Increasing system performance and flexibility: Distributed computing and routing of data within the fast formation flying mission

In 2007, the Tsinghua University, China, and the Delft University of Technology, The Netherlands, have agreed to jointly define, develop and operate the Formation for Atmospheric Science and Technology demonstration (FAST) mission. FAST will allow for a synoptic evaluation of global aerosol data and altitude profiles of the cryosphere with two cooperating micro-satellites flying in formation in 2011. One of the many technology demonstrations planned for the FAST mission involves the use of distributed space-based computing. This technique can be used to maximize the computational power available in a formation of small satellites, as well as reducing downlink budgets by processing data in flight. Its implementation on FAST is discussed in the paper. The formation flying and distributed computing demonstrations call for a communication link between the two FAST spacecraft. Important to the design of the link is that it does not necessarily need to be a direct link. In fact, during a part of the mission, such a direct link will be impossible due to the relative orbit geometry of the satellites. This requires an alternative routing of the inter-satellite communications via ground stations or via commercial satellite communication constellations. This flexible solution is explored, with special emphasis paid to the issues related with communication with a commercial satellite communication constellation.Space EngineeringAerospace Engineerin

Separating Geophysical Signals Using GRACE and High-Resolution Data: A Case Study in Antarctica

To fully exploit data from the Gravity Recovery and Climate Experiment (GRACE), we separate geophysical signals observed by GRACE in Antarctica by deriving high-spatial resolution maps for present-day glacial isostatic adjustment (GIA) and ice-mass changes with the least possible noise level. For this, we simultaneously (i) improve the postprocessing of gravity data and (ii) consistently combine them with high-resolution data from Ice Cloud and land Elevation Satellite altimeter (ICESat) and Regional Atmospheric Climate Model 2.3 (RACMO). We use GPS observations to discriminate between various candidate spatial patterns of vertical motions caused by GIA. The ICESat-RACMO combination determines the spatial resolution of estimated ice-mass changes. The results suggest the capability of the developed approach to retrieve the complex spatial pattern of present-day GIA, such as a pronounced subsidence in the proximity of the Kamb Ice Stream and pronounced uplift in the Amundsen Sea Sector.Physical and Space Geodes

Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin

Geoscience & Remote SensingCivil Engineering and Geoscience

An approach for estimating time-variable rates from geodetic time series

There has been considerable research in the literature focused on computing and forecasting sea-level changes in terms of constant trends or rates. The Antarctic ice sheet is one of the main contributors to sea-level change with highly uncertain rates of glacial thinning and accumulation. Geodetic observing systems such as the Gravity Recovery and Climate Experiment (GRACE) and the Global Positioning System (GPS) are routinely used to estimate these trends. In an effort to improve the accuracy and reliability of these trends, this study investigates a technique that allows the estimated rates, along with co-estimated seasonal components, to vary in time. For this, state space models are defined and then solved by a Kalman filter (KF). The reliable estimation of noise parameters is one of the main problems encountered when using a KF approach, which is solved by numerically optimizing likelihood. Since the optimization problem is non-convex, it is challenging to find an optimal solution. To address this issue, we limited the parameter search space using classical least-squares adjustment (LSA). In this context, we also tested the usage of inequality constraints by directly verifying whether they are supported by the data. The suggested technique for time-series analysis is expandedPhysical and Space Geodes

The design of an optimal filter for monthly GRACE gravity models

Geoscience and Remote SensingCivil Engineering and Geoscience

Empirical estimation of present-day Antarctic glacial isostatic adjustment and ice mass change

This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating a firn densification model to account for firn compaction and surface processes as well as reprocessed data sets over a slightly longer period of time. A range of different Gravity Recovery and Climate Experiment (GRACE) gravity models were evaluated and a new Ice, Cloud, and Land Elevation Satellite (ICESat) surface height trend map computed using an overlapping footprint approach. When the GIA models created from the combination approach were compared to in situ GPS ground station displacements, the vertical rates estimated showed consistently better agreement than recent conventional GIA models. The new empirically derived GIA rates suggest the presence of strong uplift in the Amundsen Sea sector in West Antarctica (WA) and the Philippi/Denman sectors, as well as subsidence in large parts of East Antarctica (EA). The total GIA-related mass change estimates for the entire Antarctic ice sheet ranged from 53 to 103 Gt yr?1, depending on the GRACE solution used, with an estimated uncertainty of ±40 Gt yr?1. Over the time frame February 2003– October 2009, the corresponding ice mass change showed an average value of ?100±44 Gt yr?1 (EA: 5±38, WA:?105±22), consistent with other recent estimates in the literature, with regional mass loss mostly concentrated in WA. The refined approach presented in this study shows the contribution that such data combinations can make towards improving estimates of present-day GIA and ice mass change, particularly with respect to determining more reliable uncertainties.Geoscience & Remote SensingCivil Engineering and Geoscience

