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NASA NTRSDate not supplied

Towards a Cloud-Based Flight Management System

This paper summarizes the results of an initial concept exploration into the Cloud Flight Management System, or Cloud FMS, idea. Cloud FMS is a concept in which part of the aircraft’s FMS is on the aircraft itself, while another part resides in a ground-based cloud environment. This paper is limited to understanding whether this idea can be practically implemented within the current constraints of air-ground network throughput, availability, reliability, and latency. Simulation and live flight tests were conducted to study this concept, and specific findings that further fine-tune the Cloud FMS concept are provided.

Flight Management System, Cloud Computing, Urban A↗
NASA NTRSDate not supplied

Lunar Relay Onboard Navigation Performance and Effects on Lander Descent to Surface

A system of Lunar relay satellites has been proposed to address communication and navigation needs and ensure robustness for the variety of upcoming robotic and human exploration missions to the Moon. The relays are envisioned to estimate self position and time knowledge onboard, allowing the system to provide in-situ navigation services to missions in the Lunar and cis-Lunar environment. The quality and accuracy of those services are highly dependent on the navigation performance of the relay itself. To assess the Lunar relay navigation performance, a series of orbit determination (OD) Monte Carlo (MC) simulations are run using Lunar gravity modeling up to a degree and order of 250 and a variety of onboard clocks and measurement types including weak-signal GNSS, Ground Network (GN) pseudorange (PR) and Doppler, and optical navigation (OpNav) center-finding (CF). The estimated trajectories produced by these Lunar relay MC simulations, along with the associated errors, and transmitted navigation reference signal parameters, are used to evaluate the expected navigation performance of a user on a descent trajectory to the Lunar surface. The scenario features a lander system performing onboard navigation relying on one-way range and Doppler measurements from reference signals emitted by the Lunar relay. This paper can be used as a reference in determining the onboard clock and measurement types necessary to obtain acceptable navigation performance for the Lunar relay, and as a baseline for Lunar lander navigation performance using accurate measurements from a relay reference signal.

Jeffrey L. Small↗
NASA NTRSDate not supplied

Lunar Relay Onboard Navigation Performance and Effects on Lander Descent to Surface

A system of Lunar relay satellites has been proposed to address communication and navigation needs and ensure robustness for the variety of upcoming robotic and human exploration missions to the Moon. The relays are envisioned to estimate self-position and time knowledge onboard, allowing the system to provide in-situ navigation services to missions in the Lunar and cis-Lunar environment. The quality and accuracy of those services are highly dependent on the navigation performance of the relay itself. To assess the Lunar relay navigation performance, a series of orbit determination (OD) Monte Carlo (MC) simulations are run using Lunar gravity modeling up to a degree and order of 250 and a variety of onboard clocks and measurement types including weak-signal GNSS, Ground Network (GN) pseudorange (PR) and Doppler, and optical navigation (OpNav) center-finding (CF). The estimated trajectories produced by these Lunar relay MC simulations, along with the associated errors, and transmitted navigation reference signal parameters, are used to evaluate the expected navigation performance of a user on a descent trajectory to the Lunar surface. The scenario features a lander system performing onboard navigation relying on one-way range and Doppler measurements from reference signals emitted by the Lunar relay. This paper can be used as a reference in determining the onboard clock and measurement types necessary to obtain acceptable navigation performance for the Lunar relay, and as a baseline for Lunar lander navigation performance using accurate measurements from a relay reference signal.

Jeffrey L. Small↗
NASA NTRS2023

Impacts of SLR Ground Station Geographic Distribution on Time-Variable Gravity Recovery

Satellite laser ranging (SLR) continues to be an essential technique for estimating Earth's low-degree gravity field. The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) do not accurately recover certain coefficients, which are needed for quantifying large-scale mass redistribution as part of Earth's time-variable gravity (TVG) field. In case of an inter-mission gap, as with GRACE and GRACE-FO, SLR can continue to provide mass-change measurements. The current SLR ground network consists of around 40 stations. However, these are not uniformly distributed and the quantity and quality of data varies widely between sites. We anticipate that future stations will improve SLR-derived gravity estimates and we investigate their potential impact on the solution in this simulation study. A single new station that enhances network geometry, particularly in the Southern hemisphere, increases the sensitivity of the network by up to 12% for certain coefficients. The addition of 5 new future stations improves certain coefficients up to 18%. We find new stations are limited in their ability to decorrelate certain coefficients regardless of their location, but that adding more data and increasing network uniformity still benefits the overall solution.

