How to cite: Fayne, J.: Climate Change Studies through SWOT Phenomenology Research, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14224, https://doi.org/10.5194/egusphere-egu24-14224, 2024.

Since the beginning of the precision satellite altimeter era in the early 1990s, efforts have been focused on computing the mean height of the ocean surface for use in various geodetic and oceanographic studies. With 30 years of satellite measurements now available, it is time to rethink how we model the mean sea surface (MSS) in the era of climate change.

There are linear changes in the height of the ocean surface due to melting ice and increasing ocean heat content that will not average to zero when computing the mean. Today, there are places in the ocean that are 15 cm higher than they were at the start of the altimetric era some 30 years ago. Today, conventional MSS models like CLS15/22 or DTU15/21 are roughly 5 cm lower than what is observed by present-day satellites like Sentinel6-MF.

We propose that linear sea level changes are estimated simultaneously and consistently with the mean sea surface computation and added to the definition of the MSS, which is tied to a particular date in time. This is possible because the MSS are tied to the 2003.01.01 period for the DTU MSS models. 

We also investigated the acceleration of sea surface height but found these small and still unstable [Nerem et al., 2018]. We also found that these are still somewhat dependent on the Side A correction of the TOPEX mission. We conclude that a longer time series is needed before a stable map of the accelerations can be computed and applied.

There is considerable evidence that using a 30-year trend pattern in sea surface height is stable and is driven by the “forced response” of Greenhouse gases and aerosols. These patterns will be reasonably persistent as we move forward in time.

Testing a new DTU23MSS mean surface tailored to the year 2023 to our processing of the recently available 2023 SWOT data, we find this new DTU23MSS reduces the spatial variability of the SWOT data which is important to the processing and particularly the roll-error correction applied to the 2D SWOT sea surface height data. Applying the new DtU21MSS to conventional satellites like Sentinel-3A/B and 6 reduces both offset and spatial variability of the data indicating that the new MSS is actually very close to a “present-day mean”

How to cite: Andersen, O. B., Nerem, S., and Nielsson, B.: Consistent Mean Sea Surface and sea level change estimation in the Era of Climate Change – application to SWOT processing. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12785, https://doi.org/10.5194/egusphere-egu24-12785, 2024.

The closure of the Sea Level Budget (SLB) at monthly, yearly, and interannual scales, with the utmost precision, remains a fundamental challenge in modern physical oceanography. Firstly, this closure is crucial to assert that all major contributors to sea level variability are accurately identified and quantified. Secondly, it serves as a valuable means for cross-validating complex global observation systems, such as the Argo in-situ network, satellite gravimetry missions GRACE/GRACE-FO, and the satellite altimetry constellation, while closely monitoring their performances. Thirdly, this closure proves to be an effective approach for testing the consistency of various observed variables within the climate system, including sea level, ocean temperature and salinity, ocean mass, land ice melt, and changes in land water storage, in accordance with conservation laws, notably those governing mass and energy.

In this presentation, we will share the latest results obtained for the sea level budget, including 1) an up-to-date estimate of the global mean budget closure from 1993 to 2022; 2) advancements in the analysis of regional patterns of each component of the budget, as well as of the budget residuals, allowing the identification of regions where the SLB does not close, with a focus on the North Atlantic and the Arctic Ocean where the residuals are significantly high. When and where the SLB closes, we can interpret the causes of the total sea level variations. The analysis at regional scales allows us to assess the relative importance of the individual components all over the oceans. When the SLB does not close, we investigate in each component the potential errors causing non-closure (e.g., in-situ data sampling, geocenter correction in gravimetric data) and how potential inconsistencies in their processing can impact large-scale patterns (e.g., geocenter and atmosphere corrections).

Future works will address questions related to the structural deficiency of the observing system, inconsistent effective resolution across different observing subsystems (in-situ data, satellite gravimetry, and satellite altimetry), potential measurement errors in a single observing subsystem, and the isolation of errors in terms of time and space. To address these questions, we will assess an SLB using synthetic components derived from oceanic models. This novel approach will enable us to estimate the spatial and temporal resolutions inherent in each observation, thereby enhancing the estimation of their respective uncertainties. We will also analyse the signature of internal climate variability on sea level budget components interannual changes, by using state-of-the-art model simulations and reanalyses.

This work is performed within the framework of the Sea Level Budget Closure Climate Change Initiative (SLBC_cci+) programme of the European Space Agency (ESA).

