This session intends to showcase climate related studies which have made use of geodetic observations and or techniques.
Modern geodetic observing systems are sensitive to a wide range of changes in the Earth’s solid and fluid layers at very diverging spatial and temporal scales related to processes as, e.g., glacial isostatic adjustment, the terrestrial water cycle, ocean dynamics, sea-level and ice-mass balance. Geodetic observables are often compared with geophysical models, which helps to explain observations, evaluate simulations, and may potentially be used to improve simulations through techniques such as data assimilation.
We invite contributions utilizing geodetic data from e.g. altimetry, gravimetry (CHAMP, GRACE, GOCE and GRACE-FO), navigation satellite systems (GNSS and DORIS) or remote sensing techniques that are based on both passive (e.g. optical and multi/hyperspectral) and active (i.e., SAR) instruments. New approaches helping to separate and interpret the variety of geophysical signals present in observations are equally appreciated.
The session closely adheres to the ideas of the recently established Inter-Commission Committee on "Geodesy for Climate Research" (ICCC) of the International Association of Geodesy (IAG), which aims to encourage collaborations between the climate and geodetic community and promote the use of geodetic observations and principles while at the same time benefiting from climate expertise in the interpretation and correction of geodetic observations. We encourage authors to tailor their presentations to include non-geodetic scientists as their audience, and, with the author’s consent, highlights from this session will be tweeted in order to increase visibility.
vPICO presentations: Thu, 29 Apr
The Global Mean Sea Level (GMSL) is rising at a rate of 3.3 mm/year over the altimetry era but at regional scale the behaviour is quite different. In some regions, the sea level rates are up to 2-3 times the global mean rate. The mechanisms behind these discrepancies are explained through the differences in the processes that affect the sea level at different scales. The concept of budget is used to express the superposition of signals that contribute to the change in sea level. At regional scale, apart from the contributions from steric and ocean mass components which are also present in the GMSL budget, the budget is also affected by atmospheric loading component and the static factors component. The static terms (also called fingerprints) include solid Earth’s deformations and gravitational changes in response to mass redistributions caused by land ice melt and land water storage changes. The goal of this study is to detect the fingerprints of the static factors using satellite altimetry-based sea level grids corrected for steric and ocean mass effects. Our preliminary results show a statistically significant correlation between observed and modelled fingerprints in some regions of the oceanic basins.
How to cite: Moreira, L. and Cazenave, A.: Sea level fingerprints due to ongoing land ice melt in altimetry data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10950, https://doi.org/10.5194/egusphere-egu21-10950, 2021.
This study addresses mapping of Argo temperature and salinity profiles onto arbitrary positions using physically advanced statistical information from model fields, and their subsequent parametrization as function of depth. Argo suffers from spatio-temporal sampling problems, and some signals are not well captured, e.g. in the deeper ocean below 2000m, around the boundary currents, in the Arctic or in the shelf/coastal regions which are not frequently visited by floats. Mapping of Argo data into sparsely sampled areas would greatly benefit from additional physical information of coherent T/S behavior in form of covariance functions. Outputs from global general ocean circulation model FESOM1.4 provide covariance information for least squares collocation and also complement the spatially undersampled Argo data in high latitudes and in deep ocean. Additionally, model covariances are used to identify areas of strong correlation with interpolation points, so that only Argo measurements inside these areas are included in the mapping procedure. Parametrization of T/S profiles is performed with b-splines where the choice of knot locations is a trade-off between accuracy and overfitting. Proposed methodology is tested in South Atlantic, but can be extended to other regions.
How to cite: Yakhontova, A., Rietbroek, R., Stolzenberger, S., and Jonas, N.: A geodetic approach to Mapping and Parametrization of Argo Temperature and Salinity Profiles, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2828, https://doi.org/10.5194/egusphere-egu21-2828, 2021.
Temporal variations in the total ocean mass representing the barystatic part of present-day global-mean sea-level rise can be directly inferred from time-series of global gravity fields as provided by the GRACE and GRACE-FO missions. A spatial integration over all ocean regions, however, largely underestimates present-day rates as long as the effects of spatial leakage along the coasts of in particular Antarctica, Greenland, and the various islands of the Canadian Archipelago are not properly considered.
