Continuous rainfall generation for a warmer climate using observed temperature sensitivities

Journal of Hydrology

Volumn 544, Issue , 2017, Pages 575-590

  Wasko, Conrad ^a   Sharma, Ashish ^a  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Climate change; Extreme rainfall; NSRP; Stochastic rainfall generation; Temperature

Indexed keywords

CLIMATE CHANGE; CLIMATE MODELS; STOCHASTIC SYSTEMS; TEMPERATURE;

EXTREME RAINFALL; HYDROLOGIC MODELING; NSRP; PROBABILISTIC ASSESSMENTS; RAINFALL GENERATION; SIMULATED RAINFALL; STOCHASTIC RAINFALL GENERATIONS; TEMPERATURE SENSITIVITY;

RAIN;

CLIMATE CHANGE; EXTREME EVENT; FLOODING; HIGH TEMPERATURE; HYDROLOGICAL MODELING; PARAMETER ESTIMATION; SENSITIVITY ANALYSIS; STOCHASTICITY; TEMPERATURE EFFECT; WARMING;

AUSTRALIA;

EID: 85006306863     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2016.12.002     Document Type: Article

References (110)

1. Allen, M.R., Ingram, W.J., Constraints on future changes in climate and the hydrologic cycle. Nature 419 (2002), 224–232, 10.1038/nature01092.
2. Andrews, F.T., Croke, B.F.W., Jakeman, A.J., An open software environment for hydrological model assessment and development. Environ. Model. Softw. 26 (2011), 1171–1185, 10.1016/j.envsoft.2011.04.006.
3. Ball, J.E., The influence of storm temporal patterns on catchment response. J. Hydrol. 158 (1994), 285–303, 10.1016/0022-1694(94)90058-2.
4. Bárdossy, A., Bogardi, I., Matyasovszky, I., Fuzzy rule-based downscaling of precipitation. Theor. Appl. Climatol. 82 (2005), 119–129, 10.1007/s00704-004-0121-0.
5. Bárdossy, A., Stehlík, J., Caspary, H.J., Automated objective classification of daily circulation patterns for precipitation and temperature downscaling based on optimized fuzzy rules. Clim. Res. 23 (2002), 11–22, 10.3354/cr023011.
6. Bates, B., McLuckie, D., Westra, S., Johnson, F., Green, J., Mummery, J., Abbs, D., Climate Change Considerations. Australian Rainfall and Runoff, 2015, Book I. Engineers Australia, Barton, ACT.
7. Berg, P., Haerter, J.O., Thejll, P., Piani, C., Hagemann, S., Christensen, J.H., Seasonal characteristics of the relationship between daily precipitation intensity and surface temperature. J. Geophys. Res., 114, 2009, D18102, 10.1029/2009JD012008.
8. Berg, P., Moseley, C., Haerter, J.O., Strong increase in convective precipitation in response to higher temperatures. Nat. Geosci. 6 (2013), 181–185, 10.1038/ngeo1731.
9. Blenkinsop, S., Chan, S.C., Kendon, E.J., Roberts, N.M., Fowler, H.J., Temperature influences on intense UK hourly precipitation and dependency on large-scale circulation. Environ. Res. Lett., 10, 2015, 054021, 10.1088/1748-9326/10/5/054021.
10. Bordoy, R., Burlando, P., Stochastic downscaling of precipitation to high-resolution scenarios in orographically complex regions: 1. Model evaluation. Water Resour. Res. 50 (2014), 540–561, 10.1002/2012WR013289.
11. Boughton, W., Droop, O., Continuous simulation for design flood estimation—a review. Environ. Model. Softw. 18 (2003), 309–318, 10.1016/S1364-8152(03)00004-5.
12. Brath, A., Montanari, A., Moretti, G., Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty). J. Hydrol. 324 (2006), 141–153, 10.1016/j.jhydrol.2005.10.001.
13. Burlando, P., Rosso, R., Extreme storm rainfall and climatic change. Atmos. Res. 27 (1991), 169–189, 10.1016/0169-8095(91)90017-Q.