How to cite: Bouih, M., Barnoud, A., Fraudeau, R., Larnicol, G., Cazenave, A., Meyssignac, B., Blazquez, A., Horwath, M., Döhne, T., Bamber, J., Abele, A., Leroux, S., Kolodziejcyk, N., Llovel, W., Spada, G., Storto, A., Yang, C., Connors, S., Restano, M., and Benveniste, J. and the SLBC_cci+ team: Global mean and local sea level budget from updated observations andresiduals analysis (SLBC_cci+ project), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16813, https://doi.org/10.5194/egusphere-egu24-16813, 2024.

An effective spatial resolution of a few hundred kilometres, typically assessed for mass variations derived from GRACE/GRACE-FO data, is a major limitation for the rigorous investigation of local causes of mass variations. This is crucial for analyzing mass changes of the West Antarctic Ice Sheet, which is one of the tipping elements in the Earth’s climate system. In this region, ice mass changes occur on spatial scales smaller than the typical GRACE/GRACE-FO resolution. Furthermore, this is also the case for the solid-Earth deformation induced by ice load changes, which in turn can affect the glacier flow. Especially in the Amundsen Sea Embayment, mass changes due to the ongoing Glacial Isostatic Adjustment (GIA) have been postulated to vary on spatial scales smaller than 200 km and to feed back significantly on ice flow dynamics. Here, we present results from a data combination approach with a focus on the Amundsen Sea Embayment, West Antarctica. This approach utilizes data from GRACE/GRACE-FO and CryoSat-2 satellite altimetry with regional climate and firn model results over a time span of 10 years from 2011 to 2020. Improved GRACE/GRACE-FO gravity-field processing and a study area in a high latitude region, where the signal-to-noise is high, benefit a high spatial resolution of the results. One processing step is the smoothing of the input data sets in order to unify their different spatial resolution. We find a best fit of the combination results with independent GNSS observations by applying a Gaussian smoother of 135 km half-response width. The weighted rms difference is 3.8 mm/a in terms of estimated bedrock motion. It is almost twice as large when the input data sets are smoothed with a 300 km half-response filter. The determined effects of solid-Earth deformation may be a useful boundary information for GIA modelling in this region, e.g. for testing rheological models or (centennial) glacial histories.

How to cite: Willen, M. O., Wouters, B., Broerse, T., Buchta, E., and Helm, V.: Combination of GRACE/GRACE-FO and CryoSat-2 data resolves Glacial Isostatic Adjustment spatially and temporally in the Amundsen Sea Embayment, West Antarctica, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11963, https://doi.org/10.5194/egusphere-egu24-11963, 2024.

Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite and its following mission GRACE-FO have measured the time-variable gravity fields of the Earth, by which water shifts around Earth can be captured. Among its innovations, GRACE has monitored the change of ice mass from Earth's ice sheets and glaciers, which is essential for the better understanding of the changing climate system. Over the past few decades, glacier mass loss has been significant across the globe. The European Alps are among the regions experiencing the greatest shrinkage of glaciers, which becomes the main focus of this work.
In this work, we will challenge the information of satellite gravimetry, hydrological models, and satellite geodesy to monitor the ice mass loss in the Alps in central Europe. The temporal variations of total water storage (TWS) in the Alpine region are determined from GRACE- and GRACE-FO-based Level-2 products provided by COST-G and Mascon surface mass change fields calculated by JPL. Furthermore, the correction of GIA effects and hydrological signals in the study area is indispensable to isolate the estimate of glacier melting. For the GIA correction, the GIA model ICE-6G_D and the regional dataset of surface displacements obtained from geodetic observation techniques are applied to GRACE data respectively, resulting in obvious different results. For the hydrological correction, the WaterGAP Global Hydrology Model (WGHM) model and the Global Land Data Assimilation System (GLDAS) model are used to estimate the mass change of the liquid part. In addition, the ice mass loss in the Alps between 2000 and 2014 based on glacier inventory was estimated in another publication, which can be a reference (-1.34 Gt/yr). Glaciers in the Alps lost mass at a rate of around -1.4 Gt/yr and around -2.2 Gt/yr depending on different ways of GIA correction during the 21-year period, which have similar magnitudes with the reference value.

How to cite: Liu, S. and Pail, R.: The estimation of glacier changes in the Alps in 2002-2022 with the use of satellite gravimetry data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11913, https://doi.org/10.5194/egusphere-egu24-11913, 2024.

