地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (10): 1538-1549.doi: 10.12082/dqxxkx.2019.180647

• 地理空间分析综合应用 • 上一篇    下一篇

全球海洋初级生产力时空异常变化对ENSO事件的响应

洪娅岚1,3,薛存金1,2,*(),刘敬一1,刘星3,孙强1,3,伍程斌1   

  1. 1. 中国科学院数字地球重点实验室,北京 100094
    2. 中国科学院空天信息研究院,北京 100094
    3. 安徽理工大学,淮南 232001
  • 收稿日期:2018-12-11 修回日期:2019-07-04 出版日期:2019-10-25 发布日期:2019-10-29
  • 通讯作者: 薛存金 E-mail:xuecj@radi.ac.cn
  • 作者简介:洪娅岚(1994-),女,硕士生,主要从事海洋时空聚类挖掘分析研究。E-mail: hongyalan@foxmail.com
  • 基金资助:
    中国科学院战略性A类型先导专项(XDA19060103);国家重点研发计划项目(2016YFA0600304);国家自然科学基金项目(41671401)

Spatiotemporal Abnormal Variations of Global Marine NPP in Response to ENSO Events

HONG Yalan1,3,XUE Cunjin1,2,*(),LIU Jingyi1,LIU Xing3,SUN Qiang1,3,WU Chengbin1   

  1. 1. Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing 100094, China
    2. Aerospace Information Research Institute, Beijing 100094, China
    3. Anhui University Of Science & Technology, Huainan 232001, China;
  • Received:2018-12-11 Revised:2019-07-04 Online:2019-10-25 Published:2019-10-29
  • Contact: XUE Cunjin E-mail:xuecj@radi.ac.cn
  • Supported by:
    Strategic Type A Pilot Project of Chinese Academy of Science(XDA19060103);National Key Research and Development Program of China(2016YFA0600304);National Natural Science Foundation of China(41671401)

摘要:

海洋初级生产力在海洋环境要素的驱动下,在不同海域呈现出不同的时空变化特征,这种时空演变特征在不同的ENSO事件类型下差异更为显著。本文基于1998年1月至2017年12月全球海洋初级生产力的卫星遥感数据集,通过改进海洋时空双约束聚类挖掘方法,挖掘了近20年海洋初级生产力的时空聚簇模式,并从时空分布和空间移动2个方面对比分析了海洋初级生产力时空演变簇与ENSO(El Niño-Southern Oscillation)事件之间的关系。结果表明:① 在EP(Eastern-Pacific)型El Niño事件期间,海洋初级生产力异常低值时空簇主要分布在赤道太平洋东部或中东部海域,异常高值时空簇主要分布在西太平洋和南太平洋中部海域;在CP(Central-Pacific)型El Niño事件期间,异常低值时空簇分布在太平洋中部,而异常高值时空簇分布在南太平洋与西太平洋海域;② 在EP型La Niña事件期间,赤道太平洋中部及东部、赤道大西洋与印度洋海域出现异常高值时空簇,南太平洋中东部海域出现异常低值时空簇;在CP型La Niña事件期间,赤道太平洋中部出现异常高值时空簇;南太平洋中西部海域出现异常低值时空簇;③ 发生在赤道太平洋的海洋初级生产力时空演变簇,在EP型ENSO事件期间具有东移特征,而在CP型ENSO事件期间,时空演变簇在赤道太平洋中部海域产生并消亡;④ ENSO事件中海洋初级生产力时空演变簇面积与MEI具有较强相关性。

关键词: 聚类挖掘, 海洋初级生产力, 时空变化模式, ENSO事件, CP型和EP型, 卫星遥感数据, 太平洋

Abstract:

Driven by multiple marine environmental factors, global marine NPP (net primary productivity) shows different spatiotemporal variations in different ocean areas, and the variations are more remarkable in ENSO events. This paper improved the Dual-constraint SpatioTemporal Clustering Approach (DcSTCA) by adjusting threshold attribute parameters to explore the spatiotemporal evolution clusters of global marine NPP using the satellite remote sensing dataset from January 1998 to December 2017, and analyzed the relationships between the marine NPP spatiotemporal evolution clusters and ENSO events. Results show that: (1) During the period of Eastern Pacific (EP) El Niño events, the spatiotemporal evolution clusters with an abnormal decreased intensity were mainly located in either the equatorial mid-eastern Pacific Ocean (PO) or the equatorial eastern PO, while the spatiotemporal evolution clusters with an abnormal increased intensity were mainly located in the equatorial western PO and the central South Pacific. During the period of Central Pacific (CP) El Niño events, the spatiotemporal evolution clusters with an abnormal decreased intensity were mainly located in the equatorial central PO, and the spatiotemporal evolution clusters with an abnormal increased intensity were mainly located in the equatorial western PO and the central South Pacific. (2) During the period of EP La Niña events, the spatiotemporal evolution clusters with an abnormal increased intensity were located in the equatorial central or the central eastern PO, the equatorial Atlantic ocean and the equatorial Indian ocean, while the spatiotemporal evolution clusters with an abnormal decreased intensity were located in the east-central South Pacific. During the period of Central Pacific (CP) La Niña events, the spatiotemporal evolution clusters with an abnormal increased intensity were mainly located in the equatorial central PO, and the spatiotemporal evolution clusters with an abnormal decreased intensity were mainly located in the mid-western South Pacific. (3) The distribution and spatial movements of marine NPP spatiotemporal evolution clusters in the tropical PO showed some regularity. The spatiotemporal evolution clusters had more significant variation characteristics in EP ENSO events as compared with in CP ENSO events. During the period of EP ENSO events, the spatiotemporal evolution clusters presented a trend of moving to the east. During the period of CP ENSO events, the spatiotemporal evolution clusters presented a tendency to arise and disappear in the central equatorial PO. (4) The area of spatiotemporal evolution cluster had a strong correlation with MEI in ENSO events.

Key words: clustering mining, net primary productivity, spatiotemporal variation pattern, ENSO events, Eastern Pacific (EP) and Central Pacific (CP) types, satellite remote sensing dataset, Pacific Ocean