In the manuscript titled “The ESGF Virtual Aggregation (CMIP6 v20240125)”, the authors study the Earth System Grid Federation (ESGF) Virtual Aggregation which provides a sustainable solution to some of the problems encountered in producing climate analysis ready data. In case of an overload of access requests, the Virtual Aggregation requires more ESGF data servers than are currently deployed. The study addresses this critical issue by focusing on data obtaining, improving deliver capabilities beyond conventional file search and download. This gap in the research makes the study timely and relevant, especially in the enhancing the efficiency and productivity of climate data analysis.

While the current focus on database operations might make the paper more suitable for a data management journal, there is potential for it to fit within Geoscientific Model Development if the numerical models of the Earth system aspects are emphasized. If the primary contribution remains database-oriented, the manuscript might not meet the scientific inquiry expectations of Geoscientific Model Development. Reframing the study to address earth system model processes more directly could improve its suitability, but if that is not feasible, the authors might consider submitting to a journal more focused on database management and database query. Please refer to the aims and scope of GMD https://www.geoscientific-model-development.net/about/aims_and_scope.html

In the manuscript titled “The ESGF Virtual Aggregation (CMIP6 v20240125)”, the authors propose a Virtual Aggregation solution to support an analysis ready data view to files stored on distributed data servers in the ESGF data infrastrcuture is described. Besides providing a standardized virtual aggregation description, the major advantage lies in the possiblility to generate logical aggregation descriptions without the need to inspect storage details of the netcdf files. This allows for a efficient implementation in the ESGF data federation based on the ESGF medatadata search capablility and ESGF data access services.  The implementation also revealed options, problems and possibilites in the current operational ESGF data fedeartion to better enable virtual aggregation in the future - these aspects are highlighted. This provides important input for the evolution of ESGF to better support data analysis exploiting virtual aggregation descriptions. 

The problem with respect to the dependency of the described solution on  available opendap servers (not forseen in the future ESGF infrastructure planing)  is described. A short comment on how other types of lightweight data servers e.g. based on xpublish would be an option for the future would be helpfull. Also a short comment on the nature of this dependency would be helpfull - DMR++ Opendap is not mentioned etc. ?

The manuscript focuses on the distributed database and data management aspects and not so much on the model development, yet there are important implications for the climate model components responsible for generating standardized model (meta)data to enable data distribution e.g. in ESGF (e.g. cmor, versioning, chunking and aggregation problems with the currently available ESGF metadata  are mentioned in the paper). With a more explicit description on this aspect it might fit better within Geoscientific Model Development. 

Minor, more technical comment:

-  The numbers in figure 6 are a bit misleading because numbers refer to different aspects.  The illustrated ESGF index is much smaller (GB scale) then the mentioned ~21 PB of data this index is addressing. Yet the ESGF index is used to generate the local sql database. The aspect that other aggregation methods like kerchunk would need to inspect the indexed ~21 PB data is probably something which should not be included in the figure ..