Abbott, B. W., and Coauthors, 2019: Human domination of the global water cycle absent from depictions and perceptions. Nat. Geosci., 12, 533–540, https://doi.org/10.1038/s41561-019-0374-y.
Abolafia-Rosenzweig, R., M. Pan, J. L. Zeng, and B. Livneh, 2021: Remotely sensed ensembles of the terrestrial water budget over major global river basins: An assessment of three closure techniques. Remote Sens. Environ., 252, 112191, https://doi.org/10.1016/j.rse.2020.112191.
Aires, F., 2014: Combining datasets of satellite-retrieved products. Part I: Methodology and water budget closure. J. Hydrometeor., 15, 1677–1691, https://doi.org/10.1175/JHM-D-13-0148.1.
Aires, F., 2018: Atmospheric water vapour profiling over ocean/land and for clear/cloudy situations using microwave observations. Remote Sensing of Clouds and Precipitation, Springer, 215–255.
Albergel, C., and Coauthors, 2013: Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing. J. Hydrometeor., 14, 1259–1277, https://doi.org/10.1175/JHM-D-12-0161.1.
Alexander, L. V., M. Bador, R. Roca, S. Contractor, M. G. Donat, and P. L. Nguyen, 2020: Intercomparison of annual precipitation indices and extremes over global land areas from in situ, space-based and reanalysis products. Environ. Res. Lett., 15, 055002, https://doi.org/10.1088/1748-9326/ab79e2.
Allan, R. P., and Coauthors, 2020: Advances in understanding large-scale responses of the water cycle to climate change. Ann. N. Y. Acad. Sci., 1472, 49–75, https://doi.org/10.1111/nyas.14337.
Asner, G. P., and Coauthors, 2012: High-resolution mapping of forest carbon stocks in the Colombian Amazon. Biogeosciences, 9, 2683–2696, https://doi.org/10.5194/bg-9-2683-2012.
Avitabile, V., and Coauthors, 2016: An integrated pan-tropical biomass map using multiple reference datasets. Global Change Biol., 22, 1406–1420, https://doi.org/10.1111/gcb.13139.
Azarderakhsh, M., W. B. Rossow, F. Papa, H. Norouzi, and R. Khanbilvardi, 2011: Diagnosing water variations within the Amazon basin using satellite data. J. Geophys. Res., 116, D24107, https://doi.org/10.1029/2011JD015997.
Babaeian, E., M. Sadeghi, S. B. Jones, C. Montzka, H. Vereecken, and M. Tuller, 2019: Ground, proximal, and satellite remote sensing of soil moisture. Rev. Geophys., 57, 530–616, https://doi.org/10.1029/2018RG000618.
Bamber, J. L., and A. Rivera, 2007: A review of remote sensing methods for glacier mass balance determination. Global Planet. Change, 59, 138–148, https://doi.org/10.1016/j.gloplacha.2006.11.031.
Bamber, J. L., R. M. Westaway, B. Marzeion, and B. Wouters, 2018: The land ice contribution to sea level during the satellite era. Environ. Res. Lett., 13, 063008, https://doi.org/10.1088/1748-9326/aac2f0.
Baumgartner, A., and E. Reichel, 1975: Die Weltwasserbilanz: Niederschlag, Verdunstung und Abfluß über Land und Meer sowie auf der Erde im Jahresdurchschnitt. R. Oldenbourg Verlag, 197 pp.
Beck, H. E., and Coauthors, 2021: Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors. Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021.
Berg, A., and J. Sheffield, 2019: Evapotranspiration partitioning in CMIP5 models: Uncertainties and future projections. J. Climate, 32, 2653–2671, https://doi.org/10.1175/JCLI-D-18-0583.1.
Berghuijs, W. R., R. A. Woods, and M. Hrachowitz, 2014: A precipitation shift from snow towards rain leads to a decrease in streamflow. Nat. Climate Change, 4, 583–586, https://doi.org/10.1038/nclimate2246.
Berry, D. I., and E. C. Kent, 2011: Air–sea fluxes from ICOADS: The construction of a new gridded dataset with uncertainty estimates. Int. J. Climatol., 31, 987–1001, https://doi.org/10.1002/joc.2059.
Bindoff, N. L., and Coauthors, 2013: Detection and attribution of climate change: From global to regional. Climate Change 2013: The Physical Science Basis, et al., Eds., Cambridge University Press, 867–952.
Blazquez, A., B. Meyssignac, J. M. Lemoine, E. Berthier, A. Ribes, and A. Cazenave, 2018: Exploring the uncertainty in GRACE estimates of the mass redistributions at the Earth surface: Implications for the global water and sea level budgets. Geophys. J. Int., 215, 415–430, https://doi.org/10.1093/gji/ggy293.
Bojinski, S., M. Verstraete, T. C. Peterson, C. Richter, A. Simmons, and M. Zemp, 2014: The concept of essential climate variables in support of climate research, applications, and policy. Bull. Amer. Meteor. Soc., 95, 1431–1443, https://doi.org/10.1175/BAMS-D-13-00047.1.
Bolch, T., L. Sandberg Sørensen, S. B. Simonsen, N. Mölg, H. Machguth, P. Rastner, and F. Paul, 2013: Mass loss of Greenland’s glaciers and ice caps 2003–2008 revealed from ICESat laser altimetry data. Geophys. Res. Lett., 40, 875–881, https://doi.org/10.1002/grl.50270.
Bonfils, C. J. W., B. D. Santer, J. C. Fyfe, K. Marvel, T. J. Phillips, and S. R. H. Zimmerman, 2020: Human influence on joint changes in temperature, rainfall and continental aridity. Nat. Climate Change, 10, 726–731, https://doi.org/10.1038/s41558-020-0821-1.
Bosilovich, M. G., F. R. Robertson, L. Takacs, A. Molod, and D. Mocko, 2017: Atmospheric water balance and variability in the MERRA-2 reanalysis. J. Climate, 30, 1177–1196, https://doi.org/10.1175/JCLI-D-16-0338.1.
Böttcher, H., and Coauthors, 2017: Independent monitoring: Building trust and consensus around GHG data for increased accountability of mitigation in the land use sector. European Commission Rep., 112 pp., https://doi.org/10.2834/513344.
Braithwaite, R. J., and P. D. Hughes, 2020: Regional geography of glacier mass balance variability over seven decades 1946–2015. Front. Earth Sci., 8, 302, https://doi.org/10.3389/feart.2020.00302.
Brenninkmeijer, C. A. M., and Coauthors, 2007: Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrumented Container: The new CARIBIC system. Atmos. Chem. Phys., 7, 4953–4976, https://doi.org/10.5194/acp-7-4953-2007.
Broadbent, A. M., A. M. Coutts, K. A. Nice, M. Demuzere, E. S. Krayenhoff, N. J. Tapper, and H. Wouters, 2019: The Air-Temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET v1.0): An efficient and user-friendly model of city cooling. Geosci. Model Dev., 12, 785–803, https://doi.org/10.5194/gmd-12-785-2019.
