An Analysis of Alternatives for the COSMIC-2 Constellation in the Context of Global Observing System Simulation Experiments

2020 ◽  
Vol 35 (1) ◽  
pp. 51-66 ◽  
Author(s):  
L. Cucurull ◽  
M. J. Mueller
Keyword(s):  
System Simulation ◽  
Three Dimensional ◽  
Lower Troposphere ◽  
Weather Forecast ◽  
Satellite System ◽  
Forecast Skill ◽  
Added Value ◽  
Simulation Experiments ◽  
Global Navigation Satellite ◽  
The Impact

Abstract Observing system simulation experiments (OSSEs) were conducted to evaluate the potential impact of the six Global Navigation Satellite System (GNSS) radio occultation (RO) receiver satellites in equatorial orbit from the initially proposed Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, known as COSMIC-2A. Furthermore, the added value of the high-inclination component of the proposed mission was investigated by considering a few alternative architecture designs, including the originally proposed polar constellation of six satellites (COSMIC-2B), a constellation with a reduced number of RO receiving satellites, and a constellation of six satellites but with fewer observations in the lower troposphere. The 2015 year version of the operational three-dimensional ensemble–variational data assimilation system of the National Centers for Environment Prediction (NCEP) was used to run the OSSEs. Observations were simulated and assimilated using the same methodology and their errors assumed uncorrelated. The largest benefit from the assimilation of COSMIC-2A, with denser equatorial coverage, was to improve tropical winds, and its impact was found to be overall neutral in the extratropics. When soundings from the high-inclination orbit were assimilated in addition to COSMIC-2A, positive benefits were found globally, confirming that a high-inclination orbit constellation of RO receiving satellites is necessary to improve weather forecast skill globally. The largest impact from reducing COSMIC-2B from six to four satellites was to slightly degrade weather forecast skill in the Northern Hemisphere extratropics. The impact of degrading COSMIC-2B to the COSMIC level of accuracy, in terms of penetration into the lower troposphere, was mostly neutral.

scholarly journals The Impact of Covariance Localization for Radar Data on EnKF Analyses of a Developing MCS: Observing System Simulation Experiments

2013 ◽  
Vol 141 (11) ◽  
pp. 3691-3709 ◽  
Author(s):  
Ryan A. Sobash ◽  
David J. Stensrud
Keyword(s):  
System Simulation ◽  
Three Dimensional ◽  
Radar Data ◽  
Convective System ◽  
State Variables ◽  
Simulation Experiments ◽  
Length Scales ◽  
Convective Scale ◽  
The Impact ◽  
Prior State

Abstract Several observing system simulation experiments (OSSEs) were performed to assess the impact of covariance localization of radar data on ensemble Kalman filter (EnKF) analyses of a developing convective system. Simulated Weather Surveillance Radar-1988 Doppler (WSR-88D) observations were extracted from a truth simulation and assimilated into experiments with localization cutoff choices of 6, 12, and 18 km in the horizontal and 3, 6, and 12 km in the vertical. Overall, increasing the horizontal localization and decreasing the vertical localization produced analyses with the smallest RMSE for most of the state variables. The convective mode of the analyzed system had an impact on the localization results. During cell mergers, larger horizontal localization improved the results. Prior state correlations between the observations and state variables were used to construct reverse cumulative density functions (RCDFs) to identify the correlation length scales for various observation-state pairs. The OSSE with the smallest RMSE employed localization cutoff values that were similar to the horizontal and vertical length scales of the prior state correlations, especially for observation-state correlations above 0.6. Vertical correlations were restricted to state points closer to the observations than in the horizontal, as determined by the RCDFs. Further, the microphysical state variables were correlated with the reflectivity observations on smaller scales than the three-dimensional wind field and radial velocity observations. The ramifications of these findings on localization choices in convective-scale EnKF experiments that assimilate radar data are discussed.

scholarly journals Evaluation on Nonholonomic Constraints and Rauch–Tung–Striebel Filter-Enhanced UWB/INS Integration

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Zhouzheng Gao ◽  
Lin Chen ◽  
Yu Min ◽  
Jie Lv ◽  
You Li
Keyword(s):  
Three Dimensional ◽  
Nonholonomic Constraints ◽  
Satellite System ◽  
Least Square ◽  
Precise Positioning ◽  
Global Navigation Satellite ◽  
Navigation Accuracy ◽  
The Impact ◽  
The Mathematical Model ◽  
Better Than

