Review of egusphere-2023-2410: Lifecycle of Updrafts and Mass Flux in Isolated Deep Convection over the Amazon Rainforest: Insights from Cell Tracking 

Summary: In this manuscript, the authors calculate a variety of statistics as a function of storm lifetime and season from a database of tracked convective cells from GoAmazon2014-15 observations. The authors present a commendable set of different methods, observations and statistics to provide additional insights about convective dynamics, how they vary as a function of storm lifecycle and season, and how their results fit in with recent results from their research group. Given the complexity of their analysis and dataset, there were many aspects of their analysis that warrant additional description and details to properly understand what their data sample represents and the subsequent results that are being presented. Similarly, many of the figures / analyses require additional descriptions to interpret and understand what is being presented. Therefore, while the work fits well within ACP’s focus and could add insights for understanding convective storm dynamics, I am not able to fully assess the science results without a better understanding of the methods.  

Major comments, questions, and/or concerns: 

Combining MAO data with storms. If a storm is within 20 km of the MAO site at any point in its lifecycle, the RWP data from MAO are used and attributed to a storm lifecycle stage based on the tracking. The average distance between the feature center and MAO site was 8.5 km, with 70% of feature positions being with 10 km of the MAO site (L252). Whether the storm updraft goes directly over the site versus if its center is ~10 km away from the site might make a significant difference in the RWP data (i.e., Z, W) that are being associated with the storm (i.e., profiles of Z and W at the center of the storm updraft region will be different from the edges of the storm). This seems like a large source of uncertainty that is not discussed. For example, are there biases in the distance of the updraft center to what was sampled by MAO with respect to the different lifecycle stages and seasons, and if so, how do these biases impact the results in the manuscript? Perhaps, showing Figure 1 as a heat map both for all storms and for storms at the different stages and seasons would help address this concern. 

 

Tracking storms with a coarse time-step. The authors focus on tracking isolated cells with a 12-minute radar data frequency at 2 km AGL. Could there be instances in the dataset where a storms dissipates, and a new one forms in similar location within the 12-minute time step, which is therefore tracked as a continuous storm? This seems like a large source of uncertainty that isn’t discussed. 

• Splits/mergers. What happens if a storm splits into two storms or merges with a different storm? Could these events be present in the dataset? This is related to concerns about the coarse time step for tracking, and how confident the authors can be about the determination of lifecycle stages. 
  
   

Using 2 km reflectivity. The authors use 2 km reflectivity for tracking and defining feature centers (L127). Why do they use this altitude, as opposed to a column maximum reflectivity that may be more accurately located with the updraft? Have they tried using different altitudes? For storms that may not be precipitating heavily, could the 2 km reflectivity with a 30 dBZ minimum threshold miss some of the beginning and ending stages of a storm lifetime? Similarly, for sheared storms, the 2 km location may not accurately describe the updraft location? 

 

p(w) seems to play an important role in the calculation of vertical mass flux and transport but is placed in the supplement without much discussion of how it is calculated and what it means. The authors do include a brief explanation of p(w), but it was not clear (L460-462). Can the authors spend more time describing this, given its importance in their calculations of mass flux? 

• L448-450: The authors state that 2 min periods of RWP observations are selected, and this is based on an assumed median updraft width of 1 km and average propagation speed. I do not understand how these variables are related to the 2 min period of RWP observations that are chosen, and found this sentence confusing? Can the authors make this clearer? 

• L452: The authors state that the average updraft/downdraft are weighted by the probability of sampling an updraft/downdraft during this time period (p(w)). However, the authors do not provide a clear description of how p(w) is calculated and place the figure of p(w) in the appendix (Figure S3). Can the authors provide a clearer description of how p(w) is calculated, and place this figure in the main manuscript, given its importance in calculating mass flux? 

Additional Methodology Clarifications:  

L164: How exactly are isolated convection (“ISO”) days determined? The authors point to Giangrande et al., 2023, but should provide the description here, given that this is defining the dataset used in this study. 

The authors state that isolated DCCs observed on “ISO” days are used for subsequent analysis. How are these isolated DCCs chosen? I am especially curious given that some 500 km2 storms seem to make it into their dataset (i.e., L274). 

It seems like many of the tracked storms last 3 or 4 time steps, but how can the authors classify these cells into their 5 lifecycle bins? 

How big is the radar domain and is this constrained by using 2 km CAPPIs, given that the radar beams will increase in altitude away from the radar?  

