1. Quick overview of ATM 419/563
ATM 419/563
Spring 2019
Fovell

2. Goal
How to use WRF in support of scientific experimentation with an appreciation of its capabilities, an understanding of its strengths, and an awareness of its limitations
The goal is to open up the “black box”
You need to be skeptical about what you see
I will provide compiled (often customized) executables of the WRF model and supporting programs, and scripts for running model and analyzing output
You can use these materials as learning examples and starting points
Later in course, if you want to compile your own, I can help
Control the degrees of freedom

3. Overview WRF model simulations Model physics and numerics topics
1D, 2D, and 3D idealized
Real-data runs
Model physics and numerics topics
Planetary boundary layer and surface layer schemes
There are 13 PBL schemes in WRF. How do they work? How do they differ?
Cloud microphysics
There are 26 microphysics schemes in WRF. Which to choose for the problem at hand?
Cumulus parameterizations
When and why do we need both microphysics and cumulus schemes? How and when do they cooperate and conflict?
15 cumulus schemes in WRFV4.0
Sources of model error
Diagnosing linear and nonlinear instability
Give people a lot of options, they tend NOT to explore

4. Simulations Idealized simulations may include
Boundary layer evolution
Downslope windstorms
Sea-breeze circulations
Squall line thunderstorms
Splitting supercell storms
Real-data cases may include
Convective outbreaks at various resolutions
Extratropical cyclones
Tropical cyclones
Snowstorms
Windstorms
Fog cases

5. Real-data WRF topics Designing and placing a domain
Selecting topographic and landuse databases
Map projections and map factors
Creating telescoping grids
Initializing real-data simulations
Combining different initialization data sources
Model verification against surface and upper air observations
Altering model vertical levels from default
Modifying topography and other landscape features
Model diffusers and dampers – what/when/where/why
Stochastic perturbations
Analysis nudging
Moving nests
Bogussing tropical cyclones
Adaptive time stepping
Nestdown and 1-way nesting
WRF restart capability
Creating and/or archiving extra model fields
Implementing passive tracers

6. Tools WRF model WRF Preprocessing System (WPS) NetCDF ncview
read_wrf_nc program
GrADS (Grid Analysis and Display System)
wrf_to_grads
NCL (NCAR Command Language)
RIP (Read-Interpolate-Plot) package
IDV (Integrated Data Viewer)
UPP (Universal Pre-Processor)
MET (Model Evaluation Tools)
ImageMagick convert and display
Python

7. Initialization data sources
GFS
FNL (GFS Final Analysis)
NAM
RAP and/or HRRR
NARR (North Americal Regional Reanalysis)
CFSR (Climate Forecast System Reanalysis)
NNRP (NCEP/NCAR Reanalysis Project)
ERA-interim
[others]

8. Data sources NCEP NOMADS archive NCDC/NCEI NOMADS archive
NCAR Research Data Archive (RDA)
MADIS archive
Other NCDC/NCEI archives
[more]

9. Grading
Common complaint: I don’t give indication of grade before semester ends

10. Tasks Attendance In-class demonstrations Experiments Final project
No exams (probably)

11. Final project Identify a topic of interest to YOU
Discuss it with me sooner rather than later (especially for viability)
Formulate testable hypotheses
Design an experiment using WRF
Use tools, insights, and strategies learned from this class in your experiments and analyses
Produce a final project in presentation format
It doesn’t have to be “publishable”, just new to you, so you gain something from this

12. From the syllabus
A key component of the course grade is the final project.
An “A” level project will have identified a viable topic, constructed thoughtful hypotheses and designed a reasonable experiment to test them, analyzed the results thoroughly and with care, crafted figures that are useful, clear, and attractive, and have produced a presentation that is well-organized, coherent, and displays what you did, how you did it, and what you learned.
The “B” level is high quality work that shows thoughtfulness and effort but reaches the “A” standards less fully or consistently.

13. Snapshots from some past student final projects

14. Tropical cyclone: 10 m wind sensitivity to PBL parameters
Control
Mod1
Mod2
Mod3
Time [hours]
Lugo 2017 – Hurricane vary PBL parameters
Distance from center [km]
Color shaded indicates maximum wind intensity (every 5 ms^-1). Black (red) contours indicate the isotachs at 10, 20 and 30 ms^-1 for control run (each individual run)

15. Terrain set to 50% of normal Terrain set to 100% of normal
Simulations of TC Matthew
Terrain set to 50% of normal
Terrain set to 100% of normal
Terrain set to 150% of normal
Davis 2017 Real-data simulation of TC Matthew & variation of topo height
October 2nd 12Z

16. Simulated Reflectivity 02Z (18th): sensitivity to microphysics
McGuinnes 2017 – Vary microphysics for lake effect case

17. Heavy precipitation case: one vs. two domains
Conway & Gallagher 2016 – Heavy rain event, illustrates issues w/ nesting

18. 6Z Observation (radar) The best simulation for intensity
Pryzyblo – 2018 – just a small part of this analysis/comparison

19. Effect of topography and surface roughness change on landfalling
hurricane
RUN1
RUN2
RUN3
RUN4
Zhou – 2-18
Fig 7. Maximum radar reflectivity at 41 h for (a) RUN1, (b) RUN2, (c) RUN3 and (d) RUN4, shaded semi–transparent grey area stands for land surface in model, while white area represents water surface.

20. Three month mean OLR Obs WRF (fix SST) WRF (vary SST)
WRF tropical channel outgoing longwave radiation (OLR), with and without time-varying sea-surface temperature (SST), vs. analysis OLR (presumed truth)
Numerous differences from observation, many of which not mitigated by varying SST
WRF (fix SST)
WRF (vary SST)
Shabaan

21. Final thoughts
You will get out of this course precisely what you put into it
You are in this course for your sake, not for mine
This will sometimes be hard, other times quite tedious, but ultimately it should be fun

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