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The Global Water Cycle Budget: A Chronological Review

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Abstract

Like civilization and technology, our understanding of the global water cycle has been continuously evolving, and we have adapted our quantification methods to better exploit new technological resources. The accurate quantification of global water fluxes and storages is crucial in studying the global water cycle. These fluxes and storages physically interact with each other, are related through the water budget, and are constrained by it. First attempts to quantify them date back to the early 1900s, and during the past few decades, they have received an increasing research interest, which is reflected in the vast amount of data sources available nowadays. However, these data have not been comprehensive enough due to the high spatiotemporal variability of the global water cycle. Herein, we provide a comprehensive review of the chronological evolution of global water cycle quantification, the distinct data sources and methods used, and a critical assessment of their contribution to improving the spatiotemporal monitoring of the global water cycle. The chronology of global water cycle components shows that the uncertainty of flux estimates over oceans remains higher than that over land. Comparing the standard deviation and the interquartile range of the estimates from the 2000s onward with those from all the estimates (1905-2019), we can affirm that statistical variability has diminished in recent years. Moreover, the variability of ocean precipitation and evaporation estimates from the 2000 onward was reduced by more than \(70\%\) compared with earlier studies. These findings advocate that the consistency of global water cycle quantification has been improved.

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Abbreviations

CHIRPS:

Climate Hazards Group Infrared Precipitation with Station Data

CLM3:

Community Land Model version 3

CMORPH:

Climate Prediction Center Morphing Method

CPC:

Climate Prediction Center

CRU TS:

University of East Anglia Climatic Research Unit Time-Series

CSR:

Center for Space Research at University of Texas

CSU:

Colorado State University

DMSP:

Defense Meteorological Satellite Program

ECMWF:

European Centre for Medium-Range Weather Forecasts

ERA:

European Centre for Medium-Range Weather Forecasts Re-Analysis

GEWEX:

Global Energy and Water Exchanges

GFZ:

Deutschen GeoForschungsZentrum

GHP:

Global Energy and Water Exchanges Hydrometeorology Panel

GLDAS:

Global Land Data Assimilation System

GLEAM:

Global Land Evaporation Amsterdam Model

GPCC:

Global Precipitation Climatology Centre

GPCP:

Global Precipitation Climatology Project

GPM:

Global Precipitation Measurement

GRACE:

Gravity Recovery and Climate Experiment

GRDC:

Global Runoff Data Centre

GRGS:

Groupe de Recherche de Géodésie Spatiale

GWAVA:

Global Water Availability Assessment

H08:

Hanasaki 2008

HTESSEL:

Land Surface Hydrology Tiled European Centre for Medium-Range Weather Forecasts Scheme for Surface Exchanges Over Land

JPL:

Jet Propulsion Laboratories

JULES:

Joint UK Land Environment Simulator

LPJmL:

Lund-Potsdam-Jena Managed Land

MacPDM:

Macro-scale Probability-Distributed Moisture

MATSIRO:

Minimal Advanced Treatments of Surface Interaction and Runoff

MERRA:

Modern-Era Retrospective Analysis for Research and Applications

MPI-HM:

Max Planck Institute - Hydrology Model

MOD16:

Moderate Resolution Imaging Spectroradiometer Global Evapotranspiration Project

MODIS:

Moderate Resolution Imaging Spectroradiometer

NRL:

Naval Research Laboratory

NTSG:

Numerical Terradynamic Simulation Group

Orchidee:

Organising Carbon and Hydrology in Dynamic Ecosystems

PGF:

Princeton Global Forcing

PREC/L:

Precipitation Reconstruction Over Land

SRB-CFSR-SEBS:

Surface Radiation Budget - Climate Forecast System Reanalysis - Surface Energy Balance System

SRB-CFSR-PM:

Surface Radiation Budget - Climate Forecast System Reanalysis - Penman-Monteith

SRB-CFSR-PT:

Surface Radiation Budget - Climate Forecast System Reanalysis - Priestly-Taylor

SRB-PGF-PM:

Surface Radiation Budget - Princeton Global Forcing - Penman-Monteith

SSM/I:

Special Sensor Microwave Imager

SSMIS:

Special Sensor Microwave Imager Sounder

TMPA:

Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis

TRMM:

Tropical Rainfall Measuring Mission

VIC:

Variable Infiltration Capacity

WaterGAP:

Water Global Assessment and Prognosis

References

  • Abbott BW, Bishop K, Zarnetske JP, Minaudo C, Chapin F, Krause S, Hannah DM, Conner L, Ellison D, Godsey SE et al. (2019) Human domination of the global water cycle absent from depictions and perceptions. Nature Geoscience 12(7), 533–540

    Article  Google Scholar 

  • Adler RF, Huffman GJ, Chang A, Ferraro R, Xie PP, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D et al. (2003) The version-2 global precipitation climatology project (gpcp) monthly precipitation analysis (1979-present). Journal of hydrometeorology 4(6):1147–1167

    Article  Google Scholar 

  • Aires F (2014) Combining datasets of satellite-retrieved products part i: Methodology and water budget closure. Journal of Hydrometeorology 15(4): 1677–1691

    Article  Google Scholar 

  • Aires F, Prigent C, Rossow W (2004) Neural network uncertainty assessment using bayesian statistics with application to remote sensing: 3. network jacobians. Journal of Geophysical Research: Atmospheres 109(D10)

  • Albrecht F (1960) Jahreskarten des Wärme-und Wasserhaushaltes der Ozeane. Verlag nicht ermittelbar

  • Alcamo J, Döll P, Henrichs T, Kaspar F, Lehner B, Rösch T, Siebert S (2003) Development and testing of the watergap 2 global model of water use and availability. Hydrological Sciences Journal 48(3), 317–337

    Article  Google Scholar 

  • Allan R, Barlow M, Byrne MP, Cherchi A, Douville H, Fowler HJ, Gan TY, Pendergrass AG, Rosenfeld D, Swann AL et al. (2020) Advances in understanding large-scale responses of the water cycle to climate change. Annals of the New York Academy of Sciences 1472: 49–75

    Article  Google Scholar 

  • Allen MR, Ingram WJ (2002) Constraints on future changes in climate and the hydrologic cycle. Nature 419(6903), 228–232

    Article  Google Scholar 

  • Arnell NW (1999) A simple water balance model for the simulation of streamflow over a large geographic domain. Journal of Hydrology 217(3–4), 314–335

    Article  Google Scholar 

  • Azarderakhsh M, Rossow WB, Papa F, Norouzi H, Khanbilvardi R (2011) Diagnosing water variations within the amazon basin using satellite data. Journal of Geophysical Research: Atmospheres 116(D24)

  • Bala G, Caldeira K, Nemani R (2010) Fast versus slow response in climate change: implications for the global hydrological cycle. Climate dynamics 35(2–3):423–434

