Evidence for added value of convection-permitting models for studying changes in extreme precipitation

Journal of Geophysical Research

Volumn 120, Issue 24, 2015, Pages 12,500-12,513

  Meredith, Edmund P ^a   Maraun, Douglas ^a,b   Semenov, Vladimir A ^a,c,d,e   Park, Wonsun ^a  

^a GEOMAR HELMHOLTZ CENTRE FOR OCEAN RESEARCH KIEL   (Germany)

^b UNIVERSITY OF GRAZ   (Austria)

^c OBUKHOV INSTITUTE OF ATMOSPHERIC PHYSICS   (Russian Federation)

^d SHIRSHOV INSTITUTE OF OCEANOLOGY   (Russian Federation)

^e INSTITUTE OF GEOGRAPHY   (Russian Federation)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATE CHANGE; CONVECTION; EXTREME EVENT; OROGRAPHY; PRECIPITATION ASSESSMENT; PRECIPITATION INTENSITY; SEA SURFACE TEMPERATURE; TROPOSPHERE; VERTICAL MOVEMENT; WARMING;

EID: 84957437011     PISSN: 01480227     EISSN: 21562202     Source Type: Journal    
DOI: 10.1002/2015JD024238     Document Type: Article

References (54)

1. Allen, M. R., and W. J. Ingram (2002), Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 224–232.
2. Ban, N., J. Schmidli, and C. Schär (2014), Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations, J. Geophys. Res. Atmos., 119, 7889–7907, doi:10.1002/2014GL062588.
3. Ban, N., J. Schmidli, and C. Schär (2015), Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?, Geophys. Res. Lett., 42, 1165–1172, doi:10.1002/2014JD021478.
4. Chan, S. C., E. J. Kendon, H. J. Fowler, S. Blenkinsop, N. M. Roberts, and C. A. T. Ferro (2014a), The value of high-resolution Met Office regional climate models in the simulation of multihourly precipitation extremes, J. Clim., 27, 6155–6174.
5. Chan, S. C., E. J. Kendon, H. J. Fowler, S. Blenkinsop, and N. M. Roberts (2014b), Projected increase in summer and winter UK sub-daily precipitation extremes from high-resolution regional climate models, Clim. Dyn., 41, 1475–1495.
6. Corfidi, S. F. (2003), Cold pools and MCS propagation: Forecasting the motion of downwind-developing MCSs, Weather Forecasting, 18(6), 997–1017.
7. Di Luca, A., R. de Elía, and R. Laprise (2012), Potential for added value in precipitation simulated by high-resolution nested regional climate models and observations, Clim. Dyn., 38(5-6), 1229–1247.
8. Di Luca, A., R. de Elía, and L. René (2015), Challenges in the quest for added value of regional climate dynamical downscaling, Curr. Clim. Change Rep., 1(1), 10–21.
9. Diffenbaugh, N. S., J. S. Pal, R. J. Trapp, and F. Giorgi (2005), Fine-scale processes regulate the response of extreme events to global climate change, Proc. Natl. Acad. Sci. U.S.A., 102 (44), 15,774–15,778.
10. Donat, M. G., et al. (2013), Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 data-set, J. Geophys. Res. Atmos., 118, 2098–2118, doi:10.1002/jgrd.50150.
11. Doswell, C. A., III (1987), The distinction between large-scale and mesoscale contribution to severe convection: A case study example, Weather Forecasting, 2(1), 3–16.
12. Eden, J. M., M. Widmann, D. Maraun, and M. Vrac (2014), Comparison of GCM- and RCM-simulated precipitation following stochastic postprocessing, J. Geophys. Res. Atmos., 119, 11,040–11,053, doi:10.1002/2014JD021732.
13. Emori, S., and S. J. Brown (2005), Dynamic and thermodynamic changes in mean and extreme precipitation under changed climate, Geophys. Res. Lett., 32 L17706, doi:10.1029/2005GL023272.
14. Feser, F., B. Rockel, H. von Storch, J. Winterfeldt, and M. Zahn (2011), Regional climate models add value to global model data: A review and selected examples, Bull. Am. Meteorol. Soc., 92(9), 1181–1192.
15. Funatsu, B. M., C. Claud, and J.-P. Chaboureau (2009), Comparison between the large-scale environments of moderate and intense precipitating systems in the Mediterranean region, Mon. Weather Rev., 137, 3933–3959.