Precise and seamless positioning is becoming a basic requirement for the Internet of Things (IoT). However, there is a gap for precise positioning in Global Navigation Satellite System- (GNSS-) denied indoor areas. Thus, a multisensor integration system based on ultrawide-band (UWB), inertial navigation system (INS), nonholonomic constraints (NHCs), and Rauch–Tung–Striebel (RTS) smoother is proposed. In this system, the UWB performs as the major precise positioning system, while the INS bridges the UWB-degraded and UWB-denied periods. Meanwhile, the NHC restrains the drifts of INS, while the RTS smoother further upgrades the navigation accuracy. The contributions of this article are as follows. First, it presents the robust least square- (RLS-) based UWB positioning. The proposed method is effective in mitigating the impact of the effect of non-line-of-sight (NLOS), which is one of the most significant error sources for UWB positioning. Second, it derives the mathematical model of the UWB/INS/NHC/RTS integration, which is new compared to the existing approaches. Results illustrate that the proposed system can provide centimeter-level positioning accuracy, millimeter-level velocimetry accuracy, and accuracy of better than 0.05 and 0.15 degrees for horizontal and vertical attitude angles, respectively. Even in the scenario with short-term UWB outages (30 s), simulation results show that the three-dimensional position still can be better than 20 cm. Such accuracy values reach the state-of-the-art for indoor positioning using UWB and INS.

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 ARE MEASURED GROUND CONTROL POINTS STILL REQUIRED IN UAV BASED LARGE SCALE MAPPING? ASSESSING THE POSITIONAL ACCURACY OF AN RTK MULTI-ROTOR PLATFORM

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 507-514 ◽  
Author(s):  
L. Teppati Losè ◽  
F. Chiabrando ◽  
F. Giulio Tonolo
Keyword(s):  
Large Scale ◽  
Control Point ◽  
Satellite System ◽  
Added Value ◽  
Ground Control ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Aerial Vehicle ◽  
Global Navigation Satellite ◽  
The Impact

Abstract. The estimate of External Orientation (E.O.) parameters for a block of images is a crucial step in the photogrammetric pipeline and the most demanding in terms of required time and human effort, both during the fieldwork and post-processing phases. Different researchers developed strategies to minimize the impact of this phase. Despite the achievement of good results, it was not possible until now to completely cancel the effect of this step. However, the efforts of the researchers in these years have also been devoted to the implementation of direct photogrammetry strategies, in order to almost completely automate the E.O. of the photogrammetric block. These new approaches were made possible also thanks to the latest developments of commercial UAVs, especially in terms of the installed GPS/GNSS (Global Positioning System/Global Navigation Satellite System) hardware. The aim of this manuscript is to evaluate the different perspectives and issues connected with the deployment of a UAV (Unmanned Aerial Vehicle) equipped with a multi-frequency GPS/GNSS receiver. Starting from the considerations mentioned above and leveraging previous works based on a fixed-wing platform, the focus of this contribution is the assessment of the real performances of an RTK multi-rotor platform addressing several questions. Is it possible to generate added-value products with centimetre 3D accuracies without measuring any ground control point? Which are the operational requirements to be taken into account in the planning phase? Are consolidated UAV mapping operational workflows already available to enable a robust direct georeferencing approach?

scholarly journals An Observing System Simulation Experiment with a Constellation of Radio Occultation Satellites

2018 ◽  
Vol 146 (12) ◽  
pp. 4247-4259 ◽  
Author(s):  
L. Cucurull ◽  
R. Atlas ◽  
R. Li ◽  
M. J. Mueller ◽  
R. N. Hoffman
Keyword(s):  
Radio Occultation ◽  
Simulation Experiment ◽  
System Simulation ◽  
Weather Prediction ◽  
Satellite System ◽  
Prediction Systems ◽  
Global Navigation Satellite ◽  
The Tropics ◽  
Observing System Simulation Experiment ◽  
The Impact

Abstract Experiments with a global observing system simulation experiment (OSSE) system based on the recent 7-km-resolution NASA nature run (G5NR) were conducted to determine the potential value of proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellations in current operational numerical weather prediction systems. The RO observations were simulated with the geographic sampling expected from the original planned Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) system, with six equatorial (total of ~6000 soundings per day) and six polar (total of ~6000 soundings per day) receiver satellites. The experiments also accounted for the expected improved vertical coverage provided by the Jet Propulsion Laboratory RO receivers on board COSMIC-2. Except that RO observations were simulated and assimilated as refractivities, the 2015 version of the NCEP’s operational data assimilation system was used to run the OSSEs. The OSSEs quantified the impact of RO observations on global weather analyses and forecasts and the impact of adding explicit errors to the simulation of perfect RO profiles. The inclusion or exclusion of explicit errors had small, statistically insignificant impacts on results. The impact of RO observations was found to increase the length of the useful forecasts. In experiments with explicit errors, these increases were found to be 0.6 h in the Northern Hemisphere extratropics (a 0.4% improvement), 5.9 h in the Southern Hemisphere extratropics (a significant 4.0% improvement), and 12.1 h in the tropics (a very substantial 28.4% improvement).