E S Tucker↗
NASA NTRS2023

DPOD2020: A DORIS Extension of the ITRF2020 for Precise Orbit Determination

As one of the tracking systems used to determine orbits of the altimeter mission satellites (such as TOPEX/Poseidon, Envisat, Jason-1/-2/-3, CryoSat-2, Saral/Altika, Sentinel-3A/-3B, HY-2A/C/D, Jason-CS/Sentinel-6A, SWOT), DORIS (Doppler Orbitography Radiopositionning Integrated by Satellite) allows to determine positions and velocities of tracking stations that define a stable reference for the estimation of the precise orbits and thus are fundamental for the quality of the altimeter data and derived mean sea level products. Due to the time evolution of the DORIS ground network, some stations included in the 2020 realization of the International Terrestrial Reference Frame (ITRF2020) have been decommissioned and since 2021.0 a few new stations were added to the tracking network. Therefore, to satisfy operational requirements for POD (Precise Orbit Determination) and routine delivery of geodetic products, the International DORIS Service (IDS) regularly updates the DPOD (DORIS terrestrial reference frame for Precise Orbit Determination). The DPOD solutions include mean positions and velocities of all the DORIS stations since 1993.0 derived from the stacking of the latest IDS weekly combined series aligned to the current ITRF. In this paper, we first present the stacking process of the DPOD2020 version 1.0. Then, we address the validation procedure of the DPO2020 including comparison with ITRF2020 and POD tests. For eighty percent of all the time segments of all the DORIS stations, the station position differences between DPOD2020 version 1.0 and ITRF2020 are smaller than ten millimeters. The major position differences between these two solutions are associated with the DORIS sites either localized in the South Atlantic Anomaly region or with time spans smaller than one year. Compared to DPOD2014, the DPOD2020 shows reduction of the main statistics of the DORIS-to-DORIS tie residuals (differences between the estimated and measured ties). The POD tests showed similar results for DPOD2020 and DPOD2014 for most of the altimetric satellites (TOPEX/Poseidon, Jason-1, CryoSat-2, Jason-3). In addition, we observed better POD results with DPOD2020 for the latest altimetric satellite Sentinel-3A as well as a slight degradation for Jason-2. That degradation was fully explained by slightly worst results for the stations localized in the South Atlantic Anomaly region.

DORIS↗
NASA NTRSDate not supplied

Impact of DORISx Post Seismic Deformation and Seasonal Corrections on the DPOD2020 Solution

As one of the tracking systems used for the altimeter missions (such as TOPEX/Poseidon, Envisat, Jason-1/-2/-3, CryoSat-2, Saral/AltiKa, Sentinel-3A/-3B, HY-2A/C/D, Jason-CS/Sentinel-6A, SWOT), the position of the DORIS tracking stations provides a fundamental reference for the estimation of the precise orbits and so, by extension is fundamental for the quality of the altimeter data analysis and derived products. Due to the time evolution of the DORIS ground network, stations included in ITRF2020 may have been decommissioned and stations that were added to the tracking network after 2021.0 are, by definition, not part of ITRF2020. Therefore, to satisfy operational requirements for precise orbit determination and routine delivery of geodetic products, the International DORIS Service maintains the DORIS terrestrial reference frame for Precise Orbit Determination (DPOD) solutions. Since 2016, the DPOD products are computed by the IDS Combination Center (CC) as a DORIS cumulative position and linear velocity solution aligned to the latest available ITRF and using the latest IDS weekly combined series. Mid-2023, the IDS CC started the computation of the second version of the DPOD2020 based on the IDS 20 weekly solutions from 1993.0 to 2023.0. With that new solution, the IDS CC will include Post Seismic Deformation (PSD) corrections for some DORIS sites such as Socorro Island. These DPOD PSD corrections are determined from the analysis of DORIS coordinate time series only. The second version will also include optional annual and semi-annual station corrections. The presentation will describe the analysis used for extracting the PSD and seasonal DORIS station corrections, compare such corrections to those derived for ITRF2020, and evaluate the impact these new corrections have on station positioning and satellite POD.

