G3.1 | Geodesy for Climate Research

G3.1

EDI
Geodesy for Climate Research
Co-organized by CL5/OS1
Convener: Bramha Dutt VishwakarmaECSECS | Co-conveners: Anna KlosECSECS, Roelof Rietbroek, Carmen Boening, Vincent HumphreyECSECS
Orals
| Fri, 28 Apr, 08:30–12:30 (CEST)
 
Room 0.11/12
Posters on site
| Attendance Thu, 27 Apr, 16:15–18:00 (CEST)
 
Hall X2
Posters virtual
| Attendance Thu, 27 Apr, 16:15–18:00 (CEST)
 
vHall GMPV/G/GD/SM
Orals |
Fri, 08:30
Thu, 16:15
Thu, 16:15
This session invites innovative Earth system and climate studies employing geodetic observations and methods. Modern geodetic observing systems have been instrumental in studying a wide range of changes in the Earth’s solid and fluid layers at various spatiotemporal scales. These changes are related to surface processes such as glacial isostatic adjustment, the terrestrial water cycle, ocean dynamics and ice-mass balance, which are primarily due to changes in the climate. To understand the Earth system response to natural climate variability and anthropogenic climate change, different time spans of observations need to be cross-compared and combined with several other datasets and model outputs. Geodetic observables are also often compared with geophysical models, which helps in explaining observations, evaluating simulations, and finally merging measurements and numerical models via data assimilation.



We look forward to contributions that:

1. Utilize 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.

2. 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.

3. Show a new approach or method for separating and interpreting the variety of geophysical signals in our Earth system and combining various observations to improve spatiotemporal resolution of Earth observation products.

4. Work on simulations of future satellite mission (such as SWOT and GRACE-2) that may advance climate sciences.

5. Work towards any of the goals of the Inter-Commission Committee on "Geodesy for Climate Research" (ICCC) of the International Association of Geodesy (IAG).



We are committed to promoting gender balance and ECS in our 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.

Orals: Fri, 28 Apr | Room 0.11/12

08:30–08:35
08:35–08:45
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EGU23-12349
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G3.1
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Highlight
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On-site presentation
Nicolaj Hansen, Louise S. Sørensen, Giorgio Spada, Daniele Melini, Rene Forsberg, Ruth Mottram, and Sebastian B. Simonsen

We use the land-ice surface height data product (ATL06 release 5) from NASA’s latest satellite laser altimetry, the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) to compute surface elevation changes (SEC) from October 2018 to September 2021 over both Antarctica and Greenland. To convert the SEC to mass change we need to remove the non-ice related SEC processes. To remove the signal from the firn compaction, we use an offline surface energy and firn model. The model is driven by outputs from the atmospheric regional climate model HIRHAM5, forced with reanalysis dataset ERA5, and it simulates the physics of the firn pack. The vertical bedrock movement also creates non-ice related signals, the glacial isostatic adjustment has been computed using the ICE-7G model and SELEN4, and the elastic rebound has been computed using a modified version of the REAR code. 

When the SEC are corrected for signals that are not associated with a change in snow or ice mass, we convert to mass change by multiplying the height change with an appropriate density.  The corrected SEC can result from a change in either melt, snow accumulation, or dynamical behavior, this means that the appropriate density depends on which physical processes are driving the observed SEC. In this study, we have made a new density parametrization to convert the volume change into mass change. The density parametrization determines if one should multiply with snow densities (250-350 kg/m³) or ice density (917 kg/m³) based on a number of criteria; the sign of SEC, ice flow velocity, and the altitude of the area.
With our new density parametrization, we get that the Greenland Ice Sheet has lost 237.5±10.3 Gt/year and the grounded Antarctic Ice Sheet has lost -137.6±27.2 Gt/year in the period. These results are in agreement with other mass balance estimates derived with different methods.

How to cite: Hansen, N., Sørensen, L. S., Spada, G., Melini, D., Forsberg, R., Mottram, R., and Simonsen, S. B.: ICESat-2 Ice Sheet Mass balance: Going below the surface, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12349, https://doi.org/10.5194/egusphere-egu23-12349, 2023.

08:45–08:55
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EGU23-6919
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G3.1
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ECS
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On-site presentation
Ladina Steiner, Holger Schmitthüsen, Jens Wickert, and Olaf Eisen

We developed a methodology for deriving automated and continuous specific surface mass balance time series for fast moving parts of ice sheets and shelves (>10m/a) by an accurate and simultaneous estimation of continuous in-situ snow density, snow water equivalent (SWE), and snow deposition and erosion, averaged over an area of several square meters and independent on weather conditions. Reliable in-situ surface mass balance estimates are scarce due to limited spatial and temporal data availability. While surface accumulation can be obtained in various ways, conversion to mass requires knowledge of the snow density, which is more difficult to obtain.

A combined Global Navigation Satellite Systems reflectometry and refractometry (GNSS-RR) approach based on in-situ refracted and reflected GNSS signals is developed. The individual GNSS-RR methods have already been successfully applied on stationary grounds and seasonal snowpacks and are now combined and transferred to moving surfaces like ice sheets. We installed a combined GNSS-RR system in November 2021 on the fast moving (~150m/d), high latitude Ekström ice shelf in the vicinity of the Neumayer III station in Antarctica. Continuous snow accumulation reference data is provided by a laser distance sensor at the same test site and manual density observations. Refracted and reflected GNSS observations from site are post-processed for SWE, snow accumulation, and snow density estimation with a sub-daily temporal resolution. Preliminary results of the first year of data show a high level of agreement with reference observations, calculated from snow accumulation data collected by the laser distance sensor and linearly interpolated monthly snow density observations of the uppermost layer equivalent to the height of snow above the buried antenna.

The deployed devices are geared towards prototype applications for reliable low-cost applications, which will allow large-scale retrieval of surface mass balance for general cryospheric applications, not only on ice sheets or shelves, but also sea ice. Regional climate models, snow modelling, and extensive remote sensing data products will profit from calibration and validation based on the derived field measurements, once such sensors can be deployed on larger scales.

How to cite: Steiner, L., Schmitthüsen, H., Wickert, J., and Eisen, O.: Combined GNSS Reflectometry/Refractometry for Continuous In Situ Surface Mass Balance Estimation on an Antarctic Ice Shelf, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6919, https://doi.org/10.5194/egusphere-egu23-6919, 2023.