Ice sheets in Antarctica and Greenland have continued to undergo rapid changes since the 1970s causing a significant rise in global mean sea level. The Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE) community has produced reconciled estimates of ice sheet mass changes for both ice sheets from the 1970s till 2021 by combining more than 50 independent mass balance estimates produced from varied satellite observations. Ice sheet mass changes are driven by competing processes due to their interaction with the atmosphere (surface mass balance) and ocean (ice dynamics). Here, we present an updated IMBIE assessment and partition mass trends into their surface mass balance (SMB) and ice dynamics components. This new assessment shows that Antarctica and Greenland contributed 29.3 mm to the global mean sea level between 1979 and 2021. While in Antarctica, almost all ice losses were driven by ice dynamical imbalance, we find that 60 % of Greenland’s ice losses were caused by increased ice discharge with reduced SMB accounting for the remainder. This exercise reveals the different drivers of Antarctica and Greenland mass changes and highlights their high interannual variability. Finally, we are aiming at producing reconciled regional ice sheet mass balance estimates for the main drainage basins of Antarctica and Greenland for the first time and will be presenting preliminary results for some of the key regions of the ice sheets that have been undergoing rapid changes. Partitioning mass trends and producing regional assessments will contribute to a better understanding of the remaining differences between the different satellite geodesy techniques employed within IMBIE and will provide a key dataset for both the Earth Observation and ice sheet modelling communities. 

How to cite: Kaitheri, A., Otosaka, I., and Shepherd, A.: Mass Balance of Greenland and Antarctic Ice Sheets since the 1970s, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21332, https://doi.org/10.5194/egusphere-egu24-21332, 2024.

Ocean Heat Content (OHC) is an essential indicator of Earth’s climate state. Climate change is driven by the disequilibrium of Earth’s radiation budget. This abundant energy in the system is the Earth Energy Imbalance (EEI), which is challenging to measure globally. About 90% of EEI is accumulated in the oceans, resulting in an increase in ocean heat content. Therefore, OHC is a suitable proxy for EEI and can be measured globally using a combination of geodetic satellite techniques. By combining satellite altimetry and satellite gravimetry, it is possible to measure the change in global ocean heat content over the mission’s lifetime. While the altimeter record covers several decades, satellite gravity missions have been observing global mass transports for two decades. To steadily estimate the system’s long-term behavior, an extended observation period of the satellite systems is needed. The upcoming satellite gravity mission Grace-C, planned to be launched in 2028 by NASA, is meant to ensure continuity and extension of the data record. At the beginning of the 2030s, an additional inclined pair will be launched by ESA to form together with GRACE-C the Mass change And Geosciences International Constellation (MAGIC), for which higher spatial and temporal resolutions are expected.

This contribution presents the results of multi-decadal closed-loop simulations of current and future satellite gravity observations. It shows the benefit of an increased duration of the observation and an improved observational system while comparing processing strategies for long-term trends in ocean mass changes. The observed climate signal is based on projections of mass change signals of oceans, ice sheets, and glaciers derived from CMIP6 climate projection under a shared socio-economic pathway scenario without drastic reduction of Greenhouse gases emissions (SSP5-8.5). A particular focus here is on the accuracy of long-term ocean trends. The direct estimation of long-term trends benefits from an increasing observation period and allows improved spatial resolution compared to trends estimated from monthly temporal gravity fields. The global ocean heat content is estimated from the steric sea-level change which is derived by subtracting the observed ocean mass change from the overall sea level change. The resulting long-term trends in ocean heat content 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., Pail, R., Blazquez, A., Meyssignac, B., and Lemoine, J.-M.: Resolving the interannual to multi-decadal variability in ocean heat content, a simulation study of current and future satellite gravity missions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10483, https://doi.org/10.5194/egusphere-egu24-10483, 2024.