Guilhem Moreaux↗
NASA NTRSDate not supplied

Impact of Size Distribution Assumption on PM2.5 Simulation

Aerosol particles, especially those with diameter that is smaller than 2.5um, i.e. PM2.5, have detrimental impact on public health. As a regulated criteria air pollutant, PM2.5 is monitored by ground networks using various instruments. At the same time aerosol assimilation modeling system is developed to simulate the aerosol distribution with continuous global coverage. In this study we compared the PM2.5 simulated by NASA’s MERRA-2 modeling system with the measurements made at US Embassy sites around the globe on diurnal cycle, monthly average, and interannual variabilities. We focused the comparison in the places that are significantly impacted by the desert dust. Simulations based on both aerodynamic and geometric diameters are compared with available measurements. Aerodynamic diameter assumption shows better model-observation agreements over several dust belt stations.

Qian Tan↗
NASA NTRS2024

Opinion: Aerosol Remote Sensing Over the Next Twenty Years

More than two decades ago, aerosol remote sensing underwent a revolution with the launch of the Terra and Aqua satellites. Advancement continued via additional launches carrying new passive and active sensors. Capable of retrieving parameters characterizing aerosol loading, rudimentary particle properties and in some cases aerosol layer height, the satellite view of Earth’s aerosol system came into focus.The modeling communities have made similar advances. Now the efforts have continued long enough that we can see developing trends in both remote sensing and modeling communities, allowing us to speculate about the future and how the community will approach aerosol remote sensing twenty years from now. We anticipate technology that will replace today’s standard multi-wavelength radiometers with hyperspectral and/or polarimetry all viewing in multiple angles.These will be supported by advanced active sensors with the ability to measure profiles of aerosol extinction in addition to backscatter. The result will be greater insight into aerosol particle properties. Algorithms will move from being primarily physically-based to include an increasing degree of Machine Learning methods, but physically-based techniques will not go extinct. However, the practice of applying algorithms to a single sensor will be in decline. Retrieval algorithms will encompass multiple sensors and all available ground measurements into a unifying framework, and these inverted products will be ingested directly into assimilation systems, becoming “cyborgs”: half observations, half model. In twenty years we will see a true democratization in space with nations large and small, private organizations and commercial entities of all sizes launching space sensors. With this increasing amount of data and aerosol products available, there will be a lot of bad data. User communities will organize to set standards and the large national space agencies will lead the effort to maintain quality by deploying and maintaining validation ground networks and focused field experiments. Through it all, interest will remain high in the global aerosol system and how that system affects climate, clouds, precipitation and dynamics, air quality, the environment and public health, transport of pathogens and fertilization of ecosystems, and how these processes are adapting to a changing climate.

aerosol remote sensing↗
NASA NTRSDate not supplied

Lunar Node – 1: Initial Flight Results and the Role of Surface Psuedolites in Lunar Navigation

