• After witnessing the continued decrease of involvement in the SpotterNetwork staff in serving SN members with troubleshooting issues recently, I have unilaterally decided to terminate the relationship between SpotterNetwork's support and Stormtrack. I have witnessed multiple users unable to receive support weeks after initiating help threads on the forum. I find this lack of response from SpotterNetwork officials disappointing and a failure to hold up their end of the agreement that was made years ago, before I took over management of this site. In my opinion, having Stormtrack users sit and wait for so long to receive help on SpotterNetwork issues on the Stormtrack forums reflects poorly not only on SpotterNetwork, but on Stormtrack and (by association) me as well. Since the issue has not been satisfactorily addressed, I no longer wish for the Stormtrack forum to be associated with SpotterNetwork.

    I apologize to those who continue to have issues with the service and continue to see their issues left unaddressed. Please understand that the connection between ST and SN was put in place long before I had any say over it. But now that I am the "captain of this ship," it is within my right (nay, duty) to make adjustments as I see necessary. Ending this relationship is such an adjustment.

    For those who continue to need help, I recommend navigating a web browswer to SpotterNetwork's About page, and seeking the individuals listed on that page for all further inquiries about SpotterNetwork.

    From this moment forward, the SpotterNetwork sub-forum has been hidden/deleted and there will be no assurance that any SpotterNetwork issues brought up in any of Stormtrack's other sub-forums will be addressed. Do not rely on Stormtrack for help with SpotterNetwork issues.

    Sincerely, Jeff D.

Forecast Models - 18z Data

Joined
Feb 29, 2004
Messages
4,133
Location
Rochester Hills, Michigan, United States of Americ
What data do the 6z/18z models ingest (particularly NAM/GFS)? I'm aware that they don't have the benefit of 0z/12z soundings... so how is this compensated for? Satellite derived data? Using the previous run's +6hr as initialization?

I search Google for a few minutes, and couldn't come up with anything.
 
I'm not sure what you mean about "compensating" for the lack of 0/12Z soundings. They have any soundings from 06/18Z, plus satellite soundings, aircraft soundings, etc. They also use parts of previous runs, depending on the model.

Take a look at http://www.meted.ucar.edu/topics_nwp.php / Understanding Assimilation Systems: How Models Create Their Initial Conditions for more detail which was just published (along with a lot of other model training on their homepage) last week.

Description:
Understanding Assimilation Systems: How Models Create Their Initial Conditions, is part of the NWP Distance Learning Course: "Effective Use of NWP in the Forecast Process." This module explains the data assimilation process, including the role of the model itself as well as the observations. It provides learners an appreciation for how models use data as a function of model resolution and data type, how data influence the analysis, the limitations of data assimilation systems, the importance of initial conditions on the quality of NWP guidance, as well as the challenges of assessing the quality of NWP guidance based on the initial conditions. The differences between 3d-var with isotropic background covariances, anisotropic background covariances, 4d-var, and ensemble Kalman filter are conceptually illustrated.
Objectives:
After completing this module, students should be able to:

1) State the 2 primary sources (types) of information used in making a model
analysis

2) List 3 advantages of using a model short-range forecast as a first guess for the analysis

3) State the fundamental assumption of data assimilation in NWP models and
describe something which can happen if this assumption is violated. The answer to this question is the same regardless of the assimilation method (e.g., 3d-var, 4d-var, ensemble Kalman filter, etc.)

4) Describe what can happen to the analysis and forecast when a model can resolve and create features smaller than the network of observations assimilated can resolve in the vicinity of the feature

5) State one reason why a model might produce a better forecast if its analysis
does not fit a perfect observation too closely

6) Given observations of a weather feature showing a first guess error in
placement of the feature, describe how the feature will differ in a 3d-var analysis, 4d-var analysis, and ensemble Kalman filter analysis

7) List 4 scenarios that can produce a poor analysis leading to a poor forecast
and describe the cause or nature of the analysis problem
Estimated time to complete: 2.00 - 3.00 h
 
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