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Map of the Caspian Sea and surrounding countries (modified from an original map provided by the Nations Online Project at http://www.nationsonline.org/).
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We examine recent Caspian Sea level change using both satellite radar altimetry and satellite gravity data. The altimetry record for 2002-2015 shows a declining level at a rate that is approximately 20 times greater than the rate of global sea level rise. Seasonal fluctuations are also much larger than in the world oceans. With a clearly defined ge...
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Context 1
... Caspian Sea is the largest enclosed inland body of water on Earth, with a surface area of ~371,000 km 2 . Located within an endorheic (no outflow) basin between Europe and Asia, it is surrounded by five countries (Russia, Kazakhstan, Turkmenistan, Iran, and Azerbaijan) ( Figure 1) and has a sea level history independent of global ocean eustatic changes. Average Caspian Sea level is currently about 27.5 m below mean sea level. ...
Context 2
... ARGO steric and GLDAS TWS annual phases are about right, then the GRACE forward modeled annual component appears to be reasonably accurate. Similar annual phasor diagrams for the three mascon estimates (JPL MC + LC, CSR MC + 200 km/LC, and CSR MC + SF/LC) are shown in Figure 10 (the results from CSR MC SF/LC are also included in the phasor diagram for comparisons). ...
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We analyze the impact of large earthquakes on the estimation of the global mean ocean mass (GMOM) change rate over the 13-year period (January 2003 to December 2015) using the Gravity Recovery and Climate Experiment (GRACE) Release-06 (RL06) monthly gravity solutions released by the Center for Space Research (CSR). We take into account the effects...
Citations
... We adopted the monthly mascon solutions published by the following [44], which have been widely used in hydrology fields. Nonetheless, the imperfect leakage correction of mascon solutions may still lead to an underestimation of the regional mass change trends [45]. For comparison, we also estimated the TWS mass anomalies using the GRACE-FO spherical harmonic coefficient solutions (up to 60 degrees/order) released by CSR from October 2018 to October 2022. ...
... We adopted the monthly mascon solutions published by the following These mascon solutions, compared with traditional spherical harmonic coefficients, enhance signal resolution and also significantly mitigate signal leakage errors [44], which have been widely used in hydrology fields. Nonetheless, the imperfect leakage correction of mascon solutions may still lead to an underestimation of the regional mass change trends [45]. For comparison, we also estimated the TWS mass anomalies using the GRACE-FO spherical harmonic coefficient solutions (up to 60 degrees/order) released by CSR from October 2018 to October 2022. ...
The southeastern Tibetan Plateau (SETP), which hosts the most extensive marine glaciers on the Tibetan Plateau (TP), exhibits enhanced sensitivity to climatic fluctuations. Under global warming, persistent glacier mass depletion within the SETP poses a risk to water resource security and sustainability in adjacent nations and regions. This study deployed a high-precision ICESat-2 satellite altimetry technique to evaluate SETP glacier thickness changes from 2018 to 2022. Our results show that the average change rate in glacier thickness in the SETP is −0.91 ± 0.18 m/yr, and the corresponding glacier mass change is −7.61 ± 1.52 Gt/yr. In the SETP, the glacier mass loss obtained via ICESat-2 data is larger than the mass change in total land water storage observed by the Gravity Recovery and Climate Experiment follow-on satellite (GRACE-FO), −5.13 ± 2.55 Gt/yr, which underscores the changes occurring in other land water components, including snow (−0.44 ± 0.09 Gt/yr), lakes (−0.06 ± 0.02 Gt/yr), soil moisture (1.88 ± 1.83 Gt/yr), and groundwater (1.45 ± 0.70 Gt/yr), with a closure error of −0.35 Gt/yr. This demonstrates that this dramatic glacier mass loss is the main reason for the decrease in total land water storage in the SETP. Generally, there are decreasing trends in solid water storage (glacier and snow) against stable or increasing trends in liquid water storage (lakes, soil moisture, and groundwater) in the SETP. This persistent decrease in solid water is linked to the enhanced melting induced by rising temperatures. Given the decreasing trend in summer precipitation, the surge in liquid water in the SETP should be principally ascribed to the increased melting of solid water.