On February 22, 2024, the Intuitive Machines IM-1 NOVA-C lander, nick-named Odysseus, landed on the lunar surface, carrying with it a cadre of NASA scientific and technology demonstration payloads. These payloads and missions marked the first delivery of NASA instruments to operate from the lunar surface since the Apollo landings. One of these payloads is Lunar Node -1 (LN-1), a navigation beacon demonstration mission. The payload was designed and built by NASA’s Marshall Space Flight Center. The payload’s main goal was to demonstrate and provide insight into the use of lunar surface-based radio navigation aids. As part of the mission, LN-1 successfully conducted multiple one-way transmissions from the NOVA-C vehicle to Deep Space Network ground receivers using its onboard S-band transmitter, while being disciplined by an onboard Space Chip Scale Atomic Clock. LN-1 transmitted to DSN on an almost daily basis during transit to the moon, including two surface passes. The payload was originally plan to conduct 7-10 days of surface operation as an always-on beacon. These passes focused on evaluating two main navigation approaches: performance and stability of ranging using time-based transfer techniques on a cubesat size and grade platform, as well as one-way psuedonoise ranging approaches. To assess performance, the measurements were compared to independent navigation solutions using multiple approaches including: one-way Doppler tracking, two-way Doppler Tracking, and visual verification of the landing location provided by visual observations from orbital platforms. While the mission only conducted limited surface operations, the data provides some initial insight to performance form the lunar surface. These results are compared with initial ground-based testing as well as continued evaluation of the flight-space platform using multiple grades of oscillators for maintaining clock and frequency stability. These focus on the timing stability of platform in a deep-space environment as well variations in state determination. Given these insights, this paper provides additional description and evaluation of how this approach can be utilized as part of a broader lunar navigation architecture, such as being developed and deployed across multiple international space agencies. Analysis is provided to develop overall timing requirements and assessment of operational scenarios, such as orbit and surface location determination. In addition, the results support discussion as to how surface pseudolites could best be used within existing standard signal definitions, such as defined in the LunaNet Interoperability Specifications. This will consider concerns such as the near-/far- problem as well as operational considerations, including whether a beacon is better suited as two- or one-way ranging platform. The use cases are focused on how these psuedolites can provide additional coverage to augment and support planned operational coverage. For example, this analysis provides analysis of mid-latitude surface missions, where there may be limited geometry and availability of orbital relays. The results will show how these navigation psuedolites can fit within the developing architecture to provide additional robustness, capability, and support multiple use cases. Lastly, the paper will discuss challenges and next steps to be addressed in the implementation and testing of a follow-on payload and a continued path towards demonstration and integration of this capability into Lunar PNT architectures.

Evan Anzalone↗
NASA NTRSDate not supplied

Lunar Node – 1: Initial Flight Results and the Role of Surface Psuedolites in Lunar Navigation

On February 22, 2024, Intuitive Machines NOVA-C lander, nick-named Odysseus, landed on the lunar surface, carrying with it a cadre of NASA scientific and technology demonstration payloads. These payloads and missions marked the first delivery of NASA instruments to operate from the lunar surface since the Apollo landings. One of these payloads is Lunar Node -1 (LN-1), a navigation beacon demonstration mission. The payload was designed and built by NASA’s Marshall Space Flight Center. The payload’s main goal was to demonstrate and provide insight into the use of lunar surface-based radio navigation aids. As part of the mission, LN-1 successfully conducted multiple one-way transmissions from the NOVA-C vehicle to Deep Space Network ground receivers using its onboard S-band transmitter, while being disciplined by an onboard Space Chip Scale Atomic Clock. LN-1 transmitted to DSN on an almost daily basis during transit to the moon, including two surface passes. The payload was originally plan to conduct 7-10 days of surface operation as an always-on beacon. These passes focused on evaluating two main navigation approaches: performance and stability of ranging using time-based transfer techniques on a cubesat size and grade platform, as well as one-way psuedonoise ranging approaches. To assess performance, the measurements were compared to independent navigation solutions using multiple approaches including: one-way Doppler tracking, two-way Doppler Tracking, and visual verification of the landing location provided by visual observations from orbital platforms. While the mission only conducted limited surface operations, the data provides some initial insight to performance form the lunar surface. These results are compared with initial ground-based testing as well as continued evaluation of the flight-space platform using multiple grades of oscillators for maintaining clock and frequency stability. These focus on the timing stability of platform in a deep-space environment as well variations in state determination. Given these insights, this paper provides additional description and evaluation of how this approach can be utilized as part of a broader lunar navigation architecture, such as being developed and deployed across multiple international space agencies. Analysis is provided to develop overall timing requirements and assessment of operational scenarios, such as orbit and surface location determination. In addition, the results support discussion as to how surface pseudolites could best be used within existing standard signal definitions, such as defined in the LunaNet Interoperability Specifications. This will consider concerns such as the near-/far- problem as well as operational considerations, including whether a beacon is better suited as two- or one-way ranging platform. The use cases are focused on how these psuedolites can provide additional coverage to augment and support planned operational coverage. For example, this analysis provides analysis of mid-latitude surface missions, where there may be limited geometry and availability of orbital relays. The results will show how these navigation psuedolites can fit within the developing architecture to provide additional robustness, capability, and support multiple use cases. Lastly, the paper will discuss challenges and next steps to be addressed in the implementation and testing of a follow-on payload and a continued path towards demonstration and integration of this capability into Lunar PNT architectures.