Geostrophic currents, driven by the Coriolis and pressure gradient forces, are crucial for understanding ocean circulation. The Antarctic Circumpolar Current (ACC) in the Southern Ocean, encircling Antarctica, has substantial global impact, and its volume transport (VT) remains challenging to measure. We utilize satellite data, combining Altimetry and Gravity Satellite missions, to estimate VT within the ACC. Our study offers a comprehensive spatial and temporal analysis, encompassing barotropic and baroclinic VT components. We validate our results with in-situ measurements from the Drake Passage. Our analysis reveals a steady spatial VT of 210.44 ± 3.4 Sv, with maxima near critical choke points. Temporally, we identify a mean VT of 15.86 ± 0.05 Sv per 1º grid cell, a linear trend of -0.007 ± 0.002 Sv per month, and significant seasonal and biannual signals. Zonal VT predominantly influences total VT, while meridional VT remains near zero. The baroclinic component drives low-frequency variations, while the barotropic component controls high-frequency variations. We propose a specific ACC zonal VT of 201.63 ± 0.71 Sv. In summary, our satellite-based approach offers valuable insights into ACC VT. This methodological extension enhances our understanding of the ACC's ocean circulation dynamics, showcasing the utility and robustness of satellite data in oceanographic research.

How to cite: Vargas Alemañy, J. A., Vigo Aguiar, I., García García, D., and Zid, F.: ACC Volume Transport: A Geodetic Analysis via Satellite Data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16124, https://doi.org/10.5194/egusphere-egu24-16124, 2024.

Water vapor plays a key role in the Earth's climate as a dominant greenhouse gas. It is also the most efficient actor of heat transfer from the surface to the atmosphere and from low to high latitudes which shapes the global atmospheric circulation and weather systems. Monitoring and understanding the spatial and temporal variability and changes of water vapor are thus of crucial importance.

This work aims at computing decadal trends of total column Integrated Water Vapour (IWV) from a global network of ground-based GNSS observations. Although GNSS observations are available with high accuracy in all weather conditions, it has been shown that, over long periods of time, changes in instrumentation, in station location and environment, and in processing methods can introduce spurious shifts in the IWV time series and bias trend estimates. Homogenization is a crucial step to detect and correct such non-climatic signals.

We have developed a relative homogenization method which involves three steps.

• Segmentation. First, change-points are detected from the difference series (GNSS – reference) with the help of the GNSSseg segmentation package (Quarello et al., 2022). The method uses a difference series in order to cancel out the common climatic variations. It also accounts for changes in the variance on fixed intervals (monthly) and a periodic bias (annual) due to representativeness differences between GNSS and the reference (in our case the ERA5 reanalysis). Because the change-points detected in the difference series could be either due to GNSS or to the reference (ERA5), the next step is the attribution.
• Attribution. Second, the detected change-points are attributed to either GNSS or to the reference (ERA5) using a statistical test based on linear regression and a predictive rule based on the Random Forest learning algorithm (Nguyen et al., 2023). This step requires additional neighbors stations (at least one).
• Correction. The last step is the correction. Here the initial GNSS series is corrected only for the shifts which are attributed to the GNSS in the second step.

We will present results of the homogenization procedure applied to a global network of GNSS stations and discuss the impact of homogenization on linear trend estimates for stations that have more than 20 years of observations.

Quarello et al., 2022, https://doi.org/10.3390/rs14143379

Nguyen et al., 2023, https://hal-obspm.ccsd.cnrs.fr/IGN-ENSG/hal-04014145v1

How to cite: Bock, O., Nguyen, N. K., and Lebarbier, E.: Homogenization of GNSS IWV time series and estimation of climatic trends, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15227, https://doi.org/10.5194/egusphere-egu24-15227, 2024.

Simulated terrestrial water storage (TWS) data from global hydrological models are indispensable for various geodetic applications, e.g., for simulating Earth orientation parameters, deriving time series of deformations of the Earth’s surface needed for the realization of global reference systems, or de-aliasing purposes of GRACE/-FO gravity products. So far, the Land Surface Discharge Model (LSDM) has been routinely used for such tasks at the GFZ. However, the current standard experiment of LSDM is already several years old, and many limitations are known, in particular a limited spatial resolution of 0.5°, which limits the accuracy of crustal deformation predictions close to rivers and lakes. In this contribution, we evaluate the suitability of LISFLOOD (https://ec-jrc.github.io/lisflood/), an open source, high-resolution hydrological rainfall-runoff-routing model, for geodetic purposes.

We compare the performance of various global LISFLOOD model runs for the time period 2000 – 2022 against the current LSDM configuration. In addition to two LISFLOOD model generations, which differ in their spatial resolution (0.1° and 0.05°) and their input land surface parameter data set, we also explore a number of high-resolution (0.05°) model runs with respect to the influence of the soil depth on simulated TWS. Model results are validated against mass anomalies from the satellite gravimetry missions GRACE and GRACE-FO on different spatial and temporal scales. Furthermore, to demonstrate the benefit of the higher spatial resolution of LISFLOOD, we utilize data from selected ground based GNSS stations to validate the models’ performance regarding mass-induced loading.

