The resolution dependence of contiguous U.S. precipitation extremes in response to CO2 forcing

Journal of Climate

Volumn 29, Issue 22, 2016, Pages 7991-8012

  van der Wiel, Karin ^a,b   Kapnick, Sarah B ^b   Vecchi, Gabriel A ^b   Cooke, William F ^b,c   Delworth, Thomas L ^b   Jia, Liwei ^a,b   Murakami, Hiroyuki ^a,b   Underwood, Seth ^b   Zeng, Fanrong ^b  

^a PRINCETON UNIVERSITY   (United States)

^b NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^c UNIVERSITY CORPORATION FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

Climate change; Climate models; Climate sensitivity; Extreme events; Model evaluation performance; Precipitation

Indexed keywords

CARBON DIOXIDE; CLIMATE CHANGE; HURRICANES; PRECIPITATION (CHEMICAL); PRECIPITATION (METEOROLOGY); STORMS;

CLIMATE SENSITIVITY; COUPLED CLIMATE MODEL; EXTREME EVENTS; EXTREME PRECIPITATION; HIGHEST RESOLUTIONS; INTRINSIC VARIABILITIES; MODEL EVALUATION/PERFORMANCE; PRECIPITATION EXTREMES;

CLIMATE MODELS;

EID: 84994184268     PISSN: 08948755     EISSN: None     Source Type: Journal    
DOI: 10.1175/JCLI-D-16-0307.1     Document Type: Article

References (77)

