wrf2kmz.py
Jonathan Beezley <[email protected]>
This is a commandline script and python module that will generate
Google Earth visualizations from surface variables in WRF output
files. The script syntax is simply:
python wrf2kmz.py wrfout [var1 [var2 [...]]]
A file called wrf.kmz will be created containing ground overlays
for all of the surface variables (var1, etc) specified on the
commandline.
Quiver plots of vector data is also supported using the syntax `var1:var2`.
(Note both variables must be surface variables.) For example, to generate
a quiver plot of fire winds along with the surface heat flux:
python wrf2kmz.py wrfout FGRNHFX UF:VF
See the docstrings in the file for information on how to customize the output
or to add the ability to visualize netCDF files generated by other models.
Dependencies:
simplekml : http://code.google.com/p/simplekml/
matplotlib : http://matplotlib.sourceforge.net/
netcdf4-python : http://code.google.com/p/netcdf4-python/
WARNING: KMZ files expect that ground overlays are unprojected, but
WRF models can output on a variety of projections. There is an experimental
reprojection component that is turned of by default. You can try
to enable this by setting no_reprojection=True in the source. There
are two methods for reprojection. The first is a custom fortran module
that requires a working installation of f2py. The second is used if
the fortran module cannot be compiled. It uses a call to matplotlib's
griddate function and is significantly slower on large domains.
[![Bitdeli Badge](https://d2weczhvl823v0.cloudfront.net/jbeezley/wrf2kmz/trend.png)](https://bitdeli.com/free "Bitdeli Badge")
WRF数据转换为KMZ格式,提供谷歌地球可视化接口wrf2kmz-master.zip
需积分: 5 13 浏览量
2024-05-03
10:11:22
上传
评论
收藏 26KB ZIP 举报
流华追梦
- 粉丝: 4444
- 资源: 2137
最新资源
- Picasso_v3.1 2.ipa
- chromedriver-mac-arm64.zip
- 蓝zapro.apk
- chromedriver-linux64.zip
- UCAS研一深度学习实验-MNIST手写数字识别python源码+详细注释(高分项目)
- 基于Python和PyTorch框架完成的一个手写数字识别实验源码(带MINIST手写数字数据集)+详细注释(高分项目)
- 基于Matlab在MNIST数据集上利用CNN完成手写体数字识别任务,并实现单层CNN反向传播算法+源代码+文档说明(高分项目)
- NVIDIA驱动、CUDA和Pytorch及其依赖
- 基于SVM多特征融合的微表情识别python源码+项目说明+详细注释(高分课程设计)
- html动态爱心代码一(附源码)
资源上传下载、课程学习等过程中有任何疑问或建议,欢迎提出宝贵意见哦~我们会及时处理!
点击此处反馈