[ncl-talk] Important announcement regarding the future of NCL

Fri Feb 8 06:44:08 MST 2019

Hi Puneet,

I think you make a lot of great points, particularly on the
analysis/factoring side. I would like to clarify my comments regarding I/O,
using your first two (***emphasis mine***).

----
"Handling of netcdf, hdf and grib data is easy. There are ***packages such
as pyhdf, netcdf4-python and pygrib***. Also for .h5 files there is ***h5py
package***. CSV data handling is also available."

"I use the python ecosystem called CDAT developed at LLNL (
http://cdat.llnl.gov/) . It has ***packages such as cdms2*** to easily
handle netcdf data I/O and its metadata. It is capable of handling large
data sets of size of the order of GBs. It also has ***packages such as
cdutil and genutil*** for performing various statistical analysis of time
series data from simulations and observations..."
----

The fact that users need to be A.) familiar with multiple packages for
handling data and B.) careful to keep them all up-to-date/compatible with
constantly evolving software while maintaining backwards portability is a
concern of mine.

I (again, my two cents) think the potential gap in an NCL -> Python
transition is not that packages *don't exist* for
reading/massaging/analyzing files, but that the ecosystem for handling said
files is somewhat fractured -- instead of being familiar with one syntax I
have to be familiar with 4 or 5 (or very proficient and Google/copying code
snippets!). netCDF I/O highlights this potential issue specifically, where
it has still be difficult for me to nail down a superior choice of
netcdf4-py, xarray, pynio, etc. and what my "best practices" should be when
using said package(s). Ex: now that pynio is going into maintenance mode,
should I go back and refactor all my existing python to use netcdf4-py to
ensure it is usable in the future?

Currently, with NCL I can read a GRIB or NetCDF file and subset a defined
time between -30S and 30N as, while attaching all coordinate/attribute data
roughly as:

f=addfile("./myfile.nc","r")
mytime=cd_inv_calendar(2018,01,04,06,0,0,f->time at units, 0)
myvar=f->var(mytime,{-30.:30.},:)

I can write a netcdf file...

fout=addfile("./myoutput.nc" ,"c")
filedimdef(fout,"time",-1,True)
fout->var=myvar

which automatically writes all coordinates, attributes, the time dimension,
etc. to said *nc file. I have yet to find a matching syntax in a Python
package with such brevity that is also straightforward.

So to clarify, while I am confident that I will be able to reproduce my
workflows in Python, I am less confident that I'll be able to do so in as
clean and straightforward manner as I have historically done.

It is here I plan to lean on the NCL team and general community for
guidance on A.) which package(s) to use for porting and long-term stability
and B.) best practices that allow me to generalize my future Python code to
multiple dataset formats, types, etc.

Apologies for any confusion,
-Colin

On Fri, Feb 8, 2019 at 4:05 AM Puneet Sharma <puneet.988 at gmail.com> wrote:

> Hello all
>
> Since I extensively use python for analysis of data generated from model
> simulations and satellite data, I would like to share some of the strong
> points of python.
>
> 1. Handling of netcdf, hdf and grib data is easy. There are packages such
> as pyhdf, netcdf4-python and pygrib. Also for .h5 files there is h5py
> package. CSV data handling is also available.
>
> 2. I use the python ecosystem called CDAT developed at LLNL (
> http://cdat.llnl.gov/
> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fcdat.llnl.gov%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329364817&sdata=T9UxuHXSIKpLqrvmtNg1wSQKk7GczRoEadE4yCG9qO0%3D&reserved=0>)
> . It has packages such as cdms2 to easily handle netcdf data I/O and its
> metadata. It is capable of handling large data sets of size of the order of
> GBs. It also has packages such as cdutil and genutil for performing various
> statistical analysis of time series data from simulations and observations.
> Since the data usually has masks and fill values, the functions and
> procedure available in these packages automatically take care of that.
> Compared with NCL, CDAT seamlessly handles masking of data using the MV2
> package. All of these packages have numpy as their base which is a python
> package for manipulating numerical data. I have struggled with NCL for
> masking data which lead me to switch to python.
>
> 3. Regridding of data and handling of various grids and interpolation
> routines which are available in NCL are also available CDAT.
>
> 4. String manipulation, data subsetting is very intuitive in python
> (CDAT). Moreover python code is highly readable since it requires forced
> indentation which keeps the code clean and readable.
>
> 5. The exceptional plotting libraries available in python such as
> matplotlib, seaborn, bokeh etc have an edge over NCL since very few lines
> of code can produce complex plots in publication format.
>
> 6. Python has intuitive data structures like dictionary, lists and
> functions like zip, enumerate for iteration which are not available in NCL
>
> The only place where I found python to be lagging was the spatial plotting
> of gridded data. Compared to matplotlib-basemap plotting tool, NCL gives
> far more clearer and visually appealing spatial plots. But that issue has
> already been solved through PyNGL package.
>
> I would further like to emphasise that together with the points mentioned
> above, there are many use cases in python which are not available in NCL
> such as
>
> 1. Interoperability with languages such as C, Java, R, FORTRAN since there
> are wrappers readily available for these languages.
>
> 2. Handling url requests for downloading data from different servers.
>
> 3. Handling of categorical data using the pandas package.
>
> 4. It is easy to call contemporary statistical functions and packages
> written in R through rpy2 package.
>
> I feel that python can become one single platform for performing different
> tasks related to atmospheric and climate data handling encompassing various
> tasks which are not yet available in NCL.
>
> I would be happy to clarify any questions.
>
> Regards
>
>
> On Fri, Feb 8, 2019 at 9:27 AM Barry Lynn <barry.h.lynn at gmail.com> wrote:
>
>> Hello
>>
>> Now that we read about the obvious advantages (logic and ease of i/o) of
>> NCL, is it possible for someone to list why someone would want to switch to
>> python?  What does python have for the scientist that NCL does not?
>>
>> Right now, I read netcdf files, ascii files, csv files, and I made graphs
>> and maps, as well as write data using Fortran based programs (WRAPIT).  I
>> find this all relatively easy to do (I do it, so it can't be too hard, it's
>> just a lot to know!).
>>
>> Why haven't I switched to Python already.  It sounds like the wave of the
>> future!  What's in the wave?
>>
>> Barry
>>
>> On Fri, Feb 8, 2019 at 4:05 AM Colin Zarzycki <czarzycki at psu.edu> wrote:
>>
>>> Like Carl, I have assumed this inevitability, although I have also
>>> scientifically "grown up" with NCL over the past decade+ and have many
>>> hundreds (probably thousands!) of hours invested in using NCL to answer a
>>> vast array of scientific questions. While I think the community's march
>>> towards Python has some underappreciated warts (I spent a couple hours
>>> updating/rolling back/softlinking mismatched libraries on my personal
