Abstract
The annular mode at the surface, referred to as the Arctic Oscillation (AO) in the Northern Hemisphere and the Antarctic Oscillation (AAO) in the Southern Hemisphere, is statistically defined by the leading mode of variability of sea level pressure (SLP) or geopotential height. Its principal component time series is set as the AO or AAO index. Although this metric is widely used, it needs an empirical orthogonal function analysis which introduces the complexity in the multi-model analysis. As an alternative measure, the zonal index (ZI), which is traditionally defined as the zonal-mean SLP difference between the two reference latitudes, has also been used. Here we re-evaluate the interannual and trend relationships between the ZI and the AO/AAO index using the two reanalysis datasets and 35 climate model simulations for both the present and future climate. For all datasets, the spatio-temporal variability of the Southern-Hemisphere ZI is almost identical to that of the AAO index. The ZI is still useful to examine the AO-related circulation variability and change in the Northern Hemisphere but mostly in the cold season. The data-dependent ZI, optimized for each data, exhibits a rather weak relationship with the AO index. This result suggests that the interannual variability and long-term trend of the midlatitude circulation can be concisely quantified by computing the fixed-latitude ZI in all seasons in the Southern Hemisphere and in the cold season in the Northern Hemisphere, not only for reanalysis data but also for climate model datasets which have significant biases varying from model to model.
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Acknowledgements
We thank to Jaemi Lee and Seoyeon Kim for proofreading. This work was supported by the project entitled “Development of Advanced Science and Technology for Marine Environmental Impact Assessment” [grant number 20210427], funded by the Ministry of Oceans and Fisheries of Korea (MOF). J. Choi was supported by the Basic Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Education (NRF-2019R1I1A1A01057039). We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Section 2 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The original CMIP5 database can be downloaded from the ESGF server (https://esgf-node.llnl.gov). The NNR and JRA-55 datasets were obtained from NOAA and JRA web interfaces (https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html and https://jra.kishou.go.jp/JRA-55/index_en.html, respectively).
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Son, SW., Shin, JH., Park, HS. et al. The Relationship Between the Zonal Index and Annular Mode Index in Reanalysis and CMIP5 Models. Asia-Pacific J Atmos Sci 58, 117–126 (2022). https://doi.org/10.1007/s13143-021-00244-3
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DOI: https://doi.org/10.1007/s13143-021-00244-3