Spatially coherent trends of annual maximum daily precipitation in the United States

Geophysical Research Letters

Volumn 42, Issue 22, 2015, Pages 9781-9789

  Sun, Xun ^a   Lall, Upmanu ^a,b  

^a Columbia University ^*  (United States)

^b Department of Earth and Environmental Sciences   (United States)

Author keywords

extreme precipitation; hierarchical Bayesian clustering; trends

Indexed keywords

BAYESIAN NETWORKS;

DAILY PRECIPITATIONS; EXTREME PRECIPITATION; HETEROGENEOUS REGION; HIERARCHICAL BAYESIAN; HIERARCHICAL BAYESIAN MODELING; PRECIPITATION EXTREMES; SIMILAR TEMPORAL PATTERNS; TRENDS;

PRECIPITATION (METEOROLOGY);

BAYESIAN ANALYSIS; CLUSTER ANALYSIS; DIURNAL VARIATION; EXTREME EVENT; HETEROGENEITY; HIERARCHICAL SYSTEM; IDENTIFICATION METHOD; PATTERN RECOGNITION; PRECIPITATION ASSESSMENT; SPATIOTEMPORAL ANALYSIS; TREND ANALYSIS; WEATHER STATION;

MIDWEST; UNITED STATES;

EID: 84956944122     PISSN: 00948276     EISSN: 19448007     Source Type: Journal    
DOI: 10.1002/2015GL066483     Document Type: Article

References (40)