Brocca, L., A. Tarpanelli, P. Filippucci, W. Dorigo, F. Zaussinger, A. Gruber, and D. Fernández-Prieto, 2018: How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products. Int. J. Appl. Earth Obs. Geoinf., 73, 752–766, https://doi.org/10.1016/j.jag.2018.08.023.
Brown, J., O. Ferrians, J. Heginbottom, and E. Melnikov, 2002: Circum-Arctic map of permafrost and ground-ice conditions, version 2. National Snow and Ice Data Center, accessed 9 August 2021, https://nsidc.org/data/ggd318.
Brown, R. D., and C. Derksen, 2013: Is Eurasian October snow cover extent increasing? Environ. Res. Lett., 8, 024006, https://doi.org/10.1088/1748-9326/8/2/024006.
Brown, R. D., B. Fang, and L. Mudryk, 2019: Update of Canadian historical snow survey data and analysis of snow water equivalent trends, 1967–2016. Atmos.–Ocean, 57, 149–156, https://doi.org/10.1080/07055900.2019.1598843.
Burnett, W. C., M. Taniguchi, and J. Oberdorfer, 2001: Measurement and significance of the direct discharge of groundwater into the coastal zone. J. Sea Res., 46, 109–116, https://doi.org/10.1016/S1385-1101(01)00075-2.
Busker, T., A. de Roo, E. Gelati, C. Schwatke, M. Adamovic, B. Bisselink, J.-F. Pekel, and A. Cottam, 2019: A global lake and reservoir volume analysis using a surface water dataset and satellite altimetry. Hydrol. Earth Syst. Sci., 23, 669–690, https://doi.org/10.5194/hess-23-669-2019.
Byrne, M. P., and P. A. O’Gorman, 2016: Understanding decreases in land relative humidity with global warming: Conceptual model and GCM simulations. J. Climate, 29, 9045–9061, https://doi.org/10.1175/JCLI-D-16-0351.1.
Byrne, M. P., and P. A. O’Gorman, 2018: Trends in continental temperature and humidity directly linked to ocean warming. Proc. Natl. Acad. Sci. USA, 115, 4863–4868, https://doi.org/10.1073/pnas.1722312115.
Cazenave, A., and Coauthors, 2018: Global sea-level budget 1993–present. Earth Syst. Sci. Data, 10, 1551–1590, https://doi.org/10.5194/essd-10-1551-2018.
Chang, A. T., J. L. Foster, and D. K. Hall, 1990: Satellite sensor estimates of Northern Hemisphere snow volume. Int. J. Remote Sens., 11, 167–171, https://doi.org/10.1080/01431169008955009.
Chen, B., and Z. Liu, 2016: Global water vapor variability and trend from the latest 36 year (1979 to 2014) data of ECMWF and NCEP reanalyses, radiosonde, GPS, and microwave satellite. J. Geophys. Res. Atmos., 121, 11 442–11 462, https://doi.org/10.1002/2016JD024917.
Chen, J., J. S. Famigliett, B. R. Scanlon, and M. Rodell, 2016: Groundwater storage changes: Present status from GRACE observations. Surv. Geophys., 37, 397–417, https://doi.org/10.1007/s10712-015-9332-4.
Cogley, J., and Coauthors, 2011: Glossary of glacier mass balance and related terms. IACS Contribution 2, 124 pp., https://unesdoc.unesco.org/ark:/48223/pf0000192525.
Cook, B. I., J. S. Mankin, K. Marvel, A. P. Williams, J. E. Smerdon, and K. J. Anchukaitis, 2020a: Twenty-first century drought projections in the CMIP6 forcing scenarios. Earth’s Future, 8, e2019EF001461, https://doi.org/10.1029/2019EF001461.
Cook, B. I., S. S. McDermid, M. J. Puma, A. P. Williams, R. Seager, M. Kelley, L. Nazarenko, and I. Aleinov, 2020b: Divergent regional climate consequences of maintaining current irrigation rates in the 21st century. J. Geophys. Res., 125, e2019JD031814, https://doi.org/10.1029/2019JD031814.
Crétaux, J. F., R. Abarca-del-Río, M. Bergé-Nguyen, A. Arsen, V. Drolon, G. Clos, and P. Maisongrande, 2016: Lake volume monitoring from space. Surv. Geophys., 37, 269–305, https://doi.org/10.1007/s10712-016-9362-6.
de Graaf, I., E. H. Sutanudjaja, L. P. H. van Beek, and M. F. P. Bierkens, 2015: A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19, 823–837, https://doi.org/10.5194/hess-19-823-2015.
de Graaf, I., R. van Beek, T. Gleeson, N. Moosdorf, O. Schmitz, E. Sutanudjaja, and M. Bierkens, 2016: A global-scale two-layer transient groundwater model: Development and application to groundwater depletion. Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-121.
Deines, J. M., A. D. Kendall, and D. W. Hyndman, 2017: Annual irrigation dynamics in the U.S. northern High Plains derived from Landsat satellite data. Geophys. Res. Lett., 44, 9350–9360, https://doi.org/10.1002/2017GL074071.
Dillon, P., and Coauthors, 2019: Sixty years of global progress in managed aquifer recharge. Hydrogeol. J., 27, 1–30, https://doi.org/10.1007/s10040-018-1841-z.
Dorigo, W. A., R. Richter, F. Baret, R. Bamler, and W. Wagner, 2009: Enhanced automated canopy characterization from hyperspectral data by a novel two step radiative transfer model inversion approach. Remote Sens., 1, 1139–1170, https://doi.org/10.3390/rs1041139.
Dorigo, W. A.,, K. Scipal, R. M. Parinussa, Y. Y. Liu, W. Wagner, R. A. M. de Jeu, and V. Naeimi, 2010: Error characterisation of global active and passive microwave soil moisture datasets. Hydrol. Earth Syst. Sci., 14, 2605–2616, https://doi.org/10.5194/hess-14-2605-2010.
Dorigo, W. A.,, and Coauthors, 2013: Global automated quality control of in situ soil moisture data from the International Soil Moisture Network. Vadose Zone J., 12, 1–21, https://doi.org/10.2136/vzj2012.0097.
Dorigo, W. A., and Coauthors, 2017: ESA CCI soil moisture for improved Earth system understanding: State-of-the art and future directions. Remote Sens. Environ., 203, 185–215, https://doi.org/10.1016/j.rse.2017.07.001.
Dorigo, W. A.,, I. Himmelbauer, L. Zappa, W. Preimesberger, D. Aberer, L. Schremmer, and I. Petrakovic, 2021: The International Soil Moisture Network: Serving Earth system science for over a decade. Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-2.
Doughty, C. E., S. R. Loarie, and C. B. Field, 2012: Theoretical impact of changing albedo on precipitation at the southernmost boundary of the ITCZ in South America. Earth Interact., 16, https://doi.org/10.1175/2012EI422.1.
Downing, J. A., and Coauthors, 2006: The global abundance and size distribution of lakes, ponds, and impoundments. Limnol. Oceanogr., 51, 2388–2397, https://doi.org/10.4319/lo.2006.51.5.2388.
Droogers, P., W. W. Immerzeel, and I. J. Lorite, 2010: Estimating actual irrigation application by remotely sensed evapotranspiration observations. Agric. Water Manage., 97, 1351–1359, https://doi.org/10.1016/j.agwat.2010.03.017.