Evan J Anzalone↗
NASA NTRSDate not supplied

Transitioning a Flexible and Scalable Satellite Ground Station Observation Network (GSON) Framework to an Operational Environment

Obtaining accurate and timely satellite observations is of paramount importance in fields like disaster management, weather diagnoses/forecasting, and Earth Sciences remote sensing. Stored mission data (SMD), from low Earth orbiting (LEO) satellite sensors, provides important observations for these fields and applications, however data access to SMD can be delayed from one and half hours to three hours from the time the observations were made. This data latency poses a significant impact on data product optimal use. We developed a Ground Station Observation Network (GSON) that utilizes commercial ground station as a service (GSaaS) providers to acquire low latency direct broadcast (DB) data from AQUA, SNPP, and JPSS-1 satellites using antennas located in strategic locations around the world. We will discuss techniques to improve the deployment efficiency and code reliability and quality of the GSON framework. Topics include right-sizing and containerization of the code to facilitate integration and adaptation with continuous delivery (CD) pipeline, locating non-code assets in referenceable repositories separated from code, adaptation of pipelines as code and simplification of CD, intersecting with code quality tests and checks as part of the pipeline execution and deployment, and establishing distributed repositories, registries, and system identities in a way that mitigates compromise to the CD pipeline. These techniques enable deployment of processing systems that are both highly specific but also dynamically modifiable. This new class of system allows for a flexible and scalable deployment while avoiding the “black box” issues that can plague large system deployments.

cluster↗
NASA NTRS2002

Converging voice and data over mission-critical networks

The U.S. National Aeronautics and Space Administration (NASA) Deep Space Network ?? DSN - is an international network of antennas that supports interplanetary spacecraft missions and radio and radar astronomy observations for the exploration of the solar system and the universe. The network also supports selected Earth-orbiting missions. This paper describes the ground communications network of the DSN and ways network infrastructure costs are being reduced by the introduction of new technology. Fundamentally, the DSN ground network architecture is a star network, and the hub is at JPL in Pasadena, California. Communications to customer sites are designed to minimize NASA costs and may be either shared IP backbone networks or dedicated circuits. One of the primary features of the network is its ability to support real-time data, voice, and video communications among antenna stations, an automated multi-mission operations systems facility at JPL (AMMOS), and mission operations centers (MOCs) at NASA and non-NASA facilities. Funding for advanced engineering to reduce ground network infrastructure costs was provided by the NASA Office of Space Science.

ground communications networks Internet voice VOIP↗
DOE OSTI2021

Cross Validation of the Network of Ground-Based Radar with GPM during the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) Field Campaign

The cross-validation of radars in a network is important in making consistent retrievals across the domain and assuring the product quality. During the RELAMPAGO field campaign, two C-band radars, namely the Colorado State University C-band Hydrological Instrument for Volumetric Observations ( CSU-CHIVO) and the C-band Scanning ARM Precipitation Radar (CSAPR-2), were deployed near the Sierras de Cordoba in Argentina, a region known for having some of the most intense severe weather in the world. In addition to these two radars, the operational radar of the Cordoba City, the Radar Meteorologico Argentino 1 (RMA-1), adds another instrument to the RELAMPAGO network. This study presents an intercomparison between the RELAMPAGO C-band radars using the GPM spaceborne radar as a common reference ..A method to bring ground-based radars into better agreement is also proposed. Moreover, the attenuation correction for the C-band radar is studied in the context of intercomparing two radars. The attenuation coefficients are computed for the RELAMPAGO domain using the local disdrometers deployed. during the campaign. After the attenuation correction, CSU-CHIVO, CSAPR-2, and RMA-1 compare well with GPM-DPR with a high correlation and bias less than 1 dB.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