1. Allen, M. R., and W. J. Ingram, 2002: Constraints on future changes in climate and the hydrologic cycle. Nature, 419, 224-232, doi:10.1038/nature01092.
2. Anderson, J. L., and Coauthors, 2004: The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations. J. Climate, 17, 4641-4673, doi:10.1175/JCLI-3223.1.
3. Barlow, M., S. Nigam, and E. Berbery, 2001: ENSO, Pacific decadal variability, and U.S. summertime precipitation, drought, and stream flow. J. Climate, 14, 2105-2128, doi:10.1175/1520-0442(2001)014<2105:EPDVAU>2.0.CO;2.
4. Bosilovich, M. G., and Coauthors, 2015: MERRA-2: Initial evaluation of the climate. NASA Tech. Rep. Series on Global Modeling and Data Assimilation 43, 139 pp. [Available online at https://gmao.gsfc.nasa.gov/pubs/tm/docs/Bosilovich803.pdf.]
5. Chen, C.-T., and T. Knutson, 2008: On the verification and comparison of extreme rainfall indices from climate models. J. Climate, 21, 1605-1621, doi:10.1175/2007JCLI1494.1.
6. Chen, M., W. Shi, P. Xie, V. Silva, V. E. Kousky, R. Wayne Higgins, and J. E. Janowiak, 2008: Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res., 113, D04110, doi:10.1029/2007JD009132.
7. Curriero, F. C., J. A. Patz, J. B. Rose, and S. Lele, 2001: The association between extreme precipitation and waterborne disease outbreaks in the United States, 1948-1994. Amer. J. Public Health, 91, 1194-1199, doi:10.2105/AJPH.91.8.1194.
8. Dai, A., 2006: Precipitation characteristics in eighteen coupled climate models. J. Climate, 19, 4605-4630, doi:10.1175/JCLI3884.1.
9. 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, 2031-2064, doi:10.1002/joc.1688.
10. DeFlorio, M. J., D. W. Pierce, D. R. Cayan, and A. J. Miller, 2013: Western U.S. extreme precipitation events and their relation to ENSO and PDO in CCSM4. J. Climate, 26, 4231-4243, doi:10.1175/JCLI-D-12-00257.1.
11. Delworth, T. L., and Coauthors, 2006: GFDL's CM2 global coupled climate models. Part I: Formulation and simulation characteristics. J. Climate, 19, 643-674, doi:10.1175/JCLI3629.1.
12. Delworth, T. L., and Coauthors, 2012: Simulated climate and climate change in the GFDL CM2.5 high-resolution coupled climate model. J. Climate, 25, 2755-2781, doi:10.1175/JCLI-D-11-00316.1.
13. Dibike, Y. B., and P. Coulibaly, 2006: Temporal neural networks for downscaling climate variability and extremes. Neural Netw., 19, 135-144, doi:10.1016/j.neunet.2006.01.003.
14. Duffy, P., B. Govindasamy, J. Iorio, J. Milovich, K. Sperber, K. Taylor, M. Wehner, and S. Thompson, 2003: High-resolution simulations of global climate, part 1: Present climate. Climate Dyn., 21, 371-390, doi:10.1007/s00382-003-0339-z.
15. Durman, C., J. M. Gregory, D. C. Hassell, R. Jones, and J. Murphy, 2001: A comparison of extreme European daily precipitation simulated by a global and a regional climate model for present and future climates. Quart. J. Roy. Meteor. Soc., 127, 1005-1015, doi:10.1002/qj.49712757316.
16. Fay, P. A., J. D. Carlisle, A. K. Knapp, J. M. Blair, and S. L. Collins, 2003: Productivity responses to altered rainfall patterns in a C4-dominated grassland. Oecologia, 137, 245-251, doi:10.1007/s00442-003-1331-3.
17. Fischer, E. M., and R. Knutti, 2015: Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes. Nat. Climate Change, 5, 560-564, doi:10.1038/nclimate2617.
18. Frei, C., R. Schöll, S. Fukutome, J. Schmidli, and P. L. Vidale, 2006: Future change of precipitation extremes in Europe: Intercomparison of scenarios from regional climate models. J. Geophys. Res., 111, D06105, doi:10.1029/2005JD005965.
19. Gandin, L. S., and R. Hardin, 1965: Objective Analysis of Meteorological Fields. Israel Program for Scientific Translation, 242 pp.
20. Griffies, S. M., 2012: Elements of the Modular Ocean Model (MOM). NOAA/Geophysical Fluid Dynamics Laboratory Tech. Rep. 7, 614 pp.
21. Groisman, P. Ya., R. W. Knight, and T. R. Karl, 2001: Heavy precipitation and high streamflow in the contiguous United States: Trends in the twentieth century. Bull. Amer. Meteor. Soc., 82, 219-246, doi:10.1175/1520-0477(2001)082<0219:HPAHSI>2.3.CO;2.
22. Gutowski, W. J., Jr., and Coauthors, 2010: Regional extreme monthly precipitation simulated by NARCCAP RCMs. J. Hydrometeor., 11, 1373-1379, doi:10.1175/2010JHM1297.1.
23. Hamlet, A. F., and D. P. Lettenmaier, 1999: Columbia River streamflow forecasting based on ENSO and PDO climate signals. J. Water Resour. Plann. Manage., 125, 333-341, doi:10.1061/(ASCE)0733-9496(1999)125:6(333).
24. Higgins, R. W., W. Shi, E. Yarosh, and R. Joyce, 2000: Improved United States precipitation quality control system and analysis. NCEP/Climate Prediction Center Atlas 7. [Available online at http://www.cpc.ncep.noaa.gov/research_papers/ncep_cpc_atlas/7/toc.html.]