Durack, P. J., and S. E. Wijffels, 2010: Fifty-year trends in global ocean salinities and their relationship to broad-scale warming. J. Climate, 23, 4342–4362, https://doi.org/10.1175/2010JCLI3377.1.
Durack, P. J., S. E. Wijffels, and R. J. Matear, 2012: Ocean salinities reveal strong global water cycle intensification during 1950 to 2000. Science, 336, 455–458, https://doi.org/10.1126/science.1212222.
Eakins, B. W., and G. F. Sharman, 2010: Volumes of the world’s oceans from ETOPO1. NOAA National Geophys. Data Center, accessed 25 August 2020, www.ngdc.noaa.gov/mgg/global/etopo1_ocean_volumes.html.
Edson, J. B., A. A. Hinton, K. E. Prada, J. E. Hare, and C. W. Fairall, 1998: Direct covariance flux estimates from mobile platforms at sea. J. Atmos. Oceanic Technol., 15, 547–562, https://doi.org/10.1175/1520-0426(1998)015<0547:DCFEFM>2.0.CO;2.
Eekhout, J. P. C., J. E. Hunink, W. Terink, and J. de Vente, 2018: Why increased extreme precipitation under climate change negatively affects water security. Hydrol. Earth Syst. Sci., 22, 5935–5946, https://doi.org/10.5194/hess-22-5935-2018.
Elliott, G. W., 1974: Precipitation signatures in sea-surface-layer conditions during BOMEX. J. Phys. Oceanogr., 4, 498–501, https://doi.org/10.1175/1520-0485(1974)004<0498:PSISSL>2.0.CO;2.
Ellison, D., and Coauthors, 2017: Trees, forests and water: Cool insights for a hot world. Global Environ. Change, 43, 51–61, https://doi.org/10.1016/j.gloenvcha.2017.01.002.
Enderlin, E. M., I. M. Howat, S. Jeong, M. J. Noh, J. H. Van Angelen, and M. R. Van Den Broeke, 2014: An improved mass budget for the Greenland ice sheet. Geophys. Res. Lett., 41, 866–872, https://doi.org/10.1002/2013GL059010.
Entekhabi, D., and Coauthors, 2010: The Soil Moisture Active Passive (SMAP) mission. Proc. IEEE, 98, 704–716, https://doi.org/10.1109/JPROC.2010.2043918.
Fairall, C. W., and Coauthors, 2003: Bulk parameterization of air–sea fluxes: Updates and verification for the COARE algorithm. J. Climate, 16, 571–591, https://doi.org/10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2.
Famiglietti, J. S., 2014: The global groundwater crisis. Nat. Climate Change, 4, 945–948, https://doi.org/10.1038/nclimate2425.
FAO, 2021: AQUASTAT database. Accessed 19 August 2021, www.fao.org/nr/water/aquastat/data/query/index.html?lang=en.
Farinotti, D., M. Huss, J. J. Fürst, J. Landmann, H. Machguth, F. Maussion, and A. Pandit, 2019: A consensus estimate for the ice thickness distribution of all glaciers on Earth. Nat. Geosci., 12, 168–173, https://doi.org/10.1038/s41561-019-0300-3.
Fekete, B. M., C. J. Vörösmarty, and W. Grabs, 2002: High-resolution fields of global runoff combining observed river discharge and simulated water balances. Global Biogeochem. Cycles, 16, 1042, https://doi.org/10.1029/1999GB001254.
Ferreira, A. P., R. Nieto, and L. Gimeno, 2019: Completeness of radiosonde humidity observations based on the Integrated Global Radiosonde Archive. Earth Syst. Sci. Data, 11, 603–627, https://doi.org/10.5194/essd-11-603-2019.
Ferreira, V. G., and Z. Asiah, 2016: An investigation on the closure of the water budget methods over Volta basin using multi-satellite data. International Association of Geodesy Symposia, Vol. 144, Springer Verlag, 171–178.
Fisher, J. B., and Coauthors, 2017: The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources. Water Resour. Res., 53, 2618–2626, https://doi.org/10.1002/2016WR020175.
Flörke, M., E. Kynast, I. Bärlund, S. Eisner, F. Wimmer, and J. Alcamo, 2013: Domestic and industrial water uses of the past 60 years as a mirror of socio-economic development: A global simulation study. Global Environ. Change, 23, 144–156, https://doi.org/10.1016/j.gloenvcha.2012.10.018.
Foley, J. A., and Coauthors, 2011: Solutions for a cultivated planet. Nature, 478, 337–342, https://doi.org/10.1038/nature10452.
Ford, T. W., E. Harris, and S. M. Quiring, 2014: Estimating root zone soil moisture using near-surface observations from SMOS. Hydrol. Earth Syst. Sci., 18, 139–154, https://doi.org/10.5194/hess-18-139-2014.
Foster, S., J. Chilton, G. J. Nijsten, and A. Richts, 2013: Groundwater—A global focus on the “local resource.” Curr. Opin. Environ. Sustain., 5, 685–695, https://doi.org/10.1016/j.cosust.2013.10.010.
Fowler, H. J., and Coauthors, 2021: Anthropogenic intensification of short-duration rainfall extremes. Nat. Rev. Earth Environ., 2, 107–122, https://doi.org/10.1038/s43017-020-00128-6.
Frederikse, T., and Coauthors, 2020: The causes of sea-level rise since 1900. Nature, 584, 393–397, https://doi.org/10.1038/s41586-020-2591-3.
Gao, H., C. Birkett, and D. P. Lettenmaier, 2012: Global monitoring of large reservoir storage from satellite remote sensing. Water Resour. Res., 48, W09504, https://doi.org/10.1029/2012WR012063.
Gardner, A. S., and Coauthors, 2013: A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science, 340, 852–857, https://doi.org/10.1126/science.1234532.
Gärtner-Roer, I., K. Naegeli, M. Huss, T. Knecht, H. Machguth, and M. Zemp, 2014: A database of worldwide glacier thickness observations. Global Planet. Change, 122, 330–344, https://doi.org/10.1016/j.gloplacha.2014.09.003.
GCOS, 2015: Status of the Global Observing System for Climate. WMO Rep., 353 pp., https://library.wmo.int/index.php?lvl=notice_display&id=18962.
GCOS, 2016: The Global Observing System for Climate: Implementation needs. WMO Rep., 235 pp., https://public.wmo.int/en/resources/library/global-observing-system-climate-implementation-needs.
Gedney, N., P. M. Cox, R. A. Betts, O. Boucher, C. Huntingford, and P. A. Stott, 2006: Detection of a direct carbon dioxide effect in continental river runoff records. Nature, 439, 835–838, https://doi.org/10.1038/nature04504.
Gentemann, C. L., and Coauthors, 2020: FluxSat: Measuring the ocean–atmosphere turbulent exchange of heat and moisture from space. Remote Sens., 12, 1796, https://doi.org/10.3390/rs12111796.
Ghiggi, G., V. Humphrey, S. I. Seneviratne, and L. Gudmundsson, 2019: GRUN: An observation-based global gridded runoff dataset from 1902 to 2014. Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019.
