C++ - Meteo @ WUR

C++

Interesting coding problems in C++

Speeding up radiative transfer solvers with machine learning

Speeding up radiative transfer solvers with machine learning

Machine learning provides great opportunities for accelerating the representation of physical processes in weather and climate models. Radiative transfer solvers, which deal with the transport of solar and thermal radiation, are often the most costly parametrization in models. Speeding them up is one of the main ambitions of SLOCS [https:

The beauty of containers in C++11

The beauty of containers in C++11

Containers for storing data are one of many great features of the C++ Standard Library [https://en.wikipedia.org/wiki/C%2B%2B_Standard_Library]. Despite their advantages, to initialize them, and to loop over them was not always easy. Fortunately, the C++11 [https://en.wikipedia.org/wiki/C%