Gravity Recovery And Climate Experiment Research Articles

Spatiotemporal coupling analysis of surface water and groundwater in Tibet based on multi-source sensors

Abstract. Lakes and groundwater are two crucial components of the global terrestrial water cycle, collectively forming a vital network for Earth's water resources. However, in the Tibetan region, the spatiotemporal relationship between lakes and groundwater and their impact on the local hydrological cycle remain inadequately understood. Satellite remote sensing serves as an effective observational tool, enabling comprehensive investigation and analysis of surface lakes and groundwater in Tibet with high spatial resolution. Therefore, this study integrates Landsat and Cryosat-2 satellite data to examine the spatiotemporal patterns of surface lake extents and water levels in Tibet. Additionally, combining Gravity Recovery and Climate Experiment (GRACE) satellite observations with the Global Land Data Assimilation System (GLDAS) model data, we quantitatively analyze the spatiotemporal variations in groundwater storage and its correlation with lake water. The results indicate that: 1) Rivers and lakes in Tibet are mainly located in the central and northwest regions, displaying noticeable intra-annual variations; 2) Substantial lagged relationships exist between groundwater storage and lake water levels and areas, revealing that lakes contribute significantly to groundwater replenishment, especially in the Ngari prefecture and Lhokha prefecture. This study comprehensively utilizes multi-source remote sensing data to dynamically monitor surface and groundwater in Tibet, providing robust support for a better understanding of the interaction between groundwater and surface water.

Analysis of terrestrial water storage variations in South Korea using GRACE satellite and GLDAS data in Google Earth Engine

With the requirement of a macroscopic approach to understanding the relationship between water resources and hydrological phenomena, such as severe droughts under climate change, this study investigates South Korea’s long-term terrestrial water storage (TWS) using GRACE satellite data. A detailed analysis of water balance in TWS, based on the GLDAS model outputs in Google Earth Engine, reveals the following results: (1) TWS anomaly shows an averaged decrease of -33.5 mm yr−1 from 2003 to 2016. (2) Spatial shifts in TWS anomaly (-1.176 to -0.424 cm) unveil regional water storage dynamics, indicating negative temporal slope changes per grid cell (-0.393 to -0.225). (3) Contributions of precipitation to TWS are not always straightforward, due to runoff inefficiencies affecting water storage and groundwater. (4) Accessible water, integrating surface water and groundwater linked only to the shallow layer’s soil moisture, constrains deep groundwater accounting, emphasizing the need for local groundwater surveys in further research.

Statistical downscaling of GRACE terrestrial water storage changes based on the Australian Water Outlook model

The coarse spatial resolution of the Gravity Recovery and Climate Experiment (GRACE) dataset has limited its application in local water resource management and accounting. Despite efforts to improve GRACE spatial resolution, achieving high resolution downscaled grids that correspond to local hydrological behaviour and patterns is still limited. To overcome this issue, we propose a novel statistical downscaling approach to improve the spatial resolution of GRACE-terrestrial water storage changes (ΔTWS) using precipitation, evapotranspiration (ET), and runoff data from the Australian Water Outlook. These water budget components drive changes in the GRACE water column in much of the global land area. Here, the GRACE dataset is downscaled from the original resolution of 1.0° × 1.0° to 0.05° × 0.05° over a large hydro-geologic basin in northern Australia (the Cambrian Limestone Aquifer—CLA), capturing sub- grid heterogeneity in ΔTWS of the region. The downscaled results are validated using data from 12 in-situ groundwater monitoring stations and water budget estimates of the CLA’s land water storage changes from April 2002 to June 2017. The change in water storage over time (ds/dt) estimated from the water budget model was weakly correlated (r = 0.34) with the downscaled GRACE ΔTWS. The weak relationship was attributed to the possible uncertainties inherent in the ET datasets used in the water budget, particularly during the summer months. Our proposed methodology provides an opportunity to improve freshwater reporting using GRACE and enhances the feasibility of downscaling efforts for other hydrological data to strengthen local-scale applications.