Gimeno, L., A. Drumond, R. Nieto, R. M. Trigo, and A. Stohl, 2010: On the origin of continental precipitation. Geophys. Res. Lett., 37, L13804, https://doi.org/10.1029/2010GL043712.
Gimeno, L., and Coauthors, 2012: Oceanic and terrestrial sources of continental precipitation. Rev. Geophys., 50, RG4003, https://doi.org/10.1029/2012RG000389.
Gleeson, T., K. M. Befus, S. Jasechko, E. Luijendijk, and M. B. Cardenas, 2016: The global volume and distribution of modern groundwater. Nat. Geosci., 9, 161–167, https://doi.org/10.1038/ngeo2590.
Gleick, P. H., 1996: Basic water requirements for human activities: Meeting basic needs. Water Int., 21, 83–92, https://doi.org/10.1080/02508069608686494.
GLIMS and NSIDC, 2005: GLIMS glacier database, version 1 (updated 2018). National Snow and Ice Data Center, accessed 11 August 2021, https://doi.org/DOI:10.7265/N5V98602.
Gonzalez, R. L., G. Liston, C. Chiu, and B. Notaros, 2019: Thesis consistency in the AMSR-E snow products: Groundwork for a coupled snowfall and SWE algorithm. M.S. thesis, Dept. of Atmospheric Science, Colorado State University, 60 pp., https://mountainscholar.org/handle/10217/199801.
Goulden, M. L., and R. C. Bales, 2014: Mountain runoff vulnerability to increased evapotranspiration with vegetation expansion. Proc. Natl. Acad. Sci. USA, 111, 14 071–14 075, https://doi.org/10.1073/pnas.1319316111.
Gruber, A., W. A. Dorigo, S. Zwieback, A. Xaver, and W. Wagner, 2013: Characterizing coarse-scale representativeness of in situ soil moisture measurements from the International Soil Moisture Network. Vadose Zone J., 12, 1–16, https://doi.org/10.2136/vzj2012.0170.
Gruber, A., T. Scanlon, R. van der Schalie, W. Wagner, and W. Dorigo, 2019: Evolution of the ESA CCI soil moisture climate data records and their underlying merging methodology. Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019.
Gutenstein, M., K. Fennig, M. Schröder, T. Trent, S. Bakan, J. B. Roberts, and F. R. Robertson, 2021: Intercomparison of freshwater fluxes over ocean and investigations into water budget closure. Hydrol. Earth Syst. Sci., 25, 121–146, https://doi.org/10.5194/hess-25-121-2021.
Haberkorn, A., 2019: European snow booklet. COST Doc., 363 pp., https://doi.org/10.16904/envidat.59.
Hamdi, R., and Coauthors, 2020: The state-of-the-art of urban climate change modeling and observations. Earth Syst. Environ., 4, 631–646, https://doi.org/10.1007/s41748-020-00193-3.
Harris, I., P. D. Jones, T. J. Osborn, and D. H. Lister, 2014: Updated high-resolution grids of monthly climatic observations—The CRU TS3.10 dataset. Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711.
Hegerl, G. C., and Coauthors, 2015: Challenges in quantifying changes in the global water cycle. Bull. Amer. Meteor. Soc., 96, 1097–1115, https://doi.org/10.1175/BAMS-D-13-00212.1.
Hegglin, M. I., and Coauthors, 2013: SPARC data initiative: Comparison of water vapor climatologies from international satellite limb sounders. J. Geophys. Res. Atmos., 118, 11 824–11 846, https://doi.org/10.1002/jgrd.50752.
Heginbottom, J. A., J. Brown, E. S. Melnikov, and O. J. Ferrians, Jr., 1993: Circum-Arctic map of permafrost and ground ice conditions. Proc. Sixth Int. Conf. on Permafrost, Beijing, China, Chinese Society of Glaciology and Geocryology, 1132–1136.
Held, I. M., and B. J. Soden, 2006: Robust responses of the hydrological cycle to global warming. J. Climate, 19, 5686–5699, https://doi.org/10.1175/JCLI3990.1.
Herold, M., and Coauthors, 2019: The role and need for space-based forest biomass-related measurements in environmental management and policy. Surv. Geophys., 40, 757–778, https://doi.org/10.1007/s10712-019-09510-6.
Hersbach, H., C. Peubey, A. Simmons, P. Berrisford, P. Poli, and D. Dee, 2015: ERA-20CM: A twentieth-century atmospheric model ensemble. Quart. J. Roy. Meteor. Soc., 141, 2350–2375, https://doi.org/10.1002/qj.2528.
Hersbach, H., and Coauthors, 2020: The ERA5 global reanalysis. Quart. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803.
Heudorfer, B., E. Haaf, K. Stahl, and R. Barthel, 2019: Index-based characterization and quantification of groundwater dynamics. Water Resour. Res., 55, 5575–5592, https://doi.org/10.1029/2018WR024418.
Hicks, F., and S. Beltaos, 2008: River ice. Hydrologic Processes, M.-k. Woo, Ed., Vol. 2, Cold Region Atmospheric and Hydrologic Studies. The Mackenzie GEWEX Experience, Springer, 281–305.
Hirschi, M., and S. I. Seneviratne, 2017: Basin-scale water-balance dataset (BSWB): An update. Earth Syst. Sci. Data, 9, 251–258, https://doi.org/10.5194/essd-9-251-2017.
Hollmann, R., and Coauthors, 2013: The ESA climate change initiative: Satellite data records for essential climate variables. Bull. Amer. Meteor. Soc., 94, 1541–1552, https://doi.org/10.1175/BAMS-D-11-00254.1.
Hosseini, M., and R. Kerachian, 2017: A data fusion-based methodology for optimal redesign of groundwater monitoring networks. J. Hydrol., 552, 267–282, https://doi.org/10.1016/j.jhydrol.2017.06.046.
Hou, A. Y., and Coauthors, 2014: The Global Precipitation Measurement mission. Bull. Amer. Meteor. Soc., 95, 701–722, https://doi.org/10.1175/BAMS-D-13-00164.1.
Huang, C., Y. Chen, S. Zhang, and J. Wu, 2018: Detecting, extracting, and monitoring surface water from space using optical sensors: A review. Rev. Geophys., 56, 333–360, https://doi.org/10.1029/2018RG000598.
Huss, M., 2011: Present and future contribution of glacier storage change to runoff from macroscale drainage basins in Europe. Water Resour. Res., 47, W07511, https://doi.org/10.1029/2010WR010299.
Huss, M., 2013: Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere, 7, 877–887, https://doi.org/10.5194/tc-7-877-2013.
Huss, M., and R. Hock, 2015: A new model for global glacier change and sea-level rise. Front. Earth Sci., 3, 54, https://doi.org/10.3389/feart.2015.00054.
Huuskonen, A., E. Saltikoff, and I. Holleman, 2014: The operational weather radar network in Europe. Bull. Amer. Meteor. Soc., 95, 897–907, https://doi.org/10.1175/BAMS-D-12-00216.1.
Idso, S. B., and A. J. Brazel, 1984: Rising atmospheric carbon dioxide concentrations may increase streamflow. Nature, 312, 51–53, https://doi.org/10.1038/312051a0.