We find that LISFLOOD significantly outperforms LSDM in many regions, especially on interannual time scales, in terms of various validation metrics (i.e., correlation, root mean squared deviation, and explained variance). Analyzing the different LISFLOOD runs reveals advantages of the new (0.05°) over the old (0.1°) model version, and a large impact of the choice of soil depth on simulated TWS.

How to cite: Dobslaw, H., Jensen, L., Dill, R., and Balidakis, K.: Assessment of global high-resolution water storage simulations from the LISFLOOD hydrological model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10526, https://doi.org/10.5194/egusphere-egu24-10526, 2024.

Under the assumption that a warming climate leads to an intensification of the global water cycle, it can be hypothesized that also the occurrence frequency and severity of extreme events such as droughts or floods will increase in the upcoming decades to centuries. Global coupled climate models, which project the future evolution of various variables of the Earth's climate system are important tools for the analysis of such expected changes. To assess the reliability of the models and to identify possible systematic discrepancies, it is essential to evaluate the model output against observations.

In this study, present and future occurrences of extreme events are analysed in water storage time series simulated by coupled global climate models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) and compared against spatio-temporal changes in water mass derived from GRACE and GRACE-FO. This comparison is based on Extreme Value Theory, as the exact timing of modelled extreme events cannot be assessed by observations due to the stochastic behavior of climate variability in unconstrained model experiments. From estimated extreme value distributions return levels are calculated, a quantity describing the magnitude or frequency of extreme values.  Challenges that have to be overcome in the analysis are the non-stationary data and the relatively short time span of the GRACE observations. The latter issue is addressed by additionally assessing GRACE-based water storage reconstructions available over many decades.

This study provides insights into the ability of global climate models to model the occurrence of TWS extremes, namely unusual dry and wet phases. It also examines whether the climate model projections predict an increasing intensity of extreme events.

How to cite: Middendorf, K., Eicker, A., Jensen, L., and Dobslaw, H.: Evaluation of extreme events in global coupled climate models by satellite gravimetry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7669, https://doi.org/10.5194/egusphere-egu24-7669, 2024.

NASA and DLR will launch in 2028 GRACE-C (Gravity Recovery and Climate Experiment – Continuation). This mission will again be launched into a polar orbit at 500 km initial altitude and extend the observation of the time-variable Earth’s gravity field from GRACE (2002-2017) and GRACE-FO (GRACE Follow-On, 2018-today). ESA plans to launch a Next Generation Gravity Mission (NGGM) in 2032, which shall fly in a lower and inclined orbit and be based on improved instrumentation. GRACE-C and NGGM will then form the double-pair Mass-Change and Geosciences International Constellation (MAGIC) to significantly increase the spatial and temporal resolution of mass transport products and deduce water mass redistribution over the oceans, ice sheets and continents.

Thanks to the 20+ years period of GRACE and GRACE-FO observations, scientists are able to analyse extreme hydrological events, such as flooding and droughts. However, due to the rather coarse spatial resolution of the GRACE and GRACE-FO data sets of approximately 350 km, finer spatial details of such extreme events are kept hidden. Further, spatial leakage limits the value of these data for smaller-scale regional investigations.

In this contribution, we will employ five years of simulated data for both a single polar pair (GRACE-FO-like) and a MAGIC baseline scenario. Thanks to the simulation, we can also assess the true values of the hydrological input models. Both simulated data sets are filtered with the same DDK filters for comparison. The filter strength can be reduced for the MAGIC baseline scenario without introducing more striping errors.

With these simulated data sets, we investigate extreme hydrological events. For example, the localisation of extreme wet events along the northern coast of Australia is much improved, with less signal leakage into the surrounding ocean.

How to cite: Boergens, E., Wilms, J., Hauk, M., Dahle, C., Dobslaw, H., and Flechtner, F.: Will the MAGIC mission improve the observability of extreme hydrological events?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8830, https://doi.org/10.5194/egusphere-egu24-8830, 2024.

Changes in soil water storage can be studied on a global scale using a variety of satellite observations. With active or passive microwave remote sensing, we can study the upper few centimeters of the soil, while satellite gravimetry allows us to detect changes in the entire column of terrestrial water storage (TWS). The combination of both types of data can provide valuable insight into hydrological dynamics in different soil depths towards a better understanding of changes in subsurface water storage.

