| 14 Nov 2025
EarthCARE Cloud Profiling Radar Observations of the Vertical Structure of Marine Stratocumulus Clouds
Abstract. Launched in May 2024, the EarthCARE Cloud Profiling Radar (EC-CPR) provides enhanced sensitivity, finer vertical and horizontal resolution, and greatly reduced surface clutter contamination compared to its predecessor, the CloudSat's CPR (CS-CPR). These improvements enable more accurate detection and characterization of the vertical structure of marine low-level clouds. This study presents the first year of EC-CPR observations of stratocumulus (Sc) clouds over the Southeast Pacific and Southeast Atlantic Oceans.
The analysis of EC-CPR clear-sky profiles and comparisons with airborne radar data confirm that surface clutter is effectively suppressed above 0.5 km. Comparisons with CS-CPR data from 2007–2008 show that EC-CPR detects nearly double the Sc amount relative to CS-CPR in the regions of study. When a columnar maximum reflectivity (ZMAX) threshold of −15 dBZ is used to flag raining profiles, CS-CPR is found to underestimate rainfall occurrence by up to ~ 20 % relative to EC-CPR.
Using a steady-state one-dimensional drizzle model, the impact of the point target response (PTR) on EC-CPR reflectivity profiles in Sc clouds is examined. PTR causes vertical stretching of radar-detected cloud boundaries, resulting in an overestimation of cloud thickness by approximately 0.4–0.5 km in drizzling clouds. Additionally, PTR induces parabolic shaping of reflectivity profiles regardless of drizzle presence, complicating the distinction between drizzle-free and drizzle-containing clouds. These findings underscore the need for cautious interpretation of radar reflectivity profiles and suggest the incorporation of additional constraints, such as Doppler velocity and path-integrated attenuation (PIA) to improve future drizzle detection strategies.
General Comments:
This paper presents some early performance characteristics of the EarthCARE cloud profiling radar with regard to detection of of hydrometeors in marine stratocumulus clouds. EarthCARE performance is shown to be a notable advance over CloudSat in respect to detection sensitivity and surface clutter suppression. Marginal improvements in the detection of precipitation (drizzle) are shown as well. The paper is timely - EarthCARE is new and a good reference specific reference relative to StCu is warranted. The presentation is generally of a high quality and the methods are appropriate. I only have a few minor comments listed below to be addressed.
Specific comments:
Line 240: 2.5 km should be 1.7 km. See Tanelli et al. 2008, Table 1.
Line 128: add ‘the’ before ‘model’.
Subsection numbering is messed up. There are two 2.1 and two 2.3 sections but no 2.2!
Figure 4: I think you could probably make this figure more compelling. I think it would help to add both an EarthCARE and CloudSat example of a thin non-precipitating cloud with cloud top at or below 1 km. There are lots of examples where CloudSat has only one or two bin of reflectivity where EarthCARE might see significantly more detail. I think you envision your panel A as showing a marginal cloud but this is actually a fairly thick StCu.
Line 220: note that this field campaign included coordinated under flights of EarthCARE here.
Lines 240-247: This paragraph describes model results. Does it belong here? I would put this back in your section 2.3 (the one that discuss the model results.
Lines 248 – 276. You might want to include a sentence or two before this discussion to describe why you are showing these results. I think you are trying to identify a multi-variable relationship with precipitation that goes beyond a simple reflectivity threshold. I also think your results show that this is hard to do and there is likely inherent uncertainty in cloud/precipitation identification. Maybe add a little discussion of that fact.
Line 280: What CloudSat years. The MDS changed by about 6 dB over the course of the mission which would significantly influence the pdf’s in figures 8 and 9.
Figure 9: I’m confused about two aspects of this figure. The CS pdf’s don’t show detections smaller than about -26 dBZ (related to question above). There is no reason that EarthCARE should detect more -15 dBZ clouds than cloudsat at altitudes above 750 m – but panels b and c show this. Why? Is it just that the time period sampled is different?
Line 320: So CS misses 20% of the EC precip detections at this height bin. Can you also add for reference what fraction of EC radar shots contain precip?
Section 3.2: You should add a bit more analysis to this section. First it would be useful to include the total fraction of radar shots with a StCu hydrometeor detection in each of the two regions for both EarthCARE and CloudSat. Second I would add a plot that shows the vertical profile of the hydrometeor detection fraction from each sensor.
Referencing in the intro is a little thin. Here are some (not a comprehensive list) to add:
Tanelli et al., "CloudSat's Cloud Profiling Radar After Two Years in Orbit: Performance, Calibration, and Processing," in IEEE Transactions on Geoscience and Remote Sensing, vol. 46, no. 11, pp. 3560-3573, Nov. 2008, doi: 10.1109/TGRS.2008.2002030
Wood, R., T. L. Kubar, and D. L. Hartmann, 2009: Understanding the Importance of Microphysics and Macrophysics for Warm Rain in Marine Low Clouds. Part II: Heuristic Models of Rain Formation. J. Atmos. Sci., 66, 2973–2990, https://doi.org/10.1175/2009JAS3072.1.
Wood, R., D. Leon, M. Lebsock, J. Snider, and A. D. Clarke (2012), Precipitation driving of droplet concentration variability in marine low clouds, J. Geophys. Res., 117, D19210, doi:10.1029/2012JD018305.
L'Ecuyer, T. S., W. Berg, J. Haynes, M. Lebsock, and T. Takemura (2009), Global observations of aerosol impacts on precipitation occurrence in warm maritime clouds, J. Geophys. Res., 114, D09211, doi:10.1029/2008JD011273.
Mülmenstädt, J., Salzmann, M., Kay, J.E. et al. An underestimated negative cloud feedback from cloud lifetime changes. Nat. Clim. Chang. 11, 508–513 (2021). https://doi.org/10.1038/s41558-021-01038-1