IPCC, 2019: Special Report on the Ocean and Cryosphere in a Changing Climate. IPCC, 765 pp., www.ipcc.ch/srocc/.
Ishii, M., Y. Fukuda, S. Hirahara, S. Yasui, T. Suzuki, and K. Sato, 2017: Accuracy of global upper ocean heat content estimation expected from present observational data sets. SOLA, 13, 163–167, https://doi.org/10.2151/sola.2017-030.
Jackson, T. J., and T. J. Schmugge, 1991: Vegetation effects on the microwave emission of soils. Remote Sens. Environ., 36, 203–212, https://doi.org/10.1016/0034-4257(91)90057-D.
Jalilvand, E., M. Tajrishy, S. A. Ghazi Zadeh Hashemi, and L. Brocca, 2019: Quantification of irrigation water using remote sensing of soil moisture in a semi-arid region. Remote Sens. Environ., 231, 111226, https://doi.org/10.1016/j.rse.2019.111226.
Jones, D. B., S. Harrison, K. Anderson, and R. A. Betts, 2018: Mountain rock glaciers contain globally significant water stores. Sci. Rep., 8, 2834, https://doi.org/10.1038/s41598-018-21244-w.
Jones, D. B., S. Harrison, K. Anderson, R. A. Betts, S. Shannon, and R. A. Betts, 2021: Rock glaciers represent hidden water stores in the Himalaya. Sci. Total Environ., 145368, https://doi.org/10.1016/j.scitotenv.2021.145368, in press.
Josey, S. A., E. C. Kent, and P. K. Taylor, 1999: New insights into the ocean heat budget closure problem from analysis of the SOC air–sea flux climatology. J. Climate, 12, 2856–2880, https://doi.org/10.1175/1520-0442(1999)012<2856:NIITOH>2.0.CO;2.
Jung, M., and Coauthors, 2019: The FLUXCOM ensemble of global land-atmosphere energy fluxes. Sci. Data, 6, 74, https://doi.org/10.1038/s41597-019-0076-8.
Kaser, G., M. Großhauser, and B. Marzeion, 2010: Contribution potential of glaciers to water availability in different climate regimes. Proc. Natl. Acad. Sci. USA, 107, 20 223–20 227, https://doi.org/10.1073/pnas.1008162107.
Kelly, R. E., A. T. Chang, L. Tsang, and J. L. Foster, 2003: A prototype AMSR-E global snow area and snow depth algorithm. IEEE Trans. Geosci. Remote Sens., 41, 230–242, https://doi.org/10.1109/TGRS.2003.809118.
Kenway, S., A. Gregory, and J. McMahon, 2011: Urban water mass balance analysis. J. Ind. Ecol., 15, 693–706, https://doi.org/10.1111/j.1530-9290.2011.00357.x.
Kerr, Y. H., and Coauthors, 2012: The SMOS soil moisture retrieval algorithm. IEEE Trans. Geosci. Remote Sens., 50, 1384–1403, https://doi.org/10.1109/TGRS.2012.2184548.
Kidd, C., A. Becker, G. J. Huffman, C. L. Muller, P. Joe, G. Skofronick-Jackson, and D. B. Kirschbaum, 2017: So, how much of the Earth’s surface is covered by rain gauges? Bull. Amer. Meteor. Soc., 98, 69–78, https://doi.org/10.1175/BAMS-D-14-00283.1.
King, M. D., and Coauthors, 2020: Dynamic ice loss from the Greenland Ice Sheet driven by sustained glacier retreat. Commun. Earth Environ., 1, 1, https://doi.org/10.1038/s43247-020-0001-2.
Kinzel, P., and C. Legleiter, 2019: sUAS-based remote sensing of river discharge using thermal particle image velocimetry and bathymetric lidar. Remote Sens., 11, 2317, https://doi.org/10.3390/rs11192317.
Kittel, C. M. M., 2020: Satellite radar observations for hydrologic and hydrodynamic modelling. Ph.D. dissertation, Technical University of Denmark, 66 pp.
Konikow, L. F., 2011: Contribution of global groundwater depletion since 1900 to sea-level rise. Geophys. Res. Lett., 38, L17401, https://doi.org/10.1029/2011GL048604.
Konings, A. G., and M. Momen, 2018: Frequency-dependence of vegetation optical depth-derived isohydriciy estimates. Int. Geoscience and Remote Sensing Symp., Valencia, Spain, IEEE, 9045–9047, https://doi.org/10.1109/IGARSS.2018.8519441.
Kooperman, G. J., M. D. Fowler, F. M. Hoffman, C. D. Koven, K. Lindsay, M. S. Pritchard, A. L. S. Swann, and J. T. Randerson, 2018: Plant physiological responses to rising CO2 modify simulated daily runoff intensity with implications for global-scale flood risk assessment. Geophys. Res. Lett., 45, 12 457–12 466, https://doi.org/10.1029/2018GL079901.
Koppa, A., S. Alam, D. G. Miralles, and M. Gebremichael, 2021, Budyko-based long-term water and energy balance closure in global watersheds from Earth observations. Water Resour. Res., 57, e2020WR028658, https://doi.org/10.1029/2020WR028658.
Korzoun, V. I., and Coauthors, 1978: World Water Balance and Water Resources of the Earth. UNESCO Press, 663 pp.
Koutsoyiannis, D., 2020: Revisiting the global hydrological cycle: Is it intensifying? Hydrol. Earth Syst. Sci., 24, 3899–3932, https://doi.org/10.5194/hess-24-3899-2020.
Kumar, S. V., C. D. Peters-Lidard, J. A. Santanello, R. H. Reichle, C. S. Draper, R. D. Koster, G. Nearing, and M. F. Jasinski, 2015: Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes. Hydrol. Earth Syst. Sci., 19, 4463–4478, https://doi.org/10.5194/hess-19-4463-2015.
Landerer, F. W., J. O. Dickey, and A. Güntner, 2010: Terrestrial water budget of the Eurasian pan-Arctic from GRACE satellite measurements during 2003–2009. J. Geophys. Res., 115, D23115, https://doi.org/10.1029/2010JD014584.
Landwehr, S., N. O’Sullivan, and B. Ward, 2015: Direct flux measurements from mobile platforms at sea: Motion and airflow distortion corrections revisited. J. Atmos. Oceanic Technol., 32, 1163–1178, https://doi.org/10.1175/JTECH-D-14-00137.1.
Lawford, R. G., and Coauthors, 2004: Advancing global- and continental-scale hydrometeorology: Contributions of GEWEX hydrometeorology panel. Bull. Amer. Meteor. Soc., 85, 1917–1930, https://doi.org/10.1175/BAMS-85-12-1917.
Lemordant, L., and P. Gentine, 2019: Vegetation response to rising CO2 impacts extreme temperatures. Geophys. Res. Lett., 46, 1383–1392, https://doi.org/10.1029/2018GL080238.
Levitus, S., and Coauthors, 2012: World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010. Geophys. Res. Lett., 39, L10603, https://doi.org/10.1029/2012GL051106.
