BCC_CSM模式夏季关键区海温回报评估

汪栩加; 郑志海; 封国林; 王阔; 申茜

doi:10.3878/j.issn.1006-9895.1408.13329

BCC_CSM模式夏季关键区海温回报评估

doi: 10.3878/j.issn.1006-9895.1408.13329

1.
兰州大学大气科学学院, 兰州730000
2.
国家气候中心气候研究开放实验室, 北京100081

基金项目: 国家重点基础研究发展计划项目2013CB430204, 公益性行业(气象)科研专项GYHY201306021, 国家自然科学基金青年科学基金项目41105070、41005051

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出版历程
- 收稿日期: 2013-12-11
- 修回日期: 2014-09-10

Summer Prediction of Sea Surface Temperatures in Key Areas in BCC_CSM Model

1.
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000
2.
Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081

摘要

摘要: 利用国家气候中心气候系统模式(Beijing Climate Center Climate System Model, BCC_CSM)的汛期回报试验数据集, 评估了夏季中低纬度海表面温度(Sea Surface Temperature, SST)的预测能力。结果表明:该模式对夏季中低纬海温具有一定的预测能力, 且在低纬地区的预测技巧尤为出色。对太平洋、热带印度洋和北大西洋这三个关键区进一步分析发现, 该模式对不同海区海温的预测能力有所不同。其中, 模式对夏季北太平洋海温及Niño 3.4指数表现出显著的预测技巧, 对热带印度洋、北大西洋海温及热带印度洋全区一致海温模态(Indian Ocean Basin-wide Warming, IOBW)也表现出一定的预测技巧, 而对北大西洋海温三极子模态(North Atlantic Tripole, NAT)的技巧相对较低。研究发现, 预测技巧与前冬的ENSO状态密切相关, 当前冬位于ENSO异常位相时, BCC_CSM模式对于三大海区夏季海温的预测技巧要高于前冬位于ENSO正常位相时, 且对NAT指数也具有更高的预测技巧。前冬ENSO所处的位相对于该模式对夏季Niño 3.4指数及IOBW指数的预测技巧影响不明显。此外, 该模式对夏季海温的预测技巧依赖于超前时间, 预测技巧在大部分情形下超前1个月的预测技巧相对更高。
- BCC_CSM模式 /
- 夏季海温 /
- 回报 /
- 评估
Abstract: In this paper, the authors assess the summer prediction skill of retrospective forecasts of global midlatitudes and low latitudes sea surface temperatures (SSTs) in the Beijing Climate Center Climate System Model (BCC_CSM).Results indicate that the SST forecasts exhibit certain skills in middle and low latitude areas and the skills over much of the low latitude areas are better.Further analysis reveals that model forecasts in different areas of the sea have different skills.Specifically, the SST forecasts exhibit significant skills over much of the North Pacific and the Niño 3.4 index in summer, followed by the Indian Ocean, Atlantic Ocean, and the Indian Ocean Basin-wide Warming (IOBW), while the North Atlantic Tripole (NAT) shows a lower forecast skill.Recent investigations have revealed that prediction skill is closely related to the El Niño Southern Oscillation (ENSO) phases of the previous winter.When the previous winter phase is characterized by ENSO, SST forecasts exhibit higher skills than when preceded by a neutral phase, and the NAT index also has higher forecast skills.The ENSO phases of the previous winter have little effect on the skills of the Niño 3.4 and IOBW indexes.In most cases, as the lead time becomes longer, the model will show a drop in forecast skills for summer SSTs and these indexes.
- BCC_CSM model /
- Summer SST /
- Hindcast /
- Assess

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