insect contamination and biased cloud-top heights, which could affect the reliability of the results.

4. The key differences between the ESCAPE and TRACER campaigns are not clearly articulated. Considering their different objectives, it is helpful to explain how differences in shallow cloud backgrounds, formation processes, and meteorology between the two campaigns may influence the results for better contextualization.

Minor comments:

1. The analysis relies on a single observational location (AMF1) for meteorological measurements, which may not fully capture the variability across the domain. Briefly addressing the spatial scale of its representativeness would be helpful.

2. The lack of a sensitivity analysis for the k-means clustering approach may introduce uncertainties in the identified modes.

3. The manuscript would benefit from more discussion on meteorology, sea breeze circulations, and potential urban influences, complementing the statistical results of clouds and precipitation.