NWP QUESTIONS version 3:
These questions relate to information in the assigned NWP COMET modules. Some questions create notes that help you pass the quizzes. Where it says ‘T/F’ it is sufficient to indicate true or false. Where it says ‘list’ several unambiguous fully correct phrases are OK. In other cases a full sentence is required.
I. NWP Essentials: NWP and Forecasting
A. What are the components of NWP models or EFS??
B. What processes and properties are typically parameterized in NWP models? (list)
C. When would a forecaster examine more than one model in formulating a forecast policy? (list)
D. How long did it take you to complete this module?
II. NWP Essentials: Data Assimilation
A. In what situations is the Data Assimilation system most likely to fail?
B. Why could a model produce a better forecast if its analysis does not fit an accurate observation too closely?
C. The primary limitation of standard 3D-VAR is that it spreads the influence of observations in the vertical and horizontal the same way in every weather situation. (T/F)
D. The circular pattern of background error covariances in standard 3D-VAR can be modified using model terrain or streamlines to improve the analysis in other places. (T/F)
E. Data Analysis Exercises (Answer the following questions found in the ‘exercises’ section of the data assimilation module. Type your answers on a separate sheet. Note: type out full answers, not ‘choice b)’ from the given choices.)
Data Voids
Using the First “Guess”
Reasons for DA failure
F. How long did it take you to complete this module?
III. NWP Essentials: Structure and Dynamics
A. What are disadvantages of using a sigma vertical coordinate or a hybrid coordinate? (list)
B. What are the primary considerations to keep in mind with respect to boundary conditions when reviewing model guidance? (list)
C. What minimum number of grid points should the size of a meteorological feature span in order to be adequately forecast in a gridpoint model?
D. List at least 2 phenomena/features where a hydrostatic model can make a good prediction and list at least 2 where the phenomena/features require a nonhydrostatic model for good prediction
E. How long did it take you to complete this module?
IV. NWP Essentials: Model Physics
A. In NWP models, what does PBL depth depend on?
B. In a heavy rainfall situation, which factors do you think are most important in determining the temperature forecast?
C. What parameters are affected by the vegetation fraction (the portion of the grid box covered by live vegetation)? (list)
D. Surface soil and vegetation canopy water errors by themselves will affect the forecast for long time periods. (T/F)
E. Model feedbacks via convection can lengthen the impact of surface moisture errors through time. (T/F)
F. Errors in surface moisture can affect the depth of the PBL due to impacts on the surface energy budget. (T/F)
G. In NWP models, land/water surface parameterizations simulate the interaction of the surface with incoming radiation to produce heat, moisture, and momentum exchanges between the surface and atmosphere. What elements of the NWP forecast need to be considered to assess the impacts of these surface/atmosphere exchanges on the forecast? (list)
H. How long did it take you to complete this module?
V. NWP Essentials: Precipitation and Clouds
A. How do NWP models deal with atmospheric moisture? (list)
B. The primary purpose of Convective Parameterization (CP) in NWP models is what?
C. If the convective parameterization scheme does not remove enough instability, what effect(s) might result in the model forecast? (list)
D. When considering forecast errors in precipitation location, which factor is the most significant contributor?
E. How long did it take you to complete this module?
VI. Statistical Methods in the NWS National Blend of Global Models
A. What role does mean absolute error (MAE) play in the Blend?
B. What are four important limitations of URMA as a data assimilation method?
C. What roles does URMA play in the Blend?
D. How long did it take you to complete this module?
VII. Verification Methods in the NWS National Blend of Global Models
A. For what characteristics is RTMA/URMA most applicable?
B. For what characteristics is MatchObsAll most applicable?
C. How long did it take you to complete this module?
VIII. Gridded Forecast Verification and Bias Correction
A. What are the steps (in order) of the verification review process?
B. What can you use to identify why a forecast may have been altered?
C. How long did it take you to complete this module?