Radio occultation atmospheric profiling from the Spire nanosatellite constellation and its impact on weather forecasting

Abstract As of May 2007, the National Centers for Environmental Prediction (NCEP) implemented a new Global Data Assimilation System. This system incorporated the assimilation of global positioning system (GPS) radio occultation (RO) profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission, which was launched in April 2006. Since then, this new type of observation has been shown to provide additional information on the thermodynamic state of the atmosphere, resulting in a significant increase in the model skill. Recent updates of the analysis and modeling codes have required a revision of the algorithm that assimilates GPS RO data. In addition, some modifications in the processing of the observations have further enhanced the need for a revisiting of the assimilation code. Better characterizations of the quality control procedures, observation error structure, and forward modeling for the GPS RO observations are described. The updated system significantly improves the data usage, in particular in the tropics. Different sets of the atmospheric refractive indices are also evaluated in this study. The model performance is proven to be quite sensitive to the chosen coefficients and a reevaluation of these constants is recommended within the GPS community. The new assimilation configuration results in an improvement in the anomaly correlation scores for the Southern Hemisphere extratropics (∼4.5 h for the 500-mb geopotential heights at day 7) and a reduction of the high- and low-level tropical wind errors. Overall, the benefits of using COSMIC on top of all the other observations used in the operational system are still very significant. The loss in model skill when COSMIC is removed from the observing system is remarkable at day 4 (∼8 h) and steadily increases beyond 12 h with the extended forecast range.

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Improved impacts in observing system simulation experiments of radio occultation observations as a result of model and data assimilation changes

Monthly Weather Review ◽

10.1175/mwr-d-20-0174.1 ◽

2020 ◽

Author(s):

L. CUCURULL ◽

S. P. F. CASEY

Keyword(s):

Data Assimilation ◽

Radio Occultation ◽

Weather Forecasting ◽

Positive Impact ◽

System Simulation ◽

Weather Prediction ◽

Wind Fields ◽

Simulation Experiments ◽

The Impact ◽

Forward Operator

AbstractAs global data assimilation systems continue to evolve, Observing System Simulation Experiments (OSSEs) need to be updated to accurately quantify the impact of proposed observing technologies in weather forecasting. Earlier OSSEs with radio occultation (RO) observations have been updated and the impact of the originally proposed Constellation Observing Satellites for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, with a high-inclination and low-inclination component, has been investigated by using the operational data assimilation system at NOAA and a 1-dimensional bending angle RO forward operator. It is found that the impact of the low-inclination component of the originally planned COSMIC-2 mission (now officially named COSMIC-2) has significantly increased as compared to earlier studies, and significant positive impact is now found globally in terms of mass and wind fields. These are encouraging results as COSMIC-2 was successfully launched in June 2019 and data have been recently released to operational weather centers. Earlier findings remain valid indicating that globally distributed RO observations are more important to improve weather prediction globally than a denser sampling of the tropical latitudes. Overall, the benefits reported here from assimilating RO soundings are much more significant than the impacts found in previous OSSEs. This is largely attributed to changes in the data assimilation and forecast system and less to the more advanced 1-dimensional forward operator chosen for the assimilation of RO observations.

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Assessment of Radio Occultation Observations from the COSMIC-2 Mission with a Simplified Observing System Simulation Experiment Configuration

Monthly Weather Review ◽

10.1175/mwr-d-16-0475.1 ◽

2017 ◽

Vol 145 (9) ◽

pp. 3581-3597 ◽

Cited By ~ 9

Author(s):

L. Cucurull ◽

R. Li ◽

T. R. Peevey

Keyword(s):

Radio Occultation ◽

Weather Forecasting ◽

System Simulation ◽

Weather Prediction ◽

Forecast Model ◽

Forecast Skill ◽

Weather Forecasts ◽

Global Coverage ◽

Prediction Systems ◽

Observing System Simulation Experiment

The mainstay of the global radio occultation (RO) system, the COSMIC constellation of six satellites launched in April 2006, is already past the end of its nominal lifetime and the number of soundings is rapidly declining because the constellation is degrading. For about the last decade, COSMIC profiles have been collected and their retrievals assimilated in numerical weather prediction systems to improve operational weather forecasts. The success of RO in increasing forecast skill and COSMIC’s aging constellation have motivated planning for the COSMIC-2 mission, a 12-satellite constellation to be deployed in two launches. The first six satellites (COSMIC-2A) are expected to be deployed in December 2017 in a low-inclination orbit for dense equatorial coverage, while the second six (COSMIC-2B) are expected to be launched later in a high-inclination orbit for global coverage. To evaluate the potential benefits from COSMIC-2, an earlier version of the NCEP’s operational forecast model and data assimilation system is used to conduct a series of observing system simulation experiments with simulated soundings from the COSMIC-2 mission. In agreement with earlier studies using real RO observations, the benefits from assimilating COSMIC-2 observations are found to be most significant in the Southern Hemisphere. No or very little gain in forecast skill is found by adding COSMIC-2A to COSMIC-2B, making the launch of COSMIC-2B more important for terrestrial global weather forecasting than that of COSMIC-2A. Furthermore, results suggest that further improvement in forecast skill might better be obtained with the addition of more RO observations with global coverage and other types of observations.

