Kefei Zhang

China University of Mining and Technology

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Suqin Wu

Jiangsu University

Xiaoming Wang

Chinese Academy of Sciences

Robert Norman

ACT Government

Wang Li

Kunming University of Science and Technology

Andong Hu

Cooperative Institute for Research in Environmental Sciences

Longjiang Li

University of Electronic Science and Technology of China

Brett Carter

RMIT University

Peng Sun

China University of Mining and Technology

Dongsheng Zhao

China University of Mining and Technology

Moufeng Wan

Hong Kong University of Science and Technology

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China University of Mining and Technology

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Chinese Academy of Sciences

RMIT University

University of Chinese Academy of Sciences

Ministry of Natural Resources

Wuhan University

Institute of Geodesy and Geophysics

Aerospace Information Research Institute

MIT University

Central South University

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Flash drought monitoring using diurnal-provided evaporative demand drought index

Journal of Hydrology (2024)

Haobo Li Suelynn Choy Safoora Zaminpardaz Xiaoming Wang Hong Liang

Flash drought, as a relatively new concept, represents a rapidly evolving drought with sudden onset, short-term duration, and great destructiveness. With the warming of the planet in recent decades, the frequent occurrences of flash droughts have resulted in considerable losses to personnel and properties on a global scale. Nowadays, the emerging Evaporative Demand Drought Index (EDDI) has revealed its significant potential and adaptability in the early warning and quantification of flash droughts. In this study, an advanced method for improving the accuracy and temporal resolution of EDDI is proposed. The new set of EDDI estimates is calculated using diurnal-provided potential evapotranspiration values that have been calibrated with weather parameters and Global Navigation Satellite Systems (GNSS) atmospheric products. Then, the monitoring performances of flash droughts resulting from the diurnal-provided EDDIs are evaluated over the period 2010–2021 in Hong Kong. Results showed that the Probability Of Detection (POD) and False Alarm Rate (FAR) were 87.1 % and 16.7 %, respectively. By comparing with their counterparts obtained from the use of monthly EDDIs, it was found that the improvements made by the new method in the metrics of POD and FAR were 24.6 % and 11.2 %, respectively. In addition, with the use of diurnal-provided EDDI, the mean lead time for flash drought detection has been prolonged to 37.74 days, offering more time to prevent and mitigate the detrimental effects brought by flash drought events.

Flash flood

Diurnal temperature variation

10.1016/j.jhydrol.2024.130961

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Citations (3)

Spatial‐Temporal Behaviors of Large‐Scale Ionospheric Perturbations During Severe Geomagnetic Storms on September 7–8 2017 Using the GNSS, SWARM and TIE‐GCM Techniques

Journal of Geophysical Research Space Physics (2022)

Wang Li Dongsheng Zhao Changyong Hé Craig Hancock Yi Shen

Abstract Geomagnetic storms on 7–8 September 2017 triggered severe ionospheric disturbances that had a serious effect on satellite navigation and radio communication. Multiple observations derived from Global Navigation Satellite System receivers, Earth's Magnetic Field and Environment Explorers (SWARM) and the Thermosphere‐Ionosphere ‐Electrodynamics General Circulation Model's simulations are utilized to investigate the spatial‐temporal ionospheric behaviors under storm conditions. The results indicate that the electron density in the Asia‐Australia, Europe‐Africa and America sectors suddenly changed with the Bz southward excursion, and the ionosphere over low‐middle latitudes under the sunlit hemisphere is easily affected by the disturbed magnetic field. The SWARM observations verified the remarkable double‐peak structure of plasma enhancements over the equator and middle latitudes. The physical mechanism of low‐middle plasma disturbances can be explained by a combination effect of equatorial electrojets, vertical E × B drifts, meridional wind and thermospheric O/N 2 change. Besides, the severe storms triggered strong Polar plasma disturbances on both dayside and nightside hemispheres, and the Polar disturbances had a latitudinal excursion associated with the offset of geomagnetic field. Remarkable plasma enhancements at the altitudes of 100–160 km were also observed in the auroral zone and middle latitudes (>47.5°N/S). The topside polar ionospheric plasma enhancements were dominated by the O+ ions. Furthermore, the TIE‐GCM's simulations indicate that the enhanced vertical E × B drifts, cross polar cap potential and Joule heating play an important role in generating the topside plasma perturbations.