    Article  Google Scholar 

  • Balsamo G, Beljaars A, Scipal K, Viterbo P, van den Hurk B, Hirschi M, Betts AK (2009) A revised hydrology for the ecmwf model: Verification from field site to terrestrial water storage and impact in the integrated forecast system. Journal of hydrometeorology 10(3):623–643

    Article  Google Scholar 

  • Barnes JC, Bowley CJ (1968) Snow cover distribution as mapped from satellite photography. Water Resources Research 4(2), 257–272

    Article  Google Scholar 

  • Baumgartner A, Reichel E (1972) Preliminary results of new investigations of world’s water balance. Applied optics 7:1705–1710

    Google Scholar 

  • Bengtsson L (2010) The global atmospheric water cycle. Environmental Research Letters 5(2):025202

    Article  Google Scholar 

  • Bishop CM et al. (1995) Neural networks for pattern recognition. Oxford University Press

    Google Scholar 

  • Bonan GB, Oleson KW, Vertenstein M, Levis S, Zeng X, Dai Y, Dickinson RE, Yang ZL (2002) The land surface climatology of the community land model coupled to the ncar community climate model. Journal of climate 15(22):3123–3149

    Article  Google Scholar 

  • Bondeau A, Smith PC, Zaehle S, Schaphoff S, Lucht W, Cramer W, Gerten D, LOTZE-CAMPEN H, Müller C, Reichstein M (2007) Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Global Change Biology 13(3), 679–706

  • Bosilovich MG, Robertson FR, Chen J (2011) Global energy and water budgets in merra. Journal of Climate 24(22), 5721–5739

    Article  Google Scholar 

  • Bralower T, Bice D (2012) Module 4: Introduction to general circulation models. In: Earth 103: Earth in the Future, College of Earth and Mineral Science, The Pennsylvania State University, http://creativecommons.org/licenses/by-nc-sa/4.0/

  • Brocca L, Filippucci P, Hahn S, Ciabatta L, Massari C, Camici S, Schüller L, Bojkov B, Wagner W (2019) Sm2rain-ascat (2007–2018): global daily satellite rainfall data from ascat soil moisture observations. Earth System Science Data 11(4)

    Article  Google Scholar 

  • Brückner E (1905) Die bilanz des kreislaufs des wassers auf der erde. Geographische Zeitschrift 11(8. H):436–445

  • Brutsaert W et al. (2005) Hydrology: an introduction. Cambridge University Press

    Book  Google Scholar 

  • Budyko MI (1955) Teplowoj Balans Zemnoi Poverkhuorti. Glavnaya geofizicheskaya observatoriya

  • Budyko MI (1961) The heat balance of the earth’s surface. Soviet Geography 2(4), 3–13

    Article  Google Scholar 

  • Budyko MI (1963) Atlas teplovogo balansa zemnogo shara. Glavnaya geofizicheskaya observatoriya

  • Budyko MI (1970) The water balance of the oceans. In: Symposium on World Water Balance, Gentbrügge, Int. Ass. Scient. Hydrol., vol 1, pp 24–33

  • Budyko MI (1974) Climate and life. Academic Press, Inc

  • Burges SJ, Wigmosta MS, Meena JM (1998) Hydrological effects of land-use change in a zero-order catchment. Journal of Hydrologic Engineering 3(2), 86–97

    Article  Google Scholar 

  • Byrne MP, O’Gorman PA (2015) The response of precipitation minus evapotranspiration to climate warming: Why the "wet-get-wetter, dry-get-drier" ling does not hold over land. Journal of Climate 28(20), 8078–8092

    Article  Google Scholar 

  • Bytheway JL, Kummerow CD (2013) Inferring the uncertainty of satellite precipitation estimates in data-sparse regions over land. Journal of Geophysical Research: Atmospheres 118(17), 9524–9533

    Article  Google Scholar 

  • Cardak O et al. (2009) Science students’ misconceptions of the water cycle according to their drawings. Journal of Applied Sciences 9(5), 865–873

    Article  Google Scholar 

  • Carson D (1982) Current parameterizations of land surface processes in atmospheric general circulation models. Land surface processes in atmospheric general circulation models pp 67–108

  • Cavalcanti I, Carril A, Penalba O, Grimm A, Menéndez C, Sanchez E, Cherchi A, Sörensson A, Robledo F, Rivera J et al. (2015) Precipitation extremes over la plata basin-review and new results from observations and climate simulations. Journal of hydrology 523:211–230

    Article  Google Scholar 

  • Chahine MT (1992a) Gewex: The global energy and water cycle experiment. Eos, Transactions American Geophysical Union 73(2), 9–14

    Article  Google Scholar 

  • Chahine MT (1992b) The hydrological cycle and its influence on climate. Nature 359(6394), 373–380

    Article  Google Scholar 

  • Chambers D, Bonin J (2012) Evaluation of release-05 grace time-variable gravity coefficients over the ocean. Ocean Science 8(5):859

    Article  Google Scholar 

  • Chapin III FS, Matson PA, Vitousek P (2011) Principles of terrestrial ecosystem ecology. Springer Science & Business Media

  • Chen M, Xie P, Janowiak JE, Arkin PA (2002) Global land precipitation: A 50-yr monthly analysis based on gauge observations. Journal of Hydrometeorology 3(3), 249–266

    Article  Google Scholar 

  • Cherubim R (1931) Uber verdunstungsmessung auf see. Ann d Hydrogr u Marit Meteor 59:325

    Google Scholar 

  • Ciabatta L, Camici S, Massari C, Filippucci P, Hahn S, Wagner W, Brocca L (2020) Soil moisture and precipitation: The sm2rain algorithm for rainfall retrieval from satellite soil moisture. In: Satellite Precipitation Measurement, Springer, pp 1013–1027

  • Clark EA, Sheffield J, van Vliet MT, Nijssen B, Lettenmaier DP (2015) Continental runoff into the oceans (1950–2008). Journal of Hydrometeorology 16(4), 1502–1520

    Article  Google Scholar 

  • Collins M, Knutti R, Arblaster J, Dufresne JL, Fichefet T, Friedlingstein P, Gao X, Gutowski WJ, Johns T, Krinner G, et al. (2013) Long-term climate change: projections, commitments and irreversibility. In: Climate Change 2013-The Physical Science Basis: Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, pp 1029–1136

  • Cox P, Betts R, Bunton C, Essery R, Rowntree P, Smith J (1999) The impact of new land surface physics on the gcm simulation of climate and climate sensitivity. Climate Dynamics 15(3), 183–203

    Article  Google Scholar 

  • Cronshey R (1986) Urban hydrology for small watersheds. Tech. rep., US Dept. of Agriculture, Soil Conservation Service, Engineering Division

  • Dai A, Trenberth KE (2002) Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. Journal of hydrometeorology 3(6):660–687

    Article  Google Scholar 

  • Dalton J (1799) Experiments and observations to determine whether the quantity of rain and dew is equal to the quantity of water carried off by the rivers and raised by evaporation: With an enquiry into the origin of springs. The Manchester Literary and Philosophical Society