Based on the latest release 06 of monthly gravity fields processed at GFZ, we quantify (and subsequently correct) the contribution of spatial leakage to the post-processed mass anomalies of continental water storage and ocean bottom pressure. We find that by utilizing the sea level equation to predict spatially variable ocean mass trends out of the (leakage-corrected) terrrestial mass distributions from GRACE and GRACE-FO consistent results are obtained also from spatial integrations over ocean masks with different coastal buffer zones ranging from 400 to 1000 km. However, the results are critically dependent on coefficients of degree 1, 2 and 3, that are not precisely determined from GRACE data alone and need to be augemented by information from satellite laser ranging. We will particularly discuss the impact of those low-degree harmonics on the secular rates in global barystatic sea-level.
How to cite: Thomas, M., Dobslaw, H., Bagge, M., Dill, R., Klemann, V., Boergens, E., Dahle, C., and Flechtner, F.: Impact of Low-Degree Stokes Coefficients and Spatial Leakage on Barystatic Sea-Level Rise from GRACE/GRACE-FO, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11684, https://doi.org/10.5194/egusphere-egu21-11684, 2021.
The combined 18+ years long time series of observations of the Earth's gravity field from the satellite missions GRACE and GRACE-FO provides us with an unprecedented opportunity to analyse mass change and re-distribution in the Earth system. Furthermore, as the mission continues, we may also gain more insight into those types of variability in the water mass system that act over time scales of several years and possibly even decades.
For our analysis presented here, we updated the previous Ocean Mass Change (OMC) product by the ESA CCI Sea Level Budget Closure project, including (1) corrections for Glacial Isostatic Adjustment, (2) restorement of GAD background fields, (3) subtraction of atmospheric mean fields, and (4) replacement of dedicated low-degree coefficients for centre-of-mass, oblateness (TN14) and C30 (TN14) in the spherical harmonic gravity field solutions. We applied least-squares minimisation of the residual of a multi-parameter functional fit to the OMC series, including i.a. linear trend, semi-/annual signals, and an optional quadratic fit. We analysed the complete residual series based on the four monthly GRACE and GRACE-FO RL06 solutions from CSR/GFZ/JPL and ITSG-Grace2018 after removal of linear trend and seasonal cycles.
The remaining signal shows clear evidence of interannual oscillations and correlates (>0.5) with the Multivariate ENSO index (MEI). By spectral analysis and by an independent simulated-annealing approach, we locate several primary modes of the residual between 130 and 29 months. The phase of the lowest of these partial frequencies approximates that of solar flux data representing the solar cycle and the shortest major mode resembles the frequency of the Quasi Biennial Oscillation. However, minor phase-shifts and a direct physical link in this regard are not yet fully understood. When we include the extra modes in our OMC minimisation approach, it can be shown that recent acceleration in global ocean mass may indeed be smaller than previously anticipated by quadratic fitting while neglecting longer wavelengths.
Furthermore, the extrapolation of the fit including three prominent interannual modes between 29 and 130 months is able to predict recent La Niña related negative ocean mass anomalies. Our findings might support and integrate in similar analyses of the global sea level and other ECVs elsewhere. However, we must emphasise that an analysis of near-decadal oscillations from a sub-20 year lasting data set is yet to become more stable with increasing observation length from GRACE-FO.
How to cite: Gutknecht, B. D., Groh, A., and Horwath, M.: Interannual Variability in Global Ocean Mass Derived from 18+ Years of GRACE and GRACE-FO Satellite Gravimetry, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10433, https://doi.org/10.5194/egusphere-egu21-10433, 2021.
Space geodetic estimates of ocean bottom pressure (OBP) derived by several analysis centres are evaluated. To this end, an array of 14 in situ bottom pressure recorders has been deployed between South Africa and Antarctica. The continuous measurement period of four years (2011 to 2014) and a recorder spacing of roughly 2.8 degrees latitude allows an in-depth analysis of bottom pressure variability.
Our goal is to relate OBP from GRACE to in situ observations and detect which spatial and temporal features are reproduced. The recorders in the southern part of the transect generally tend to be in better agreement with GRACE and better reflect longer spatial scales of ocean bottom pressure. Over the vast expanse of the Antarctic Circumpolar Current annual and semi-annual cycles are weak (about 1cm equivalent water height (EWH)) and not reproduced well by GRACE. Variability in general amounts to a standard deviation of 2cm. This level is well captured and correlations on the order of 0.5 are found.
