Improved simulation of extreme precipitation in a high-resolution atmosphere model

Geophysical Research Letters

Volumn 40, Issue 21, 2013, Pages 5803-5808

  Kopparla, Pushkar ^a   Fischer, Erich M ^a   Hannay, Cécile ^b   Knutti, Reto ^a  

^a ETH Zurich   (Switzerland)

^b NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

atmospheric model; extreme precipitation; GCM; high resolution

Indexed keywords

ATMOSPHERIC MODEL; ATMOSPHERIC SIMULATIONS; EXTREME PRECIPITATION; EXTREME PRECIPITATION EVENTS; GCM; HIGH RESOLUTION; HIGH-RESOLUTION MODELS; PRECIPITATION EXTREMES;

MODELS; PRECIPITATION (METEOROLOGY);

COMPUTER SIMULATION;

ATMOSPHERIC MODELING; CLIMATE MODELING; GENERAL CIRCULATION MODEL; NUMERICAL MODEL; PRECIPITATION (CLIMATOLOGY); PRECIPITATION ASSESSMENT; RESOLUTION;

AUSTRALIA; UNITED STATES;

EID: 84887510487     PISSN: 00948276     EISSN: 19448007     Source Type: Journal    
DOI: 10.1002/2013GL057866     Document Type: Article

References (38)

