Modeling the Ocean Mixed Layer Response to Atmospheric Monsoon Forcing

Leah Johnson, Brown University, Providence, RI, United States, Baylor Fox-Kemper, Brown University, Earth, Environmental and Planetary Sciences, Providence, RI, United States and Qing Li, Los Alamos National Laboratory, Los Alamos, NM, United States
Sea surface temperature variability plays a key role in monsoon intraseasonal oscillation dynamics over the Bay of Bengal. The relatively shallow mixed layers and strong surface forcing throughout the bay implies a fast timescale of mixed layer response on the order of days and weeks that are relevant for the monsoon. This work compares a suite of 1-D mixed layer models to examine model fidelity during the monsoon intraseasonal oscillation. A dynamical systems approach combined with classic turbulence theory provides a framework to evaluate the mixed layer model response over a range of forcing conditions and isolates the parameter space where model fidelity breaks. This method is then applied to multiple case studies during the summer monsoon. Results show that mixed layer models diverge from each other during active monsoon spells yet converge during break periods. The variability of sea surface temperature predicted by the different models can exceed the observed geographic variability of SST within the bay, implying a fundamental error in modeling the 1-D response of the upper ocean that can be comparable to the effects of lateral processes. This inherent timescale of model error and agreement as a function of active and break spells is discussed in terms of air-sea feedback, mixed layer memory and model prediction.