Mean values and trends of OBP cannot be identified due to the instrumental setup. Close to the Agulhas Retroflection, signals of up to 30cm EWH are found, which cannot be resolved by GRACE. Our analysis reveals: GRACE OBP possesses longer space and time scales than in situ OBP and it misses eddy-scale signals. Filtering with DDK4 appears to be preferable to DDK6.
How to cite: Schröter, J., Androsov, A., Lück, C., Übbing, B., Rietbroek, R., Danilov, S., and Kusche, J.: Evaluation of GRACE RL06 analysis in the Southern Ocean, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11978, https://doi.org/10.5194/egusphere-egu21-11978, 2021.
The German Research Centre for Geosciences (GFZ) maintains the “Gravity Information Service” (GravIS, gravis.gfz-potsdam.de) portal in collaboration with the Alfred-Wegener-Institute (AWI) and Technische Universität Dresden. Main objective of this portal is the dissemination of data describing mass variations in the Earth system based on observations of the satellite gravimetry missions GRACE and GRACE-FO.
The provided data sets encompass products of terrestrial water storage (TWS) variations over the continents, ocean bottom pressure (OBP) variations from which global mean barystatic sea-level rise can be estimated, and mass changes of the ice sheets in Greenland and Antarctica. All data sets are provided as time series of regular grids for each area, as well as in the form of regional basin averages. Regarding the latter, for the continental TWS data the user can choose between classical river basins and a novel segmentation based on climatic regions. For the oceans, the segmentation into different regions is derived similarly but based on modelled OBP data. All time series are accompanied by realistic uncertainty estimates.
All data sets can be interactively displayed at the portal and are freely available for download. This contribution aims to show the features and possibilities of the GravIS portal to researchers without a dedicated geodetic background, working in the fields of hydrology, oceanography, and cryosphere.
How to cite: Dahle, C., Boergens, E., Dobslaw, H., Groh, A., Sasgen, I., Reißland, S., and Flechtner, F.: The GravIS Portal: User-friendly Global Mass Variations from GRACE and GRACE-FO, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11069, https://doi.org/10.5194/egusphere-egu21-11069, 2021.
The acquisition of time-lapse satellite gravity measurements during the GRACE and GRACE Follow On (FO) missions revolutionized our understanding of the Earth system, through the accurate quantification of the mass transport at global and regional scales. Largely related to the water cycle, along with some geophysical signals, decadal trends and seasonal cycles dominate the mass transport signals, constituting about 80 % of the total variability measured during GRACE (FO) missions. We focus here on the interannual variability, constituting the remaining 20 % of the signal, once linear trends and seasonal signals have been removed. Empirical orthogonal functions (EOFs) highlight the most prominent signals, including short-lived signals triggered by major earthquakes, interannual oscillations in the water cycle driven by the El Nino Southern Oscillation (ENSO) and significant decadal variability, potentially related to the Pacific Decadal Oscillation (PDO). The interpretation of such signals remains however limited due to the arbitrary nature of the statistical decomposition in eigen values. To overcome these limitations, we performed a LASSO (Least Absolute Shrinkage and Selection Operator) regression of eight climate indices, including ENSO, PDO, NPGO (North Pacific Gyre Oscillation), NAO (North Atlantic Oscillation), AO (Arctic Oscillation), AMO (Atlantic Multidecadal Oscillation), SAM (Southern Annular Mode) and IOD (Indian Ocean Dipole). The LASSO regularization, coupled with a cross-validation, proves to be remarkably successful in the automatic selection of relevant predictors of the climate variability for any geographical location in the world. As expected, ENSO and PDO impact the global water cycle both on land and in the ocean. The NPGO is also a major actor of the global climate, showing similarities with the PDO in the North Pacific. AO is generally favored over NAO, especially in the Mediteranean Sea and North Atlantic. SAM has a preponderant influence on the interannual variability of ocean bottom pressures in the Southern Ocean, and, in association with ENSO, modulates the interannual variability of ice mass loss in West Antarctica. AMO has a strong influence on the interannual water cycle along the Amazon river, due to the exchange of moisture in tropical regions. IOD has little to no impact on the interannual water cycle. All together, climate modes generate changes in the water mass distribution of about 100 mm for land, 50 mm for shallow seas and 15 mm for oceans. Climate modes account for a secondary but significant portion of the total interannual variability (at maximum 60% for shallow seas, 50 % for land and 40% for oceans). While such processes are insufficient to fully explain the complex nature of the interannual variability of water mass transport on a global scale, climate modes can be used to correct the GRACE (FO) measurements for a significant part of the natural climate variability and uncover smaller signals masked by such water mass transports.
