全球格点化海洋环境数据集研究进展
收稿日期: 2022-05-05
修回日期: 2022-07-15
网络出版日期: 2022-09-13
基金资助
国家重点研发计划项目“多域环境高性能计算服务化体系结构”(2018YFB0203801);国家自然科学基金项目“IaaS云环境下大规模科学工作流优化执行方法研究”(61572510)
Research Progress of Global Gridded Ocean Environment Datasets
Received date: 2022-05-05
Revised date: 2022-07-15
Online published: 2022-09-13
Supported by
the National Key Research and Development Program of China “High-performance computing servitizing architecture in multi-domain environment”(2018YFB0203801);The National Natural Science Foundation of China “Research on optimization execution method of large-scale scientific workflow in IaaS cloud environment”(61572510)
海洋科学是在观测数据积累的基础上不断发展的一门学科,其发展史上的任何一次重大突破都离不开观测技术及相应数据集的更新换代。格点化数据集的时间延拓已成为海洋数据产品更新的主要形式,总结了当前格点化海洋环境数据集的发展现状。首先,将海洋观测的发展历史总结为3个阶段:稀疏观测主导的初始积累期,大型观测计划主导的快速增长期,以及资料同化和再分析为主导的高质量发展期。其次,从温度、盐度和流场3个关键要素出发,重点介绍近几十年来国际上公开发布和更新的全球格点化海洋环境数据集,包括HYCOM、OFES、OSCAR、Drifter、ECCO和PHY等6种流场数据集,Argo、IAP、EN4和ISAS 4种三维温盐数据集,OISST、ERSST和HadISST 3种海表面温度数据集以及SMOS、Aquarius和SMAP 3种海表面盐度数据集。在已有的研究基础上,对这些数据集的来源、特征信息及优缺点作了简要回顾,为海洋科技工作者提供参考。最后,建议未来从完善和发展海洋立体观测系统,增加数据质量评估质量和改进以及优化数值模式3个方面进行研究。
汪浩笛 , 陈诗尧 , 鲍森亮 , 任开军 . 全球格点化海洋环境数据集研究进展[J]. 地球科学进展, 2022 , 37(8) : 822 -840 . DOI: 10.11867/j.issn.1001-8166.2022.044
Marine science is a discipline developed on the basis of continuous observation data accumulation, and major breakthroughs in marine science development history are inseparable from the updating of ocean datasets. The time extension of existing gridded datasets has become the main form of updating ocean data products. This review summarizes the current development of gridded marine environment datasets. First, the historical development of ocean observations is divided into three stages: an initial accumulation period dominated by sparse observations, a rapid growth period guided by international observation programs, and a high-quality development period driven by data assimilation and ocean reanalysis. Starting from the three key elements of temperature, salinity, and ocean current, we focus on the global gridded ocean environment datasets published and updated internationally in recent decades, including six flow field datasets, such as HYCOM and OFES, and ten thermohaline datasets, such as Argo and IAP. Based on previous studies, the sources, characteristic information, advantages, and disadvantages of these datasets are briefly reviewed to provide a reference for marine scientists. Finally, the future development direction and research focus of ocean gridded datasets are discussed.
