Literature DB >> 29556764

Extreme phenophase delays and their relationship with natural forcings in Beijing over the past 260 years.

Yang Liu1,2, Mingqing Zhang3, Xiuqi Fang4,5.   

Abstract

By merging reconstructed phenological series from published articles and observations of China Phenology Observation Network (CPON), the first blooming date of Amygdalus davidiana (FBA) in Beijing between 1741 and 2000 is reconstructed. The Butterworth method is used to remove the multi-year variations for generating the phenological series of annual variations in the first blooming date of A. davidiana. The extreme delay years in the phenological series are identified using the percentage threshold method. The characteristics of the extreme delays and the correspondence of these events with natural forcings are analysed. The main results are as follows. In annual phenological series, the extreme delays appeared in single year as main feature, only A.D.1800-1801, 1816-1817 and 1983-1984 were the events of two consecutively extreme years. Approximately 85% of the extreme delays occurred during 1-2 years after the large volcanic eruptions (VEI ≥ 4) in the eastern rim or the western rim of the Pacific Ocean, as the same proportion of the extreme delays followed El Niño events. About 73% years of the extreme delays fall in the valleys of sunspot cycles or the Dalton minimum period in the year or the previous year. According to the certainty factor (CF), the large eruptions have the greatest influence to the extreme delays; sunspot activity is the second, and ENSO is the last one. The extreme phenological delayed year is most likely to occur after a large eruption, which particularly occurs during El Niño year and its previous several years were in the descending portion or valley of sunspot phase.

Entities:  

Keywords:  Beijing; ENSO; Extreme phenophase delays; First blooming date; Large eruption; Sunspot phase

Mesh:

Year:  2018        PMID: 29556764     DOI: 10.1007/s00484-018-1528-0

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


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