25. Hsu, K.-L., X. Gao, S. Sorooshian, and H. Gupta, 1997: Precipitation estimation from remotely sensed information using artificial neural networks. J. Appl. Meteor., 36, 1176-1190, doi:10.1175/1520-0450(1997)036<1176:PEFRSI>2.0.CO;2.
26. Iorio, J., P. Duffy, B. Govindasamy, S. Thompson, M. Khairoutdinov, and D. Randall, 2004: Effects of model resolution and subgrid-scale physics on the simulation of precipitation in the continental United States. Climate Dyn., 23, 243-258, doi:10.1007/s00382-004-0440-y.
27. IPCC, 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.
28. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Cambridge University Press, 1535 pp., doi:10.1017/CBO9781107415324.
29. Jackson, R. B., S. R. Carpenter, C. N. Dahm, D. M. McKnight, R. J. Naiman, S. L. Postel, and S. W. Running, 2001: Water in a changing world. Ecol. Appl., 11, 1027-1045, doi:10.1890/1051-0761(2001)011[1027:WIACW]2.0.CO;2.
30. Jia, L., and Coauthors, 2015: Improved seasonal prediction of temperature and precipitation over land in a high-resolution GFDL climate model. J. Climate, 28, 2044-2062, doi:10.1175/JCLI-D-14-00112.1.
31. Kapnick, S. B., and T. L. Delworth, 2013: Controls of global snow under a changed climate. J. Climate, 26, 5537-5562, doi:10.1175/JCLI-D-12-00528.1.
32. Kapnick, S. B., T. L. Delworth, M. Ashfaq, S. Malyshev, and P. Milly, 2014: Snowfall less sensitive to warming in Karakoram than in Himalayas due to a unique seasonal cycle. Nat. Geosci., 7, 834-840, doi:10.1038/ngeo2269.
33. Kharin, V. V., F. W. Zwiers, X. Zhang, and G. C. Hegerl, 2007: Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations. J. Climate, 20, 1419-1444, doi:10.1175/JCLI4066.1.
34. Kharin, V. V., F. Zwiers, X. Zhang, and M. Wehner, 2013: Changes in temperature and precipitation extremes in the CMIP5 ensemble. Climatic Change, 119, 345-357, doi:10.1007/s10584-013-0705-8.
35. Knapp, A. K., and Coauthors, 2008: Consequences of more extreme precipitation regimes for terrestrial ecosystems. BioScience, 58, 811-821, doi:10.1641/B580908.
36. Kunkel, K. E., 2003: North American trends in extreme precipitation. Nat. Hazards, 29, 291-305, doi:10.1023/A:1023694115864.
37. Kunkel, K. E., K. Andsager, and D. R. Easterling, 1999: Long-term trends in extreme precipitation events over the conterminous United States and Canada. J. Climate, 12, 2515-2527, doi:10.1175/1520-0442(1999)012<2515:LTTIEP>2.0.CO;2.
38. Lee, J.-E., R. Pierrehumbert, A. Swann, and B. R. Lintner, 2009: Sensitivity of stable water isotopic values to convective parameterization schemes. Geophys. Res. Lett., 36, L23801, doi:10.1029/2009GL040880.
39. Lundquist, J. D., M. Hughes, B. Henn, E. D. Gutmann, B. Livneh, J. Dozier, and P. Neiman, 2015: High-elevation precipitation patterns: Using snow measurements to assess daily gridded datasets across the Sierra Nevada, California. J. Hydrometeor., 16, 1773-1792, doi:10.1175/JHM-D-15-0019.1.
40. Mallakpour, I., and G. Villarini, 2015: The changing nature of flooding across the central United States. Nat. Climate Change, 5, 250-254, doi:10.1038/nclimate2516.
41. Maloney, E. D., and Coauthors, 2014: North American climate in CMIP5 experiments. Part III: Assessment of twenty-first-century projections. J. Climate, 27, 2230-2270, doi:10.1175/JCLI-D-13-00273.1.
42. Mantua, N. J., and S. R. Hare, 2002: The Pacific decadal oscillation. J. Oceanogr., 58, 35-44, doi:10.1023/A:1015820616384.
43. Mehran, A., A. AghaKouchak, and T. Phillips, 2014: Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations. J. Geophys. Res. Atmos., 119, 1695-1707, doi:10.1002/2013JD021152.
44. Milly, P., and Coauthors, 2014: An enhanced model of land water and energy for global hydrologic and earth-system studies. J. Hydrometeor., 15, 1739-1761, doi:10.1175/JHM-D-13-0162.1.
45. Min, S.-K., X. Zhang, F. W. Zwiers, and G. C. Hegerl, 2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378-381, doi:10.1038/nature09763.
46. Msadek, R., G. Vecchi, M. Winton, and R. Gudgel, 2014: Importance of initial conditions in seasonal predictions of Arctic sea ice extent. Geophys. Res. Lett., 41, 5208-5215, doi:10.1002/2014GL060799.
47. Muller, C. J., P. A. O'Gorman, and L. E. Back, 2011: Intensification of precipitation extremes with warming in a cloud-resolving model. J. Climate, 24, 2784-2800, doi:10.1175/2011JCLI3876.1.
48. Murakami, H., and Coauthors, 2015: Simulation and prediction of category 4 and 5 hurricanes in the high-resolution GFDL HiFLOR coupled climate model. J. Climate, 28, 9058-9079, doi:10.1175/JCLI-D-15-0216.1.
49. Ning, L., E. E. Riddle, and R. S. Bradley, 2015: Projected changes in climate extremes over the northeastern United States. J. Climate, 28, 3289-3310, doi:10.1175/JCLI-D-14-00150.1.
50. O'Gorman, P. A., 2015: Precipitation extremes under climate change. Curr. Climate Change Rep., 1, 49-59, doi:10.1007/s40641-015-0009-3.
