useR! 2024

In this presentation, we discuss the development of a custom solution for gridding oceanographic data using Spatio Temporal Kriging. The high computational load necessitated the use of lower level languages, and the computation time was significantly reduced through parallel processing. Applying the code to irregularly spaced oceanographic data observed in the field was a challenging process that required a flexible solution. We successfully gridded the oceanographic observational data using the developed code, demonstrating its effectiveness. Despite the high performance of tools like gstat, they did not meet the main project requirements as they do not support 4D input data that changes over space (xyz) and time (t). Moving forward, our goal is to enable the processing of as many datasets as possible at the level of personal computers, thereby promoting accessibility in research. We aim to share our experiences and insights, hoping to inspire further advancements in the field of oceanographic data analysis.