scholarly journals Assimilation of Circumpolar Wind Vectors Derived from Highly Elliptical Orbit Imagery: Impact Assessment Based on Observing System Simulation Experiments

2013 ◽  
Vol 52 (8) ◽  
pp. 1891-1908 ◽  
Author(s):  
L. Garand ◽  
J. Feng ◽  
S. Heilliette ◽  
Y. Rochon ◽  
A. P. Trishchenko
Keyword(s):  
System Simulation ◽  
Weather Prediction ◽  
Elliptical Orbit ◽  
Added Value ◽  
The Arctic ◽  
Polar Regions ◽  
Simulation Experiments ◽  
The Real ◽  
Forecast Validation ◽  
The Impact

AbstractThere is a well-recognized spatiotemporal meteorological observation gap at latitudes higher than 55°, especially in the region 55°–70°. A possible solution to address this issue is a constellation of four satellites in a highly elliptical orbit (HEO), that is, two satellites for each polar region. An important satellite product to support weather prediction is atmospheric motion wind vectors (AMVs). This study uses observing system simulation experiments (OSSEs) to evaluate the benefit to forecasts resulting from the assimilation of HEO AMVs covering one or both polar regions. The OSSE employs the operational global data assimilation system of the Canadian Meteorological Center. HEO AMVs are assimilated north of 50°N and south of 50°S. From 2-month assimilation cycles, the study examines the following three issues: 1) the impact of AMV assimilation in the real system, and how this compares to the impact seen in the simulated system, 2) the added value of HEO AMVs in the Arctic on top of what is currently available, and 3) the relative impact of HEO AMVs in the Arctic and Antarctic in comparison with no AMVs. Although the simulated impact of currently available AMVs is somewhat higher than the real impact, a firm conclusion is that the added value of Arctic HEO AMVs is substantial, improving predictability at days 3–5 by a few hours in terms of 500-hPa geopotential height. The impact of HEO AMVs is relatively stronger in the Southern Hemisphere. Forecast validation of atmospheric profiles against the simulated “true” state and against analyses generated within the assimilation cycles yields very similar results beyond 48 h.

scholarly journals Measurement of the Sea Surface Height with Airborne GNSS Reflectometry and Delay Bias Calibration

2021 ◽  
Vol 13 (15) ◽  
pp. 3014
Author(s):  
Feng Wang ◽  
Dongkai Yang ◽  
Guodong Zhang ◽  
Jin Xing ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Arrival Time ◽  
Elevation Angle ◽  
Satellite System ◽  
Sea Surface Height ◽  
Antenna Pattern ◽  
Sea Surface ◽  
Observation Method ◽  
Global Navigation Satellite ◽  
The Impact

Sea surface height can be measured with the delay between reflected and direct global navigation satellite system (GNSS) signals. The arrival time of a feature point, such as the waveform peak, the peak of the derivative waveform, and the fraction of the peak waveform is not the true arrival time of the specular signal; there is a bias between them. This paper aims to analyze and calibrate the bias to improve the accuracy of sea surface height measured by using the reflected signals of GPS CA, Galileo E1b and BeiDou B1I. First, the influencing factors of the delay bias, including the elevation angle, receiver height, wind speed, pseudorandom noise (PRN) code of GPS CA, Galileo E1b and BeiDou B1I, and the down-looking antenna pattern are explored based on the Z-V model. The results show that (1) with increasing elevation angle, receiver height, and wind speed, the delay bias tends to decrease; (2) the impact of the PRN code is uncoupled from the elevation angle, receiver height, and wind speed, so the delay biases of Galileo E1b and BeiDou B1I can be derived from that of GPS CA by multiplication by the constants 0.32 and 0.54, respectively; and (3) the influence of the down-looking antenna pattern on the delay bias is lower than 1 m, which is less than that of other factors; hence, the effect of the down-looking antenna pattern is ignored in this paper. Second, an analytical model and a neural network are proposed based on the assumption that the influence of all factors on the delay bias are uncoupled and coupled, respectively, to calibrate the delay bias. The results of the simulation and experiment show that compared to the meter-level bias before the calibration, the calibrated bias decreases the decimeter level. Based on the fact that the specular points of several satellites are visible to the down-looking antenna, the multi-observation method is proposed to calibrate the bias for the case of unknown wind speed, and the same calibration results can be obtained when the proper combination of satellites is selected.

