What is a breadboard (retrieval) algorithm in the context of geophysical satellite retrievals/remote sensing? In a recent met-jobs job posting (different version here) for a researcher with a background in climatology/meteorology/hydrology or
environmental sciences, I saw the phrase breadboard retrieval algorithm (emphasis mine):


  Sentinel-4 Retrieval: This Research Fellow Opportunity aims at
  testing of breadboard retrieval algorithms. It is foreseen that
  synthetic satellite data, and possibly also real measurements data from
  airborne and satellite sensors will be used for this purpose. The
  activity might also cover the exploration of alternative retrieval
  approaches depending on the expertise and skills of the candidate.


What is a breadboard (retrieval) algorithm?  Google Search yields precious few results, mostly from ESA.  Another usage I found

Albert, Preusker, and Fischer (2012), ENVISAT workshop:


  Originally, three breadboard algorithms were developed at the 
  Freie Universität Berlin, and the knowledge for their creation 
  was  transferred  to  ESA  /  Bomem  for  the  creation  of  the  ESA  algorithms.  In  the  meantime,  the  original  look-up  table approach was replaced for the breadboard algorithms by the use of artificial neural networks, which significantly eases the interpolation  of  the  simulation  results  onto  the  actual  viewing geometry.


Wikipedia tells me that, in electronics, a breadboard is a construction base for prototyping electronics.  The details of the article do not appear relevant for the algorithm usage, but it makes me guess that the meaning of breadboard is related to prototyping.  However, from context, it is clear that the job ad or the ENVISAT paper has nothing to do with electronics.

What does breadboard mean in the context of Earth observation retrieval algorithm development (which are the only contexts I could find)?  Is it simply a synonym for prototype, or does it have a different meaning?
When determining the retrieval algorithm for a spectrometer that will be built, it is first done on highly mathematical software platforms.  The software allows to the best curve approximation fitting equations to be derived (across all detected wavelengths) that will work for the proposed optics.  This is important because the diffracted light that is detected will interfere with itself very uniquely, depending on the geometry of your optical setup.   The data from the spectrometer's detector needs to be interpreted with a good curve fitting function so that you can get good wavelength resolution from your instrument.  

When building a spectrometer for operational use on a satellite, it is ideal to be able to process the retrieval algorithm using hardware, rather than software.  The hardware processor allows real time function that isn't dependent on an operating system that requires lot's of computational overhead.  So, you build a breadboard that you can connect to your spectrometer so that your retrieval algorithm is processed using integrated circuits that can be programmed.  You essentially hard-code your algorithm into hardware.

Search for "breadboard spectrometer" in Google and you will find many examples.  

Now, to answer your question.  A breadboard algorithm is developed using software that is used to help engineer the actual breadboards to be built in the future.  The software allows you to predict the response of your proposed circuitry to the spectrometer detector without having to actually build the breadboard yet.  Once your breadboard algorithm is setup properly (confirmed by testing the software version of your needed hardware) you can go about building the actual breadboard spectrometer model.

Once a breadboard spectrometer model is built and passes quality control checks, you can evaluate the spectrometer performance and see if its worth optimizing and fabricating a standalone instrument payload that can be deployed in the field (or in space).