A hierarchical Bayesian regional model for nonstationary precipitation extremes in Northern California conditioned on tropical moisture exports

Water Resources Research

Volumn 51, Issue 3, 2015, Pages 1472-1492

  Steinschneider, Scott ^a   Lall, Upmanu ^a  

^a Columbia University ^*  (United States)

Author keywords

atmospheric rivers; extremes; peaks over threshold; tropical moisture exports

Indexed keywords

MOISTURE; PRECIPITATION (METEOROLOGY); RAIN; RISK PERCEPTION; TROPICS;

EXTREME PRECIPITATION; EXTREME PRECIPITATION EVENTS; EXTREMES; INTERANNUAL VARIABILITY; PEAKS OVER THRESHOLD; PRECIPITATION EXTREMES; REGIONAL FREQUENCY ANALYSIS; TROPICAL MOISTURE EXPORTS;

CLIMATE MODELS;

AIR MASS; BAYESIAN ANALYSIS; FLOODING; FRONTAL FEATURE; HIERARCHICAL SYSTEM; MOISTURE CONTENT; PRECIPITATION (CLIMATOLOGY);

CALIFORNIA; UNITED STATES;

EID: 85027934159     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/2014WR016664     Document Type: Article

References (70)

1. Alexander, L. V., P. Uotila, and, N. Nicholls, (2009), Influence of sea surface temperature variability on global temperature and precipitation extremes, J. Geophys. Res., 114, D18116, doi: 10.1029/2009JD012301.
2. Berg, P., C. Moseley, and, J. O. Haerter, (2013), Strong increase in convective precipitation in response to higher temperatures, Nat. Geosci., 6 (3), 181-185.
3. Coles, S., (2001), An Introduction to Statistical Modeling of Extreme Values, Springer, London, U. K.
4. Davison, A. C., and, R. L. Smith, (1990), Models for exceedances over high thresholds, J. R. Stat. Soc., Ser. B, 52 (3), 393-442.
5. Dee, D. P., et al. (2011), The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. R. Meteorol. Soc., 137, 553-597, doi: 10.1002/qj.828.
6. Dettinger, M. D., (2013), Atmospheric rivers as drought busters on the U.S. West Coast, J. Hydrometeorol., 14, 1721-1732.
7. Dettinger, M. D., and, D. R. Cayan, (2014), Drought and the California delta-A matter of extremes, San Francisco Estuary Watershed Sci., 12(2), pp. 1-6.
8. Dettinger, M. D., F. M. Ralph, T. Das, P. J. Neiman, and, D. Cayan, (2011), Atmospheric rivers, floods, and the water resources of California, Water, 3, 455-478.
9. Dirmeyer, P. A., and, J. L. Kinter III, (2009), The "Maya Express": Floods in the U.S. Midwest, Eos Trans. AGU, 90 (12), 101-108.
10. Dirmeyer, P. A., and, J. L. Kinter III, (2010), Floods over the U.S. Midwest: A regional water cycle perspective, J. Hydrometeorol., 11, 1172-1181.
11. Duane, S., A. D. Kennedy, B. J. Pendleton, and, D. Roweth, (1987), Hybrid Monte Carlo, Phys. Lett. B, 195 (2), 216-222.
12. Ensor, L. A., and, S. M. Robeson, (2008), Statistical characteristics of daily precipitation: Comparisons of gridded and point datasets, J. Appl. Meteorol. Climatol., 47, 2468-2476, doi: 10.1175/2008JAMC1757.1.
13. Fischer, E. M., U. Beyerle, and, R. Knutti, (2013), Robust spatially aggregated projections of climate extremes, Nat. Clim. Change, 3, 1033-1038.
14. Friederichs, P., and, T. L. Thorarinsdottir, (2012), Forecast verification for extreme value distributions with an application to probabilistic peak wind prediction, Environmetrics, 23 (7), 579-594.
15. Gelman, A., and, D. B. Rubin, (1992), Inference from iterative simulation using multiple sequences, Stat. Sci., 7 (4), 457-511.
