Terrestrial contribution to the heterogeneity in hydrological changes under global warming

Water Resources Research

Volumn 52, Issue 4, 2016, Pages 3127-3142

  Kumar, Sanjiv ^a,b   Zwiers, Francis ^a   Dirmeyer, Paul A ^c   Lawrence, David M ^d   Shrestha, Rajesh ^a   Werner, Arelia T ^a  

^a UNIVERSITY OF VICTORIA   (Canada)

^b NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^c CENTER FOR OCEAN LAND ATMOSPHERE STUDIES   (United States)

^d NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

Budyko framework; global warming; hydrological change; land surface; potential evapotranspiration

Indexed keywords

CATCHMENTS; EVAPOTRANSPIRATION; GLOBAL WARMING; RUNOFF;

BUDYKO FRAMEWORK; COUPLED MODEL INTERCOMPARISON PROJECT; EFFICIENCY PARAMETERS; EVAPORATIVE DEMANDS; HYDROLOGICAL CHANGES; HYDROLOGICAL CYCLES; LAND SURFACE; POTENTIAL EVAPOTRANSPIRATION;

CLIMATE MODELS;

CATCHMENT; CLIMATE MODELING; EVAPOTRANSPIRATION; GLOBAL WARMING; HETEROGENEITY; HYDROLOGICAL CYCLE; LAND SURFACE; PRECIPITATION (CLIMATOLOGY); RUNOFF; STREAMFLOW;

NORTH AMERICA;

EID: 84971310913     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/2016WR018607     Document Type: Article

References (70)

