A high-resolution ocean bottom temperature product for the northeast US continental shelf marine ecosystem

被引:9
|
作者
du Pontavice, Hubert [1 ,2 ]
Chen, Zhuomin [3 ]
Saba, Vincent S. [2 ]
机构
[1] Princeton Univ, Atmospher & Ocean Sci Program, 300 Forrestal Rd,Sayre Hall, Princeton, NJ 08540 USA
[2] Princeton Univ, Northeast Fisheries Sci Ctr, Natl Marine Fisheries Serv, NOAA,Geophys Fluid Dynam Lab, 201 Forrestal Rd, Princeton, NJ 08540 USA
[3] Univ Connecticut, Dept Marine Sci, Groton, CT 06340 USA
关键词
MID-ATLANTIC BIGHT; SEASONAL VARIABILITY; REGIME SHIFTS; GEORGES BANK; SLOPE WATER; GULF; MAINE; SURFACE; MODEL; CONFIGURATION;
D O I
10.1016/j.pocean.2022.102948
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
The northeast U.S. continental shelf is a highly productive and socio-economically important marine ecosystem in which annual and seasonal variations of bottom temperature play a major role in the distribution, phenology, and productivity of its predominately demersal marine taxa. However, bottom temperature mea-surements are limited spatially and temporally and thus do not provide the required resolution to assess sub-seasonal variability and trends. Here we combined three ocean products, a regional ocean model (ROMS) and two global ocean data assimilated models (GLORYS12v1 and PSY4V3R1) to build a high-resolution, long-term bottom temperature product for the northeast U.S. continental shelf between 1959 and 2021. We bias-corrected ROMS using monthly decadal climatologies from ocean observations and analyzed long-term changes in the combined time series. Model skill was assessed using a large number of in situ observations. The combined bottom temperature product showed a long-term warming of the northeast U.S. continental shelf of + 0.36 degrees C decade-1 over the past 63 years, with notable variations among seasons and regions. The strongest long-term warming occurred during the summer months and in the Gulf of Maine. Although biases were observed, the bottom temperature product exhibited good performance reproducing seasonal and annual variability in observed temperature. This high-resolution product could be used in a wide range of applications from local to regional spatial scales, from long-term to near-term time scales, and from fisheries to marine ecology.
引用
收藏
页数:31
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