10.1029/2021ja029830

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The WOA-CNN-LSTM-Attention Model for Predicting GNSS Water Vapor

IEEE Transactions on Geoscience and Remote Sensing (2024)

Xiangrong Yan Weifang Yang Motong Gao Nan Ding Wenyuan Zhang

Precipitable water vapor (PWV), as an important representative parameter of atmospheric water vapor contents, can be obtained by means of Global Navigation Satellite Systems (GNSS) using both ground-based and space-borne observation techniques. However, the PWV prediction models currently accessible tend to be simplistic combinations or individual models. In this study, we develop a WOA-CNN-LSTM-Attention model to predict PWV, which takes the sixteen GNSS PWV values near the HKKP station as characteristic parameters and the spatial relationship between the point of interest and its neighboring GNSS stations into consideration. An optimal model via the whale optimization algorithm (WOA) is investigated by using a wavelet analysis to separate noises, through combining convolutional neural network (CNN), long short-term memory neural network (LSTM) and attention mechanism. Results show that considerable improvement in the prediction accuracy has been achieved through a comparison between CNN-LSTM-Attention and the conventional LSTM and CNN-LSTM models. In terms of long-term predictability, CNN-LSTM-Attention is proven to be a superior model when 8 features are incorporated. The model's root mean square error (RMSE) is 2.30 mm which is reduced by 20.42 % than in the case of 0 feature is used. As a further analysis, we also examine the prediction performance of various models for hourly PWV using 7, 15, 30, 60 and 90 days of data as different lengths of training. The results show that CNN-LSTM-Attention has a better prediction effect when the training length is 30 days, the RMSE is 0.74 mm and the Nash-Sutcliffe efficiency coefficient (NSE) is 0.98.

Atmospheric models

10.1109/tgrs.2024.3406694

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Identification of Inclined Ionospheric Layers Using Analysis of GPS Occultation Data

IEEE Transactions on Geoscience and Remote Sensing (2011)

A. G. Pavelyev Kefei Zhang Chuansheng Wang Yuriy Kuleshov Yuei‐An Liou

The ionosphere and atmosphere may have significant impacts on the high-stable navigational signals of the Global Positioning System (GPS) in the communication link satellite to satellite. The classification of the different types of the ionospheric impact on the phase and amplitude of the GPS signals at altitudes of 40-90 km is introduced using the CHAllenging Minisatellite Payload (CHAMP) radio occultation (RO) data. An analytical model is elaborated for the description of the radio wave propagation in the stratified ionosphere and atmosphere. The propagation medium consists of sectors having the spherically symmetric distributions of refractivity. The newly developed model presents analytical expressions for the phase path and refractive attenuation of radio waves. The model explains significant amplitude and phase variations at altitudes of 40-90 km of the RO ray perigee associated with the influence of the inclined ionospheric layers. An innovative eikonal acceleration technique is described and applied to the identification and location of the inclined ionospheric layers using the comparative analysis of the amplitude and phase variations of the RO signals.

Radio occultation

Occultation

Ionogram

10.1109/tgrs.2010.2091138

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Application of the locality principle to radio occultation studies of the Earth's atmosphere and ionosphere

Atmospheric measurement techniques (2015)

