Links between global terrestrial water storage and large-scale modes of climatic variability

Global Land ◽

<p>Large-scale modes of climatic variability, or teleconnections, influence global patterns of climate variability and provide a framework for understanding complex responses of the global water cycle to global climate. Here, we examine how Terrestrial Water Storage (TWS) responds to 14 major teleconnections (TCs) during the 2003&#8211;2016 period based on data obtained from the Gravity Recovery and Climate Experiment (GRACE). By examining correlations between the teleconnections and TWS anomalies (TWSA) data, we find these teleconnections significantly influence TWSA over more than 80.8% of the global land surface. The El Ni&#241;o-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), and the Atlantic Multidecadal Oscillation (AMO) are significantly correlated with TWSA variations in 55.8%&#65292;56.2% and 60% the global land surface, while other teleconnections affect TWSA at regional scales. We also explore the TCs&#8217; effect on three key hydrological components, including precipitation (P), evapotranspiration (ET) and runoff (R), and their contribution to TWSA variations in 225 river basins. It&#8217;s found the TCs generally exert the comprehensive but not equally impact on all three components (P, ET and R). Our findings demonstrate a significant and varying effect of multiple TCs in terrestrial hydrological balance.</p>

Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data

Hydrology and Earth System Sciences ◽

10.5194/hess-15-533-2011 ◽

2011 ◽

Vol 15 (2) ◽

pp. 533-546 ◽

Cited By ~ 35

Author(s):

M. Becker ◽

B. Meyssignac ◽

L. Xavier ◽

A. Cazenave ◽

R. Alkama ◽

...

Keyword(s):

Large Scale ◽

Amazon Basin ◽

Hydrological Modeling ◽

Water Cycle ◽

Southern Oscillation ◽

Water Storage ◽

Direct Estimate ◽

Abstract. Terrestrial water storage (TWS) composed of surface waters, soil moisture, groundwater and snow where appropriate, is a key element of global and continental water cycle. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) space gravimetry mission provides a new tool to measure large-scale TWS variations. However, for the past few decades, direct estimate of TWS variability is accessible from hydrological modeling only. Here we propose a novel approach that combines GRACE-based TWS spatial patterns with multi-decadal-long in situ river level records, to reconstruct past 2-D TWS over a river basin. Results are presented for the Amazon Basin for the period 1980–2008, focusing on the interannual time scale. Results are compared with past TWS estimated by the global hydrological model ISBA-TRIP. Correlations between reconstructed past interannual TWS variability and known climate forcing modes over the region (e.g., El Niño-Southern Oscillation and Pacific Decadal Oscillation) are also estimated. This method offers new perspective for improving our knowledge of past interannual TWS in world river basins where natural climate variability (as opposed to direct anthropogenic forcing) drives TWS variations.

Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-7-8125-2010 ◽

2010 ◽

Vol 7 (5) ◽

pp. 8125-8155

Author(s):

M. Becker ◽

B. Meyssignac ◽

L. Xavier ◽

R. Alkama ◽

B. Decharme

Keyword(s):

Large Scale ◽

Amazon Basin ◽

Hydrological Modeling ◽

Water Cycle ◽

Southern Oscillation ◽

Water Storage ◽

Direct Estimate ◽

Abstract. Terrestrial water storage (TWS) composed of surface waters, soil moisture, groundwater and snow where appropriate, is a key element of global and continental water cycle. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) space gravimetry mission provides a new tool to measure large-scale TWS variations. However, for the past few decades, direct estimate of TWS variability is accessible from hydrological modeling only. Here we propose a novel approach that combines GRACE-based TWS spatial patterns with multi-decadal-long in situ river level records, to reconstruct past 2-dimensional TWS over a river basin. Results are presented for the Amazon Basin for the period 1980–2008, focusing on the interannual time scale. Results are compared with past TWS estimated by the global hydrological model ISBA-TRIP. Correlations between reconstructed past interannual TWS variability and known climate forcing modes over the region (e.g., El Niño-Southern Oscillation and Pacific Decadal Oscillation) are also estimated. This method offers new perspective for improving our knowledge of past interannual TWS in world river basins where natural climate variability (as opposed to direct anthropogenic forcing) drives TWS variations.

Links between global terrestrial water storage and large-scale modes of climatic variability

Journal of Hydrology ◽

10.1016/j.jhydrol.2021.126419 ◽

2021 ◽

pp. 126419

Author(s):

Lanlan Guo ◽

TieWei Li ◽

Deliang Chen ◽

Junguo Liu ◽

Bin He ◽

...

