scholarly journals Analysis of Satellite Radio Occultation Architecture and its Stakeholders

2021 ◽  
Author(s):  
Paul T. Grogan ◽  
I. Josue Tapia-Tamayo
Keyword(s):  
Global Navigation Satellite System ◽  
Radio Occultation ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Satellite System ◽  
Weather Data ◽  
Navigation Satellite ◽  
Functional Requirements ◽  
Global Navigation ◽  
Global Navigation Satellite

Global Navigation Satellite System Radio Occultation (GNSS-RO) is a technique that relies on the change of a signal transmitted from a Global Navigation Satellite System (GNSS) as it passes through the planet’s atmosphere. This technique is not only suitable to study weather forecasting or climate change, but also offers a low-cost application. This report aims to characterize and parametrize the system architecture of commercial companies pursuing the Commercial Weather Data Pilot (CWDP) contract by the National Oceanic and Atmospheric Administration (NOAA). The approach of the paper will start by explaining the Radio Occultation technique and its potential application to Numerical Weather Prediction (NWP). The paper then identifies the main stakeholders of radio occultation and NWP, and their needs. Some key functional requirements are pinpointed, and the challenges that some of these architectures must overcome is discussed.

scholarly journals A Severe Weather Quick Observing System Simulation Experiment (QuickOSSE) of Global Navigation Satellite System (GNSS) Radio Occultation (RO) Superconstellations

2017 ◽  
Vol 145 (2) ◽  
pp. 637-651 ◽  
Author(s):  
S. Mark Leidner ◽  
Thomas Nehrkorn ◽  
John Henderson ◽  
Marikate Mountain ◽  
Tom Yunck ◽  
...  
Keyword(s):  
Global Navigation Satellite System ◽  
Simulation Experiment ◽  
System Simulation ◽  
Weather Prediction ◽  
Satellite System ◽  
Navigation Satellite ◽  
Global Navigation ◽  
Global Navigation Satellite ◽  
Observing System Simulation Experiment ◽  
The Impact

Global Navigation Satellite System (GNSS) radio occultations (RO) over the last 10 years have proved to be a valuable and essentially unbiased data source for operational global numerical weather prediction. However, the existing sampling coverage is too sparse in both space and time to support forecasting of severe mesoscale weather. In this study, the case study or quick observing system simulation experiment (QuickOSSE) framework is used to quantify the impact of vastly increased numbers of GNSS RO profiles on mesoscale weather analysis and forecasting. The current study focuses on a severe convective weather event that produced both a tornado and flash flooding in Oklahoma on 31 May 2013. The WRF Model is used to compute a realistic and faithful depiction of reality. This 2-km “nature run” (NR) serves as the “truth” in this study. The NR is sampled by two proposed constellations of GNSS RO receivers that would produce 250 thousand and 2.5 million profiles per day globally. These data are then assimilated using WRF and a 24-member, 18-km-resolution, physics-based ensemble Kalman filter. The data assimilation is cycled hourly and makes use of a nonlocal, excess phase observation operator for RO data. The assimilation of greatly increased numbers of RO profiles produces improved analyses, particularly of the lower-tropospheric moisture fields. The forecast results suggest positive impacts on convective initiation. Additional experiments should be conducted for different weather scenarios and with improved OSSE systems.

scholarly journals Short vertical-wavelength gravity wave activities in the upper troposphere lower stratosphere observed with global navigation satellite system radio occultation under different QBO phases

2021 ◽  
Vol 893 (1) ◽  
pp. 012007
Author(s):  
Firas Rasyad ◽  
Tri Wahyu Hadi ◽  
Noersomadi
Keyword(s):  
Global Navigation Satellite System ◽  
Radio Occultation ◽  
Lower Stratosphere ◽  
Satellite System ◽  
Navigation Satellite ◽  
Vertical Wavelength ◽  
Upper Troposphere ◽  
Research Activities ◽  
Global Navigation ◽  
Global Navigation Satellite

Abstract Gravity Waves (GWs) are believed to play important role in the generation of the driving force of the stratospheric Quasi-Biennial Oscillation (QBO). Deep convection in the equatorial region can generate large amount of GW with short vertical wavelength (λz <1 km) but studies of these wave activities in the upper troposphere lower stratosphere (UTLS) region are still limited. Recent advances in Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieval techniques have made it possible to derive global temperature profile with vertical resolution of less than 1 km. In this research, activities of GW with λz from 0.5 to 3.5 km in the UTLS region of 20-27 km heights are identified by calculating the GW potential energy (E p). Correlation between GW activities and QBO phases is examined using 50 hPa zonal wind as the QBO index. The results show that during both easterly and westerly QBO phases, the GW E p value increases gradually with time and reaches its peak in the transition periods. This pattern is seen in E p with all vertical wavelengths between 0.5-3.5 km but the percentage value of E p for λz<1 km is higher during the transition from westerly to easterly QBO. The GW E p values exhibit downward propagation with the QBO phase but there are also discernible upward propagations of GW activities below 24 km height and intersect those two bring large changes in QBO phases. Additionally, higher percentage of E p with λz<1 km is also found to be associated with El Niño events.

scholarly journals Empirical Model for Total Precipitable Water Retrieval from Ground-based GNSS Observations in Thailand

2020 ◽  
Author(s):  
Weeranat Phasamak ◽  
Seubson Soisuvarn ◽  
Yuttapong Rangsanseri
Keyword(s):  
Real Time ◽  
Global Navigation Satellite System ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Satellite System ◽  
Navigation Satellite ◽  
Total Precipitable Water ◽  
Global Navigation ◽  
Global Navigation Satellite ◽  
Gnss Observations

Retrieval of Total Precipitable Water (TPW) using ground-based Global Navigation Satellite System (GNSS) observations is a challenging task due to its real‐time and high temporal resolution. In this paper, we present a method for establishing an analytic model for retrieving the total precipitable water (TPW) based on Global Navigation Satellite System (GNSS) observations over one-year period from 12 distributed stations across Thailand. The derived zenith total delay (ZTD) at all stations agrees well with the TPW data available from Global Data Assimilation System (GDAS) Numerical Weather Prediction (NWP) model. At first, a unique relationship between the ZTD and the TPW was established by taking into account of the variation of station altitudes. In addition, the bias correction technique using probability distribution function (PDF) matching was also applied to improve the final model. The inversion model of TPW from ZTD is then easily obtained using a numerical technique. The performance of our method has been successfully evaluated on an independent test data. This model can be useful in the further near real-time TPW measurements from widely available GNSS receivers.

scholarly journals OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fahad Alhomayani ◽  
Mohammad H. Mahoor
Keyword(s):  
Global Navigation Satellite System ◽  
Urban Areas ◽  
Satellite System ◽  
Reference Points ◽  
Navigation Satellite ◽  
Data Types ◽  
Entry Barrier ◽  
Promising Alternative ◽  
Global Navigation ◽  
Global Navigation Satellite

AbstractIn recent years, fingerprint-based positioning has gained researchers’ attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points’ number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

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