Sub-seasonal variability of surface soil moisture over eastern China

被引:5
|
作者
Zhou, Yang [1 ]
Dong, Xuan [1 ]
Chen, Haishan [1 ]
Cao, Lu [2 ]
Shao, Qing [3 ]
Sun, Shanlei [1 ]
Yang, Ben [4 ]
Rao, Jian [1 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Key Lab Meteorol Disaster, Minist Educ,Sch Atmospher Sci, 219 Ningliu Rd, Nanjing 210044, Jiangsu, Peoples R China
[2] Jiangsu Meteorol Bur, Jiangsu Meteorol Observ, Nanjing 210008, Peoples R China
[3] Zhejiang Meteorol Bur, Zhejiang Inst Meteorol Sci, Hangzhou 310008, Peoples R China
[4] Nanjing Univ, Sch Atmospher Sci, Nanjing 210032, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Sub-seasonal; Soil moisture; Soil moisture memory; Eastern China; SUBSEASONAL FORECAST SKILL; AIR-TEMPERATURE; LAND; INITIALIZATION; PRECIPITATION; IMPACT; OSCILLATION; MEMORY;
D O I
10.1007/s00382-020-05464-3
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Various surface soil moisture (SM) data from station observations, the Soil Moisture Active Passive (SMAP) mission, three reanalyses (ERA-Interim, CFSR, and NCEP RII), and the Global Land Data Assimilation System (GLDAS) are used to explore the sub-seasonal variations of SM (SSV-SM) over eastern China. Based on the correlation with SM of SMAP, reanalyses, and GLDAS, it is found that the variations of SM observed by Liuhe and Chunan stations can generally represent the SM variations over eastern China. The correlation coefficients between the SMAP and station SM are around 0.7. The SMAP product can well capture the time variation of SM over eastern China. The spectral analysis suggests that periodic variations of SM are mainly and significantly over the 10-30-day period over eastern China in all the data. The significant spectra over the 10-30-day period basically occur during the rainy season over eastern China. For the spatial aspect of SSV-SM, precipitation is the main factor causing the spatial distribution of SSV-SM over eastern China. However, the spectra of the station precipitation are not consistent with those of the station SM, and there is less coherence between the precipitation and SM over the periods during which SM has significant spectra. This indicates that SSV-SM is also affected by other factors.
引用
收藏
页码:3527 / 3541
页数:15
相关论文
共 50 条
  • [31] Sub-seasonal interannual variability associated with the excess and deficit Indian winter monsoon over the Western Himalayas
    A. P. Dimri
    Climate Dynamics, 2014, 42 : 1793 - 1805
  • [32] Sub-seasonal interannual variability associated with the excess and deficit Indian winter monsoon over the Western Himalayas
    Dimri, A. P.
    CLIMATE DYNAMICS, 2014, 42 (7-8) : 1793 - 1805
  • [33] Hybrid Deep Learning and S2S Model for Improved Sub-Seasonal Surface and Root-Zone Soil Moisture Forecasting
    Xu, Lei
    Yu, Hongchu
    Chen, Zeqiang
    Du, Wenying
    Chen, Nengcheng
    Huang, Min
    REMOTE SENSING, 2023, 15 (13)
  • [34] Skilful sub-seasonal forecasts of aggregated temperature over Europe
    Baker, Laura
    Charlton-Perez, Andrew
    Mattu, Kanzis L.
    METEOROLOGICAL APPLICATIONS, 2023, 30 (06)
  • [35] On the seasonal and sub-seasonal factors influencing East China tropical cyclone landfall
    Sparks, Nathan
    Toumi, Ralf
    ATMOSPHERIC SCIENCE LETTERS, 2021, 22 (02):
  • [36] New perspectives on sub-seasonal xylem anatomical responses to climatic variability
    Ziaco, Emanuele
    Liang, Eryuan
    TREES-STRUCTURE AND FUNCTION, 2019, 33 (04): : 973 - 975
  • [37] Unraveling sub-seasonal precipitation variability in the Middle East via Indian Ocean sea surface temperature
    Hochman, Assaf
    Shachar, Noam
    Gildor, Hezi
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [38] Effects of sub-seasonal variability on seasonal-to-interannual Indian Ocean meridional heat transport
    Halkides, D. J.
    Han, Weiqing
    Lee, Tong
    Masumoto, Yukio
    GEOPHYSICAL RESEARCH LETTERS, 2007, 34 (12)
  • [39] Sub-seasonal to seasonal drivers of dry extreme rainfall events over Northeast Thailand
    Abatan, Abayomi A.
    Collins, Matthew
    Babel, Mukand S.
    Khadka, Dibesh
    De Silva, Yenushi K.
    FRONTIERS IN CLIMATE, 2023, 4
  • [40] Deep learning for daily spatiotemporally continuity of satellite surface soil Moisture over eastern China in summer
    Zhou, Yang
    Zhang, Yan
    Wang, Ruliang
    Chen, Haishan
    Zhao, Qifan
    Liu, Binshuo
    Shao, Qing
    Cao, Lu
    Sun, Shanlei
    JOURNAL OF HYDROLOGY, 2023, 619