  • Dastorani MT, Moghadamnia A, Piri J, Rico-Ramirez M (2010) Application of ann and anfis models for reconstructing missing flow data. Environmental monitoring and assessment 166(1–4):421–434

    Article  Google Scholar 

  • Devi U, Shekhar MS, Singh GP, Rao NN, Bhatt US (2019) Methodological application of quantile mapping to generate precipitation data over northwest himalaya. International Journal of Climatology 39(7), 3160–3170

    Article  Google Scholar 

  • de Rosnay P, Polcher J (1998) Modelling root water uptake in a complex land surface scheme coupled to a gcm. Hydrology and Earth System Sciences Discussions

    Article  Google Scholar 

  • Dickinson RE (1984) Modeling evapotranspiration for three-dimensional global climate models. Climate processes and climate sensitivity 29:58–72

    Article  Google Scholar 

  • Dirmeyer PA, Gao X, Zhao M, Guo Z, Oki T, Hanasaki N (2006) Gswp-2: Multimodel analysis and implications for our perception of the land surface. Bulletin of the American Meteorological Society 87(10), 1381–1398

    Article  Google Scholar 

  • Dubach LL, Ng C (1988) Compendium of meteorological space programs, satellites, and experiments

  • Durack PJ (2015) Ocean salinity and the global water cycle. Oceanography 28(1), 20–31

    Article  Google Scholar 

  • Eischeid JK, Bruce Baker C, Karl TR, Diaz HF (1995) The quality control of long-term climatological data using objective data analysis. Journal of applied meteorology 34(12):2787–2795

    Article  Google Scholar 

  • Eischeid JK, Pasteris PA, Diaz HF, Plantico MS, Lott NJ (2000) Creating a serially complete, national daily time series of temperature and precipitation for the western united states. Journal of Applied Meteorology 39(9), 1580–1591

    Article  Google Scholar 

  • Essery R, Best M, Betts R, Cox PM, Taylor CM (2003) Explicit representation of subgrid heterogeneity in a gcm land surface scheme. Journal of Hydrometeorology 4(3), 530–543

    Article  Google Scholar 

  • Evans J, McCabe M (2010) Regional climate simulation over australia’s murray-darling basin: A multitemporal assessment. Journal of Geophysical Research: Atmospheres 115(D14)

  • Falkenmark M, Lindh G (1974) How can we cope with the water resources situation by the year 2015? Ambio pp 114–122

  • Federer C, Vörösmarty C, Fekete B (1996) Intercomparison of methods for calculating potential evaporation in regional and global water balance models. Water Resources Research 32(7), 2315–2321

    Article  Google Scholar 

  • Fekete BM, Vörösmarty CJ, Roads JO, Willmott CJ (2004) Uncertainties in precipitation and their impacts on runoff estimates. Journal of Climate 17(2), 294–304

    Article  Google Scholar 

  • Flato G, Marotzke J, Abiodun B, Braconnot P, Chou SC, Collins W, Cox P, Driouech F, Emori S, Eyring V, et al. (2014) Evaluation of climate models. In: Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, pp 741–866

  • Flato GM (2011) Earth system models: an overview. Wiley Interdisciplinary Reviews: Climate Change 2(6), 783–800

    Google Scholar 

  • Friedl MA, McIver DK, Hodges JC, Zhang XY, Muchoney D, Strahler AH, Woodcock CE, Gopal S, Schneider A, Cooper A et al. (2002) Global land cover mapping from modis: algorithms and early results. Remote sensing of Environment 83(1–2), 287–302

    Article  Google Scholar 

  • Fritzsche R (1906) Niederschlag, Abfluss und Verdunstung auf den Landflächen der Erde. as (Dresden Druck von W. Baensch)

  • Fuchs T, Rapp J, Rubel F, Rudolf B (2001) Correction of synoptic precipitation observations due to systematic measuring errors with special regard to precipitation phases. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere 26(9), 689–693

    Article  Google Scholar 

  • Funk CC, Peterson PJ, Landsfeld MF, Pedreros DH, Verdin JP, Rowland JD, Romero BE, Husak GJ, Michaelsen JC, Verdin AP et al. (2014) A quasi-global precipitation time series for drought monitoring. US Geological Survey data series 832(4):1–12

    Google Scholar 

  • Gleick PH (1993) Water in crisis: a guide to the world’s fresh water resources. Oxford University Press, New York

    Google Scholar 

  • Gonzalez Miralles D, Holmes T, De Jeu R, Gash J, Meesters A, Dolman A (2011) Global land-surface evaporation estimated from satellite-based observations. Hydrology and Earth System Sciences pp 453–469

  • Gosling SN, Arnell NW (2011) Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis. Hydrological Processes 25(7), 1129–1145

    Article  Google Scholar 

  • Greve P, Orlowsky B, Mueller B, Sheffield J, Reichstein M, Seneviratne SI (2014) Global assessment of trends in wetting and drying over land. Nature geoscience 7(10):716–721

    Article  Google Scholar 

  • Gutenstein M, Fennig K, Schröder M, Trent T, Bakan S, Roberts JB, Robertson FR (2021) Intercomparison of freshwater fluxes over ocean and investigations into water budget closure. Hydrology and Earth System Sciences 25(1), 121–146

    Article  Google Scholar 

  • Haddeland I, Clark DB, Franssen W, Ludwig F, Voß F, Arnell NW, Bertrand N, Best M, Folwell S, Gerten D et al. (2011) Multimodel estimate of the global terrestrial water balance: setup and first results. Journal of Hydrometeorology 12(5), 869–884

    Article  Google Scholar 

  • Hagemann S, Dümenil L (1997) A parametrization of the lateral waterflow for the global scale. Climate dynamics 14(1):17–31

    Article  Google Scholar 

  • Hagemann S, Gates LD (2003) Improving a subgrid runoff parameterization scheme for climate models by the use of high resolution data derived from satellite observations. Climate Dynamics 21(3–4), 349–359

    Article  Google Scholar 

  • Halbfaß W (1934) Flohr, ef beitrag zur methode der kartographischen darstellung von wasserkräften. Geographische Zeitschrift 40(10):391

    Google Scholar 

  • Hanasaki N, Kanae S, Oki T, Masuda K, Motoya K, Shirakawa N, Shen Y, Tanaka K (2008) An integrated model for the assessment of global water resources-part 1: Model description and input meteorological forcing. Hydrology & Earth System Sciences 12(4)

    Article  Google Scholar 

  • Hanel M, Kožín R, Heřmanovskỳ M, Roub R (2017) An r package for assessment of statistical downscaling methods for hydrological climate change impact studies. Environmental modelling & software 95:22–28

    Article  Google Scholar 

  • Hawkins E, Smith RS, Gregory JM, Stainforth DA (2016) Irreducible uncertainty in near-term climate projections. Climate Dynamics 46(11–12), 3807–3819

    Article  Google Scholar 

  • Hegerl GC, Black E, Allan RP, Ingram WJ, Polson D, Trenberth KE, Chadwick RS, Arkin PA, Sarojini BB, Becker A (2018) Challenges in quantifying changes in the global water cycle. Bulletin of the American Meteorological Society 99(1)