Li, B., and Coauthors, 2019: Global GRACE data assimilation for groundwater and drought monitoring: Advances and challenges. Water Resour. Res., 55, 7564–7586, https://doi.org/10.1029/2018WR024618.
Lievens, H., and Coauthors, 2019: Snow depth variability in the Northern Hemisphere mountains observed from space. Nat. Commun., 10, 4629, https://doi.org/10.1038/s41467-019-12566-y.
Liman, J., M. Schröder, K. Fennig, A. Andersson, and R. Hollmann, 2018: Uncertainty characterization of HOAPS 3.3 latent heat-flux-related parameters. Atmos. Meas. Tech., 11, 1793–1815, https://doi.org/10.5194/amt-11-1793-2018.
Liu, W., and Coauthors, 2018: Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets. Hydrol. Earth Syst. Sci., 22, 351–371, https://doi.org/10.5194/hess-22-351-2018.
Liu, W. T., K. B. Katsaros, and J. A. Businger, 1979: Bulk parameterization of air-sea exchanges of heat and water vapor including the molecular constraints at the interface. J. Atmos. Sci., 36, 1722–1735, https://doi.org/10.1175/1520-0469(1979)036<1722:BPOASE>2.0.CO;2.
Llovel, W., S. Purkey, B. Meyssignac, A. Blazquez, N. Kolodziejczyk, and J. Bamber, 2019: Global ocean freshening, ocean mass increase and global mean sea level rise over 2005–2015. Sci. Rep., 9, 17717, https://doi.org/10.1038/s41598-019-54239-2.
Looser, U., I. Dornblut, and T. de Couet, 2007: The Global Terrestrial Network for River Discharge (GTN-R): Real-time access to river discharge data on a global scale. GRDC Rep. 36, 66 pp.
Lopez, O., and Coauthors, 2020: Mapping groundwater abstractions from irrigated agriculture: Big data, inverse modeling and a satellite–model fusion approach. Hydrol. Earth Syst. Sci., 24, 5251–5277, https://doi.org/10.5194/hess-24-5251-2020.
Luck, M., M. Landis, and F. Gassert, 2015: Aqueduct water stress projections: Decadal projections of water supply and demand using CMIP5 GCMs. World Resources Institute Tech. Note, 20 pp.
Luijendijk, E., T. Gleeson, and N. Moosdorf, 2020: Fresh groundwater discharge insignificant for the world’s oceans but important for coastal ecosystems. Nat. Commun., 11, 1260, https://doi.org/10.1038/s41467-020-15064-8.
Luo, Z., Q. Shao, W. Wan, H. Li, X. Chen, S. Zhu, and X. Ding, 2021: A new method for assessing satellite-based hydrological data products using water budget closure. J. Hydrol., 594, 125927, https://doi.org/10.1016/j.jhydrol.2020.125927.
Makihara, Y., 1996: A method for improving radar estimates of precipitation by comparing data from radars and raingauges. J. Meteor. Soc. Japan, 74, 459–480, https://doi.org/10.2151/jmsj1965.74.4_459.
Mariotti, A., M. V. Struglia, N. Zeng, and K. M. Lau, 2002: The hydrological cycle in the Mediterranean region and implications for the water budget of the Mediterranean Sea. J. Climate, 15, 1674–1690, https://doi.org/10.1175/1520-0442(2002)015<1674:THCITM>2.0.CO;2.
Martens, B., and Coauthors, 2017: GLEAM v3: Satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017.
Martens, B., R. de Jeu, N. Verhoest, H. Schuurmans, J. Kleijer, and D. Miralles, 2018: Towards estimating land evaporation at field scales using GLEAM. Remote Sens., 10, 1720, https://doi.org/10.3390/rs10111720.
Marvel, K., B. I. Cook, C. J. W. Bonfils, P. J. Durack, J. E. Smerdon, and A. P. Williams, 2019: Twentieth-century hydroclimate changes consistent with human influence. Nature, 569, 59–65, https://doi.org/10.1038/s41586-019-1149-8.
Massari, C., and Coauthors, 2020: A daily 25 km short-latency rainfall product for data-scarce regions based on the integration of the Global Precipitation Measurement mission rainfall and multiple-satellite soil moisture products. Hydrol. Earth Syst. Sci., 24, 2687–2710, https://doi.org/10.5194/hess-24-2687-2020.
Masunaga, H., M. Schröder, F. A. Furuzawa, C. Kummerow, E. Rustemeier, and U. Schneider, 2019: Inter-product biases in global precipitation extremes. Environ. Res. Lett., 14, 125016, https://doi.org/10.1088/1748-9326/ab5da9.
McCabe, M. F., A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood, 2016: The GEWEX LandFlux project: Evaluation of model evaporation using tower-based and globally gridded forcing data. Geosci. Model Dev., 9, 283–305, https://doi.org/10.5194/gmd-9-283-2016.
McCabe, M. F., D. G. Miralles, T. R. H. Holmes, and J. B. Fisher, 2019: Advances in the remote sensing of terrestrial evaporation. Remote Sens., 11, 1138, https://doi.org/10.3390/rs11091138.
Milliman, J. D., and K. L. Farnsworth, 2011: River Discharge to the Coastal Ocean: A Global Synthesis. Cambridge University Press, 384 pp.
Miralles, D. G., R. A. M. De Jeu, J. H. Gash, T. R. H. Holmes, and A. J. Dolman, 2011: Magnitude and variability of land evaporation and its components at the global scale. Hydrol. Earth Syst. Sci., 15, 967–981, https://doi.org/10.5194/hess-15-967-2011.
Miralles, D. G., and Coauthors, 2016: The WACMOS-ET project—Part 2: Evaluation of global terrestrial evaporation data sets. Hydrol. Earth Syst. Sci., 20, 823–842, https://doi.org/10.5194/hess-20-823-2016.
Miralles, D. G., P. Gentine, S. I. Seneviratne, and A. J. Teuling, 2019: Land–atmospheric feedbacks during droughts and heatwaves: State of the science and current challenges. Ann. N. Y. Acad. Sci., 1436, 19–35, https://doi.org/10.1111/nyas.13912.
Mitchell, A. L., A. Rosenqvist, and B. Mora, 2017: Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD+. Carbon Balance Manage., 12, 9, https://doi.org/10.1186/s13021-017-0078-9.
Moesinger, L., W. Dorigo, R. de Jeu, R. van der Schalie, T. Scanlon, I. Teubner, and M. Forkel, 2020: The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA). Earth Syst. Sci. Data, 12, 177–196, https://doi.org/10.5194/essd-12-177-2020.
Mohan, C., A. W. Western, Y. Wei, and M. Saft, 2018: Predicting groundwater recharge for varying land cover and climate conditions—A global meta-study. Hydrol. Earth Syst. Sci., 22, 2689–2703, https://doi.org/10.5194/hess-22-2689-2018.
Moholdt, G., B. Wouters, and A. S. Gardner, 2012: Recent mass changes of glaciers in the Russian High Arctic. Geophys. Res. Lett., 39, L10502, https://doi.org/10.1029/2012GL051466.
Mokany, K., R. J. Raison, and A. S. Prokushkin, 2006: Critical analysis of root: Shoot ratios in terrestrial biomes. Global Change Biol., 12, 84–96, https://doi.org/10.1111/j.1365-2486.2005.001043.x.
