Today's personnel engaged in meteorology and related fields often involve meteorological numerical models and data processing. Whether it is used as a means of business forecasting or as a scientific research tool, it is a very important skill to master meteorological numerical models and efficient pre- and post-processing languages. . As a leader in mesoscale meteorological numerical models, WRF has complete functions and is the first choice of most people. And mastering the model is only the first step. It is also an important task to further process the results of the numerical model into the products we need for business or scientific research. In terms of current trends, the python language has become the first choice.
This content combines theory with practice, including theoretical explanations of WRF mode, from the introduction of dynamic equations and parameterization schemes to mode application scenarios, and practical links, from basic Linux commands to the installation and operation of WRF mode. Another major feature is the combination of python language and WRF mode operation to automate the mode operation and improve the efficiency of scientific research and business. At the same time, master the common scenarios of python processing before and after WRF, including data processing, visual drawing, etc.
[Method]: Online + permanent review + long-term assistance in Q&A group + courseware materials
【Introduction】:
Topic 1. "WRF Basics and Linux Basics":
1. Theoretical knowledge and application prospect of WRF model
Introduction to WRF Dynamic Theory
WRF pattern code framework
Application prospect of WRF mode
2. Linux knowledge and basic operation
Linux basic commands
Set timed tasks
Supercomputing submission task
3. WRF mode installation
Basic library installation (GNU compiler, zlib, libpng, jasper, hdf5, netcdf4, mpich2)
WRF/WPS installation
Topic 2, "WRF Mode Operation":
1. WRFDomainWizard sets the simulation area
2. WPS (geogrid, ungrib, metgrid) pre-processing
GFS/FNL/ERA5 data-driven, nested simulation
3. WRF(real.exe, wrf.exe) integral operation
Parametric scheme settings
Experience with common parameters
4. Restart breakpoint and continue running
5. How to get better WRF simulation results (WRF operation experience and precautions)
Topic 3, "Python Basics":
1. Python installation and basic syntax
2. Python commonly used meteorological data processing library
numpy, datetime, pandas, scipy, netcdf-python
3. Basics of python meteorological drawing
1) Line chart drawing
2) Coloring and contour + map
3) Flow field vector + map
4) Map drawing (cartopy)
Topic 4. " Introduction to WRF Application Cases ":
1. Northwest Pacific typhoon simulation
2. Severe weather process - hail case simulation
3. WRF-solar simulates solar radiation
Topic 5, " python helps WRF automatic operation ":
1. Python automatically runs the WRF history example
2. Build an automated WRF business forecast system
1) Python automatically downloads GFS real-time forecast data
2) Python automatically runs the WRF forecast system
3) python automatically sends emails to prompt WRF running results
Topic 6, "WRF mode before and after processing":
1. Introduction to WRF post-processing
2. Introduction to wrf-python library
3. Python draws WRF simulation area and terrain
4. Python extracts site forecast elements and draws
5. Python draws 500hPa high-altitude form field
6. Python draws radar reflectivity DBZ vertical profile
7. Python draws 700hPa water vapor field
8. Python draws the ground rainfall field