14. Burlando, P., Rosso, R., Comment on “Parameter estimation and sensitivity analysis for the modified Bartlett-Lewis rectangular pulses model of rainfall” by S. Islam et al. J. Geophys. Res. 96 (1991), 9391–9395, 10.1029/91JD00288.
15. Burton, A., Kilsby, C.G., Fowler, H.J., Cowpertwait, P.S.P., O'Connell, P.E., RainSim: a spatial–temporal stochastic rainfall modelling system. Environ. Model. Softw. 23 (2008), 1356–1369, 10.1016/j.envsoft.2008.04.003.
16. Chandler, R.E., A spectral method for estimating parameters in rainfall models. Bernoulli 3 (1997), 301–322, 10.2307/3318594.
17. Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W.J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A.J., Wehner, M., Long-term Climate Change: Projections, Commitments and Irreversibility. Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M., (eds.) Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 2013, Cambridge University Press, Cambridge, UK and New York, NY, USA, 1029–1136.
18. Conway, D., Jones, P.D., The use of weather types and air flow indices for GCM downscaling. J. Hydrol. 212–213 (1998), 348–361, 10.1016/S0022-1694(98)00216-9.
19. Coombes, P., Kuczera, G., Frost, A., O'Loughlin, G., Lees, S., The impact of rainwater tanks in the Upper Parramatta River catchment. Aust. J. Water Resour. 7 (2003), 121–129, 10.1080/13241583.2003.11465235.
20. Cowpertwait, P., Isham, V., Onof, C., Point process models of rainfall: developments for fine-scale structure. Proc. R Soc. A Math. Phys. Eng. Sci. 463 (2007), 2569–2587, 10.1098/rspa.2007.1889.
21. Cowpertwait, P., O'Connell, P., Metcalfe, A., Mawdsley, J., Stochastic point process modelling of rainfall. II. Regionalisation and disaggregation. J. Hydrol. 175 (1996), 47–65, 10.1016/S0022-1694(96)80005-9.
22. Cowpertwait, P., O'Connell, P., Metcalfe, A., Mawdsley, J., Stochastic point process modelling of rainfall. I. Single-site fitting and validation. J. Hydrol. 175 (1996), 17–46, 10.1016/S0022-1694(96)80004-7.
23. Cowpertwait, P.S.P., A generalized spatial-temporal model of rainfall based on a clustered point process. Proc. R. Soc. A Math. Phys. Eng. Sci. 450 (1995), 163–175, 10.1098/rspa.1995.0077.
24. Cowpertwait, P.S.P., Kilsby, C.G., O'Connell, P.E., A space-time Neyman-Scott model of rainfall: empirical analysis of extremes. Water Resour. Res. 38 (2002), 6-1–6-14, 10.1029/2001WR000709.
25. Cowpertwait, P.S.P., Lockie, T., Davis, M.D., A stochastic spatial-temporal disaggregation model for rainfall. J. Hydrol. 45 (2006), 1–12.
26. Diaz-Nieto, J., Wilby, R.L., A comparison of statistical downscaling and climate change factor methods: impacts on low flows in the River Thames, United Kingdom. Clim. Change 69 (2005), 245–268, 10.1007/s10584-005-1157-6.
27. Fatichi, S., Ivanov, V.Y., Caporali, E., Simulation of future climate scenarios with a weather generator. Adv. Water Resour. 34 (2011), 448–467, 10.1016/j.advwatres.2010.12.013.
28. Fealy, R., Sweeney, J., Statistical downscaling of precipitation for a selection of sites in Ireland employing a generalised linear modelling approach. Int. J. Climatol. 27 (2007), 2083–2094, 10.1002/joc.1506.
29. Fowler, H., Kilsby, C., O'Connell, P., A stochastic rainfall model for the assessment of regional water resource systems under changed climatic condition. Hydrol. Earth Syst. Sci. 4 (2000), 263–282.
30. Fowler, H.J., Blenkinsop, S., Tebaldi, C., Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int. J. Climatol. 27 (2007), 1547–1578, 10.1002/joc.1556.
