Earth Observation Using Python. Rebekah B. Esmaili

decoding and encoding standard WMO GRIB and BUFR files.

      

2.4 Summary

      I hope you are excited to begin your Python journey. Since it is free and open‐source, Python is a valuable tool that you can carry with you for the rest of your career. Furthermore, there are many existing packages to perform common tasks in the Earth Sciences, such as importing common datasets, organizing data, performing mathematical analysis, and displaying results. In the next chapter, I will describe some of the common satellite data formats you may encounter.

References

      1 Dask: Scalable analytics in Python. (n.d.). Retrieved November 25, 2020, from https://dask.org/

      2 ecmwf/cfgrib. (2020). Python, European Centre for Medium‐Range Weather Forecasts. Retrieved from https://github.com/ecmwf/cfgrib (Original work published July 16, 2018).

      3 Matplotlib: Python plotting — Matplotlib 3.3.3 documentation. (n.d.). Retrieved November 25, 2020, from https://matplotlib.org/.

      4 MetPy — MetPy 0.12. (n.d.). Retrieved November 25, 2020, from https://unidata.github.io/MetPy/latest/index.html.

      5  NumPy. (n.d.). Retrieved November 25, 2020, from https://numpy.org/

      6 Overview: Why xarray? — xarray 0.16.2.dev3+g18a59a6d.d20200920 documentation. (n.d.). Retrieved November 25, 2020, from http://xarray.pydata.org/en/stable/why‐xarray.html.

      7 pandas documentation — pandas 1.1.4 documentation. (n.d.). Retrieved November 25, 2020, from https://pandas.pydata.org/pandas‐docs/stable/index.html.

      8 Vaze, P., Neeck, S., Bannoura, W., Green, J., Wade, A., Mignogno, M., et al. (2010). The Jason‐3 Mission: completing the transition of ocean altimetry from research to operations. In R. Meynart, S. P. Neeck, & H. Shimoda (Eds.) (p. 78260Y). Presented at the Remote Sensing, Toulouse, France. https://doi.org/10.1117/12.868543.