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Xiongwei Ma
School of Geodesy and Geomatics, Wuhan University, Wuhan 430072, China

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School of Geodesy and Geomatics,Wuhan University 129 Luoyu Road, Wuhan 430079, China

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Journal article
Published: 14 May 2021 in Remote Sensing
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From the aspect of global drought monitoring, improving the regional drought monitoring method is becoming increasingly important for the sustainable development of regional agriculture and the economy. The standardized precipitation conversion index (SPCI) calculated by the Global Navigation Satellite System (GNSS) observation is a new means for drought monitoring that has the advantages of simple calculation and real-time monitoring. However, only SPCI with a 12-month scale has been verified on a global scale, while its capability and applicability for monitoring drought at a short time scale in regional areas have never been investigated. Therefore, this study aims to evaluate the performance of SPCI at other time scales in Yunnan, China, and propose an improved method for SPCI. The data of six GNSS stations were selected to calculate SPCI; the standardized precipitation evapotranspiration index (SPEI) and composite meteorological drought index (CI) are introduced to evaluate the SPCI at a short time scale in Yunnan Province. In addition, a modified CI (MCI) was proposed to calibrate the SPCI because of its large bias in Yunnan. Experimental results show that (1) SPCI exhibits better agreement with CI in Yunnan Province when compared to SPEI; (2) the capability of SPCI for drought monitoring is superior to that of SPEI in Yunnan; and (3) the improved SPCI is more suitable for drought monitoring in Yunnan, with a relative bias of 5.43% when compared to the MCI. These results provide a new means for regional drought monitoring in Yunnan, which is significant for dealing with drought disasters and formulating related disaster prevention and mitigation policies.

ACS Style

Xiongwei Ma; Yibin Yao; Qingzhi Zhao. Regional GNSS-Derived SPCI: Verification and Improvement in Yunnan, China. Remote Sensing 2021, 13, 1918 .

AMA Style

Xiongwei Ma, Yibin Yao, Qingzhi Zhao. Regional GNSS-Derived SPCI: Verification and Improvement in Yunnan, China. Remote Sensing. 2021; 13 (10):1918.

Chicago/Turabian Style

Xiongwei Ma; Yibin Yao; Qingzhi Zhao. 2021. "Regional GNSS-Derived SPCI: Verification and Improvement in Yunnan, China." Remote Sensing 13, no. 10: 1918.

Journal article
Published: 01 April 2021 in Journal of Hydrology
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Terrestrial evaporation is the central link of land surface energy balance, which is very important for climate change, water cycle research and drought monitoring. Potential evapotranspiration (ETP) is an important form of ET, which play a significance for calculating standardized precipitation evapotranspiration index (SPEI). This paper proposed a novel method of retrieving ETP using precipitable water vapor (PWV) and temperature to obtain the high precision and resolution ETP dataset, and the ETP and SPEI are obtained with the temporal-spatial resolutions of monthly and 0.125° × 0.125°, respectively, in China. The PWV derived from the European Center for Medium-range Weather Forecasts (ECMWF) is first validated and calibrated using the Global Navigation Satellite System (GNSS) technique. ETP and SPEI at specific stations are then calculated using the site-based revised Thornthwaith (S-RTH) model with high precision. Finally, spherical harmonic function is applied to fit the coefficients of the S-RTH model in China, and a RTH model over China (C-RTH) with high spatial resolution (0.125° × 0.125°) is established. Statistical result reveals that (1) the average root mean square (RMS) and mean absolute error (MAE) of the calibrated ECMWF-derived PWV have been improved from 2.0/1.7 mm to 1.7/1.4 mm, respectively using the GNSS-derived PWV. (2) The improvement rate of ETP derived from the S-RTH model is approximately 68% compared with that from the TH model, and the average RMS and MAE of the ETP difference between S-RTH and Penman–Monteith (PM) are 10.7 mm and 8.5 mm, respectively. (3) The average RMS and MAE of potential difference between C-RTH and PM are 17.6 mm and 13.7 mm, respectively. Although the accuracy of the C-RTH model is slightly lower than that of the S-RTH model, it is significantly improved compared with the TH model, and the calculated ETP data have been converted from point to surface. The proposed method expands the application of GNSS technique to obtain ETP data set, which provides the basic data guarantee for drought disaster prevention and control in China.

ACS Style

Xiongwei Ma; Qingzhi Zhao; Yibin Yao; Wanqiang Yao. A novel method of retrieving potential ET in China. Journal of Hydrology 2021, 598, 126271 .