51. O'Gorman, P. A., and T. Schneider, 2009: The physical basis for increases in precipitation extremes in simulations of 21st-century climate change. Proc. Natl. Acad. Sci. USA, 106, 14 773-14 777, doi:10.1073/pnas.0907610106.
52. 2 warming. Climate Dyn., 28, 351-363, doi:10.1007/s00382-006-0180-2.
53. Peterson, T. C., X. Zhang, M. Brunet-India, and J. L. Vázquez-Aguirre, 2008: Changes in North American extremes derived from daily weather data. J. Geophys. Res., 113, D07113, doi:10.1029/2007JD009453.
54. Pielke, R. A., Jr., and M. W. Downton, 2000: Precipitation and damaging floods: Trends in the United States, 1932-97. J. Climate, 13, 3625-3637, doi:10.1175/1520-0442(2000)013<3625:PADFTI>2.0.CO;2.
55. Putman, W. M., and S.-J. Lin, 2007: Finite-volume transport on various cubed-sphere grids. J. Comput. Phys., 227, 55-78, doi:10.1016/j.jcp.2007.07.022.
56. Rayner, N., D. E. Parker, E. Horton, C. Folland, L. Alexander, D. Rowell, E. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.
57. Rienecker, M. M., and Coauthors, 2011: MERRA: NASA's Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 3624-3648, doi:10.1175/JCLI-D-11-00015.1.
58. Rosenzweig, C., F. N. Tubiello, R. Goldberg, E. Mills, and J. Bloomfield, 2002: Increased crop damage in the US from excess precipitation under climate change. Global Environ. Change, 12, 197-202, doi:10.1016/S0959-3780(02)00008-0.
59. Schoof, J. T., 2015: High-resolution projections of 21st century daily precipitation for the contiguous US. J. Geophys. Res. Atmos., 120, 3029-3042, doi:10.1002/2014JD022376.
60. Schoof, J. T., and S. M. Robeson, 2016: Projecting changes in regional temperature and precipitation extremes in the United States. Wea. Climate Extremes, 11, 28-40, doi:10.1016/j.wace.2015.09.004.
61. Schubert, S. D., Y. Chang, M. J. Suarez, and P. J. Pegion, 2008: ENSO and wintertime extreme precipitation events over the contiguous United States. J. Climate, 21, 22-39, doi:10.1175/2007JCLI1705.1.
62. Sen Roy, S., and R. C. Balling, 2004: Trends in extreme daily precipitation indices in India. Int. J. Climatol., 24, 457-466, doi:10.1002/joc.995.
63. Sheffield, J., and Coauthors, 2013: North American climate in CMIP5 experiments. Part I: Evaluation of historical simulations of continental and regional climatology. J. Climate, 26, 9209-9245, doi:10.1175/JCLI-D-12-00592.1.
64. Shiu, C.-J., S. C. Liu, C. Fu, A. Dai, and Y. Sun, 2012: How much do precipitation extremes change in a warming climate? Geophys. Res. Lett., 39, L17707, doi:10.1029/2012GL052762.
65. Sillmann, J., V. Kharin, F. Zwiers, X. Zhang, and D. Bronaugh, 2013: Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J. Geophys. Res. Atmos., 118, 2473-2493, doi:10.1002/jgrd.50188.
66. Stock, C. A., and Coauthors, 2015: Seasonal sea surface temperature anomaly prediction for coastal ecosystems. Prog. Oceanogr., 137, 219-236, doi:10.1016/j.pocean.2015.06.007.
67. Sun, Y., S. Solomon, A. Dai, and R. W. Portmann, 2007: How often will it rain? J. Climate, 20, 4801-4818, doi:10.1175/JCLI4263.1.
68. Thibeault, J. M., and A. Seth, 2014: Changing climate extremes in the northeast United States: Observations and projections from CMIP5. Climatic Change, 127, 273-287, doi:10.1007/s10584-014-1257-2.
69. Toreti, A., and Coauthors, 2013: Projections of global changes in precipitation extremes from Coupled Model Intercomparison Project phase 5 models. Geophys. Res. Lett., 40, 4887-4892, doi:10.1002/grl.50940.
70. Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84, 1205-1217, doi:10.1175/BAMS-84-9-1205.
71. Vecchi, G. A., and Coauthors, 2014: On the seasonal forecasting of regional tropical cyclone activity. J. Climate, 27, 7994-8016, doi:10.1175/JCLI-D-14-00158.1.
72. Villarini, G., E. Scoccimarro, and S. Gualdi, 2013: Projections of heavy rainfall over the central United States based on CMIP5 models. Atmos. Sci. Lett., 14, 200-205, doi:10.1002/asl2.440.
73. Villarini, G., J. A. Smith, and G. A. Vecchi, 2013: Changing frequency of heavy rainfall over the central United States. J. Climate, 26, 351-357, doi:10.1175/JCLI-D-12-00043.1.
74. Wehner, M. F., R. L. Smith, G. Bala, and P. Duffy, 2010: The effect of horizontal resolution on simulation of very extreme US precipitation events in a global atmosphere model. Climate Dyn., 34, 241-247, doi:10.1007/s00382-009-0656-y.
75. Westra, S., and Coauthors, 2014: Future changes to the intensity and frequency of short-duration extreme rainfall. Rev. Geophys., 52, 522-555, doi:10.1002/2014RG000464.
76. Wuebbles, D., and Coauthors, 2014: CMIP5 climate model analyses: Climate extremes in the United States. Bull. Amer. Meteor. Soc., 95, 571-583, doi:10.1175/BAMS-D-12-00172.1.
77. Zhang, W., and Coauthors, 2016: Improved simulation of tropical cyclone responses to ENSO in the western North Pacific in the high-resolution GFDL HiFLOR coupled climate model. J. Climate, 29, 1391-1415, doi:10.1175/JCLI-D-15-0475.1.