DOI: 10.3390/rs12040649
论文题名: A novel ENSO monitoring method using precipitable water vapor and temperature in Southeast China
作者: Zhao Q. ; Liu Y. ; Yao W. ; Ma X. ; Yao Y.
刊名: Remote Sensing
ISSN: 20724292
出版年: 2020
卷: 12, 期: 4 语种: 英语
英文关键词: El Niño-Southern Oscillation (ENSO)
; Precipitable water vapor (PWV)
; Standard PWV and T index (SPTI)
; Temperature (T)
Scopus关键词: Atmospheric pressure
; Global positioning system
; Oceanography
; Orthogonal functions
; Spectrum analysis
; Surface waters
; Water vapor
; Weather forecasting
; El Nino southern oscillation
; Empirical Orthogonal Function
; Global Navigation Satellite Systems
; Precipitable water vapor
; Sea surface temperature anomalies
; Southern oscillation
; Spatio-temporal consistencies
; Spatiotemporal characteristics
; Climatology
英文摘要: Southeast China, a non-core region influenced by the El Nino-Southern Oscillation (ENSO), has been seldom investigated before. However, the occurrence of ENSO will affect the redistribution of precipitation and the temperature (T) spatial pattern on a global scale. This condition will further lead to flood or drought disasters in Southeast China. Therefore, the method of monitoring the occurrence of ENSO is important and is the focus of this paper. The spatiotemporal characteristics of precipitable water vapor (PWV) and T are first analyzed during ENSO using the empirical orthogonal function (EOF). The results showed that a high correlation spatiotemporal consistency exist between PWV and T. The response thresholds of PWV and T to ENSO are determined by moving the window correlation analysis (MWCA). If the sea surface temperature anomaly (SSTA) at the Nino 3.4 region exceeded the ranges of (-1.17°C, 1.04°C) and (-1.15°C, 1.09°C), it could cause the anomalous change of PWV and T in Southeast China. Multichannel singular spectral analysis (MSSA) is introduced to analyze the multi-type signals (tendency, period, and anomaly) of PWV and T over the period of 1979-2017. The results showed that the annual abnormal signal and envelope line fluctuation of PWV and T agreed well in most cases with the change in SSTA. Therefore, a standard PWV and T index (SPTI) is proposed on the basis of the results to monitor ENSO events. The PWV and T data derived from the grid-based European Center for Medium-Range Weather Forecasting (ECMWF) reanalysis products and GNSS/RS stations in Southeast China were used to validate the performance of the proposed SPTI. Experimental results revealed that the time series of average SPTI calculated in Southeast China corresponded well to that of SSTA with a correlation coecient of 0.66 over the period of 1979-2017. The PWV values derived from the Global Navigation Satellite System (GNSS) and radiosonde data at two specific stations (WUHN and 45004) were also used to calculate the SPTI. The results showed that the correlation coefficients between SPTI and SSTA were 0.73 and 0.71, respectively. Such results indicate the capacity of the proposed SPTI to monitor the ENSO in Southeast China. © 2020 by the author. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159661
Appears in Collections: 气候变化与战略
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作者单位: College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China; School of Geodesy and Geomatics, Wuhan University, Wuhan, 430072, China
Recommended Citation:
Zhao Q.,Liu Y.,Yao W.,et al. A novel ENSO monitoring method using precipitable water vapor and temperature in Southeast China[J]. Remote Sensing,2020-01-01,12(4)