16. Grell, G. A. (1993), Prognostic evaluation of assumptions used by cumulus parameterizations, Mon. Weather Rev., 121, 764–787.
17. Grell, G. A. and D. Devenyi (2002), A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29(14), 1693, doi:10.1029/2002GL015311.
18. Groisman, P. Y., R. W. Knight, D. R. Easterling, T. R. Karl, G. C. Hegerl, and V. N. Razuvaev (2005), Trends in intense precipitation in the climate
19. Han, J., and H. L. Pan (2011), Revision of convection and vertical diffusion schemes in the NCEP global forecast system, Weather Forecasting, 26, 520–533.
20. Hazeleger, W., B. J. J. M. van den Hurk, E. Min, G. J. van Oldenborgh, A. C. Petersen, D. A. Stainforth, E. Vasileiadou, and L. A. Smith (2015), Tales of future weather, Nat. Clim. Change, 5(2), 107–113.
21. Hohenegger, C., P. Brockhaus, and C. Schär (2008), Towards climate simulations at cloud-resolving scales, Meteorol. Z., 17(4), 383–394.
22. Janjic, Z. I. (1994), The step–mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes, Mon. Weather Rev., 122, 927–945.
23. Jiménez, P. A., and J. Dudhia (2012), Improving the representation of resolved and unresolved topographic effects on surface wind in the WRF model, J. Appl. Meteorol. Climatol., 51, 300–316.
24. Kain, J. S. (2004), The Kain–Fritsch convective parameterization: An update, J. Appl. Meteorol., 43, 170–181.
25. Karl, T. R., and R. W. Knight (1998), Secular trends of precipitation amount, frequency, and intensity in the United States, Bull. Am. Meteorol. Soc., 79, 231–241.
26. Kendon, E. J., N. M. Roberts, C. A. Senior, and M. J. Roberts (2012), Realism of rainfall in a very high resolution regional climate model, J. Clim., 25, 5791–5806.
27. Kendon, E., N. M. Roberts, H. J. Fowler, M. J. Roberts, S. C. Chan, and C. A. Senior (2014), Heavier summer downpours with climate change revealed by weather forecast resolution model, Nat. Clim. Change, 4, 570–576.
28. Kharin, 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. Clim., 20(8), 1419–1444.
29. Kitoh, A., T. Ose, K. Kurihara, S. Kusunoki, M. Sugi, and KAKUSHIN Team-3 Modeling Group (2009), Projection of changes in future weather extremes using super-high-resolution global and regional atmospheric models in the KAKUSHIN Program: Results of preliminary experiments, Hydrol. Res. Lett., 3, 49–53.
30. Knupp, K. R., and W. R. Cotton (1985), Convective cloud downdraft structure: An interpretive survey, Rev. Geophys., 23(2), 183–215.
31. Kotlyakov, V. M., L. V. Desinov, S. V. Dolgov, N. I. Koronkevich, E. A. Likhacheva, A. N. Makkaveev, A. A. Medvedev, and V. A. Rudakov (2013), Flooding of July 6–7, 2012, in the town of Krymsk, Reg. Res. Russia, 3(1), 32–39, doi:10.1134/S2079970513010061.
32. Lean, H. W., P. A. Clark, M. Dixon, N. M. Roberts, A. Fitch, R. Forbes, and C. Halliwell (2008), Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom, Mon. Weather Rev., 136(9), 3408–3424.
33. LeMone, M. A., G. M. Barnes, and E. J. Zipser (1984), Momentum flux by lines of cumulonimbus over the tropical oceans, J. Atmos. Sci., 41(12), 1914–1932.
34. Lenderink, G., and E. van Meijgaard (2008), Increase in hourly precipitation extremes beyond expectations from temperature changes, Nat. Geosci., 1, 511–514.
35. Li, F., W. D. Collins, M. F. Wehner, D. L. Williamson, and J. G. Olson (2011a), Response of precipitation extremes to idealized global warming in an aqua-planet climate model: Towards a robust projection across different horizontal resolutions, Tellus A, 63(5), 876–883.