Keyword(s):

Large Scale ◽

Climatic Variability ◽

Water Storage ◽

The AmazonWater Cycle: Perspectives fromWater Budget Closure and Ocean Salinity

Journal of Climate ◽

10.1175/jcli-d-20-0309.1 ◽

2020 ◽

pp. 1-44

Author(s):

J. E. Jack Reeves Eyre ◽

Xubin Zeng

Keyword(s):

Water Vapor ◽

Land Surface ◽

Water Cycle ◽

Water Storage ◽

River Mouth ◽

Small Subset ◽

Crucial Component ◽

Ocean Salinity ◽

AbstractGlobal and regional water cycle includes precipitation, water vapor divergence, and change of column water vapor in the atmosphere, and land surface evapotranspiration, terrestrial water storage change, and river discharge which is linked to ocean salinity near the river mouth. The water cycle is a crucial component of the Earth system, and numerous studies have addressed its individual components (e.g., precipitation). Here we assess, for the first time, if remote sensing and reanalysis datasets can accurately and self consistently portray the Amazon water cycle. This is further assisted with satellite ocean salinity measurements near the mouth of the Amazon River. The widely-used practice of taking the mean of an ensemble of datasets to represent water cycle components (e.g., precipitation) can produce large biases in water cycle closure. Closure is achieved with only a small subset of data combinations (e.g., ERA5 reanalysis precipitation and evapotranspiration plus GRACE satellite terrestrial water storage), which rules out the lower precipitation and higher evapotranspiration estimates, providing valuable constraints on assessments of precipitation, evapotranspiration and their ratio. The common approach of using the Óbidos stream gauge (located hundreds of kilometres from the river mouth) multiplied by a constant (1.25) to represent the entire Amazon discharge is found to misrepresent the seasonal cycle, and this can affect the apparent influence of Amazon discharge on tropical Atlantic salinity.

Global terrestrial water storage connectivity revealed using complex climate network analyses

Nonlinear Processes in Geophysics ◽

10.5194/npg-22-433-2015 ◽

2015 ◽

Vol 22 (4) ◽

pp. 433-446 ◽

Cited By ~ 5

Author(s):

A. Y. Sun ◽

J. Chen ◽

J. Donges

Keyword(s):

Spatial Patterns ◽

Land Surface ◽

Water Storage ◽

Data Sets ◽

Land Surface Models ◽

Data Set ◽

Surface Models ◽

Global Land ◽

Abstract. Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations

Hydrology and Earth System Sciences ◽

10.5194/hess-21-821-2017 ◽

2017 ◽

Vol 21 (2) ◽

pp. 821-837 ◽

Cited By ~ 23

Author(s):

Liangjing Zhang ◽

Henryk Dobslaw ◽

Tobias Stacke ◽

Andreas Güntner ◽

Robert Dill ◽

...

Keyword(s):

Large Scale ◽

Water Cycle ◽

Numerical Models ◽

Water Storage ◽

Satellite Mission ◽

Validation Data ◽

Data Set ◽

Terrestrial Water ◽

Grace Satellite

Abstract. Estimates of terrestrial water storage (TWS) variations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to assess the accuracy of four global numerical model realizations that simulate the continental branch of the global water cycle. Based on four different validation metrics, we demonstrate that for the 31 largest discharge basins worldwide all model runs agree with the observations to a very limited degree only, together with large spreads among the models themselves. Since we apply a common atmospheric forcing data set to all hydrological models considered, we conclude that those discrepancies are not entirely related to uncertainties in meteorologic input, but instead to the model structure and parametrization, and in particular to the representation of individual storage components with different spatial characteristics in each of the models. TWS as monitored by the GRACE mission is therefore a valuable validation data set for global numerical simulations of the terrestrial water storage since it is sensitive to very different model physics in individual basins, which offers helpful insight to modellers for the future improvement of large-scale numerical models of the global terrestrial water cycle.

A reexamination of the dry gets drier and wet gets wetter paradigm over global land: insight from terrestrial water storage changes

10.5194/hess-2021-645 ◽

2022 ◽

Author(s):

Jinghua Xiong ◽

Shenglian Guo ◽

Jie Chen ◽

Jiabo Yin

Keyword(s):

Climate Change ◽

Land Surface ◽

Climate Models ◽

Water Storage ◽

Global Climate Models ◽

Historical Period ◽

Wetting And Drying ◽

Global Land ◽

Abstract. The “dry gets drier and wet gets wetter” (DDWW) paradigm has been widely used to summarize the expected trends of the global hydrologic cycle under climate change. However, the paradigm is challenged over land due to different measures and datasets, and is still unexplored from the perspective of terrestrial water storage anomaly (TWSA). Considering the essential role of TWSA in wetting and drying of the land surface, here we built upon a large ensemble of TWSA datasets including satellite-based products, global hydrological models, land surface models, and global climate models to evaluate the DDWW hypothesis during the historical (1985–2014) and future (2071–2100) periods under various scenarios. We find that 27.1 % of global land confirms the DDWW paradigm, while 22.4 % of the area shows the opposite pattern during the historical period. In the future, the DDWW paradigm is still challenged with the percentage supporting the pattern lower than 20 %, and both the DDWW-validated and DDWW-opposed proportion increase along with the intensification of emission scenarios. Our findings will provide insights and implications for global wetting and drying trends from the perspective of TWSA under climate change.

