scholarly journals TWIGA project activities for the enhancement of heavy rainfall predictions in Africa: low-cost GNSS network deployment and NWP model parameterization.

Author(s):  
Alessandra Mascitelli ◽  
Agostino Niyonkuru Meroni ◽  
Stefano Barindelli ◽  
Marco Manzoni ◽  
Giulio Tagliaferro ◽  
...  

<p>One of the objectives of the H2020 project TWIGA - Transforming Weather Water data into value-added Information services for sustainable Growth in Africa - is the improvement of heavy rainfall prediction in Africa. In this area, the scarcity of data to support such predictions makes it fundamental to enhance the monitoring of atmospheric parameters.</p><p>In this project, GNSS observations and SAR images from Sentinel missions are used to produce water vapor products to be assimilated into Numerical Weather Prediction Models (NWPs).</p><p>GNSS observations, collected by ad-hoc networks of geodetic and low-cost stations, are processed to obtain near real-time (NRT) Zenith Total Delay (ZTD) time series, while Sentinel-1 SAR images are used to derive Atmospheric Phase Screens, APSs. The free and open source GNSS software goGPS, developed by the Politecnico di Milano spin-off Geomatics Research and Development (GReD), is used for the retrieval of ZTDs time series.</p><p>After proper calibration and validation procedures, the delay maps from SAR and the delay time series from GNSS will be finally assimilated into NWP models to improve the prediction of heavy rainfall.</p><p>The GNSS-related activities will be presented in terms of network deployment and processing settings evaluation. A network of 5 single-frequency low-cost GNSS stations was installed in Uganda, and a new network of dual-frequency low-cost stations is going to be installed in Kenya. To improve the outputs provided by these networks, preliminary tests on ionospheric delay corrections at various distances were performed. Different methods, focused on the reconstruction of a synthetic L2 observation for the single-frequency receivers, were employed and evaluated with the aim to define the optimal approach.</p><p>In order to demonstrate the capability to achieve GNSS NRT processing within TWIGA, an automated procedure was set up to estimate hourly ZTDs from two geodetic permanent stations located in South Africa (Cape Town and Southerland) and to upload them to the TWIGA project web portal.</p><p>Meanwhile, first sets of WRF NWP model parameterizations have been defined for both South Africa and Kenya. A cooperation has been established with the Kenya Meteorological Department on the exploitation of 3DVAR tool for water vapor data assimilation into WRF. Studies to define a strategy for ZTD maps retrieval from InSAR APS have been performed on Italian datasets and further investigations on TWIGA-collected African datasets will follow.</p><p> </p><p>  </p><p> </p>

2020 ◽  
Author(s):  
Robert Weber ◽  
Zohreh Adavi ◽  
Marcus Franz Glaner

<p>Water vapor is one of the most variable components in the Earth’s atmosphere, which has a significant role in the formation of clouds, rain and snow, air pollution and acid rain. Therefore, increasing the accuracy of estimated water vapor can lead to more accurate predictions of severe weather, upcoming storms, and reducing natural hazards. In recent years, GNSS has turned out to be a valuable tool for remotely sensing the atmosphere. GNSS tomography is one of the most valuable tools to reconstruct the Spatio-temporal structure of the troposphere. However, locating dual-frequency receivers with a sufficient spatial resolution for GNSS tomography of a few tens of kilometers is not economically feasible. Therefore, in this research, the feasibility of using single-frequency receivers in GNSS tomography as a possible alternative approach has been investigated. The accuracy of the reconstructed model of water-vapor distribution using low-cost receivers is verified using radiosonde measurements in the area of the EPOSA (Echtzeit Positionierung Austria) GNSS network, which is mostly located in the east part of Austria for the period DoYs 233-246 in 2019.</p>


2021 ◽  
Author(s):  
Agostino N Meroni ◽  
Alessandra Mascitelli ◽  
Stefano Barindelli ◽  
Naomi Petrushevsky ◽  
Marco Manzoni ◽  
...  

