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Analyze simulation errors of phytoplankton blooms in typical Arctic seas based on CMIP6 models
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Meiqing Yang1, Zhixuan Feng1, 2, *, Hongjun Song3
Haiyang Xuebao | 2023, 45(7) : 40 - 55
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Haiyang Xuebao | 2023, 45(7): 40-55
Article
Analyze simulation errors of phytoplankton blooms in typical Arctic seas based on CMIP6 models
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Meiqing Yang1, Zhixuan Feng1, 2, *, Hongjun Song3
Affiliations
  • 1State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
  • 2Institute of Eco-Chongming, East China Normal University, Shanghai 202162, China
  • 3Key Laboratory of Marine Ecological Environment Science and Technology, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
Published: 2023-07-01 doi: 10.12284/hyxb2023115
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Phytoplankton blooms in polar regions with seasonal sea ice cover show a unimodal seasonality. However, the bloom processes are controlled by multiple physical and biogeochemical factors, including sea ice, light availability, mixed layer depth, and nutrients; those may result in great uncertainties in simulating phytoplankton bloom by the Earth System Models (ESMs). In this study, the results of 11 Coupled Model Intercomparison Phase-6 (CMIP6) ESMs were analyzed and evaluated with various types of observational products in order to determine whether those ESMs can correctly model the phytoplankton blooms in three Arctic shelf seas, Barents Sea, Chukchi Sea, and Bering Sea. By calculating multiple indices that represent light and nutrient limitations, the error sources of simulated surface chlorophyll a concentrations were comprehensively analyzed. Our results show that the 11 ESMs can be divided into three groups based on ice-adjusted photoperiod, rate of change of mixed layer depth, and surface nitrate concentration. Some groups are characterized by the smallest bias between modeled indices and observation-based reference, and those ESMs perform best in simulating phytoplankton bloom characteristics. The other groups of ESMs differ significantly from the reference values in terms of surface nitrate and/or rate of change of mixed layer depth, resulting in delayed occurrences of annual chlorophyll a peak concentration and greater differences in corresponding peak values. In general, in addition to the two primary constraints of light and nutrients, the ESMs should also well represent the upper mixed layer controlled by temperature and salinity distributions, so as to accurately simulate the seasonal variation of surface chlorophyll a concentration. The above analyses indicate ESMs can be used in assessing polar planktonic ecosystems, and there is room for improving ecosystem-related parametrization in future ESM development.

Arctic Ocean  /  sea ice  /  phytoplankton bloom  /  upper mixed layer  /  earth system models  /  CMIP6
Meiqing Yang, Zhixuan Feng, Hongjun Song. Analyze simulation errors of phytoplankton blooms in typical Arctic seas based on CMIP6 models[J]. Haiyang Xuebao, 2023 , 45 (7) : 40 -55 . DOI: 10.12284/hyxb2023115
Year 2023 volume 45 Issue 7
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Article Info
doi: 10.12284/hyxb2023115
  • Receive Date:2022-11-07
  • Online Date:2025-12-28
  • Published:2023-07-01
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  • Received:2022-11-07
  • Revised:2023-02-27
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Affiliations
    1State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China
    2Institute of Eco-Chongming, East China Normal University, Shanghai 202162, China
    3Key Laboratory of Marine Ecological Environment Science and Technology, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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