16. Hersbach, H., (2000), Decomposition of the continuous ranked probability score for ensemble prediction systems, Weather Forecast, 15, 559-570.
17. Hirabayashi, Y., R. Mahendran, S. Koirala, L. Konoshima, D. Yamazaki, S. Watanabe, H. Kim, and, S. Kanae, (2013), Global flood risk under climate change, Nat. Clim. Change Lett., 3, 816-821, doi: 10.1038/nclimate1911.
18. Hirschboeck, K. K., (1988), Flood hydroclimatology, in Flood Geomorphology, edited by, V. R. Baker, R. C. Kochel, and, P. C. Patton, pp. 27-49, John Wiley, N. Y.
19. Houze, Jr., R. A., K. L. Rasmussen, S. Medina, S. R. Brodzik, and, U. Romatschke, (2011), Anomalous atmospheric events leading to the summer 2010 Floods in Pakistan, Bull. Am. Meteorol. Soc., 92, 291-298, doi: 10.1175/2010BAMS3173.1.
20. Jain, S., and, U. Lall, (2000), Magnitude and timing of annual maximum floods: Trends and large-scale climate associations for the Blacksmith Fork River, Utah, Water Resour. Res., 36, 3641-3651.
21. Jain, S., and, U. Lall, (2001), Floods in a changing climate: Does the past represent the future? Water Resour. Res., 37, 3193-3205.
22. Karamperidou, C., F. Cioffi, and, U. Lall, (2012), Surface temperature gradients as diagnostic indicators of midlatitude circulation dynamics, J. Clim., 25, 4154-4171.
23. Khaliq, M. N., T. B. M. J. Ouarda, J.-C. Ondo, P. Gachon, and, B. Bobee, (2006), Frequency analysis of a sequence of dependent and/or non-stationary hydro-meteorological observations: A review, J. Hydrol., 329 (3-4), 534-552.
24. Knippertz, P., and, H. Wernli, (2010), A Lagrangian climatology of tropical moisture exports to the northern hemispheric extratropics, J. Clim., 23, 987-1003.
25. Knippertz, P., H. Wernli, and, G. Glaser, (2012), A global climatology of tropical moisture exports, J. Clim., 26, 3031-3045.
26. Komori, D., S. Nakamura, M. Kiguchi, A. Nishijima, D. Yamazaki, S. Suzuki, A. Kawasaki, K. Oki, and, T. Oki, (2012), Characteristics of the 2011 Chao Phraya River flood in Central Thailand, Hydrol. Res. Lett., 6, 41-46.
27. Koutsoyiannis, D., (2006), Nonstationarity versus scaling in hydrology, J. Hydrol., 324 (1-4), 239-254.
28. Koutsoyiannis, D., and, A. Montanari, (2014), Negligent killing of scientific concepts: The stationarity case, Hydrol. Sci. J., doi: 10.1080/02626667.2014.959959.
29. Kwon, H.-H., C. Brown, and, U. Lall, (2008), Climate informed flood frequency analysis and prediction in Montana using hierarchical Bayesian modeling, Geophys. Res. Lett., 35, L05404, doi: 10.1029/2007GL032220.
30. Lackmann, G. W., (2013), The south-central U.S. flood of May 2010: Present and future, J. Clim., 26, 4688-4709.
31. Laio, F., and, S. Tamea, (2007), Verification tools for probabilistic forecasts of continuous hydrologic variables, Hydrol. Earth Syst. Sci., 11, 1267-1277.
32. Lall, U., (1987), Project risk considering sampling uncertainties and a finite project operation period, in Application of Frequency and Risk in Water Resources, edited by, V. P. Singh, pp. 305-318, D. Reidel, Baton Rouge, La.
33. Lavers, D. A., and, G. Villarini, (2013a), Atmospheric rivers and flooding over the central United States, J. Clim., 26, 7829-7836.
34. Lavers, D. A., and, G. Villarini, (2013b), The nexus between atmospheric rivers and extreme precipitation across Europe, Geophys. Res. Lett., 40, 3259-3264, doi: 10.1002/grl.50636.
