Abstract:

During the last years the members of the group have been using [1] the R computer language (www.cran-r.org) both for research and lecturing as well. It allows a Project Based Learning approach in which students interact with each other while becoming familiar with a programming language already adopted by many scientific communities as a standard. Some of the topics that are currently being taught using R are “Physics of the Atmosphere” and “Satellite Oceanography and Meteorology” at the MSc level. The R language allows the students performing powerful data analysis tasks in the same computer language that they can use during their future research, since R is a data analysis language that is spreading very fast in the scientific community. Additionally, it is free software, which makes it a good alternative for students that might not have the resources needed to buy a license.

One of the topics that is taught to students from the “Physics of the Atmosphere” course is atmospheric thermodynamics. A core part of this curriculum consists in students performing computations involving buoyancy, vertical evolutions of a particle given an ambient sounding and atmospheric stability, amongst others. During the last six years, these concepts have been taught to students using standard R functions. However, in order to improve the performance of the code, we have ported substantial parts of the code to a C extension that is called from R, developing this way the library “aiRthermo”.

This package allows the user (currently not only our students, but other members of the scientific community as well) to perform simple computations regarding the density of dry and moist air, conversion between different moisture indices, and, particularly, adiabatic and pseudoadiabatic evolutions of air parcels given an ambient sounding, leading this way to estimations of several instability indices (K, Total-Totals, Lifted Index or CAPE/CIN, amongst others).

Through the use of this library, the students are trained in the analysis of convective instability. They are also assigned different homeworks. The availability of this code makes them easy to numerically calculate complex tasks such as quantitative estimations of temperature differences due to the Föhn effect. This is made possible by the fact that the evolution of the lifted air parcel can be returned to the calling routine by the software. Plotting routines in the package allow to produce a Stüve diagram that includes the original sounding and the trajectory of the lifted air parcel as well. This way, the students are able to improve their understanding of the topic. The code in aiRthermo is also available to other researchers through CRAN, and we hope that this helps other students/professors to benefit from its use. https://cran.r-project.org/package=aiRthermo

References:
[1] Ibarra-Berastegi, G. Saenz, J, Esnaola, G. 2016. TEACHING MSc STUDENTS HOW TO HANDLE SATELLITE IMAGES FOR OCEANIC STUDIES USING R. EDULEARN 2016 8TH INTERNATIONAL CONFERENCE ON EDUCATION AND NEW LEARNING TECHNOLOGIES pp. 0631 - 0637. : ISSN 2340-1117, ISBN 978-84-608-8860-4

Keywords:

Atmospheric thermodynamics, aiRthermo, R, CRAN.