Key words: Ocean observations; Gridded; Data assimilation; Reanalysis datasets
1 | WU Jia, GAO Xuejie. A gridded daily observation dataset over China region and comparison with the other datasets[J]. Chinese Journal of Geophysics, 2013, 56(4): 1 102-1 111. |
1 | 吴佳, 高学杰. 一套格点化的中国区域逐日观测资料及与其它资料的对比[J]. 地球物理学报, 2013, 56(4): 1 102-1 111. |
2 | von SCHUCKMANN K, le TRAON P Y, SMITH N, et al. Copernicus marine service ocean state report, issue 4[J]. Journal of Operational Oceanography, 2020, 13(): S1-S172. |
3 | YOSHIMORI M, RAIBLE C C, STOCKER T F, et al. Simulated decadal oscillations of the Atlantic meridional overturning circulation in a cold climate state[J]. Climate Dynamics, 2010, 34(1): 101-121. |
4 | NIE Sicheng. Global sea ice simulation uncertainty, parameter optimization and application[D]. Nanjing: Nanjing University, 2018. |
4 | 聂思程. 全球海冰模拟不确定性及参数优化与应用[D]. 南京: 南京大学, 2018. |
5 | ZOU Tao. A new risk assessment method for jacket platform and nuclear power plant based on global sensitivity analysis and global uncertainty analysis[D]. Qingdao: Ocean University of China, 2012. |
5 | 邹涛. 基于整体敏感性分析与整体不确定性分析的海洋及海岸结构风险评估新方法[D]. 青岛: 中国海洋大学, 2012. |
6 | DOBLAS-REYES F J, WEISHEIMER A, DéQUé M, et al. Addressing model uncertainty in seasonal and annual dynamical ensemble forecasts[J]. Quarterly Journal of the Royal Meteorological Society, 2009, 135(643): 1 538-1 559. |
7 | FORGET G, CAMPIN J M, HEIMBACH P, et al. ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation[J]. Geoscientific Model Development, 2015, 8(10): 3 071-3 104. |
8 | DU Y, ZHANG Y H, ZHANG L Y, et al. Thermocline warming induced extreme Indian Ocean dipole in 2019[J]. Geophysical Research Letters, 2020, 47(18): e2020GL090079. |
9 | HU S J, SPRINTALL J, GUAN C, et al. Deep-reaching acceleration of global mean ocean circulation over the past two decades[J]. Science Advances, 2020, 6(6): eaax7727. |
10 | LI G, CHENG L, ZHU J, et al. Increasing ocean stratification over the past half-century[J]. Nature Climate Change, 2020, 10(12): 1 116-1 123. |
11 | CHENG L J, ABRAHAM J, HAUSFATHER Z, et al. How fast are the oceans warming? [J]. Science, 2019, 363(6 423): 128-129. |
12 | HEWITT J, JULIAN K, BONE E K. Chatham-Challenger Ocean Survey 20/20 Post-Voyage analyses: objective 10-Biotic habitats and their sensitivity to physical disturbance[Z]. 2011. |
13 | DENG Ke. The newly built “Meteor” survey ship successfully completed the deep sea survey[J]. International Journal of Science and Technology Exchange, 1987(2):14-15. |
13 | 邓柯. 新建的“流星”号调查船成功地完成深海调查[J]. 国际科技交流, 1987(2):14-15. |
14 | DAI Wentian. Seafloor hydrothermal deposition mineralization is a newly recognized, common and important mineralization process[J]. Geology and Prospecting, 1985(6):24-30. |
14 | 戴问天. 海底热液沉积成矿——一种新近被认识的、普遍而重要的成矿作用[J]. 地质与勘探, 1985(6):24-30. |
15 | BEKIASHEV K A, SEREBRIAKOV V V. International Council for the Exploration of the Sea (ICES)[M]// International marine organizations. Dordrecht: Springer Netherlands, 1981: 465-477. |
16 | UNESCO I. Intergovernmental Oceanographic Commission (IOC), biennial report 2012-2013[Z]. 2014. |
17 | LINDSTROM E J, EBBESMEYER C C, OWENS W B. Structure and origin of a small cyclonic eddy observed during the POLYMODE local dynamics experiment[J]. Journal of Physical Oceanography, 1986, 16(3): 562-570. |
18 | SHEU R S, LIU G S. Atmospheric humidity variations associated with westerly wind bursts during Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE)[J]. Journal of Geophysical Research: Atmospheres, 1995, 100(D12): 25 759-25 768. |
19 | SUMMERHAYES C. The Global Ocean Observing System (GOOS) in 1998[J]. Elsevier Oceanography Series, 2002, 66: 57-66. |
20 | WANG F, HU D X. Introduction to international NPOCE program[J]. Chinese Journal of Oceanology and Limnology, 2010, 28(4): 953. |
