42 replies to this topic

[dtk]

phil882, on 19 February 2012 - 12:16 PM, said:

Excellent Information... really interesting to see that dropsondes had quite a positive impact in some periods (especially between January 29th - Feb 5) while in other periods the impact was negligible. It is good to see that the vast majority of the time, the impact is positive as one would expect

Do you have a source link to the figures you have provided above, or is this information restricted to the public?

The NASA GMAO site: http://gmao.gsfc.nas.../fp/obs_impact/
NAVY: http://www.nrlmry.na...ns_main_od.html

I think that ECMWF has an internal monitoring package.
An ensemble-based package is in development for NCEP.

Lastly, here is a figure from the GMAO that shows the fraction of observations that are beneficial (getting to my previous point that only a small majority of observations contribute positively to a given system....I've seen fractions as high as 60% for some systems, but the point remains):

[baroclinic_instability]

Totally curious, you mentioned representativeness, but I was also wondering if issues arise regarding uneven distribution of data (i.e., a lone dropsonde into a Pacific cyclone, etc.)? What types of schemes are in place now to deal with extreme data distribution differences within a various domain?

[Rainshadow]

dtk, on 19 February 2012 - 12:51 PM, said:

The NASA GMAO site: http://gmao.gsfc.nas.../fp/obs_impact/
NAVY: http://www.nrlmry.na...ns_main_od.html

I think that ECMWF has an internal monitoring package.
An ensemble-based package is in development for NCEP.

Lastly, here is a figure from the GMAO that shows the fraction of observations that are beneficial (getting to my previous point that only a small majority of observations contribute positively to a given system....I've seen fractions as high as 60% for some systems, but the point remains):

Are Dropsonde missions routinely scheduled? The ones the week of Jan 29th I believe were because at one time it looked like there was going to be a major event on Super Bowl weekend. The Euro did a great job with this event, but up to this one it didn't appear to me to be any better (or worse) than most of the other medium range models beyond day4 this winter. I know the previous sentence is subjective and is based on the PHI CWA (Well Walt Drag agrees with me, so that must count for something.). The GFS overphased solution on 15/00z, once something that off (in retrospect always easier) gets into the modeling, does it take a while for it to be corrected? It seemed every sounding run after that it did trend closer to what was in the end the Euro solution.

[dtk]

baroclinic_instability, on 19 February 2012 - 01:03 PM, said:

Totally curious, you mentioned representativeness, but I was also wondering if issues arise regarding uneven distribution of data (i.e., a lone dropsonde into a Pacific cyclone, etc.)? What types of schemes are in place now to deal with extreme data distribution differences within a various domain?

I don't really think this is as much of an issue, per say, but does yield an analysis/IC that is of variable quality for different parts of the globe.

How the observational information is used to correct the guess (short term model forecast) is highly dependent on the background error covariance information. This is one of the reasons why ensemble methods have become so popular within the DA community.....as they allow you to sample/estimate through Monte Carlo type methods where you need to spread observational informational out over larger spatial distances or with larger amplitude (in addition to inherit model-driven multivariate aspects of the correlations). In the case of 4DVAR, this can be somewhat accounted for implicitly through the linearized model that is used as part of the update. There are ways to account for this within 3DVAR, but it's more difficult.

Ensemble methods are imperfect, however, due to the inherit issues related to sampling a huge space (the background error covariance for a modern day NWP models is huge, ~10^7 or greater....state space squared.....and we're trying to sample this with only ~50-100 ensemble members). This is why various places (UKMet, NCEP, CMC, others) are investing in hybrid type technologies where you combine ensemble-based information with the variational (with a full rank, static background error estimate) framework.

As an example, there have been projects that utilized ensemble-based methods to construct historical reanalysis....from a limited subset of surface pressure data only (and I'm talking full 3D analyses). That's about as extreme as it gets.

[dtk]

Rainshadow, on 19 February 2012 - 01:05 PM, said:

Are Dropsonde missions routinely scheduled? The ones the week of Jan 29th I believe were because at one time it looked like there was going to be a major event on Super Bowl weekend. The Euro did a great job with this event, but up to this one it didn't appear to me to be any better (or worse) than most of the other medium range models beyond day4 this winter. I know the previous sentence is subjective and is based on the PHI CWA (Well Walt Drag agrees with me, so that must count for something.). The GFS overphased solution on 15/00z, once something that off (in retrospect always easier) gets into the modeling, does it take a while for it to be corrected? It seemed every sounding run after that it did trend closer to what was in the end the Euro solution.

The big ones for the US are of course the WSR and Hurricane type missions. Any other observations labeled "recon" could be from missions of opportunity, international field experiments/missions, or who knows (I'd have to dig on a case by case basis). We pretty much share all observations with each other these days (even experimental).

In terms of your last question, that's hard to say because you are also talking about the model forecast grabbing onto a solution. Models have errors to, and even if given perfect initial conditions could be prone to grabbing onto certain types of solutions. It's possible that something finds its way into the analysis/short-term forecast that takes a while for the assimilation to completely get rid of.

[bluewave]

dtk, on 19 February 2012 - 01:30 PM, said:

The big ones for the US are of course the WSR and Hurricane type missions. Any other observations labeled "recon" could be from missions of opportunity, international field experiments/missions, or who knows (I'd have to dig on a case by case basis). We pretty much share all observations with each other these days (even experimental).

In terms of your last question, that's hard to say because you are also talking about the model forecast grabbing onto a solution. Models have errors to, and even if given perfect initial conditions could be prone to grabbing onto certain types of solutions. It's possible that something finds its way into the analysis/short-term forecast that takes a while for the assimilation to completely get rid of.

Was there an upgrade applied to the OP GFS this week or only just the ensembles?

http://www.nws.noaa....ncrease_aab.htm

[dtk]

bluewave, on 19 February 2012 - 01:36 PM, said:

Was there an upgrade applied to the OP GFS this week or only just the ensembles?

http://www.nws.noaa....ncrease_aab.htm

The OP GFS remained unchanged (there is a GFS/GDAS upgrade coming, likely in May....but it's mostly on the data assimilation component and not the model itself). The version of the model used in the GEFS was finally upgraded to use the same options that are used in the current OP GFS.

[bluewave]

dtk, on 19 February 2012 - 02:17 PM, said:

The OP GFS remained unchanged (there is a GFS/GDAS upgrade coming, likely in May....but it's mostly on the data assimilation component and not the model itself). The version of the model used in the GEFS was finally upgraded to use the same options that are used in the current OP GFS.

Thanks for the information.