Yanai Waves in the Deep East Indian Ocean Observed with Seismic Ocean Tomography
Abstract
Near-surface measurements of meridional velocity suggest that wind forcing excites equatorial waves in the biweekly band in the Indian Ocean. The characteristics of these waves in the deep ocean are poorly constrained, and it is unclear how well models capture the deep variability. In this work, biweekly temperature variations in a few low vertical modes in the deep east Indian Ocean are observed using seismically generated sound waves. These so-called T waves are generated by earthquakes off Sumatra and received by a hydrophone station off Diego Garcia. Changes in their travel times reflect temperature-induced sound speed variations in the intervening ocean. Regression analysis indicates that these variations are caused by westward-propagating Yanai waves. A comparison between T-wave data and model output shows generally good consistency in biweekly variations dominated by the first three vertical modes, although the biweekly variance differs by up to a factor of 2 between the data and the models. A similar degree of discrepancy appears in the comparison between the models and deep mooring measurements. These results highlight the potential of using T-wave data to study biweekly Yanai waves in the deep equatorial ocean and to calibrate numerical simulations of the variability they cause. Significance Statement Biweekly Yanai waves are an important mode of variability in the tropical Indian Ocean, affecting the Indian and Australian–Indonesian monsoons. This study examines biweekly Yanai waves in the east Indian Ocean using sound waves generated by natural repeating earthquakes. The sound waves sample the deep structure of Yanai waves, which has been poorly constrained by previous observations. The seismic data generally show good consistency with output from two ocean general circulation models, although quantitative differences are manifested and can help improve the representation of Yanai waves in numerical models.
Copyright and License
© 2025 American Meteorological Society.
Acknowledgement
S. P. and J. C. gratefully acknowledge support from the National Science Foundation under Grant OCE-2023161. The computations presented here were conducted on the Resnick High Performance Computing Center, a facility supported by the Resnick Sustainability Institute at the California Institute of Technology. We sincerely thank Pattabhi Rama Rao and Uday Bhaskar of INCOIS, who kindly provided us with current-meter observations. This is PMEL Contribution 5644.
Data Availability
The IMS hydrophone data are available directly from the CTBTO on request and signing a confidentiality agreement to access the virtual Data Exploitation Centre (vDEC: https://www.ctbto.org/resources/for-researchers-experts/vdec). All seismic data were downloaded through the IRIS Data Management Center (https://ds.iris.edu/ds/nodes/dmc/), including the seismic networks II (GSN; https://doi.org/10.7914/SN/II) and MY, PS, GE (https://doi.org/10.14470/TR560404). Global Seismographic Network (GSN) is a cooperative scientific facility operated jointly by the Incorporated Research Institutions for Seismology (IRIS), the U.S. Geological Survey (USGS), and the National Science Foundation (NSF), under Cooperative Agreement EAR-1261681. Bathymetry data were downloaded from and freely available at https://download.gebco.net/. Argo data were downloaded from https://sio-argo.ucsd.edu/RG_Climatology.html. Argo data were collected and made freely available by the International Argo Program and the national programs that contribute to it (https://www.argo.ucsd.edu and https://www.ocean-ops.org). The Argo program is part of the Global Ocean Observing System. ECCO data were available at https://podaac.jpl.nasa.gov/dataset/ECCO_L4_TEMP_SALINITY_05DEG_DAILY_V4R4. The processing code is available at https://github.com/joernc/sot and https://github.com/Shirui-peng/SOTgpm. The sediment thickness data were downloaded from https://ngdc.noaa.gov/mgg/sedthick/. JRA-55-do dataset is provided online (https://esgf-node.llnl.gov/search/input4mips/ search with the keyword “OMIP”). The mooring velocity data are available from INCOIS (https://incois.gov.in/portal/datainfo/cm.jsp).
Files
phoc-JPO-D-24-0107.1.pdf
Additional details
Funding
- National Science Foundation
- OCE-2023161
Dates
- Accepted
-
2025-01-08
- Available
-
2025-04-28Published online
Caltech Custom Metadata
- Caltech groups
- Division of Geological and Planetary Sciences (GPS) , Resnick Sustainability Institute
- Publication Status
- Published