A Drought Monitoring Method Based on Precipitable Water Vapor and Precipitation

2020 ◽  
Vol 33 (24) ◽  
pp. 10727-10741
Author(s):  
Qingzhi Zhao ◽  
Xiongwei Ma ◽  
Wanqiang Yao ◽  
Yang Liu ◽  
Yibin Yao

AbstractPrecipitable water vapor (PWV) with high precision and high temporal resolution can be obtained based on the global navigation and satellite positioning system (GNSS) technique, which is important for GNSS in disaster prevention and mitigation. However, related studies on drought monitoring using PWV have rarely been performed before, which becomes the focus of this paper. This paper proposes a novel drought monitoring method using GNSS-derived PWV and precipitation, and a multi-time-scale standardized precipitation conversion index (SPCI) is established. This index is different from the traditional index in terms of expression, standardization, and time scale. The proposed SPCI is then compared with the standardized precipitation index/standardized precipitation evapotranspiration index/self-calibrating Palmer drought severity index (SPI/SPEI/scPDSI) and applied to local and global drought monitoring. Validated results show that multi-time-scale SPCI has good consistency with the corresponding SPI/SPEI/scPDSI. The correlation between SPCI and SPEI is the strongest (more than 0.96) on a 12-month scale, which indicates the application potential of SPCI in drought monitoring. In addition, applications for regional (Queensland, Australia) and global drought/wet monitoring further verify the capability of the proposed SPCI. The average percentage deviations of drought/wet monitoring between SPCI and SPEI are 2.77% and 3.75%, respectively on a global scale. The above results show that the SPCI developed in this study is efficiently applied to global flood/wet studies.

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5566 ◽  
Author(s):  
Qingzhi Zhao ◽  
Xiongwei Ma ◽  
Wanqiang Yao ◽  
Yang Liu ◽  
Zheng Du ◽  
...  

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.


2018 ◽  
Vol 31 (17) ◽  
pp. 6897-6911 ◽  
Author(s):  
Chuanpeng Zhao ◽  
Yaohuan Huang ◽  
Zhonghua Li ◽  
Mingxing Chen

Global changes, such as human activities and climate change, increase the odds of worsening drought. The Gravity Recovery and Climate Experiment (GRACE) satellite provides an opportunity to monitor drought levels by the total amount of water, instead of using a small finite set of water cycle elements or indirect indicators. The potential gap lies in the insufficient size of the GRACE record. The database does not meet the requirements of a stationary annual cycle calculated over a relatively long period as recommended by the IPCC, and the disturbance from long-term global changes is often not considered. In this work, a GRACE-based modulated water deficit (GRACE-MWD) process for drought monitoring under the modulated annual cycle (MAC) reference frame in southwest China was proposed. GRACE-MWD achieved a higher ratio of agreement with the standardized precipitation evapotranspiration index at a time scale of 3 months (SPEI03): it ranged from 0.48 to 0.84, while the GRACE-based drought severity index (GRACE-DSI) ranged from 0.48 to 0.68. Compared with remote sensing datasets widely used in drought monitoring, GRACE-MWD data are less affected by seasonality from land-cover categories, which benefit from the MAC reference frame. The ratio-of-agreement metric for the study area showed that GRACE-MWD had a time scale between 7 and 11 months in reference to SPEI and the standardized precipitation index (SPI). The stability of the MAC reference frame to GRACE-MWD was further discussed when GRACE records were extended and was more stable than that of the stationary annual cycle. GRACE-MWD meets global changes via an adaptive reference frame, which is worthy of generalizing to global applications.


2017 ◽  
Author(s):  
Monica Campanelli ◽  
Alessandra Mascitelli ◽  
Paolo Sanò ◽  
Henri Diémoz ◽  
Victor Estellés ◽  
...  