A. G. Pavelyev Yuei‐An Liou S. S. Matyugov A. A. Pavelyev В. Н. Губенко

Abstract. A new formulation of the previously introduced principle of locality is presented. The principle can be applied for modernization of the radio occultation (RO) remote sensing of the atmospheres and ionospheres of the Earth and other planets. The principle states that significant contributions to variations of the intensity and phase of the radio waves passing through a layered medium are connected with influence of the vicinities of tangential points where the refractivity gradient is perpendicular to the radio ray trajectory. The RO method assumes spherical symmetry of the investigated medium. In this case, if location of a tangent point relative to the spherical symmetry centre is known, the time derivatives of the RO signal phase and Doppler frequency variations can be recalculated into the refractive attenuation. Several important findings are consequences of the locality principle: (i) if position of the centre of symmetry is known, the total absorption along the ray path can be determined at a single frequency; (ii) in the case of low absorption the height, displacement from the radio ray perigee, and tilt of the inclined ionospheric (atmospheric) layers can be evaluated; (iii) the contributions of the layered and irregular structures in the RO signal can be separated and parameters of layers and turbulence can be measured at a single frequency using joint analysis of the intensity and phase variations. Specially for the Earth's troposphere, the altitude distributions of the weak total absorption (about of 1–4 db) of the radio waves at GPS frequencies corresponding to possible influence of the oxygen, water vapour, and hydrometeors can be measured with accuracy of about 0.1 db at a single frequency. In accordance with the locality principle, a new index of ionospheric activity is introduced. This index is measured from the phase variations of radio waves passing through the ionosphere. Its high correlation with the S4 scintillation index is established. This correlation indicates the significant influence of locally spherical symmetric ionospheric layers on variations of the phase and intensity of the RO signal passing through transionospheric communication links. Obtained results expand applicable domain of the RO method as a powerful remote sensing technique for geophysical and meteorological research.

Radio occultation

10.5194/amt-8-2885-2015

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Citations (14)

Using global navigation satellite system data for real-time moisture analysis and forecasting over the Australian region I. The system

Journal of Southern Hemisphere Earth System Science (2019)

J. Le Marshall Robert Norman D.C. Howard Susan Rennie Michael J. Moore

The use of high spatial and temporal resolution data assimilation and forecasting around Australia’s capital cities and rural land provided an opportunity to improve moisture analysis and forecasting. To support this endeavour, RMIT University and Geoscience Australia worked with the Bureau of Meteorology (BoM) to provide real-time GNSS (global navigation satellite system) zenith total delay (ZTD) data over the Australian region, from which a high-resolution total water vapour field for SE Australia could be determined. The ZTD data could play an important role in high-resolution data assimilation by providing mesoscale moisture data coverage from existing GNSS surface stations over significant areas of the Australian continent. The data were used by the BoM’s high-resolution ACCESS-C3 capital city numerical weather prediction (NWP) systems, the ACCESS-G3 Global system and had been used by the ACCESS-R2-Regional NWP model. A description of the data collection and analysis system is provided. An example of the application of these local GNSS data for a heavy rainfall event over SE Australia/Victoria is shown using the 1.5-km resolution ACCESS-C3 model, which was being prepared for operational use. The results from the test were assessed qualitatively, synoptically and also examined quantitatively using the Fractions Skills Score which showed the reasonableness of the forecasts and demonstrated the potential for improving rainfall forecasts over south-eastern Australia by the inclusion of ZTD data in constructing the moisture field. These data have been accepted for operational use in NWP.

Zenith

10.1071/es19009

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Spaceborne GNSS-R Wind Speed Retrieval Using Machine Learning Methods

Remote Sensing (2022)

Changyang Wang Kegen Yu Fangyu Qu Jinwei Bu Shuai Han

This paper focuses on sea surface wind speed estimation using L1B level v3.1 data of reflected GNSS signals from the Cyclone GNSS (CYGNSS) mission and European Centre for Medium-range Weather Forecast Reanalysis (ECMWF) wind speed data. Seven machine learning methods are applied for wind speed retrieval, i.e., Regression trees (Binary Tree (BT), Ensembles of Trees (ET), XGBoost (XGB), LightGBM (LGBM)), ANN (Artificial neural network), Stepwise Linear Regression (SLR), and Gaussian Support Vector Machine (GSVM), and a comparison of their performance is made. The wind speed is divided into two different ranges to study the suitability of the different algorithms. A total of 10 observation variables are considered as input parameters to study the importance of individual variables or combinations thereof. The results show that the LGBM model performs the best with an RMSE of 1.419 and a correlation coefficient of 0.849 in the low wind speed interval (0–15 m/s), while the ET model performs the best with an RMSE of 1.100 and a correlation coefficient of 0.767 in the high wind speed interval (15–30 m/s). The effects of the variables used in wind speed retrieval models are investigated using the XGBoost importance metric, showing that a number of variables play a very significant role in wind speed retrieval. It is expected that these results will provide a useful reference for the development of advanced wind speed retrieval algorithms in the future.