We use daily Gravity Recovery and Climate Experiment (GRACE) data and satellite soil moisture data to identify extreme hydroclimatic events, focusing on prolonged droughts. To enhance our comprehension of the subsurface, we utilize not just surface soil moisture data but also integrate information on root zone soil moisture. Original level-3 surface soil moisture data sets of SMAP and SMOS are compared to post-processed level-4 data products (both surface and root zone soil moisture) and a multi-satellite product provided by the ESA CCI.

We analyse the correspondence between high and low percentiles in TWS and soil moisture time series, which allows us to identify extreme events in different integration depths and storage compartments. Furthermore, we compute the rate of change of anomalies to assess how quickly the system accumulates storage deficits during drought conditions and recovers from them for different soil depths. Our investigation focuses on the temporal dynamics of near-surface soil moisture and TWS, highlighting the cascading effects that propagate from the surface into the subsurface. The results we obtained indicate characteristic patterns of the temporal dynamics of drought recovery in varying soil depths. Specifically, our analysis shows that surface soil moisture recovers faster than TWS, and that this recovery process slows down as soil integration depth increases.

How to cite: Blank, D., Eicker, A., and Güntner, A.: From surface to subsurface: Investigating drought cascades and recovery patterns with (daily) satellite observations of soil moisture and terrestrial water storage, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7888, https://doi.org/10.5194/egusphere-egu24-7888, 2024.

During periods of drought, quantifying the intensity of water loss within hydrologic reservoirs, both on and below the surface, is critical to sustain water resources. Drought intensity is typically characterized using drought indices which are driven by meteorologic observations, such as precipitation. These drought indices provide good insight into the quantity of water entering the hydrologic system, however, they are unable to quantify the amount of water retained in a watershed or the amount lost due to runoff and evapotranspiration. We address this by leveraging the sensitivity of three-dimensional Global Positioning System displacements to local and regional hydrologic-storage fluctuations, and produce a new geodetic drought index (GDI), derived from estimated hydrologic-storage deviations, to directly characterize hydrologic storage anomalies. The GDI is derived comparably to the Standardized Precipitation Evapotranspiration Index such that it may be easily incorporated into current drought management workflows. We directly compare the GDI to hydrologic observations within California and find strong associations between specific time scales of the GDI and groundwater well, artificial-reservoir storage, and stream discharge observations. The GDI is most sensitive to groundwater, exhibiting a correlation coefficient of 0.87 at the 3-month time scale. Both artificial-reservoir storage and stream discharge exhibit peak correlation coefficients when considering the 1-month GDI, at 0.81 and 0.47 respectively. No relationship is observed with soil moisture observations. The correlation coefficients decline rapidly away from the optimal time scale, indicating the 1- and 3-month GDI are strong predictors of hydrologic variation within California. In addition to capturing long-term trends, rapid changes in the GDI initiate during clusters of large atmospheric-river events that closely mirror fluctuations in the hydrologic observations. The GDI provides an opportunity to improve hydrologic models for drought-management and to advance our understanding of the water cycle.

How to cite: Young, Z. M., Martens, H. R., Hoylman, Z. H., and Gardner, W. P.: A Geodetic Drought Index Driven by Hydrologic Loading Estimates Calculated from Three-Dimensional GPS Displacements  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3658, https://doi.org/10.5194/egusphere-egu24-3658, 2024.