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Assimilation of GNSS tomography products into WRF using radio occultation data assimilation operator

10.5194/amt-2018-419 ◽

2019 ◽

Cited By ~ 1

Author(s):

Natalia Hanna ◽

Estera Trzcina ◽

Gregor Möller ◽

Witold Rohm ◽

Robert Weber

Keyword(s):

Standard Deviation ◽

Data Assimilation ◽

Radio Occultation ◽

Weather Forecasting ◽

Heavy Precipitation ◽

Horizontal Resolution ◽

Global Navigation Satellite Systems ◽

Total Delay ◽

Water Vapour Content ◽

Precipitation Events

Abstract. From Global Navigation Satellite Systems (GNSS) signals, accurate and high-frequency atmospheric parameters can be determined in all-weather conditions. GNSS tomography is a novel technique that takes advantage of these parameters, especially of slant troposphere observations between GNSS receivers and satellites, traces these signals through a 3D grid of voxels and estimates by an inversion process the refractivity of the water vapour content within each voxel. In the last years, the GNSS tomography development focused on numerical methods to stabilize the solution, which has been achieved to a great extent. Currently, we are facing new challenges and possibilities in the application of GNSS tomography in numerical weather forecasting – the main research objective of this paper. In the first instance, refractivity fields were estimated using two different GNSS tomography models (TUW, WUELS), which cover the area of Central Europe during the period of 29 May–14 June 2013, when heavy precipitation events were observed. For both models, Slant Wet Delays (SWD) were calculated based on estimates of Zenith Total Delay (ZTD) and horizontal gradients, provided for 72 GNSS sites by Geodetic Observatory Pecny (GOP). In total, three sets of SWD observations were tested (set0 without compensation for hydrostatic anisotropic effects, set1 with compensation of this effect, set2 cleaned by wet delays outside the inner voxel model). The GNSS tomography outputs have been assimilated into the nested (12- and 36-km horizontal resolution) Weather Research and Forecasting (WRF) model, using its three-dimensional variational data assimilation (WRFDA 3DVar) system, in particular its radio occultation observations operator (GPSREF). As only total refractivity is assimilated in GPSREF, it was calculated as the sum of the hydrostatic part derived from the ALADIN-CZ model and the wet part from the GNSS tomography. We compared the results of the GNSS tomography data assimilation to the radiosonde (RS) observations. The validation shows the improvement in the weather forecasting of relative humidity (bias, standard deviation) and temperature (standard deviation) during heavy precipitation events. Future improvements to the assimilation method are also discussed.

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Assimilation of GNSS tomography products into the Weather Research and Forecasting model using radio occultation data assimilation operator

Atmospheric Measurement Techniques ◽

10.5194/amt-12-4829-2019 ◽

2019 ◽

Vol 12 (9) ◽

pp. 4829-4848 ◽

Cited By ~ 2

Author(s):

Natalia Hanna ◽

Estera Trzcina ◽

Gregor Möller ◽

Witold Rohm ◽

Robert Weber

Keyword(s):

Standard Deviation ◽

Data Assimilation ◽

Radio Occultation ◽

Weather Forecasting ◽

Heavy Precipitation ◽

Global Navigation Satellite Systems ◽

Weather Research And Forecasting ◽

The Impact ◽

Precipitation Events ◽

Weather Research

Abstract. From Global Navigation Satellite Systems (GNSS) signals, accurate and high-frequency atmospheric parameters can be determined in all-weather conditions. GNSS tomography is a technique that takes advantage of these parameters, especially of slant troposphere observations between GNSS receivers and satellites, traces these signals through a 3-D grid of voxels, and estimates by an inversion process the refractivity of the water vapour content within each voxel. In the last years, the GNSS tomography development focused on numerical methods to stabilize the solution, which has been achieved to a great extent. Currently, we are facing new challenges and possibilities in the application of GNSS tomography in numerical weather forecasting, the main research objective of this paper. In the first instance, refractivity fields were estimated using two different GNSS tomography models (TUW, WUELS), which cover the area of central Europe during the period of 29 May–14 June 2013, when heavy-precipitation events were observed. For both models, slant wet delays (SWDs) were calculated based on estimates of zenith total delay (ZTD) and horizontal gradients, provided for 88 GNSS sites by Geodetic Observatory Pecny (GOP). In total, three sets of SWD observations were tested (set0 without compensation for hydrostatic anisotropic effects, set1 with compensation of this effect, set2 cleaned by wet delays outside the inner voxel model), in order to assess the impact of different factors on the tomographic solution. The GNSS tomography outputs have been assimilated into the nested (12 and 36 km horizontal resolution) Weather Research and Forecasting (WRF) model, using its three-dimensional variational data assimilation (WRFDA 3D-Var) system, in particular, its radio occultation observation operator (GPSREF). As only total refractivity is assimilated in GPSREF, it was calculated as the sum of the hydrostatic part derived from the ALADIN-CZ model and the wet part from the GNSS tomography. We compared the results of the GNSS tomography data assimilation to the radiosonde (RS) observations. The validation shows the improvement in the weather forecasting of relative humidity (bias, standard deviation) and temperature (standard deviation) during heavy-precipitation events. Future improvements to the assimilation method are also discussed.

