Experimental and Parallel Model Runs
This page links to graphics and other data from model
for the different branches of the EMC. In no way do they represent
operational forecasts, but we offer them so that meteorologists in the
field may give us feedback on the results. Diagnostic tools are used
to analyze the date at EMC, and the results of this analysis are what appear
as links below.
Before going to the data, however, we suggest you read
the following section, which discusses the experimental process, from how
EMC uncovers a problem to the final "parallel" run, performed to remove
the final "bugs" prior to operational implementation.
How model changes get tested and implemented
How do we determine what experiments to perform to
improved the numerical weather prediction (NWP) model?
Through examination of existing model biases or error patterns,
Through research done at NCEP or elsewhere which might improve
an existing NWP model, using
new physical parameterizations,
new data assimilation methods, or
Through anticipated increases in computer resources which
drive decisions on what improvements can be implemented.
Terms typically used for model experiments before
model changes become operational include, in roughly chronological order
from problem identification to pre-implementation:
Once these steps have been taken there are additional approvals
required for NWP model changes to be made operational, at both EMC, NCEP,
and NWS headquarters.
case study (examine one weather event to diagnose model perfomance,
sensitivity study (low-resolution model runs to see if a
model change will have a significant positive or negative impact on model
experimental runs (low-resolution forecasts without data
assimilation, to check the changed model climate)
retrospective (usually in conjunction with model climate
parallel (full data assimilation system at expected operational
model resolution, with 'bundles' of experimental changes which have passed
previous tests above)
How do all the planned changes interact together?
Assessment done by NCEP and field office Science and Operations
Forecast impact of:
Amplification of changes and errors through the data assimilation
Changes in old biases and errors
Effects on vertical motion (model spin-up)
Accumulate vertification statistics for an objective comparison
to existing operational model configuration
A schematic of the full model change cycle can be found
here [link will be activated to flowchart "Path to Operations" soon!].
CURRENT MODEL EXPERIMENTS
Global Modeling Branch experimental runs:
Mesoscale Modeling Branch experimental runs:
Marine Modeling and Analysis Branch experimental
Climate Modeling Branch experimental runs: