G3.1

At the level of a watershed, the conservation of mass imposes that the net moisture transport through the atmospheric boundaries is balanced by the river discharge and an accumulation/depletion in terrestrial sources such as the soil, surface waters and groundwater.

There are considerable uncertainties connected with modelled water balance components, especially since most models only simulate part of the system: either the atmosphere, the surface or the subsurface. Uncertainties in boundary conditions propagate as biases in the simulated results. For example, not accounting for anthropogenic groundwater extraction potentially introduces biases in arid regions, where groundwater is a non-negligible source of moisture for the atmosphere. The use of observations is therefore an important aid to evaluate model performances and to detect possible biases in water balance components.

In this contribution, we compare total water storage changes derived from the Gravity Recovery Climate Experiment (GRACE) and its follow-on mission, with modelled components of the water balance. We use ERA5 reanalysis data to compute (net) atmospheric transports, and river discharge from GloFAS (Global Flood Awareness System). Furthermore, we use precipitation estimates (e.g. from GPCC) together with evapotranspiration from the Surface Energy Balance System (SEBS). We finally perform an accounting of the water balance components for the world’s largest watersheds and show to what extent we can find agreements, inconsistencies and biases in the data and models.

How to cite: Rietbroek, R., Penning de Vries, M., Zeng, Y., and Su, B.: Closing the water balance of large watersheds using satellite gravimetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3734, https://doi.org/10.5194/egusphere-egu22-3734, 2022.

Continuous monitoring of the Global Terrestrial Water Storage changes (TWS) is challenging because of the large surface of continents and the variety of storage compartments (WCRP, 2018). The only observing system which provides global TWS mass change estimates so far is space gravimetry. Unfortunately, most storage compartments (lakes, groundwater, glaciers…) are too small to be resolved given the current spatial resolution of gravimetry missions. This intrinsic property makes gravimetry-based TWS changes estimates difficult to attribute and to interpret at individual basin scale.

In this context, combining gravimetry-based TWS estimates with other sources of information with higher spatial resolution is a promising strategy. In this study, we combine gravimetry data with independent observations from satellite altimetry and high resolution visible imagery to derive refined estimates of the TWS changes in hydrological basins containing lakes and glaciers (See Data used). The combination consists in including independent observations of glacier (Hugonnet et al., 2021) and lake (Cretaux et al., 2016) mass changes in the conversion process from gravity L2 data to water mass changes data. The combination is done for all regions of the world on a monthly basis.

This approach allows to split properly glacier and TWS changes at interannual to decadal time scales, and derive glacier-free estimates of TWS in the endorheic basins and the exorheic basins. We find that for the period from 2002 to 2020, the total TWS trend of 0.23±0.25 mm SLE/yr is mainly due to a mass loss in endorheic basins TWS of 0.20±0.12 mm SLE/yr. Over the same period, exorheic basins present a non-significative trend of 0.03±0.14 mm SLE/yr. On the contrary, the interannual variability in the TWS change of 4 mm SLE is mainly due to the exorheic basins TWS change.

How to cite: Blazquez, A., Berthier, E., Meyssignac, B., Longuevergne, L., and Crétaux, J.-F.: Combining space gravimetry observations with data from satellite altimetry and high resolution visible imagery to resolve mass changes of endorheic basins and exorheic basins., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8525, https://doi.org/10.5194/egusphere-egu22-8525, 2022.

Observed time-series of water transport in rivers can be perceived mathematically as a superposition of non-linear long-term trends, periodic variations, episodic events, colored instrument noise, and other components. Various statistical methods are readily available to extract and quantify both stationary and non-stationary components in order to subsequently attribute parts of the signal to underlying causal mechanisms. However, the available algorithms differ vastly in terms of computational complexity and implicit assumptions, and may thus have their own individual advantages and disadvantages. By employing a suite of time-series analysis methods for 1D (Wavelets, Singular Spectrum Analysis, Empirical Mode Decomposition) and additional statistical assessments like Pruned Exact Linear Time (PELT) tests for change point detection, we will analyze data from two virtual stations at Elbe River (Germany) and Urmia Lake (Iran) that are representative for the central European region with a rather humid climate, and the more arid conditions of Central Asia with much smaller hydrological signal variations, respectively. It is in particular the latter region with a much less developed in situ hydrometeorological observing system, where we expect that carefully processed geodetic data might contribute most to the monitoring of large-scale terrestrial water dynamics. This contribution will highlight the benefits of more advanced signal analysis methods for extracting relevant hydrometeorological information over more conventionally applied algorithms.

How to cite: Iran Pour, S., Eicker, A., Balidakis, K., Karimi, H., Amiri-Simkooei, A., and Dobslaw, H.: Efficiency of different signal processing methods to isolate signature characteristics in altimetric water level measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1449, https://doi.org/10.5194/egusphere-egu22-1449, 2022.

To assess realistic climate change mitigation strategies, it is important to research and understand the global carbon cycle. Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. Their atmospheric concentrations are affected by anthropogenic emissions as well as exchange fluxes with oceans and the terrestrial biosphere. For the prediction of future atmospheric CO2 and CH4 concentrations, it is critical to understand how the natural exchange fluxes respond to a changing climate. One of the factors that impact these fluxes is the changing hydrological cycle.        
In our project, we combine information about the hydrological cycle from geodetic satellites (e.g. GRACE & GRACE-FO) with carbon cycle observations from other satellites (e.g. TROPOMI & OCO-2). Specifically, we plan to investigate the impact of a changing water level in soils on CH4 emissions from wetlands and on the photosynthetic CO2 uptake of plants. Details of our approach and first results will be presented.

How to cite: Klemme, A., Warneke, T., Bovensmann, H., Weigelt, M., Müller, J., Notholt, J., and Lämmerzahl, C.: Using satellite geodesy for carbon cycle research, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7583, https://doi.org/10.5194/egusphere-egu22-7583, 2022.

Global and interactively coupled climate models are important tools for projecting future climate conditions. Even though the quality and reliability of such models has increased during the most recent years, large model uncertainties still exist for various climate elements, so that it is crucial to continuously evaluate them against independent observations. Changes in the distribution and availability of terrestrial water storage (TWS), which can be measured by the satellite gravimetry missions GRACE and GRACE-FO, represent an important part of the climate system in general, and the terrestrial water cycle in particular. However, the use of satellite gravity data for the evaluation of interactively coupled climate models has only very recently become feasible. Challenges mainly arise from large model differences with respect to land water storage-related variables, from conceptual discrepancies between modeled and observed TWS, and from the still rather short time series of satellite data.

This presentation will highlight the latest results achieved from our ongoing research on climate model evaluation based on the analysis of an ensemble of models taking part in the Coupled Model Intercomparison Project Phase 6 (CMIP6). We will focus on long-term wetting and drying conditions in TWS, by deriving several hot spot regions of common trends in GRACE/-FO observations and regions of large model consensus. However, as the observational record currently only covers about 20 years, observed trends may still be obscured by natural climate variability. Therefore, to further attribute the wetting or drying in the identified hot spot regions to either interannual/decadal variability or anthropogenic climate change, we investigate the influence of dedicated climate modes (such as ENSO, PDO, AMO etc.) on TWS variability and trends. Furthermore, we perform a numerical model investigation with 250 years of CMIP6 TWS data to quantify the degree to which trends computed over differently long time intervals can be expected to represent long-term trends, and to discriminate regions of rather robust trends from regions of large fluctuations in the trend caused by decadal climate variability.

How to cite: Jensen, L., Eicker, A., and Dobslaw, H.: Attributing land water storage trends from satellite gravimetry to long-term wetting and drying conditions with global climate models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2335, https://doi.org/10.5194/egusphere-egu22-2335, 2022.

Satellite gravity missions are unique observation systems to directly observe mass transport processes in the Earth system. Since 2000, CHAMP, GRACE, GOCE, and GRACE-FO have almost continuously been observing Earth’s mass changes and have improved our understanding of large-scale processes such as the global water cycle, melting of continental ice sheets and mountain glaciers, changes in ocean mass that are closely related to the mass-related component of sea-level rise, which are subtle indicators of climate change, on global to regional scale. The existing observation record of more than two decades is already closing in on the minimum time series of 30 years needed to decouple natural and anthropogenic forcing mechanisms according to the Global Climate Observing System (GCOS).