35. Lavers, D. A., R. P. Allan, E. F. Wood, G. Villarini, D. J. Brayshaw, and, A. J. Wade, (2011), Winter floods in Britain are connected to atmospheric rivers, Geophys. Res. Lett., 38, L23803, doi: 10.1029/2011GL049783.
36. Lavers, D. A., R. P. Allan, G. Villarini, B. Lloyd-Hughes, D. J. Brayshaw, and, A. J. Wade, (2013), Future changes in atmospheric rivers and their implications for winter flooding in Britain, Environ. Res. Lett., 8, 034010, doi: 10.1088/1748-9326/8/3/034010.
37. Lenderink, G., and, E. van Meijgaard, (2008), Increases in hourly precipitation extremes beyond expectations from temperature changes, Nat. Geosci., 1, 511-514.
38. Leung, L. R., and, Y. Qian, (2009), Atmospheric rivers induced heavy precipitation and flooding in the western U.S. simulated by the WRF regional climate model, Geophys. Res. Lett., 36, L03820, doi: 10.1029/2008GL036445.
39. Liepert, B. G., (2013), Atmospheric rivers in changing climate, Environ. Res. Lett., 8, 031006, doi: 10.1088/1748-9326/8/3/031006.
40. Lima, C. H. R., and, U. Lall, (2010), Spatial scaling in a changing climate: A hierarchical Bayesian model for non-stationary multi-site annual maximum and monthly streamflow, J. Hydrol., 383, 307-318.
41. Lin, C. A., L. Wen, G. Lu, Z. Wu, J. Zhang, Y. Yang, Y. Zhu, and, L. Tong, (2010), Real-time forecast of the 2005 and 2007 summer severe floods in the Huaihe River Basin of China, J. Hydrol., 381 (1-2), 33-41.
42. Lu, M., U. Lall, A. Schwartz, and, H.-H. Kwon, (2013), Precipitation predictability associated with tropical moisture exports and circulation patterns for a major flood in France in 1995, Water Resour. Res., 49, 6381-6392, doi: 10.1002/wrcr.20512.
43. Marsh, T. J., (2004), The January 2003 flood on the Thames, Weather, 59, 59-62.
44. Merz, B., et al. (2014), Floods and climate: emerging perspectives for flood risk assessment and management, Natural Hazards and Earth System Sciences Discussions, 2 (2), 1559-1612.
45. Milly, P. C. D., R. T. Wetherald, K. A. Dunne, and, T. L. Delworth, (2002), Increasing risk of great floods in a changing climate, Nature, 415, 514-517.
46. Moore, B. J., P. J. Neiman, F. M. Ralph, and, F. E. Barthold, (2012), Physical processes associated with heavy flooding rainfall in Nashville, Tennessee, and vicinity during 1-2 May 2010: The role of an atmospheric river and mesoscale convective systems, Mon. Weather Rev., 140, 358-378.
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. Clim., 24, 2784-2800.
48. Munich Re (2012), Natural Catastrophes 2011: Analyses, Assessments, Positions, Topics Geo, Munich Re Reinsurance Co., Munich, Germany.
49. Nakamura, J., U. Lall, Y. Kushnir, A. W. Robertson, and, R. Seager, (2013), Dynamical structure of extreme floods in the U.S. Midwest and the United Kingdom, J. Hydrometeorol., 14, 485-504, doi: 10.1175/JHM-D-12-059.1.
50. Neiman, P. J., F. M. Ralph, G. A. Wick, J. D. Lundquist, and, M. D. Dettinger, (2008), Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the west coast of North America based on eight years of SSM/I satellite observations, J. Hydrometeorol., 9, 22-47.
51. Neiman, P. J., L. J. Schick, F. M. Ralph, M. Hughes, and, G. A. Wick, (2011), Flooding in western Washington, the connection to atmospheric rivers, J. Hydrometeorol., 12, 1337-1358.
