Investigating a Wet Bulb Globe Temperature Calculation for MetPy
30 July 2020
Caitlyn McAllister
by
Caitlyn McAllister
2020 Unidata summer intern
During the duration of this summer’s internship program I hit the ground running
by learning how to code in Python. Before this internship, I had only opened
Python a few times while attending classes and did a little coding in this
language for a collaborative project at my university. I familiarized myself over
the first month by using the workshops available in JupyterLab provided by
Unidata. I learned everything from loops to using the THREDDS data sever to plot
variables. Outside of the language, I got to learn how an online community works
with GitHub to share and process software and data. I also learned about
development environments, which I had no clue about before. I will definitely be
using all of these tools moving forward.
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Building Support for Efficient MetPy Calculations Across Large Datasets with Dask
30 July 2020
Russell Manser
by
Russell Manser
2020 Unidata summer intern
Coming into this summer, my goal was to integrate Dask Array support into MetPy. I
knew that this was an ambitious task, but I am happy to say that I made progress
toward accomplishing it!
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Enhancing the netCDF C++ Library and the Siphon Package
16 August 2019
Aodhan Sweeney
by
Aodhan
Sweeney
2019 Unidata summer intern
This summer at Unidata I worked on expanding functionality for both the netCDF C++ library
and the Python data access tool Siphon. Previously, the netCDF C++ library was
lacking important functionality that was included in other netCDF libraries. Fortunately,
adding this functionality is a straightforward process. I created function wrappers in the
C++ library that would call previously made functions in the C library. This allows those
working in a C++ framework to continue to use the netCDF libraries without sacrificing
additional functionality.
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Converting Ugly Text to Beautiful Maps:
Adding METAR Support in MetPy
16 August 2019
Max Grover
by Max Grover
2019 Unidata summer intern
The primary task that I completed this summer was adding METAR functionality to
MetPy. METAR stands for
METeorological Aerodrome Report. METARs contain information about surface data including
temperature, dew point, wind speed and direction, and several other meteorological
variables. Prior to this summer, MetPy did not have the ability to parse METARs. Also, the
current parser that is used to generate netCDF files on the Unidata THREDDS server had a
substantial amount of missing data. By adding METAR parsing tools, we made additional
surface data available to the user, making it easier to make high quality surface maps
using
MetPy.
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A Summer of Code and Outreach:
Have you heard of the Integrated Data Viewer?
16 August 2019
Jessica Blunt
by Jessica Blunt
2019 Unidata summer intern
The overarching theme of my projects this summer has been improving the accessibility of
the
Integrated Data Viewer (IDV) for
the average scientist. The IDV is a versatile and powerful, though complicated, program.
When I ask people if they’ve heard of the IDV, there are two types of answers that stand
out. The first, a simple “no” or “I think someone mentioned it
once.” The second, something
like “I’ve tried to figure it out, but didn’t get very far.” I worked to reach
those who
gave the second answer.
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