Optimal combinations of global evapotranspiration and terrestrial water storage products for catchment water balance

ABSTRACT During the last two decades, a great number of global products about evapotranspiration ( E ) and terrestrial water storage ( S ) have been released. This has led to numerous combinations for describing catchment water balance, and hence determining an appropriate combination has become an important issue. The main objective of this study is to evaluate various global products of E and S at the catchment scale and determine the most appropriate combination, taking two Korean catchments as examples. For E , we evaluated global evapotranspiration (Global ET), Global Land Evaporation Amsterdam Model (GLEAM), and Penman–Monteith–Leuning (PML). For S , six individual datasets of Gravity Recovery and Climate Experiment (GRACE) were evaluated, with Global Land Data Assimilation System (GLDAS) products used for comparison. We found that the performance is sensitive to the choice of E product while various S products displayed minimal differences in results. Based on four evaluation criteria, the combination of PML and GRACE-SH-GFZ is suggested as the most suitable pair. For the period between 2003 and 2013, these data exhibit noteworthy trends of increasing E , offset by decreasing S . Warming climate is suspected to be behind these trends. Our research presents an approach that allows for the estimation of monthly streamflow exclusively with global data products, which is an advancement in hydrological analysis and particularly useful for regions that lack in-situ data networks. This approach provides a new perspective in the application of global datasets for the assessment of water balance and could significantly improve predictions in ungauged basins.

Understanding the shift in drivers of terrestrial water storage decline in the central Inner Mongolian steppe over the past two decades

Terrestrial water storage (TWS) in mid-latitude arid and semiarid Eurasia steppe is under threat from climate change and human activities. The central Inner Mongolian steppe is a hotspot of this change, and in addition serves as an important ecological barrier in North China. However, the limitations of scarce observations make the variations of TWS in this study area have not been well tracked and quantified yet, and the drivers of TWS remain unclear. Here we use the gravity recovery and climate experiment (GRACE) satellites and its follow-on (GRACE-FO) missions, combined with data-driven models to fill the data gaps between GRACE and GRACE-FO. A significant TWS decrease (−2.7 ± 0.2 mm/yr, p < 0.05) was captured over the past two decades (2002–2020), which is consistent with land surface models (LSMs) that assimilated with GRACE data (R = 0.81, p < 0.01). By integrating GRACE satellites and open-loop LSMs, the contrary trends of TWS were identified over the period, and GRACE contrasts with the increase in TWS simulated by LSMs that excludes human activities. We observe a shift in the dominant factor driving the TWS decline from climatic (2002–2010) to anthropogenic factors (2011–2020). This shift accounts for the anthropogenic-driven increase in TWS decline from −2.0 mm/yr to −4.4 mm/yr, indicating the increasingly significant impact of human activities on TWS. We further reveal the climate-driven mechanisms of TWS using wavelet analysis and multiple drought indicators. The results showed that the TWS decline in the first period was mainly caused by continuous droughts, which were driven by the deficit in precipitation-minus-evapotranspiration. This study highlights the risk of TWS depletion in the central Inner Mongolian steppe that is eco-fragile, providing insights into the water resources sustainability and ecosystem conservation in vast dryland ecosystems of the world.

Temporal and spatial variations of terrestrial water storage in the northeastern Tibetan Plateau retrieved by GNSS observations

The variation of solid Earth's hydrologic loading could cause the elastic vertical deformation of the crust, and the Global Navigation Satellite System (GNSS) could effectively monitor the vertical displacement of surface loads. However, the widely used Green's function method does not work well in areas where GNSS sites are sparse. Here, the vertical displacement time series of GNSS stations and the Slepian basis function method have been applied to convert displacement signals into spatial spectrum signals. The elastic mass load theory is used to study the changes in terrestrial water storage on the Northeastern Tibetan Plateau (NETP). The temporal and spatial characteristics of seasonal water changes are well-represented by the GNSS, the Gravity Recovery and Climate Experiment (GRACE), and the Global Land Data Assimilation System (GLDAS). Several data points suggest that the change in water storage shows a gradual increase from the northeast to the southwest. The greatest annual amplitude of water storage retrieved by GNSS is ~159 mm, which is greater than the ~47 mm and ~44 mm obtained by GRACE and GLDAS. These results demonstrate that GNSS is capable of capturing small-scale hydrological changes in this region, whereas GRACE and GLDAS data tend to underestimate seasonal variations in water storage. We also used GNSS to describe the hydrological drought conditions in NETP, showing that GNSS could be used as an independent method to characterize hydrological drought events. The findings suggest it could observe water storage with high spatial and temporal resolution and aid in comprehending regional hydrological trends with a sparse GNSS station network.

Estimation of groundwater storage variations in African river basins: Response to global climate change using GRACE and GRACE-FO among past two decades

Groundwater Storage (GWS) is an important component of the water cycle and a vital resource for supplying water to millions of people as well as sustaining domestic and economic activities, especially in arid and semi-arid regions such as Africa. This study aims to estimate and analyze the recent groundwater changes (ΔGW) for 11 major African basins in light of climate changes and global warming utilizing the data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) from January 2003 to December 2021. We proposed a new gap-filling technique to calculate the missing months between GRACE and GRACE-FO missions for the continuous estimation of groundwater changes. Then, we establish a new framework to analyze and investigated the climate parameters that could affect groundwater changes using Empirical Orthogonal Function (EOF) technique. Our analysis reveals that the new gap-filling technique is significantly consistent with the TWS time-series based on the trend line analysis. The lowest GPCC drought index value occurs in the lower Nile basin by approximately −0.93, while the highest occurs in the middle of Africa in Congo basin by approximately −0.02. The precipitation rate is mostly concentrated in mid-Africa while North and South Africa shows a weak rate. Meanwhile, according to the analysis of dependent climate parameters, climate change has had a negative impact on groundwater. However, the long-term effect on the groundwater does not clearly appear because most of Africa is located within semi-arid and arid regions. The effect of rain on groundwater was evident through EOF analysis, which shows GWS EOF Mode-2 (36.28%) and precipitation EOF Mode-1 (78.34%) were found to be in significant agreement in spatio-temporal domains.

Changes in terrestrial water storage in the Three-North region of China over 2003–2021: Assessing the roles of climate and vegetation restoration

Large-scale vegetation restoration has markedly enhanced ecosystem services in the Three-North (TN) region, concurrently exacerbating the pre-existing water resource crisis stemming from climate change in this arid domain. However, the specific contributions of climate and vegetation changes to the evolution of water resources in the TN region have yet to be elucidated. This study leverages data from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-on mission (GRACE-FO), specifically the terrestrial water storage anomaly (TWSA) from 2003 to 2021. We identify two TWSA rising (TWSA_rⅠ and TWSA_rⅡ) and two declining (TWSA_dⅠ and TWSA_dⅡ) hotspots in the TN region. By exploring the relative importance of climate drivers and vegetation dynamics in influencing the temporal dynamics of TWSA, we found that vegetation restoration assumes a more pivotal role than climate factors in 45.2% of the total area within the identified hotspots, predominantly evident in TWSA declining hotspots. The heightened TWSA in TWSA_rⅠ and TWSA_rⅡ primarily stems from precipitation recharge, with precipitation-dominated areas constituting 19.3% of the area within the identified hotspots. Potential evapotranspiration dominates TWSA changes in only 4.6% of the region within the identified hotspots, primarily scattered in TWSA_dⅠ and TWSA_dⅡ. Furthermore, a comparative assessment of soil moisture and groundwater responses to environmental factors indicates that water storage at shallower layers is more responsive to climate factors, while the impacts of vegetation changes on TWSA are more discernibly reflected in water storage at deeper layers. These findings furnish scientific guidance for future ecological restoration planning and sustainable water resources management.

Assessment of the Added Value of the GOCE GPS Data on the GRACE Monthly Gravity Field Solutions

The time-varying gravity field models derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission suffer from pronounced longitudinal stripe errors in the spatial domain. A potential way to mitigate such errors is to combine GRACE data with observations from other sources. In this study, we investigate the impacts on GRACE monthly gravity field solutions of incorporating the GPS data collected by the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) mission. To that end, we produce GRACE/GOCE combined monthly gravity field solutions through combination on the normal equation level and compare them with the GRACE-only solutions, for which we have considered the state-of-the-art ITSG-Grace2018 solutions. Analysis in the spectral domain reveals that the combined solutions have a notably lower noise level beyond degree 30, with cumulative errors up to degree 96 being reduced by 31%. A comparison of the formal errors reveals that the addition of GOCE GPS data mainly improves (near-) sectorial coefficients and resonant orders, which cannot be well determined by GRACE alone. In the spatial domain, we also observe a significant reduction by at least 30% in the noise of recovered mass changes after incorporating the GOCE GPS data. Furthermore, the signal-to-noise ratios of mass changes over 180 large river basins were improved by 8–20% (dependent on the applied Gaussian filter radius). These results demonstrate that the GOCE GPS data can augment the GRACE monthly gravity field solutions and support a future GOCE-type mission for tracking more accurate time-varying gravity fields.

Water availability identification from GRACE dataset and GLDAS hydrological model over data-scarce river basins of Ethiopia

ABSTRACT The nature of the heterogeneity of terrestrial water storage in the main river basins of Ethiopia is poorly understood. In river basins, measurements of terrestrial water storage changes are exceedingly rare in all temporal dimensions. This study investigates the spatiotemporal variation of water storage in the main river basins of Ethiopia using the Gravity Recovery and Climate Experiment (GRACE) with Global Land Data Assimilation System (GLDAS). The results revealed significant variation in liquid water equivalents from GRACE and terrestrial water storage from GLDAS for each river basin, following a seasonal pattern. I found that GRACE and GLDAS datasets can be combined effectively to evaluate the long-term water storage in large-scale basins with limited hydrological data, and the obtained result provides a reliable outcome that will be essential for the establishment of climate change adaptation pathways in the future for essential water resource management and optimization.

Preliminary Evidence for the Decline in Discharge at Falaj Daris, Nizwa, Oman

Falaj Daris is one of the oldest active aflāj located in Oman and the largest in the Dakhiliyah governorate. It is a 7,999-meter long Dāwūdī-type falaj. Ninety-five percent of water drawn from falaj Daris is used for agricultural irrigation and the remaining five percent is used for domestic purposes. In this paper, we analyzed several datasets including falaj Daris discharge, borehole water levels in wadi al-Abyadh, whose aquifer falaj Daris taps, and GRACE satellite data to determine the historical trend of falaj Daris discharge during 1982-2020. A set of standard statistical methods and data visualization techniques were applied including the Mann-Kendall trend test. Preliminary evidence shows a decline of 226,000 L/day in falaj Daris discharge between 1982-2020. This finding is supported by the overall trends in borehole water levels in wadi al-Abyadh. All these trends were confirmed using GRACE satellite data which shows a decrease in water volume of 6 (WET cm) in the larger basin between 2002-2021. Keywords: qanat; falaj Daris; wadi al-Abyadh; Nizwa, Oman; GRACE satellite.

VARIABILITY OF EQUIVALENT WATER HEIGHT (EWH) IN INDONESIA DURING 14 YEARS OF GRACE GRAVITY SATELLITE MISSION

GRACE Satellite (Gravity Recovery and Climate Experiment) is a gravity monitoring satellite, that is very sensitive to mass changes, especially the signals that produce by redistribution of water masses. Data from this satellite can be used to observe water distribution in the form of spherical harmonic coefficients. Water mass variations are presented as Equivalent Water Height (EWH). The results of GRACE processing showed that the largest EWH was 27.298 cm in January 2015 and the smallest EWH was 29.816 cm in June 2004 in Sumatera Island. The positive trend occurred in Sumatra island and the negative trend occurred in eastern Indonesia. Generally, the trend of Indonesian rainfall throughout 2002 to 2016 was constant. However, there was a change in seasonal patterns in 2014. This research also use Mascon data from GRACE satellite to determine the radius of the gaussian filter and TRMM satellite’s data to observe rainfall data to be compared with the EWH variability from GRACE.

Assessing the impact of agriculture, coal mining, and ecological restoration on water sustainability in the Mu Us Sandyland

Balancing water demand for socio–economic development and ecosystem stability presents a challenge for regional sustainable management, especially in drylands. Previous studies have indicated that large–scale ecological restoration projects (ERPs) lead to a decline in terrestrial water storage (TWS) in the Mu Us Sandyland (MUS). However, the effects of other human activities (e.g., cropland reclamation, coal mining) on water resources remain unclear, raising concerns regarding water crisis and human–natural system sustainability. Through the utilization of coal mine location data, we found that the impact of coal mass loss on the Gravity Recovery and Climate Experiment (GRACE) products cannot be ignored in MUS, especially in the coal–rich northeastern part. Combining these data with auxiliary datasets, we observed a significant (p < 0.05) decrease in TWS (−0.85 cm yr−1) and groundwater storage (GWS, −0.95 cm yr−1) in the MUS, with human activities accounting for 79.23 % of TWS and 90.45 % of GWS reductions, primarily due to increased agricultural and industrial water consumption. Agricultural water consumption increased 2.23 times from 2001 to 2020, attributed to enhanced water use intensity (62.6 %) and cropland expansion (37.4 %). Industrial water consumption in Shenmu, a representative coal county, experienced a 4.16–fold rise between 2001 and 2020. Despite these challenges, local governments have alleviated water stress, ensured food security, and increased household income by comprehensive management strategies, such as enhancing water–saving technology and enforcing stringent policies. Previous studies have overestimated the amount of water resources consumed by ERPs. However, ERPs has played a critical role in stabilizing the regional ecological environment and ensuring the region as a vital food and energy supplier. Our findings can guide for socio-economic development and water management policies in similar regions.

Reconstruction of Past Water Levels in Data-Deficient Karst Springs

Karst aquifers are crucial for providing fresh water worldwide but are also incredibly sensitive to human impact and climate change. This study aims to reconstruct the historical water levels of karst springs, despite the lack of data. By combining collected data, we have created a detailed numerical model to understand the complex behavior of karst aquifers. Our research reveals significant drops in the water levels at Longtan Spring, mainly due to the overuse of groundwater and inadequate water recharge, which is critical for the success of the Springs Resurgence project. We have also mapped out historical groundwater levels and identified the necessary conditions to get the spring flowing again. The model proved to be reliable during its calibration from 2000 to 2007, with an average Nash–Sutcliffe efficiency coefficient of 0.52 for the monitoring wells. For the period from 1960 to 2019, our model showed a strong correlation coefficient of over 0.97 when compared with data from the GRACE satellite mission, demonstrating its high accuracy. The approach we have taken in this study provides a feasible way to figure out historical water levels in karst springs, which is vital for protecting these essential fresh water sources. This work will provide a strong basis for policies to restore the spring.

Monsoon-Based Linear Regression Analysis for Filling Data Gaps in Gravity Recovery and Climate Experiment Satellite Observations

Over the past two decades, the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its successor, GRACE-follow on (GRACE-FO), have played a vital role in climate research. However, the absence of certain observations during and between these missions has presented a persistent challenge. Despite numerous studies attempting to address this issue with mathematical and statistical methods, no definitive optimal approach has been established. This study introduces a practical solution using Linear Regression Analysis (LRA) to overcome data gaps in both GRACE data types—mascon and spherical harmonic coefficients (SHCs). The proposed methodology is tailored to monsoon patterns and demonstrates efficacy in filling data gaps. To validate the approach, a global analysis was conducted across eight basins, monitoring changes in total water storage (TWS) using the technique. The results were compared with various geodetic products, including data from the Swarm mission, Institute of Geodesy and Geoinformation (IGG), Quantum Frontiers (QF), and Singular Spectrum Analysis (SSA) coefficients. Artificial data gaps were introduced within GRACE observations for further validation. This research highlights the effectiveness of the monsoon method in comparison to other gap-filling approaches, showing a strong similarity between gap-filling results and GRACE’s SHCs, with an absolute relative error approaching zero. In the mascon approach, the coefficient of determination (R2) exceeded 91% for all months. This study offers a readily usable gap-filling product—SHCs and smoothed gridded observations—with accurate error estimates. These resources are now accessible for a wide range of applications, providing a valuable tool for the scientific community.

Benchmarking multimodel terrestrial water storage seasonal cycle against Gravity Recovery and Climate Experiment (GRACE) observations over major global river basins

Abstract. The increasing reliance on global models for evaluating climate- and human-induced impacts on the hydrological cycle underscores the importance of assessing the models' reliability. Hydrological models provide valuable data on ungauged river basins or basins with limited gauge networks. The objective of this study was to evaluate the reliability of 13 global models using the Gravity Recovery and Climate Experiment (GRACE) satellite's total water storage (TWS) seasonal cycle for 29 river basins in different climate zones. Results show that the simulated seasonal total water storage change (TWSC) does not compare well with GRACE even in basins within the same climate zone. The models overestimated the seasonal peak in most boreal basins and underestimated it in tropical, arid, and temperate zones. In cold basins, the modeled phase of TWSC precedes that of GRACE by up to 2–3 months. However, it lagged behind that of GRACE by 1 month over temperate and arid to semi-arid basins. The phase agreement between GRACE and the models was good in the tropical zone. In some basins with major underlying aquifers, those models that incorporate groundwater simulations provide a better representation of the water storage dynamics. With the findings and analysis of our study, we concluded that R2 (Water Resource Reanalysis tier 2 forced with Multi-Source Weighted Ensemble Precipitation (MSWEP) dataset) models with optimized parameterizations have a better correlation with GRACE than the reverse scenario (R1 models are Water Resource Reanalysis tier 1 and tier 2 forced with the ERA-Interim (WFDEI) meteorological reanalysis dataset). This signifies an enhancement in the predictive capability of models regarding the variability of TWSC. The seasonal peak, amplitude, and phase difference analyses in this study provide new insights into the future improvement of large-scale hydrological models and TWS investigations.

Assessing Groundwater Sustainability in the Arabian Peninsula and Its Impact on Gravity Fields through Gravity Recovery and Climate Experiment Measurements

This study addresses the imperative to comprehend gravity shifts resulting from groundwater storage (GWS) variations in the Arabian Peninsula. Despite the critical importance of water resource sustainability and its relationship with gravity, limited research emphasizes the need for expanded exploration. The investigation explores the impact of GWS extraction on the gravity field, utilizing Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data in addition to validation using the WaterGAP Global Hydrology Model (WGHM). Spanning April 2002 to June 2023, this study predicts GWS trends over the next decade using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The comprehensive time-series analysis reveals a significant GRACE-derived groundwater storage (GWS) trend of approximately −4.90 ± 0.32 mm/year during the study period. This trend has a notable impact on the gravity anomaly (GA) values, as observed through the decomposition analysis. The projected GWS indicates a depletion rate of 14.51 km3/year over the next decade. The correlation between GWS and GA is substantial at 0.80, while the GA and rainfall correlation is negligible due to low precipitation rates. Employing multiple linear regression explains 80.61% of the variance in gravity anomaly due to GWS, precipitation, and evapotranspiration. This study investigates climate change factors—precipitation, temperature, and evapotranspiration—providing a holistic understanding of the forces shaping GWS variations. Precipitation and evapotranspiration exhibit nearly equal values, limiting GWS replenishment opportunities. This research holds significance in studying extensive GWS withdrawal in the Arabian Peninsula, particularly concerning crust mass stability.