21 | HU Dunxin, WANG Fan, SPRINTALL J, et al. Review on observational studies of western tropical Pacific Ocean circulation and climate[J]. Journal of Oceanology and Limnology, 2020, 38(4): 906-929. |
22 | SHI J Q, YIN X Q, SHU Q, et al. Evaluation on data assimilation of a global high resolution wave-tide-circulation coupled model using the tropical Pacific TAO buoy observations[J]. Acta Oceanologica Sinica, 2018, 37(3): 8-20. |
23 | CHAO G F, WU X R, ZHANG L X, et al. China Ocean ReAnalysis (CORA) version 1.0 products and validation for 2009-18[J]. Atmospheric and Oceanic Science Letters, 2021, 14(5): 100023. |
24 | WANG H D, CHEN S Y, WANG N, et al. Evaluation of multi-model current data in the East/Japan Sea[C]//2020 IEEE 3rd international conference on information communication and signal processing. Shanghai, China. IEEE, 2020: 486-491. |
25 | CASTELLANOS P, CAMPOS E J D, GIDDY I, et al. Inter-comparison studies between high-resolution HYCOM simulation and observational data: the South Atlantic and the Agulhas leakage system[J]. Journal of Marine Systems, 2016, 159: 76-88. |
26 | SMITH S, SPENCE P, CUMMINGS J, et al. Validation studies of the recently upgraded navy coupled ocean data assimilation (NCODA) system[Z]. 2011. |
27 | Allard R, Campbell T, Hebert D, et al. The U.S. Navy’s emerging sea ice prediction capabilities[C]// EGU general assembly conference. EGU General Assembly Conference Abstracts, 2014. |
28 | MASUMOTO Y. Sharing the results of a high-resolution ocean general circulation model under a multi-discipline framework—a review of OFES activities[J]. Ocean Dynamics, 2010, 60(3): 633-652. |
29 | SASAKI H, SASAI Y, KAWAHARA S, et al. A series of eddy-resolving ocean simulations in the world ocean-OFES (OGCM for the Earth Simulator) project[C]// Oceans’ 04 MTS/IEEE Techno-Ocean '04. Kobe. IEEE, 2004: 1 535-1 541. |
30 | SASAKI H, SASAI Y, NONAKA M, et al. An eddy-resolving simulation of the quasi-global ocean driven by satellite-observed wind field: preliminary outcomes from physical and biological fields[J]. Journal of the Earth Simulator, 2006, 6:35-49. |
31 | SASAKI H, NONAKA M, MASUMOTO Y, et al. An eddy-resolving hindcast simulation of the quasiglobal ocean from 1950 to 2003 on the earth simulator[M]// High resolution numerical modelling of the atmosphere and ocean. New York, NY: Springer New York, 2008: 157-185. |
32 | SASAI Y, ISHIDA A, YAMANAKA Y, et al. Chlorofluorocarbons in a global ocean eddy-resolving OGCM: pathway and formation of Antarctic bottom water[J]. Geophysical Research Letters, 2004, 31(12): L12305. |
33 | SASAKI H, KIDA S, FURUE R, et al. A global eddying hindcast ocean simulation with OFES2[J]. Geoscientific Model Development, 2020, 13(7): 3 319-3 336. |
34 | LAURINDO L C, MARIANO A J, LUMPKIN R. An improved near-surface velocity climatology for the global ocean from drifter observations[J]. Deep Sea Research Part I: Oceanographic Research Papers, 2017, 124: 73-92. |
35 | BONJEAN F, LAGERLOEF G S E. Diagnostic model and analysis of the surface currents in the tropical Pacific Ocean[J]. Journal of Physical Oceanography, 2002, 32(10): 2 938-2 954. |
36 | JOHNSON E S, BONJEAN F, LAGERLOEF G S E, et al. Validation and error analysis of OSCAR sea surface currents[J]. Journal of Atmospheric and Oceanic Technology, 2007, 24(4): 688-701. |
37 | BOGRAD S J, THOMSON R E, RABINOVICH A B, et al. Near-surface circulation of the northeast Pacific Ocean derived from WOCE-SVP satellite-tracked drifters[J]. Deep Sea Research Part II: Topical Studies in Oceanography, 1999, 46(11/12): 2 371-2 403. |
38 | LUMPKIN R, ?ZG?KMEN T, CENTURIONI L. Advances in the application of surface drifters[J]. Annual Review of Marine Science, 2017, 9: 59-81. |
