Abstract
It has been shown that the changes in global terrestrial water storage (TWS) are strongly linked to the teleconnections (TCs) that induce large-scale climate variations. However, the contributions of the different TCs to global changes of TWS and its components (water storage components, WSCs) remain undetermined. To fill this gap, we systematically assess the relationships between six major ocean-related TCs and different WSCs derived from the Gravity Recovery and Climate Experiment (GRACE) mission and hydrological models under different timescales. Additionally, the interrelationships of the TCs are also analyzed via the independent component analysis for further investigation. The results allow an improved understanding of the hydrometeorological process controlling WSC changes. Specifically, the annual timescale analysis can constrain high-frequency noises and retain the informative fluctuations of WSC residuals. ENSO and AMO are found to be the two most dominant TCs controlling the variations of WSCs globally. TWS and groundwater storage (GWS) are the two WSCs most correlated with the dominant TCs. The WSCs at shallow depths, which are largely affected by strongly hysteretic controls of TCs, are more closely linked to the TCs with many high-frequency components that tend to have weak hysteresis on WSCs. As for the interrelationships of TCs, the independent component, which is highly correlated with all six TCs, has a predominant influence on WSCs.
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Abbreviations
- AMO:
-
Atlantic Multidecadal Oscillation
- AO:
-
Arctic Oscillation
- CLSM:
-
Catchment Land Surface Model
- ENSO:
-
El Niño-Southern Oscillation
- GRACE:
-
Gravity Recovery And Climate Experiment
- GWS:
-
Groundwater Storage
- IC:
-
Independent Components
- ICA:
-
Independent Component Analysis
- IOD:
-
Indian Ocean Dipole
- ITCZ:
-
Intertropical Convergence Zone
- JPL:
-
Jet Propulsion Laboratory
- MEI:
-
Multivariate Enso Index
- NAO:
-
North Atlantic Oscillation
- NOAA:
-
National Oceanic and Atmospheric Administration
- PCW:
-
Plant Canopy Water
- PDO:
-
Pacific Decadal Oscillation
- RZSM:
-
Root Zone Soil Moisture
- SnWS:
-
Snow Water Storage
- STL:
-
Seasonal-Trend Decomposition By Loess
- SWS:
-
Surface Water Storage
- TC:
-
Teleconnection
- TWS:
-
Terrestrial Water Storage
- WGHM:
-
Watergap Global Hydrology Model
- WSC:
-
Water Storage Component
References
Anyah RO, Forootan E, Awange JL, Khaki M (2018) Understanding linkages between global climate indices and terrestrial water storage changes over Africa using GRACE products. Sci Total Environ 635:1405–1416. https://doi.org/10.1016/j.scitotenv.2018.04.159
Banerjee C, Kumar DN (2018) Analyzing large-scale hydrologic processes using GRACE and hydrometeorological datasets. Water Resour Manag 32(13):4409–4423. https://doi.org/10.1007/s11269-018-2070-x
Chen A, Guan H, Batelaan O (2021a) Seesaw terrestrial wetting and drying between eastern and western Australia. Earths Future 9(5):e2020EF001893. https://doi.org/10.31219/osf.io/qz3pe
Chen H, Teegavarapu RSV, Xu YP (2021b) Oceanic-atmospheric variability influences on baseflows in the Continental United States. Water Resour Manag 35(9):3005–3022. https://doi.org/10.1007/s11269-021-02884-6
Cleveland RB, Cleveland WS, Mcrae JE (1990) STL: A seasonal-trend decomposition procedure based on loess. J Off Stat 6:3–73
Colebrook JM (1978) Continuous plankton records: zooplankton and environment, north-east Atlantic and North Sea, 1948-1975. Oceanol Acta 1(1):9–23. Retrieved from http://archimer.ifremer.fr/doc/00123/23405/21232.pdf
García-García D, Ummenhofer CC, Zlotnicki V (2011) Australian water mass variations from GRACE data linked to Indo-Pacific climate variability. Remote Sens Environ 115(9):2175–2183. https://doi.org/10.1016/j.rse.2011.04.007
Girishkumar MS, Prakash VPT, Ravichandran M (2015) Influence of Pacific Decadal Oscillation on the relationship between ENSO and tropical cyclone activity in the Bay of Bengal during October–December. Clim Dyn 44(11–12):3469–3479. https://doi.org/10.1007/s00382-014-2282-6
Guo L, Li T, Chen D, Liu J, He B, Zhang Y (2021) Links between global terrestrial water storage and large-scale modes of climatic variability. J Hydrol 598:126419. https://doi.org/10.1016/j.jhydrol.2021.126419