<p>The H2020 TWIGA - Transforming Weather Water data into value-added Information services for sustainable Growth in Africa - project aims to establish various services in sub-Saharan Africa for a better management of water resources by linking satellite, in-situ and modelled information. The delivery of timely and accurate weather forecasts is one of the envisaged services. GNSS (Global Navigation Satellite Systems) and SAR (Synthetic Aperture Radar) data provide information on the atmospheric water vapor content, which can be assimilated into Numerical Weather Prediction (NWP) models. The assimilation enables these models to exploit observations for a better simulation of the atmospheric dynamics and the subsequent improvement of the forecasts. The activities related to GNSS, SAR and NWP integration are presented in what follows.</p><p>As for GNSS, the modeling of ionospheric errors was investigated for the recently deployed single-frequency low-cost sensors in Uganda. A quality assessment of three different algorithms (ANGBAS, SEID, goSEID) for synthetic L2 observations reconstruction, evaluating the impact on the Zenith Total Delay (ZTD) estimation, was carried out. The three methods show good performances with an overall accuracy ranging between 0.1 and 1 cm when the corrections are computed from geodetic stations at distances up to 65 km from the target receiver. Additionally, an operational system for the retrieval of near real-time GNSS ZTD was implemented. It shows a precision lower than 1 cm, compatible with the target requirements for the assimilation into NWP models.</p><p>GNSS is also used to perform the orbital corrections of the SAR products, reducing the large-scale errors like phase trends and biases. The merging of multiple Sentinel-1 frames to cover extended areas requires large computational resources. Work is ongoing to deal with the computationally intensive unwrapping of large interferograms. Moreover, the removal of ionospheric delays, which are not related to the water vapor content, is under development. </p><p>Concerning NWP, the Weather Research and Forecasting (WRF) model has been used, at cloud-resolving scales, to test the sensitivity of the simulations of three heavy rainfall events (in Uganda and in South Africa) to the Planetary Boundary Layer (PBL) and the microphysical numerical schemes. Non-local PBL schemes are found to outperform the local PBL scheme considered in the study, because they better describe the vertical atmospheric mixing. In parallel, by exploiting a multiphysics set of numerical simulations in West Africa, it was found that the spatial variability of the surface heat fluxes significantly affects the lower atmospheric dynamics. This happens through a differential heating of the atmosphere across soil moisture gradients. Experiments on the assimilation of water vapor data are ongoing.</p>


2018 ◽  
Vol 10 (9) ◽  
pp. 1493 ◽  
Author(s):  
Andreas Krietemeyer ◽  
Marie-claire ten Veldhuis ◽  
Hans van der Marel ◽  
Eugenio Realini ◽  
Nick van de Giesen

Dual-frequency Global Navigation Satellite Systems (GNSSs) enable the estimation of Zenith Tropospheric Delay (ZTD) which can be converted to Precipitable Water Vapor (PWV). The density of existing GNSS monitoring networks is insufficient to capture small-scale water vapor variations that are especially important for extreme weather forecasting. A densification with geodetic-grade dual-frequency receivers is not economically feasible. Cost-efficient single-frequency receivers offer a possible alternative. This paper studies the feasibility of using low-cost receivers to increase the density of GNSS networks for retrieval of PWV. We processed one year of GNSS data from an IGS station and two co-located single-frequency stations. Additionally, in another experiment, the Radio Frequency (RF) signal from a geodetic-grade dual-frequency antenna was split to a geodetic receiver and two low-cost receivers. To process the single-frequency observations in Precise Point Positioning (PPP) mode, we apply the Satellite-specific Epoch-differenced Ionospheric Delay (SEID) model using two different reference network configurations of 50–80 km and 200–300 km mean station distances, respectively. Our research setup can distinguish between the antenna, ionospheric interpolation, and software-related impacts on the quality of PWV retrievals. The study shows that single-frequency GNSS receivers can achieve a quality similar to that of geodetic receivers in terms of RMSE for ZTD estimations. We demonstrate that modeling of the ionosphere and the antenna type are the main sources influencing the ZTD precision.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4261
Author(s):  
Dong-Hyo Sohn ◽  
Byung-Kyu Choi ◽  
Yosup Park ◽  
Yoon Chil Kim ◽  
Bonhwa Ku