Moninger, W. R., S. G. Benjamin, B. D. Jamison, T. W. Schlatter, T. L. Smith, and E. J. Szoke, 2010: Evaluation of regional aircraft observations using TAMDAR. Wea. Forecasting, 25, 627–645, https://doi.org/10.1175/2009WAF2222321.1.
Moreira, A. A., A. L. Ruhoff, D. R. Roberti, V. de Arruda Souza, H. R. Rocha, and R. C. D. de Paiva, 2019: Assessment of terrestrial water balance using remote sensing data in South America. J. Hydrol., 575, 131–147, https://doi.org/10.1016/j.jhydrol.2019.05.021.
Morrow, R., and Coauthors, 2019: Global observations of fine-scale ocean surface topography with the Surface Water and Ocean Topography (SWOT) mission. Front. Mar. Sci., 6, 232, https://doi.org/10.3389/fmars.2019.00232.
Mortimer, C., L. Mudryk, C. Derksen, K. Luojus, R. Brown, R. Kelly, and M. Tedesco, 2020: Evaluation of long-term Northern Hemisphere snow water equivalent products. Cryosphere, 14, 1579–1594, https://doi.org/10.5194/tc-14-1579-2020.
Munier, S., and F. Aires, 2018: A new global method of satellite dataset merging and quality characterization constrained by the terrestrial water budget. Remote Sens. Environ., 205, 119–130, https://doi.org/10.1016/j.rse.2017.11.008.
Munier, S., F. Aires, S. Schlaffer, C. Prigent, F. Papa, P. Maisongrande, and M. Pan, 2014: Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi basin and closure correction model. J. Geophys. Res. Atmos., 119, 12 100–12 116, https://doi.org/10.1002/2014JD021953.
National Academies of Sciences, Engineering, and Medicine, 2016: Attribution of Extreme Weather Events in the Context of Climate Change. National Academies Press, 186 pp.
Ning, S., H. Ishidaira, and J. Wang, 2014: Statistical downscaling of grace-derived terrestrial water storage using satellite and GLDAS products. Ann. J. Hydraul. Eng., 70, 133–138, https://doi.org/10.2208/jscejhe.70.I_133.
Oki, T., 1999: The global water cycle. Global Energy and Water Cycles, K. A. Browning and R. J. Gurney, Eds., Cambridge University Press, 10–27.
Oki, T., and S. Kanae, 2006: Global hydrological cycles and world water resources. Science, 313, 1068–1072, https://doi.org/10.1126/science.1128845.
Padrón, R. S., and Coauthors, 2020: Observed changes in dry-season water availability attributed to human-induced climate change. Nat. Geosci., 13, 477–481, https://doi.org/10.1038/s41561-020-0594-1.
Pan, M., and E. F. Wood, 2006: Data assimilation for estimating the terrestrial water budget using a constrained ensemble Kalman filter. J. Hydrometeor., 7, 534–547, https://doi.org/10.1175/JHM495.1.
Pan, M., A. K. Sahoo, T. J. Troy, R. K. Vinukollu, J. Sheffield, and A. E. F. Wood, 2012: Multisource estimation of long-term terrestrial water budget for major global river basins. J. Climate, 25, 3191–3206, https://doi.org/10.1175/JCLI-D-11-00300.1.
Pan, S., and Coauthors, 2020: Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling. Hydrol. Earth Syst. Sci., 24, 1485–1509, https://doi.org/10.5194/hess-24-1485-2020.
Paul, F., and Coauthors, 2009: Recommendations for the compilation of glacier inventory data from digital sources. Ann. Glaciol., 50, 119–126, https://doi.org/10.3189/172756410790595778.
Pellarin, T., and Coauthors, 2020: The Precipitation Inferred from Soil Moisture (PrISM) near real-time rainfall product: Evaluation and comparison. Remote Sens., 12, 481, https://doi.org/10.3390/rs12030481.
Pellet, V., F. Aires, S. Munier, D. Fernández Prieto, G. Jordá, W. A. Dorigo, J. Polcher, and L. Brocca, 2019: Integrating multiple satellite observations into a coherent dataset to monitor the full water cycle—Application to the Mediterranean region. Hydrol. Earth Syst. Sci., 23, 465–491, https://doi.org/10.5194/hess-23-465-2019.
Pellet, V., F. Aires, F. Papa, S. Munier, and B. Decharme, 2020: Long-term total water storage change from a satellite water cycle reconstruction over large southern Asian basins. Hydrol. Earth Syst. Sci., 24, 3033–3055, https://doi.org/10.5194/hess-24-3033-2020.
Peña-Arancibia, J. L., L. A. Bruijnzeel, M. Mulligan, and A. I. J. M. van Dijk, 2019: Forests as ‘sponges’ and ‘pumps’: Assessing the impact of deforestation on dry-season flows across the tropics. J. Hydrol., 574, 946–963, https://doi.org/10.1016/j.jhydrol.2019.04.064.
Penman, J., and Coauthors, 2003: Good practice guidance for land use, land-use change and forestry. IPCC Rep., 590 pp.
Petersen, W., and Coauthors, 2016: GPM level 1 science requirements: Science and performance viewed from the ground. NASA Doc., 1 p., https://ntrs.nasa.gov/citations/20160012025.
Petzold, A., and Coauthors, 2015: Global-scale atmosphere monitoring by in-service aircraft—Current achievements and future prospects of the European Research Infrastructure IAGOS. Tellus, 67B, 28452, https://doi.org/10.3402/tellusb.v67.28452.
Pfahl, S., P. A. O’Gorman, and E. M. Fischer, 2017: Understanding the regional pattern of projected future changes in extreme precipitation. Nat. Climate Change, 7, 423–427, https://doi.org/10.1038/nclimate3287.
Popp, T., and Coauthors, 2020: Consistency of satellite climate data records for Earth system monitoring. Bull. Amer. Meteor. Soc., 101, E1948–E1971, https://doi.org/10.1175/BAMS-D-19-0127.1.
Preimesberger, W., T. Scanlon, C.-H. Su, A. Gruber, and W. Dorigo, 2020: Homogenization of structural breaks in the global ESA CCI soil moisture multisatellite climate data record. IEEE Trans. Geosci. Remote Sens., 59, 2845–2862, https://doi.org/10.1109/TGRS.2020.3012896.
Pritchard, H. D., 2019: Asia’s shrinking glaciers protect large populations from drought stress. Nature, 569, 649–654, https://doi.org/10.1038/s41586-019-1240-1.
Prytherch, J., E. C. Kent, S. Fangohr, and D. I. Berry, 2015: A comparison of SSM/I-derived global marine surface-specific humidity datasets. Int. J. Climatol., 35, 2359–2381, https://doi.org/10.1002/joc.4150.
Pulliainen, J., 2006: Mapping of snow water equivalent and snow depth in boreal and sub-Arctic zones by assimilating space-borne microwave radiometer data and ground-based observations. Remote Sens. Environ., 101, 257–269, https://doi.org/10.1016/j.rse.2006.01.002.
