1. requested by CLIVAR PSMIP (Process Study & Model Improvement Panel)
How to better integrate knowledge from field experiments into models/parameterizations
Discussion
requested by CLIVAR PSMIP (Process Study & Model Improvement Panel)

2. The GCSS Paradigm(s)
from Randall et al. (2003)

3. Some questions
Are there useful and achievable metrics that could be applied to both field experiment data and models (e.g. PBL depth, vertical velocity, diurnal cycle)?
Is it appropriate to group satellite and field experiment data in the same category? They are used very differently and attack different issues.
Are there critical unknowns in field experiment case studies that prevent adequate constraints for process models (e.g. subsidence, entrainment, precipitation, advection).
How do we better use multiple cases from field data to go beyond single case studies (e.g column droplet concentration closure, scalings between cloud and precipitation properties derived from all data in a campaign)
Is there anything to be learned from revisiting GCSS case studies?
Is survey-type sampling from field experiments useful (e.g. VOCALS 20oS mission)?

4. The GCSS Paradigm
from Randall et al. (2003)