We estimate precipitable water vapor (PWV) from data collected by the low-cost Global Navigation Satellite System (GNSS) receiver at a vessel. The dual-frequency GNSS receiver that the vessel ISABU is equipped with that is operated by the Korea Institute of Ocean Science and Technology. The ISABU served in the Pacific Ocean for scientific research during a period from August 30 to September 21, 2018. It also performs radiosonde observations to obtain a vertical profile of troposphere on the vessel’s path. The GNSS-derived PWV is compared to radiosonde observations and the Atmospheric Infrared Sounder (AIRS) on NASA’s Aqua satellite output. A bias and root-mean-square (RMS) error between shipborne GNSS-PWV and radiosonde-PWV were −1.48 and 5.22 mm, respectively. When compared to the ground GNSS-PWV, shipborne GNSS-PWV has a relatively large RMS error in comparison with radiosonde-PWV. However, the GNSS observations on the vessel are still in good agreement with radiosonde observations. On the other hand, the GNSS-PWV is not well linearly correlated with AIRS-PWV. The RMS error between the two observations was approximately 8.97 mm. In addition, we showed that the vessel on the sea surface has significantly larger carrier phase multipath error compared to the ground-based GNSS observations. This also can result in reducing the accuracy of shipborne GNSS-PWV. However, we suggest that the shipborne GNSS has sufficient potential to derive PWV with the kinematic precise point positioning (PPP) solution on the vessel.


Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5536 ◽  
Author(s):  
Simone Rover ◽  
Alfonso Vitti

Snowpack is an important fresh water storage; the retrieval of snow water equivalents from satellite data permits to estimate potentially available water amounts which is an essential parameter in water management plans running in several application fields (e.g., basic needs, hydroelectric, agriculture, hazard and risk monitoring, climate change studies). The possibility to assess snowpack height from Global Navigation Satellite Systems (GNSS) observations by means of the GNSS reflectometry technique (GNSS-R) has been shown by several studies. However, in general, studies are being conducted using observations collected by continuously operating reference stations (CORS) built for geodetic purposes and equipped with geodetic-grade instruments. Moreover, CORS are located on sites selected according to criteria different from those more suitable for snowpack studies. In this work, beside an overview of key elements of GNSS reflectometry, single-frequency GNSS observations collected by u-blox M8T GNSS receivers and patch antennas from u-blox and Tallysman have been considered for the determination of antenna height from the snowpack surface on a selected test site. Results demonstrate the feasibility of GNSS-R even with non-geodetic-grade instruments, opening the way towards diffuse GNSS-R targeted applications.


2011 ◽  
Vol 64 (S1) ◽  
pp. S180-S191 ◽  
Author(s):  
Baocheng Zhang ◽  
Peter J.G. Teunissen ◽  
Dennis Odijk

In this contribution, a novel un-differenced (UD) (PPP-RTK) concept, i.e. a synthesis of Precise Point Positioning and Network-based Real-Time Kinematic concept, is introduced. In the first step of our PPP-RTK approach, the UD GNSS observations from a regional reference network are processed based upon re-parameterised observation equations, corrections for satellite clocks, phase biases and (interpolated) atmospheric delays are calculated and provided to users. In the second step, these network-based corrections are used at the user site to restore the integer nature of his UD phase ambiguities, which makes rapid and high accuracy user positioning possible. The proposed PPP-RTK approach was tested using two GPS CORS networks with inter-station distances ranging from 60 to 100 km. The first test network is the northern China CORS network and the second is the Australian Perth CORS network. In the test of the first network, a dual-frequency PPP-RTK user receiver was used, while in the test of the second network, a low-cost, single-frequency PPP-RTK user receiver was used. The performance of fast ambiguity resolution and the high accuracy positioning of the PPP-RTK results are demonstrated.