AMA Style

Xiongwei Ma, Qingzhi Zhao, Yibin Yao, Wanqiang Yao. A novel method of retrieving potential ET in China. Journal of Hydrology. 2021; 598 ():126271.

Chicago/Turabian Style

Xiongwei Ma; Qingzhi Zhao; Yibin Yao; Wanqiang Yao. 2021. "A novel method of retrieving potential ET in China." Journal of Hydrology 598, no. : 126271.

Journal article
Published: 15 February 2020 in Remote Sensing
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Southeast China, a non-core region influenced by the El Niño–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 Niño 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 coefficient 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.

ACS Style

Qingzhi Zhao; Yang Liu; Wanqiang Yao; Xiongwei Ma; Yibin Yao. A Novel ENSO Monitoring Method using Precipitable Water Vapor and Temperature in Southeast China. Remote Sensing 2020, 12, 649 .

AMA Style

Qingzhi Zhao, Yang Liu, Wanqiang Yao, Xiongwei Ma, Yibin Yao. A Novel ENSO Monitoring Method using Precipitable Water Vapor and Temperature in Southeast China. Remote Sensing. 2020; 12 (4):649.

Chicago/Turabian Style

Qingzhi Zhao; Yang Liu; Wanqiang Yao; Xiongwei Ma; Yibin Yao. 2020. "A Novel ENSO Monitoring Method using Precipitable Water Vapor and Temperature in Southeast China." Remote Sensing 12, no. 4: 649.

Journal article
Published: 03 February 2020 in IEEE Transactions on Geoscience and Remote Sensing
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Except for its known aspects of positioning, navigation, and timing (PNT), the Global Navigation Satellite System (GNSS) has extended its application to the rainfall forecasting. GNSS-derived zenith total delay (ZTD) or precipitable water vapor (PWV) has been used as a single factor to predict the occurrence of rainfall; however, the rainfall is highly correlated with myriad atmospheric parameters, which cannot be perfectly reflected by a single predictor. In this article, an improved rainfall forecasting model (IRFM) is proposed to forecast the rainfall. The IRFM considers five predictors: monthly PWV value, seasonal PWV/ZTD variations, and their first derivatives: it can forecast rainfall using a single predicator or an arbitrary combination of those predicators. The merit of IRFM is reducing the false forecasted rainfall (FFR) events and missed detected rainfall (MDR) events as much as possible while guaranteeing the true detected rainfall (TDR) events. An optimized selecting principle of predictors’ threshold has been determined using the percentile method. The test experiment has been performed using five GNSS stations derived from continuously operating reference system (CORS) network of Zhejiang province, China. The analysis reveals that the IRFM considering five predictors provides a better performance than that only using a single predictor or a combination of arbitrary predictors. The statistical result shows the average TDR value of more than 95%, FFR value of less than 30%, and MDR of less than 5%, respectively. Compared to the existing rainfall forecasting methods using ZTD or PWV, the IRFM reduces the FFR and MDR, respectively, with the lowest values, while the TDR value is the highest.

ACS Style

Qingzhi Zhao; Yang Liu; Xiongwei Ma; Wanqiang Yao; Yibin Yao; Xin Li. An Improved Rainfall Forecasting Model Based on GNSS Observations. IEEE Transactions on Geoscience and Remote Sensing 2020, 58, 4891 -4900.

AMA Style

Qingzhi Zhao, Yang Liu, Xiongwei Ma, Wanqiang Yao, Yibin Yao, Xin Li. An Improved Rainfall Forecasting Model Based on GNSS Observations. IEEE Transactions on Geoscience and Remote Sensing. 2020; 58 (7):4891-4900.

Chicago/Turabian Style

Qingzhi Zhao; Yang Liu; Xiongwei Ma; Wanqiang Yao; Yibin Yao; Xin Li. 2020. "An Improved Rainfall Forecasting Model Based on GNSS Observations." IEEE Transactions on Geoscience and Remote Sensing 58, no. 7: 4891-4900.