52. Olsen, J. R., J. R. Stedinger, N. C. Matalas, and, E. Z. Stakhiv, (1999), Climate variability and flood frequency estimation for the Upper Mississippi and Lower Missouri rivers, J. Am. Water Resour. Assoc., 35, 1509-1523, doi: 10.1111/j.1752-1688.1999.tb04234.x.
53. Pickands, J., (1975), Statistical inference using extreme order statistics, Ann. Stat., 3, 119-131.
54. Ralph, F. M., T. Coleman, P. J. Neiman, R. J. Zamora, and, M. D. Dettinger, (2013), Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal Northern California, J. Hydrometeorol., 14, 443-459.
55. Ribatet, M., E. Sauquet, J.-M. Gresillon, and, T. B. M. J. Ouarda, (2007), A regional Bayesian POT model for flood frequency analysis, Stochastic Environ. Res. Risk Assess., 21, 327-339.
56. Romps, D. M., (2011), Response of tropical precipitation to global warming, J. Atmos. Sci., 68, 123-138.
57. Schneider, J. M., and, D. L. Ford Jr,. (2011), Evaluating PRISM precipitation grid data as possible surrogates for station data at four sites in Oklahoma, Okla. Acad. Sci. Proc., 90, 77-88.
58. Shane, R. M., and, W. R. Lynn, (1964), Mathematical model for flood risk evaluation, J. Hydraul. Div. Am. Soc. Civ. Eng., 90 (HY6), 4119-4122.
59. Slingo, J., et al. (2014), The Recent Storms and Floods in the UK, U. K. Met. Off. and Cent. for Ecol. and Hydrol, Exeter, Devon, U. K. [Available at http://www.metoffice.gov.uk/research/news/2014/uk-storms-and-floods.]
60. St. George, S., and, T. R. Ault, (2011), Is energetic decadal variability a stable feature of the central Pacific Coast's winter climate?, J. Geophys. Res., 116, D12102, doi: 10.1029/2010JD015325.
61. Ulbrich, U., T. Brucher, A. H. Fink, G. C. Leckebusch, A. Kruger, and, J. G. Pinto, (2003), The central European floods of August 2002: Part 1-Rainfall periods and floods development, Weather, 58, 371-377.
62. van den Honert, R. C., and, J. McAneney, (2011), The 2011 Brisbane Floods: Causes, impacts and implications, Water, 3, 1149-1173.
63. Villarini, G., F. Serinaldi, J. A. Smith, and, W. F. Krajewski, (2009), On the stationarity of annual flood peaks in the continental United States during the 20th century, Water Resour. Res., 45, W08417, doi: 10.1029/2008WR007645.
64. Ward, P. J., W. Beets, L. M. Bouwer, J. C. J. H. Aerts, and, H. Renssen, (2010), Sensitivity of river discharge to ENSO, Geophys. Res. Lett., 37, L12402, doi: 10.1029/2010GL043215.
65. Weigel, A., M. Liniger, and, C. Appenzeller, (2007), The discrete Brier and ranked probability skill scores, Mon. Weather Rev., 135 (1), 118-124.
66. Weller, G. B., D. S. Cooley, and, S. R. Sain, (2012), An investigation of the pineapple express phenomenon via bivariate extreme value theory, Environmetrics, 23, 420-439.
67. Wernli, H., and, H. C. Davies, (1997), A Lagrangian-based analysis of extratropical cyclones. I: The method and some applications, Q. J. R. Meteorol. Soc., 123, 467-489.
68. Zhu, Y., and, R. E. Newell, (1994), Atmospheric rivers and bombs, Geophys. Res. Lett., 21, 1999-2002.
69. Zhu, Y., and, R. E. Newell, (1998), A proposed algorithm for moisture fluxes from atmospheric rivers, Mon. Weather Rev., 126, 725-735.
70. Zong, Y., and, X. Chen, (2000), The 1998 Flood on the Yangtze, China, Nat. Hazards, 22, 165-184.