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Ocean observations to improve our understanding, modeling, and forecasting of subseasonal-to-seasonal variability

TitleOcean observations to improve our understanding, modeling, and forecasting of subseasonal-to-seasonal variability
Publication TypeJournal Article
Year of Publication2019
AuthorsSubramanian AC, Balmaseda M.A, Centurioni L, Chattopadhyay R., Cornuelle BD, DeMott C., Flatau M., Fujii Y., Giglio D., Gille ST, Hamill T.M, Hendon H., Hoteit I., Kumar A., Lee J.H, Lucas A.J, Mahadevan A., Matsueda M., Nam S., Paturi S., Penny S.G, Rydbeck A., Sun R., Takaya Y., Tandon A., Todd R.E, Vitart F., Yuan D.L, Zhang C.D
Date Published2019/08
Type of ArticleReview
Accession NumberWOS:000479256900001
Keywordsair-sea interaction; Argo; assimilation; california current system; coupled data; diurnal cycle; drifters; ensemble; Environmental Sciences & Ecology; gliders; ice; impacts; madden-julian oscillation; Marine & Freshwater Biology; pacific; predictions; satellite; sea interaction research; seasonal; subseasonal

Subseasonal-to-seasonal (S2S) forecasts have the potential to provide advance information about weather and climate events. The high heat capacity of water means that the subsurface ocean stores and re-releases heat (and other properties) and is an important source of information for S2S forecasts. However, the subsurface ocean is challenging to observe, because it cannot be measured by satellite. Subsurface ocean observing systems relevant for understanding, modeling, and forecasting on S2S timescales will continue to evolve with the improvement in technological capabilities. The community must focus on designing and implementing low-cost, high-value surface and subsurface ocean observations, and developing forecasting system capable of extracting their observation potential in forecast applications. S2S forecasts will benefit significantly from higher spatio-temporal resolution data in regions that are sources of predictability on these timescales (coastal, tropical, and polar regions). While ENSO has been a driving force for the design of the current observing system, the subseasonal time scales present new observational requirements. Advanced observation technologies such as autonomous surface and subsurface profiling devices as well as satellites that observe the ocean-atmosphere interface simultaneously can lead to breakthroughs in coupled data assimilation (CDA) and coupled initialization for S2S forecasts.

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