G3.1

EDI
Geodesy for Climate Research

This session invites innovative Earth system and climate studies based on geodetic measuring techniques. Modern geodetic observing systems document 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 and ice-mass balance. Different time spans of observations need to be cross-compared and combined to resolve a wide spectrum of climate-related signals. Geodetic observables are also often compared with geophysical models, which helps to explain observations, evaluate simulations, and finally merge measurements and numerical models via data assimilation.
We appreciate contributions utilizing geodetic data from diverse geodetic satellites including altimetry, gravimetry (CHAMP, GRACE, GOCE and GRACE-FO), navigation satellite systems (GNSS and DORIS) or remote sensing techniques that are based on both passive (i.e., optical and hyperspectral) and active (i.e., SAR) instruments. We welcome studies that cover a wide variety of applications of geodetic measurements and their combination to observe and model Earth system signals in hydrological, ocean, atmospheric, climate and cryospheric sciences. Any new approaches helping to separate and interpret the variety of geophysical signals are equally appreciated. Contributions working towards any of the goals of the Inter-Commission Committee on "Geodesy for Climate Research" (ICCC) of the International Association of Geodesy (IAG) are also welcomed in this session.
With author consent, highlights from this session will be tweeted with a dedicated hashtag during the conference in order to increase the impact of the session.

Including G Division Outstanding ECS Award Lecture
Co-organized by CL5.2/CR2/OS4
Convener: Anna KlosECSECS | Co-conveners: Roelof Rietbroek, Carmen Boening, Henryk Dobslaw, Vincent HumphreyECSECS
Presentations
| Fri, 27 May, 10:20–11:47 (CEST), 13:20–14:37 (CEST)
 
Room -2.16

Presentations: Fri, 27 May | Room -2.16

Chairpersons: Anna Klos, Eva Boergens
10:20–10:30
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EGU22-12642
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solicited
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G Division Outstanding ECS Award Lecture
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Presentation form not yet defined
Kristel Chanard

Understanding how the Earth’s shape, gravity field and rotation change in response to shifting hydrological, atmospherical and oceanic mass loads at its surface has great potential for monitoring the evolving climate. Recent advances in the field, namely hydrogeodesy, have required hand-in-hand development and improvement of the observing techniques and of our understanding of the solid Earth-climate interactions. 

In particular, measurement of the spatial and temporal variations of the Earth's gravity field by the GRACE and GRACE-Follow On satellite missions offer an unprecedented measurement of the evolution of water mass redistribution, at timescales ranging from months to decades. However, the use of GRACE and GRACE-FO data for hydrological applications presents two major difficulties. First, the mission design and data processing lead to measurement noise and errors that limit GRACE missions to large-scale applications and complicates geophysical interpretation. Moreover, temporal observational gaps, including the 11 month-long gap between missions, prevent the interpretation of long-term mass variations. Secondly, disentangling sources of signals from the solid Earth and continental hydrology is challenging and requires to develop methods benefiting from multiple geodetic techniques. 

To reduce noise and enhance geophysical signals in the data, we develop a method based on a spectral analysis by Multiple Singular Spectrum Analysis (M-SSA) which, using the spatio-temporal correlations of the GRACE-GRACE-FO time series, can fill observational gaps and remove a significant portion of the distinctive noise pattern while maintaining the best possible spatial resolution. This processing reveals hydrological signals that are less well or not resolved by other processing strategies. We discuss regional hydrological mass balance, including lakes, aquifers and ice caps regions, derived from the GRACE-GRACE-FO M-SSA solution. Furthermore, we discuss methods to separate sources of gravity variations using additional in-situ hydrological data or geodetic measurements of the Earth’s deformation. 

How to cite: Chanard, K.: Geodesy: a sensor for hydrology , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12642, https://doi.org/10.5194/egusphere-egu22-12642, 2022.

10:30–10:37
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EGU22-3415
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ECS
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On-site presentation
Eva Boergens and Andreas Güntner

The German-American satellite missions GRACE (Gravity Recovery and Climate Experiment) and its successor GRACE-Follow-On (GRACE-FO) observed the unique data set of total water storage (TWS) variations over the continents since 2002. With this nearly 20 years of data, we can investigate trends in water storage beyond the strong declining trends of the ice sheets and glaciers. Unlike all other continents, Africa exhibits an overall positive trend in TWS. This contribution will take a detailed look into Africa's water storage changes and trends. Further, we attempt to explain these trends by comparison to other hydrological observations such as precipitation.

The long-term TWS increase in Africa is most pronounced in the East-African rift centred around Lake Victoria and the Niger River Basin. Other regions such as Madagaskar exhibit a (statistically significant) negative TWS trend. Furthermore, the trends are not monotonous over time. For example, the increasing trend in East Africa only started around the year 2006 and accelerated after 2012. On the other hand, South Africa wetted until 2012 and dried again since then.

This study divides the African continent into climatically similar regions and investigates the regional mean TWS signals. They are more complex than a linear trend and sinusoidal annual and semiannual seasonality; thus, we employ the STL method (Seasonal Trend decomposition based on Loess). In this way, turning points are identified in the so-called trend component to mark significant trend changes.

The observed TWS changes in Africa are caused mainly by changing precipitation patterns, as observed, for example, with the GPCP (Global Precipitation Climatology Project) data set. In some regions, such as South Africa, the correlation between precipitation and TWS change is evident, whereas other areas show a more complex relationship between these two variables.

 

How to cite: Boergens, E. and Güntner, A.: Trends in Africa’s Terrestrial Water Storage , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3415, https://doi.org/10.5194/egusphere-egu22-3415, 2022.

10:37–10:44
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EGU22-3734
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Virtual presentation
Roelof Rietbroek, Marloes Penning de Vries, Yijian Zeng, and Bob Su

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.

10:44–10:51
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EGU22-5765
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Presentation form not yet defined
Guillaume Ramillien, Lucia Seoane, and José Darrozes

We propose a spatial characterization of the hydrological contributions of several climate drivers that impact continental water mass storage of Australia determined by remote sensing techniques over the period 2002 - 2021. For this purpose, the Slepian functions help for recognizing the signatures of such important changes in the varying gravity field solutions provided by GRACE and GRACE-FO satellite missions such as mascon solutions of 400-km resolution. Time series of 25 Slepian coefficients that correspond to ~99.9% of the eigenvalue spectrum are used to be analyzed and compared to the profiles of climate indexes i.e. El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and South Annular Mode (SAM). The best correlations enable to extract specific Slepian coefficients, and then reconstruct the regional hydrological structures that concern each climate driver, in particular for the southeastern basins strongly influenced by the important flooding during La Niña episode of 2010.

How to cite: Ramillien, G., Seoane, L., and Darrozes, J.: Water mass impacts of the main climate drivers over Australia by satellite gravimetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5765, https://doi.org/10.5194/egusphere-egu22-5765, 2022.

10:51–10:58
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EGU22-7903
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ECS
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Presentation form not yet defined
Karim Douch, Peyman Saemian, and Nico Sneeuw

Since 2002, estimates of the spatio-temporal variations of Earth’s gravity field derived from the Gravity Recovery and Climate Experiment (GRACE and now GRACE-FO) mission measurements have provided new insights into large scale water redistributions at inter-annual, seasonal and sub-seasonal timescales. It has been shown for example that for many large drainage basins the empirical relationship between aggregated Terrestrial Water Storage (TWS) and discharge at the outlet reveals an underlying dynamic that is approximately linear and time-invariant.

In this contribution, we further analyse this relationship in the case of the Amazon basin and sub-basins by investigating different physically interpretable, lumped-parameter models for the TWS-discharge dynamics. To this end, we first put forward a linear and continuous-time model using a state-space representation. We then enhance the model by introducing a non-linear term accounting for the observed saturation of the discharge. Finally, we reformulate the model by replacing the discharge by the river stage at the outlet and add a prescribed model of the rating curve to obtain the discharge. The suggested models are successively calibrated against TWS anomaly derived from GRACE data and discharge or river stage records using the prediction-error-method. It is noteworthy that one of the estimated parameters can be interpreted as the total amount of drainable water stored across the basin, a quantity that cannot be observed by GRACE alone. This quantity is estimated to be on average 1,750 km³ during the period 2004-2009. These models are eventually combined with the equation of water mass balance, in order to obtain a consistent representation of the basin-scale rainfall-runoff dynamics suited to data assimilation.

How to cite: Douch, K., Saemian, P., and Sneeuw, N.: Identification of conceptual rainfall-runoff models of large drainage basins based on GRACE and in-situ data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7903, https://doi.org/10.5194/egusphere-egu22-7903, 2022.

10:58–11:05
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EGU22-4918
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On-site presentation
Corinne Vassallo, Srinivas Bettadpur, and Clark Wilson

Though machine learning (ML) methods have been around for decades, they have only more recently been adopted in the geosciences. The availability of existing long data records combined with the capability of ML algorithms to learn highly non-linear relationships between data sources means there is even more potential for the replacement or augmentation of existing scientific analyses with ML methods. Here, I give an example of how I used a convolutional neural network (CNN) for the task of pixelwise classification of the North American Land Data Assimilation System (NLDAS) Total Water Storage data into their corresponding drought levels based on the Palmer Drought Severity Index (PDSI). Promising results indicate there is much to be explored in the application of ML to drought identification and monitoring.

How to cite: Vassallo, C., Bettadpur, S., and Wilson, C.: Drought Identification in NLDAS Data using Machine Learning Methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4918, https://doi.org/10.5194/egusphere-egu22-4918, 2022.

11:05–11:12
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EGU22-8525
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ECS
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On-site presentation
Alejandro Blazquez, Etienne Berthier, Benoit Meyssignac, Laurent Longuevergne, and Jean-François Crétaux

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.

11:12–11:19
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EGU22-1449
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Virtual presentation
Siavash Iran Pour, Annette Eicker, Kyriakos Balidakis, Hamed Karimi, Alireza Amiri-Simkooei, and Henryk Dobslaw

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.

11:19–11:26
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EGU22-7583
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ECS
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On-site presentation
Alexandra Klemme, Thorsten Warneke, Heinrich Bovensmann, Matthias Weigelt, Jürgen Müller, Justus Notholt, and Claus Lämmerzahl

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.

11:26–11:33
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EGU22-10986
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ECS
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Presentation form not yet defined
Srinivas Pernati, Komali Bharath Narayana Reddy, and Balaji Devaraju

The relationship between water storage and vegetation growth differs with changes in different water
compartments such as total water storage, soil moisture and groundwater. This relationship can be
established between variations in water storage and Normalized Difference Vegetation Index (NDVI)
values. The compartments of water storage anomalies were computed with Gravity Recovery and Climate
Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data sets. NDVI data from
Global Inventory Monitoring and Modeling System (GIMMS) was used to compare with water storage
anomalies. These water storage anomalies and NDVI values were aggregated over each sub-basin of the
Ganga catchment. A correlation analysis was made between water storage components and NDVI values,
which helped to determine how vegetation growth depends on changes in different water compartments.
Initial computations of auto-correlation and cross-correlation between water storage components and
NDVI show different lags for different sub-basins. 

How to cite: Pernati, S., Bharath Narayana Reddy, K., and Devaraju, B.: How changes in compartments of water storage affect the vegetation?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10986, https://doi.org/10.5194/egusphere-egu22-10986, 2022.

11:33–11:40
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EGU22-2335
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ECS
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On-site presentation
Laura Jensen, Annette Eicker, and Henryk Dobslaw

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.

11:40–11:47
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EGU22-8529
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ECS
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On-site presentation
Marius Schlaak, Roland Pail, Laura Jensen, and Annette Eicker

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.

Lunch break
Chairpersons: Anna Klos, Eva Boergens
13:20–13:27
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EGU22-6800
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Presentation form not yet defined
Donald Argus, Hilary Martens, Adrian Borsa, David Wiese, Ellen Knappe, Stacy Larochelle, Mackenzie Anderson, Athina Peidou, Ashlesha Khatiwada, Nicholas Lau, Alissa White, Zachary Hoylman, Matthew Swarr, Qian Cao, Ming Pan, Kristel Chanard, Jean-Philippe Avouac, Gardner Payton, and Felix Landerer

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.

13:27–13:34
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EGU22-10152
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ECS
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Virtual presentation
Christian Mielke, Makan Karegar, Helena Gerdener, and Jürgen Kusche

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.

13:34–13:41
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EGU22-64
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ECS
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Presentation form not yet defined
Saturday Ehisemhen Usifoh, T.Nhung Le, Benjamin Männel, Pierre Sakic, Dodo Joseph, and Harald Schuh

Surface loading on GNSS stations in Africa

Usifoh Saturday E1,2,3, Nhung Le Thi1,2, Benjamin Männel1, Pierre Sakic1, Dodo Joseph3, Harald Schuh1,2
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.

13:41–13:48
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EGU22-3577
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ECS
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Presentation form not yet defined
A hierarchical Constrained Bayesian (ConBay) approach to jointly estimate water storage and post glacier rebound from GRACE(-FO) and GNSS data
(withdrawn)
Nooshin Mehrnegar and Ehsan Forootan
13:48–13:55
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EGU22-246
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ECS
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On-site presentation
Grzegorz Leszczuk, Anna Klos, Jurgen Kusche, Artur Lenczuk, Helena Gerdener, and Janusz Bogusz

Hydrological loading is one of the main contributors into seasonal displacements of the Earth’s crust, as derived from the Global Positioning System (GPS) permanent stations. Recent studies proved that hydrological signatures may be also observed in GPS displacements outside seasonal band. Such estimates may be, however, biased, since (1) total character of GPS displacements is generated by a set of geophysical phenomena combined with GPS-specific signals and errors and (2) the exact sensitivity of GPS for individual components has not yet been properly recognized. In this study, we propose a completely new approach to establish a set of benchmarks of GPS stations, for which sensitivity to geophysical phenomena is identified. We focus on hydrological changes within the Amazon basin, but the same approach could be employed to analyze other phenomena. Analysis is performed for vertical displacements from 63 GPS stations provided by the Nevada Geodetic Laboratory (NGL), collected between 1995 and 2021. Results are compared to data from GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On missions (2002-2021), provided by GFZ (GeoForschungsZentrum) as RL06 solution in a form of spherical harmonic coefficients truncated to d/o 96, filtered with DDK3 decorrelation anisotropic filter. We also utilize GLWS (Global Land Water Storage) datatset provided by University of Bonn, as a result of assimilation of GRACE Total Water Storage (TWS) anomalies into WaterGAP Global Hydrological Model (WGHM). We make also use of two hydrological models: pure WGHM and GLDAS (Global Land Data Assimilation System), for which TWS values are provided. Both GRACE and TWS data are converted to vertical displacements of Earth’s crust using load Love numbers, while GPS displacements are reduced for non-tidal atmospheric and oceanic changes. We find the largest values of trends and annual signals for GPS stations proximate to Amazon river. GRACE, GLWS and hydrological models disagree at the level of 8 mm, at maximum. This is mainly caused by the GLDAS model which lacks in the contribution of surface water. Supplementing GLDAS with surface water layer employed from WGHM reduces this difference to 1 mm. Benchmarks of GPS stations are established by using a wavelet decomposition with Meyer’s mother wavelet. We divide both the GPS, GRACE and GLWS displacement time series into 4 decomposition levels, defined by exact periods they contain. Then, we compute correlation coefficients between individual levels of details. We show that the number of 32%, 64%, 97%, 89% and 68% out of 63 GPS stations is significantly correlated to GRACE for periods, respectively, from 2 to 5 months, from 4 to 9 months, from 7 months to 1.4 years, from 1.1 to 3.0 years and from 3.0 years onwards. These numbers change into: 48%, 73%, 100%, 81% and 50% out of 63 GPS stations, when GRACE is replaced with GLWS. 12 or 21 out of 63 GPS stations correlate positively with GRACE or GLWS within entire frequency band, which means that a character of these GPS displacement time series is generated mostly by hydrological changes.

How to cite: Leszczuk, G., Klos, A., Kusche, J., Lenczuk, A., Gerdener, H., and Bogusz, J.: Benchmarking Amazonian GPS stations: an improved way to model hydrological changes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-246, https://doi.org/10.5194/egusphere-egu22-246, 2022.

13:55–14:02
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EGU22-2586
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ECS
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Virtual presentation
Alisa Yakhontova, Roelof Rietbroek, Jürgen Kusche, Sophie Stolzenberger, and Bernd Uebbing

Understanding variations in the ocean heat content is tightly linked to understanding interactions of the global energy cycle with the regional water cycle. Mass, volume, temperature and density changes of  the ocean water column can be estimated with complimentary observations of sea surface height from radar altimetry, ocean bottom pressure from Gravity Recovery and Climate Experiment (GRACE), temperature and salinity from Argo floats. These three techniques have their specific deficiencies and advantages, which can be exploited in a joint inversion framework in order to improve temporal and spatial coverage of oceanic temperature and salinity estimates as well as regionally varying sea level contributions. Solving an inverse problem for temperature and salinity, forward operators are formulated linking the satellite observations to temperature and salinity at depth. This is done by (1) parametrization of temperature and salinity profiles over the full depth of the ocean with B-splines to reduce dimensionality while keeping complexity of the data intact and (2) linearization of the integrated density from parameterized T/S curves. We apply forward operators in the East Indian Ocean to resolve for sea surface height, ocean bottom pressure, temperature and salinity, and assess the regional importance of these factors. We explore the stability of a joint inversion using these forward operators in combination with along-track radar altimetry, GRACE and temperature and salinity by exploring a closed-loop inversion.

How to cite: Yakhontova, A., Rietbroek, R., Kusche, J., Stolzenberger, S., and Uebbing, B.: Contributions of ocean bottom pressure and density changes to regional sea level change in the East Indian Ocean from GRACE, altimetry and Argo data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2586, https://doi.org/10.5194/egusphere-egu22-2586, 2022.

14:02–14:09
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EGU22-5670
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Presentation form not yet defined
A sea-level budget (2003-2020) from a statistical, global, simultaneous inversion
(withdrawn)
Samantha Royston, Aoibheann Brady, Stephen Chuter, Yann Ziegler, Bramha Vishwakarma, Richard Westaway, Jonathan Rougier, and Jonathan Bamber
14:09–14:16
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EGU22-12684
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ECS
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On-site presentation
Andreas Kvas, Katrin Bentel, Saniya Behzadpour, and Torsten Mayer-Gürr

With an observation period of almost twenty years and global data coverage, satellite gravimetry has become a crucial tool for monitoring the state of our planet in a changing climate. Gravimetry-derived mass change has seen numerous applications in different geoscientific disciplines and has fundamentally improved our understanding of the Earth system. One such application is the determination of meridional and zonal volume transport variability based on ocean bottom pressure (OBP) variations, which can provide key insights into climate-relevant ocean currents like the Atlantic Meridional Overturning Circulation (AMOC) or the Antarctic Circumpolar Current (ACC). However, the limited spatial resolution, signal leakage from other geophysical subsystems like the hydrosphere, cryosphere or solid Earth make satellite gravimetry-derived transport estimates difficult to interpret. In this study we investigate geostrophic volume transport variability based on observations of the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) for selected cross sections in the Atlantic and Southern Ocean. We focus on interannual transport variations in the deep ocean, where the more moderately sloping topography poses less stringent requirements on the spatial resolution of the OBP fields, and the lower temporal resolution reduces the impact of observation noise by providing longer averaging periods. Basis for the derived transport variations are high-resolution OBP fields determined in an ensemble Kalman filter approach. This allows us to also propagate the inherent observational noise to transport level and together with glacial isostatic adjustment (GIA) und hydrological model statistics quantify the uncertainty and sensitivity of the derived transport time series. We further contrast results for the Atlantic and Southern Ocean and show the different impact of the satellite observation geometry on meridional and zonal transport estimates.

How to cite: Kvas, A., Bentel, K., Behzadpour, S., and Mayer-Gürr, T.: Twenty years of volume transport from satellite gravimetry in the Atlantic and Southern Ocean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12684, https://doi.org/10.5194/egusphere-egu22-12684, 2022.

14:16–14:23
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EGU22-9943
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Virtual presentation
Christian Ullrich, Olivier Francis, Sajad Tabibi, and Helmut Titz

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.

14:23–14:30
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EGU22-7081
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On-site presentation
Andrzej Araszkiewicz, Michał Mierzwiak, Damian Kiliszek, Joanna Nowak Da Costa, and Marcin Szołucha

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.

14:30–14:37
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EGU22-6390
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ECS
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On-site presentation
Khanh Ninh Nguyen, Olivier Bock, and Emilie Lebarbier

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.