Can storms that initiate outside the radar domain move into the domain? If so, how would the authors know its lifecycle stage? 

“Average Z:” Many times in the manuscript the authors talk about average Z, and sometimes I was confused whether they are referring to the 2 km CAPPI Z used in the tracking, Z from the SIPAM radar at different altitudes, or the Z from the RWP observations. Can the authors make this clearer throughout the manuscript? 

L234: Does “at least 10 consecutive cloud echoes” mean consecutive in time or height?  

L366: When the authors use the term “Mature” DCCs (here and elsewhere in the manuscript), are the authors referring to data in lifetime bin 3 or data in lifetime bins 2-4, since bins 2 and 4 are defined as “early mature” and “late mature?” 

L556: The authors state that “time 0 represents the timestep when the indicated lifecycle stage of the DCC was identified using tobac.” I am having a hard time interpreting what this means. What if there are more than one radar timesteps for a given lifecycle stage? In that case, which time is used?  

L556: Is the equivalent potential temperature from MAO used even when cells are >20km away from MAO? If so, can what is happening at MAO be accurately related to the storm dynamics from the respective storm? 

L609: What Tb measurement is being used in this analysis? Is it the Tb measurement at MAO, at the feature center, or some average over the entire feature? 

Figure 1 (L762): Is this data for all tracked cells, or only the cells that go into the analyses presented in the remaining figures? 

Figure 2 (L768): Are “other DCC days” the same as ACE days as described in the text? If so, can the authors use the same terminology? 

Figure 2: (L770): Why is there a propagation speed threshold here of 0.5 m/s? I don’t believe this was mentioned in the text? 

Figure 3: For this (and all) boxplot figures, what is being shown? For example, do the bars that extend out represent the max/min values or some other value? A clearer description of that is being shown in the boxplots is necessary. 

Figure 16: Is this showing the mean or median equivalent potential temperature?  

L826: Is there a typo here? Should Figure 8 be Figure 13? 

There is an inconsistency of Figure S3 caption to what is stated in the figure image (within 1 min versus within 2 mins). 

Other Suggestions: 

L69: The NASA Investigation of Convective Updrafts Mission (e.g., van den Heever, 2021; Stephens et al., 2020 Prasanth et al., 2023) is planning to do this, so it would probably be good to mention this here, since this research has implications for this mission as well. 

Many of the results involve comparing results between the different seasons, which show up in different figures and makes comparing them quite difficult. Can the authors combine figures effectively, so that differences between results can be more clearly assessed? This is particularly the case for Figures 12-14 and 8-10. 

In terms of assessing whether their smaller sample had sampling biases, what is the reason for using the nearest neighbor distance as a metric, as opposed to metrics (i.e., reflectivities, ETHs) that may be more telling of the types/intensities of storms being sampled? It seems like it would be important to understand if their sample represents both weak and strong storms, compared to the possible population of storms? 

L457: For calculating mass flux, the authors assume the storm area is constant as a function of height, based on the area of the storm at 2 km AGL? It seems like the authors potentially have the data to validate this assumption (i.e., SIPAM radar data), or can find supporting literature for this assumption?  

This manuscript is already quite lengthy, and while all the analyses are interesting, perhaps some areas (i.e., S3.3) are less relevant to the authors focus on updrafts and can be removed. This may allow them to better describe their other analyses within a more reasonable space. 

References:  

van den Heever, S. (2021). NASA selects new mission to study storms, impacts on climate models. NASA Earth. Retrieved from https://www.nasa.gov/press-release/nasa-selects-new-mission-to-study-storms-impacts-on-climate-models 

Stephens, G., van den Heever, S. C., Haddad, Z. S., Posselt, D. J., Storer, R. L., Grant, L. D., et al. (2020). A distributed small satellite approach for measuring convective transports in the Earth's atmosphere. IEEE Transactions on Geoscience and Remote Sensing, 58(1), 4–13. https://doi.org/10.1109/TGRS.2019.2918090 

Prasanth, S., Haddad, Z. S., Sawaya, R. C., Sy, O. O., van den Heever, M., Narayana Rao, T., & Hristova-Veleva, S. (2023). Quantifying the vertical transport in convective storms using time sequences of radar reflectivity observations. Journal of Geophysical Research: Atmospheres, 128, e2022JD037701. https://doi.org/10.1029/2022JD037701.