08:55–09:25
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EGU23-4554
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G3.1
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ECS
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solicited
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Highlight
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Virtual presentation
Sophie Coulson, Sonke Dangendorf, Jerry X. Mitrovica, Mark Tamisiea, Linda Pan, and David Sandwell

Rapid melting of ice sheets and glaciers drives a unique geometry, or fingerprint, of sea-level change, including a sea-level fall in the vicinity of the ice sheet that is an order of magnitude greater than the associated global mean sea-level rise of the melt event. The detection of individual fingerprints has been challenging due to sparse sea surface height measurements at high latitudes and the difficulty of disentangling ocean dynamic variability from the signal. Efforts to date have analyzed sea level records outside the zone of major sea-level fall, where the gradients and amplitudes of the fingerprint signal are significantly lower. We predict the fingerprint of Greenland Ice Sheet (GrIS) melt using new ice mass loss estimates from radar altimetry data and model reconstructions of nearby glaciers, and compare this prediction to an independent, altimetry-derived sea surface height trend corrected for ocean dynamic variability in the region adjacent to the ice sheet. The two fields show consistent gradients across the region, with the expected strong drawdown of the sea surface toward GrIS. A statistically significant correlation between the two fields (p < 0.001) provides the first unambiguous observational detection of the near-field sea level fingerprint of recent GrIS melting in our warming world. This detection provides a robust map of the impact of ice mass flux on global oceans since the early 1990s, and validates theoretical and numerical developments in the sea level modelling community.

How to cite: Coulson, S., Dangendorf, S., Mitrovica, J. X., Tamisiea, M., Pan, L., and Sandwell, D.: A Detection of the Sea Level Fingerprint of Greenland Ice Sheet Melt, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4554, https://doi.org/10.5194/egusphere-egu23-4554, 2023.

09:25–09:35
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EGU23-16296
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G3.1
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ECS
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Highlight
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On-site presentation
Carolina M.L. Camargo, Theo Gerkema, Yochi Okta Andrawina, and Aimée B.A. Slangen

In comparison with the number of tide gauges measuring in-situ sea-level change along the Northern Hermisphere coastlines, the Southern Hemisphere has a poor spatial distribution of stations. For example, along the South American Atlantic coastline, only 12 tide gauges are registered at the Permanent Service for Mean Sea-level (PSMSL), of which only two have been updated in the last three years. While satellite altimetry can be used to provide data in locations where there is no in-situ data, estimating coastal sea-level change using altimetry data is challenging due to the distortion of the satellite signal close to the land. Consequently, sea-level change along the South American Atlantic coastline is still poorly understood. Here, we fill this gap by using coastal altimetry products together with a new network of tide gauges deployed along the coast of Brazil (by the SIMCosta project). Via a sea-level budget analysis, we look at the regional drivers of sea-level change along the coast.

 

Recently, a large effort has been put towards developing algorithms that improve the accuracy of standard radar altimetry in coastal regions. Here, we compare both a coastal altimetry product (XTRACT/ALES) and a standard altimetry product (from CMEMS) to the local tide gauges. Previous studies have shown that, for some regions, coastal sea level is driven by open ocean sea-level change ( e.g., Dangendorf et al, 2021). Following this approach, we use clusters of coherent sea-level variability (Camargo et al., 2022), extracted with a network detection algorithm (delta-Maps), that extend to the open ocean, as proxies of the drivers of sea-level change along the coast.  The northern part of the study region, covering the Amazon Plateau, has a good match between the coastal altimetry-observed sea-level change and the sum of the drivers. The sum of the drivers and coastal altimetry trends also match, considering the uncertainty bars, for the most southern part, covering the Patagonian Shelf. For the other regions, we find a large difference between the coastal altimetry-observed sea-level change and the sum of the drivers. Thus, it is possible that these regions cover large-scale features, which are not strongly correlated with coastal sea level.

 

References

Camargo, C. M. L., Riva, R. E. M., Hermans, T. H. J., Schütt, E. M., Marcos, M., Hernandez-Carrasco, I., and Slangen, A. B. A.: Regionalizing the Sea-level Budget With Machine Learning Techniques, EGUsphere [preprint, accepted], https://doi.org/10.5194/egusphere-2022-876, 2022.

Dangendorf, S., Frederikse, T., Chafik, L., Klinck, J. M., Ezer, T., & Hamlington, B. D.: Data-driven reconstruction reveals large-scale ocean circulation control on coastal sea level. Nature Climate Change, 11, 514-520. https://doi.org/10.1038/s41558-021-01046-1, 2021.

How to cite: M.L. Camargo, C., Gerkema, T., Okta Andrawina, Y., and B.A. Slangen, A.: Sea-level change along the South American Atlantic coastline, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16296, https://doi.org/10.5194/egusphere-egu23-16296, 2023.

09:35–09:45
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EGU23-5889
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G3.1
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ECS
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On-site presentation
|
Lennart Schawohl, Annette Eicker, Meike Bagge, and Henryk Dobslaw

Global coupled climate models are important for predicting future climate conditions. Due to sometimes large and often systematic model uncertainties, it is crucial to evaluate the outcome of model experiments 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. However, the use of satellite gravity data for the evaluation of coupled climate models has only very recently become feasible. Challenges arise, e.g., from the still rather short time series of satellite data and from signal separation issues related to GRACE/-FO observing all mass change including non-water related variations such as glacial isostatic adjustment. Apart from climate model uncertainties, these challenges might be the reason for a disagreement between the direction of linear water storage trends of models and observations in several regions of the world, one of them located in Eastern Canada.

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 from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We will focus on long-term wetting and drying conditions in TWS. Using an ensemble of 52 GIA models that differ in the applied ice history, solid Earth rheology, and numerical code, this presentation will discuss how GIA modeling uncertainty does influence (i) the determination of water storage trends from GRACE/FO data, and (ii) the (dis-)agreement between drying/wetting trends in satellite gravimetry and CMIP6 climate models. We will show that the apparent disagreement between observations and models in highly GIA-affected regions in North America crucially depend on the particular model chosen for reducing the GIA effect from the GRACE satellite data.

How to cite: Schawohl, L., Eicker, A., Bagge, M., and Dobslaw, H.: Influence of GIA uncertainty on climate applications from satellite gravimetry, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5889, https://doi.org/10.5194/egusphere-egu23-5889, 2023.

