ESE315 Tutorial 2 - Revision history

Atmoschem at 01:16, 10 November 2023

2023-11-10T01:16:54Z

Atmoschem at 01:07, 10 November 2023

2023-11-10T01:07:31Z

Atmoschem at 05:37, 22 October 2019

2019-10-22T05:37:11Z

Atmoschem at 12:43, 21 October 2019

2019-10-21T12:43:28Z

Atmoschem at 11:27, 21 October 2019

2019-10-21T11:27:35Z

Atmoschem at 10:54, 21 October 2019

2019-10-21T10:54:45Z

Atmoschem at 10:52, 21 October 2019

2019-10-21T10:52:04Z

Atmoschem at 15:04, 23 September 2019

2019-09-23T15:04:34Z

Atmoschem: Created page with "=Under development="

2019-09-21T00:45:30Z

Created page with "=Under development="

New page

=Under development=

@@ Line 1: / Line 1: @@
 =Analyzing 2D and 3D atmospheric (geoscience) datasets with Python=
 This tutorial shows you how to read 2D or 3D data in NetCDF format into python, plot them, and do a bunch of analyses.
 [https://www.unidata.ucar.edu/software/netcdf/ NetCDF] (network Common Data Form) is a set of interfaces for array-oriented data access and a freely distributed collection of data access libraries for C, Fortran, C++, Java, and other languages. The netCDF libraries support a machine-independent format for representing scientific data. Together, the interfaces, libraries, and format support the creation, access, and sharing of scientific data.

@@ Line 25: / Line 25: @@
 =Reference=
 *[https://www.unidata.ucar.edu/software/netcdf/ netcdf data format]
 *[http://xarray.pydata.org/en/stable/ Description of the xarray project, with links to tutorials]

@@ Line 27: / Line 27: @@
 *[https://www.unidata.ucar.edu/software/netcdf/ netcdf data format]
 *[http://xarray.pydata.org/en/stable/ Description of the xarray project, with links to tutorials]
 *[https://scitools.org.uk/cartopy/docs/latest/ Description of the cartopy project]
 *[https://matplotlib.org/3.1.1/index.html Description of matplotlib]
 *[https://matplotlib.org/examples/color/colormaps_reference.html Colormaps in matplotlib]

@@ Line 16: / Line 16: @@
 ==Tutorial-02-1.ipynb==
-In this tutorial, you will learn to read a NetCDF file containing a full year of daily surface air temperature data. You will learn to extract a time slice from this 3D array and make a global plot of this 2D data.
+In this tutorial, you will learn to read a NetCDF file containing a full year of daily surface air temperature data. You will learn to extract a time slice from this 3D array and make a global plot of this 2D data. You will also learn to calculate time averages (or zonal averages, area averages, etc.)
 ==Tutorial-02-2.ipynb==
-In this tutorial, you will learn to overlay several datasets in one plot
+In this tutorial, you will learn to overlay several datasets in one plot.

@@ Line 1: / Line 1: @@
 =Analyzing 2D and 3D atmospheric (geoscience) datasets with Python=
-This tutorial shows you how to read 2D or 3D data in NetCDF format into python and do a bunch of analyses.
+This tutorial shows you how to read 2D or 3D data in NetCDF format into python, plot them, and do a bunch of analyses.
 [https://www.unidata.ucar.edu/software/netcdf/ NetCDF] (network Common Data Form) is a set of interfaces for array-oriented data access and a freely distributed collection of data access libraries for C, Fortran, C++, Java, and other languages. The netCDF libraries support a machine-independent format for representing scientific data. Together, the interfaces, libraries, and format support the creation, access, and sharing of scientific data.
@@ Line 16: / Line 16: @@
 ==Tutorial-02-1.ipynb==
 ==Tutorial-02-2.ipynb==
@@ Line 25: / Line 28: @@
 *[http://xarray.pydata.org/en/stable/ Description of the xarray project, with links to tutorials]
 *[https://scitools.org.uk/cartopy/docs/latest/ Description of the cartopy project]
+*[https://matplotlib.org/3.1.1/index.html Description of matplotlib]

← Older revision		Revision as of 10:52, 21 October 2019
Line 1:		Line 1:
−	=~~Statistical analyses~~ with python=	+	=Analyzing 2D and 3D atmospheric (geoscience) datasets with Python=
		+	This tutorial shows you how to read 2D or 3D data in netcdf format into python and do a bunch of analyses.
		+
		+	[https://www.unidata.ucar.edu/software/netcdf/ NetCDF] (network Common Data Form) is a set of interfaces for array-oriented data access and a freely distributed collection of data access libraries for C, Fortran, C++, Java, and other languages. The netCDF libraries support a machine-independent format for representing scientific data. Together, the interfaces, libraries, and format support the creation, access, and sharing of scientific data.
		+
		+	NetCDF data is:
		+	*Self-Describing. A netCDF file includes information about the data it contains.
		+	*Portable. A netCDF file can be accessed by computers with different ways of storing integers, characters, and floating-point numbers.
		+	*Scalable. A small subset of a large dataset may be accessed efficiently.
		+	*Appendable. Data may be appended to a properly structured netCDF file without copying the dataset or redefining its structure.
		+	*Sharable. One writer and multiple readers may simultaneously access the same netCDF file.
		+	*Archivable. Access to all earlier forms of netCDF data will be supported by current and future versions of the software.
		+
		+	If you work in earth or environmental sciences, you will inevitably run into datasets in netcdf format. However, you do not need to know all the functionality of netcdf in order to start working with it. As with anything else in research, start playing with the data and look up resources along the way.
		+
		+
		+	==Tutorial-02-1.ipynb==
		+
		+
		+	==Tutorial-02-2.ipynb==
		+
		+
		+	=Reference=
		+	*[http://xarray.pydata.org/en/stable/ Description of the xarray project, with links to tutorials]
		+	*[https://scitools.org.uk/cartopy/docs/latest/ Description of the cartopy project]
		+	*

← Older revision		Revision as of 15:04, 23 September 2019
Line 1:		Line 1:
−	=~~Under development~~=	+	=Statistical analyses with python=