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This study focuses on utilizing the increasing availability of satellite trajectory data from global navigation satellite system‐enabled low‐Earth orbiting satellites and their precision orbit determination (POD) solutions to expand and refine thermospheric model validation capabilities. The research introduces an updated interface for the GEODYN‐II POD software, leveraging high‐precision space geodetic POD to investigate satellite drag and assess density models. This work presents a case study to examine five models (NRLMSIS2.0, DTM2020, JB2008, TIEGCM, and CTIPe) using precise science orbit (PSO) solutions of the Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2). The PSO is used as tracking measurements to construct orbit fits, enabling an evaluation according to each model's ability to redetermine the orbit. Relative in‐track deviations, quantified by in‐track residuals and root‐mean‐square errors (RMSe), are treated as proxies for model densities that differ from an unknown true density. The study investigates assumptions related to the treatment of the drag coefficient and leverages them to eliminate bias and effectively scale model density. Assessment results and interpretations are dictated by the timescale at which the scaling occurs. DTM2020 requires the least scaling (∼−7%) to achieve orbit fits closely matching the PSO within an in‐track RMSe of 7 m when scaled over 2 weeks and 2 m when scaled daily. The remaining models require substantial scaling of the mean density offset (∼30 − 75%) to construct orbit fits that meet the aforementioned RMSe criteria. All models exhibit slight over or under‐sensitivity to geomagnetic activity according to trends in their 24‐hr scaling factors. Plain Language Summary: This research aims to make use of data from well‐tracked satellites that orbit close to Earth where they still interact with the atmosphere via satellite drag. The goal is to use high‐quality orbit solutions of satellites to provide additional means of testing density models of the Earth's upper atmosphere. By updating a precise orbit software tool called GEODYN‐II, we demonstrate how a satellite's orbit is affected by the drag forces from different density models of the upper atmosphere, and how those orbits can be used to assess the accuracy of the models. Each density model produces an orbit fit that deviates from the precise orbit of a satellite, and these deviations are used as proxies for model error relative to the unknown true density. We tested five different models using precise orbit solutions from the ICESat‐2 satellite. Various assumptions related to the drag force are investigated and used to scale the model densities at different timescales. We find that all models benefit from scaling to produce orbit fits that more closely match the ICESat‐2 precise orbit. Key Points: Precision orbit determination solutions are expanded to study satellite drag and assess upper atmospheric density models using GEODYNA proof‐of‐concept case study assessment of density models is presented using ICESat‐2 precise science orbits and orbit fitsAssessment results are provided for empirical (MSIS2, DTM2020, JB2008) and physics‐based (TIEGCM, CTIPe) models for 14‐days in November 2018 [ABSTRACT FROM AUTHOR]

The 2017–2027 United States National Academy of Sciences Decadal Survey (DS) for Earth Science and Applications from Space identified Mass Change (MC) as one of five Designated Observables (DOs) having the highest priority in terms of Earth observations required to advance Earth system science over the next decade. In response to this designation, NASA initiated several multi‐center studies, with the goal of recommending observing system architectures for each DO for implementation within this decade. This paper provides an overview of the Mass Change Designated Observable (MCDO) Study along with key findings. The study process included: (a) generation of a Science and Applications Traceability Matrix (SATM) that maps required measurement parameters to the DS Science and Applications Objectives; (b) identification of three architecture classes relevant for measuring mass change: Precise Orbit Determination (POD), Satellite‐Satellite‐Tracking (SST) and Gravity Gradiometry (GG), along with variants within each architecture class; and (c) creation of a Value Framework process that considers science value, cost, risk, schedule, and partnership opportunities, to identify and recommend high value observing systems for further in‐depth study. The study team recommended the implementation of an SST architecture, and identified variants that simultaneously (a) satisfy the baseline measurement parameters of the SATM; (b) maximize the probability of providing overlap with the Gravity Recovery and Climate Experiment Follow‐On (GRACE‐FO) mission currently in operation, accelerating science return from both missions; and (c) provide a pathway towards substantial improvements in resolution and accuracy of mass change data products relative to the program of record. Plain Language Summary: This study provides an overview of the Mass Change Designated Observable Study. The goals of the study were to recommend observing systems for NASA to implement within this decade to measure Earth system mass change, after it was identified in the United States National Academy of Sciences Decadal Survey as one of the five most important observations to advance Earth system science. Mass change observations are critical to understanding changes in sea level, the health of the ice sheets and glaciers worldwide, and changes in freshwater availability across the globe. The study team recommended that NASA implement an architecture similar in nature to its two predecessor missions: the Gravity Recovery and Climate Experiment (GRACE), and GRACE Follow‐On (GRACE‐FO). This will maximize the chances that there will not be a data gap between GRACE‐FO (currently operational) and the next observing system. Further, the study team recommended collaborating with potential international partners to add more satellites to this architecture, in order to improve resolution of Earth system mass change in space and time. Key Points: A Science and Applications Traceability Matrix to satisfy the 2017 Earth Science Decadal Survey Mass Change Science Objectives was developedA value framework process was used to identify and evaluate high‐value mass change observing systems for implementation within this decadeHigh value observing systems provide continuity with Gravity Recovery and Climate Experiment Follow‐On and a pathway for improved resolution and accuracy in resolving mass change [ABSTRACT FROM AUTHOR]

