What is the meaning of phenomenology? From what I understand, phenomenology as it is used in science means talking about the details of a phenomenon without going deep into the fundamental physical processes that lead to the phenomenon.  It is much more based on observation rather than theory.
Is this correct?  If not, please help me with a correct definition (and don't just refer me to Wikipedia, I'm having a hard time understanding that definition) as well as some examples.
 A: At present for physics research, a phenomenologist is a theoretical physicist who is well grounded in the current physical theories and at the same time understands the data and can create detailed theoretical models that can predict the behavior of future experiments.
In this context, phenomenology is the study of the way current theories fit the data and predict new behaviors.
Take as an example the physics coming out of the LHC. The most glaring is the discovery of the Higgs boson.To search though for the Higgs boson in the data the theory of Higgs was not enough. One needs a theoretical model to predict the background if no Higgs exists within the energy range sought, which will be a collection of mathematical formulae predicted by the existing knowledge of the standard model, of how protons hitting protons hadronize and the expected crossection/ percentages of background channels under the putative Higgs signal:

The continuous lines, broken by dashed ones at the measured resonance, are the backgrounds calculated rigorously using phenomenological models. At the resonance the signal  has been added to the background  to get a fit.
As another example currently string theory is aiming to describe all elementary particle interactions and include quantization of gravity. The pure theoretical models are many, but the experiments are studied with specific phenomenological models that project the expected string behavior with specific assumptions that allow a comparison with the data. As an example come the string  models with large extra dimensions, for example, which predict specific behaviors for the data ( that have not been seen up to now).