... Moreover, for popular GRACE products in terms of spherical harmonics (SH), an additional postprocessing step such as decorrelation and spatial smoothing 20,21 is necessary to reduce the correlated and high degree errors. However, postprocessing is accompanied by signal attenuation and distortion 3,22,23 . As alternatives to SH products, the mascon GRACE products provide grid results with improved resolutions that can be used directly without postprocessing [24][25][26][27] . ...
Given the spatial resolution of ~300 km in Gravity Recovery and Climate Experiment (GRACE) measurements, accurately quantifying mass variations at smaller scales proves challenging. Here, we present a high-resolution time-variable gravity field model of continental North China. This model, denoted as IGP-NorthChina2022TG, contains 15 gravity field solutions determined using an innovative approach that relies on terrestrial gravity measurements and Slepian basis functions. IGP-NorthChina2022TG provides degree 150 gravity changes (spatial resolution of ~120 km) on a semi-annual basis from September 2009 to September 2016, in contrast to the monthly degree 60 GRACE solutions. Despite their different temporal resolutions, the good agreement between GRACE and the ground-based results up to degree 60 confirms the robustness and reliability of the proposed method and favors the combination of these two types of measurements. The gravity changes with much finer spatial resolution from IGP-NorthChina2022TG could complement GRACE solutions for sub-regional scale investigations in North China.
... The original mass fields are contaminated by north-south stripe noise, which is linked to the correlated errors in the SHCs (i.e., spurious correlations between specific ΔC nm /ΔS nm ). To this end, researchers used the PnMl method Chen et al., 2017). The P4M6 method treats all ΔC nm /ΔS nm with the same m as a series. ...
In this study, we aim to estimate the mass changes in Panama using the Gravity Recovery and Climate Experiment level-2 products, which are formed as spherical harmonic coefficients and limited by stripe noise. The empirical de-striping method and the temporal filter achieved by empirical mode decomposition can be used to reveal the signals but are still limited in signal reservation and noise reduction. To this end, we put forward a novel efficient strategy that uses the variational mode decomposition algorithm to filter the time series of each SHC separately. Based on the two reliable mascon products and in situ short-term groundwater observations, various comparisons in spatial, spectral, and temporal domains are implemented. In addition, the SNR (signal-to-noise ratio) index and the three-cornered hat method are adopted for assessment. The main results and conclusions are as follows: 1) Our filter outperforms the two previous methods with the best SNR (2.14) and the lowest Panama regional uncertainty (70 mm) for all available months. 2) Our estimate of the basin groundwater storage is closest to one of the groundwater observations with the maximum correlation coefficient (0.72, p<0.05). This result suggests that our method seems to detect small-scale mass signals that are undetectable in the two mascon products. Our work provides a reference for studying the mass change of small-scale basins in low latitudes.
... In the GRACE data, we identify large negative trends i.e. increasing water deficit with −15 mm/a or more, e.g., in the Parana-Sao Francisco-Atlantico river basins in South America, the Caspian Sea region, in parts of Northern India and in glacier regions such as Alaska, Patagonia, and Northern Canada. This is not surprising, as in previous studies (e.g., Gardner et al. 2011;Luthcke et al. 2013;Getirana 2016;Panda and Wahr 2016;Chen et al. 2017;Rodell et al. 2018); these regions were identified to have been affected by severe droughts, decreasing surface water levels, groundwater depletion and melting of glaciers. In contrast, large positive trends (i.e., wetting) can be found in Eastern Canada, West Africa, the Zambesi basin and African Great Lake region, and in the La Plata basin in South America, which were all associated with regions that are either experiencing increasing precipitation and/or transform from dry to wet conditions, e.g., recovery after a drought during the observation period takes place (e.g., Rodell et al. 2018). ...