Combining satellite altimetry and gravimetry data to improve Antarctic mass balance and gia estimates

This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating reprocessed data sets over a longer period of time, and now include a firn densification model to convert the altimetry volume estimates into mass. When the GIA models created from the combination approach were compared to insitu GPS ground station displacements, the vertical rates estimated showed good agreement after a systematic bias was removed from the computed GIA models. The new models suggest the potential for GIA uplift in the Amundsen Sea Sector, as well as the possible subsidence in large parts of East Antarctica.Geoscience & Remote SensingCivil Engineering and Geoscience

A Comparison of Global and Regional GRACE Models for Land Hydrology

When using GRACE as a tool for hydrology, many different gravity field model products are now available to the end user. The traditional spherical harmonics solutions produced from GRACE are typically obtained through an optimization of the gravity field data at the global scale, and are generated by a number of processing centers around the world. Alternatives to this global approach include so-called regional techniques, for which many variants exist, but whose common trait is that they only use the gravity data collected over the area of interest to generate the solution. To determine whether these regional solutions hold any advantage over the global techniques in terms of overall accuracy, a range of comparisons were made using some of the more widely used regional and global methods currently available. The regional techniques tested made use of either spherical radial basis functions or single layer densities (i.e., mascons), with the global solutions having been obtained from the various major processing centers. The solutions were evaluated using a range of computed statistics over a selection of major river basins, which were globally distributed and ranged in size from 1 to 6 million km(2). For one of the basins tested, the Zambezi, additional validation tests were conducted through comparisons against a custom designed regional hydrology model of the region. We could not prove that current regional models perform better than global ones. Monthly mean water storage variations agree at the level of 0.02 m equivalent water height. The differences in terms of monthly mean water storage variations between regional and global solutions are comparable with the differences among only global or regional solutions. Typically they reach values of 0.02 m equivalent water heights, which seems to be the level of accuracy of current GRACE solutions for river basins above 1 million km(2). The amplitudes of the seasonal mass variations agree at the sub-entimetre level. Evident from all of the comparisons shown is the importance that the choice of regularization, or spatial filtering, can have on the solution quality. This was found to be true for global as well as regional techniques.Earth Observation and Space SystemsAerospace Engineerin

Using geodetic measurements to improve estimates of Antarctica's GIA and present-day mass balance

Physical and Space Geodes

A high resolution model of linear trend in mass variations from DMT-2: Added value of accounting for coloured noise in GRACE data

We present a high resolution model of the linear trend in the Earth’s mass variations based on DMT-2 (Delft Mass Transport model, release 2). DMT-2 was produced primarily from K-Band Ranging (KBR) data of the Gravity Recovery And Climate Experiment (GRACE). It comprises a time series of monthly solutions complete to spherical harmonic degree 120. A novel feature in its production was the accurate computation and incorporation of stochastic properties of coloured noise when processing KBR data. The unconstrained DMT-2 monthly solutions are used to estimate the linear trend together with a bias, as well as annual and semi-annual sinusoidal terms. The linear term is further processed with an anisotropic Wiener filter, which uses full noise and signal covariance matrices. Given the fact that noise in an unconstrained model of the trend is reduced substantially as compared to monthly solutions, the Wiener filter associated with the trend is much less aggressive compared to a Wiener filter applied to monthly solutions. Consequently, the trend estimate shows an enhanced spatial resolution. It allows signals in relatively small water bodies, such as Aral sea and Ladoga lake, to be detected. Over the ice sheets, it allows for a clear identification of signals associated with some outlet glaciers or their groups. We compare the obtained trend estimate with the ones from the CSR-RL05 model using (i) the same approach based on monthly noise covariance matrices and (ii) a commonly-used approach based on the DDK-filtered monthly solutions. We use satellite altimetry data as independent control data. The comparison demonstrates a high spatial resolution of the DMT-2 linear trend. We link this to the usage of high-accuracy monthly noise covariance matrices, which is due to an accurate computation and incorporation of coloured noise when processing KBR data. A preliminary comparison of the linear trend based on DMT-2 with that computed from GSFC global mascons v01 reveals, among other, a high concentration of the signal along the coast for both models in areas like the ice sheets, Gulf of Alaska, and Iceland.Accepted Author ManuscriptPhysical and Space Geodes