How best to store multi-dimensional timeseries data in a (R)DBMS environment? Any suggestions on how multi-dimensional time-series data should be stored and organized in an RDBMS environment? For example, we have multiple experiments from multiple customers. This translates well to say a NetCDF file type structure, where one NetCDF can be for one customer project, and it contains several data variables overtime. This image explains the concept.

From my preliminary research, this seems like an unsolved problem or one with a complicated solution. Are there any recent (not necessarily optimal) attempts at this?
I think you're over-complicating things.  For this example



Modeling this as a relational table is simple:

create table Forecast
( 
  reference_time datetime,
  latitude float,
  longitude float,
  precipitation float,
  temperature float,
  constraint primary key (reference_time,latitude,longitude)
)


It may not be extremely efficient for storage space and processing, depending on data structures and algorithms used by 
the RDBMS that implements it.  But it's logically very straightforward to model this as a relation.