How to cite: Pfeffer, J., Cazenave, A., and Barnoud, A.: Analysis of the interannual variability in satellite gravity solutions : impact of climate modes on water mass displacements across continents and oceans, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2217, https://doi.org/10.5194/egusphere-egu21-2217, 2021.
The Upper East Region (UER) of Ghana, located between 10.2–11.2°N, 1.6°W–0.03°E, is characterised by a long dry season and annual floods that are exacerbated by the opening of the Bagre Dam in neighbouring Burkina Faso. The UER lies within the Volta Basin, which has been the subject of numerous hydrological studies. The basin spans several jurisdictions with varying meteorological conditions; thus, basin-wide studies may not truly reflect localised dynamics of water storage over the UER. Data from the Gravity Recovery and Climate Experiment (GRACE) mission and hydrological models, e.g., the Global Land Data Assimilation System (GLDAS), have been used for hydrological studies. Nonetheless, GRACE’s resolution may restrict its application to large areas (≥150,000 km2) or smaller areas with storage variations of ≥8 km3, while GLDAS does not model surface water. With this in mind, this research evaluates GRACE and GLDAS for water storage analysis over the UER (~9000 km2).
We used the latest mass concentration solution from the Centre for Space Research, GLDAS-NOAH, and the Global Precipitation Measurement (GPM) from April 2002 to June 2017. The long-term mean (2004–2009) was removed from GPM and NOAH. The GRACE time series was characterised by an increasing trend in terrestrial water storage anomalies (TWSA) (6.2 mm/yr), annual and semi-annual amplitudes of 99.4 mm and 10.5 mm, and annual and semi-annual phases of 39.1° and 13.6°, respectively. The minimum variation (-150.8 mm, -47.4 km3) in TWSA occurred in May 2003, while the maximum (222.3 mm, 69.9 km3) occurred in September 2012, both of which are during the rainy season. Rainfall anomalies showed a declining trend at a rate of 0.25 mm/yr. A Pearson correlation coefficient (r) between rainfall and TWSA revealed a low r = 0.30 (p-value << 0.01 ). Conversely, time-lagged r = 0.60, one and two months after rainfall. The largest (r = 0.66) occurred two months after rainfall. NOAH-based evapotranspiration anomalies (ETA) indicated a slow, but increasing, trend (0.4 mm/yr). Furthermore NOAH-derived TWSA underestimated storage, yielding a rate of decline of 2.1 mm/yr, which could be due to unmodelled surface water. However, NOAH-derived TWSA were comparatively strongly correlated with rainfall (r = 0.69 and 0.87 at lags 0 and 1). As rainfall is the only source of input to the water balance equation and as rates of ETA suggest conditions in the UER support water loss, these results may indicate a strong contribution to TWSA from the yet unmodelled water from the Bagre Dam.
This study was the first to investigate the impact of meteorological conditions on water availability in the UER using GRACE and GLDAS. The results show that GLDAS-NOAH underestimated storage, and that TWSA increased, although this increase is not entirely explained by rainfall. Subsequent experiments will incorporate the contribution of water from the Bagre Dam as well as other meteorological data (e.g., wind speed, humidity) to better explain the differences in those parameters and fully characterise the impact of meteorological conditions on water availability in the UER.
How to cite: Kelly, C., Hamm, N., Hancock, C., Grebby, S., and Marsh, S.: Examining water storage variations as a function of meteorology using GRACE and GLDAS, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3637, https://doi.org/10.5194/egusphere-egu21-3637, 2021.