Guo Y, Huang S, Huang Q, Wang H, Fang W, Yang Y, Wang L (2019) Assessing socioeconomic drought based on an improved Multivariate Standardized Reliability and Resilience Index. J Hydrol 568:904–918. https://doi.org/10.1016/j.jhydrol.2018.11.055
Han Z, Huang S, Huang Q, Leng G, Wang H, He L et al (2019) Assessing GRACE-based terrestrial water storage anomalies dynamics at multi-timescales and their correlations with teleconnection factors in Yunnan Province, China. J Hydrol 574:836–850. https://doi.org/10.1016/j.jhydrol.2019.04.093
Hassani H, Heravi S, Zhigljavsky A (2013) Forecasting UK industrial production with multivariate singular spectrum analysis. J Forecast 32(5):395–408. https://doi.org/10.1002/for.2244
Hu B, Wang L, Li X, Zhou J, Pan Y (2021) Divergent changes in terrestrial water storage across global arid and humid basins. Geophys Res Lett 48(1):1–11. https://doi.org/10.1029/2020GL091069
Humphrey V, Zscheischler J, Ciais P, Gudmundsson L, Sitch S, Seneviratne SI (2018) Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage. Nature 560(7720):628–631. https://doi.org/10.1038/s41586-018-0424-4
Hyvärinen A, Oja E (2000) Independent component analysis: algorithms and applications. Neural Netw 13(4–5):411–430. https://doi.org/10.1016/S0893-6080(00)00026-5
Hyvärinen Aapo, Karhunen J, Oja E (2001) Independent component analysis. Wiley Online Library. https://doi.org/10.1016/b978-0-444-64165-6.02006-1
Kennedy AM, Garen DC, Koch RW (2009) The association between climate teleconnection indices and Upper Klamath seasonal streamflow: trans-niño index. Hydrol Process 23:973–984. https://doi.org/10.1002/hyp
Krishan G, Lohani AK, Rao MS, Kumar CP (2014) Prioritization of groundwater monitoring sites using cross-correlation analysis. NDCWWC J (A Half Yearly Journal of New Delhi Centre of WWC) 3:28–31
Kuss AJM, Gurdak JJ (2014) Groundwater level response in U.S. principal aquifers to ENSO, NAO, PDO, and AMO. J Hydrol 519:1939–1952. https://doi.org/10.1016/j.jhydrol.2014.09.069
Liu X, Feng X, Ciais P, Fu B (2020) Widespread decline in terrestrial water storage and its link to teleconnections across Asia and eastern Europe. Hydrol Earth Syst Sci 24(7):3663–3676. https://doi.org/10.5194/hess-24-3663-2020
Long D, Yang Y, Wada Y, Hong Y, Liang W, Chen Y et al (2015) Deriving scaling factors using a global hydrological model to restore GRACE total water storage changes for China’s Yangtze River Basin. Remote Sens Environ 168:177–193. https://doi.org/10.1016/j.rse.2015.07.003
Long D, Pan Y, Zhou J, Chen Y, Hou X, Hong Y et al (2017) Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models. Remote Sens Environ 192:198–216. https://doi.org/10.1016/j.rse.2017.02.011
Müller Schmied H, Cáceres D, Eisner S, Flörke M, Herbert C, Niemann C et al (2020) The global water resources and use model WaterGAP v2.2d: model description and evaluation. Geosci Model Dev 14:1037–1079. https://doi.org/10.5194/gmd-2020-225
Ndehedehe CE, Awange JL, Kuhn M, Agutu NO, Fukuda Y (2017) Climate teleconnections influence on West Africa’s terrestrial water storage. Hydrol Process 31(18):3206–3224. https://doi.org/10.1002/hyp.11237
Ni S, Chen J, Wilson CR, Li J, Hu X, Fu R (2018) Global terrestrial water storage changes and connections to ENSO events. Surv Geophys 39(1):1–22. https://doi.org/10.1007/s10712-017-9421-7
Nie N, Zhang W, Chen H, Guo H (2018) A global hydrological drought index dataset based on gravity recovery and climate experiment (GRACE) data. Water Resour Manag 32(4):1275–1290. https://doi.org/10.1007/s11269-017-1869-1
Oñate-Valdivieso F, Uchuari V, Oñate-paladines A (2020) Large-scale climate variability patterns and drought: a case of study in South–America. Water Resour Manag 34:2061–2079
Phillips T, Nerem RS, Fox-Kemper B, Famiglietti JS, Rajagopalan B (2012) The influence of ENSO on global terrestrial water storage using GRACE. Geophys Res Lett 39(16):1–7. https://doi.org/10.1029/2012GL052495
Qian C, Yu JY, Chen G (2014) Decadal summer drought frequency in China: the increasing influence of the Atlantic multi-decadal oscillation. Environ Res Lett 9(12). https://doi.org/10.1088/1748-9326/9/12/124004
Runge J, Nowack P, Kretschmer M, Flaxman S, Sejdinovic D (2019) Detecting and quantifying causal associations in large nonlinear time series datasets. Sci Adv 5:eaau4996–eaau4996
