Emergent Constraint for Future Decline in Arctic Phytoplankton Concentration

北极的 环境科学 耦合模型比对项目 生产力 生物地球化学循环 叶绿素 叶绿素a 浮游植物 硝酸盐 营养物 生态系统 约束(计算机辅助设计) 海洋学 气候学 大气科学 气候模式 气候变化 生态学 生物 数学 植物 经济 宏观经济学 地质学 几何学
作者
Kyung Min Noh,Hyung‐Gyu Lim,Eun Jin Yang,Jong‐Seong Kug
出处
期刊:Earth’s Future [American Geophysical Union]
卷期号:11 (4) 被引量:9
标识
DOI:10.1029/2022ef003427
摘要

Abstract In recent decades, the Arctic Ocean has experienced continuous warming and freshening, affecting biogeochemical factors such as nutrient supply, light availability, chlorophyll, and productivity. While Arctic marine productivity is projected to increase due to the expansion of the open ocean and increased chlorophyll concentration, uncertainties related to chlorophyll and nutrients may distract the fidelity of productivity in current Earth system models (ESMs). Here, we analyze the existing uncertainty in the Arctic chlorophyll projections using the 26 ESMs participating in Coupled Model Intercomparison Projects 5 and 6 (CMIP5 and CMIP6). We found that the uncertainty in the Arctic chlorophyll projections in the CMIP6 ESMs is greater than in the CMIP5 ESMs due to increasing uncertainty in the background nitrate concentration. A significant relationship between background nitrate and projected chlorophyll ( r = 0.86) is demonstrated using the observational climatology of nitrate. Based on this strong relationship, the emergent constraint is applied to reduce the uncertainty of future chlorophyll projections. Declines in chlorophyll concentration based on emergent constraint are estimated to be further decreased in the future (44.9% % to 50.9% %) than at present, which is about three‐fold larger than the multi‐model mean projection (−13.5% %). Comparing cumulative density functions before and after the emergent constraint, the probability of the decreasing chance of chlorophyll is increased by approximately 36% from 60% in prior CMIP5,6 to 93%–96% after constraint. Our results imply that reducing the uncertainty in background nitrate concentration can improve the fidelity of future projections of the Arctic ecosystem in the ESMs.
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