Widespread Decline in Terrestrial Water Storage and Its Link to Teleconnections across Asia and Eastern Europe

10.5194/hess-2019-281 ◽

2019 ◽

Cited By ~ 1

Author(s):

Xianfeng Liu ◽

Xiaoming Feng ◽

Philippe Ciais ◽

Bojie Fu

Keyword(s):

Land Surface ◽

Southern Oscillation ◽

Water Storage ◽

Surface Model ◽

Global Changes ◽

Eastern European ◽

European Regions ◽

Multiple Sources ◽

Abstract. Recent global changes in terrestrial water storage (TWS) and associated freshwater availability raise major concerns over the sustainability of global water resources. However, our knowledge regarding the long-term trend in TWS and its components is still not well documented. In this work, we characterize the spatiotemporal variations in TWS and its components over the Asian and Eastern European regions during the period of April 2002 to June 2017 using multiple sources of data, including Gravity Recovery and Climate Experiment (GRACE) satellite observations, land surface model simulations and precipitation observations. The connections of TWS and global major teleconnections (TCs) are also discussed. The results indicate a widespread decline in TWS during 2002–2017, and five hotspots of TWS negative trends were identified with trends between −8.94 mm yr−1 and −21.79 mm yr−1. TWS partitioning suggests that these negative trends are primarily attributed to the intensive overextraction of groundwater and warm-induced surface water loss, but the contributions of each hydrological component vary among hotspots. The results also indicate that the El Niño-Southern Oscillation, Arctic Oscillation and North Atlantic Oscillation are the three largest, dominant factors controlling the variations in TWS through the covariability effect on climate variables. However, seasonal results suggest a divergent response of hydrological components to TCs among seasons and hotspots. Our findings provide insights into changes in TWS and its components over the Asian and Eastern European regions, where there is a growing demand for food grains and water supplies.

Emerging Changes in Terrestrial Water Storage Variability as a Target for Future Satellite Gravity Missions

Remote Sensing ◽

10.3390/rs12233898 ◽

2020 ◽

Vol 12 (23) ◽

pp. 3898

Author(s):

Laura Jensen ◽

Annette Eicker ◽

Henryk Dobslaw ◽

Roland Pail

Keyword(s):

Land Surface ◽

Seasonal Cycle ◽

Climate Model ◽

Water Cycle ◽

Water Storage ◽

Phase Changes ◽

Satellite Gravity ◽

Climate change will affect the terrestrial water cycle during the next decades by impacting the seasonal cycle, interannual variations, and long-term linear trends of water stored at or beyond the surface. Since 2002, terrestrial water storage (TWS) has been globally observed by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO). Next Generation Gravity Missions (NGGMs) are planned to extend this record in the near future. Based on a multi-model ensemble of climate model output provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6) covering the years 2002–2100, we assess possible changes in TWS variability with respect to present-day conditions to help defining scientific requirements for NGGMs. We find that present-day GRACE accuracies are sufficient to detect amplitude and phase changes in the seasonal cycle in a third of the land surface, whereas a five times more accurate double-pair mission could resolve such changes almost everywhere outside the most arid landscapes of our planet. We also select one individual model experiment out of the CMIP6 ensemble that closely matches both GRACE observations and the multi-model median of all CMIP6 realizations, which might serve as basis for satellite mission performance studies extending over many decades to demonstrate the suitability of NGGM satellite missions to monitor long-term climate variations in the terrestrial water cycle.

Validation of Terrestrial Water Storage Variations as Simulated by Different Global Numerical Models with GRACE Satellite Observations

10.5194/hess-2016-330 ◽

2016 ◽

Author(s):

Liangjing Zhang ◽

Henryk Dobslaw ◽

Tobias Stacke ◽

Andreas Güntner ◽

Robert Dill ◽

...

Keyword(s):

Large Scale ◽

Water Cycle ◽

Numerical Models ◽

Water Storage ◽

Satellite Mission ◽

Validation Data ◽

Data Set ◽

Terrestrial Water ◽

Limited Degree

Abstract. Estimates of terrestrial water storage (TWS) variations from the satellite mission GRACE are used to assess the accuracy of four global numerical model realizations that simulate the continental branch of the global water cycle. Based on four different validation metrics, we demonstrate that for the 31 largest discharge basins worldwide all model runs agree with the observations to a very limited degree only, together with large spreads among the models themselves. Since we apply a common atmospheric forcing data-set to all hydrological models considered, we conclude that those discrepancies are not entirely related to uncertainties in meteorologic input, but instead to the model structure and parametrization, and in particular to the representation of individual storage compartments with different spatial characteristics in each of the models. TWS as monitored by the GRACE mission is therefore a valuable validation data-set for global numerical simulations of the terrestrial water storage since it is sensitive to very different model physics in individual basins, which offers helpful insight to modellers for the future improvement of large-scale numerical models of the global terrestrial water cycle.