1. Allan, R. P., and, B. J. Soden, (2008), Atmospheric warming and the amplification of precipitation extremes, Science, 321 (5895), 1481-1484.
2. Allen, M. R., and, W. J. Ingram, (2002), Constraints on future changes in climate and the hydrologic cycle, Nature, 419 (6903), 224-232.
3. Boer, G., (1993), Climate change and the regulation of the surface moisture and energy budgets, Clim. Dyn., 8 (5), 225-239.
4. 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, Clim. Dyn., 21 (5-6), 371-390.
5. Gutowski Jr., W., E. Takle, K. Kozak, J. Patton, R. Arritt, and, J. Christensen, (2007), A possible constraint on regional precipitation intensity changes under global warming, J. Hydrometeorol., 8 (6), 1382-1396.
6. Haylock, M. R., N. Hofstra, A. M. G. Klein Tank, E. J. Klok, P. D. Jones, and, M. New, (2008), A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006, J. Geophys. Res., 113, D20119, doi: 10.1029/2008JD010201.
7. 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/index.html].
8. Hurrell, J. W., et al. (2013), The Community Earth System Model: A framework for collaborative research, Bull. Am. Meteorol. Soc., 94, 1339-1360.
9. 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, Clim. Dyn., 23 (3), 243-258.
10. Jones, D. A., W. Wang, and, R. Fawcett, (2009), High-quality spatial climate data-sets for Australia, Aust. Meteorol. Oceanogr. J., 58 (4), 233-248.
11. Kendon, E. J., D. P. Rowell, and, R. G. Jones, (2010), Mechanisms and reliability of future projected changes in daily precipitation, Clim. Dyn., 35 (2-3), 489-509.
12. Kharin, V., F. Zwiers, X. Zhang, and, G. Hegerl, (2007), Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations, J. Clim., 20 (8), 1419-1444.
13. King, A. D., L. V. Alexander, and, M. G. Donat, (2013), The efficacy of using gridded data to examine extreme rainfall characteristics: A case study for Australia, Int. J. Climatol., 33 (10), 2376-2387, doi: 10.1002/joc.3588.
14. Knutti, R., and, J. Sedláček, (2012), Robustness and uncertainties in the new CMIP5 climate model projections, Nat. Clim. Change, 3, 369-373, doi: 10.1038/nclimate1716.
15. Lenderink, G., and, E. van Meijgaard, (2008), Increase in hourly precipitation extremes beyond expectations from temperature changes, Nat. Geosci., 1 (8), 511-514.
16. Masson, D., and, R. Knutti, (2011), Spatial-scale dependence of climate model performance in the CMIP3 ensemble, J. Clim., 24 (11), 2680-2692.
17. Neale, R. B., J. Richter, S. Park, P. H. Lauritzen, S. J. Vavrus, P. J. Rasch, and, M. Zhang, (2013), The mean climate of the Community Atmosphere Model (CAM4) in forced SST and fully coupled experiments, J. Clim., 26 (14), 5150-5168, doi: 10.1175/JCLI-D-12-00236.1.
18. O'Gorman, P. A., and, T. Schneider, (2009a), The physical basis for increases in precipitation extremes in simulations of 21st-century climate change, Proc. Natl. Acad. Sci., 106 (35), 14,773-14,777.
19. O'Gorman, P. A., and, T. Schneider, (2009b), Scaling of precipitation extremes over a wide range of climates simulated with an idealized GCM, J. Clim., 22 (21), 5676-5685.
20. 2 warming, Clim. Dyn., 28 (4), 351-363.
21. Perkins, S. E., A. J. Pitman, N. J. Holbrook, and, J. McAneney, (2007), Evaluation of the AR4 climate models' simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions, J. Clim., 20 (17), 4356-4376.
22. Pope, V., and, R. Stratton, (2002), The processes governing horizontal resolution sensitivity in a climate model, Clim. Dyn., 19 (3), 211-236.
23. 2-induced climate change in CMIP2 experiments: Quantification of agreement and role of internal variability, J. Clim., 14 (9), 2088-2104.
24. Roeckner, E., R. Brokopf, M. Esch, M. Giorgetta, S. Hagemann, L. Kornblueh, E. Manzini, U. Schlese, and, U. Schulzweida, (2006), Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model, J. Clim., 19 (16), 3771-3791.
25. Salathé, E. P., R. Steed, C. F. Mass, and, P. H. Zahn, (2008), A high-resolution climate model for the U.S. Pacific Northwest: Mesoscale feedbacks and local responses to climate change, J. Clim., 21 (21), 5708-5726.
26. Schlemmer, L., C. Hohenegger, J. Schmidli, C. S. Bretherton, and, C. Schär, (2011), An idealized cloud-resolving framework for the study of midlatitude diurnal convection over land, J. Atmos. Sci., 68 (5), 1041-1057.
27. Schlemmer, L., C. Hohenegger, J. Schmidli, and, C. Schär, (2012), Diurnal equilibrium convection and land surface-atmosphere interactions in an idealized cloud-resolving model, Q. J. R. Meteorol. Soc., 138 (667), 1526-1539.
28. 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 (3), 125-161.
29. Shaffrey, L., et al. (2009), U.K. HiGEM: The new U.K. high-resolution global environment model-Model description and basic evaluation, J. Clim., 22 (8), 1861-1896.
30. 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.
31. Sillmann, J., V. V. Kharin, X. Zhang, F. W. Zwiers, and, D. Bronaugh, (2013), Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate, J. Geophys. Res. Atmos., 118, 1716-1733, doi: 10.1002/jgrd.50203.
32. Stephens, G. L., T. L'Ecuyer, R. Forbes, A. Gettlemen, J.-C. Golaz, A. Bodas-Salcedo, K. Suzuki, P. Gabriel, and, J. Haynes, (2010), Dreary state of precipitation in global models, J. Geophys. Res., 115, D24211, doi: 10.1029/2010JD014532.
33. Sun, Y., S. Solomon, A. Dai, and, R. Portmann, (2007), How often will it rain?, J. Clim., 20 (19), 4801-4818.
34. Tebaldi, C., K. Hayhoe, J. M. Arblaster, and, G. A. Meehl, (2006), Going to the extremes, Clim. Change, 79 (3-4), 185-211.
35. Tebaldi, C., J. M. Arblaster, and, R. Knutti, (2011), Mapping model agreement on future climate projections, Geophys. Res. Lett., 38, L23701, doi: 10.1029/2011GL049863.
36. Trenberth, K. E., A. Dai, R. M. Rasmussen, and, D. B. Parsons, (2003), The changing character of precipitation, Bull. Am. Meteorol. Soc., 84 (9), 1205-1217, doi: 10.1175/BAMS-84-9-1205.
37. Wehner, M., R. Smith, G. Bala, and, P. Duffy, (2010), The effect of horizontal resolution on simulation of very extreme U.S. precipitation events in a global atmosphere model, Clim. Dyn., 34 (2-3), 241-247.
38. Wilcox, E., and, L. Donner, (2007), The frequency of extreme rain events in satellite rain-rate estimates and an atmospheric general circulation model, J. Clim., 20 (1), 53-69.