Towards improvement in process understanding and modeling of the Tropical Pacific

Abstract:

Monitoring and forecasting weather and climate variations to serve societal needs are major community endeavours, relying on a suitable and sustained observing system and high quality numerical models able to integrate the observational information and propagate it into the future. The need of observations for data assimilation is widely recognized, and a governance framework to ensure quality control and timeliness of observations has long been put in place. Comparatively less attention has been paid to the value of observations for model and data assimilation improvement. Yet, the quality of the models and data assimilation underpins the capability for optimal use of the observational information. Here we advocate for a consistent and holistic framework to ensure that observational processes studies end up integrated into forecasting systems. As a starting point, we identify key limiting aspects on the model representation of the Tropical Pacific climate system that need to be overcome to guarantee success of future coupled reanalyses and forecasting systems. We then discuss how TPOS can facilitate process studies targeting these key aspects, and we end-up spelling out additional steps needed to close the process-understanding-to-model-improvement continuous integration cycle