Next Generation Gravity Missions (NGGMs) are expected to be implemented in the near future to continue the observation record. The Mass-change And Geoscience International Constellation (acronym: MAGIC) is a joint investigation of ESA with NASA’s MCDO study resulting in a jointly accorded Mission Requirements Document (MRD) responding to global user community needs. These NGGM concepts have set high anticipation for enhanced monitoring capabilities of mass transports in the Earth’s system with significantly improved spatial and temporal resolution. They will allow an evaluation of long-term trends within the Terrestrial Water Storage (TWS), which was adopted as a new Essential Climate Variable in 2020.

This study is based on modeled mass transport time series of components of the TWS, obtained from future climate projections until the year 2100 following the shared socio-economic pathway scenario 5-8.5 (SSP5-8.5). It evaluates the recoverability of long-term climate trends, annual amplitude, and phase of the TWS employing closed-loop numerical simulations of different current and NGGM concepts up to a spatial resolution of 250 km (Spherical Harmonic Degree 80). The assumed satellite constellations are GRACE-type in-line single-pair missions and Bender double-pair missions with realistic noise assumptions for the key payload and ocean-tide background model errors. In the interpretation and discussion of the results, special emphasis will be given on the dependence of the length of the measurement time series and the quantification of the robustness of the derived trends, systematic changes, as well as possibilities to improve the trend parameterization.

How to cite: Schlaak, M., Pail, R., Jensen, L., and Eicker, A.: Closed Loop Simulations on Recoverability of Climate-Related Mass Transport Signals in Current and Next-Generation Satellite Gravity Missions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8529, https://doi.org/10.5194/egusphere-egu22-8529, 2022.

Drought has struck the southwest U.S. for the fourth time this millennium, reducing freshwater available to agriculture and urban centers.  We are bringing new insight by quantifying change in water in the ground using GPS elastic displacements, GRACE gravity, artificial reservoir levels, and snow models. Precipitation in Water Year 2021 was half of normal; the rise in total water in autumn and winter is 1/3 of the seasonal average (estimated using chiefly GPS); water was parched from the ground in the spring and summer, bringing water in the ground to its historic low (estimated using primarily GRACE).  In the Central Valley, soil moisture plus groundwater each year increases by 11 km3 and is maximum in April.  Only half of groundwater lost during periods of drought is replenished in subsequent years of heavy precipitation.  The Central Valley has lost groundwater at 2 km3/year from 2006 to 2021, with 2/3 of the loss coming from the southern Valley.

How to cite: Argus, D., Martens, H., Borsa, A., Wiese, D., Knappe, E., Larochelle, S., Anderson, M., Peidou, A., Khatiwada, A., Lau, N., White, A., Hoylman, Z., Swarr, M., Cao, Q., Pan, M., Chanard, K., Avouac, J.-P., Payton, G., and Landerer, F.: Intensifying hydrologic drought in California, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6800, https://doi.org/10.5194/egusphere-egu22-6800, 2022.

Global Navigation Satellite System (GNSS) networks in South Africa indicate a spatially coherent uplift. The cause of this uplift is not clear, but one hypothesis is a crustal deformation due to mantle flow and dynamic topography (Hammond et al., 2021, JGR Solid Earth). We provide an alternative evidence based on elastic loading modelling and independent observations, suggesting that land water loss due to multiple drought periods is a dominant driver of land uplift in South Africa.

The use of continuously measuring GNSS stations has proven to be a successful method for quantifying terrestrial water mass changes, by inverting the observed vertical displacements of the Earth’s crust. Depending on the density of the GNSS network, this method has the potential to derive not only temporal but also spatial higher-resolution total water storage change (TWSC) than the Gravity and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. Since vertical displacements in GNSS data are not only affected by water mass changes, extensive time series analyses are required to reduce or eliminate non-hydrology-related deformations, such as non-tidal oceanic and atmospheric loading. In this way, GNSS also offers an alternative method to monitor the frequently occurring droughts in South Africa, like the severe “Day Zero” drought in Cape Town from 2015-2017.

