圣劳伦斯湾SMOS、SMAP和现场海面盐度的比较

IF 1.6 4区地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmosphere-Ocean Pub Date : 2022-12-21 DOI:10.1080/07055900.2022.2155103

J. Dumas, D. Gilbert

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引用次数: 0

摘要

摘要圣劳伦斯湾（GSL）是受五大湖-圣劳伦斯河流域淡水排放影响的加拿大东部半封闭海域。研究气候变化下GSL海洋条件的变化对生态系统和渔业管理具有重要意义。为了用卫星SSS数据补充现有的现场海面盐度（SSS）测量结果，本研究将所有可用年份的土壤水分海洋盐度（SMOS）和土壤水分主动和被动（SMAP）卫星SSS与现场SSS观测结果进行了比较。尽管水相对较冷，靠近陆地和海冰，但卫星SSS能够捕捉到GSL中SSS的年际变化和年周期，其相关性在南部GSL为0.80至0.85，在北部GSL为0.22至0.77。所有卫星SSS数据产品都能够探测到2017年南部GSL的盐度非常低的年份。

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Comparison of SMOS, SMAP and In Situ Sea Surface Salinity in the Gulf of St. Lawrence

ABSTRACT The Gulf of St. Lawrence (GSL) is an Eastern Canada semi-enclosed sea under the influence of the freshwater discharge from the Great Lakes – St. Lawrence River drainage basin. Studying the variability of oceanographic conditions in the GSL under a changing climate is important for ecosystem and fisheries management. To supplement the available in situ sea surface salinity (SSS) measurements with satellite SSS data, this study compares all available years of Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active and Passive (SMAP) satellite SSS to in situ SSS observations. Despite the relatively cold water and proximity to land and sea ice, the satellite SSS is able to capture the interannual variability and annual cycle of SSS in the GSL, with correlations ranging from 0.80 to 0.85 in the Southern GSL, and 0.22 to 0.77 in the Northern GSL. All satellite SSS data products were able to detect the very low salinity year of 2017 in the Southern GSL.

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来源期刊

Atmosphere-Ocean 地学-海洋学

CiteScore

2.50

自引率

16.70%

发文量

审稿时长

>12 weeks

期刊介绍： Atmosphere-Ocean is the principal scientific journal of the Canadian Meteorological and Oceanographic Society (CMOS). It contains results of original research, survey articles, notes and comments on published papers in all fields of the atmospheric, oceanographic and hydrological sciences. Arctic, coastal and mid- to high-latitude regions are areas of particular interest. Applied or fundamental research contributions in English or French on the following topics are welcomed: climate and climatology; observation technology, remote sensing; forecasting, modelling, numerical methods; physics, dynamics, chemistry, biogeochemistry; boundary layers, pollution, aerosols; circulation, cloud physics, hydrology, air-sea interactions; waves, ice, energy exchange and related environmental topics.