We investigate the possibility to use the Low-Earth Orbiter mission well known as GRACE to detect sudden regional variations of water mass storage caused by heavy precipitation and flooding episodes caused by the passage of tropical hurricanes of categories 4-5 (from day to a week). For this purpose, daily water mass solutions are produced from along-track GRACE geopotential anomalies to catch the signatures of these intense meteorological events. These geopotential variations are derived from accurate inter-satellite K-Band Range Rate (KBRR) measurements made along the 5-second orbits by imposing the total energy conservation to the twin GRACE vehicles. The determination of these surface sources is made over a regional network of juxtaposed triangular tiles of quasi-constant areas, and they are refreshed by a Kalman filtering for integrating progressively daily geopotential observations. These latter data have been previously reduced from known gravitational effects of atmosphere and oceanic masses (including periodic tides) for isolating the continental hydrology contribution. Our estimates of regional hydrological impacts are also compared to the ones obtained by synthesis of daily degree-40 Stokes coefficients provided by ITSG, Graz.
How to cite: Ramillien, G., Seoane, L., and Darrozes, J.: Rapid extreme meteorological events detected by daily regional GRACE solutions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10179, https://doi.org/10.5194/egusphere-egu21-10179, 2021.
Climate models provide important information to understand how the climate has changed in the past and how it can evolve in the future. Such models simulate in detail the physics, chemistry and biology of the atmosphere, oceans and land hydrosphere. Climate models are developed and constantly updated by a number of modelling groups around the world. A large number of models makes it necessary to store them in one place, so that they can be easily accessed and compared. The objective of the Coupled Model Intercomparison Project phase 6 (CMIP6) is to make the multi-model output publicly available in a standardized format. This framework aims to improve our understanding of climate changes resulting from both natural factors and changes in radiative forcing. The CMIP6 models are useful in many scientific applications regarding evolution of processes occurring in the atmosphere, ocean and continental hydrosphere.
In this study, we use the chosen climate models to assess the role of land hydrosphere changes in polar motion. The mass variations of land water storage impacts the Earth’s inertia tensor and causes disturbances of the pole motion. Such temporal variations of polar motion due to continental hydrosphere are described with hydrological angular momentum (HAM). Here, we use soil moisture and snow water equivalent variables, which are delivered by CMIP6 simulations, to compute time series of HAM. We then analyse HAM variability in a wide variety of oscillations, taking into account trends, seasonal, short-term non-seasonal and long-term non-seasonal changes. We consider past changes in HAM but also analyse its future evolution. This will allow to determine how future changes in the terrestrial hydrosphere will affect the movement of the pole. The consistency between HAM obtained from various CMIP6 models is assessed as well.
How to cite: Nastula, J., Śliwińska, J., and Wińska, M.: Hydrological excitation of polar motion determined from CMIP6 climate models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5514, https://doi.org/10.5194/egusphere-egu21-5514, 2021.
Climate change will affect terrestrial water storage (TWS) during the next decades by impacting the seasonal cycle, interannual variations, and long-term linear trends. But how exactly will the variability change in the future? Reliable projections are needed not only for sensible water management but also as input for long-term performance studies of possible Next Generation Gravity Missions (NGGMs).
In this contribution, an ensemble of climate model projections provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6) covering the years 2002 – 2100 is utilized to assess possible changes in TWS variability. To demonstrate performance and identify shortcomings of the models we first compare modeled TWS to globally observed TWS from the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) in the time span 2002 – 2020. We then analyze changes in the variability of TWS from model projections until the end of the century and the consensus on such changes within the model ensemble.
Based on these projections, we find that present-day GRACE accuracies are sufficient to detect amplitude and phase changes in the seasonal cycle in one third of the land surface after 30 years of observation, whereas a five times more accurate NGGM mission could resolve such changes almost everywhere outside the most arid landscapes of our planet. We also select one individual model experiment out of the CMIP6 ensemble that closely matches both GRACE observations and the multi-model median of all CMIP6 realizations. This model run might serve as basis for multi-decadal satellite mission performance studies to demonstrate the suitability of NGGM satellite missions to monitor long-term climate variations in the terrestrial water cycle.