We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5\(^\circ \), covering the time frame 2003 to 2019 without gaps, and including monthly uncertainty quantification. GLWS2.0 was derived by assimilating monthly GRACE/-FO mass change maps into the WaterGAP global hydrology model via the ensemble Kalman filter, taking data and model uncertainty into account. TWSA in GLWS2.0 is then accumulated over several hydrological storage variables. In this article, we describe the methods and data sets that went into GLWS2.0, how it compares to GRACE/-FO data in terms of representing TWSA trends, seasonal signals, and extremes, as well as its validation via comparing to GNSS-derived vertical loading and its comparison with a version of the NASA Catchment Land Surface Model GRACE Data Assimilation (CLSM-DA). We find that, in the average over more than 1000 stations globally, GLWS2.0 correlates better with GNSS observations of vertical loading at short-term, seasonal, and long-term temporal bands than GRACE/-FO. While some differences exist, overall GLWS2.0 agrees reasonably well with CLSM-DA in terms of TWSA trends and annual amplitudes and phases.Highlights
We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies over the global land with a spatial resolution of 0.5\(^\circ \), covering the period 2003 to 2019 without gaps, and including uncertainty quantification.
GLWS2.0 synthesizes monthly GRACE/-FO mass change maps with daily precipitation and radiation data via the WaterGAP model framework, taking data and model uncertainty into account.
Here we describe the methods and data sets that went into GLWS2.0 and its validation from a geodetic applications perspective. We find that, in the global average, GLWS2.0 fits better than GRACE/-FO to GNSS observations of vertical loading.
... There is an irrational correlation between SHCs of the specific degree (odd or even) for an order m [62]. Some studies used the PnMl (e.g., P4M6) method to remove the noise for the mass estimation of ice caps [26], mountain glaciers [63], and TWS [64]. For instance, in the case of the P4M6 method, this algorithm reserves the SHCs of low degrees (0~6). ...
Among the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on temporal gravity products, the north–south stripe noise in the spherical harmonic coefficient (SHC) products contaminates the inversion of the Earth’s mass field. In this study, GRACE SHC products are adopted to estimate the mass changes in Nicaragua. To improve this estimation, we propose an empirical low-pass filter to suppress stripe noise. After only using our filter, the Nicaragua regional uncertainty diminishes from 123.26 mm to 69.11 mm, and the mean signal-to-noise ratio of all available months (2002–2021) improves from 1.67 to 1.8. Subsequently, our filter is employed to estimate the basin terrestrial water storage (TWS) change in Nicaragua. In the end, TWS change estimations are compared with various observations such as mascon products, hydrological models, and in situ groundwater observation. The main conclusions are as follows: (1) After using the wavelet coherent analysis, there is a negative resonance between TWS and the climate factor (El Nino–Southern Oscillation) with a period of 2~4 years; (2) The significant ~3.8-year periodic signal in groundwater storage change estimation is contributed by GRACE aliasing error. Our work can provide new knowledge and references for mass change in small areas.
... Since the launch of the Gravity Recovery and Climate Experiment (GRACE) satellite in 2002, the time-variable gravity field models recovered from GRACE's observations have been widely used in the research of various fields, such as the global water cycle and land water storage change, 1-4 the global mean sea level (GMSL) change, 5,6 and the detection of coseismic signals. 7,8 With global warming, the mass change caused by polar ice sheet melting can be monitored by the GRACE satellite. ...
... The high frequency signal is unlikely related to changes in the Caspian sea level as supported by satellite altimetry measurements (J. Chen et al., 2017). Other examples of MSSA decomposition at various locations are provided in Figure S12. ...
... Validation of solutions against independent observations is thus essential to assess solution quality (J. Chen et al., 2017). ...