    Google Scholar 

  • Held IM, Soden BJ (2006) Robust responses of the hydrological cycle to global warming. Journal of climate 19(21):5686–5699

    Article  Google Scholar 

  • Hersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz-Sabater J, Nicolas J, Peubey C, Radu R, Schepers D et al. (2020) The era5 global reanalysis. Quarterly Journal of the Royal Meteorological Society 146(730), 1999–2049

    Article  Google Scholar 

  • Hildebrand PH, Houser P, Schlosser CA (2003) Observing the global water cycle from space. In: 31st International Conference on Radar Meteorology, Citeseer

  • Hodnebrog Ø, Myhre G, Samset BH, Alterskjær K, Andrews T, Boucher O, Faluvegi G, Fläschner D, Forster PM, Kasoar M et al. (2019) Water vapour adjustments and responses differ between climate drivers. Atmospheric Chemistry and Physics 19(20), 12887–12899

    Article  Google Scholar 

  • Hoeting JA, Madigan D, Raftery AE, Volinsky CT (1999) Bayesian model averaging: a tutorial. Statistical science pp 382–401

  • Hollinger J (1991) Dmsp special sensor microwave/imager calibration/validation. Tech. rep, NAVAL RESEARCH LAB WASHINGTON DC

  • Hong Y, Hsu KL, Sorooshian S, Gao X (2004) Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. Journal of Applied Meteorology 43(12), 1834–1853

    Article  Google Scholar 

  • Hong Y, Adler RF, Hossain F, Curtis S, Huffman GJ (2007) A first approach to global runoff simulation using satellite rainfall estimation. Water Resources Research 43(8)

  • Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden P, Dai X, Maskell K, Johnson CA (2001) Climate change 2001: The scientific basis. Cambridge University Press p 881

  • Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Hong Y, Bowman KP, Stocker EF (2007) The trmm multisatellite precipitation analysis (tmpa): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of hydrometeorology 8(1):38–55

    Article  Google Scholar 

  • Huffman GJ, Adler RF, Bolvin DT, Gu G (2009) Improving the global precipitation record: Gpcp version 2.1. Geophysical Research Letters 36(17)

  • Huffman GJ, Adler RF, Bolvin DT, Nelkin EJ (2010) The trmm multi-satellite precipitation analysis (tmpa). In: Satellite rainfall applications for surface hydrology, Springer, pp 3–22

  • Huffman GJ, Bolvin DT, Braithwaite D, Hsu K, Joyce R, Xie P, Yoo SH (2015) Nasa global precipitation measurement (gpm) integrated multi-satellite retrievals for gpm (imerg). Algorithm Theoretical Basis Document (ATBD) Version 4:26

  • Hurrell JW, Holland MM, Gent PR, Ghan S, Kay JE, Kushner PJ, Lamarque JF, Large WG, Lawrence D, Lindsay K et al. (2013) The community earth system model: a framework for collaborative research. Bulletin of the American Meteorological Society 94(9), 1339–1360

    Article  Google Scholar 

  • Jasechko S, Sharp ZD, Gibson JJ, Birks SJ, Yi Y, Fawcett PJ (2013) Terrestrial water fluxes dominated by transpiration. Nature 496(7445), 347–350

    Article  Google Scholar 

  • Johnson GC, Chambers DP (2013) Ocean bottom pressure seasonal cycles and decadal trends from grace release-05: Ocean circulation implications. Journal of Geophysical Research: Oceans 118(9), 4228–4240

    Article  Google Scholar 

  • Joyce RJ, Janowiak JE, Arkin PA, Xie P (2004) Cmorph: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of hydrometeorology 5(3):487–503

    Article  Google Scholar 

  • Kemp W, Burnell D, Everson D, Thomson A (1983) Estimating missing daily maximum and minimum temperatures. Journal of climate and applied meteorology 22(9):1587–1593

    Article  Google Scholar 

  • Kessler A (1968) Globalbilanzen von Klimaelementen: ein Beitrag zur allgemeinen Klimatologie der Erde. na

  • Kharin VV, Zwiers F, Zhang X, Wehner M (2013) Changes in temperature and precipitation extremes in the cmip5 ensemble. Climatic change 119(2):345–357

    Article  Google Scholar 

  • Kibler KM, Biswas RK, Juarez Lucas AM (2014) Hydrologic data as a human right? equitable access to information as a resource for disaster risk reduction in transboundary river basins. Water policy 16(S2):36–58

    Article  Google Scholar 

  • Kidd C, Becker A, Huffman GJ, Muller CL, Joe P, Skofronick-Jackson G, Kirschbaum DB (2017) So, how much of the earth’s surface is covered by rain gauges? Bulletin of the American Meteorological Society 98(1), 69–78

    Article  Google Scholar 

  • Koirala S (2010) Explicit representation of groundwater process in a global-scale land surface model to improve hydrological predictions. PhD thesis, University of Tokyo

  • Korzoun VI (1978) World water balance and water resources of the earth. Studies and Reports in Hydrology 25

  • Kumar S, Allan RP, Zwiers F, Lawrence DM, Dirmeyer PA (2015) Revisiting trends in wetness and dryness in the presence of internal climate variability and water limitations over land. Geophysical Research Letters 42(24), 10–867

    Article  Google Scholar 

  • Kummerow C, Poyner P, Berg W, Thomas-Stahle J (2004) The effects of rainfall inhomogeneity on climate variability of rainfall estimated from passive microwave sensors. Journal of Atmospheric and Oceanic Technology 21(4), 624–638

    Article  Google Scholar 

  • Kunkee DB, Poe GA, Boucher DJ, Swadley SD, Hong Y, Wessel JE, Uliana EA (2008) Design and evaluation of the first special sensor microwave imager/sounder. IEEE Transactions on Geoscience and Remote Sensing 46(4), 863–883

    Article  Google Scholar 

  • Landerer FW, Swenson S (2012) Accuracy of scaled grace terrestrial water storage estimates. Water resources research 48(4)

  • Lawford R (1999) A midterm report on the gewex continental-scale international project (gcip). Journal of Geophysical Research: Atmospheres 104(D16), 19279–19292

    Article  Google Scholar 

  • L’Ecuyer TS, Stephens GL (2002) An estimation-based precipitation retrieval algorithm for attenuating radars. Journal of applied meteorology 41(3):272–285

    Article  Google Scholar 

  • Levizzani V, Cattani E (2019) Satellite remote sensing of precipitation and the terrestrial water cycle in a changing climate. Remote Sensing 11(19):2301

    Article  Google Scholar 

  • Liang X, Lettenmaier DP, Wood EF, Burges SJ (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. Journal of Geophysical Research: Atmospheres 99(D7), 14415–14428

    Article  Google Scholar 

  • Lim WH, Roderick ML (2009) An Atlas on Global Water Cycle: Based on the IPCC AR4 Climate Models. ANU Press

