Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability
文献类型：期刊论文
| 作者 | Subramanian, Aneesh C.1; Balmaseda, Magdalena A.2; Centurioni, Luca3; Chattopadhyay, Rajib4; Cornuelle, Bruce D.3; DeMott, Charlotte5; Flatau, Maria6; Fujii, Yosuke7; Giglio, Donata1; Gille, Sarah T.3 |
| 刊名 | FRONTIERS IN MARINE SCIENCE
 |
| 出版日期 | 2019-08-08 |
| 卷号 | 6页码:8 |
| 关键词 | subseasonal seasonal predictions air-sea interaction satellite Argo gliders drifters |
| DOI | 10.3389/fmars.2019.00427 |
| 通讯作者 | Subramanian, Aneesh C.(aneeshcs@colorado.edu) |
| 英文摘要 | 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. |
| 资助项目 | NOAA Climate Variability and Prediction Program[NA14OAR4310276] ; NSF Earth System Modeling Program[OCE1419306] ; NASA[NNX14AO78G] ; NASA[80NSSC19K0059] ; NSFC[91858204] ; NSFC[41720104008] ; NSFC[41421005] ; [NA16OAR4310094] |
| WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology |
| 语种 | 英语 |
| 出版者 | FRONTIERS MEDIA SA |
| WOS记录号 | WOS:000479256900001 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/162339]  |
| 专题 | 中国科学院海洋研究所 |
| 通讯作者 | Subramanian, Aneesh C. |
| 作者单位 | 1.Univ Colorado, Atmospher & Ocean Sci, Boulder, CO 80309 USA 2.ECMWF, Reading, Berks, England 3.Univ Calif San Diego, Scripps Inst Oceanog, San Diego, CA 92103 USA 4.Indian Inst Trop Meteorol, Pune, Maharashtra, India 5.Colorado State Univ, Dept Atmospher Sci, Ft Collins, CO 80523 USA 6.US Naval Res Lab, Monterey, CA USA 7.Japan Meteorol Agcy, Meteorol Res Inst, Tsukuba, Ibaraki, Japan 8.NOAA, Earth Syst Res Lab, Div Phys Sci, Boulder, CO USA 9.Bur Meteorol, Melbourne, Vic, Australia 10.King Abdullah Univ Sci & Technol, Earth Sci & Engn, Thuwal, Saudi Arabia |
| 推荐引用方式 GB/T 7714 | Subramanian, Aneesh C.,Balmaseda, Magdalena A.,Centurioni, Luca,et al. Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability[J]. FRONTIERS IN MARINE SCIENCE,2019,6:8. |
| APA | Subramanian, Aneesh C..,Balmaseda, Magdalena A..,Centurioni, Luca.,Chattopadhyay, Rajib.,Cornuelle, Bruce D..,...&Zhang, Chidong.(2019).Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability.FRONTIERS IN MARINE SCIENCE,6,8. |
| MLA | Subramanian, Aneesh C.,et al."Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability".FRONTIERS IN MARINE SCIENCE 6(2019):8. |
入库方式： OAI收割
来源：海洋研究所
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