Abstract. The estimation of the precipitable water vapor content (W) with high temporal and spatial resolution is of great interest in both meteorological and climatological studies. Several methodologies based on remote sensing techniques have been recently developed, in order to obtain accurate and frequent measurements of this atmospheric parameter. Among them, the relative low cost and easy deployment of sun-sky radiometers, or sun-photometers, operating in several international networks, allowed the development of automatic estimations of W from these instruments with high temporal resolution. However the great problem of this methodology is the estimation of the sun-photometric calibration parameters. The objective of this paper is to validate a new methodology based on the hypothesis that the calibration parameters characterizing the atmospheric transmittance at 940 nm are dependent on vertical profiles of temperature, air pressure and moisture typical of each measurement site. To obtain the calibration parameters some simultaneously seasonal independent measurements of W taken over a large range of solar zenith angle and covering a wide range of W, are needed. In this work yearly GNSS/GPS dataset were used for obtaining a table of photometric calibration constants and the methodology was applied and validated in three European ESR-SKYNET network sites, characterized by different atmospheric and climatic conditions: Rome, Valencia and Aosta. Results were validated against the GNSS/GPS and AErosol Robotic NETwork (AERONET) W estimations. In both the validations the agreement was very high with a percentage RMSD of about 6 %, 13 % and 8 % in the case of GPS intercomparison at Rome, Aosta and Valencia, respectively, and of 8 % in the case of AERONET comparison in Valencia. Analysing the results by W classes, the present methodology was found to clearly improve W estimation at low W content when compared against AERONET in term of %Bias, bringing the agreement with the GPS (considered the reference one), from a %Bias of 5.76 to 0.52.


2020 ◽  
Vol 13 (9) ◽  
pp. 4963-4972
Author(s):  
Zhilu Wu ◽  
Yanxiong Liu ◽  
Yang Liu ◽  
Jungang Wang ◽  
Xiufeng He ◽  
...  

Abstract. The calibration microwave radiometer (CMR) on board the Haiyang-2A (HY-2A) satellite provides wet tropospheric delay correction for altimetry data, which can also contribute to the understanding of climate system and weather processes. The ground-based global navigation satellite system (GNSS) provides precise precipitable water vapor (PWV) with high temporal resolution and could be used for calibration and monitoring of the CMR data, and shipborne GNSS provides accurate PWV over open oceans, which can be directly compared with uncontaminated CMR data. In this study, the HY-2A CMR water vapor product is validated using ground-based GNSS observations of 100 International GNSS Service (IGS) stations along the global coastline and 56 d shipborne GNSS observations over the Indian Ocean. The processing strategy for GNSS data and CMR data is discussed in detail. Special efforts were made in the quality control and reconstruction of contaminated CMR data. The validation result shows that HY-2A CMR PWV agrees well with ground-based GNSS PWV with 2.67 mm as the root mean square (rms) within 100 km. Geographically, the rms is 1.12 mm in the polar region and 2.78 mm elsewhere. The PWV agreement between HY-2A and shipborne GNSS shows a significant correlation with the distance between the ship and the satellite footprint, with an rms of 1.57 mm for the distance threshold of 100 km. Ground-based GNSS and shipborne GNSS agree with HY-2A CMR well.


2020 ◽  
Author(s):  
Jeongeun Won ◽  
Sangdan Kim

<p>In drought monitoring, it is very important to select climate variables to interpret drought. Most drought monitoring interprets drought as deficit in precipitation, so drought indices focused on the moisture supply side of the atmosphere have been mainly used. However, droughts can be caused not only by lack of rainfall, but also by various climate variables such as increase in temperature. In this regard, interest in potential evapotranspiration(PET), which is an moisture demand side of the atmosphere, is increasing and a PET-based drought index has been developed. However, complex droughts caused by various climate variables cannot be interpreted as a drought index that only considers precipitation or PET. In this study, we suggest a drought monitoring method that can reflect various future climate variables, including precipitation. In other words, copula-based joint drought index(CJDI), which incorporate standardized precipitation index(SPI) based on precipitation and evaporative demand drought index(EDDI) based on PET, is developed. CJDI, which considers both precipitation and PET, which are key variables related to drought, is able to properly monitor the drought events in Korea. In addition, future Drought severity – duration - frequency curves are derived to project future droughts compared to various drought indices. It is shown that CJDI can be used as a more reasonable drought index to establish the adaptation policy for future droughts by presenting the pattern of future droughts more realistically.</p><p><strong>Acknowledgment: </strong>This study was funded by the Korea Ministry of Environment (MOE) as Smart Urban Water Resources Management Program. (2019002950004)</p><p><strong>Keywords</strong>: Climate change; Copula; Drought; CJDI; Drought severity-duration-frequency curve</p>