>>> machine after simply running conda update last week), there is no denying
>>> that its growth across, not only Earth, but the broader data sciences and
>>> rising stature in university curricula makes it likely the preeminent tool
>>> of the next generation of researchers. For better or for worse, adoption
>>> and growth of languages are driven by the size/engagement of their userbase
>>> instead of optimal practicality for each individual.
>>>
>>> A couple thoughts after reading the pivot roadmap...
>>>
>>> A.) Based on my "toe-in-the-water geoscience Python scripting" the last
>>> few years, I actually think one of the weaker points in (right now) is that
>>> I have yet to find a workflow for weather/climate data I/O where opening,
>>> massaging, and writing netCDF datasets (and their corresponding variables,
>>> dimensions, etc.) comes with the same ease as in NCL. Some of that is
>>> naturally due to tremendous work that has been undertaken in the past to
>>> support multiple formats behind the curtain, but this also includes NCL's
>>> amazingly useful calendar routines, coordinate subscripting, simple
>>> handling of attributes, ability to trivially output a new *.nc file in 3
>>> lines, etc. As the roadmap notes on pg. 13-14, currently a host of somewhat
>>> fractured Python packages that can lack clean, easy-to-understand syntax
>>> are used by the community and (to me) this is a large gap that has remained
>>> unfilled even with the proliferation of Python support over the last few
>>> years.
>>>
>>> Therefore, I would argue additional examples* regarding side by side
>>> snippets of "writing Python for NCLers" with a specific emphasis on I/O
>>> would be incredibly helpful moving forward, particularly with respect to
>>> functionality NCL has historically "wrapped" to make life easier (for me,
>>> trading off ease-of-use for a little abstraction/processing inefficiency is
>>> OK, especially if it means I have time to grab a cup of coffee).
>>>
>>> B.) Hopefully I am interpreting the goal of NCOMP correctly, but I am
>>> also glad to see there is effort to port NCL's functions that are
>>> highly-specific to the atmospheric sciences (ex: aforementioned calendar
>>> routines, climatological analysis, vertical coordinate interpolation,
>>> etc.). This functionality is the workhorse when, for example, I can take
>>> data straight from a native model grid and have clean, interpolated,
>>> post-processed variables "on my desk" in a couple minutes with ~10 lines of
>>> code.
>>>
>>> -Colin
>>>
>>> *the first draft/examples on the NCL site from Karin Meier-Fleischer are
>>> already incredibly useful!
>>>
>>> On Thu, Feb 7, 2019 at 4:25 PM Adam Phillips <asphilli at ucar.edu> wrote:
>>>
>>>> Hi all,
>>>> Not everyone got my original post so I am resending this to the
>>>> cgd-etal list. My apologies for the duplicate email.
>>>>
>>>> See Mary Haley's email below for information about the future of NCL.
>>>> Quick summary: NCL is *not* going away, NCL graphics will continue to
>>>> be developed, and the support structure remains intact. If you have any
>>>> questions, feel free to contact myself, Nan Rosenbloom, or Laura Landrum,
>>>> as all of us serve on the NCL Advisory Board.
>>>> Best,
>>>> Adam
>>>>
>>>> ---------- Forwarded message ---------
>>>> From: Mary Haley <haley at ucar.edu>
>>>> Date: Wed, Feb 6, 2019 at 6:24 AM
>>>> Subject: [ncl-talk] Important announcement regarding the future of NCL
>>>> To: Ncl-talk <ncl-talk at ucar.edu>
>>>>
>>>>
>>>> Dear NCL Users,
>>>>
>>>> This letter is in regard to the future of NCL, following NCAR's
>>>> decision to move to Python as the scripting language of choice for future
>>>> visualization and analysis software development. Note that this decision
>>>> targets new development, leaving existing NCL functionality intact.
>>>>
>>>> NCAR is committed to supporting data analysis software for atmospheric,
>>>> oceanic, and climate science research. However, decreases in budgets and
>>>> staff, coupled with the enormous functionality that Python brings to the
>>>> earth sciences, has made it difficult to justify continuing new development
>>>> on NCL. Python has seen rapid adoption by the earth science community and
>>>> duplicates much of NCL's functionality, while adding critical features that
>>>> NCL doesn't offer.