Drought is one of the most complex recurring natural disasters, defined by a deficiency of precipitations that causes prolonged water scarcity. Failure to manage drought risk has the potential to have dire consequences for people, livelihoods, economy and ecosystems.
In northern Italy, particularly in the highly productive industrial area of the Po river basin, the 2021-2022 period culminated in the most severe drought of the last two centuries.
In order to evaluate the best policies to address the problems caused by water scarcity, it is crucial to measure and monitor variations in terrestrial water storage (TWS). For drought monitoring, in fact, changes or anomalies in TWS provide direct observations of total water availability, complementing model-based measures such as drought severity indices.
To estimate the quantities and spatial distribution of TWS loss, we analyze vertical ground displacement time-series data from Global Navigation Satellite System (GNSS) stations in the Po river basin.
We use a regularization model, based on L1-norm, to reconstruct the long-term temporal evolution of vertical ground displacement trends. Next, we performed a Principal Component Analysis (PCA) on GNSS time series to extract a spatially consistent signal in vertical ground displacements. The temporal evolution of the first principal component is well-correlated with trend changes of the Po river level and with the  SPEI-12 drought index, with stations moving upward during periods of river/index level decrease and vice versa, indicating that common long-term variations in vertical ground displacements are driven by the hydrology of the area.
The inversion of the displacements associated with the first principal component allows us to estimate variations in equivalent water height (EWH) and find that between January 2021 and August 2022, the GNSS stations underwent uplift, up to 7 mm, which corresponds to ~70 Gtons of water loss. The results are compared with the Global Land Data Assimilation System (GLDAS) model and the Gravity Recovery and Climate Experiment (GRACE) data: while the temporal evolution of the three products, when averaged over the study area, is similar, the spatial distributions are different. This is likely due to the fact that GLDAS only takes surface water into account, and GRACE has a too-coarse spatio-temporal resolution.
Our results show that multi-year changes in water storage can be effectively monitored both in terms of temporal evolution and spatial distribution using space geodetic measurements, such as GNSS. This approach eliminates the need to rely solely on large-scale models or satellite measurements, which cannot reach the spatial resolution required at the scale of river basins such as the Po.

How to cite: Pintori, F. and Serpelloni, E.: Drought‐Induced Vertical Displacements and Water Loss in the Po River Basin (Northern Italy) From GNSS Measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12650, https://doi.org/10.5194/egusphere-egu24-12650, 2024.

The distribution of atmospheric, hydrological, and oceanic mass loads on the lithosphere affects the deformation of the Earth's surface over time. Monitoring of the relative displacements of the dense global network of permanent Global Navigation Satellite System (GNSS) stations enables the direct measurement of these loads on a global scale. The application of inverse GNSS methods provides an independent tool to retrieve the time variable gravity (TVG) models of the Earth system and to support hydrogeodesy studies, including the monitoring of the water storage cycle or polar ice mass loss.

The goal of this study is to investigate the effectiveness of using inverse GNSS methods to provide independent C₂₀ and C₃₀ coefficients. These coefficients are essential for deriving highly accurate Gravity Recovery and Climate Experiment (GRACE)-based TVG models. In this study, surface mass variations of low-degree TVG coefficients are derived from the displacements of continuously tracking GNSS sites based on the 21 years (2000-2021) of the Center for Orbit Determination in Europe solutions of the 3rd data reprocessing campaign of the International GNSS Service in the framework of the preparation of the International Terrestrial Reference Frame 2020. The geometrical displacements of the GNSS stations calculated by inverse methods are compared with changes in the gravity field based on independent estimates obtained from the GRACE and GRACE Follow-On (GRACE-FO) satellite missions and the Satellite Laser Ranging (SLR).

As an alternative to the solutions provided by SLR, it is shown that the C₂₀ and C₃₀ coefficients can be derived based on GNSS station displacements. The challenge of the inverse GNSS approach is to properly choose the maximum degree of TVG expansion. Compared with the SLR-based solution, the most consistent GNSS estimate of the temporal gravity variation rate of the C₂₀ coefficient (−1.73 ± 0.10 × 10⁻¹¹/year) and annual variation (4.7 ± 0.6 × 10⁻¹¹/43.9° ± 7.5°) was obtained by expansion of the spherical harmonics to degree and order of 8. The GNSS-based C₃₀ series is superior to the SLR-based estimates before the launch of the Laser Relativity Satellite. From August 2016, when the C₃₀ estimates are essential for correcting the GRACE solutions, the root mean square between GNSS and SLR solutions is 4.2 × 10⁻¹¹. GNSS could potentially support GRACE/GRACE-FO solutions that face problems in deriving C₂₀ and C₃₀, which are fundamental to estimates of ice mass changes in the polar regions. Recovery of mass change in the Antarctic ice sheet from April 2002 to December 2020 based on the coefficients replaced by GNSS estimates results in a linear trend of −111 ± 3 Gt/year. In comparison, the trend for the SLR-based replacement from Technical Note 14 shows a trend of −114 ± 2 Gt/year.

How to cite: Nowak, A., Zajdel, R., Gałdyn, F., and Sośnica, K.: Using Inverse GNSS Methods for the Determination of C20 and C30 Gravity Field Coefficients for the Support of GRACE Solutions   , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-327, https://doi.org/10.5194/egusphere-egu24-327, 2024.