09:45–09:55
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EGU23-10758
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G3.1
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Virtual presentation
Donald Argus, Felix Landerer, David Wiese, and Geoffrey Blewitt

For 25 years, geodesists have inferred that the displacement of the "geocenter" estimated from (SLR) satellite laser ranging represents fluctuation of Earth's fluid envelope relative to solid Earth.  However, SLR determines the displacement of the (CN) center of network of geodetic sites relative to the (CM) center of mass of Earth, consisting of solid Earth, the oceans, the atmosphere, and continental water, snow, and ice. Because solid Earth's surface is deforming in elastic response to the changing load of continental water, atmosphere and oceans, CN only roughly approximates the (CE) center of mass of solid Earth.  In this study, estimate the velocity of CM relative to the (CE) center of mass of Earth by first correcting SLR site displacements (estimated by the International Laser Ranging Service 2020) for their elastic response relative to CE produced by fluctuations of continental water, atmosphere and oceans.  We maintain that by correcting for loading displacements relative to CE, we arrive at an estimate of the displacement of CE.  We find that transforming the SLR series from CN to CE reduces the discrepancy between the seasonal oscillation of Earth's fluid envelope estimated by SLR and that assumed by GRACE (using the technique of Sun et al. 2017) by 40 per cent.  In both SLR and GRACE, a total of 0.5 x 1016 kg of mass moves between hemispheres from southern oceans in August to snow-covered areas in North America and Europe (in particular in Canada and Siberia).  The primary remaining difference between the two techniques is that mass in the northern hemisphere is maximum on February 5 in SLR, 20 days before it is maximum on Feb 25 in GRACE.  Knowing the total transfer of the mass of between hemispheres places a boundary constraint on global models of circulation of water on land and in the oceans and atmospheres (that may be applied to forecasting extreme events such as flooding and drought).

How to cite: Argus, D., Landerer, F., Wiese, D., and Blewitt, G.: Resolving the discrepancy betweenthe seasonal oscillation of Earth's fluid envelope estimated with SLR and that assumed in GRACE, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10758, https://doi.org/10.5194/egusphere-egu23-10758, 2023.

09:55–10:15
Coffee break
10:45–10:55
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EGU23-13048
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G3.1
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ECS
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On-site presentation
Kyriakos Balidakis, Henryk Dobslaw, Florian Zus, Annette Eicker, Robert Dill, and Jens Wickert

Accurate representation of the time-variable atmospheric state is achieved by assimilating numerous and disparse observations into numerical weather models (NWM). The four-dimensional atmospheric density distribution, a derivative of essential meteorological variables, affect among else how electromagnetic signals propagate through Earth’s atmosphere and how satellites orbit through Earth’s gravity field. Atmospheric refraction to which microwave signals are subjected as they traverse the electrically neutral atmosphere is quantified e.g., during the GNSS data analysis, and holds valuable information about the water vapor distribution in the vicinity of the ground stations. Satellite gravimetry as realized by the GRACE and GRACE-FO missions is sensitive to mass redistribution within Earth’s fluid envelope, including but not limited to the atmosphere and the terrestrail water storage, and also to high-frequency variations stemming from the time-integrated effect of precipitation and evapotranspiration. In this contribution we employ two state-of-the-art meso-beta scale NWM (ECMWF’s latest reanalysis ERA5 and DWD’s operational model ICON-global) as well as ERA5‘s ensemble members to demonstrate that tropospheric mosture distribution and net atmospheric freshwater fluxes are quite uncertain in modern NWM in comparison to other quantities such as hydrostatic atmospheric mass and that certain space geodetic observing systems such as GNSS and GRACE-FO are appropriate tools to monitor them, thus enhancing the accuracy of weather prediction.

How to cite: Balidakis, K., Dobslaw, H., Zus, F., Eicker, A., Dill, R., and Wickert, J.: Prospects of Space Geodesy to Monitor Atmospheric Moisture and Atmospheric Net-Water Fluxes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13048, https://doi.org/10.5194/egusphere-egu23-13048, 2023.

10:55–11:05
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EGU23-7836
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G3.1
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On-site presentation
Galina Dick, Florian Zus, Jens Wickert, Benjamin Männel, and Markus Bradke

Global Navigation Satellite System (GNSS) is now an established observing system for atmospheric water vapour with high spatiotemporal resolution. Water vapour is under-sampled in the current climate-observing systems and obtaining and exploiting more high-quality humidity observations is essential for climate monitoring.

The Global Climate Observing System (GCOS), supported by the World Meteorological Organization (WMO), is establishing a reference climate observation network, the GCOS Reference Upper Air Network (GRUAN). Currently, this network comprises 30 reference sites worldwide, designed to detect long-term trends of key climate variables such as temperature and humidity in the upper atmosphere. GRUAN observations are required to be of reference quality, with known biases removed and with an associated uncertainty value, based on thorough characterization of all sources of measurement. In support of these goals, GNSS precipitable water (GNSS-PW) measurement has been included as a priority one measurement of the essential climate variable water vapor. The GNSS-PW program produces a nearly continuous reference measurement of PW and is therefore a substantial part of GRUAN.

GFZ contributes to GRUAN with its expertise in processing of ground-based GNSS network data to generate precise PW products. GFZ hosts a central processing facility for the GNSS data and is responsible for the installation of GNSS hardware, data transfer, processing and archiving, as well as derivation of GNSS-PW products according to GRUAN requirements including PW uncertainty estimation. Currently half of the GRUAN sites are equipped with GNSS receivers. GNSS-PW products for GRUAN and the results of validation studies will be presented.

 

How to cite: Dick, G., Zus, F., Wickert, J., Männel, B., and Bradke, M.: GNSS-derived Precipitable Water Vapor for Climate Monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7836, https://doi.org/10.5194/egusphere-egu23-7836, 2023.

