卫星遥感资料初始场对厄尔尼诺-南方涛动动力预测误差影响研究
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作者:姜华1 2 宋春阳1 2 张守文3 袁智4 穆博5 向亮6 谭晶1 2 黄勇勇1 2 何越1 2
单位:
卫星海洋环境监测预警全国重点实验室(国家海洋环境预报中心), 北京 100081;
国家海洋环境预报中心 自然资源部海洋灾害预报技术重点实验室, 北京 100081;
南方海洋科学与工程广东省实验室(珠海), 广东 珠海 519082;
中国空间技术研究院遥感卫星总体部,北京 100086;
国家卫星海洋应用中心,北京 100081
中国科学院海洋研究所,山东 青岛 266071
分类号:P732.6
出版年·卷·期(页码):2026·43·第四期(1-15)
摘要:在国家海洋环境预报中心全球气候预测系统(NMEFC_CESM)中分别同化海洋二号B卫星(HY-2B)和多源卫星融合两类海温资料建立初始场,构建天基厄尔尼诺/拉尼娜集合预测系统。为探讨卫星遥感资料初始场对厄尔尼诺-南方涛动(ENSO)预测误差的影响,通过改变同化数据源,设计了3类敏感性数值试验:第一类为同化海表温度和重构三维海温的对比试验;第二类试验是对同化所用的重构三维海温,设置经过和未经过海表高度订正的两组对比试验;第三类试验是将卫星资料初始场误差减半,测试其对ENSO预测误差的影响。试验结果表明:同化多源卫星融合海温资料构建的预测初始场精度高于HY-2B单星海温初始场,ENSO预测结果更稳定且更接近观测;仅同化表层海温、不同化次表层海温时,ENSO预测效果较差,即使降低初始场误差,也不会产生实质性的提升,表明次表层同化对于ENSO预测非常重要;采用经过海表高度订正的重构三维海温作为同化数据源,预测结果明显最优,表明开展海表面高度订正对于次表层海温重构具有关键作用;当初始场误差减小50%时,Niño3.4区域的12个月预测平均绝对误差降至0.5℃以下,预测准确率有效提升,针对预测误差较大的海温事件优化作用更为明显。
关键词:厄尔尼诺-南方涛动预测误差 卫星资料初始场 动力试验 多源卫星融合 重构三维海温
Abstract:Based on the global climate prediction system NMEFC_CESM of the National Marine Environmental Forecasting Center, this paper assimilates the HY-2B satellite and multi-source satellite remote sensing fusion types of sea surface temperature data to establish the initial field, and constructs a satellite-based El Niño/La Niña ensemble prediction system. To explore the influence of satellite remote sensing data initial field on the ENSO prediction error, three types of sensitivity numerical experiments were designed by changing the initial field: The first type includes the assimilation of sea surface temperature and the comparison experiment of assimilating reconstructed three-dimensional sea surface temperature; The second type is the assimilation of reconstructed three-dimensional sea surface temperature, with two groups of comparison experiments before and after sea surface height correction; The third type is to reduce the initial field error of satellite data by half, and test its impact on the ENSO prediction error. The experimental results show that the prediction initial field constructed by assimilating multi-source satellite fusion is more accurate than that constructed by the single-star sea surface temperature data of HY-2B, and the ENSO prediction results are more stable and closer to the observation; Only assimilating the surface sea temperature and differentiating the subsurface sea temperature, the effect of ENSO prediction is poor, even if the initial field error is reduced, it will not produce a substantive improvement, indicating the importance of subsurface assimilation for ENSO prediction; The prediction results using the reconstructed three-dimensional sea surface temperature corrected by sea surface height as the assimilation data source are significantly the best, indicating the importance of sea surface height correction for subsurface sea surface temperature reconstruction; When the initial field error is reduced by 50%, the 12-month average absolute error of Niño3.4 drops below 0.5 ℃, and the prediction accuracy significantly improves, especially for events with relatively large prediction errors.
Key words:ENSO prediction error; initial field of satellite data; dynamic experiment; multi-source satellite fusion; reconstruction of three-dimensional sea surface temperature
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