39 | LUMPKIN R, PAZOS M. Measuring surface currents with Surface Velocity Program drifters: the instrument, its data, and some recent results[Z]. 2007. |
40 | LUMPKIN R, GRODSKY S A, CENTURIONI L, et al. Removing spurious low-frequency variability in drifter velocities[J]. Journal of Atmospheric and Oceanic Technology, 2013, 30(2): 353-360. |
41 | STAMMER D, DAVIS R, FU L L, et al. The consortium for Estmiating the Circulation and Climate of he Ocean (ECCO) [Z]. 1999. |
42 | MENEMENLIS D, CAMPIN J M, HEIMBACH P, et al. ECCO2: high resolution global ocean and sea ice data synthesis[Z]. 2008. |
43 | K?HL A, STAMMER D. Decadal sea level changes in the 50-year GECCO ocean synthesis[J]. Journal of Climate, 2008, 21(9): 1 876-1 890. |
44 | K?HL A. Evaluation of the GECCO2 ocean synthesis: transports of volume, heat and freshwater in the Atlantic[J]. Quarterly Journal of the Royal Meteorological Society, 2015, 141(686): 166-181. |
45 | EMMERSON J A, HOLLYMAN P R, BLOOR I S M, et al. Effect of temperature on the growth of the commercially fished common whelk (Buccinum undatum, L.): a regional analysis within the Irish Sea[J]. Fisheries Research, 2020, 223: 105437. |
46 | PARENT L, FERRY N, BARNIER B, et al. Global eddy-permitting ocean reanalyses and simulations of the period 1992 to present[Z]. 2013. |
47 | ROEMMICH D H, DAVIS R E, RISER S C, et al. The Argo Project. Global ocean observations for understanding and prediction of climate variability[R]. Defense Technical Information Center, 2003. |
48 | ZENG Xiaomei, translated. ARGO, a milestone for the Global Ocean Observing System, established the 3,000th buoy station[J]. Meteorological Science and Technology, 2007,35(6):871. |
48 | 曾晓梅编 译. 全球海洋观测系统的里程碑——国际ARGO观测系统建立第3000个浮标站[J]. 气象科技, 2007, 35(6):871. |
49 | HU C Q, GOU Y, ZHANG T, et al. Analysis of thermocline influencing factors based on decision tree methods[Z]. 2018. |
50 | YANG Xiaoxin, WU Xiaofen, LU Shaolei. Gridded mixed layer & thermocline data set derived from Argo profiles of the Western Pacific Ocean[J]. Marine Forecasts, 2018, 35(3): 57-67. |
50 | 杨小欣, 吴晓芬, 卢少磊. 基于Argo资料的西太平洋混合层和温跃层数据产品研制[J]. 海洋预报, 2018, 35(3): 57-67. |
51 | ZHANG C L, XU J P, BAO X W, et al. An effective method for improving the accuracy of Argo objective analysis[J]. Acta Oceanologica Sinica, 2013, 32(7): 66-77. |
52 | HOSODA S, OHIRA T, NAKAMURA T. A monthly mean dataset of global oceanic temperature and salinity derived from Argo float observations[J]. JAMSTEC Report of Research and Development, 2008, 8: 47-59. |
53 | DHOMPS A L, GUINEHUT S, le TRAON P Y, et al. A global comparison of Argo and satellite altimetry observations[J]. Ocean Science, 2011, 7(2): 175-183. |
54 | SMITH T M, REYNOLDS R W. Extended reconstruction of global sea surface temperatures based on COADS data (1854-1997)[J]. Journal of Climate, 2003, 16(10): 1 495-1 510. |
55 | CHENG L J, ZHU J, COWLEY R, et al. Time, probe type, and temperature variable bias corrections to historical expendable bathythermograph observations[J]. Journal of Atmospheric and Oceanic Technology, 2014, 31(8): 1 793-1 825. |
56 | ZHANG Min, ZHAO Chang, ZHANG Yuanling, et al. Discrepancies in the ocean heat content of two EN4 products[J]. Advances in Marine Science, 2020, 38(3): 390-399. |
56 | 张敏, 赵昌, 张远凌, 等. EN4两套分析数据中海洋热含量的差异[J]. 海洋科学进展, 2020, 38(3): 390-399. |
57 | ISHII M, KIMOTO M. Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections[J]. Journal of Oceanography, 2009, 65(3): 287-299. |
58 | WIJFFELS S E, WILLIS J, DOMINGUES C M, et al. Changing expendable bathythermograph fall rates and their impact on estimates of thermosteric sea level rise[J]. Journal of Climate, 2008, 21(21): 5 657-5 672. |
59 | GAILLARD F, REYNAUD T, THIERRY V, et al. In situ-based reanalysis of the global ocean temperature and salinity with ISAS: variability of the heat content and steric height[J]. Journal of Climate, 2016, 29(4): 1 305-1 323. |