The ever-changing fluid mass (oceans, continental water, snow, atmosphere, …) redistributions on the Earth's surface give rise to a motion of the deformable terrestrial crust, that is its geometrical center-of-figure (CF), with respect to the center-of-mass (CM) of the Earth, about which satellites naturally orbit. This motion, called “geocenter motion”, is the largest scale variability of mass within the Earth system. Yet, non-tidal geocenter motion, which reflects major water and atmosphere mass transports occurring over large regions, is traditionally neglected.

However, new climate-driven precise monitoring of geocenter motion is needed. Indeed, satellite altimetry and gravimetry precise orbits connect sea level and global water budgets to the Earth’s center of mass. As such, the geocenter motion is now the leading error term in Regional Mean Sea Level and mass changes over polar ice sheets estimates. Reliable solutions of geocenter motion are thus crucial for assessing the current status of climate change and its future evolution (e.g., for the Earth’s Energy Imbalance).

Global Navigation Satellite Systems (GNSS) measurement models and derived products are currently aligned to the International Terrestrial Reference Frame (ITRF) origin (which is referenced to the crust), instead of CM. Looking at sub-daily cross-track perturbations estimated with the GNSS receivers on board the Jason-3 and Sentinel-6 MF altimetry satellites during their tandem phase (December 18, 2020 – April 7, 2022) revealed consistent diurnal oscillations with an impressive temporal resolution. These could only be related to the miscentering effect of the constellation solution around the Earth’ CM. In this paper, a parametric model is derived, representing the translation of the GNSS ground station networks with respect to the center of mass of the whole Earth system. This model is estimated with GNSS-based low Earth satellite precise orbits and unambiguously validated with independent altimetry satellite missions (e.g., Sentinel-3A, Sentinel-6 MF, Jason-3). It helps to clearly identify interannual variations in the geocenter motion, as short as a day long.

How to cite: Couhert, A., Mercier, F., Moyard, J., and Exertier, P.: Assessing daily to interannual geocenter motion variations from Low Earth Orbiters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17367, https://doi.org/10.5194/egusphere-egu24-17367, 2024.

We are strengthening the application of GPS's capability to estimate change in total water using measurements of elastic displacements of Earth's surface; breaking down total water into its components such as snow, soil moisture, and groundwater; and integrating GRACE gravity data to infer change in total water in groundwater basins.

In California's Sierra Nevada, GPS each day tracks the dumping and dissipation of storm water.  In Water Year 2023, total water increased abruptly during each of two sequences of snow-dominated atmospheric rivers.  Subsurface water, which we take to be total water inferred from GPS minus snow water equivalent, to rise in early January at the time of the first AR sequence, remain constant from late Jan through March (with no increase during the second AR sequence), and rise from April to June as the snowpack melts.  Subsurface water increases in the Sierra Nevada by 0.6 m from Oct 2022 to Jun 2023, 45 per cent of cumulative precipitation of 1.4 m.  Such a big rise in subsurface water begins to rejuvenate the Sierra Nevada critical zone (Earth's living outer layer between the top of the trees and the bottom of groundwater) and to replenish subsurface water lost during the prior 3 years of drought from 2020 to 2022.

Change in total water in California's Central Valley can be determined neither by GRACE alone nor GPS alone.  There GPS records primarily Earth's poroelastic response, from which water change is difficult to infer.  GRACE cannot distinguish water change in Central Valley from water change in the Sierra Nevada without assuming a hydrology model.  We integrate GPS elastic displacements and GRACE gravity to estimate water change in the Central Valley.  In the rigorous inversion, GPS determines water change in the Sierra Nevada and Coast Ranges and the remaining water change from GRACE is placed in the Central Valley.  We find Central Valley groundwater increased by 0.75 m in the first nine months of Water Year 2023 (the biggest gain ever recorded), replenishing more groundwater than lost during the prior 3 years of drought.

How to cite: Argus, D., Martens, H., David, W., Matthew, S., Adrian, B., Athina, P., Lau, N., Kim, D., Gaastra, K., Ellmer, M., Young, Z., Knappe, E., Molotch, N., Alam, S., Landerer, F., Gardner, P., and John, R.: The Big Soak:  Change in Water in 2023 in North America's Pacific Mountain System , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14655, https://doi.org/10.5194/egusphere-egu24-14655, 2024.