11:05–11:15
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EGU23-258
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G3.1
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ECS
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On-site presentation
Muharrem Hilmi Erkoç

This study investigates the reasons for the decrease in the water level of Beysehir Lake and the shrinkage in the lake's surface area in recent years. For this purpose, the lake water level was determined from multi-mission satellite altimeter data, and the lake area was calculated using high-resolution optical satellite images. Data from Copernicus Global Land Service was used for multi-mission satellite altimeter data, and the lake level trend between 1993-2022 was calculated with the least squares method. European Space Agency's (ESA) Sentinel-2 high-resolution optical images were used to determine the change in the lake surface area between 2015 and 2020. These high-resolution optical images were processed with The Sentinel Application Platform (SNAP) software. The Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) were calculated based on processed optical images, and these indexes reflect the changes in water surface area. From the satellite altimeter data, a decreasing trend of 2.5 ± 0.5 cm/yr in the lake water level in the last ten years and shrinkage of approximately 8 km2 in the last 6 years from the satellite images were determined. The possibility of one of the most important reasons being drought was emphasized, and monthly average air temperature data and monthly average precipitation data were obtained from the Turkish General Directorate of Meteorology. With these data, 3- and 12-month Standardized Precipitation Evapotranspiration Index (SPEI) were calculated. Regarding these calculated drought indexes, moderate, extreme, and severe hydrological drought has been determined in the region. According to the analysis, drought is thought to be the most important reason for the decrease in the lake water level and shrinkage in the lake surface area.

Keywords : Geodesy for Climate, Lake Water Level, Satellite Altimetry, In-situ observation, Sentinel-2

How to cite: Erkoç, M. H.: Examination of Causes for Decrease in the Water Level of Beysehir Lake and Shrinkage in the Lake's Surface Area., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-258, https://doi.org/10.5194/egusphere-egu23-258, 2023.

11:15–11:25
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EGU23-5086
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G3.1
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ECS
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On-site presentation
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Helena Gerdener, Jürgen Kusche, Kerstin Schulze, Petra Döll, and Anna Klos

The satellite mission Gravity Recovery And Climate Experiment (GRACE) provided and its successor GRACE-FollowOn (GRACE-FO) provides a great opportunity to derive observations of the global water cycle from space. The missions have contributed and largely increased our knowledge about various hydrological processes on Earth, for example the melting of glaciers in Greenland or groundwater depletion in India. Nonetheless, the spatial resolution of about 300 km, missing months in the time series and the multi-month gap between GRACE and GRACE-FO complicate or even impede the usage in some applications. Further, separating single storage information, e.g. groundwater, from the GRACE/-FO derived total water storage anomalies (TWSA) is still difficult.

In recent decades, data assimilation techniques were used to downscale and disaggregate the GRACE/-FO TWSA, however, to our knowledge they focus on hydrological instead of geodetic applications, only a few assimilate GRACE/-FO TWSA on a global scale and open access is rare. Therefore, we provide the new Global Land Water Storage (GLWS2.0) data set that offers total water storage anomalies on a 0.5° monthly grid covering the global land except Greenland and Antarctica for the time period 2003 to 2019 without missing months and the GRACE/GRACE-FO gap and will soon be publicly available. GLWS2.0 is derived by assimilating GRACE and GRACE-FO TWSA into the WaterGAP model using the Ensemble Kalman Filter considering uncertainties.

We contrast the GLWS2.0 data with the GRACE/-FO observations and the model simulations in the spatial domain via linear trends, annual amplitudes and non-seasonal TWSA and in the spectral domain via degree variances, c20 coefficients and other representation of spherical harmonics. Worldwide, 1030 GNSS stations are used to validate GLWS2.0 by analyzing the vertical loading at short-term, seasonal and long-term temporal bands and we find that GLWS2.0 agrees better with GNSS than GRACE/-FO. In addition, a good agreement to another global data assimilation product is found, which assimilates GRACE/-FO TWSA into the Catchment Land Surface Model by NASA’s Goddard Space Flight Center.

How to cite: Gerdener, H., Kusche, J., Schulze, K., Döll, P., and Klos, A.: The global land water storage data set GLWS 2.0: assimilating GRACE and GRACE-FO into a global hydrological model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5086, https://doi.org/10.5194/egusphere-egu23-5086, 2023.

11:25–11:35
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EGU23-12485
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G3.1
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ECS
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On-site presentation
Vasaw Tripathi, Bramha Dutt Vishwakarma, and Martin Horwath

Time variable satellite gravimetry, realized with the missions GRACE and GRACE-FO, allows for the only global observation of total water storage (TWS) changes. These observations are inherently smoothed due to the upward continuation of the gravity field at the satellite orbits. Additionally, the correlated errors seen as north-south stripes in global maps require further filtering to separate signal from noise. This causes the signal at any region to be biased by signal at neighboring regions, better known as leakage effect. Various methods have been proposed to mitigate leakage and to spatially assign TWS changes at smaller spatial scales than the satellite data is available by using auxiliary information. Unfortunately, there is a large spatio-temporally variable degree of discrepancy in the agreement or the disagreement within these methods, leaving the non-geodetic users of GRACE TWS changes with the complex question of choosing an appropriate method. The scaling factor approach and the Data-Driven Correction (DDC) approach are the most widely used methods. The scaling factor approach uses a numerical model output of TWS changes, whereas the DDC approach uses only GRACE observations to account for leakage.
Tripathi et al., 2022 (10.5194/hess-26-4515-2022) found for the Indus basin, that a newly proposed variant of the scaling factor method, called Frequency-Dependent scaling, using the WaterGAP (Water Global Assessment and Prognosis) hydrology model (WGHM v2.2d), produced results with a striking agreement against the results from the DDC approach. Therefore, this contribution extends the comparison of Frequency-Dependent scaling using WGHM v2.2d against the DDC method for 189 global hydrological basins. We achieved an agreement between the results from both methods well within the uncertainties of GRACE TWS observations for almost 85-90% of the global hydrological basins. Such an agreement can bring a much-needed consolidation in the treatment of leakage effect across the user community. The disagreement in the rest of the basins varies across time scales, such as long-term trends and periodic signals, and is being further analysed.

How to cite: Tripathi, V., Vishwakarma, B. D., and Horwath, M.: Data-Driven and Scaling Factor methods of GRACE leakage correction: Can they be reconciled?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12485, https://doi.org/10.5194/egusphere-egu23-12485, 2023.

11:35–11:45
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EGU23-2734
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G3.1
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ECS
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Virtual presentation
Xuewen Wan, Nengfang Chao, Ying Hu, Jiangyuan Wang, Zheng Liu, and Kaihui Zou

With the intensification of global climate change, droughts have occurred frequently in the Yangtze River Basin (YRB), which has caused significant impacts on human production, life, and socio-economic development. To reduce the damage caused by drought in the YRB, the drought characteristics must be comprehensively detected and quantified. Here, the spatial and temporal variability of precipitation, runoff, soil moisture, terrestrial water storage, and groundwater in the YRB from the Gravity Recovery and Climate Experiment (GRACE), hydrological and in situ observations were comprehensively estimated by decomposing them into seasonal, subseasonal, trend, and interannual observations. The new weighted GRACE drought standardisation index (WGDSI) was reconstructed using the component contribution ratio and compared with the standardised soil moisture index (SSI), standardised precipitation index (SPI06), and standardisation runoff index (SRI). Additionally, the drought characteristics identified based on observations of the water storage deficit, severity, peak, duration, and recovery time were also quantified using the WGDSI over the YRB. The results indicated that changes in soil moisture, terrestrial water storage, and groundwater in the YRB increased from 2003 to 2019 and mainly based on seasonal and interannual signals. The correlation coefficients between the WGDSI and the SSI, SPI06, and SRI were 0.92, 0.62, and 0.79, respectively, which represented increases of 9%, 14%, and 21% compared to that with the unweighted GRACE drought standardisation index, respectively. The interannual variability of the hydrologic variables was more consistent with drought events in the YRB, which was beneficial for detecting drought. Two serious droughts occurred in the YRB from 2003 to 2019. In 2006, a continuous 7-month-long drought occurred, with a peak at -28.974 km3, severity of -174.767 km3∙month, average drought recovery rate of 0.83 km3/month, and recovery time of 30 months, while in 2011, a continuous 5-month-long drought occurred, with a peak at -18.384 km3, severity of -78.106 km3/month, average drought recovery rate of 0.40 km3/month and recovery time of 39 months. The above results indicate that the WGDSI can be used to monitor and quantify drought over the YRB. The index proposed in this study can be applied to generate new datasets and methods for detecting and quantifying global drought.

How to cite: Wan, X., Chao, N., Hu, Y., Wang, J., Liu, Z., and Zou, K.: Reconstructing a new terrestrial water storage deficit index to detect and quantify drought in the Yangtze River Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2734, https://doi.org/10.5194/egusphere-egu23-2734, 2023.

11:45–11:55
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EGU23-10619
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G3.1
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ECS
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Virtual presentation
On the plausibility of climate variable trends
(withdrawn)
Ashraf Rateb, Bridget R. Scanlon, and Alexander Y. Sun
11:55–12:05
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EGU23-12215
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G3.1
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On-site presentation
Jolanta Nastula, Tomasz Kur, Justyna Śliwińska, Małgorzata Wińska, and Aleksander Partyka

Geophysical interpretation of polar motion (PM) and finding the sources of its excitation is an important but challenging task that takes place on the boundary between geodesy and geophysics. Especially the role of hydrological signals in PM excitation is not yet fully understood, mainly because of the lack of agreement between estimates of hydrological angular momentum (HAM) computed from different data sources (e.g., land surface models, global hydrological models, satellite gravity measurements).

The recently observed climate changes affect the global distribution and transport of continental water mass, which may also influence the HAM. Projections of past and future changes in the physical and chemical properties of the atmosphere, ocean, and hydrosphere caused by climate change are delivered by climate models, which are collected and made available to the public in the frame of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Such models provide many of variables, including variations in soil moisture and snow water storage, which are necessary for HAM computation. However, CMIP6 models differ in terms of initial conditions, physical properties of atmosphere, oceans, hydrosphere, and climate forcing. Such divergences obviously contribute to the differences between various CMIP6-based HAM series.

In this study, we investigate various groups of models according to providing institute, mean of selected models and more sophisticated combinations determined using different methods like e.g., variance components estimation, three cornered hat method. The obtained series are analyzed and evaluated in several spectral bands. The goal of such study is to check whether grouping or combining the models could improve the consistency between CMIP6-based HAM and hydrological signal in geodetically observed PM excitation. To evaluate the combined CMIP6-based HAM series, we compare them with geodetic residuals (GAO) obtained from geodetic angular momentum reduced by atmospheric and oceanic signals, as well as with HAM computed from data from Gravity Recovery and Climate Experiment (GRACE) mission. Generally, the analyses confirm the results obtained from previous studies (Nastula et al. 2022). It is possible to find grouped CMIP6 models that provide HAM series as or more compliant with GAO than HAM determined from GRACE.

How to cite: Nastula, J., Kur, T., Śliwińska, J., Wińska, M., and Partyka, A.: Study on combination approaches for hydrological angular momentum determined from climate data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12215, https://doi.org/10.5194/egusphere-egu23-12215, 2023.

12:05–12:15
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EGU23-16692
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G3.1
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ECS
|
Virtual presentation
Jagat Dwipendra Ray, Swapnali Patar, and Rebarani Mahata

The Earth Surface undergoes continuous deformation due to surface mass variations. These mass variations are primarily caused by the hydrological cycle, snowfall, ice melt and glacial isostatic adjustment (GIA). Modern geodetic sensing techniques like the Global Navigational Satellite System (GNSS) can sense these mass variations with unprecedented accuracy.  Therefore, the GNSS positioning time series provides a unique opportunity to study these mass variations and their causes.

In this study, we have used the GNSS time series from the region of Africa and Antarctica to analyse the mass variations. Conditions like draught and ice melting characterise these two regions. Therefore this current study will look at the signals of these two physical conditions. The results obtained are discussed and analysed.

How to cite: Ray, J. D., Patar, S., and Mahata, R.: Geodetic sensing of mass variations due to climatic conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16692, https://doi.org/10.5194/egusphere-egu23-16692, 2023.

12:15–12:30

Posters on site: Thu, 27 Apr, 16:15–18:00 | Hall X2

X2.50
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EGU23-632
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G3.1
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ECS
|
Metehan Uz, Orhan Akyılmaz, and Ck Shum

Gravity Recovery and Climate Experiment (GRACE) and GRACE-FollowOn (GFO) satellites can monitor the global spatio-temporal changes in terrestrial water storage anomalies (TWSA) with monthly temporal and ~300 km spatial resolutions. Since these native resolutions may not be adequate for various studies requiring better localization of TWSA signal both in spatial and temporal domains, in recent years, considerable efforts have been devoted to downscaling TWSA to higher resolutions. However, the majority of these studies have focused on spatial downscaling; only a few studies attempted to improve the temporal resolution. Here, we utilized an in-house developed Deep Learning (DL) based model to downscale the monthly GRACE/GFO Mass Concentration (Mascon) TWSA to daily resolution across the Contiguous United States (CONUS). The simulative performance of the DL algorithm is tested by comparing the simulations to independent (non-GRACE) dataset and the land hydrology models. In addition, we assessed the potential of our daily simulations to detect long- and short-term variations in TWSA. The validation results show that our DL-aided simulations do not overestimate or underestimate GRACE/GFO TWSA and can monitor variations in the water cycle at a higher temporal resolution.

How to cite: Uz, M., Akyılmaz, O., and Shum, C.: Deep Learning-aided Temporal Downscaling of Satellite GravimetryTerrestrial Water Storage Anomalies Across the Contiguous United States (CONUS), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-632, https://doi.org/10.5194/egusphere-egu23-632, 2023.

X2.51
|
EGU23-15762
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G3.1
Karim Douch, Peyman Saemian, and Nico Sneeuw

Hydro-climatic variables such as precipitation (P), evapotranspiration (ET), terrestrial water storage (TWS) or river discharge define the terrestrial water cycle at local and global scales. The robust detection and quantification of steady trends in these variables require analysing sufficiently long time series of observations. Yet, historical discharge records may suffer from long data gaps or simply be too short; different reanalyses or data-driven models of P and ET often show large discrepancies and the associated uncertainty is not systematically provided. Finally, TWS has been observed only since the launch of GRACE in 2002 and also suffers from dozens of missing epochs.

Here, we present a 3-step approach to consistently reconstruct the historical time series of TWS and discharge at the catchment scale. In the first step, we use in-situ discharge observations and TWS anomaly derived from GRACE(-FO) observations to identify a reduced-order and mass-conserving rainfall-discharge model of the catchment. In the second step, the model is run with different precipitation and evapotranspiration data sets to select the pair P and ET reproducing most accurately the observed discharge and TWS. If necessary, the resulting net water flux (P-ET) is adjusted with a bias to improve the simulation accuracy. lastly, we apply a Bayesian smoother such as the Rauch–Tung–Striebel smoother to estimate TWS and discharge along with their respective uncertainty over the period covered by the P-ET time series. Critical to the proposed approach is the rainfall-discharge model identification. Here, we assume that the observed monthly-averaged discharge at the outlet is primarily driven by the TWS in the upstream catchment. As a consequence, we first estimate a storage-discharge model in the form of a continuous-time differential equation. This equation is subsequently coupled with the water mass balance equation to form the rainfall-discharge model. Remarkably, this final model is estimated independently of any P and ET models.

Finally, we apply the proposed approach to Amazonian and Siberian catchments for a period spanning from 1980 to 2020. In the first case, linear and time-invariant models capture with reasonable accuracy the observed drainage dynamics. In contrast, non-linear or linear and time-variable models are necessary to take correctly into account the temperature-dependent snow and ice accumulation and thaw in the case of Siberian catchments.

How to cite: Douch, K., Saemian, P., and Sneeuw, N.: Reduced order rainfall-discharge model for hydro-climatic data assimilation: a data-driven approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15762, https://doi.org/10.5194/egusphere-egu23-15762, 2023.

X2.52
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EGU23-4048
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G3.1
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ECS
Nicholas Lau, Ellen Knappe, and Adrian Borsa

One of the most dynamic components of Earth surface mass variability is the constant global redistribution of terrestrial water storage (TWS) across temporal scales of hours to decades. Mass loading and unloading from TWS changes induce instantaneous elastic deformation of the solid earth, producing predominantly vertical transient displacements that are observable by geodetic methods. The global expansion of Global Navigation Satellite Systems (GNSS) networks during the last decade have provided new opportunities of directly estimating changes in TWS at high spatial and temporal resolutions. While contemporary GNSS studies have demonstrated the ability to map regional-scale water storage variability, incorporating these geodetic TWS estimates with in-situ hydrologic measurements can provide further insights on the physical mechanisms underlying the terrestrial water cycle.

 

In this study, we investigate the potential of using GNSS-derived TWS estimates to infer individual watershed condition along California’s Sierra Nevada, a major water source for urban and agricultural use. Utilizing the dense GNSS network in the western United States, we invert vertical displacements for TWS change at subbasin scale spatial resolution (USGS HUC-8). Joint analysis of our TWS estimates and stream gauge data shows contrasting seasonal behaviours in the northern and southern Sierra Nevada. The snow-dominated southern section exhibits a significant time lag between maximum storage and maximum baseflow from March to May, indicating wet-season decoupling between surface storage and the subsurface reservoirs that drive baseflow. In contrast, the northern section exhibits little to no lag, indicative of persistent surface-to-subsurface coupling, consistent with the higher rain-to-snow ratio in the north. Furthermore, we demonstrate that GNSS-derived TWS estimates can be used to infer watershed antecedent storage conditions, in which interannual variability in summer storage (dry season) influences streamflow recession behaviours during early precipitation season. Continued development of GNSS-based water storage estimates and future assimilation with hydrologic models should provide additional understanding of the water budget and hillslope hydrology in the Sierra Nevada.

How to cite: Lau, N., Knappe, E., and Borsa, A.: Empirical GNSS-derived terrestrial water storage-streamflow relationship in the Sierra Nevada ranges, California, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4048, https://doi.org/10.5194/egusphere-egu23-4048, 2023.

X2.53
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EGU23-1929
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G3.1
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ECS
Gael Kermarrec, Anna Klos, Henryk Dobslaw, Janusz Bogusz, and Annette Eicker

The interpretation of hydrospheric changes in the context of climate change can be enhanced using Global Navigation Satellite System (GNSS) displacement time series (DTS) combined with the one of a hydrological model. Our methodology is based on a computationally filtering strategy called the Savitzky-Golay filter and applied to selected stations in Europe. We use the GNSS solutions provided by the International GNSS Service (IGS) and, for the first time, the Nevada Geodetic Laboratory (NGL). The new hybrid dataset shows a high correspondence with DTS derived from the Gravity Recovery and Climate Experiment (GRACE) gravity mission but allows the identification of local and station-specific effects. Prior to this analysis, we eliminate various effects such as non-tidal atmospheric and oceanic loadings, glacial isostatic adjustment, barystatic sea-level changes, or thermoelastic deformation from GNSS DTS.

How to cite: Kermarrec, G., Klos, A., Dobslaw, H., Bogusz, J., and Eicker, A.: Hydrospheric mass loading for Europe from GNSS vertical displacement and a hydrological model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1929, https://doi.org/10.5194/egusphere-egu23-1929, 2023.

X2.54
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EGU23-4288
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G3.1
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ECS
Artur Lenczuk, Anna Klos, and Janusz Bogusz

For more than 30 years, the Global Navigation Satellite System (GNSS) has successfully detected local crust deformations. These changes in deformation are caused, among other things, by changes in Total Water Storage (TWS), which reflect regular changes in the water system, but are also coupled with changes resulting from unexpected climate change. Current water conflicts caused by climate variability, increased human activity, population growth and food demand are leading to an increased importance of monitoring the abundance of the terrestrial hydrosphere. Such monitoring is increasingly being carried out using GNSS observations, mainly due to the impressive number of permanent stations distributed on Earth. However, the distribution of GNSS stations is irregular, and the displacement time series is often incomplete. Moreover, because of systematic errors, consistency of several parameters estimated for nearby GNSS stations may be very low. To eliminate the impact of these errors, but still capture regular changes in the climate system, we estimated drought severity index (DSI) using GNSS displacement time series over Europe, and interpolated these station-based DSI values over European area in a 1 per 1 degree grid. The quality of interpolated GNSS-DSI values has been assessed using four external datasets: (1) the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) data, (2) combination of GRACE/-FO data with the Satellite Laser Ranging (SLR) data, provided by the University of Bonn, (3) combination of SLR data and high-low Satellite-To-Satellite Tracking (hlSST) data, provided by Leibniz University Hannover, and (4) the self-calibrating Palmer Drought Severity Index (scPDSI). The external datasets have low spatial resolution, when compared to station-dependent GNSS-DSI and the scPDSI index is unable to capture several real water changes. Using GNSS displacements for estimated of DSI reduces these limitations. Our results show that GNSS-based DSI is spatially coherent with indicators derived from other datasets and is able to map dry and wet periods occurring over Europe. GNSS-DSI are also able to capture extreme short events not observed by other datasets. We note that the GRACE-DSI values show the least consistency with GNSS-DSI values. We find also that the DSI values estimated from combined GRACE and SLR indices have largest root-mean-square values for Europe. Our results show that GNSS displacements can be applied to study human and/or climate impact on water changes in small spatial and temporal scales, which may be averaged out in the other datasets; this hold the true especially in regions where GNSS stations are densely distributed.

How to cite: Lenczuk, A., Klos, A., and Bogusz, J.: Quality assessment of the gridded climate indices estimated from GNSS displacements for the European area, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4288, https://doi.org/10.5194/egusphere-egu23-4288, 2023.

X2.55
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EGU23-5486
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G3.1
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ECS
Charlotte Hacker

The Gravity Recovery and Climate Experiment (GRACE) mission has monitored total water storage anomalies (TWSA) globally with unprecedented resolution and accuracy since 2002. However, many applications require a data-based, multi-decadal extended record of TWSA prior to the GRACE period as well as bridging the eleven-months gap between GRACE and its successor GRACE-FO. Statistical and machine-learning 'reconstruction' approaches have been developed to this end, mostly via identifying relations of GRACE-derived TWSA to climate variables, and some regional or global land data sets are now publicly available.

In this contribution, we  compare the two global reconstructions by HUMPHREY AND GUDMUNDSSON (2019) and LI ET AL. (2021) mutually and against output from the the WaterGAP hydrological model from 1979 onwards, against large-scale mass-change derived from geodetic satellite laser ranging from 1992 onwards, and finally against differing GRACE/-FO solutions from 2002 onwards. 

We find that the reconstructions agree surprisingly well in many regions at seasonal and sub-seasonal timescales, even in the pre-GRACE era. We find larger differences at inter-annual timescales which we speculate are in part due to the way reconstructions are trained and in part on which specific GRACE solution they are trained as well as the climatological characteristic of the region. Our comparisons against independent SLR data reveal that reconstructions (only) partially succeed in representing anomalous TWSA for regions that are influenced by large climate modes such as ENSO.

How to cite: Hacker, C.: How realistic are multi-decadal reconstructions of GRACE-like total water storage anomalies?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5486, https://doi.org/10.5194/egusphere-egu23-5486, 2023.

X2.56
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EGU23-8590
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G3.1
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ECS
|
Marius Schlaak, Pail Roland, Alejandro Blazquez, Benoit Meyssignac, and Jean-Michel Lemoine

Satellite gravity missions have been almost continuously observing global mass transports for more than two decades. The resulting data record already improved our understanding of large-scale processes of the water cycle and is reaching a timespan, which has significance concerning climate related mass transport signals such as changes in the essential climate variables terrestrial water storage (TWS) and sea level. The observations of the currently flown GRACE-FO mission will be continued by NASA’s Mass Change (MC) Mission and extended to the Mass change And Geosciences International Constellation (MAGIC) by ESA’s Next Generation Gravity Mission (NGGM), setting anticipation for higher spatial and temporal resolution of satellite gravity observations in the near future.

This contribution presents initial results of multi-decadal closed loop simulations of current and future satellite gravity observations, comparing their capabilities to allow a direct estimation of long-term trends in changes of TWS and ocean mass. The observed climate signal is based on components of the TWS, as well as mass change signals of oceans, ice sheets, and glaciers extracted from CMIP6 climate projection following the shared socio-economic pathway scenario. A special focus here is on the long-term trend over the oceans. By subtracting the observed ocean mass change from the overall sea level change, the global ocean heat content can be computed from the steric component of the sea-level rise. The resulting long-term trends are then compared to initial inputs to the simulation to illustrate the difference in performance between current and future satellite gravity constellations.

How to cite: Schlaak, M., Roland, P., Blazquez, A., Meyssignac, B., and Lemoine, J.-M.: Multi-decadal Satellite Gravity Mission Simulations Comparing Resolving Capabilities of a Long-term Trend in the Global Ocean Heat Content, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8590, https://doi.org/10.5194/egusphere-egu23-8590, 2023.