... portunities to validate GRACE/GRACE-FO solutions. In particular, due to its large spatial extent, significant signal amplitude and minimal groundwater variations in the region, the Caspian sea has become an ideal candidate to seek validation of mass change measurements with sea level variations measured by satellite altimetry (Swenson & Wahr, 2007;J. Chen et al., 2017). Nonetheless, the comparison of GRACE/GRACE-FO SH estimates at the regional scale with independent datasets suffers another challenge. ...
Gravity Recovery And Climate Experiment and Follow On (GRACE/-FO) global monthly measurements of Earth's gravity field have led to significant advances in quantifying mass transfer. However, a significant temporal gap between missions hinders evaluating long-term mass variations. Moreover, instrumental and processing errors translate into large non-physical North-South stripes polluting geophysical signals. We use Multichannel Singular Spectrum Analysis (M-SSA) to overcome both issues by exploiting spatio-temporal information of Level-2 GRACE/-FO solutions, filtered using the DDK7 decorrelation and a new complementary filter, built based on the residual noise between fully processed data and a parametric fit to observations. Using an iterative M-SSA on Equivalent Water Height (EWH) time series processed by Center of Space Research, GeoForschungsZentrum, Institute of Geodesy at Graz University of Technology, and Jet Propulsion Laboratory, we replace missing data and outliers to obtain a combined evenly sampled solution. Then, we apply M-SSA to retrieve common signals between each EWH time series and its same-latitude neighbors to further reduce residual spatially uncorrelated noise. Comparing GRACE/-FO M-SSA solution with Satellite Laser Ranging and Swarm low-degree Earth's gravity field and hydrological model demonstrates its ability to satisfyingly fill missing observations. Our solution achieves a noise level comparable to mass concentration (mascon) solutions over oceans (3.0 mm EWH), without requiring a priori information nor regularization. While short-wavelength signals are challenging to capture using highly filtered spherical harmonics or mascons solutions, we show that our technique efficiently recovers localized mass variations using well-documented mass transfers associated with reservoir impoundments.
... The mascon products are available from three centers: JPL, CSR, and GSFC, at a grid sampling of ≤1 • . The RL06 CSR mascon solution is based on the regularization method and derived entirely from the GRACE information without any input from external models, and, unlike the JPL solution, is independent from TWS and other geophysical models (Chen et al., 2017;Save et al., 2016). The solutions are computed on an equal area geodesic grid composed of hexagonal tiles, approximately 120 km wide or 1 • × 1 • at the equator (Chen et al., 2017). ...
... The RL06 CSR mascon solution is based on the regularization method and derived entirely from the GRACE information without any input from external models, and, unlike the JPL solution, is independent from TWS and other geophysical models (Chen et al., 2017;Save et al., 2016). The solutions are computed on an equal area geodesic grid composed of hexagonal tiles, approximately 120 km wide or 1 • × 1 • at the equator (Chen et al., 2017). The spatial resolution of CSR RL06M v01 (hereinafter abbreviated as CSR v01) for the equivalent water height (EWH) is 0.25 • × 0.25 • , whereas its temporal resolution is monthly from January 2003 to December 2016. ...
The Urmia lake in north-west Iran has dried up to perilously low levels in the past two decades. In this study, we investigate the drivers behind the decline in lake water level with the help of in-situ and remote sensing data. We use total water storage (TWS) changes from the gravity recovery and climate experiment (GRACE) satellite mission. TWS from GRACE includes all the water storage compartments in a column and is the only remote sensing product that can help in estimating groundwater storage (GWS) changes. The coarse spatial (approx. 300 km) resolution of GRACE does not allow us to identify local changes that may have led to the Urmia lake disaster. In this study, we tackle the poor resolution of the GRACE data by employing three machine learning (ML) methods including random forest (RF), support vector regression (SVR) and multi-layer perceptron (MLP). The methods predict the groundwater storage anomaly (GWSA), derived from GRACE, as a function of hydro-climatic variables such as precipitation, evapotranspiration, land surface temperature (LST) and normalized difference vegetation index (NDVI) on a finer scale of 0.25° × 0.25°. We found that i) The RF model exhibited highest R (0.98), highest NSE (0.96) and lowest RMSE (18.36 mm) values. ii) The RF downscaled data indicated that the exploitation of groundwater resources in the aquifers is the main driver of groundwater storage and changes in the regional ecosystem, which has been corroborated by few other studies as well. The impact of precipitation and evapotranspiration on the GWSA was found to be rather weak, indicating that the anthropogenic derivers had the most significant impact on the GWSA changes. iii) We generally observed a significant negative trend in GWSA, having also significant positive correlations with the well data. However, over regions with dam construction significant negative correlations were found.