In this study, daily GNSS time series of vertical displacements (2000-present) are analysed. A long-term trend as well as annual and semi-annual signals are separated from the noisy observations using Singular Spectral Analysis (SSA). The final time series of all stations are inverted into water mass loading over a uniform grid, with the deformation properties of the Earth’s crust being defined by the Preliminary Reference Earth Model (PREM). An experimental approach shows that a 2° x 2° grid resolution of the GNSS-derived TWSC provides appropriate solutions over most of South Africa. The GNSS solution agrees with a GRACE-assimilated solution and a hydrological model at monthly scale over different provinces, with correlations up to 93% and 94%, respectively. The long-term trend averaged over the entire country is correlated with 80% and 54%, respectively. Negative long-term TWSC trends are evident in all data sets and provide compelling evidence that long-term land uplift in South Africa has a hydrological origin.

How to cite: Mielke, C., Karegar, M., Gerdener, H., and Kusche, J.: GNSS observations of the land uplift in South Africa: Implication for water loss estimation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10152, https://doi.org/10.5194/egusphere-egu22-10152, 2022.

Surface loading on GNSS stations in Africa

Usifoh Saturday E^1,2,3, Nhung Le Thi^1,2, Benjamin Männel¹, Pierre Sakic¹, Dodo Joseph³, Harald Schuh^1,2
1GFZ German Research Centre for Geosciences, Potsdam, Germany, ²Institut für Geodäsie und Geoinformationstechnik Technische Universität, Berlin, Germany, ³Centre for Geodesy and Geodynamics, Toro, Bauchi State, Nigeria.

 Corresponding author: parker@gfz-potsdam.de

Abstract

The global navigation satellite systems (GNSS) have revolutionalized the ability to monitor the Earth’s system related to different types of natural processes. This includes tectonic and volcanic deformation, earthquake-related displacements, redistribution of oceanic and atmospheric mass, and changes in the continental water storage. As loading affects the GNSS cordinates, we investigated the effect and assessed the impact of applying dedicated corrections provided by the Earth System Modeling group of German Research Center for Geosciences (GFZ). However, loading caused by mass redistribution results in displacement, predominantly with seasonal periods. Significant temporal changes in mass redistribution (e.g caused by climate change) will result to further trends in the station coordinate time series.

In this contribution, we will compare the PPP coordinate time series with the loading-corrected PPP time series by looking at the amplitude and the correlation between the GNSS time series and the model corrections. Also we will compare the PPP coordinate time series with the loading time series by assessing the RMS reduction and change of amplitude.The result shows that loading-induced displacement varies considerably among GNSS stations and applying corrections to the derived time series has favourable impacts on the reduction in the non-linear motion in GNSS height time series of the African stations.

How to cite: Usifoh, S. E., Le, T. N., Männel, B., Sakic, P., Joseph, D., and Schuh, H.: Surface loading on GNSS stations in Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-64, https://doi.org/10.5194/egusphere-egu22-64, 2022.

The Federal Office of Metrology and Surveying (BEV) in Austria is responsible for the geodetic reference system like gravity and height reference frame. Some of these gravity reference stations are monitored regularly by different geodetic terrestrial techniques. The gravity data on some stations show variations and/or changes in gravity. In this presentation, the alpine geodetic reference stations Obergurgl and Franz-Josefs- Höhe in the Austrian eastern Alps will be presented. Both stations are investigated with different geodetic terrestrial techniques in a cooperation of the University of Luxemburg with BEV.

Global warming and associated climate change during the last century and recent decades are among the main reasons for glacier retreat in the Alps. Absolute gravity measurements have been regularly performed in the Austrian Eastern Alps since 1987 in the Ötztal Valley at Obergurgl. In addition, absolute gravity has been regularly observed at Obergurgl from 1987 to 2009 with the absolute gravimeter JILAg6. From 2010, the absolute gravity measurements were continued with the highest accurate absolute gravimeters FG5 from BEV and FG5x from University of Luxemburg. The newest gravity data show again a small increase of gravity. Additionally, a permanent GNSS station was established in 2019 to record information about the assumed vertical uplift at this station.