How to cite: Jensen, L., Eicker, A., Dobslaw, H., and Pail, R.: Land Water Storage Variabilities in GRACE and Climate Models – How do they compare and which future changes can we expect?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7129, https://doi.org/10.5194/egusphere-egu21-7129, 2021.
Hydrological loading deforms the Earth’s crust at various spatial and temporal resolutions. In this study, we compare hydrologically-induced Earth’s crust displacements computed for European area using GRACE (Gravity Recovery and Climate Experiment) observations and two hydrological models, namely: GLDAS (Global Land Data Assimilation) and WGHM (WaterGAP Global Hydrological Model), with Earth’s crust displacements observed by the GPS (Global Positioning System). For GRACE, we use displacements estimated from RL06 spherical harmonic solution up to degree and order 90, provided by the GFZ (German Research Center for Geosciences) and denoised using DDK3 filter. For the GPS, we utilize solution provided by the NGL (Nevada Geodetic Laboratory). Our study is performed twofold. First, hydrologically-induced displacements are retrieved for the largest river basins in Europe and then, these are estimated for the GPS locations. To estimate the seasonal and inter-annual (changes with periods longer than tropical year or aperiodic) changes, the Singular Spectrum Analysis (SSA) algorithm is used. We demonstrate that the largest seasonal displacements induced by hydrological changes are observed by GRACE for eastern European areas, which is also confirmed by hydrological models. Inter-annual displacements show large variations for GRACE-predicted displacements in southeastern European river basins, as Dnieper, Dniester, Don, Guadiana, Kuban, Tigris and Euphrates, Kura-Ozero Sevan and Volga. These displacements are higher than variations obtained for annual signals, what implies that inter-annual changes are more powerful than other signals. Inter-annual variations are, however, not prominent in GLDAS and WGHM models, proving that they are underestimated in model-predicted displacements (except of Kura-Ozero Sevan as well as Tigris and Euphrates river basins for WGHM). For central and eastern European river basins, smaller inter-annual displacements are observed by GRACE, but it is in agreement with GLDAS and WGHM models which also reveal similar changes. For 107 GPS permanent stations located in river basins used in this study, we compute correlation coefficients between annual, inter-annual and both-combined signals estimated with SSA for GPS displacements and models-/GRACE-predicted displacements. The greatest coefficients (40%-60%) are found for northern and western European river basins for GLDAS and GRACE, while for the WGHM model positive correlation is only found for inter-annual signals. Root-mean square (RMS) reduction of GPS displacements estimated once these are reduced by inter-annual signals estimated for models-/GRACE-observed displacements is between -20% and 20%. Our study reveals a need of including the hydrology-induced displacements in the analyses of GPS position time series, as their impact is observed for the longest periods, affecting the GPS velocity.
How to cite: Leszczuk, G., Klos, A., Kusche, J., Gerdener, H., Lenczuk, A., and Bogusz, J.: Inter-annual displacements induced by hydrological changes in Europe: comparison between hydrological models, GRACE and GPS , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7784, https://doi.org/10.5194/egusphere-egu21-7784, 2021.
We estimate change in total water and its components each month from January 2006 to the Present using geodetic observations from space and complementary hydrologic measurements. Estimates of changes in total water inferred from GPS elastic displacements are used to strengthen the spatial resolution of GRACE observations of mass change, resulting in sharper images of water change. We furthermore distinguish between different components of water change. Change in surface water in man's artificial reservoirs and natural lakes are known from gauging measurements of water levels. The distribution and magnitude of snow accumulation is inferred from sticks and scales on the ground. We remove the effect of surface water and snow to infer change in water in the ground, consisting of soil moisture and groundwater. This determination is bringing powerful insights into understanding the water cycle. We are finding more water to be lost during drought and gained during heavy precipitation than in the hydrology models, suggesting that the hydrology models must be revised to have a greater capacity to store water in the ground. Not all rain and melting snow that falls on the mountains of California, Oregon, and Washington is found to runoff into rivers taking water to the ocean. Rain and melting snow is instead found to infiltrate the ground in the wet fall and winter and and to be parched from the ground in the dry spring and summer.
How to cite: Argus, D., Wiese, D., Martens, H., Anderson, M., Peidou, A., Elmer, M., Borsa, A., Knappe, E., and Landerer, F.: Estimating water change at Earth's surface using GRACE gravity and GPS positioning: Inferring groundwater change in the United States, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8578, https://doi.org/10.5194/egusphere-egu21-8578, 2021.