Optimizing Parameters in the Common Land Model by Using Gravity Recovery and Climate Experiment Satellite Observations

Terrestrial water storage (TWS) is pivotal in understanding environmental dynamics, climate change, and human impacts. Despite the utility of land surface models, uncertainties persist in their parameterization schemes. This study employs GRACE (Gravity Recovery and Climate Experiment) satellite data to optimize the runoff parameterization scheme within the Common Land Model by a data assimilation and parameter optimization method. The optimization algorithm sets an adjustment factor that varies with time and space for runoff simulation and updates it along with the running of the land surface model. The evaluation reveals that there are improved correlation coefficients and reduced root mean square errors compared to GRACE observations. Independent assessments by using in situ river discharge observations demonstrate enhanced model performance, particularly in mountainous regions such as western North America. This study underscores the efficacy of integrating GRACE data to improve land surface model parameterization, offering more accurate predictions of TWS changes.

Spatiotemporal Evolution Features of the 2022 Compound Hot and Drought Event over the Yangtze River Basin

A rare compound hot and drought (CHD) event occurred in the Yangtze River Basin (YRB) in the summer of 2022, which brought serious social crisis and ecological disaster. The analysis of the causes, spatiotemporal characteristics and impacts of this event is of great significance and value for future drought warning and mitigation. We used the Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) data, meteorological data, hydrological data and satellite remote sensing data to discuss the spatiotemporal evolution, formation mechanism and the influence of the CHD event. The results show that the drought severity caused by the CHD event was the most severe during 2003 and 2022. The CHD event lasted a total of five months (from July to November), and there were variations in the damage in different sub-basins. The Wu River Basin (WRB) is the region where the CHD event lasted the longest, at six months (from July to December), while it also lasted four or five months in all the other basins. Among them, the WRB, Dongting Lake Rivers Basin (DLRB) and Mainstream of the YRB (MSY) are the three most affected basins, whose hot and drought severity values are 7.750 and −8.520 (WRB), 7.105 and −9.915 (DLRB) and 6.232 and −9.143 (MSY), respectively. High temperature and low precipitation are the direct causes of the CHD event, and the underlying causes behind this event are the triple La Niña and negative Indian Ocean Dipole event. The two extreme climate events made the Western Pacific Subtropical High (WPSH) unusually strong, and then the WPSH covered a more northerly and westerly region than in previous years and remained entrenched for a long period of time over the YRB and its adjacent regions. Moreover, this CHD event had a devastating impact on local agricultural production and seriously disrupted daily life and production. Our results have implications for the study of extreme disaster events.

Analysis of combined series of hydrological angular momentum developed based on climate models

Mass changes in the hydrosphere represent an important contributor to polar motion (PM) variations, especially at seasonal time scales (i.e., annual and semiannual). Although well studied, hydrological angular momentum (HAM) remains a major source of uncertainty in estimating PM excitation. In this work, we use a large number of climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to determine HAM series both from individual models and their combination, formed with a multi-model mean, a weighted mean, and a three-cornered hat (TCH) method. The CMIP6-based HAM series are analysed in several spectral bands and evaluated with a reference hydrological signal in geodetically observed PM excitation (GAO). HAM determined from CMIP6 were also compared to HAM calculated from Gravity Recovery and Climate Experiment (GRACE) measurements. We find that while climate models do not allow for reliable estimation of non-seasonal changes in HAM, they can help interpret seasonal variability. For annual prograde and semiannual retrograde oscillations, several combined CMIP6-based series exhibit higher amplitude and phase consistency with GAO than the corresponding series computed from GRACE data. Whether one uses a simple average of the models, a weighted average, or a combination of models from the TCH method has little impact on the resulting HAM series and their level of agreement with GAO. Our study advances the understanding of hydrological signal in Earth’s rotation at seasonal time scales.