1. Alkama, R.; L. Marchand, A. Ribes, and, B. Decharme, (2013), Detection of global runoff changes: Results from observations and CMIP5 experiments, Hydrol. Earth Syst. Sci.; 17 (7), 2967-2979, doi: 10.5194/hess-17-2967-2013.
2. Allan, R. P.; (2014), Climate change: Dichotomy of drought and deluge, Nat. Geosci.; 7 (10), 700-701, doi: 10.1038/ngeo2243.
3. Allen, R. G.; M. Smith, L. S. Pereira, and, A. Perrier, (1994), An update for the calculation of reference evapotranspiration, ICID Bull.; 43, 35-92.
4. Basu, N. B.; P. S. C. Rao, H. E. Winzeler, S. Kumar, P. Owens, and, V. Merwade, (2010), Parsimonious modeling of hydrologic responses in engineered watersheds: Structural heterogeneity versus functional homogeneity, Water Resour. Res.; 46, W04501, doi: 10.1029/2009WR007803.
5. Berghuijs, W. R.; R. A. Woods, and, M. Hrachowitz, (2014), A precipitation shift from snow towards rain leads to a decrease in streamflow, Nat. Clim. Change, 4 (7), 583-586, doi: 10.1038/nclimate2246.
6. Betts, R. A.; et al.; (2007), Projected increase in continental runoff due to plant responses to increasing carbon dioxide, Nature, 448 (7157), 1037-1041, doi: 10.1038/nature06045.
7. Budyko, M. I.; (1958), The Heat Balance of the Earth's Surface, US Dep. of Commer.; Washington, D. C.
8. Cao, L.; G. Bala, K. Caldeira, R. Nemani, and, G. Ban-Weiss, (2010), Importance of carbon dioxide physiological forcing to future climate change, Proc. Natl. Acad. Sci. U. S. A.; 107 (21), 9513-9518, doi: 10.1073/pnas.0913000107.
9. Chadwick, R.; I. Boutle, and, G. Martin, (2012), Spatial patterns of precipitation change in CMIP5: Why the rich do not get richer in the tropics, J. Clim.; 26 (11), 3803-3822, doi: 10.1175/JCLI-D-12-00543.1.
10. Chen, J.; F. P. Brissette, D. Chaumont, and, M. Braun, (2013), Performance and uncertainty evaluation of empirical downscaling methods in quantifying the climate change impacts on hydrology over two North American river basins, J. Hydrol.; 479, 200-214, doi: 10.1016/j.jhydrol.2012.11.062.
11. Chou, C.; and, J. D. Neelin, (2004), Mechanisms of global warming impacts on regional tropical precipitation, J. Clim.; 17 (13), 2688-2701, doi: 10.1175/1520-0442(2004)017<2688:MOGWIO>2.0.CO;2.
12. Chow, V.; et al.; (1988), Applied Hydrology, pp. 80-93, McGraw-Hill, N. Y.
13. Dahlin, K. M.; R. A. Fisher, and, P. J. Lawrence, (2015), Environmental drivers of drought deciduous phenology in the community land model, Biogeosci. Discuss.; 12, 5803-5839.
14. Dai, A.; T. Qian, K. E. Trenberth, and, J. D. Milliman, (2009), Changes in continental freshwater discharge from 1948 to 2004, J. Clim.; 22 (10), 2773-2792, doi: 10.1175/2008JCLI2592.1.
15. Daly, C.; M. Halbleib, J. I. Smith, W. P. Gibson, M. K. Doggett, G. H. Taylor, J. Curtis, and, P. P. Pasteris, (2008), Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States, Int. J. Climatol.; 28 (15), 2031-2064, doi: 10.1002/joc.1688.
16. Deser, C.; R. Knutti, S. Solomon, and, A. S. Phillips, (2012), Communication of the role of natural variability in future North American climate, Nat. Clim. Change, 2 (11), 775-779, doi: 10.1038/nclimate1562.
17. Dirmeyer, P. A.; S. Kumar, M. J. Fennessy, E. L. Altshuler, T. DelSole, Z. Guo, B. A. Cash, and, D. Straus, (2013), Model estimates of land-driven predictability in a changing climate from CCSM4, J. Clim.; 26 (21), 8495-8512, doi: 10.1175/JCLI-D-13-00029.1.
18. Flato, G.; et al.; (2013), 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, edited by, T. F. Stocker, et al.; pp. 741-866, Cambridge Univ. Press, Cambridge, U. K.
19. Fu, Q.; and, S. Feng, (2014), Responses of terrestrial aridity to global warming, J. Geophys. Res. Atmos.; 119, 7863-7875, doi: 10.1002/2014JD021608.
20. Greve, P.; and, S. I. Seneviratne, (2015), Assessment of future changes in water availability and aridity, Geophys. Res. Lett.; 42, 5493-5499, doi: 10.1002/2015GL064127.
21. Greve, P.; B. Orlowsky, B. Mueller, J. Sheffield, M. Reichstein, and, S. I. Seneviratne, (2014), Global assessment of trends in wetting and drying over land, Nat. Geosci.; 7 (10), 716-721, doi: 10.1038/ngeo2247.
22. Greve, P.; L. Gudmundsson, B. Orlowsky, and, S. I. Seneviratne, (2015), Introducing a probabilistic Budyko framework, Geophys. Res. Lett.; 42, 2261-2269, doi: 10.1002/2015GL063449.
23. Groisman, P. Y.; and, D. R. Legates, (1994), The accuracy of United States precipitation data, Bull. Am. Meteorol. Soc.; 75 (2), 215-227, doi: 10.1175/1520-0477(1994)075<0215:TAOUSP>2.0.CO;2.
24. Haddeland, I.; et al.; (2011), Multimodel estimate of the global terrestrial water balance: Setup and first results, J. Hydrometeorol.; 12 (5), 869-884, doi: 10.1175/2011JHM1324.1.
25. Hagemann, S.; C. Chen, J. O. Haerter, J. Heinke, D. Gerten, and, C. Piani, (2011), Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models, J. Hydrometeorol.; 12 (4), 556-578, doi: 10.1175/2011JHM1336.1.
26. 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 (3), 623-642, doi: 10.1002/joc.3711.
27. Held, I. M.; and, B. J. Soden, (2006), Robust responses of the hydrological cycle to global warming, J. Clim.; 19 (21), 5686-5699, doi: 10.1175/JCLI3990.1.
28. Herring, S. C.; M. P. Hoerling, T. C. Peterson, and, P. A. Stott, (Eds.) (2014), Explaining extreme events of 2013 from a climate perspective, Bull. Am. Meteorol. Soc.; 95 (9), supplement, 1-96.
29. Jiang, C.; L. Xiong, D. Wang, P. Liu, S. Guo, and, C.-Y. Xu, (2015), Separating the impacts of climate change and human activities on runoff using the Budyko-type equations with time-varying parameters, J. Hydrol.; 522, 326-338.
30. Jimenez Cisneros, B. E.; T. Oki, N. W. Arnell, G. Benito, J. G. Cogley, P. Doll, T. Jiang, and, S. S. Mwakalila, (2014), Freshwater resources, in Climate Change 2014: Impacts, Adaptation and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by, C. B. Field, et al.; pp. 229-269, Cambridge Univ. Press, Cambridge.
31. Jones, G. S.; P. A. Stott, and, N. Christidis, (2013), Attribution of observed historical near-surface temperature variations to anthropogenic and natural causes using CMIP5 simulations, J. Geophys. Res. Atmos.; 118, 4001-4024, doi: 10.1002/jgrd.50239.
32. Koster, R.; (2014), " Efficiency Space": A framework for evaluating joint evaporation and runoff behavior, Bull. Am. Meteorol. Soc.; 96 (3), 393-396, doi: 10.1175/BAMS-D-14-00056.1.
33. Koster, R. D.; and, M. J. Suarez, (1999), A simple framework for examining the interannual variability of land surface moisture fluxes, J. Clim.; 12 (7), 1911-1917, doi: 10.1175/1520-0442(1999)012<1911:ASFFET>2.0.CO;2.
34. Kumar, S.; V. Merwade, J. Kam, and, K. Thurner, (2009), Streamflow trends in Indiana: Effects of long term persistence, precipitation and subsurface drains, J. Hydrol.; 374 (1-2), 171-183, doi: 10.1016/j.jhydrol.2009.06.012.
35. Kumar, S.; V. Merwade, J. L. Kinter III, and, D. Niyogi, (2013a), Evaluation of temperature and precipitation trends and long-term persistence in CMIP5 twentieth-century climate simulations, J. Clim.; 26, 4168-4185.
36. Kumar, S.; P. A. Dirmeyer, V. Merwade, T. DelSole, J. M. Adams, and, D. Niyogi, (2013b), Land use/cover change impacts in CMIP5 climate simulations: A new methodology and 21st century challenges, J. Geophys. Res. Atmos.; 118, 6337-6353, doi: 10.1002/jgrd.50463.
37. Kumar, S.; R. P. Allan, F. Zwiers, D. M. Lawrence, and, P. A. Dirmeyer, (2015), Revisiting trends in wetness and dryness in the presence of internal climate variability and water limitations over land, Geophys. Res. Lett.; 42, 10,867-10,875, doi: 10.1002/2015GL066858.
38. Lawrence, D. M.; et al.; (2011), Parameterization improvements and functional and structural advances in version 4 of the Community Land Model, J. Adv. Model. Earth Syst.; 3, M03001, doi: 10.1029/2011MS000045.
39. Li, D.; M. Pan, Z. Cong, L. Zhang, and, E. Wood, (2013), Vegetation control on water and energy balance within the Budyko framework, Water Resour. Res.; 49, 969-976, doi: 10.1002/wrcr.20107.
40. Manabe, S.; (1969), Climate and the ocean circulation1, Mon. Weather Rev.; 97 (11), 739-774, doi: 10.1175/1520-0493(1969)097<0739:CATOC>2.3.CO;2.
41. Mekis, É.; and, L. A. Vincent, (2011), An overview of the second generation adjusted daily precipitation dataset for trend analysis in Canada, Atmos. Ocean, 49 (2), 163-177, doi: 10.1080/07055900.2011.583910.
42. Milly, P. C. D.; (1994), Climate, soil water storage, and the average annual water balance, Water Resour. Res.; 30 (7), 2143-2156, doi: 10.1029/94WR00586.
43. Milly, P. C. D.; K. A. Dunne, and, A. V. Vecchia, (2005), Global pattern of trends in streamflow and water availability in a changing climate, Nature, 438 (7066), 347-350, doi: 10.1038/nature04312.
44. Oleson, K. W.; et al.; (2010), Technical description of version 4.0 of the Community Land Model (CLM), NCAR Tech. Note NCAR/TN-478+STR, National Center for Atmospheric Research, Boulder, Colo.
45. Roderick, M. L.; and, G. D. Farquhar, (2011), A simple framework for relating variations in runoff to variations in climatic conditions and catchment properties, Water Resour. Res.; 47, W00G07, doi: 10.1029/2010WR009826.
46. Roderick, M. L.; F. Sun, W. H. Lim, and, G. D. Farquhar, (2014), A general framework for understanding the response of the water cycle to global warming over land and ocean, Hydrol. Earth Syst. Sci.; 18 (5), 1575-1589, doi: 10.5194/hess-18-1575-2014.