The Ice, Cloud and land Elevation Satellite‐2 was launched on 15 September 2018 with mission goals of collecting surface elevation data that can precisely measure ice sheet topography, cloud and aerosol heights, land topography, as well as vegetation height for ecosystems studies. The Constraint Analysis and Monitoring System (CAMS) was implemented as an ICESat‐2 ground system element to perform Mission Planning and Spacecraft Safety Monitoring. Mission Planning requires CAMS to serve as an interface between the Project Science Office, the Instrument Support Facility and the Mission Operation Control Center. By ingesting inputs received from all three groups, the CAMS builds an optimized and deconflicted timeline of science and instrument activities. Based upon the timeline of activities, the CAMS utilizes a sophisticated set of algorithms to model and predict the location and pointing of the spacecraft instrument relative to the Earth and Sun. From the predicted position and pointing, the CAMS provides precise monitoring of instrument health, and performs space asset laser conjunction detection. Furthermore, the CAMS determines alternative plans to prevent detected health constraint violations or mitigate potential laser conjunctions. This paper provides an overview of the CAMS and presents the operational performance of planning science and instrument activities, the monitoring of instrument constraints for health and safety, and the space asset laser conjunction screening and mitigation process. Plain Language Summary: The Ice, Cloud and land Elevation Satellite‐2 (ICESat‐2) Constraint Analysis and Monitoring System (CAMS) accurately models and predicts the instrument position and pointing for both Mission Planning and Spacecraft Safety Monitoring. Spacecraft Safety Monitoring involves ensuring the instrument health and safety as well as protecting other space assets in the space environment from being intersected by the ICESat‐2 laser energy (lased). The CAMS accomplishes this by screening the predicted position of known space assets and monitoring instrument health constraints through modeling and prediction. When a health constraint violation is predicted during a spacecraft maneuver, the CAMS performs the analysis necessary to re‐plan the maneuver in order to mitigate the constraint violation. When a laser conjunction has been predicted, the CAMS makes a recommendation to mission operations to perform an avoidance slew or to suspend the firing of the laser until the event has passed. One of the most critical aspects for accurate constraint and lasing event forecasting is the error modeling. The CAMS contains an overall system performance tool which assesses the accuracy of all the system's inputs and outputs. From these performance evaluations the error models can be tuned and continually improved to perform better Spacecraft Safety Monitoring. Key Points: The CAMS is an element of the ICESat‐2 ground system responsible for mission planning and spacecraft safety monitoringSpacecraft safety monitoring includes ICESat‐2 instrument health monitoring and space asset laser conjunction screeningThe CAMS develops alternative attitude and activity plans to prevent instrument health constraint violations and mitigate laser conjunctions [ABSTRACT FROM AUTHOR]