Journal article
Published: 03 February 2020 in Applied Sciences
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Ecological restoration and climate change in the Loess Plateau region have become research hotspots. Climate change and anthropogenic activities have led to spatial–temporal pattern variations in vegetation and extreme climatic indices and meteorological factors. Therefore, obtaining a better understanding is necessary of the internal relations between vegetation and meteorological factors. In this paper, the interplay between vegetation index and various factors, including extreme climatic indices and meteorological factors, during a long-term time series is investigated using Mann–Kendall trend analysis, and Pearson correlation coefficient analysis. The mechanisms of interaction between vegetation growth and various factors in the Loess Plateau are then analyzed. Results reveal that (i) the rapid growth of vegetation during 2000–2015 has made a major contribution to the growth trend of the Loess Plateau in the past 33 years (1982–2015). During 2000–2015, the increase of vegetation may inhibit the increase of extreme warm index and the decrease of extreme cold index; (ii) a warm and dry climate developed with decreasing relative humidity and increasing temperature; (iii) the normalized vegetation index (NDVI) is strongly correlated with extreme climatic indices and meteorological factors, especially precipitable water vapor (PWV), with a correlation coefficient of 0.94; and (iv) the daily temperature range, diurnal temperature range and sunshine duration (SSD) exerted different time-delay effects on vegetation growth in the Loess Plateau. The above findings provide an essential theoretical basis for ecological policy formulation in the Loess Plateau.

ACS Style

Qingzhi Zhao; Xiongwei Ma; Liang Liang; Wanqiang Yao. Spatial–Temporal Variation Characteristics of Multiple Meteorological Variables and Vegetation over the Loess Plateau Region. Applied Sciences 2020, 10, 1000 .

AMA Style

Qingzhi Zhao, Xiongwei Ma, Liang Liang, Wanqiang Yao. Spatial–Temporal Variation Characteristics of Multiple Meteorological Variables and Vegetation over the Loess Plateau Region. Applied Sciences. 2020; 10 (3):1000.

Chicago/Turabian Style

Qingzhi Zhao; Xiongwei Ma; Liang Liang; Wanqiang Yao. 2020. "Spatial–Temporal Variation Characteristics of Multiple Meteorological Variables and Vegetation over the Loess Plateau Region." Applied Sciences 10, no. 3: 1000.

Journal article
Published: 30 December 2019 in IEEE Access
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Considering the noncore region influenced by El Niño-Southern Oscillation (ENSO) events, China is hardly investigated in terms of the vegetation variation during the ENSO period.Therefore, this study focused on increasing knowledge of vegetation growth and variation during the ENSO period.The novelty of this paper is introduced the moving window correlation analysis method to determine the thresholds of vegetation response to sea surface temperature anomaly (SSTa) and southern oscillation index (SOI) and analyze the main reasons for such variations.China was divided into seven areas based on different weather conditions, and the variations in vegetation growth in various areas during the ENSO period were analyzed. The response of vegetation to ENSO events in China was analyzed from the perspectives of precipitable water vapor (PWV), temperature, and precipitation, thereby revealing the interplay of multi-factors on vegetation growth.The main conclusions include (1) a positive vegetation response to El Niño exists all over China with thresholds of SSTa ≥ 1.87°C and SOI ≤ –3.27hPa, whereas a negative response of vegetation variation to La Niña exists with thresholds of SSTa ≤ –1.05°C and SOI ≥ 1.7hPa; (2) the correlations (p < 0.05) of PWV to normalized difference vegetation index (NDVI) (PWV-NDVI), temperature-NDVI, and precipitation-NDVI reached 0.84, 0.86, and 0.68, respectively, and PWV, temperature, and precipitation were negatively/positively abnormal during El Niño/La Niña periods; (3) in coastal areas of Southeast China, correlations between NDVI and PWV/temperature/ precipitation are poor and the opposite anomalies of PWV/temperature/ precipitation existed when compared to other areas of China.

ACS Style

Qingzhi Zhao; Xiongwei Ma; Wanqiang Yao; Yang Liu; Yibin Yao. Anomaly Variation of Vegetation and Its Influencing Factors in Mainland China During ENSO Period. IEEE Access 2019, 8, 721 -734.

AMA Style

Qingzhi Zhao, Xiongwei Ma, Wanqiang Yao, Yang Liu, Yibin Yao. Anomaly Variation of Vegetation and Its Influencing Factors in Mainland China During ENSO Period. IEEE Access. 2019; 8 (99):721-734.

Chicago/Turabian Style

Qingzhi Zhao; Xiongwei Ma; Wanqiang Yao; Yang Liu; Yibin Yao. 2019. "Anomaly Variation of Vegetation and Its Influencing Factors in Mainland China During ENSO Period." IEEE Access 8, no. 99: 721-734.