1. Akaike, H., (1974), New look at statistical-model identification, IEEE Trans. Autom. Control, 19 (6), 716-723.
2. Angel, J. R., and, F. A. Huff, (1997), Changes in heavy rainfall in Midwestern United States, J. Water Resour. Plann. Manage., 123 (4), 246-249.
3. Biernacki, C., and, G. Govaert, (1997), Using the classification likelihood to choose the number of clusters, Comput. Sci. Stat., 29, 451-457.
4. Biernacki, C., G. Celeux, and, G. Govaert, (2000), Assessing a mixture model for clustering with the integrated completed likelihood, IEEE Trans. Pattern Anal. Mach. Intell., 22 (7), 719-725.
5. Celeux, G., F. Forbes, C. P. Robert, and, D. M. Titterington, (2006), Deviance information criteria for missing data models, Bayesian Anal., 1 (4), 651-673.
6. Chen, X., Z. Hao, N. Devineni, and, U. Lall, (2014), Climate information based streamflow and rainfall forecasts for Huai River basin using hierarchical Bayesian modeling, Hydrol. Earth Syst. Sci., 18 (4), 1539-1548.
7. Cioffi, F., U. Lall, E. Rus, and, C. K. B. Krishnamurthy, (2014), Space-time structure of extreme precipitation in Europe over the last century, Int. J. Climatol., 35, 1749-1760.
8. DeIorio, M., and, C. P. Robert, (2002), Discussion of Spiegelhalter et al, J. R. Stat. Soc., Ser. B, 64, 629-630.
9. Devineni, N., U. Lall, N. Pederson, and, E. Cook, (2013), A tree-ring-based reconstruction of Delaware River basin streamflow using hierarchical Bayesian regression, J. Clim., 26 (12), 4357-4374.
10. Donat, M. G., et al., (2013), Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset, J. Geophys. Res. Atmos., 118, 2098-2118, doi: 10.1002/jgrd.50150.
11. Gelman, A., J. B. Carlin, H. S. Stern, and, D. B. Rubin, (2014), Bayesian Data Analysis, 3rd ed., Chapman and Hall, London.
12. Ghosh, S., and, B. K. Mallick, (2011), A hierarchical Bayesian spatio-temporal model for extreme precipitation events, Environmetrics, 22 (2), 192-204.
13. Hall, J., B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. Kjeldsen, J. Kriauciuniene, Z. Kundzewicz, and, M. Lang, (2014), Understanding flood regime changes in Europe: A state of the art assessment, Hydrol. Earth Syst. Sci., 18 (7), 2735-2772.
14. Homan, M. D., and, A. Gelman, (2014), The no-U-turn sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo, J. Mach. Learn. Res., 15 (1), 1593-1623.
15. 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 (2), 231-241.
16. Keim, B. D., (1999), Precipitation annual maxima as a measure of change in extreme rainfall magnitudes in the southeastern United States over the past century, Southeast. Geogr., 39 (2), 235-245.
17. Krishnamurthy, C. K. B., U. Lall, and, H.-H. Kwon, (2009), Changing frequency and intensity of rainfall extremes over India from 1951 to 2003, J. Clim., 22 (18), 4737-4746.
18. 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.
19. Kysely, J., L. Gaal, and, J. Picek, (2011), Comparison of regional and at-site approaches to modelling probabilities of heavy precipitation, Int. J. Climatol., 31 (10), 1457-1472.
20. Madsen, H., D. Lawrence, M. Lang, M. Martinkova, and, T. Kjeldsen, (2014), Review of trend analysis and climate change projections of extreme precipitation and floods in Europe, J. Hydrol., 519, 3634-3650.
21. Mass, C., A. Skalenakis, and, M. Warner, (2011), Extreme precipitation over the west coast of North America: Is there a trend?, J. Hydrometeorol., 12 (2), 310-318.
22. McLachlan, G., and, D. Peel, (2004), Finite Mixture Models, John Wiley, New York.
23. Parr, D., and, G. Wang, (2015), Hydrological changes in the U.S. Northeast using the Connecticut River Basin as a case study: Part 1. Modeling and analysis of the past, Global Planet. Change, 122, 208-222.
24. Petrow, T., and, B. Merz, (2009), Trends in flood magnitude, frequency and seasonality in Germany in the period 1951-2002, J. Hydrol., 371 (1), 129-141.
25. Pryor, S. C., J. A. Howe, and, K. E. Kunkel, (2009), How spatially coherent and statistically robust are temporal changes in extreme precipitation in the contiguous USA?, Int. J. Climatol., 29 (1), 31-45.
26. Renard, B., (2011), A Bayesian hierarchical approach to regional frequency analysis, Water Resour. Res., 47, W11513, doi: 10.1029/2010WR010089.
27. Renard, B., et al., (2008), Regional methods for trend detection: Assessing field significance and regional consistency, Water Resour. Res., 44, W08419, doi: 10.1029/2007WR006268.
28. Renard, B., X. Sun, and, M. Lang, (2013), Bayesian methods for non-stationary extreme value analysis, in Extremes in a Changing Climate: Detection, Analysis and Uncertainty, edited by, A. AghaKouchak, et al., pp. 39-95, Springer, Dordrecht, Netherlands.
29. Ross, T., and, N. Lott, (2013), A climatology of 1980-2003 extreme weather and climate events, Tech. Rep. 2003-01. [Available at http://www.ncdc.noaa.gov/billions/docs/lott-and-ross-2003.pdf.]
30. Sang, H. Y., and, A. E. Gelfand, (2009), Hierarchical modeling for extreme values observed over space and time, Environ. Ecol. Stat., 16 (3), 407-426.
31. Sankarasubramanian, A., and, U. Lall, (2003), Flood quantiles in a changing climate: Seasonal forecasts and causal relations, Water Resour. Res., 39 (5), 1134, doi: 10.1029/2002WR001593.
32. Schwarz, G., (1978), Estimating the dimension of a model, Ann. Stat., 6 (2), 461-464.
33. Shang, H., J. Yan, and, X. Zhang, (2011), El Nino-Southern Oscillation influence on winter maximum daily precipitation in California in a spatial model, Water Resour. Res., 47, W11507, doi: 10.1029/2011WR010415.
34. Smith, A. B., and, R. W. Katz, (2013), US billion-dollar weather and climate disasters: Data sources, trends, accuracy and biases, Nat. Hazards, 67 (2), 387-410.
35. Spiegelhalter, D. J., N. G. Best, B. R. Carlin, and, A. van der Linde, (2002), Bayesian measures of model complexity and fit, J. R. Stat. Soc., Ser. B, 64, 583-616.
36. Steinschneider, S., and, U. Lall, (2015), A hierarchical Bayesian regional model for nonstationary precipitation extremes in Northern California conditioned on tropical moisture exports, Water Resour. Res., 51, 1472-1492, doi: 10.1002/2014WR016664.
37. Sullivan, K., and, L. Uccellini, (2013), Service assessment: Hurricane/post-tropical cyclone Sandy, October 22-29, 2012, Natl. Oceanic and Atmos. Admin. [Available at http://www.nws.noaa.gov/os/assessments/pdfs/Sandy13.pdf.]
38. Sun, X., M. Thyer, B. Renard, and, M. Lang, (2014), A general regional frequency analysis framework for quantifying local-scale climate effects: A case study of ENSO effects on Southeast Queensland rainfall, J. Hydrol., 512, 53-68.
39. Sun, X., B. Renard, M. Thyer, S. Westra, and, M. Lang, (2015), A global analysis of the asymmetric effect of ENSO on extreme precipitation, J. Hydrol., 530, 51-65.
40. Villarini, G., J. A. Smith, M. L. Baeck, R. Vitolo, D. B. Stephenson, and, W. F. Krajewski, (2011), On the frequency of heavy rainfall for the Midwest of the United States, J. Hydrol., 400 (1-2), 103-120.