  • Loaiciga HA, Valdes JB, Vogel R, Garvey J, Schwarz H (1996) Global warming and the hydrologic cycle. Journal of Hydrology 174(1–2), 83–127

    Article  Google Scholar 

  • Lorenz C, Kunstmann H, Devaraju B, Tourian MJ, Sneeuw N, Riegger J (2014) Large-scale runoff from landmasses: a global assessment of the closure of the hydrological and atmospheric water balances. Journal of Hydrometeorology 15(6), 2111–2139

    Article  Google Scholar 

  • L’vovitch M (1945) World water regime elements. Sverdlovsk, Moscow, Russia

  • L’vovitch M (1970) World water balance (general report). In: World water balance: Proceedings of the Reading Symposium, pp 401–415

  • L’vovitch M (1973) The global water balance. Eos, Transactions American Geophysical Union 54(1), 28–53

  • Manabe S (1969) Climate and the ocean circulation: I. the atmospheric circulation and the hydrology of the earth’s surface. Monthly Weather Review 97(11):739–774

  • Marcinek J (1964) Der abfluß von den landflächen der erde und seine verteilung auf \(5^{\circ }\) zonen. PhD thesis, VEB Verlag für Bauwesen

  • Marengo JA (2005) Characteristics and spatio-temporal variability of the amazon river basin water budget. Climate Dynamics 24(1), 11–22

    Article  Google Scholar 

  • Markonis Y, Hanel M, Máca P, Kyselỳ J, Cook E (2018) Persistent multi-scale fluctuations shift european hydroclimate to its millennial boundaries. Nature communications 9(1):1–12

    Article  Google Scholar 

  • Markonis Y, Papalexiou S, Martinkova M, Hanel M (2019) Assessment of water cycle intensification over land using a multisource global gridded precipitation dataset. Journal of Geophysical Research: Atmospheres 124(21), 11175–11187

    Article  Google Scholar 

  • Markonis Y, Pappas C, Hanel M, Papalexiou SM (2021) A cross-scale framework for integrating multi-source data in earth system sciences. Environmental Modelling & Software 139:104997

    Article  Google Scholar 

  • Mather JR (1962) Average climatic water balance data of the continents: part 1. africa. Publications in Climatology

  • Mather JR (1963a) Average climatic water balance data of the continents: part 2. asia (excluding u.s.s.r.). Publications in Climatology

  • Mather JR (1963b) Average climatic water balance data of the continents: part 3. u.s.s.r. Publications in Climatology

  • Mather JR (1963c) Average climatic water balance data of the continents: part 4. australia, new zeland, and oceania. Publications in Climatology

  • Mather JR (1964a) Average climatic water balance data of the continents: part 5. europa. Publications in Climatology

  • Mather JR (1964b) Average climatic water balance data of the continents: part 6. north america (excluding united states). Publications in Climatology

  • Mather JR (1964c) Average climatic water balance data of the continents: part 7. united states. Publications in Climatology

  • Mather JR (1965) Average climatic water balance data of the continents: part 8. south america. Publications in Climatology

  • Mather JR (1969) The average annual water balance of the world. AWRA Symposium

  • McCabe MF, Rodell M, Alsdorf DE, Miralles DG, Uijlenhoet R, Wagner W, Lucieer A, Houborg R, Verhoest NE, Franz TE et al. (2017) The future of earth observation in hydrology. Hydrology and earth system sciences 21(7):3879

    Article  Google Scholar 

  • McGuffie K, Henderson-Sellers A (2001) Forty years of numerical climate modelling. International Journal of Climatology: A Journal of the Royal Meteorological Society 21(9), 1067–1109

    Article  Google Scholar 

  • Meigh J, McKenzie A, Sene K (1999) A grid-based approach to water scarcity estimates for eastern and southern africa. Water Resources Management 13(2), 85–115

    Article  Google Scholar 

  • Meinardus W (1934) Eine neue niederschlagskarte der erde. Petermanns Geogr Mitt 80:1–4

    Google Scholar 

  • Mira A (1964) Physical geographical atlas of the world, moscow, russia, 1964. Sovietgeography, Review and Translation 6

  • Mitchell J, Wilson C, Cunnington W (1987) On co2 climate sensitivity and model dependence of results. Quarterly Journal of the Royal Meteorological Society 113(475), 293–322

    Article  Google Scholar 

  • Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. International Journal of Climatology: A Journal of the Royal Meteorological Society 25(6), 693–712

    Article  Google Scholar 

  • Möller F (1951) Quarterly charts of rainfall for the whole earth. Petermanns Geograph Mitt 95:1–7

    Google Scholar 

  • Monteith J, Unsworth M (2013) Principles of environmental physics: plants, animals, and the atmosphere. Academic Press

    Google Scholar 

  • Mu Q, Heinsch FA, Zhao M, Running SW (2007) Development of a global evapotranspiration algorithm based on modis and global meteorology data. Remote sensing of Environment 111(4), 519–536

    Article  Google Scholar 

  • Mu Q, Zhao M, Running SW (2011) Improvements to a modis global terrestrial evapotranspiration algorithm. Remote Sensing of Environment 115(8), 1781–1800

    Article  Google Scholar 

  • Muller C, Chapman L, Johnston S, Kidd C, Illingworth S, Foody G, Overeem A, Leigh R (2015) Crowdsourcing for climate and atmospheric sciences: current status and future potential. International Journal of Climatology 35(11), 3185–3203

    Article  Google Scholar 

  • Munier S, Aires F (2018) A new global method of satellite dataset merging and quality characterization constrained by the terrestrial water budget. Remote Sensing of Environment 205:119–130

    Article  Google Scholar 

  • Nace RL (1968) Water of the world geological survey

  • Newman AJ, Clark MP, Craig J, Nijssen B, Wood A, Gutmann E, Mizukami N, Brekke L, Arnold JR (2015) Gridded ensemble precipitation and temperature estimates for the contiguous united states. Journal of Hydrometeorology 16(6), 2481–2500

    Article  Google Scholar 

  • Newman AJ, Clark MP, Longman RJ, Gilleland E, Giambelluca TW, Arnold JR (2019) Use of daily station observations to produce high-resolution gridded probabilistic precipitation and temperature time series for the hawaiian islands. Journal of Hydrometeorology 20(3), 509–529

    Article  Google Scholar 

  • NOAA US (1987) Space-based remote sensing of the earth: a report to the Congress. NASA

  • NRC (1986) Global Change in the Geosphere-Biosphere. National Academy Press

  • Oki T (1999) 1.2 the global water cycle. Global Energy and Water Cycles 134800000(10)

  • Oki T (2006) The hydrologic cycles and global circulation. Encyclopedia of hydrological sciences pp 13–22

  • Oki T, Kanae S (2006) Global hydrological cycles and world water resources. science 313(5790):1068–1072

