Abstract
The meridional heat transport (MHT) estimated at 26N in the Atlantic Ocean as part of the RAPID-MOCHA project is one of the prominent observable oceanic indices of the global climate. Understanding the linear relationship between the MHT and other global climate indicators is important for improving our understanding of climate dynamics and providing benchmarks for assessing earth system reanalysis products. The MHT time series exhibits significant correlation with various climate indices but the dynamical interpretation of these correlations is difficult since these indices are typically correlated among themselves. To clarify the implications of these correlations, we investigate the regression patterns between the MHT and field variables from the ERA5 monthly reanalysis dataset. We use a method that allows us to decompose these regression patterns into statistically significant spatio-temporal components that can be subsequently linked to known global climate indices. Our preliminary results suggest that up to 40% of the monthly variance of the MHT can be linearly attributed to three global modes. These modes, explaining 19, 13, and 8 percent of the MHT variance, are respectively strongly related to the Arctic Oscillation index, the Southern Oscillation index, and the Antarctic Oscillation index, which are three indices uncorrelated with each other. Yet, each of these three modes exhibits air-sea heat flux and 2-m atmospheric temperature patterns over northern hemisphere latitudes that are markedly different. This implies that the net impacts on regional climates of MHT changes at any time can vary depending on the global state of the climate system.
The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)