06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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Item Open Access A novel spatial filter to reduce north-south striping noise in GRACE spherical harmonic coefficients(2022) Yi, Shuang; Sneeuw, NicoPrevalent north-south striping (NSS) noise in the spherical harmonic coefficient products of the satellite missions gravity recovery and climate experiment greatly impedes the interpretation of signals. The overwhelming NSS noise always leads to excessive smoothing of the data, allowing a large room for improvement in the spatial resolution if this particular NSS noise can be mitigated beforehand. Here, we put forward a new spatial filter that can effectively remove NSS noise while remaining orthogonal to physical signals. This new approach overcomes the limitations of the previous method proposed by Swenson and Wahr (2006), where signal distortion was large and high-order coefficients were uncorrectable. The filter is based on autocorrelation in the longitude direction and cross-correlation in the latitude direction. The NSS-type noise identified by our method is mainly located in coefficients of spherical harmonic order larger than about 20 and degree beyond 30, spatially between latitudes ± 60°. After removing the dominating NSS noise with our method, a weaker filter than before is added to handle the residual noise. Thereby, the spatial resolution can be increased and the amplitude damping can be reduced. Our method can coincidentally reduce outliers in time series without significant trend bias, which underpins its effectiveness and reliability.Item Open Access Downscaling GRACE total water storage change using partial least squares regression(2021) Vishwakarma, Bramha Dutt; Zhang, Jinwei; Sneeuw, NicoThe Gravity Recovery And Climate Experiment (GRACE) satellite mission recorded temporal variations in the Earth’s gravity field, which are then converted to Total Water Storage Change (TWSC) fields representing an anomaly in the water mass stored in all three physical states, on and below the surface of the Earth. GRACE provided a first global observational record of water mass redistribution at spatial scales greater than 63000 km2. This limits their usability in regional hydrological applications. In this study, we implement a statistical downscaling approach that assimilates 0.5° × 0.5° water storage fields from the WaterGAP hydrology model (WGHM), precipitation fields from 3 models, evapotranspiration and runoff from 2 models, with GRACE data to obtain TWSC at a 0.5° × 0.5° grid. The downscaled product exploits dominant common statistical modes between all the hydrological datasets to improve the spatial resolution of GRACE. We also provide open access to scripts that researchers can use to produce downscaled TWSC fields with input observations and models of their own choice.Item Open Access A probabilistic approach to characterizing drought using satellite gravimetry(2024) Saemian, Peyman; Tourian, Mohammad J.; Elmi, Omid; Sneeuw, Nico; AghaKouchak, AmirIn the recent past, the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its successor GRACE Follow‐On (GRACE‐FO), have become invaluable tools for characterizing drought through measurements of Total Water Storage Anomaly (TWSA). However, the existing approaches have often overlooked the uncertainties in TWSA that stem from GRACE orbit configuration, background models, and intrinsic data errors. Here we introduce a fresh view on this problem which incorporates the uncertainties in the data: the Probabilistic Storage‐based Drought Index (PSDI). Our method leverages Monte Carlo simulations to yield realistic realizations for the stochastic process of the TWSA time series. These realizations depict a range of plausible drought scenarios that later on are used to characterize drought. This approach provides probability for each drought category instead of selecting a single final category at each epoch. We have compared PSDI with the deterministic approach (Storage‐based Drought Index, SDI) over major global basins. Our results show that the deterministic approach often leans toward an overestimation of storage‐based drought severity. Furthermore, we scrutinize the performance of PSDI across diverse hydrologic events, spanning continents from the United States to Europe, the Middle East, Southern Africa, South America, and Australia. In each case, PSDI emerges as a reliable indicator for characterizing drought conditions, providing a more comprehensive perspective than conventional deterministic indices. In contrast to the common deterministic view, our probabilistic approach provides a more realistic characterization of the TWS drought, making it more suited for adaptive strategies and realistic risk management.Item Open Access Forecasting next year's global land water storage using GRACE data(2024) Li, Fupeng; Kusche, Jürgen; Sneeuw, Nico; Siebert, Stefan; Gerdener, Helena; Wang, Zhengtao; Chao, Nengfang; Chen, Gang; Tian, KunjunExisting approaches for predicting total water storage (TWS) rely on land surface or hydrological models using meteorological forcing data. Yet, such models are more adept at predicting specific water compartments, such as soil moisture, rather than others, which consequently impedes accurately forecasting of TWS. Here we show that machine learning can be used to uncover relations between nonseasonal terms of Gravity Recovery and Climate Experiment (GRACE) derived total water storage and the preceding hydrometeorological drivers, and these relations can subsequently be used to predict water storage up to 12 months ahead, and