On day four on the new job, my boss made me the data curator of record for a popular dataset. Gulp. Day FOUR! I did NOT think I was ready.
Within an hour, I fielded the first phone inquiry. Luckily, it was an easy question and I knew the answer off the top of my head.
In two weeks of answering questions and reading the download logs, I realized how many data users come from poor countries that cannot afford pricey data analysis and visualization software.
Our family trip to Tanzania in 2010 taught me the value of convertible currencies--or rather how hard life can be when your nation's currency is not accepted as payment abroad. If you need something made abroad, how do you pay for it? You need to have something that people will pay you for in dollars, euros or yen so you can convert it into dollars (if needed) to purchase it.
This has major implications. Say you need gas or diesel for fuel and asphalt for roads. The term petrodollars refers to the OPEC agreement to set the price of crude oil in dollars. If your currency isn't convertible to dollars, how do you get the crude oil to make that gas, diesel and asphalt? What kind of transportation network would you have without dollars? Without all-weather roads and vehicles, how do you grow your economy and get your goods to markets where they will fetch better prices?
I can't control OPEC, but I can help--in my own small way--by helping scientists and risk managers in poor countries access and use weather and climate data without spending scarce convertible cash.
Behold, my current obsession.
GRIB data and makes it ready for further analysis--all using public domain or open-source software Furthermore, it is my goal to figure out cross-platform and easily accessible ways to do this.
Can you pick out the summer hemisphere? Or the day/night sides? Yowza, Siberia and the Himalayas are cold.
Do you know why the tropopause temperature appears to be anti-correlated with the surface temperature?
Anyway, I was just getting the hang of being a reference librarian for this dataset and making plans to update the help pages (including adding tutorials!) when my boss added a half dozen more datasets to my workload.
They are not nearly so popular, so they shouldn't demand as much time. But, seriously? People use BUFR in real life?
My boss has plans to put me on YouTube so I can teach people how to be bona fide weathergirls. Stay tuned for a link when the tutorials go live.
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