Under construction.
Ignore the remainder of this web page. It is from past terms, and will be deleted soon.
(
Stull is gradually moving the material to the new web pages above.)
Lect. # |
Date (2020) |
Topics (& instructor: Roland Stull or Tim Chui) |
Learning Goals At the end of the class meeting, you should be able to: |
Assignments. Legend: C = Coiffier 2011: Fundamentals of NWP, S = Stull 2017: Practical Meteorology (NWP chapter only), W = Warner 2011: Numerical Weather & Clim. Pred., c = chapter, p = page |
12 |
9 Feb 2020 |
Acoustic split time differencing(Lecture by Tim Chui) |
For the Acoustic Time-splitting lecture: • Before class, skim paper by paper by Wicker and Skamarock (2002) on split time differencing: https://journals.ametsoc.org/doi/pdf/10.1175/1520-0493%282002%29130%3C2088%3ATSMFEM%3E2.0.CO%3B2 Homework 5: See this link for the assignment on acoustic time splitting. |
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18, 20 Feb |
Spring Break / Reading Week |
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13 |
???? |
Vapor display software, presented by Nadya Moisseeva. |
• open WRF output in the Vapor program to create 3-D visualizations of your forecasts. | BEFORE class, use the instructions on this link to install Vapor on your own laptop. Also, download the sample WRF output file to your own laptop, which is the forecast for a strong low off the BC coast that caused damaging winds on 20 Dec 2018. Bring your laptop to class. In class, Nadya will show you how to use Vapor to view the WRF output. |
22 |
16 Mar |
9. Spectral methods
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• start with the variation of a weather variable with distance (such as T vs. x) and convert it into a Fourier series. • convert simple equations of motion into forecast equations for spectral amplitude. • integrate (i.e., time-step) these equations forward in time to get forecasts of spectral amplitude, and then do an inverse Fourier transform to recover the physical signal. • summarize the steps needed to utilize the spectral method for spherical domains such as Earth's atmosphere. • relate truncation type (triangular, trapezoidal, rhomboidal) and order to the effective horizontal resolution |
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Pseudo-spectral methods |
( not covered in 2020) |
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Semi-Lagrangian |
tbd |
See Dr. May Wong's lecture slides on Semi-Lagrangian methods (not covered in 2020) |
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Smoothing & Filtering
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• explain the relationship between smoothing and filtering • use the discrete fourier transform (DFT) to create any arbitrary filter • compare running-mean vs. ideal filters. • explain what filtering is used in WRF and why it is used. |
During the online class: • Stull - Smoothing & Filtering lecture notes (not covered in 2020) Reading AFTER class: • WRF-ARW4 Tech Note - Chapter 4 HW xx - Topic: Smoothing & Filtering. (not assigned in 2020) 1) What are the weights in a 5-point smoother (applied once) that is equivalent to a 3-point smoother ( 0.25 / 0.50 / 0.25 ) applied twice? 2) For a continuous (not discrete) problem, derive the filter response function for the case where the smoother weights are given by the following sinc function: w(tau) = 2*B* [sin(2*pi*B*tau) ] / (2*pi*B*tau) , where B = bandwidth (=the cutoff wavenumber for the filter). Note, this w(tau) function is already normalized; namely, the area under the w(tau) curve = 1. Hint: the definite integral of the sinc function is |
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Data Assimilation
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Data Assimilation • explain why numerical models need initial conditions • define data assimilation • list 3 major methods of doing data assimilation • indentify the factors that cause certain observations or grid-point values to be weighted less than other. • show how the Cressman, Barnes, and Bratseth schemes are all types of successive correction assimilation methods. • identify optimum interpolation as a least-squares approach. • show how optimum interpolation method can be re-written as a cost function for a variational approach • explain the basic concepts of 3-D Var and 4-D Var. |
HW xx Topic - Data Assimilation. (not covered in 2020) 1) Analytically derive eq. (20.20) of Stull's NWP chapter by finding the analysis value "A" that gives the minimum cost function "J" as defined by Stull's eq. (20.21). |
24 |
2 Apr |
Verification |
• calculate verification statistics for continuous, binary, and probabilistic forecasts. • explain pros and cons of each verification statistics • identify the range of values of each statistic, and explain which values are good and bad. • compare the forecast skill of NWP models from different organizations worldwide. |
See Stull's Verification lecture slides-2020 HW 11 Topic: Forecast Verification From Stull's Practical Meteorology book, chapter 20 https://www.eoas.ubc.ca/books/Practical_Meteorology/prmet102/Ch20-nwp-v102.pdf Do the following exercises at the end of chapter 20 ,from the "Applied " section of exercises:
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25 |
7 Apr |
Post-processing, Catch-up & Review |
• explain the reasons for statistical post-processing of NWP forecasts • use different statistical methods to perform post-processing • compare MOS , Perfect-prog, and other methods. |
See Dr. Thomas Nipen's lecture slides on Probabilistic Forecasts See Stull's lecture slides on post-processing, operational forecasting, and terrain issues Also listen to ECMWF's lecture on new developments in statistical post-processing: https://confluence.ecmwf.int/download/attachments/45754015/TK_StatisticalPostrocessing_2015.mp4 |
26 |
16 Apr - instead of a final exam |
Student presentations on WRF-ARW4 Physics Schemes, with selections from:
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• list 3 of each of the schemes that was discussed by you and your classmates. • identify the default schemes used in WRF, and show how to change these schemes via the namelist. • give talks on NWP topics with confidence |
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topics needing a home: |
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END OF COURSE |
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