Journal article
Published: 16 December 2019 in Sensors
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Standardized precipitation evapotranspiration index (SPEI) is an acknowledged drought monitoring index, and the evapotranspiration (ET) used to calculated SPEI is obtained based on the Thornthwaite (TH) model. However, the SPEI calculated based on the TH model is overestimated globally, whereas the more accurate ET derived from the Penman–Monteith (PM) model recommended by the Food and Agriculture Organization of the United Nations is unavailable due to the lack of a large amount of meteorological data at most places. Therefore, how to improve the accuracy of ET calculated by the TH model becomes the focus of this study. Here, a revised TH (RTH) model is proposed using the temperature (T) and precipitable water vapor (PWV) data. The T and PWV data are derived from the reanalysis data and the global navigation satellite system (GNSS) observation, respectively. The initial value of ET for the RTH model is calculated based on the TH model, and the time series of ET residual between the TH and PM models is then obtained. Analyzed results reveal that ET residual is highly correlated with PWV and T, and the correlate coefficient between PWV and ET is −0.66, while that between T and ET for cases of T larger or less than 0 °C are −0.54 and 0.59, respectively. Therefore, a linear model between ET residual and PWV/T is established, and the ET value of the RTH model can be obtained by combining the TH-derived ET and estimated ET residual. Finally, the SPEI calculated based on the RTH model can be obtained and compared with that derived using PM and TH models. Result in the Loess Plateau (LP) region reveals the good performance of the RTH-based SPEI when compared with the TH-based SPEI over the period of 1979–2016. A case analysis in April 2013 over the LP region also indicates the superiority of the RTH-based SPEI at 88 meteorological and 31 GNSS stations when the PM-based SPEI is considered as the reference.

ACS Style

Qingzhi Zhao; Xiongwei Ma; Wanqiang Yao; Yang Liu; Zheng Du; Pengfei Yang; Yibin Yao; Yao. Improved Drought Monitoring Index Using GNSS-Derived Precipitable Water Vapor over the Loess Plateau Area. Sensors 2019, 19, 5566 .

AMA Style

Qingzhi Zhao, Xiongwei Ma, Wanqiang Yao, Yang Liu, Zheng Du, Pengfei Yang, Yibin Yao, Yao. Improved Drought Monitoring Index Using GNSS-Derived Precipitable Water Vapor over the Loess Plateau Area. Sensors. 2019; 19 (24):5566.

Chicago/Turabian Style

Qingzhi Zhao; Xiongwei Ma; Wanqiang Yao; Yang Liu; Zheng Du; Pengfei Yang; Yibin Yao; Yao. 2019. "Improved Drought Monitoring Index Using GNSS-Derived Precipitable Water Vapor over the Loess Plateau Area." Sensors 19, no. 24: 5566.

Journal article
Published: 29 November 2019 in Remote Sensing
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Some seasonal natural floods can be attributed to typhoons that bring a large amount of atmospheric water vapor, and variations in atmospheric water vapor can be reflected in the precipitable water vapor (PWV). Therefore, monitoring typhoons based on the anomalous variations of the PWV is the focus of this paper. The anomalous variations of ERA5(fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting)-derived PWV with other atmospheric parameters related to typhoons, such as precipitation, pressure, and wind, were first analyzed during typhoon periods. After that, a typhoon-monitoring method with and without considering the typhoon’s acceleration was proposed according to the time of the maximum value of the PWV during the typhoon period in this paper. Corresponding experiments based on the measured and simulated data were performed to evaluate the proposed method. The experimental measurement of Typhoon Hato revealed that the velocity of the typhoon’s movement estimated by the proposed method was close to the observed value, and the maximum difference between the estimated and observed values was less than 3 km/h. A simulated experiment was also carried out in which the acceleration of the typhoon’s movement was also considered. The simulated results verified the reliability and feasibility of the proposed method. The estimated velocity and acceleration of the typhoon’s movement were almost equal to the true values under the cases of using different numbers of stations and selecting various typhoon locations. Such results obtained above indicate that the method proposed in this paper has a significant potential application value for typhoon monitoring.

ACS Style

Qingzhi Zhao; Xiongwei Ma; Wanqiang Yao; Yibin Yao. A New Typhoon-Monitoring Method Using Precipitation Water Vapor. Remote Sensing 2019, 11, 2845 .

AMA Style

Qingzhi Zhao, Xiongwei Ma, Wanqiang Yao, Yibin Yao. A New Typhoon-Monitoring Method Using Precipitation Water Vapor. Remote Sensing. 2019; 11 (23):2845.

Chicago/Turabian Style

Qingzhi Zhao; Xiongwei Ma; Wanqiang Yao; Yibin Yao. 2019. "A New Typhoon-Monitoring Method Using Precipitation Water Vapor." Remote Sensing 11, no. 23: 2845.