An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models
Lee, Younjoo J.; Matrai, Patricia A.; Friedrichs, Marjorie A. M.; Saba, Vincent S.; Antoine, David; Ardyna, Mathieu; Asanuma, Ichio; Babin, Marcel; Belanger, Simon; Benoit-Gagne, Maxime; Devred, Emmanuel; Fernandez-Mendez, Mar; Gentili, Bernard; Hirawake, Toru; Kang, Sung-Ho; Kameda, Takahiko; Katlein, Christian; Lee, Sang H.; Lee, Zhongping; Melin, Frederic; Scardi, Michele; Smyth, Tim J.; Tang, Shilin; Turpie, Kevin R.; Waters, Kirk J.; Westberry, Toby K.; ylee@bigelow.org
2015
发表期刊JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
卷号120期号:9页码:6508-6541
文章类型2169-9275
摘要We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.
部门归属[Lee, Younjoo J.; Matrai, Patricia A.] Bigelow Lab Ocean Sci, East Boothbay, ME 04544 USA; [Friedrichs, Marjorie A. M.] Virginia Inst Marine Sci, Coll William & Mary, Gloucester Point, VA 23062 USA; [Saba, Vincent S.] Northeast Fisheries Sci Ctr, NOAA Natl Marine Fisheries Serv, Princeton, NJ USA; [Antoine, David; Gentili, Bernard] Univ Paris 06, Univ Paris 04, Villefranche Sur Mer, France; [Antoine, David; Gentili, Bernard] CNRS, UMR 7093, LOV, Observ Oceanol, Villefranche Sur Mer, France; [Antoine, David] Curtin Univ, Remote Sensing & Satellite Res Grp, Dept Phys Astron & Med Radiat Sci, Perth, WA 6845, Australia; [Ardyna, Mathieu; Babin, Marcel; Benoit-Gagne, Maxime; Devred, Emmanuel] Univ Laval, CNRS, Takuvik Joint Int Lab, Quebec City, PQ, Canada; [Asanuma, Ichio] Tokyo Univ Informat Sci, Chiba, Japan; [Belanger, Simon] Univ Quebec Rimouski, Dept Biol Chem & Geog, Rimouski, PQ, Canada; [Fernandez-Mendez, Mar; Katlein, Christian] Alfred Wegener Inst Helmholtz Zentrum Polarund me, Bremerhaven, Germany; [Hirawake, Toru] Hokkaido Univ, Fac Fisheries Sci, Hakodate, Hokkaido, Japan; [Kang, Sung-Ho] Korea Polar Res Inst, Inchon, South Korea; [Kameda, Takahiko] Fisheries Res Agcy, Seikai Natl Fisheries Res Inst, Nagasaki, Japan; [Lee, Sang H.] Pusan Natl Univ, Dept Oceanog, Busan, South Korea; [Lee, Zhongping] Univ Massachusetts, Sch Environm, Boston, MA 02125 USA; [Melin, Frederic] Inst Environm & Sustainabil, European Commiss Joint Res Ctr, Ispra, Italy; [Scardi, Michele] Univ Roma Tor Vergata, Dept Biol, I-00173 Rome, Italy; [Smyth, Tim J.] Plymouth Marine Lab, Plymouth, Devon, England; [Tang, Shilin] Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou, Guangdong, Peoples R China; [Turpie, Kevin R.] Univ Maryland, Baltimore Cty Joint Ctr Earth Syst Technol, Baltimore, MD 21201 USA; [Waters, Kirk J.] NOAA Off Coastal Management, Charleston, SC USA; [Westberry, Toby K.] Oregon State Univ, Dept Bot & Plant Pathol, Corvallis, OR 97331 USA ; LTO
关键词Arctic Ocean Net Primary Productivity Model Skill Assessment Subsurface Chlorophyll-a Maximum Ocean Color Model Remote Sensing
学科领域Oceanography
收录类别SCI
文献类型期刊论文
条目标识符http://ir.scsio.ac.cn/handle/344004/15030
专题热带海洋环境国家重点实验室(LTO)
通讯作者ylee@bigelow.org
推荐引用方式
GB/T 7714
Lee, Younjoo J.,Matrai, Patricia A.,Friedrichs, Marjorie A. M.,et al. An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models[J]. JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS,2015,120(9):6508-6541.
APA Lee, Younjoo J..,Matrai, Patricia A..,Friedrichs, Marjorie A. M..,Saba, Vincent S..,Antoine, David.,...&ylee@bigelow.org.(2015).An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS,120(9),6508-6541.
MLA Lee, Younjoo J.,et al."An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models".JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS 120.9(2015):6508-6541.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。