>>>>
>>>> Based on recommendations from NSF, CISL and NCL advisory panels, the
>>>> results of the NCL survey, and months of evaluating different strategies
>>>> for the future development and support of NCL, NCAR has arrived at these
>>>> major decisions, effective immediately:
>>>>
>>>>    - Python will be adopted as the scripting language platform for
>>>>    future visualization and analysis development.
>>>>    - NCL's core language and file I/O will be placed into maintenance
>>>>    mode.
>>>>    - NCL's graphics will have continued development through PyNGL
>>>>    <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.pyngl.ucar.edu&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329374786&sdata=EmUPhs%2Bznl0n%2BfSn5FvTxNRZAEglW2wPjJoE0hPYBTI%3D&reserved=0>
>>>>    ***.
>>>>    - NCL's unique and critical computational routines will be ported
>>>>    to an as-yet-to-be-named Python package.
>>>>    - PyNIO
>>>>    <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.pyngl.ucar.edu%2FNio.shtml&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329374786&sdata=YBh0FYsusbznXL4iwcc7m%2FBSLMVYhUMr3Dr4FfH5utQ%3D&reserved=0>
>>>>    *** will be placed into maintenance mode.
>>>>    - Development will continue on WRF-Python
>>>>    <https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwrf-python.readthedocs.io%2Fen%2Flatest%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329384791&sdata=EOLfxBPDxSY4mF7LaFbVG8mXE0zOKMkxbYOJQh%2BzVwk%3D&reserved=0>
>>>>    ***.
>>>>    - All software, including NCL and PyNIO, will be moved to a more
>>>>    open development software platform to allow for continued community
>>>>    development.
>>>>
>>>> *** PyNIO, PyNGL, and WRF-Python are Python modules built on top of
>>>> NCL libraries, and are developed and supported by the NCL team.
>>>>
>>>>
>>>> NCAR recognizes the significance of these changes. It will take time
>>>> for NCL users to transition to Python, and some users may not want to make
>>>> the switch at all. As such, we want to stress that NCL is not going away.
>>>> NCL users will be able to download NCL and execute their scripts for the
>>>> foreseeable future.
>>>>
>>>> To help users who want to begin transitioning their graphical NCL
>>>> scripts to PyNGL right away, Karin Meier-Fleischer of DKRZ has written a
>>>> first draft of an "NCL-to-Python Transition Guide
>>>> <http:///www.ncl.ucar.edu/Document/Manuals/NCL_to_Python/Transition_Guide_NCL_PyNGL.pdf>"
>>>> accompanied by a suite of NCL and Python examples
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.ncl.ucar.edu%2FApplications%2FNCL_to_Python%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329394845&sdata=k3FG0t6xfujiS5gd7XPex01Q7GvyNcJi2B1cWgO8SBY%3D&reserved=0>.
>>>> Additionally, we will soon begin converting a subset of the NCL application
>>>> examples to Python, using PyNGL
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.pyngl.ucar.edu%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329394845&sdata=hYXGosu2HTtUlyuhsOzLH97oRnlqXP4ZvFg0rz9eSlg%3D&reserved=0>
>>>> and matplotlib
>>>> <https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fmatplotlib.org&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329404810&sdata=XjcqHswb5%2B9OUFokSahHrdfwOIvV%2BXJK2%2BTVfCn9b%2Fk%3D&reserved=0>,
>>>> and will continue to answer questions on the ncl-talk
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmailman.ucar.edu%2Fmailman%2Flistinfo%2Fncl-talk&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329414815&sdata=cQ33ooiYHy0uXHIelw4%2FgN13CZLIJWFH%2Focc9STx3Is%3D&reserved=0>
>>>> email list, but scaling back in order to start helping with Python
>>>> questions.
>>>>
>>>> For a detailed report and roadmap on the "pivot to Python" decision and
>>>> transition plan, please read the "NCL and the Pivot to Python:
>>>> Discussion and Roadmap
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.ncl.ucar.edu%2FDocument%2FPivot_to_Python%2FNCL_Pivot_to_Python_Report_and_Roadmap.pdf&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329414815&sdata=20Cze1zNBLIshsLTPcMdhlamxFowLYg5kJIzqtlTZ7M%3D&reserved=0>"
>>>> report, which can be found on a special page we created containing other
>>>> supporting documents
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.ncl.ucar.edu%2FDocument%2FPivot_to_Python%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329424833&sdata=LklVI7m0aT%2BkbI65oS0%2BnNnZlelDJ5sYmCSeJyR5%2BPY%3D&reserved=0>