Impacts of Assimilating Measurements of Different State Variables with a Simulated Supercell Storm and Three-Dimensional Variational Method

2013 ◽  
Vol 141 (8) ◽  
pp. 2759-2777 ◽  
Author(s):  
Guoqing Ge ◽  
Jidong Gao ◽  
Ming Xue
Keyword(s):  
Potential Temperature ◽  
Three Dimensional ◽  
Horizontal Wind ◽  
Cold Pool ◽  
State Variables ◽  
Wind Fields ◽  
Simulation Experiments ◽  
Supercell Storm ◽  
The Impact ◽  
Analysis Quality

Abstract This paper investigates the impacts of assimilating measurements of different state variables, which can be potentially available from various observational platforms, on the cycled analysis and short-range forecast of supercell thunderstorms by performing a set of observing system simulation experiments (OSSEs) using a storm-scale three-dimensional variational data assimilation (3DVAR) method. The control experiments assimilate measurements every 5 min for 90 min. It is found that the assimilation of horizontal wind can reconstruct the storm structure rather accurately. The assimilation of vertical velocity , potential temperature , or water vapor can partially rebuild the thermodynamic and precipitation fields but poorly retrieves the wind fields. The assimilation of rainwater mixing ratio can build up the precipitation fields together with a reasonable cold pool but is unable to properly recover the wind fields. Overall, data have the greatest impact, while have the second largest impact. The impact of is the smallest. The impact of assimilation frequency is examined by comparing results using 1-, 5-, or 10-min assimilation intervals. When is assimilated every 5 or 10 min, the analysis quality can be further improved by the incorporation of additional types of observations. When are assimilated every minute, the benefit from additional types of observations is negligible, except for . It is also found that for , , and measurements, more frequent assimilation leads to more accurate analyses. For and , a 1-min assimilation interval does not produce a better analysis than a 5-min interval.

scholarly journals GNSS-Assisted Integrated Sensor Orientation with Sensor Pre-Calibration for Accurate Corridor Mapping

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2783 ◽  
Author(s):  
Yilin Zhou ◽  
Ewelina Rupnik ◽  
Paul-Henri Faure ◽  
Marc Pierrot-Deseilligny
Keyword(s):  
Satellite System ◽  
Sensor Calibration ◽  
Image Block ◽  
Integrated Sensor ◽  
Physical Constraints ◽  
Pose Determination ◽  
Sensor Orientation ◽  
Global Navigation Satellite ◽  
Oblique Images ◽  
The Impact

With the development of unmanned aerial vehicles (UAVs) and global navigation satellite system (GNSS), the accurate camera positions at exposure can be known and the GNSS-assisted bundle block adjustment (BBA) approach is possible for integrated sensor orientation (ISO). This study employed ISO approach for camera pose determination with the objective of investigating the impact of a good sensor pre-calibration on a poor acquisition geometry. Within the presented works, several flights were conducted on a dike by a small UAV embedded with a metric camera and a GNSS receiver. The multi-lever-arm estimation within the BBA procedure makes it possible to merge image blocks of different configurations such as nadir and oblique images without physical constraints on camera and GNSS antenna positions. The merged image block achieves a better accuracy and the sensor self-calibrated well. The issued sensor calibration is then applied to a less preferable acquisition configuration and the accuracy is significantly improved. For a corridor acquisition scene of about 600 m , a centimetric accuracy is reached with one GCP. With the provided sensor pre-calibration, an accuracy of 3.9 c m is achieved without any GCP.

scholarly journals Georeferencing of Laser Scanner-Based Kinematic Multi-Sensor Systems in the Context of Iterated Extended Kalman Filters Using Geometrical Constraints

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2280 ◽  
Author(s):  
Sören Vogel ◽  
Hamza Alkhatib ◽  
Johannes Bureick ◽  
Rozhin Moftizadeh ◽  
Ingo Neumann
Keyword(s):  
State Constraints ◽  
Laser Scanner ◽  
Measurement Data ◽  
Satellite System ◽  
Sensor Systems ◽  
Measurement Models ◽  
Non Linear ◽  
Geometrical Constraints ◽  
Global Navigation Satellite ◽  
The Impact

Georeferencing is an indispensable necessity regarding operating with kinematic multi-sensor systems (MSS) in various indoor and outdoor areas. Information from object space combined with various types of prior information (e.g., geometrical constraints) are beneficial especially in challenging environments where common solutions for pose estimation (e.g., global navigation satellite system or external tracking by a total station) are inapplicable, unreliable or inaccurate. Consequently, an iterated extended Kalman filter is used and a general georeferencing approach by means of recursive state estimation is introduced. This approach is open to several types of observation inputs and can deal with (non)linear systems and measurement models. The capability of using both explicit and implicit formulations of the relation between states and observations, and the consideration of (non)linear equality and inequality state constraints is a special feature. The framework presented is evaluated by an indoor kinematic MSS based on a terrestrial laser scanner. The focus here is on the impact of several different combinations of applied state constraints and the dependencies of two classes of inertial measurement units (IMU). The results presented are based on real measurement data combined with simulated IMU measurements.

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