GPS is emerging as an effective technique to estimate changes in total water storage at Earth's surface. In California's mountains, GPS indicates that more subsurface storage is lost during drought and gained during years of heavy precipitation than predicted by hydrology models [Argus et al. 2017]. Atmospheric rivers provide a majority of the annual precipitation in coastal environments across North America. The Russian River watershed is often affected by these large storms, which can produce extensive flooding events. In this study, we estimate changes in water storage for the 2017 water year (October 2016 – September 2017), a historically wet year in California, in which more than 20 atmospheric rivers impacted the Russian River watershed. Using GPS displacements, we quantify the water gained during higher intensity atmospheric rivers. We further resolve the time it takes for the storm water to dissipate: that is, we distinguish between water that runs off into rivers and water that is stored in the ground as soil moisture. Finally, we investigate the empirical relationships between GPS displacement and precipitation, evapotranspiration, and soil moisture estimates with the aim of improving constraints to hydrologic models.
How to cite: Knappe, E., Borsa, A., Martens, H., Argus, D., Hoylman, Z., Gardner, W. P., Wilson, A., and Ralph, M.: Tracking the storage and dissipation of atmospheric river storm water in the Russian River watershed using GPS elastic displacements, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9270, https://doi.org/10.5194/egusphere-egu21-9270, 2021.
The Global Positioning System (GPS) measures surface displacements in response to time-varying terrestrial water mass variations. Components of surface water storage include water in lakes and reservoirs, snow, and soil moisture. Groundwater depletion or recharge will also contribute to the overall water storage. Understanding the nature of the observed GPS displacements related to the continental water variations is important to help identify which compartment in the total water storage controls the water changes in any particular region. In this study, we demonstrate the potential of GPS to observe the surface displacements induced by groundwater variations in France. In-situ groundwater observations from boreholes in France are used to be compared with GPS displacements. Groundwater data are processed to obtain the Equivalent Water Height (EWH) and used to forward model surface deformation. Displacements predicted using EWH variations from the WaterGAP Global Hydrology Model (WGHM) will also be compared to the GPS displacements.
How to cite: Saraswati, A. T., Hsu, K.-H., van Dam, T., and Eicker, A.: Surface deformations observed by GPS and its relation to groundwater variations in France, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15146, https://doi.org/10.5194/egusphere-egu21-15146, 2021.
Glacial Isostatic Adjustment (GIA) and the hydrological cycle are both associated with mass changes, which are observed by GRACE, and vertical land motion (VLM), which is observed by GPS. Hydrology-related VLM results from the instantaneous response of the elastic solid Earth to surface loading by freshwater, whereas GIA-related VLM reveals the long-term response of the visco-elastic Earth mantle to past glacial cycles. Thus, observations of mass changes and VLM are interrelated and GIA and hydrology are difficult to investigate independently. Taking advantage of the differences in the spatio-temporal characteristics of the GIA and hydrology fields, we can separate the respective contributions of each process. In this work, we use a Bayesian Hierarchical Modelling (BHM) approach to provide a new data-driven estimate of GIA and time-evolving hydrology-related VLM for North America. We detail our processing strategy to prepare the input data for the BHM while preserving the content of the original observations. We discuss the separation of GIA and hydrology processes from a statistical and geophysical point of view. Finally, we assess the reliability of our estimates and compare our results to the latest GIA and hydrological models. Specifically, we compare our GIA solution to a forward-model global field, ICE-6G, and a recent GIA estimate developed for North America (Simon et al. 2017). Our time-evolving hydrology field is compared with WaterGAP, a global water balance model. Overall, for both GIA and hydrology, there is a good agreement between our results and the forward models, but we also find differences which possibly highlight deficiencies in these models.
How to cite: Ziegler, Y., Vishwakarma, B. D., Brady, A., Chuter, S., Royston, S., Westaway, R., and Bamber, J.: Data-driven estimate of past and present surface loading over North America: Bayesian Hierarchical Modelling approach applied to GPS and GRACE observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11055, https://doi.org/10.5194/egusphere-egu21-11055, 2021.
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