NASA ground communications

As part of the Communications Requirements and Constraints, NASA's two major Ground Data Networks were briefly described. The NASA Communication Network, called NASCOM, is the worldwide operational telecommunications system which interconnects as the tracking and telemetry acquisition sites, launch areas, mission and project control centers, data capture facilities, and network control centers in support of space flight. For the Space Station era, NASCOM plans are set for higher data rate service utilizing data packet switched technology. Increased use of fiber optics is expected in a much more diverse network topology. The second major ground network, the Program Support Communications Network (PSCN), interconnects all NASA Centers and NASA contractor locations for intercenter non-operation communications. The primary functions are to transport voice, video, data and facsimile information for intercenter coordination, and to provide user access to space science and applications data bases. For the Space Station era, PSCN plans address the significant increase in forecast requirements for science data distribution and access to the Numerical Aerodynamics Simulator, and increased use of the Video Teleconference System.

Roeder, John↗
NASA NTRS1990

Predicting thunderstorm evolution using ground-based lightning detection networks

Lightning measurements acquired principally by a ground-based network of magnetic direction finders are used to diagnose and predict the existence, temporal evolution, and decay of thunderstorms over a wide range of space and time scales extending over four orders of magnitude. The non-linear growth and decay of thunderstorms and their accompanying cloud-to-ground lightning activity is described by the three parameter logistic growth model. The growth rate is shown to be a function of the storm size and duration, and the limiting value of the total lightning activity is related to the available energy in the environment. A new technique is described for removing systematic bearing errors from direction finder data where radar echoes are used to constrain site error correction and optimization (best point estimate) algorithms. A nearest neighbor pattern recognition algorithm is employed to cluster the discrete lightning discharges into storm cells and the advantages and limitations of different clustering strategies for storm identification and tracking are examined.

Goodman, Steven J.↗
NASA NTRS1998

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

Chepfer, H.↗
NASA NTRS2005

LEO Download Capacity Analysis for a Network of Adaptive Array Ground Stations

To lower costs and reduce latency, a network of adaptive array ground stations, distributed across the United States, is considered for the downlink of a polar-orbiting low earth orbiting (LEO) satellite. Assuming the X-band 105 Mbps transmitter of NASA s Earth Observing 1 (EO-1) satellite with a simple line-of-sight propagation model, the average daily download capacity in bits for a network of adaptive array ground stations is compared to that of a single 11 m dish in Poker Flats, Alaska. Each adaptive array ground station is assumed to have multiple steerable antennas, either mechanically steered dishes or phased arrays that are mechanically steered in azimuth and electronically steered in elevation. Phased array technologies that are being developed for this application are the space-fed lens (SFL) and the reflectarray. Optimization of the different boresight directions of the phased arrays within a ground station is shown to significantly increase capacity; for example, this optimization quadruples the capacity for a ground station with eight SFLs. Several networks comprising only two to three ground stations are shown to meet or exceed the capacity of the big dish, Cutting the data rate by half, which saves modem costs and increases the coverage area of each ground station, is shown to increase the average daily capacity of the network for some configurations.

Ingram, Mary Ann↗
NASA NTRS2000

Some Long-Standing Issues Arising From Comparisons Between TOMS and The Ground-Based Ozone Network

Data from the series of Total Ozone Mapping Spectrometers (TOMS) have been compared to column ozone measurements taken by ground-based systems (Dobsons, Brewers and Filtermeters). On average, the comparisons show good agreement, with approximately 80% of the ground stations having less than a 2.5% standard deviation when compared to TOMS on a monthly mean basis. There are, however, differences that imply possible errors either in the TOMS ozone retrieval algorithm or in the basic assumptions used by the ground-based instruments. Some of the issues arising from these differences are: What are the relative calibrations of TOMS instruments? Why do the calibrations of the ground-based stations vary as much as they do with respect to TOMS as a transfer standard? Why are the TOMS data so much larger (approximately 6%) than the ground-based data in Antarctica and other ice-covered locations? Why is there seasonality in the difference between TOMS and ground-based stations in the Southern Hemisphere? Why are the differences a function of total ozone? Where and why are the differences a function of reflectivity? Why do some terrain and land-sea boundary features appear in the TOMS ozone data? The above issues will be highlighted by using data from TOMS and the ground stations. Plots of the individual station differences will be available.

Labow, Gordon J.↗