  • Otto-Bliesner BL, Brady EC, Fasullo J, Jahn A, Landrum L, Stevenson S, Rosenbloom N, Mai A, Strand G (2016) Climate variability and change since 850 ce: An ensemble approach with the community earth system model. Bulletin of the American Meteorological Society 97(5), 735–754

    Article  Google Scholar 

  • O’Gorman P, Muller CJ (2010) How closely do changes in surface and column water vapor follow clausius-clapeyron scaling in climate change simulations? Environmental Research Letters 5(2):025207

    Article  Google Scholar 

  • O’Gorman PA, Allan RP, Byrne MP, Previdi M (2012) Energetic constraints on precipitation under climate change. Surveys in geophysics 33(3–4):585–608

    Article  Google Scholar 

  • Palissy B (1580) Discours admirables. Martin Le Jeune, Paris

  • Pan M, Wood EF (2006) Data assimilation for estimating the terrestrial water budget using a constrained ensemble kalman filter. Journal of Hydrometeorology 7(3), 534–547

    Article  Google Scholar 

  • Pan M, Sahoo AK, Troy TJ, Vinukollu RK, Sheffield J, Wood EF (2012) Multisource estimation of long-term terrestrial water budget for major global river basins. Journal of Climate 25(9), 3191–3206

    Article  Google Scholar 

  • Papalexiou SM (2018) Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency. Advances in water resources 115:234–252

    Article  Google Scholar 

  • Papalexiou SM, Markonis Y, Lombardo F, AghaKouchak A, Foufoula-Georgiou E (2018) Precise temporal disaggregation preserving marginals and correlations (dipmac) for stationary and nonstationary processes. Water Resources Research 54(10), 7435–7458

    Article  Google Scholar 

  • Pappas C, Papalexiou SM, Koutsoyiannis D (2014) A quick gap filling of missing hydrometeorological data. Journal of Geophysical Research: Atmospheres 119(15), 9290–9300

    Article  Google Scholar 

  • Pendergrass AG (2018) What precipitation is extreme? Science 360(6393), 1072–1073

    Article  Google Scholar 

  • Pendergrass AG, Hartmann DL (2014) Two modes of change of the distribution of rain. Journal of Climate 27(22), 8357–8371

    Article  Google Scholar 

  • Petković V, Kummerow CD (2017) Understanding the sources of satellite passive microwave rainfall retrieval systematic errors over land. Journal of Applied Meteorology and Climatology 56(3), 597–614

    Article  Google Scholar 

  • Pfister L, Savenije HH, Fenicia F, et al. (2009) Leonardo Da Vinci’s water theory: on the origin and fate of water. Iahs Press

  • Phillips NA (1956) The general circulation of the atmosphere: A numerical experiment. Quarterly Journal of the Royal Meteorological Society 82(352), 123–164

    Article  Google Scholar 

  • Pollio MV (1648) De architectura, liber octavus. In: Vitruvius (ed) De Architectura, Elsevier, pp 150 – 172

  • Postel SL, Daily GC, Ehrlich PR (1996) Human appropriation of renewable fresh water. Science 271(5250), 785–788

    Article  Google Scholar 

  • Prein AF, Pendergrass AG (2019) Can we constrain uncertainty in hydrologic cycle projections? Geophysical Research Letters 46(7), 3911–3916

    Article  Google Scholar 

  • Qian T, Dai A, Trenberth KE, Oleson KW, (2006) Simulation of global land surface conditions from 1948 to, (2004) part i: Forcing data and evaluations. Journal of Hydrometeorology 7(5), 953–975

    Article  Google Scholar 

  • Raschke E, Karstens U, Nolte-Holube R, Brandt R, Isemer HJ, Lohmann D, Lobmeyr M, Rockel B, Stuhlmann R (1998) The baltic sea experiment baltex: A brief overview and some selected results of the authors. Surveys in Geophysics 19(1), 1–22

    Article  Google Scholar 

  • Raschke E, Meywerk J, Warrach K, Andrea U, Bergström S, Beyrich F, Bosveld F, Bumke K, Fortelius C, Graham L et al. (2001) The baltic sea experiment (baltex): a european contribution to the investigation of the energy and water cycle over a large drainage basin. Bulletin of the American Meteorological Society 82(11), 2389–2414

    Article  Google Scholar 

  • Rasmussen JL (1970) The atmospheric water balance and the hydrology of large river basins 1. JAWRA Journal of the American Water Resources Association 6(4), 631–639

    Article  Google Scholar 

  • Redelsperger JL, Thorncroft CD, Diedhiou A, Lebel T, Parker DJ, Polcher J (2006) African monsoon multidisciplinary analysis: An international research project and field campaign. Bulletin of the American Meteorological Society 87(12), 1739–1746

    Article  Google Scholar 

  • Reichel E (1952) Der stand des verdunstungsproblems. Ber Dt Wetterdienst US-Zone 35:155–172

    Google Scholar 

  • Reichle R (2012) The merra-land data product (version 1.2). GMAO Off Note 3

  • Richardson T, Forster P, Andrews T, Boucher O, Faluvegi G, Fläschner D, Hodnebrog Ø, Kasoar M, Kirkevåg A, Lamarque JF et al. (2018) Drivers of precipitation change: An energetic understanding. Journal of climate 31(23):9641–9657

    Article  Google Scholar 

  • Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim GK et al. (2011) Merra: Nasa’s modern-era retrospective analysis for research and applications. Journal of climate 24(14):3624–3648

    Article  Google Scholar 

  • Robertson F, Bosilovich M, Roberts J, Reichle R, Adler R, Ricciardulli L, Berg W, Huffman G (2014) Consistency of estimated global water cycle variations over the satellite era. Journal of Climate 27(16), 6135–6154

    Article  Google Scholar 

  • Rodell M, Houser P, Jambor U, Gottschalck J, Mitchell K, Meng CJ, Arsenault K, Cosgrove B, Radakovich J, Bosilovich M et al. (2004) The global land data assimilation system. Bulletin of the American Meteorological Society 85(3), 381–394

    Article  Google Scholar 

  • Rodell M, Beaudoing HK, L’Ecuyer T, Olson WS, Famiglietti JS, Houser PR, Adler R, Bosilovich MG, Clayson CA, Chambers D et al. (2015) The observed state of the water cycle in the early twenty-first century. Journal of Climate 28(21), 8289–8318

    Article  Google Scholar 

  • Roderick M, Sun F, Lim WH, Farquhar G (2014) A general framework for understanding the response of the water cycle to global warming over land and ocean. Hydrology and Earth System Sciences 18(5), 1575–1589

    Article  Google Scholar 

  • Rodgers CD (2000) Inverse methods for atmospheric sounding: theory and practice, vol 2. World scientific

  • Rost S, Gerten D, Bondeau A, Lucht W, Rohwer J, Schaphoff S (2008) Agricultural green and blue water consumption and its influence on the global water system. Water Resources Research 44(9)

  • Rudolf B, Schneider U (2005) Calculation of gridded precipitation data for the global land-surface using in-situ gauge observations. In: Proc. Second Workshop of the Int. Precipitation Working Group, pp 231–247