60 | DESBRUYèRES D, CHAFIK L, MAZE G. A shift in the ocean circulation has warmed the subpolar North Atlantic Ocean since 2016[J]. Communications Earth & Environment, 2021, 2: 48. |
61 | MU Z Y, ZHANG W M, WANG P Q, et al. Assimilation of SMOS sea surface salinity in the regional ocean model for South China Sea[J]. Remote Sensing, 2019, 11(8): 919. |
62 | KOLODZIEJCZYK N, HAMON M, BOUTIN J, et al. Objective analysis of SMOS and SMAP sea surface salinity to reduce large-scale and time-dependent biases from low to high latitudes[J]. Journal of Atmospheric and Oceanic Technology, 2021, 38(3): 405-421. |
63 | WANG Chenqi, LI Xiang, ZHANG Yunfei, et al. A comparative study of three SST reanalysis products and buoys data over the China offshore area[J]. Acta Oceanologica Sinica, 2020, 42(3): 118-128. |
63 | 王晨琦, 李响, 张蕴斐, 等. 3套不同的SST再分析数据与中国近海浮标观测的对比研究[J]. 海洋学报, 2020, 42(3): 118-128. |
64 | REYNOLDS R W, SMITH T M, LIU C Y, et al. Daily high-resolution-blended analyses for sea surface temperature[J]. Journal of Climate, 2007, 20(22): 5 473-5 496. |
65 | HUANG B Y, LIU C Y, BANZON V, et al. Improvements of the Daily Optimum Interpolation Sea Surface Temperature (DOISST) version 2.1[J]. Journal of Climate, 2021, 34(8): 2 923-2 939. |
66 | HUGHES S L, HOLLIDAY N P, COLBOURNE E, et al. Comparison of in situ time-series of temperature with gridded sea surface temperature datasets in the North Atlantic[J]. ICES Journal of Marine Science, 2009, 66(7): 1 467-1 479. |
67 | HUANG B Y, THORNE P W, BANZON V F, et al. Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): upgrades, validations, and intercomparisons[J]. Journal of Climate, 2017, 30(20): 8 179-8 205. |
68 | HUANG B Y, BANZON V F, FREEMAN E, et al. Extended Reconstructed Sea Surface Temperature Version 4 (ERSST.v4). part I: upgrades and intercomparisons [J]. Journal of Climate, 2019, 28(3):911-930. |
69 | HUANG B Y, MENNE M J, BOYER T, et al. Uncertainty estimates for sea surface temperature and land surface air temperature in NOAAGlobalTemp version 5[J]. Journal of Climate, 2020, 33(4): 1 351-1 379. |
70 | KENNEDY J J, RAYNER N A, ATKINSON C P, et al. An ensemble data set of sea surface temperature change from 1850: the met office Hadley centre HadSST.4.0.0.0 data set[J]. Journal of Geophysical Research: Atmospheres, 2019, 124(14): 7 719-7 763. |
71 | DESER C, PHILLIPS A S, ALEXANDER M A. Twentieth century tropical sea surface temperature trends revisited[J]. Geophysical Research Letters, 2010, 37(10): L10701. |
72 | KENNEDY J J, RAYNER N A, SMITH R O, et al. Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 1. measurement and sampling uncertainties[J]. Journal of Geophysical Research: Atmospheres, 2011, 116(D14): D14103. |
73 | FONT J, CDRIANO C, MEMBER S, et al. Satellite remote sensing missions for monitoring water, carbon and global climate change[J]. Proceedings of the IEEE, 2010, 98(5):645-648. |
74 | BOUTIN J, VERGELY J L, MARCHAND S, et al. New SMOS Sea Surface Salinity with reduced systematic errors and improved variability[J]. Remote Sensing of Environment, 2018, 214: 115-134. |
75 | le VINE D M, DINNAT E P, MEISSNER T, et al. Status of Aquarius/SAC-D and Aquarius salinity retrievals[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(12): 5 401-5 415. |
76 | KAO H Y, LAGERLOEF G, LEE T, et al. Assessment of Aquarius sea surface salinity[J]. Remote Sensing, 2018, 10(9): 1341. |
77 | ENTEKHABI D, NJOKU E G, O'NEILL P E, et al. The Soil Moisture Active Passive (SMAP) mission[C]// Proceedings of the IEEE. 2010: 704-716. |
78 | TANG W Q, FORE A, YUEH S, et al. Validating SMAP SSS with in situ measurements[J]. Remote Sensing of Environment, 2017, 200: 326-340. |
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