31. Fowler, H.J., Kilsby, C.G., O'Connell, P.E., Burton, A., A weather-type conditioned multi-site stochastic rainfall model for the generation of scenarios of climatic variability and change. J. Hydrol. 308 (2005), 50–66, 10.1016/j.jhydrol.2004.10.021.
32. Frost, A., Srikanthan, R., Cowpertwait, P., 2004. Stochastic Generation of Point Rainfall Data at Subdaily Timescales: A Comparison of DRIP and NSRP.
33. Gyasi-Agyei, Y., Stochastic disaggregation of daily rainfall into one-hour time scale. J. Hydrol. 309 (2005), 178–190, 10.1016/j.jhydrol.2004.11.018.
34. Haerter, J.O., Berg, P., Unexpected rise in extreme precipitation caused by a shift in rain type?. Nat. Geosci. 2 (2009), 372–373, 10.1038/ngeo523.
35. Hardwick Jones, R., Westra, S., Sharma, A., Observed relationships between extreme sub-daily precipitation, surface temperature, and relative humidity. Geophys. Res. Lett., 37, 2010, L22805, 10.1029/2010GL045081.
36. Heneker, T.M., Lambert, M.F., Kuczera, G., A point rainfall model for risk-based design. J. Hydrol. 247 (2001), 54–71, 10.1016/S0022-1694(01)00361-4.
37. Ivancic, T.J., Shaw, S.B., Examining why trends in very heavy precipitation should not be mistaken for trends in very high river discharge. Clim. Change 133 (2015), 681–693, 10.1007/s10584-015-1476-1.
38. Johnson, F., Sharma, A., A nesting model for bias correction of variability at multiple time scales in general circulation model precipitation simulations. Water Resour. Res. 48 (2012), 1–16, 10.1029/2011WR010464.
39. Johnson, F., Sharma, A., Measurement of GCM skill in predicting variables relevant for hydroclimatological assessments. J. Clim. 22 (2009), 4373–4382, 10.1175/2009JCLI2681.1.
40. Kendon, E.J., Rowell, D.P., Jones, R.G., Buonomo, E., Robustness of future changes in local precipitation extremes. J. Clim. 21 (2008), 4280–4297, 10.1175/2008JCLI2082.1.
41. Kennedy, M., Turner, L., Canterford, R., Pearce, H., 1991. Temporal Distributions Within Rainfall Bursts. Melbourne, Australia.
42. Khaliq, M.N., Cunnane, C., Modelling point rainfall occurrences with the modified Bartlett-Lewis rectangular pulses model. J. Hydrol. 180 (1996), 109–138, 10.1016/0022-1694(95)02894-3.
43. Kilsby, C.G., Jones, P.D., Burton, A., Ford, A.C., Fowler, H.J., Harpham, C., James, P., Smith, A., Wilby, R.L., A daily weather generator for use in climate change studies. Environ. Model. Softw. 22 (2007), 1705–1719, 10.1016/j.envsoft.2007.02.005.
44. King, A.D., Klingaman, N.P., Alexander, L.V., Donat, M.G., Jourdain, N.C., Maher, P., Extreme rainfall variability in australia: patterns, drivers, and predictability. J. Clim. 27 (2014), 6035–6050, 10.1175/JCLI-D-13-00715.1.
45. Koutsoyiannis, D., Onof, C., Rainfall disaggregation using adjusting procedures on a Poisson cluster model. J. Hydrol. 246 (2001), 109–122, 10.1016/S0022-1694(01)00363-8.
46. Koutsoyiannis, D., Onof, C., Wheater, H.S., Multivariate rainfall disaggregation at a fine timescale. Water Resour. Res., 39, 2003, 1173, 10.1029/2002WR001600.
47. Kuczera, G., Lambert, M., Heneker, T., Jennings, S., Frost, A., Coombes, P., Joint probability and design storms at the crossroads. Aust. J. Water Resour. 10 (2006), 63–79, 10.1080/13241583.2006.11465282.
48. Lafon, T., Dadson, S., Buys, G., Prudhomme, C., Bias correction of daily precipitation simulated by a regional climate model: a comparison of methods. Int. J. Climatol. 33 (2013), 1367–1381, 10.1002/joc.3518.