  • Sahoo AK, Pan M, Troy TJ, Vinukollu RK, Sheffield J, Wood EF (2011) Reconciling the global terrestrial water budget using satellite remote sensing. Remote Sensing of Environment 115(8), 1850–1865

    Article  Google Scholar 

  • Saltikoff E, Kurri M, Leijnse H, Barbosa S, Stiansen K (2017) Maintenance keeps radars running. Bulletin of the American Meteorological Society 98(9), 1833–1840

    Article  Google Scholar 

  • Salzmann M (2016) Global warming without global mean precipitation increase? Science advances 2(6):e1501572

    Article  Google Scholar 

  • Samset BH, Myhre G, Forster P, Hodnebrog Ø, Andrews T, Boucher O, Faluvegi G, Fläschner D, Kasoar M, Kharin V, et al. (2018) Weak hydrological sensitivity to temperature change over land, independent of climate forcing. npj Climate and Atmospheric Science 1(1):1–8

  • Schlesinger WH (2005) Biogeochemistry, vol 8. Elsevier

    Google Scholar 

  • Schlosser CA, Houser PR (2007) Assessing a satellite-era perspective of the global water cycle. Journal of climate 20(7):1316–1338

    Article  Google Scholar 

  • Schmidt W (1915) Strahlung und verdunstung an freien wasserflächen; ein beitrag zum wärmehaushalt des weltmeers und zum wasserhaushalt der erde. Ann Calender Hydrographie und Maritimen Meteorologie 43:111–124

    Google Scholar 

  • Schmitt RW (1995) The ocean component of the global water cycle. Reviews of Geophysics 33(S2), 1395–1409

    Article  Google Scholar 

  • Schneider U, Becker A, Finger P, Meyer-Christoffer A, Ziese M, Rudolf B (2014) Gpcc’s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theoretical and Applied Climatology 115(1–2), 15–40

    Article  Google Scholar 

  • Schneider U, Finger P, Meyer-Christoffer A, Rustemeier E, Ziese M, Becker A (2017) Evaluating the hydrological cycle over land using the newly-corrected precipitation climatology from the global precipitation climatology centre (gpcc). Atmosphere 8(3):52

    Article  Google Scholar 

  • Seager R, Naik N, Vecchi GA (2010) Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. Journal of Climate 23(17), 4651–4668

    Article  Google Scholar 

  • Sheffield J, Wood EF (2007) Characteristics of global and regional drought, 1950–2000: Analysis of soil moisture data from off-line simulation of the terrestrial hydrologic cycle. Journal of Geophysical Research: Atmospheres 112(D17)

  • Sheffield J, Goteti G, Wood EF (2006) Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of climate 19(13):3088–3111

    Article  Google Scholar 

  • Sheffield J, Ferguson CR, Troy TJ, Wood EF, McCabe MF (2009) Closing the terrestrial water budget from satellite remote sensing. Geophysical Research Letters 36(7)

  • Sheffield J, Wood EF, Pan M, Beck H, Coccia G, Serrat-Capdevila A, Verbist K (2018) Satellite remote sensing for water resources management: Potential for supporting sustainable development in data-poor regions. Water Resources Research 54(12), 9724–9758

    Article  Google Scholar 

  • Shepard D (1968) A two-dimensional interpolation function for irregularly-spaced data. In: Proceedings of the 1968 23rd ACM national conference, pp 517–524

  • Shiklomanov IA (1998) World water resources: A new appraisal and assessment for the 21st century. UNESCO

  • Shuttleworth WJ, Wallace J (1985) Evaporation from sparse crops-an energy combination theory. Quarterly Journal of the Royal Meteorological Society 111(469), 839–855

    Article  Google Scholar 

  • Simmons A (2006) Era-interim: New ecmwf reanalysis products from 1989 onwards. ECMWF newsletter 110:25–36

    Google Scholar 

  • Simolo C, Brunetti M, Maugeri M, Nanni T (2010) Improving estimation of missing values in daily precipitation series by a probability density function-preserving approach. International Journal of Climatology 30(10), 1564–1576

    Article  Google Scholar 

  • Skliris N, Zika JD, Nurser G, Josey SA, Marsh R (2016) Global water cycle amplifying at less than the clausius-clapeyron rate. Scientific reports 6(1):1–9

    Article  Google Scholar 

  • Speidel D, Agnew A (1982) The natural geochemistry of our environment. Westview Press p 16

  • Starr V, Peixoto J (1958) On the global balance of water vapor and the hydrology of deserts. Tellus 10(2), 188–194

    Article  Google Scholar 

  • Stewart RE, Leighton H, Marsh P, Moore G, Ritchie H, Rouse W, Soulis E, Strong G, Crawford R, Kochtubajda B (1998) The mackenzie gewex study: The water and energy cycles of a major north american river basin. Bulletin of the American Meteorological Society 79(12), 2665–2684

    Article  Google Scholar 

  • Stommel H, Stommel E (1979) The year without a summer. Scientific American 240(6), 176–187

    Article  Google Scholar 

  • Sun Q, Miao C, Duan Q, Ashouri H, Sorooshian S, Hsu KL (2018) A review of global precipitation data sets: Data sources, estimation, and intercomparisons. Reviews of Geophysics 56(1), 79–107

    Article  Google Scholar 

  • Syed TH, Famiglietti JS, Chambers DP, Willis JK, Hilburn K (2010) Satellite-based global-ocean mass balance estimates of interannual variability and emerging trends in continental freshwater discharge. Proceedings of the National Academy of Sciences 107(42), 17916–17921

    Article  Google Scholar 

  • Takata K, Emori S, Watanabe T (2003) Development of the minimal advanced treatments of surface interaction and runoff. Global and planetary Change 38(1–2), 209–222

    Article  Google Scholar 

  • Tapiador FJ, Navarro A, Moreno R, Sánchez JL, García-Ortega E (2020) Regional climate models: 30 years of dynamical downscaling. Atmospheric Research 235:104785

    Article  Google Scholar 

  • Tapley BD, Bettadpur S, Ries JC, Thompson PF, Watkins MM (2004) Grace measurements of mass variability in the earth system. Science 305(5683), 503–505

    Article  Google Scholar 

  • Thackeray CW, DeAngelis AM, Hall A, Swain DL, Qu X (2018) On the connection between global hydrologic sensitivity and regional wet extremes. Geophysical Research Letters 45(20), 11–343

    Article  Google Scholar 

  • Thornthwaite CW (1948) An approach toward a rational classification of climate. Geographical review 38(1):55–94

    Article  Google Scholar 

  • Trenberth KE, Guillemot CJ (1998) Evaluation of the atmospheric moisture and hydrological cycle in the ncep/ncar reanalyses. Climate Dynamics 14(3), 213–231

    Article  Google Scholar 

  • Trenberth KE, Dai A, Rasmussen RM, Parsons DB (2003) The changing character of precipitation. Bulletin of the American Meteorological Society 84(9), 1205–1218