2010 ◽  
Vol 49 (11) ◽  
pp. 2301-2314 ◽  
Author(s):  
John Hanesiak ◽  
Mark Melsness ◽  
Richard Raddatz

Abstract High-temporal-resolution total-column precipitable water vapor (PWV) was measured using a Radiometrics Corporation WVR-1100 Atmospheric Microwave Radiometer (AMR). The AMR was deployed at the University of Manitoba in Winnipeg, Canada, during the 2003 and 2006 growing seasons (mid-May–end of August). PWV data were examined 1) to document the diurnal cycle of PWV and to provide insight into the various processes controlling this cycle and 2) to assess the accuracy of the Canadian regional Global Environmental Multiscale (GEM) model analysis and forecasts (out to 36 h) of PWV. The mean daily PWV was 22.6 mm in 2003 and 23.8 mm in 2006, with distinct diurnal amplitudes of 1.5 and 1.8 mm, respectively. It was determined that the diurnal cycle of PWV about the daily mean value was controlled by evapotranspiration (ET) and the occurrence/timing of deep convection. The PWV in both years reached its hourly maximum later in the afternoon as opposed to at solar noon. This suggested that the surface and atmosphere were well coupled, with ET primarily being controlled by the vapor pressure deficit between the vegetation/surface and atmosphere. The decrease in PWV during the evening and overnight periods of both years was likely the result of deep convection, with or without precipitation, which drew water vapor out of the atmosphere, as well as the nocturnal decline in ET. The results did not change for days on which low-level winds were light (i.e., maximum winds from the surface to 850 hPa were below 20 km h−1), which supports the notion that the diurnal PWV pattern was associated with the daily cycles of local ET and convection/precipitation and was not due to advection. Comparison of AMR PWV with the Canadian GEM model for the growing seasons of 2003 and 2006 indicated that the model error was 3 mm (13%) or more even in the first 12 h, with mean absolute errors ranging from 2 to 3.5 mm and root-mean-square errors from 3 to 4.5 mm over the full 36-h forecast period. It was also found that the 3–9-h forecast period of GEM had better error scores in 2006 than in 2003.


2020 ◽  
Vol 12 (4) ◽  
pp. 649
Author(s):  
Qingzhi Zhao ◽  
Yang Liu ◽  
Wanqiang Yao ◽  
Xiongwei Ma ◽  
Yibin Yao

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.


2019 ◽  
Vol 3 ◽  
pp. 741
Author(s):  
Wedyanto Kuntjoro ◽  
Z.A.J. Tanuwijaya ◽  
A. Pramansyah ◽  
Dudy D. Wijaya

Kandungan total uap air troposfer (precipitable water vapor) di suatu tempat dapat diestimasi berdasarkan karakteristik bias gelombang elektromagnetik dari satelit navigasi GPS, berupa zenith wet delay (ZWD). Pola musiman deret waktu ZWD sangat penting dalam studi siklus hidrologi khususnya yang terkait dengan kejadian-kejadian banjir. Artikel ini menganalisis korelasi musiman antara ZWD dan debit sungai Cikapundung di wilayah Bandung Utara berdasarkan estimasi rataan pola musimannya. Berdasarkan rekonstruksi sejumlah komponen harmonik ditemukan bahwa pola musiman ZWD memiliki kemiripan dan korelasi yang kuat dengan pola musiman debit sungai. Pola musiman ZWD dan debit sungai dipengaruhi secara kuat oleh fenomena pertukaran Monsun Asia dan Monsun Australia. Korelasi linier di antara keduanya menunjukkan hasil yang sangat kuat, dimana hampir 90% fluktuasi debit sungai dipengaruhi oleh kandungan uap air di troposfer dengan level signifikansi 95%. Berdasarkan spektrum amplitudo silang dan koherensi, kedua kuantitas ini nampak didominasi oleh siklus monsun satu tahunan disertai indikasi adanya pengaruh siklus tengah tahunan dan 4 bulanan.


2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.


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