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The Impact of Assimilating Large Volumes of GNSS Radio Occultation Observations from Spire’s Commercial Constellation into NASA’s GEOS

The upcoming retrospective analysis for the 21st century (R21C) reanalysis product from NASA will include the full dataset of GNSS Radio Occultation (RO) observations collected by Spire with their constellation of smallsats. The Spire RO dataset, which was purchased by NASA for its Commercial Smallsat Data Acquisition (CSDA) archive, has global coverage and increases in number from approximately 6 thousand RO profiles per day during 2019 to approximately 20 thousand in 2022-2023. This more than doubles the volume of RO profiles from all other routinely assimilated RO missions combined during 2022. The increase in the number of RO profiles available is particularly important in the extratropics as the next largest RO constellation, the state-of-the-science Formosa Satellite Mission 7 (FORMOSAT-7)/Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) mission (hereafter COSMIC-2), is focused on the Tropics and only provides approximately 4 thousand RO profiles per day. The large number of observations in the Spire RO dataset have great potential to improve analyses and forecasts of the Earth’s atmosphere produced by numerical weather prediction systems. Their impact is assessed through numerical experiments using NASA’s Global Earth Observing System (GEOS) Atmospheric Data Assimilation System (ADAS) with and without the observations from the COSMIC-2 mission. The ability of the Spire RO observations to make up for the omission of the RO observations from COSMIC-2 is directly assessed over the tropics and the impact of Spire over the extratropics is compared to that of the available RO missions that sample over this region. Finally, the quality of the Spire RO observations is compared to that of the routinely assimilated RO missions using Forecast Sensitivity-based Observation Impact (FSOI).

Michael J. Murphy

Impacts from Assimilating Large Volumes of GNSS Radio Occultation (RO) Observations during ROMEX in NASA’s Global Earth Observing System

The GNSS Radio Occultation (RO) Modeling Experiment (ROMEX) seeks to quantify the benefit of the increasing quantity of RO observations available for use in operational numerical weather prediction (NWP) systems and products. ROMEX includes participation from multiple operational NWP centers and NWP models, among them are NASA’s Global Earth Observing System (GEOS) model produced and run at the Global Modeling and Assimilation Office (GMAO). The design of the numerical experiments core to ROMEX include: 1) a control model run that includes all the RO observations currently used operationally with the sole exception of those from commercial sources and 2) a ROMEX model run that adds to the control over 25 thousand additional RO profiles per day from commercial RO providers, with both experiments run over the three-month period of September through November 2022. The ROMEX model run greatly augments the relatively small subset of the currently available commercial RO profiles which have been purchased for routine use in operational NWP by the various NWP centers. While this smaller subset of commercial RO profiles currently used in operations has been shown to have a positive impact on NWP forecasts, the additional impact from the ROMEX RO dataset has yet to be determined and is the focus of ROMEX. Results from GEOS are presented, including the impact on both analyses and forecasts over the study period and statistics using the forecast sensitivity-based observation impact (FSOI) method. The impact from varying the method of quality control and specifying the observation uncertainty for RO observations within the GEOS data assimilation system is also examined.

Michael J Murphy

Atmospheric and ocean sensing with GNSS

The 1980s and 1990s saw the Global Positioning System (GPS) transform space geodesy from an elite national enterprise to one open to the individual researcher. By adapting the tools from that endeavor we are learning to probe the atmosphere and the ocean surface in novel ways, including ground-based sensing of atmospheric moisture; space-based profiling of atmospheric refractivity by active limb sounding; and global ocean altimetry with reflected signals.

reflectometry

Global navigation satellite sounding of the atmosphere and GNSS altimetry : prospects for geosciences

The vast illuminating power of the Global Positioning System (GPS), which transformed space geodesy in the 199Os, is now serving to probe the earth's fluid envelope in unique ways. Three distinct techniques have emerged: ground-based sensing of the integrated atmospheric moisture; space-based profiling of atmospheric refractivity, pressure, temperature, moisture, and other properties by active limb sounding; and surface (ocean and ice) altimetry and scatterometry with reflected signals detected from space. Ground-based GPS moisture sensing is already in provisional use for numerical weather prediction. Limb sounding, while less mature, offers a bevy of attractions, including high accuracy, stability, and vertical resolution; all-weather operation; and exceptionally low cost. GPS bistatic radar, r 'reflectometry,' is the least advanced but shows promise for a number of niche applications.

occultation

The New Tropospheric Product of the International GNSS Service

We compare this new approach for generating the IGS tropospheric products with the previous approach, which was based on explicit combination of total zenith delay contributions from the IGS ACs. The new approach enables the IGS to rapidly generate highly accurate and highly reliable total zenith delay time series for many hundreds of sites, thus increasing the utility of the products to weather modelers, climatologists, and GPS analysts. In this paper we describe this new method, and discuss issues of accuracy, quality control, utility of the new products and assess its benefits.

International GNSS Service (IGS)

GNSS to the Moon

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GPS

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS

A High-Performance Computing GNSS-aware Path Planning Algorithm for Safe Urban Flight Operations

The emergence and development of advanced technologies and vehicle types have created a growing demand for new forms of flight operations. These new and increasingly complex operational paradigms, such as Advanced and Urban Air Mobility (AAM/UAM), present regulatory authorities and the aviation community with several design-and-implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is to develop protocols that can integrate these operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive, autonomous, risk mitigation capability becomes critical to meet this challenge. This paper proposes and evaluates a computationally-efficient path planning approach to perform pre-flight planning and autonomous in-flight re-routing to minimize exposures to selected hazards. In our evaluation, hazards associated with degraded and missing critical GPS navigation data are considered. In this paper, we first present a high-performance computing path planning approach based on an adapted Bellman-Ford algorithm, developed in the CUDA programming language. Using the adapted path planning algorithm, we test this algorithm when encountering issues with GPS quality, and deliver an implementation that can produce flight paths that minimize exposure to risks, while maintaining a low computational burden. In our evaluation, the computation of periodic and aperiodic path updates are evaluated, prioritizing specific events as triggers for updates, based on changes to satellite availability. These critical events can lead to significant exposure to navigational hazards if not dealt with correctly.

GNSS