2020 ◽  
Vol 55 (2) ◽  
pp. 61-76
Author(s):  
Ashraf Farah

AbstractThe GNSS observations suffer from different types of errors that could affect the achieved positioning accuracy based on the receiver type used. Single-frequency receivers are widely used worldwide because of its low cost. The ionospheric delay considers the most challenging error for single-frequency GNSS observations. All satellite navigation systems, except GLONASS, are advising their users to correct for the ionospheric delay using a certain model. Those models’ coefficients are sent to users in the system’s navigation message. These models are different in their accuracy and behavior based on its foundation theory as well as the updating rate of their coefficients. The GPS uses Klobuchar model for mitigating the ionospheric delay. BeiDou system (BDS-2) adopts a slightly modified Klobuchar model that resembles GPS ICA (Ionospheric Correction Algorithm) with eight correction parameters but is formulated in a geographic coordinate system with different coefficients in origin and updating rate. Galileo system uses a different model (NeQuick model). This article investigates the behavior of the three models in correcting the ionospheric delay for three stations at different latitudes during 3 months of different states of ionospheric activity, comparing with International GNSS Service-Global Ionospheric Maps (IGS-GIMs). It is advised from this research’s outputs to use the GPS model for mitigating the ionospheric delay in low-latitude regions during the state of low-and medium-activity ionosphere. It is advised to use the BeiDou model for mitigating the ionospheric delay in mid-latitude regions during different states of ionospheric activity. It is advised to use the Galileo model for mitigating the ionospheric delay in high-latitude regions during different states of ionospheric activity. Also, the Galileo model is recommended for mitigating the ionospheric delay for low-latitude regions during the state of high-activity ionosphere.


Author(s):  
Balazs Lupsic ◽  
Bence Takacs

AbstractThe number of devices equipped with global satellite positioning has exceeded seven billion recently. There are a wide variety of receivers regarding their accuracy and reliability. Low cost, multi-frequency units have been released on the market latterly; however, the number of single-frequency receivers is still significant. Since their measurements are influenced by ionospheric delay, accurate ionosphere models are of utmost importance to reduce the effect. This paper summarizes how Gauss process regression (GPR) can be applied to derive near real-time regional ionosphere models using raw Global Navigation Satellite System (GNSS) observations of permanent stations. While Gauss process is widely used in machine learning, GPR is a nonparametric, Bayesian approach to regression. GPR has several benefits for ionosphere monitoring since it is quite robust and efficient to derive a grid model from data available in irregular set of ionospheric pierce points. The corresponding instrumental delays are estimated by a parallel Kalman filter. The presented algorithm can be applied near real-time, however the results are offline calculated and are compared to two high quality TEC map products. Based on the analysis, the accuracy of the GPR modell is in 2 TECu range. The developed methods could be efficiently applied in the field of autonomous vehicle navigation with meeting both accuracy and integrity requirements.


GPS Solutions ◽  
2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Zohreh Adavi ◽  
Robert Weber ◽  
Marcus Franz Glaner

AbstractWater vapor is one of the most variable components in the earth's atmosphere and has a significant role in forming clouds, rain and snow, air pollution, and acid rain. Therefore, increasing the accuracy of estimated water vapor can lead to more accurate predictions of severe weather, upcoming storms, and natural hazards. In recent years, GNSS has turned out to be a valuable tool for remotely sensing the atmosphere. In this context, GNSS tomography evolved to an extremely promising technique to reconstruct the spatiotemporal structure of the troposphere. However, locating dual-frequency (DF) receivers with a spatial resolution of a few tens of kilometers sufficient for GNSS tomography is not economically feasible. Therefore, in this research, the feasibility of using single-frequency (SF) observations in GNSS tomography as an alternative approach has been investigated. The algebraic reconstruction technique (ART) and the total variation (TV) method are examined to reconstruct a regularized solution. The accuracy of the reconstructed water vapor distribution model using low-cost receivers is verified by radiosonde measurements in the area of the EPOSA (Echtzeit Positionierung Austria) GNSS network, which is mostly located in the east part of Austria for the period DoY 232–245, 2019. The results indicate that irrespective of the investigated ART and TV techniques, the quality of the reconstructed wet refractivity field is comparable for both SF and DF schemes. However, in the SF scheme the MAE with respect to the radiosonde measurements for ART + NWM and ART + TV can reach up to 10 ppm during noontime. Despite that, all statistical results demonstrate the degradation of the retrieved wet refractivity field of only 10–40% when applying the SF scheme in the presence of the initial guess.


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