The ICESat‐2 Precision Orbit Determination (POD) system computes the precise position of the laser altimeter instrument in inertial space, a measurement necessary for accurate geolocation of individual photon surface returns. ICESat‐2 POD solutions are generated by the reduction of Global Positioning System (GPS) double‐difference carrier phase observable residuals with NASA Goddard Space Flight Center's GEODYN software. Independent satellite laser ranging (SLR) measurements are withheld from the POD solutions and used as an independent arbiter of POD performance. Measurement model updates in the form of estimated GPS antenna phase center and satellite laser ranging retro‐reflector tracking point offset vectors as well as a GPS antenna phase center variation map have led to significant improvement in POD performance. GPS residual analysis and orbit precision analysis show no significant anomalous temporal or geographic POD performance issues. The independent SLR residual analysis indicates that POD solutions have achieved a radial orbit accuracy just below 1.5 cm, thus exceeding the mission radial orbit accuracy requirement of 3.0 cm by more than a factor of 2. Future POD processing updates have been identified and will lead to even further improvements in POD performance. Key Points: ICESat‐2 surface return elevation accuracy depends directly on the performance and accuracy of precisely positioning the instrumentICESat‐2 mission Precision Orbit Determination (POD) requirement is 3.0 cm radial RMS over a 24‐h periodICESat‐2 POD performance is achieving a factor of 2 improvement over the mission requirement at 1.5 cm radial RMS [ABSTRACT FROM AUTHOR]

ICESat‐2 science requirements are dependent on the accurate real‐time pointing control (i.e., geolocation control) and postprocessed geolocation knowledge of the laser altimeter surface returns. Prelaunch pointing alignment errors and postlaunch pointing alignment variation result in large geolocation errors that must be calibrated on orbit. In addition, the changing sun‐orbit geometry causes thermal‐mechanical forced laser frame alignment variations at the orbit period and trends from days, weeks, and months. Early mission analysis computed precise postlaunch laser beam alignment calibration. The alignment calibration was uploaded to the spacecraft and enabled the pointing control performance to achieve 4.4 ± 6.0 m, a significant improvement over the 45 m (1 σ) mission requirement. Laser frame alignment calibrations are used to reduce the alignment bias and time variation, as well as the orbital variation contributions to geolocation knowledge error from 6 to 1.7 m (1 σ). Relative beam alignment of the six beams is calibrated and shown to contribute between 0.5 ± 0.1 m and 2.4 ± 0.2 m of remaining geolocation knowledge error. Independent geolocation assessment based on comparison to high‐resolution digital elevation models agrees well with the calibration geolocation error estimates. The analysis demonstrates the ICESat‐2 mission is performing far better than its geolocation knowledge requirement of 6.5 m (1 σ) after the laser frame alignment bias variation and orbital variation calibrations have been applied. Remaining geolocation error is beam dependent and ranges from 2.5 m for beam 6 to 4.4 m for beam 2 (mean + 1 σ). Key Points: Systematic time varying pointing errors are the largest ICESat‐2 pointing control and geolocation knowledge error sourceThe systematic pointing errors have been calibrated and corrected to meet and exceed the mission geolocation requirementsFurther geolocation improvements can be made through the application of the relative beam alignment calibration [ABSTRACT FROM AUTHOR]

Satellite laser ranging (SLR) observations are routinely applied toward the estimation of dynamic oblateness, C20, which is the largest globally integrated component of Earth's time‐variable gravity field. Since 2002, GRACE and GRACE Follow‐On have revolutionized the recovery of higher spatial resolution features of global time‐variable gravity, with SLR continuing to provide the most reliable estimates of C20. We quantify the effect of various SLR processing strategies on estimating C20 and demonstrate better signal recovery with the inclusion of GRACE‐derived low‐degree gravity information in the forward model. This improved SLR product modifies the Antarctic and Greenland Ice Sheet mass trends by −15.4 and −3.5 Gt/year, respectively, as compared to CSR TN11, and improves global mean sea level budget closure by modifying sea level rise by +0.08 mm/year. We recommend that this new C20 product be applied to RL06 GRACE data products for enhanced accuracy and scientific interpretation. Key Points: New satellite laser ranging C20 solution reveals larger Antarctic and Greenland ice mass losses and mass‐driven sea level riseThe new C20 result improves closure of the global mean sea level budget and agreement with an independent Antarctic ice mass assessmentWe recommend this new product for replacing the GRACE C20 values for science applications [ABSTRACT FROM AUTHOR]

