Efficient online data assimilation for coupled atmosphere-ocean field reconstructions

Abstract:

Coupled interactions between the ocean and the atmosphere are fundamental to low-frequency variability of the Earth System. While the instrumental record provides an account of this coupled variability, the relatively short length of the record often hinders investigation of the mechanisms of variability on decadal and longer timescales. Moreover, even during the instrumental period, consistent reanalysis of the coupled atmosphere—ocean system remains on open challenge. Recent reconstruction studies using data assimilation (DA) provide an objective framework for estimating coupled fields over longer periods, but they often omit dynamical constraints from forecasts between analysis times, affecting their representation of ocean memory and coupled dynamics. Linear inverse models (LIMs) offer an efficient method to incorporate temporal dynamics with forecasts based on coupled global climate models (GCMs). In this talk, we provide a brief overview of multi-variate LIMs for online DA within the Last Millennium Reanalysis framework and our newest annually-resolved atmosphere-ocean reconstructions over the Common Era.

The introduction of dynamical memory into the climate reconstruction significantly improves the consistency of upper-ocean heat content (OHC) estimates and its relationship with sea-surface temperature (SST). Additionally, the inclusion of LIM forecasts provides a base dynamical consistency with GCMs when proxy information is limited. Ocean indices calculated from reconstructed SST and OHC fields, including ENSO, the PDO, and global averages, show high correlation (~0.6 – 0.9) when validated against instrumental products. Compared to previous reconstructions, online DA reconstructions show cooler large-scale average temperatures, especially over 1000 – 1200 C.E. (~0.25 – 0.5 K cooler). Despite cooler large-scale average temperatures, the reconstructions highlight periods of multi-decadal warmth over high-latitude Europe during this time, consistent with previous work.