... Then, the selected scale factor is multiplied with the filtered GRACE TWSA to produce the rescaled GRACE TWSA. The accuracy of the restored GRACE signal depends on the accuracy of the scale factor (Chen et al. 2017). Large-scale hydrologic models typically simulate soil moisture and snow water. ...
The Gravity Recovery And Climate Experiments (GRACE) satellite mission has been instrumental in estimating large-scale groundwater storage changes across the globe. GRACE observations include significant errors, so pre-processing is normally required before the data are used. In particular, the terrestrial water storage anomalies (TWSA) are usually filtered to reduce the effects of measurement errors and then rescaled to reduce the unintended impacts of the filtering. The scaling is typically selected to maximize the Nash-Sutcliffe Efficiency (NSE) between the rescaled filtered TWSA and the original TWSA from large-scale hydrologic models that represent an incomplete water budget. The objectives of this study are as follows (1) to evaluate the use of NSE in the current GRACE rescaling methodology, (2) develop an improved methodology that incorporates a complete regional water budget, and (3) examine the impacts of the rescaling methodology on regional assessments of groundwater depletion. To evaluate the use of NSE as a performance metric, we compare it to an analytical solution that restores the relative variability between the rescaled filtered and original GRACE TWSA series. The relative variability approach produces more reliable estimates when comparing to TWSA estimates from global positioning systems (GPS) for the Sacramento and San Joaquin River basins in California. Rescaling the complete regional water budget results in a larger scale factor than the scale factor from the large-scale hydrologic model outputs, and the new TWSA results are more consistent with those from GPS. The large scale factor also suggests that regional groundwater depletion is more severe than previously estimated.
... From south to north, from the humid subtropical climate in the southern Himalayas to the cold semiarid climate in the southern TP, the spatial difference of climate change leads to the uneven distribution of glacier mass in the TP [14], [15]. In addition, glacier melting or accumulation may lead to abnormal changes in river flow, such as increased water volume, nonseasonal floods, and drought, and may even make a significant contribution to global sea-level rise [16], [17], [18]. However, only a few glaciers have been continuously monitored for more than a decade due to the steep topography and geographical location. ...
Glacier mass changes in high mountainous areas are in an unbalanced status due to global climate warming. In this study, we use the Gravity Recovery and Climate Experiment as well as its Follow-on mission (GRACE/GRACE-FO) data to constrain the spatiotemporal variations of glacier mass in the high mountain of Tibetan Plateau (TP) during 2002 and 2020. The total glacier mass balance shows a descending trend over the TP and its surroundings with an overall melting rate of ~21 Gt/yr in the past two-decades. The significant glacier mass loss of spatial pattern is mainly concentrated in the periphery of the TP, such as the Himalayas, Hindu Kush and Tianshan, while the Kunlun Mountains demonstrates an increasing trend of glacier mass balance. The annual variation of glaciers in 22 sub-regions shows significant spatial differences in the amplitudes and phases, which is the direct feedback of regional climate change. In addition, based on the wavelet spectrum analysis, we find that the abnormal glacier mass changes correlate well with the interannual oscillations of precipitation and temperature. This corresponds to the extreme climate events, such as 2010-2012 La Niña event and 2015-2016 El Niño event. All these results validate the climate process in response to the interannual variation of glaciers on the TP, thus is of great significance to the study of systematic balance of regional water cycle.