36. Li, F., W. D. Collins, M. F. Wehner, D. L. Williamson, J. G. Olson, and C. Algieri (2011b), Impact of horizontal resolution on simulation of precipitation extremes in an aqua-planet version of Community Atmospheric Model (CAM3), Tellus A, 63(5), 884–892.
37. Meredith, E. P., V. A. Semenov, D. Maraun, W. Park, and A. V. Chernokulsky (2015), Crucial role of Black Sea warming in amplifying the 2012 Krymsk precipitation extreme, Nat. Geosci., 8, 615–619.
38. Orlowsky, B., and S. I. Seneviratne (2011), Global changes in extreme events: Regional and seasonal dimension, Clim. Change, 110, 669–696.
39. Otte, T. L., C. G. Nolte, M. J. Otte, and J. H. Bowden (2012), Does nudging squelch the extremes in regional climate modeling?, J. Clim., 25(20), 7046–7066.
40. Prein, A. F., A. Gobiet, M. Suklitsch, H. Truhetz, N. K. Awan, K. Keuler, and G. Georgievski (2013), Added value of convection permitting seasonal simulations, Clim. Dyn., 41(9-10), 2655–2677.
41. Prein, A. F., et al. (2015), A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges, Rev. Geophys., 53, 323–361, doi:10.1002/2014RG000475.
42. Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax (2007), Daily high resolution blended analyses for sea surface temperature, J. Clim., 20, 5473–5496.
43. Schoenberg Ferrier, B., J. Simpson, and W.-K. Tao (1996), Factors responsible for precipitation efficiencies in midlatitude and tropical squall simulations, Mon. Weather Rev., 124(10), 2100–2125.
44. Semenov, V. A., and L. Bengtsson (2002), Secular trends in daily precipitation characteristics: Greenhouse gas simulation with a coupled AOGCM, Clim. Dyn., 19, 123–140.
45. Seneviratne, S. I., et al. (2012), Changes in climate extremes and their impacts on the natural physical environment, in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, A Spec. Rep. of Working Groups I and II of the Intergovernmental Panel on Clim. Change (IPCC), edited by C. B. Field, pp. 109–230, Cambridge Univ. Press, Cambridge, U. K., and New York.
46. Shepherd, J. M., B. S. Ferrier, and P. S. Ray (2001), Rainfall morphology in Florida convergence zones: A numerical study, Mon. Weather Rev., 129(2), 177–197.
47. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers (2008), A description of the advanced research WRF version 3 NCAR Tech. Note NCAR/TN-475 + STR, 125 pp.
48. Tiedtke, M. (1989), A comprehensive mass flux scheme for cumulus parameterization in large–scale models, Mon. Weather Rev., 117, 1779–1800.
49. Trenberth, K. E. (1999), Conceptual framework for changes of extremes of the hydrological cycle with climate change, in Weather and Climate Extremes, pp. 327–339, Springer, Netherlands.
50. Volosciuk, C., D. Maraun, V. A. Semenov, and W. Park (2015), Extreme precipitation in an atmosphere general circulation model: Impact of horizontal and vertical model resolution, J. Clim., 28(3), 1184–1205.
51. Warner, T. T., and H.-M. Hsu (2000), Nested-model simulation of moist convection: The impact of coarse-grid parameterized convection on fine-grid resolved convection, Mon. Weather Rev., 128(7), 2211–2231.
52. Wong, G., D. Maraun, M. Vrac, M. Widmann, J. M. Eden, and T. Kent (2014), Stochastic model output statistics for bias correcting and downscaling precipitation including extremes, J. Clim., 27(18), 6940–6959.
53. Yang, Q., L. R. Leung, S. A. Rauscher, T. D. Ringler, and M. A. Taylor (2014), Atmospheric moisture budget and spatial resolution dependence of precipitation extremes in aquaplanet simulations, J. Clim., 27(10), 3565–3581.
54. Zhang, C., Y. Wang, and K. Hamilton (2011), Improved representation of boundary layer clouds over the Southeast Pacific in ARW–WRF using a modified Tiedtke cumulus parameterization scheme, Mon. Weather Rev., 139, 3489–3513.