Seven years of GRACE intersatellite range-rate measurements are used to test the new ocean tide model FES2014 and to compare against similar results obtained with earlier models. These qualitative assessments show that FES2014 represents a marked improvement in accuracy over its earlier incarnation, FES2012, with especially notable improvements in the Arctic Ocean for constituents K1 and S2. Degradation appears to have occurred in two anomalous regions: the Ross Sea for the O1 constituent and the Weddell Sea for M2. [ABSTRACT FROM AUTHOR]

The Antarctic Ice Sheet is the largest potential source of future sea-level rise. Mass loss has been increasing over the last 2 decades for the West Antarctic Ice Sheet (WAIS) but with significant discrepancies between estimates, especially for the Antarctic Peninsula. Most of these estimates utilise geophysical models to explicitly correct the observations for (unobserved) processes. Systematic errors in these models introduce biases in the results which are difficult to quantify. In this study, we provide a statistically rigorous error-bounded trend estimate of ice mass loss over the WAIS from 2003 to 2009 which is almost entirely data driven. Using altimetry, gravimetry, and GPS data in a hierarchical Bayesian framework, we derive spatial fields for ice mass change, surface mass balance, and glacial isostatic adjustment (GIA) without relying explicitly on forward models. The approach we use separates mass and height change contributions from different processes, reproducing spatial features found in, for example, regional climate and GIA forward models, and provides an independent estimate which can be used to validate and test the models. In addition, spatial error estimates are derived for each field. The mass loss estimates we obtain are smaller than some recent results, with a time-averaged mean rate of -76±15 Gt yr-1 for the WAIS and Antarctic Peninsula, including the major Antarctic islands. The GIA estimate compares well with results obtained from recent forward models (IJ05-R2) and inverse methods (AGE-1). The Bayesian framework is sufficiently flexible that it can, eventually, be used for the whole of Antarctica, be adapted for other ice sheets and utilise data from other sources such as ice cores, accumulation radar data, and other measurements that contain information about any of the processes that are solved for. [ABSTRACT FROM AUTHOR]

We use a Monte Carlo approach to invert a spherical harmonic representation of cryosphere-attributed mass change in order to infer the most likely underlying mass changes within irregularly shaped ice-covered areas at nominal 26 km resolution. By inverting a spherical harmonic representation through the incorporation of additional fractional ice coverage information, this approach seeks to eliminate signal leakage between non-ice-covered and ice-covered areas. The spherical harmonic representation suggests a Greenland mass loss of 251±25 Gt a−1 over the December 2003 to December 2010 period. The inversion suggests 218±20 Gt a−1 was due to the ice sheet proper, and 34±5 Gt a−1 (or d~14 %) was due to Greenland peripheral glaciers and ice caps (GrPGICs). This mass loss from GrPGICs exceeds that inferred from all ice masses on both Ellesmere and Devon islands combined. This partition therefore highlights that GRACE-derived “Greenland” mass loss cannot be taken as synonymous with “Greenland ice sheet” mass loss when making comparisons with estimates of ice sheet mass balance derived from techniques that sample only the ice sheet proper. [ABSTRACT FROM AUTHOR]

Satellite altimeter measurements of sea surface height include a small contribution from vertical motion of the seafloor caused by crustal loading. Loading by ocean tides is routinely allowed for in altimeter data processing. Here, loading by nontidal fluids of the atmosphere, ocean, and terrestrial hydrosphere is examined. The crustal deformation can be computed from either geophysical models or from Gravity Recovery and Climate Experiment (GRACE) gravity inversions of mass variability. The loading corrections are found to be very small, rarely exceeding a few millimeters. Nonetheless, they form a significant correction to altimetric determinations of global mean sea level. The correction is most important at the annual cycle and should be accounted for when attempting to balance the global sea level budget. [ABSTRACT FROM AUTHOR]

