Hi John-
Thanks for the updates. Are you looking at determining this for a
dataset from the analysis/forecast hour 0 fields in a dataset, or from
the reference time in each GRIB record?
Don
On 3/2/15 5:06 PM, John Caron wrote:
Hi Don:
The CDM now has an "auxiliary coordinate" that gives the reference time
(aka run time) for each valid time in a Best dataset. We are working
with the IDV group to help them show that info to the user.
Currently we are looking at the presence of analysis vs forecast GRIB
records in the NCEP datasets to see what makes sense there. As usual,
its not really clear what different groups do when they generate GRIB,
so we are trying to be careful not to assume too much.
All this work is being done on the 4.6 development branch.
Thanks for your comments.
John
On Wed, Feb 11, 2015 at 2:54 PM, Don Murray (NOAA Affiliate)
<don.murray@xxxxxxxx <mailto:don.murray@xxxxxxxx>> wrote:
Hi Ryan-
I think this sounds like a workable solution. I assume that the
Complete is essentially how the Best works now. Given the problems
it has, I'm not sure if it's needed. An Analysis dataset would be a
good addition.
And of course, it would be good to be able to query any timestep for
the model run time so the forecast hour can be computed.
Will this be an update to 4.5 or will we have to wait for 4.6?
Thanks for attacking this problem.
Don
On 2/11/15 11:24 AM, Ryan May wrote:
Greetings!
The recent upgrades by NCEP to the time range of the operational GFS
half degree output has raised an issue with the Best timeseries
dataset
on Grib Collections in TDS. Best is designed to take all the
forecast
times available in the Grib Collection and, for each one, use
the GRIB
record that has the smallest forecast offset (i.e. the forecast
closest
to the start of its model run).
The problem occurs where, for example, NCEP puts out GFS runs
every 6
hours, but at the later parts of the forecast, the time interval
within
a single run's output is 12 hours. The result is that even with no
missing data, eventually the Best time series has output every 6
hours
by interleaving two different forecasts. Given that forecasts
this far
into the future can vary widely from run to run, this can yield very
surprising and confusing results. Note that this issue is not
limited to
the GFS, but for any model collection where time steps in the output
become larger than the time between individual model runs.
There is also a second issue regarding a model run having multiple
fields with a 0 hour forecast offset. It turns out that (at least
ideally) NCEP will put out one version of the 0 hour forecast
with the
analysis flag set, denoting the field as the one to use to
initialize
the model. Then a second field is put out as 0 hour forecast
(without
the analysis flag) that actually corresponds to a time after a
single
model integration step. This non-analysis 0 hour forecast
contains the
full collection of parameters that are available throughout the
forecast, whereas the analysis only contains the fields that
result from
data assimilation. Currently, the Best time series will contain
whichever version of the 0 hour forecast that comes first in the
file.
To address the first issue and make the data easier to use, we
propose
to modify Best such that when a set of forecast runs is
combined, the
forecasts included from a run will be consecutive in time. This
implies
that any missing forecasts within a run will not be filled by a
previous
run; however, an older forecast can be used to fill in gaps when a
collection is missing entire run(s). This behavior ensures that
the Best
time series will no longer alternate repeatedly between different
forecast solutions, but rather only jump once from one set of
forecasts
(model run) to another.
To address the second issue, we propose an additional
modification to
Best such that only 0 hour Forecasts are used to make up Best,
and not
Analysis fields. Additionally, we propose to add two more virtual
datasets: Analysis and Complete. Analysis will contain the
collection of
all analysis fields from the grib collection. Complete behaves
just as
Best currently does, containing every possible time, using the
smallest
forecast offset. In this case, the forecasts included from a run
will
not be guaranteed to be be consecutive in time, as they could be
mixed
between various runs as long as the smallest forecast offset
condition
is met.Â
We are seeking comments on these solutions to see if they
represent a
useful set of features given the problems outlined above.
Thanks!
The TDS development team
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