    Article  Google Scholar 

  • Trenberth KE, Smith L, Qian T, Dai A, Fasullo J (2007) Estimates of the global water budget and its annual cycle using observational and model data. Journal of Hydrometeorology 8(4), 758–769

    Article  Google Scholar 

  • Trenberth KE, Fasullo JT, Mackaro J (2011) Atmospheric moisture transports from ocean to land and global energy flows in reanalyses. Journal of climate 24(18):4907–4924

    Article  Google Scholar 

  • Trenberth KE, Zhang Y, Gehne M (2017) Intermittency in precipitation: Duration, frequency, intensity, and amounts using hourly data. Journal of Hydrometeorology 18(5), 1393–1412

    Article  Google Scholar 

  • Turk JT, Mostovoy GV, Anantharaj V (2010) The nrl-blend high resolution precipitation product and its application to land surface hydrology. In: Satellite Rainfall Applications for Surface Hydrology, Springer, pp 85–104

  • Uppala SM, Kållberg P, Simmons A, Andrae U, Bechtold VDC, Fiorino M, Gibson J, Haseler J, Hernandez A, Kelly G et al. (2005) The era-40 re-analysis. Quarterly Journal of the Royal Meteorological Society: A journal of the atmospheric sciences, applied meteorology and physical oceanography 131(612):2961–3012

    Article  Google Scholar 

  • Van Dijk A, Renzullo LJ, et al. (2011) Water resource monitoring systems and the role of satellite observations. Copernicus GmbH

  • Van der Ent RJ, Savenije HH, Schaefli B, Steele-Dunne SC (2010) Origin and fate of atmospheric moisture over continents. Water Resources Research 46(9)

  • Van der Leeden F (1990) The water encyclopedia. CRC Press

    Google Scholar 

  • Vinukollu RK, Meynadier R, Sheffield J, Wood EF (2011a) Multi-model, multi-sensor estimates of global evapotranspiration: Climatology, uncertainties and trends. Hydrological Processes 25(26), 3993–4010

    Article  Google Scholar 

  • Vinukollu RK, Wood EF, Ferguson CR, Fisher JB (2011b) Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches. Remote Sensing of Environment 115(3), 801–823

    Article  Google Scholar 

  • Wahr J, Molenaar M, Bryan F (1998) Time variability of the earth’s gravity field: Hydrological and oceanic effects and their possible detection using grace. Journal of Geophysical Research: Solid Earth 103(B12), 30205–30229

    Article  Google Scholar 

  • Walker D, Forsythe N, Parkin G, Gowing J (2016) Filling the observational void: Scientific value and quantitative validation of hydrometeorological data from a community-based monitoring programme. Journal of Hydrology 538:713–725

    Article  Google Scholar 

  • Wambua RM, Mutua BM, Raude JM (2016) Prediction of missing hydro-meteorological data series using artificial neural networks (ann) for upper tana river basin, kenya. vol 4:35–43

  • Wang G, Wang D, Trenberth KE, Erfanian A, Yu M, Bosilovich MG, Parr DT (2017) The peak structure and future changes of the relationships between extreme precipitation and temperature. Nature Climate Change 7(4), 268–274

    Article  Google Scholar 

  • Wang K, Dickinson RE (2012) A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. Reviews of Geophysics 50(2)

  • Webb RS, Rosenzweig CE, Levine ER (1993) Specifying land surface characteristics in general circulation models: Soil profile data set and derived water-holding capacities. Global Biogeochemical Cycles 7(1), 97–108

    Article  Google Scholar 

  • Wehbe Y, Temimi M, Adler RF (2020) Enhancing precipitation estimates through the fusion of weather radar, satellite retrievals, and surface parameters. Remote Sensing 12(8):1342

    Article  Google Scholar 

  • Wild M, Liepert B (2010) The earth radiation balance as driver of the global hydrological cycle. Environmental Research Letters 5(2):025203

    Article  Google Scholar 

  • Willmott CJ, Rowe CM, Mintz Y (1985) Climatology of the terrestrial seasonal water cycle. Journal of Climatology 5(6), 589–606

    Article  Google Scholar 

  • Willmott CJ, Robeson SM, Feddema JJ (1994) Estimating continental and terrestrial precipitation averages from rain-gauge networks. International Journal of Climatology 14(4), 403–414

    Article  Google Scholar 

  • Wundt W (1938) Das Bild des Wasserkreislaufs auf Grund früherer und neuer Forschungen. Reichs-und Preuß, Ministerium für Ernährung und Landwirtschaft, Landesanst

    Google Scholar 

  • Wüst G (1922) Verdunstung und niederschlag auf der erde. Z Ges f Erdkunde Berlin

  • Wüst G, Defant A (1936) Schichtung und Zirkulation des atlantischen Ozeans. W. de Gruyter

  • Wüst G, Brogmus W, Noodt E (1954) Die zonale verteilung von salzgehalt, niederschlag, verdunstung, temperatur und dichte an der oberfläche der ozeane. Kieler Meeresforschungen 10(1954):2

    Google Scholar 

  • Yasunari T (1994) Gewex-related asian monsoon experiment (game). Advances in space research 14(1):161–165

    Article  Google Scholar 

  • Young KC (1992) A three-way model for interpolating for monthly precipitation values. Monthly Weather Review 120(11), 2561–2569

    Article  Google Scholar 

  • Zhang K, Kimball JS, Nemani RR, Running SW (2010) A continuous satellite-derived global record of land surface evapotranspiration from 1983 to 2006. Water Resources Research 46(9)

  • Zhang Y, Pan M, Wood EF (2016) On creating global gridded terrestrial water budget estimates from satellite remote sensing. In: Remote Sensing and Water Resources, Springer, pp 59–78

  • Zhang Y, Pan M, Sheffield J, Siemann AL, Fisher CK, Liang M, Beck HE, Wanders N, MacCracken RF, Houser PR, et al. (2018) A climate data record (cdr) for the global terrestrial water budget: 1984–2010. Hydrology and Earth System Sciences (Online) 22(PNNL-SA-129750)

  • Zhao M, Golaz JC, Held IM, Ramaswamy V, Lin SJ, Ming Y, Ginoux P, Wyman B, Donner L, Paynter D et al. (2016) Uncertainty in model climate sensitivity traced to representations of cumulus precipitation microphysics. Journal of Climate 29(2), 543–560

    Article  Google Scholar 

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Acknowledgements

This work was supported by the Faculty of Environmental Sciences, Czech University of Life Sciences Prague internal Grant 2020B0001 “A multiscale framework for data analysis of global precipitation”. The data compiled herein and the R code for the figures are publicly available at https://github.com/MiRoVaGo/chronology_gwc.

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Vargas Godoy, M.R., Markonis, Y., Hanel, M. et al. The Global Water Cycle Budget: A Chronological Review. Surv Geophys 42, 1075–1107 (2021). https://doi.org/10.1007/s10712-021-09652-6

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