Saji NH, Yamagata T (2003) Possible impacts of Indian Ocean Dipole mode events on global climate. Clim Res 25(2):151–169. https://doi.org/10.3354/cr025151
Scanlon BR, Zhang Z, Save H, Wiese DN, Landerer FW, Long D et al (2016) Global evaluation of new GRACE mascon products for hydrologic applications. Water Resour Res 12:9412–9429. https://doi.org/10.1111/j.1752-1688.1969.tb04897.x
Scanlon BR, Zhang Z, Save H, Sun AY, Müller Schmied H, van Beek LPH et al (2018) Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data. Proc Natl Acad Sci U S A 115:E1080–E1089. https://doi.org/10.1073/pnas.1704665115
Soni A, Syed TH (2015) Diagnosing land water storage variations in major Indian river basins using GRACE observations. Glob Planet Change 133:263–271. https://doi.org/10.1016/j.gloplacha.2015.09.007
Sun Z, Zhu X, Pan Y, Zhang J, Liu X (2018) Drought evaluation using the GRACE terrestrial water storage deficit over the Yangtze River Basin, China. Sci Total Environ 634:727–738. https://doi.org/10.1016/j.scitotenv.2018.03.292
Sun Z, Long D, Yang W, Li X, Pan Y (2020) Reconstruction of GRACE data on changes in total water storage over the global land surface and 60 basins. Water Resour Res 56(4):1–21. https://doi.org/10.1029/2019WR026250
Thomas BF, Famiglietti JS (2019) Identifying climate-induced groundwater depletion in GRACE observations. Sci Rep 9(1):1–9. https://doi.org/10.1038/s41598-019-40155-y
Wang J, Song C, Reager JT, Yao F, Famiglietti JS, Sheng Y et al (2018) Recent global decline in endorheic basin water storages. Nat Geosci 11(12):926–932. https://doi.org/10.1038/s41561-018-0265-7
Xia Y, Hao Z, Shi C, Li Y, Meng J, Xu T et al (2019) Regional and global land data assimilation systems: innovations, challenges, and prospects. J Meteorol Research 33(2):159–189. https://doi.org/10.1007/s13351-019-8172-4
Yang P, Xia J, Zhan C, Qiao Y, Wang Y (2017) Monitoring the spatio-temporal changes of terrestrial water storage using GRACE data in the Tarim River basin between 2002 and 2015. Sci Total Environ 595:218–228. https://doi.org/10.1016/j.scitotenv.2017.03.268
Yao Z (2017) Natural and human-induced impacts on regional terrestrial water storage changes from GRACE and hydro-meteorological data. Doctoral dissertation, Wuhan: Wuhan University (in Chinese with English abstract)
Zhang Y, He BIN, Guo L, Liu D (2019) Differences in response of terrestrial water storage components to precipitation over 168 global river basins. J Hydrometeorol 20(9):1981–1999. https://doi.org/10.1175/JHM-D-18-0253.1
Zhang Z, Chao BF, Chen J, Wilson CR (2015) Terrestrial water storage anomalies of yangtze river basin droughts observed by GRACE and connections with ENSO. Glob Planet Change 126:35–45. https://doi.org/10.1016/j.gloplacha.2015.01.002
Acknowledgments
The JPL GRACE RL06 mascons solutions can be downloaded from CSR (http://grace.jpl.nasa.gov/); the WGHM data are available at https://doi.pangaea.de/10.1594/PANGAEA.918447; the GLDAS data are available from NASA (https://ldas.gsfc.nasa.gov/gldas/); the teleconnection data are available from NOAA (https://psl.noaa.gov/). This study is supported by the National Natural Science Foundation of China Grants 51779179, 51861125202, and 51609173 and the National Key Research & Development Program of China (2019YFC1805701).
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Peijun Li: Conceptualization, Methodology, Software, Data curation, Writing - original draft, Visualization, Investigation. Yuanyuan Zha: Conceptualization, Methodology, Software, Data curation, Writing - original draft, Visualization, Investigation, Funding acquisition. Liangsheng Shi: Supervision, Validation, Funding acquisition. Hua Zhong: Supervision, Validation. Chak-Hau Michael Tso: Writing - review & editing. Mousong Wu: Validation, Writing - review & editing.
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Li, P., Zha, Y., Shi, L. et al. Assessing the Global Relationships Between Teleconnection Factors and Terrestrial Water Storage Components. Water Resour Manage 36, 119–133 (2022). https://doi.org/10.1007/s11269-021-03015-x
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DOI: https://doi.org/10.1007/s11269-021-03015-x