Modelling ocean diurnal cycle and its scale interaction to longer scale climatic variabilities

Abstract

Coupled climate models play a crucial role in weather and climate prediction/projection at different temporal (diurnal, intra-seasonal, seasonal, etc.) and spatial (short-range, extended-range, long-range) scales. Although coupled models have come a long way in their development, several challenges remain unaddressed, such as (a) underestimation of diurnal phase and amplitude in ocean and atmospheric parameters, (b) misrepresentation of phase and amplitude of intra-seasonal variability and feedbacks, and (c) high seasonal mean biases in air-sea interactive properties and precipitation, that hinders the weather and climate forecasts at various temporal and spatial scales. The present article documents these coupled modelling problems and explores a possible approach to address these issues. This study shows that representing the diurnal ocean skin temperature variability can be a way forward to overcome the long-lasting diurnal, intra-seasonal, and seasonal scale problems specifically linked to the Indian summer monsoon period. Through carefully designed sensitivity experiments, this study shows that the implementation of a diurnal skin temperature parameterisation along with a modern turbulent bulk flux algorithm improves the diurnal variability of surface ocean, subsurface ocean, and atmospheric convection. The diurnal improvements then scale interacts with longer range variabilities and also improves the representation of intra-seasonal and seasonal variabilities in a coupled climate model.