The manner in which errors in tide models affect monthly gravity solutions from GRACE satellite data is re-examined. We perform a complete simulation of GRACE gravity estimation, including allowance for accelerometer calibrations and satellite state-vector adjustment. Errors in monthly geoid estimates are for most regions of a order of 0.5 mm, or roughly 1 cm of equivalent water height when smoothed over radii of 600 km. In polar regions where ocean tide models are suspect, errors can grow significantly larger: over 2 mm in geoid height, although over very localized regions. Errors from diurnal tides tend to cancel, but they are not completely eliminated, inducing geoid errors of the order of 0.3 mm. The currently accepted GRACE total error budget is roughly an order of magnitude larger than the component arising from tide modelling errors. [ABSTRACT FROM AUTHOR]

The Jason-1 verification phase has proven to be a unique and successful calibration experiment to quantify the agreement with its predecessor TOPEX/Poseidon. Although both missions have met prescribed error budgets, comparison of the mean and time-varying sea surface height profiles from near simultaneous observations derived from the missions' Geophysical Data Records exhibit significant basin scale differences. Several suspected sources causing this disagreement are identified and improved upon, including (a) replacement of TOPEX and Jason project POE with enhanced orbits computed at GSFC within a consistent ITRF2000 terrestrial reference frame, (b) application of waveform retracking corrections to TOPEX significant wave height and sea surface heights, (c) resultant improved efficacy of the TOPEX sea state bias estimation from the value added sea surface height, and (d) estimation of Jason-1 sea state bias employing dual TOPEX/Jason crossover and collinear sea surface height residuals unique to the validation mission. The resultant mean sea surface height comparison shows improved agreement at better than 60 percent level of variance reduction with a standard deviation less then 0.5 cm. [ABSTRACT FROM AUTHOR]

The Jason-1 radar altimeter satellite, launched on December 7, 2001 is the follow on to the highly successful TOPEX/Poseidon (T/P) mission and will continue the time series of centimeter level ocean topography measurements. Orbit error is a major component in the overall error budget of all altimeter satellite missions. Jason-1 is no exception and has set a 1-cm radial orbit accuracy goal, which represents a factor of two improvement over what is currently being achieved for T/P. The challenge to precision orbit determination (POD) is both achieving the 1-cm radial orbit accuracy and evaluating the performance of the 1-cm orbit. There is reason to hope such an improvement is possible. The early years of T/P showed that GPS tracking data collected by an on-board receiver holds great promise for precise orbit determination. In the years following the T/P launch there have been several enhancements to GPS, improving its POD capability. In addition, Jason-1 carries aboard an enhanced GPS receiver and significantly improved SLR and DORIS tracking systems along with the altimeter itself. In this article we demonstrate the 1-cm radial orbit accuracy goal has been achieved using GPS data alone in a reduced dynamic solution. It is also shown that adding SLR data to the GPS-based solutions improves the orbits even further. In order to assess the performance of these orbits it is necessary to process all of the available tracking data (GPS, SLR, DORIS, and altimeter crossover differences) as either dependent or independent of the orbit solutions. It was also necessary to compute orbit solutions using various combinations of the four available tracking data in order to independently assess the orbit performance. Towards this end, we have greatly improved orbits determined solely from SLR+DORIS data by applying the reduced dynamic solution strategy. In addition, we have computed reduced dynamic orbits based on SLR, DORIS, and crossover data that are a significant improvement over the SLR- and DORIS-based dynamic solutions. These solutions provide the best performing orbits for independent validation of the GPS-based reduced dynamic orbits. The application of the 1-cm orbit will significantly improve the resolution of the altimeter measurement, making possible further strides in radar altimeter remote sensing. [ABSTRACT FROM AUTHOR]