A second alpine research station was established near the Pasterze Glacier at Großglockner Mountain in 2019. The Pasterze Glacier is one of the largest glaciers in the eastern Alps and is in the vicinity of the highest mountain of Austria, the Großglockner. The station is monitored by repeated absolute gravity measurements and is equipped with a permanent GNSS station. In addition, precise leveling measurements were also tied to this station. In this contribution, initial results of the geodetic research like the gravity results, precise leveling and GNSS measurements will be presented. In the future, gravity data will be quantitively compared to ice mass balance information derived from glacier inventories. A Geodetic Global Navigation Satellite System reflectometry (GNSS-R) antenna will also be installed to study glacier-ice change. A third station at an altitude of 3300 m is planned and will be checked for operating absolute gravity measurements there. The geodynamical processes like vertical uplift and postglacial deformation will be investigated together with glacier retreat on these stations.

How to cite: Ullrich, C., Francis, O., Tabibi, S., and Titz, H.: Geodetic climate research in the Austrian Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9943, https://doi.org/10.5194/egusphere-egu22-9943, 2022.

Earth's visible environmental changes, both natural and man-made, are influencing climate change on a global scale. For this reason, it is necessary to continuously monitor these changes and study the impact of human activities on them. One of the parameters indicating climate change is the systematic increase in temperature for the last 80 years. It causes more evaporation of water from natural and artificial water bodies. Consequently, the water content in the atmosphere is also increasing. Precipitable water is therefore one of the most important parameters when studying climate change. 

The aim of this study was to analyze long-term precipitation water data from a dense GNSS network over Poland. Twelve-year observations from over a hundred ASG-EUPOS stations were used to estimate changes in precipitation water values. These data were verified by comparison with available radio sounding data. Analysis of GPS-based PW values showed a clear increasing trend in PW values by 0.078 mm/year. The spatial-temporal distribution of mean PW values and their fluctuations over the years have been investigated. The obtained results confirm the fact that Poland lies on the border of continental and oceanic climate influence, and are in agreement with climate research concerning this region. 

How to cite: Araszkiewicz, A., Mierzwiak, M., Kiliszek, D., Nowak Da Costa, J., and Szołucha, M.: GPS-based multi-annual variation of the precipitable water over Poland territory, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7081, https://doi.org/10.5194/egusphere-egu22-7081, 2022.

In recent years, the detection and correction of the non-natural irregularities in the long climatic records, so-called homogenization, has been studied. This work is motivated by the problem of identification of origins of the breakpoints in the segmentation of difference series (difference between a candidate series and a reference series). Several segmentation methods have been developed for the difference series, but many of them assume that the reference series is homogenous. However, the homogeneity of the reference series, in reality, is uncertain and unproven. In our study, we applied the segmentation method GNSSseg (Quarello et al., 2020) on the difference between the Integrated water vapour estimates of the CODE REPRO2015 GNSS data set and the ERA5 reanalysis. About 36.5% of change points can be validated from the GPS metadata, and the origins of the remaining 64.5% are questionable (Nguyen et al., 2021). The ambiguity can be leveraged when there is at least one nearby GPS station with respect to which the candidate series can be compared. The proposed method uses weighted t-tests combining the candidate GPS and ERA series and their homologues (denoted GPS' and ERA') from each nearby station. If sufficient consistency emerges from the six tests for all the nearby stations, a decision can be made whether the breakpoint detected in the candidate GPS-ERA series is due to GPS or, alternatively, to ERA. For each quadruplet (GPS, ERA, GPS', ERA'), six t-tests are performed, and the outcomes are combined. In a set of 81 globally distributed GNSS time series spanning more than 25 years, 56 series have at least one nearby station, where 171 breakpoints are detected in segmentation, in which 136 breakpoints are attributed to the GPS. Among those, 94 breakpoints have consistent results between all the nearby stations. GPS-related breakpoints are used for the correction of the mean shift in the difference series. The impact of the breakpoint correction on the GNSS IWV trend estimates is then evaluated. 

Quarello A, Bock O, & Lebarbier E. (2020). A new segmentation method for the homogenisation of GNSS-derived IWV time-series. arXiv: Methodology.

Nguyen KN, Quarello A, Bock O, Lebarbier E. Sensitivity of Change-Point Detection and Trend Estimates to GNSS IWV Time Series Properties. Atmosphere. 2021; 12(9):1102. https://doi.org/10.3390/atmos12091102

How to cite: Nguyen, K. N., Bock, O., and Lebarbier, E.: A new method for the attribution of breakpoints in segmentation of IWV difference time series, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6390, https://doi.org/10.5194/egusphere-egu22-6390, 2022.