>>>> .
>>>>
>>>> The NCL team welcomes your input on this decision. We also want to know
>>>> if there are other ways we can help ease the transition to Python and
>>>> encourage users to become more active contributors through open
>>>> development. Please use this GitHub issue
>>>> <https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FNCAR%2Fncl%2Fissues%2F64&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329434829&sdata=coO0pqbI1PIYncvcLTXrNVoDb5mdBVhJrvfcM7aoqMo%3D&reserved=0>
>>>> to submit questions or comments so we can keep the discussion public.
>>>>
>>>> *NCL Team:*
>>>> John Clyne (acting group head)
>>>> Rick Brownrigg
>>>> Mary Haley
>>>> Kevin Hallock
>>>> Bill Ladwig
>>>>
>>>>
>>>>
>>>>
>>>> _______________________________________________
>>>> ncl-talk mailing list
>>>> ncl-talk at ucar.edu
>>>> List instructions, subscriber options, unsubscribe:
>>>> http://mailman.ucar.edu/mailman/listinfo/ncl-talk
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmailman.ucar.edu%2Fmailman%2Flistinfo%2Fncl-talk&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329434829&sdata=GW7fysQG1uZKKyM4OZWdKWAkSj%2B2hfSKc79Q3DROk6c%3D&reserved=0>
>>>>
>>>>
>>>> --
>>>> Adam Phillips
>>>> Associate Scientist,  Climate and Global Dynamics Laboratory, NCAR
>>>> www.cgd.ucar.edu/staff/asphilli/
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.cgd.ucar.edu%2Fstaff%2Fasphilli%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329444834&sdata=L1mVw4W6lgytQ1l1NDjrQmnMrYNBJH5DtJ4%2FQhl25hU%3D&reserved=0>
>>>> 303-497-1726
>>>>
>>>>
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.cgd.ucar.edu%2Fstaff%2Fasphilli&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329454843&sdata=Xf8uu9gA4auoBpZOEhbn5PmheZxb8s9J1mU2L4GDJxw%3D&reserved=0>
>>>>
>>>>
>>>> --
>>>> Adam Phillips
>>>> Associate Scientist,  Climate and Global Dynamics Laboratory, NCAR
>>>> www.cgd.ucar.edu/staff/asphilli/
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.cgd.ucar.edu%2Fstaff%2Fasphilli%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329454843&sdata=IPrK4QjYJa27o0CRK2nDReOC1IM2uTE5oIyFvHlMtBI%3D&reserved=0>
>>>> 303-497-1726
>>>>
>>>>
>>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.cgd.ucar.edu%2Fstaff%2Fasphilli&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329464848&sdata=c16MxUfIcZIpATjPVNdb%2BaOAknGIzJZKQdRaTGXOkGA%3D&reserved=0>
>>>>
>>>
>>>
>>> --
>>> Colin M. Zarzycki, Ph.D.
>>> Assistant Professor of Meteorology and Climate Dynamics
>>> Department of Meteorology and Atmospheric Science
>>> Pennsylvania State University
>>> Web: http://www.colinzarzycki.com
>>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.colinzarzycki.com%2F&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329474902&sdata=l8dwjZxe7zqSfEMtOxtMabUMldAgkASPYG7yisnvZ7k%3D&reserved=0> |
>>> Office: +1 (814) 863-6888
>>> _______________________________________________
>>> ncl-talk mailing list
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>>>
>>
>>
>> --
>> Barry H. Lynn, Ph.D
>> Senior Associate Scientist, Lecturer,
>> The Institute of the Earth Science,
>> The Hebrew University of Jerusalem,
>> Givat Ram, Jerusalem 91904, Israel
>> Tel: 972 547 231 170
>> Fax: (972)-25662581
>>
>> C.E.O, Weather It Is, LTD
>> Weather and Climate Focus
>> http://weather-it-is.com
>> <https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fweather-it-is.com&data=02%7C01%7Ccmz5202%40psu.edu%7C5b27ea917f2c42e9cb7f08d68da493fe%7C7cf48d453ddb4389a9c1c115526eb52e%7C0%7C0%7C636852135329484862&sdata=7Agdci1ZASfjxpU1nUxOTmPNCkjuYPqkUUVnLeiB7fc%3D&reserved=0>
>> Jerusalem, Israel
>> Local: 02 930 9525
>> Cell: 054 7 231 170
>> Int-IS: x972 2 930 9525
>>
>> _______________________________________________
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>
>
> --
> Puneet Sharma
> Ph.D. Research Scholar
> Centre for Atmospheric Sciences
> IIT Delhi, Hauz Khas
> Contact No. 9891582124
>
> https://www.puneetks.com
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-- 
Colin M. Zarzycki, Ph.D.
Assistant Professor of Meteorology and Climate Dynamics
Department of Meteorology and Atmospheric Science
Pennsylvania State University
Web: http://www.colinzarzycki.com | Office: +1 (814) 863-6888
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