47. 2, Water Resour. Res.; 51, 5450-5463, doi: 10.1002/2015WR017031.
48. Sagarika, S.; A. Kalra, and, S. Ahmad, (2014), Evaluating the effect of persistence on long-term trends and analyzing step changes in streamflows of the continental United States, J. Hydrol.; 517, 36-53, doi: 10.1016/j.jhydrol.2014.05.002.
49. Sankarasubramanian, A.; and, R. M. Vogel, (2002), Annual hydroclimatology of the United States, Water Resour. Res.; 38 (6), doi: 10.1029/2001WR000619.
50. Sankarasubramanian, A.; R. M. Vogel, and, J. F. Limbrunner, (2001), Climate elasticity of streamflow in the United States, Water Resour. Res.; 37 (6), 1771-1781.
51. Santer, B. D.; et al.; (2007), Identification of human-induced changes in atmospheric moisture content, Proc. Natl. Acad. Sci. U. S. A.; 104 (39), 15,248-15,253, doi: 10.1073/pnas.0702872104.
52. Seager, R.; N. Naik, and, G. A. Vecchi, (2010), Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming, J. Clim.; 23 (17), 4651-4668, doi: 10.1175/2010JCLI3655.1.
53. Seager, R.; M. Hoerling, S. Schubert, H. Wang, B. Lyon, A. Kumar, J. Nakamura, and, N. Henderson, (2015), Causes of the 2011-14 California drought, J. Clim.; 28, 6997-7024, doi: 10.1175/JCLI-D-14-00860.1.
54. Scheff, J.; and, D. M. W. Frierson, (2014), Scaling potential evapotranspiration with greenhouse warming, J. Clim.; 27, 1539-1558, doi: 10.1175/JCLI-D-13-00233.1.
55. Schaake, J. C,. (1990), From climate to flow, in Climate Change and U.S. Water Resources, edited by P. E. Waggoner, pp. 177-206, John Wiley.
56. Sheffield, J.; E. F. Wood, and, M. L. Roderick, (2012), Little change in global drought over the past 60 years, Nature, 491 (7424), 435-438, doi: 10.1038/nature11575.
57. Sheffield, J.; et al.; (2013), North American climate in CMIP5 experiments. Part I: Evaluation of historical simulations of continental and regional climatology, J. Clim.; 26, 9209-9245.
58. Shuttleworth, W. J.; (2012), Daily estimates of evaporation, in Terrestrial Hydrometeorology, pp. 334-358, John Wiley, Chichester, U. K.; doi: 10.1002/9781119951933.ch23.
59. Stahl, K.; H. Hisdal, J. Hannaford, L. M. Tallaksen, H. A. J. van Lanen, E. Sauquet, S. Demuth, M. Fendekova, and, J. Jódar, (2010), Streamflow trends in Europe: Evidence from a dataset of near-natural catchments, Hydrol. Earth Syst. Sci.; 14 (12), 2367-2382, doi: 10.5194/hess-14-2367-2010.
60. Taylor, K. E.; R. J. Stouffer, and, G. A. Meehl, (2011), An overview of CMIP5 and the experiment design, Bull. Am. Meteorol. Soc.; 93 (4), 485-498, doi: 10.1175/BAMS-D-11-00094.1.
61. Trenberth, K. E.; A. Dai, G. van der Schrier, P. D. Jones, J. Barichivich, K. R. Briffa, and, J. Sheffield, (2014), Global warming and changes in drought, Nat. Clim. Change, 4 (1), 17-22, doi: 10.1038/nclimate2067.
62. Vano, J. A.; T. Das, and, D. Lettenmaier, (2012), Hydrologic sensitivity of Colorado River runoff to changes in precipitation and temperature, J. Hydrometeorol.; 13, 932-949.
63. Vano, J. A.; et al.; (2013), Understanding uncertainties in future Colorado River streamflow, Bull. Am. Meteorol. Soc.; 95 (1), 59-78, doi: 10.1175/BAMS-D-12-00228.1.
64. Wan, H.; X. Zhang, F. Zwiers, and, S.-K. Min, (2014), Attributing northern high-latitude precipitation change over the period 1966-2005 to human influence, Clim. Dyn.; 45, 1713-1726, doi: 10.1007/s00382-014-2423-y.
65. Zhang, D.; Z. Cong, G. Ni, D. Yang, and, S. Hu, (2015), Effects of snow ratio on annual runoff within the Budyko framework, Hydrol. Earth Syst. Sci.; 19 (4), 1977-1992, doi: 10.5194/hess-19-1977-2015.
66. Zhang, J.; et al.; (2015b), Responses of crop water use efficiency to climate change and agronomic measures in the semiarid area of Northern China, PLoS ONE, 10 (9), e0137409, doi: 10.1371/journal.pone.0137409.
67. Zhang, L.; W. R. Dawes, and, G. R. Walker, (2001), Response of mean annual evapotranspiration to vegetation changes at catchment scale, Water Resour. Res.; 37 (3), 701-708, doi: 10.1029/2000WR900325.
68. Zhang, L.; K. Hickel, W. R. Dawes, F. H. S. Chiew, A. W. Western, and, P. R. Briggs, (2004), A rational function approach for estimating mean annual evapotranspiration, Water Resour. Res.; 40, W02502, doi: 10.1029/2003WR002710.
69. Zhang, L.; N. Potter, K. Hickel, Y. Zhang, and, Q. Shao, (2008), Water balance modeling over variable time scales based on the Budyko framework-Model development and testing, J. Hydrol.; 360 (1-4), 117-131, doi: 10.1016/j.jhydrol.2008.07.021.
70. Zhang, X.; F. W. Zwiers, G. C. Hegerl, F. H. Lambert, N. P. Gillett, S. Solomon, P. A. Stott, and, T. Nozawa, (2007), Detection of human influence on twentieth-century precipitation trends, Nature, 448 (7152), 461-465, doi: 10.1038/nature06025.