Python in New Orleans: Once Bitten, Quickly Smitten

The upcoming 2012 AMS Annual Meeting in New Orleans is only the second with a whole symposium devoted to the use of Python programming language in the atmospheric sciences. The first was last year’s meeting in Seattle.
The quick return of Python to the conference program–including beginning and advanced short courses over the weekend (21-22 January)–suggests what a growing community of modelers and programmers already knows. Once they’ve encountered the Python language, people tend to become devotees.
“Python is an elegant and robust programming language that combines the power and flexibility of traditional compiled languages with the ease-of-use of simpler scripting and interpreted languages,” according to Filipe Pires Fernandes of  the School of Marine Science and Technology in New Bedford, Massachusetts, who presents Monday (23 January, 2 p.m.).
Python, for example, is at the heart of the National Weather Service’s graphical forecast editor (GFE) tool and thus at the basis of the usage of the whole gridded forecast product suite in effect over the last decade. “Python’s introspective capabilities permitted developers to build a tool framework in which forecasters could write simple expressions and apply them directly to the forecast process without the burden of needing to know details about data structures or user interfaces,” writes Thomas LeFebvre of NOAA, who will discuss (Tuesday, 24 January, 8:30 am) how “a large part of GFE’s success is the result of the rich set of features that Python offers.”
Symposium Chair Johnny Lin of North Park University produced a short video to explain the attraction of Python, now the “eighth most popular programming language in the world” and preview the upcoming symposium:

The symposium program features numerous new software packages, with many of the presentations demonstrating how Python is a solution to software quirks and limitations that have become more bothersome as technology advances. One presenter is using Python to display data and model output on Google Earth. Another developed a new Skew-T diagram and Hodograph visualization and research tool (SHARPY), recasting a standard program, SHARP, in Python. Explains Patrick Marsh of NOAA’s National Severe Storms Laboratory: “Unfortunately, SHARP utilizes several GEMPAK routines which makes compiling, let alone installing and using, a non-trivial task.”
Andrew Charles of the Bureau of Meteorology in Australia used Python to create a web-based tool to integrate contour plotting with GIS applications. “With ever increasing amounts of data being made available, the related increase in required storage means static plots are not a viable solution for the delivery of all maps to end users,” writes Charles about his (11:30 a.m. Tuesday) presentation. “Contour plots are one of the most used data visualisation techniques in meteorology and oceanography and yet, surprisingly, there are few available solutions for the generation of contour plots to be used as map overlays from live data sources.”

Emergency Response Technology Goes On Demand

When the American Red Cross responded the morning after the 24 May tornado outbreak in central Oklahoma, they had a new tool in their pocket. The Warning Decision Support System—Integrated Information (WDSS-II), developed by NOAA’s National Severe Storm Lab, cut disaster assessment time from 72 hours down to 24, a major improvement that could save many lives when it comes to rescue in the wake of a disaster.
The WDSS-II works by narrowing when and where the severe weather most likely occurred. Using radars, satellites, and other observation systems, the On Demand feature of the tool records tracks of rotation and hail swath images that can be opened in Google Earth. When street maps are overlaid with these images, disaster teams can assess which areas likely need assistance first, as well as the most accessible routes to take.
“They no longer have to put boots on the ground to visually assess the situation before planning how they will deploy response teams,” comments Kurt Hondl, NSSL research meteorologist. “It makes the coordination and planning of the American Red Cross’s response so much more efficient.”
The WDSS-II On Demand software is available to American Red Cross officers and other assessment organizations. More than 250 volunteers in Oklahoma and Texas have been trained so far by the Red Cross to utilize the NSSL On Demand software.  Other organizations, like FEMA and the Department of Homeland Security, have begun to take advantage of the technology as well.

Kermit Would Approve

It’s not easy being green, as Kermit the Frog famously lamented on the TV show, “Sesame Street,” but it might be getting easier thanks in part to the Tungara frog—a native of Central and South America. David Wendell of the University of Cincinnati recently led a study that developed a new type of foam that can absorb CO2 and convert it to sugar before it escapes into the atmosphere (a process that occurs naturally in plants during photosynthesis). A key ingredient in the foam, which could be placed into the exhaust systems of power plants, is a protein that is naturally created by the Tungara frog to form a foam nest that protects their eggs. (Here’s a brief video showing a frog weaving the nest.)  
“I read about a protein that the frog uses that allows bubbles to form in the nest, but doesn’t destroy the lipid membranes of the eggs that the females lay in the foam, and realized that it was perfect for our own foam,” says Wendell. The CO2-absorbing foam is an amalgam of numerous enzymes harvested from plants, fungi, bacteria, and frogs, and it converts all of the solar energy it captures into sugars, making it as much as five times more efficient than plants, and, according to Wendell, “the first technology that actually consumes more carbon than it generates.” The invention recently won the $50,000 grand prize at the 2010 Earth Awards, which were founded in 2007 to encourage innovative designs “to improve our quality of life and build a new economy.”