10.3390/rs14143507

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Citations (13)

Sensing small-scale structures in the troposphere with tomographic principles (IAG working group)

Gregor Moeller C. O. Ao Zohreh Adavi Hugues Brenot André Sá

Within the International Association of Geodesy (IAG), a new working group was formed with the intention to bring together researchers and professionals working on tomography-based concepts for sensing the neutral atmosphere with space-geodetic techniques. Hereby the focus lies on Global Navigation Satellite Systems (GNSS) but also on complementary observation techniques, like Interferometric Synthetic Aperature Radar (InSAR) or microwave radiometers, sensitive to the water vapor distribution in the lower atmosphere.In the next four years (2019-2023), we will address current challenges in tropospheric tomography with focus on ground-based and space-based measurements, the combination of measurement techniques and the design of new observation concepts using tomographic principles. While geodetic GNSS networks are nowadays the backbone for troposphere tomography studies, further local densifications, e.g. at airports, cities or fundamental stations are necessary to achieve very fine spatial and temporal resolution. Besides, the combination of ground-based GNSS with other microwave techniques like radio occultation or InSAR seems to be beneficial due their complementary nature. Therefore, several further developments in the field of tropospheric tomography are required. This includes more dynamical tomography models - adaptable to varying input data, advanced ray-tracing algorithms for the reconstruction of space-based observations and the coordination of a benchmark campaign.In this presentation, we will give an overview about the current challenges in tropospheric tomography and the objectives of working group. The latter will also include standards for data exchange and therefore, make tomographic products available for the assimilation into numerical weather prediction models but also for various other disciplines, which rely on accurate wet refractivities or derived products like tropospheric signal delays.

10.5194/egusphere-egu2020-8469

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Citations (1)

An investigation of atmospheric temperature and pressure using an improved spatio-temporal Kriging model for sensing GNSS-derived precipitable water vapor

Spatial Statistics (2022)

Qimin He Kefei Zhang Suqin Wu Lian Dajun Li Li

Precipitable water

10.1016/j.spasta.2022.100664

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Citations (5)

A Two-Step Projected Iterative Algorithm for Tropospheric Water Vapor Tomography

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2022)

Shangyi Liu Kefei Zhang Suqin Wu Wenyuan Zhang Longjiang Li

The tropospheric tomography is an ill-posed inversion problem due to the sparsity of Global Navigation Satellite Systems (GNSS) stations and the limitation on the projection angles of GNSS signals, which in turn affects the stability and robustness of the tomographic solution. To address this, a new tomographic algorithm, named two-step projected iterative algorithm (TSPIA), is proposed. The wet refractivity (WR) field was constructed in two steps: first, an iterative preprocessing for the initial input values was performed, then its resultant solution was input into the projected iterative method, in which a hypothesis convex set was constructed to constrain the reconstruction based on the classical algebraic iterative reconstruction (AIR) methods. In addition, a two-dimensional normalized cumulative periodogram (2D-NCP) termination criterion was investigated since the traditional criteria for judging the convergence of iterations use pre-fixed empirical thresholds, which may lead to excessive iterations and need complicated work. The TSPIA was tested using GNSS data in Hong Kong over a wet period and a dry period. Statistical results showed that, compared to the classical AIR methods, the accuracy of the reconstructed WR field of the TSPIA were improved by about 10% and 15% when radiosonde and ECMWF data were used as the reference, respectively. Moreover, experiments for the proposed 2D-NCP criterion demonstrated noticeable computational efficiency. These results suggest that the new approaches proposed in this study can improve the performance of the iterative methods for GNSS tropospheric tomography.

Algebraic Reconstruction Technique

Robustness

10.1109/jstars.2022.3192437

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Citations (2)