X2.57
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EGU23-13524
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G3.1
Roelof Rietbroek, Sedigheh Karimi, and Amin Shakya

In a warming climate, atmospheric water vapour will increase, intensifying the global water cycle. However, this ”wet-get-wetter” and ”dry-get-drier” paradigm does not hold on regional scales and models seem to contradict observations. Furthermore, it is unknown whether modelled atmospheric moisture fluxes, entering and leaving the watersheds, are mass consistent with river discharge and sinks and sources such as aquifers, soil layers and surface waters. Consequently, observational evidence of the changing water cycle components is crucial for scrutinizing models. It is also essential to assess climatic water cycle trends which have far reaching ecological and socio-economic consequences, through the occurrence of heat waves, flooding, forest fires and water availability.

In this contribution, we introduce a 5 year research project, which was recently funded through the Vidi talent scheme programme of the Dutch Research Council. We will explain how we plan to use satellite gravimetry, radar altimetry, in a joint inversion scheme, to estimate water fluxes in and out of the watersheds of the North Sea region, and those of the Greater Horn of Africa. Furthermore, we’ll show how regional sea level change and vertical land motion will be consistently accounted for in the proposed estimation scheme.

How to cite: Rietbroek, R., Karimi, S., and Shakya, A.: Unravelling watershed fluxes to detect emerging changes of the water balance, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13524, https://doi.org/10.5194/egusphere-egu23-13524, 2023.

X2.58
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EGU23-9933
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G3.1
Benjamin D. Gutknecht, Anne Springer, and Jürgen Kusche

Terrestrial Water Storage (TWS) is a measure of the total amount of net-accumulated water in all continental storage compartments. The Global Climate Observing System programme (GCOS) has recently approved TWS Anomalies as an Essential Climate Variable (ECV). With GRACE and GRACE-FO we have the ability to look back on an observable that can be interpreted as monthly TWS change since the year 2002. In the continental water mass budget equation, this change balances the water fluxes from precipitation, evapotranspiration and runoff. 

Within the framework of the new Collaborative Research Cluster 1502 'DETECT', we analyse terrestrial/atmospheric and surface water fluxes and associated budget contributions from model simulations, reanalyses and remote sensing observations for all larger river basins in Europe and combine them with catchment-integrating TWS variability. While, as a first step, we are updating previous budget analyses with latest available data sets, the project's central objective is to quantify to what extent regional changes of land and water use contribute to observed budget changes.

In this presentation, we introduce our central objectives and show first results of the latest continuation of catchment-wide water mass flux time-series analysis over Europe. We discuss our budgeting strategies as well as opportunities and hurdles concerning data availability and uncertainties --- also in view of the recently launched SWOT mission and future GRACE successors.

How to cite: Gutknecht, B. D., Springer, A., and Kusche, J.: Water Mass Fluxes and Budgets at Catchment-Scale over Europe in the Collaborative Research Cluster 'DETECT', EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9933, https://doi.org/10.5194/egusphere-egu23-9933, 2023.

X2.59
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EGU23-12155
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G3.1
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ECS
|
Highlight
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Barbara Jenny, Nicolaj Hansen, Tim Jensen, and René Forsberg

An important application of the NASA/GFZ GRACE and GRACE-FO satellites is the derivation of ice mass changes in the arctic regions from the gravity field changes. Looking at climate change, it is important to know how fast the ice caps are melting for global sea level rise estimation and validation of climate models. We use recently released L2 GRACE/GRACE-FO models, including the latest CSR release 6.1, which show major improvement over earlier models, especially for Antarctica, as well as the latest TU Graz models.  We also compare the GRACE results to a new surface mass balance model, and joint high-resolution inversion with ESA’s Earth Explorer CryoSat altimetry data, highlighting areas of dynamic changes and giving a higher resolution on the main mass change areas. The study is a precursor to a project for demonstrating use of Level-1 laser data for glacial change detection.

How to cite: Jenny, B., Hansen, N., Jensen, T., and Forsberg, R.: Mass change of Antarctica from new GRACE/GRACE-FO releases, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12155, https://doi.org/10.5194/egusphere-egu23-12155, 2023.

Posters virtual: Thu, 27 Apr, 16:15–18:00 | vHall GMPV/G/GD/SM

vGGGS.2
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EGU23-8001
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G3.1
|
ECS
Anne Barnoud, Julia Pfeffer, Anny Cazenave, Robin Fraudeau, Victor Rousseau, and Michaël Ablain

We investigate the performances of GRACE and GRACE Follow-On satellite gravimetry missions in assessing the ocean mass budget at global scale over 2005-2020. For that purpose, we focus on the last years of the record (2015-2020) when GRACE and GRACE Follow-On faced instrumental problems. We compare the global mean ocean mass estimates from GRACE and GRACE Follow-On to the sum of its contributions from Greenland, Antarctica, land glaciers, terrestrial water storage and atmospheric water content estimated with independent observations. Significant residuals are observed in the global mean ocean mass budget at interannual time scales. Our analyses suggest that the terrestrial water storage variations based on global hydrological model likely contributes to a large part to the misclosure of the global mean ocean mass budget at interannual time scales. We also compare the GRACE-based global mean ocean mass with the altimetry-based global mean sea level corrected for the Argo-based thermosteric contribution (an equivalent of global mean ocean mass). After correcting for the wet troposphere drift of the radiometer on-board the Jason-3 altimeter satellite, we find that mass budget misclosure is reduced but still significant. However, replacing the Argo-based thermosteric component by the ORAS5 ocean reanlaysis or from CERES top of the atmosphere observations leads to closure of the mass budget over the 2015-2020 time span. We conclude that the two most likely sources of error in the global mean ocean mass budget are the thermosteric component based on Argo and the terrestrial water storage contribution based on global hydrological models. The GRACE and GRACE Follow-On data are unlikely to be responsible on their own for the non-closure of the global mean ocean mass budget.

How to cite: Barnoud, A., Pfeffer, J., Cazenave, A., Fraudeau, R., Rousseau, V., and Ablain, M.: Revisiting the global mean ocean mass budget over 2005-2020, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8001, https://doi.org/10.5194/egusphere-egu23-8001, 2023.