Pulliainen, J., and Coauthors, 2020: Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018. Nature, 581, 294–298, https://doi.org/10.1038/s41586-020-2258-0.
Raj, R. P., and Coauthors, 2020: Arctic sea level budget assessment during the GRACE/Argo time period. Remote Sens., 12, 2837, https://doi.org/10.3390/rs12172837.
Rast, M., J. Johannessen, and W. Mauser, 2014: Review of understanding of Earth’s hydrological cycle: Observations, theory and modelling. Surv. Geophys., 35, 491–513, https://doi.org/10.1007/s10712-014-9279-x.
Reinecke, R., L. Foglia, S. Mehl, T. Trautmann, D. Cáceres, and P. Döll, 2019: Challenges in developing a global gradient-based groundwater model (G3M v1.0) for the integration into a global hydrological model. Geosci. Model Dev., 12, 2401–2418, https://doi.org/10.5194/gmd-12-2401-2019.
Reul, N., and Coauthors, 2020: Sea surface salinity estimates from spaceborne L-band radiometers: An overview of the first decade of observation (2010–2019). Remote Sens. Environ., 242, 111769, https://doi.org/10.1016/j.rse.2020.111769.
RGI, 2017: Randolph Glacier Inventory 6.0. RGI Tech. Rep., 71 pp., https://doi.org/10.7265/n5-rgi-60.
Robertson, F. R., and Coauthors, 2020: Uncertainties in ocean latent heat flux variations over recent decades in satellite-based estimates and reduced observation reanalyses. J. Climate, 33, 8415–8437, https://doi.org/10.1175/JCLI-D-19-0954.1.
Robock, A., K. Y. Vinnikov, G. Srinivasan, J. K. Entin, S. E. Hollinger, N. A. Speranskaya, S. Liu, and A. Namkhai, 2000: The Global Soil Moisture Data Bank. Bull. Amer. Meteor. Soc., 81, 1281–1299, https://doi.org/10.1175/1520-0477(2000)081<1281:TGSMDB>2.3.CO;2.
Rodell, M., J. S. Famiglietti, J. Chen, S. I. Seneviratne, P. Viterbo, S. Holl, and C. R. Wilson, 2004: Basin scale estimates of evapotranspiration using GRACE and other observations. Geophys. Res. Lett., 31, L20504, https://doi.org/10.1029/2004GL020873.
Rodell, M., E. B. McWilliams, J. S. Famiglietti, H. K. Beaudoing, and J. Nigro, 2011: Estimating evapotranspiration using an observation based terrestrial water budget. Hydrol. Processes, 25, 4082–4092, https://doi.org/10.1002/hyp.8369.
Rodell, M., and Coauthors, 2015: The observed state of the water cycle in the early twenty-first century. J. Climate, 28, 8289–8318, https://doi.org/10.1175/JCLI-D-14-00555.1.
Rodell, M., J. S. Famiglietti, D. N. Wiese, J. T. Reager, H. K. Beaudoing, F. W. Landerer, and M. H. Lo, 2018: Emerging trends in global freshwater availability. Nature, 557, 651–659, https://doi.org/10.1038/s41586-018-0123-1.
Sadat-Noori, M., I. R. Santos, C. J. Sanders, L. M. Sanders, and D. T. Maher, 2015: Groundwater discharge into an estuary using spatially distributed radon time series and radium isotopes. J. Hydrol., 528, 703–719, https://doi.org/10.1016/j.jhydrol.2015.06.056.
Sahely, H. R., S. Dudding, and C. A. Kennedy, 2003: Estimating the urban metabolism of Canadian cities: Greater Toronto area case study. Can. J. Civ. Eng., 30, 468–483, https://doi.org/10.1139/l02-105.
Sahoo, A. K., M. Pan, T. J. Troy, R. K. Vinukollu, J. Sheffield, and E. F. Wood, 2011: Reconciling the global terrestrial water budget using satellite remote sensing. Remote Sens. Environ., 115, 1850–1865, https://doi.org/10.1016/j.rse.2011.03.009.
Saltikoff, E., and Coauthors, 2019: An overview of using weather radar for climatological studies successes, challenges, and potential. Bull. Amer. Meteor. Soc., 100, 1739–1752, https://doi.org/10.1175/BAMS-D-18-0166.1.
Schmied, H. M., and Coauthors, 2021: 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-14-1037-2021.
Schmitt, R. W., 1995: The ocean component of the global water cycle. Rev. Geophys., 33, 1395–1409, https://doi.org/10.1029/95RG00184.
Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, M. Ziese, and B. Rudolf, 2014: GPCC’s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor. Appl. Climatol., 115, 15–40, https://doi.org/10.1007/s00704-013-0860-x.
Schneider, U., P. Finger, A. Meyer-Christoffer, E. Rustemeier, M. Ziese, and A. Becker, 2017: Evaluating the hydrological cycle over land using the newly-corrected precipitation climatology from the Global Precipitation Climatology Centre (GPCC). Atmosphere, 8, 52, https://doi.org/10.3390/atmos8030052.
Schröder, M., M. Lockhoff, J. M. Forsythe, H. Q. Cronk, T. H. Vonder Haar, and R. Bennartz, 2016: The GEWEX water vapor assessment: Results from intercomparison, trend, and homogeneity analysis of total column water vapor. J. Appl. Meteor. Climatol., 55, 1633–1649, https://doi.org/10.1175/JAMC-D-15-0304.1.
Seneviratne, S. I., T. Corti, E. L. Davin, M. Hirschi, E. B. Jaeger, I. Lehner, B. Orlowsky, and A. J. Teuling, 2010: Investigating soil moisture-climate interactions in a changing climate: A review. Earth-Sci. Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004.
Sheffield, J., C. R. Ferguson, T. J. Troy, E. F. Wood, and M. F. McCabe, 2009: Closing the terrestrial water budget from satellite remote sensing. Geophys. Res. Lett., 36, L07403, https://doi.org/10.1029/2009GL037338.
Shepherd, A., and Coauthors, 2018: Mass balance of the Antarctic ice sheet from 1992 to 2017. Nature, 558, 219–222, https://doi.org/10.1038/s41586-018-0179-y.
Shepherd, A., and Coauthors, 2020: Mass balance of the Greenland ice sheet from 1992 to 2018. Nature, 579, 233–239, https://doi.org/10.1038/s41586-019-1855-2.
Shige, S., and C. D. Kummerow, 2016: Precipitation-top heights of heavy orographic rainfall in the Asian monsoon region. J. Atmos. Sci., 73, 3009–3024, https://doi.org/10.1175/JAS-D-15-0271.1.
Shiklomanov, I. A., 2000: Appraisal and assessment of world water resources. Water Int., 25, 11–32, https://doi.org/10.1080/02508060008686794.
Shiklomanov, I. A., 2008: Water Resources of Russia and Their Use. GGI, 600 pp.
Shiklomanov, I. A., and J. Rodda, 2004: World water resources at the beginning of the twenty-first century. Choice Rev. Online, 41, 4063–4063, https://doi.org/10.5860/CHOICE.41-4063.
Shiklomanov, I. A., S. Déry, M. Tretiakov, D. Yang, D. Magritsky, A. Georgiadi, and W.