Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction

Frontiers in Marine Science

Ibrahim Hoteit¹  Simona Masina²  Doroteaciro Iovino²  Matthew J. Martin³  Andrew M. Moore⁴  Paul Sandery⁵  Christopher C. Chapman⁵  Terry O’Kane⁵  Bernadette M. Sloyan⁵  Thomas Moore⁵  Andrea Storto⁶  Aneesh Subramanian⁷  SungHyun Nam⁸  Chunxue Yang⁹  Yosuke Fujii^1,10  Catia Domingues^1,11  James A. Carton^1,12  Stephen G. Penny^1,12  Hao Zuo^1,13  Frederic Vitart^1,13  Patricia de Rosnay^1,13  Magdalena A. Balmaseda^1,13  Philip Browne^1,13  Dinand Schepers^1,13  Patrick Laloyaux^1,13  Matthieu Chevallier^1,14  Francois Counillon^1,15  Santha Akella^1,16  Sergey Frolov^1,17  Patrick Hogan^1,18  Patrick Heimbach^1,19 

[1] 0King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;1Euro-Mediterranean Center on Climate Change, Lecce, Italy;2Met Office, Exeter, United Kingdom;3University of California, Santa Cruz, Santa Cruz, CA, United States;4Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT, Australia;5NATO Centre for Maritime Research and Experimentation, La Spezia, Italy;6Department of Atmospheric and Oceanic Science, University of Colorado, Boulder, Boulder, CO, United States;7Seoul National University, Seoul, South Korea;8Istituto di Scienze Marine, Consiglio Nazionale delle Ricerche, Rome, Italy;9JMA Meteorological Research Institute, Tsukuba, Japan;Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, TAS, Australia;Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, United States;European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom;Météo-France, Toulouse, France;Nansen Environmental and Remote Sensing Center, Bergen, Norway;National Aeronautics and Space Administration, Goddard Space Flight Center, Greenbelt, MD, United States;Naval Research Laboratory, Monterey, CA, United States;Naval Research Laboratory, Stennis Space Center, MS, United States;The University of Texas at Austin, Austin, TX, United States;

关键词: data assimilation;    reanalysis;    coupled data assimilation;    S2S prediction;    decadal prediction;    ocean observation network;   

DOI  :  10.3389/fmars.2019.00391

来源: DOAJ

【 摘 要 】

Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate as well as the initialization of operational long-range prediction models. There are many remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean-observing system throughout its history, the presence of biases and drifts in models, and the simplifying assumptions made in DA solution methods. From a governance point of view, more support is needed to bring the ocean-observing and DA communities together. For prediction applications, there is wide agreement that protocols are needed for rapid communication of ocean-observing data on numerical weather prediction (NWP) timescales. There is potential for new observation types to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of NWP, covering hours to weeks, out to multiple decades. Better communication between DA and observation communities is encouraged in order to allow operational prediction centers the ability to provide guidance for the design of a sustained and adaptive observing network.

【 授权许可】

Unknown