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Analysis of Satellite Radio Occultation Architecture and its Stakeholders

10.31224/osf.io/zeqj9 ◽

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.

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Seeking Optimal GNSS Radio Occultation Constellations Using Evolutionary Algorithms

Remote Sensing ◽

10.3390/rs11050571 ◽

2019 ◽

Vol 11 (5) ◽

pp. 571 ◽

Cited By ~ 4

Author(s):

Xiaohua Xu ◽

Yi Han ◽

Jia Luo ◽

Jens Wickert ◽

Milad Asgarimehr

Keyword(s):

Evolutionary Algorithms ◽

Radio Occultation ◽

Weather Forecasting ◽

Fitness Function ◽

Sampling Rate ◽

Pso Algorithm ◽

Low Earth Orbit ◽

Temporal Sampling ◽

Leo Satellites ◽

Lattice Flower Constellation

Given the great achievements of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission in providing huge amount of GPS radio occultation (RO) data for weather forecasting, climate research, and ionosphere monitoring, further Global Navigation Satellite System (GNSS) RO missions are being followingly planned. Higher spatial and also temporal sampling rates of RO observations, achievable with higher number of GNSS/receiver satellites or optimization of the Low Earth Orbit (LEO) constellation, are being studied by high number of researches. The objective of this study is to design GNSS RO missions which provide multi-GNSS RO events (ROEs) with the optimal performance over the globe. The navigation signals from GPS, GLONASS, BDS, Galileo, and QZSS are exploited and two constellation patterns, the 2D-lattice flower constellation (2D-LFC) and the 3D-lattice flower constellation (3D-LFC), are used to develop the LEO constellations. To be more specific, two evolutionary algorithms, including the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm, are used for searching the optimal constellation parameters. The fitness function of the evolutionary algorithms takes into account the spatio-temporal sampling rate. The optimal RO constellations are obtained for which consisting of 6–12 LEO satellites. The optimality of the LEO constellations is evaluated in terms of the number of global ROEs observed during 24 h and the coefficient value of variation (COV) representing the uniformity of the point-to-point distributions of ROEs. It is found that for a certain number of LEO satellites, the PSO algorithm generally performs better than the GA, and the optimal 2D-LFC generally outperforms the optimal 3D-LFC with respect to the uniformity of the spatial and temporal distributions of ROEs.

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The COSMIC/FORMOSAT-3 Radio Occultation Mission after 12 Years: Accomplishments, Remaining Challenges, and Potential Impacts of COSMIC-2

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-18-0290.1 ◽

2020 ◽

Vol 101 (7) ◽

pp. E1107-E1136 ◽

Cited By ~ 12

Author(s):

Shu-peng Ho ◽

Richard A. Anthes ◽

Chi O. Ao ◽

Sean Healy ◽

Andras Horanyi ◽

...

Keyword(s):

Radio Occultation ◽

Weather Forecasting ◽

Signal To Noise Ratio ◽

Beam Steering ◽

Lower Troposphere ◽

Satellite Mission ◽

Remote Sensing Technique ◽

Global Positioning ◽

Vertical Variations ◽

The Tropics

Abstract Launched in 2006, the Formosa Satellite Mission 3–Constellation Observing System for Meteorology, Ionosphere and Climate (FORMOSAT-3/COSMIC) was the first constellation of microsatellites carrying global positioning system (GPS) radio occultation (RO) receivers. Radio occultation is an active remote sensing technique that provides valuable information on the vertical variations of electron density in the ionosphere, and temperature, pressure, and water vapor in the stratosphere and troposphere. COSMIC has demonstrated the great value of RO data in ionosphere, climate, and meteorological research and operational weather forecasting. However, there are still challenges using RO data, particularly in the moist lower troposphere and upper stratosphere. A COSMIC follow-on constellation, COSMIC-2, was launched into equatorial orbit in 2019. With increased signal-to-noise ratio (SNR) from improved receivers and digital beam steering antennas, COSMIC-2 will produce at least 5,000 high-quality RO profiles daily in the tropics and subtropics. In this paper, we summarize 1) recent (since 2011 when the last review was published) contributions of COSMIC and other RO observations to weather, climate, and space weather science; 2) the remaining challenges in RO applications; and 3) potential contributions to research and operations of COSMIC-2.

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