even exceptional droughts on the basis of near real‐time observational forcing data. Validation by actual GRACE observations suggests that the method developed here has the capability to forecast trends in global land water storage for the following year. If applied in early warning systems, these predictions would better inform decision‐makers to improve current drought and water resource management.Item Open Access Analytical solutions for gravitational potential up to its third-order derivatives of a tesseroid, spherical zonal band, and spherical shell(2023) Deng, Xiao-Le; Sneeuw, NicoThe spherical shell and spherical zonal band are two elemental geometries that are often used as benchmarks for gravity field modeling. When applying the spherical shell and spherical zonal band discretized into tesseroids, the errors may be reduced or cancelled for the superposition of the tesseroids due to the spherical symmetry of the spherical shell and spherical zonal band. In previous studies, this superposition error elimination effect (SEEE) of the spherical shell and spherical zonal band has not been taken seriously, and it needs to be investigated carefully. In this contribution, the analytical formulas of the signal of derivatives of the gravitational potential up to third order (e.g., V , Vz, Vzz, Vxx, Vyy, Vzzz, Vxxz, and Vyyz) of a tesseroid are derived when the computation point is situated on the polar axis. In comparison with prior research, simpler analytical expressions of the gravitational effects of a spherical zonal band are derived from these novel expressions of a tesseroid. In the numerical experiments, the relative errors of the gravitational effects of the individual tesseroid are compared to those of the spherical zonal band and spherical shell not only with different 3D Gauss–Legendre quadrature orders ranging from (1,1,1) to (7,7,7) but also with different grid sizes (i.e., 5∘×5∘, 2∘×2∘, 1∘×1∘, 30′×30′, and 15′×15′) at a satellite altitude of 260 km. Numerical results reveal that the SEEE does not occur for the gravitational components V , Vz, Vzz, and Vzzzof a spherical zonal band discretized into tesseroids. The SEEE can be found for the Vxxand Vyy, whereas the superposition error effect exists for the Vxxzand Vyyzof a spherical zonal band discretized into tesseroids on the overall average. In most instances, the SEEE occurs for a spherical shell discretized into tesseroids. In summary, numerical experiments demonstrate the existence of the SEEE of a spherical zonal band and a spherical shell, and the analytical solutions for a tesseroid can benefit the investigation of the SEEE. The single tesseroid benchmark can be proposed in comparison to the spherical shell and spherical zonal band benchmarks in gravity field modeling based on these new analytical formulas of a tesseroid.Item Open Access Current availability and distribution of Congo Basin’s freshwater resources(2023) Tourian, Mohammad J.; Papa, Fabrice; Elmi, Omid; Sneeuw, Nico; Kitambo, Benjamin; Tshimanga, Raphael M.; Paris, Adrien; Calmant, StéphaneThe Congo Basin is of global significance for biodiversity and the water and carbon cycles. However, its freshwater availability and distribution remain relatively unknown. Using satellite data, here we show that currently the Congo Basin’s Total Drainable Water Storage lies within a range of 476 km 3 to 502 km 3 , unevenly distributed throughout the region, with 63% being stored in the southernmost sub-basins, Kasaï (220-228 km 3 ) and Lualaba (109-169 km 3 ), while the northern sub-basins contribute only 173 ± 8 km 3 . We further estimate the hydraulic time constant for draining its entire water storage to be 4.3 ± 0.1 months, but, regionally, permanent wetlands and large lakes act as resistors resulting in greater time constants of up to 105 ± 3 months. Our estimate provides a robust basis to address the challenges of water demand for 120 million inhabitants, a population expected to double in a few decades.Item Open Access High-dimensional experiments for the downward continuation using the LRFMP algorithm(2024) Schneider, Naomi; Michel, Volker; Sneeuw, NicoTime-dependent gravity data from satellite missions like GRACE-FO reveal mass redistribution in the system Earth at various time scales: long-term climate change signals, inter-annual phenomena like El Niño, seasonal mass transports and transients, e. g. due to earthquakes. For this contemporary issue, a classical inverse problem has to be considered: the gravitational potential has to be modelled on the Earth’s surface from measurements in space. This is also known as the downward continuation problem. Thus, it is important to further develop current mathematical methods for such inverse problems. For this, the (Learning) Inverse Problem Matching Pursuits ((L)IPMPs) have been developed within the last decade. Their unique feature is the combination of local as well as global trial functions in the approximative solution of an inverse problem such as the downward continuation of the gravitational potential. In this way, they harmonize the ideas of a traditional spherical harmonic ansatz and the radial basis function approach. Previous publications on these methods showed proofs of concept. In this paper, we report on the progress of our developments towards more realistic scenarios. In particular, we consider the methods for high-dimensional experiment settings with more than 500 000 grid points which yields a resolution of 20 km at best on a realistic satellite geometry. We also explain the changes in the methods that had to be done to work with such a large amount of data.