49. Lall, U., Sharma, A., A nearest neighbor bootstrap for resampling hydrologic time series. Water Resour. Res. 32 (1996), 679–693, 10.1029/95WR02966.
50. Lenderink, G., Attema, J., A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands. Environ. Res. Lett., 10, 2015, 085001, 10.1088/1748-9326/10/8/085001.
51. Lenderink, G., Mok, H.Y., Lee, T.C., van Oldenborgh, G.J., Scaling and trends of hourly precipitation extremes in two different climate zones – Hong Kong and the Netherlands. Hydrol. Earth Syst. Sci. 15 (2011), 3033–3041, 10.5194/hess-15-3033-2011.
52. Lenderink, G., van Meijgaard, E., Increase in hourly precipitation extremes beyond expectations from temperature changes. Nat. Geosci. 1 (2008), 511–514, 10.1038/ngeo262.
53. Leonard, M., A Stochastic Space-Time Rainfall Model for Engineering Risk Assessment. 2010, The University of Adelaide.
54. Leonard, M., Lambert, M.F., Metcalfe, a.V., Cowpertwait, P.S.P., A space-time Neyman-Scott rainfall model with defined storm extent. Water Resour. Res., 44, 2008, W09402, 10.1029/2007WR006110.
55. Leonard, M., Metcalfe, A., Lambert, M., Kuczera, G., Implementing a space-time rainfall model for the Sydney region. Water Sci. Technol. 55 (2007), 39–47, 10.2166/wst.2007.093.
56. Loriaux, J.M., Lenderink, G., De Roode, S.R., Siebesma, a.P., Understanding convective extreme precipitation scaling using observations and an entraining plume model. J. Atmos. Sci. 70 (2013), 3641–3655, 10.1175/JAS-D-12-0317.1.
57. Maraun, D., Wetterhall, F., Ireson, A.M., Chandler, R.E., Kendon, E.J., Widmann, M., Brienen, S., Rust, H.W., Sauter, T., Themeßl, M., Venema, V.K.C., Chun, K.P., Goodess, C.M., Jones, R.G., Onof, C., Vrac, M., Thiele-Eich, I., Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Rev. Geophys., 48, 2010, RG3003, 10.1029/2009RG000314.
58. Meehl, G.a., Washington, W.M., Arblaster, J.M., Hu, A., Teng, H., Tebaldi, C., Sanderson, B.N., Lamarque, J.F., Conley, A., Strand, W.G., White, J.B., Climate system response to external forcings and climate change projections in CCSM4. J. Clim. 25 (2012), 3661–3683, 10.1175/JCLI-D-11-00240.1.
59. Mehrotra, R., Evans, J.P., Sharma, A., Sivakumar, B., Evaluation of downscaled daily rainfall hindcasts over Sydney, Australia using statistical and dynamical downscaling approaches. Hydrol. Res. 45 (2014), 226–249, 10.2166/nh.2013.094.
60. Mehrotra, R., Sharma, A., Development and application of a multisite rainfall stochastic downscaling framework for climate change impact assessment. Water Resour. Res., 46, 2010, W07526, 10.1029/2009WR008423.
61. Mehrotra, R., Westra, S., Sharma, A., Srikanthan, R., Continuous rainfall simulation: 2. A regionalized daily rainfall generation approach. Water Resour. Res., 48, 2012, W01536, 10.1029/2011WR010490.
62. Menabde, M., Seed, A., Harris, D., Austin, G., Multiaffine random field model of rainfall. Water Resour. Res. 35 (1999), 509–514, 10.1029/1998WR900020.
63. Menabde, M., Sivapalan, M., Modeling of rainfall time series and extremes using bounded random cascades and levy-stable distributions. Water Resour. Res. 36 (2000), 3293–3300, 10.1029/2000WR900197.
64. Milly, P.C.D., Betancourt, J., Falkenmark, M., Hirsch, R.M., Kundzewicz, Z.W., Lettenmaier, D.P., Stouffer, R.J., CLIMATE CHANGE: stationarity is dead: whither water management?. Science (80-.) 319 (2008), 573–574, 10.1126/science.1151915.
65. Milly, P.C.D., Betancourt, J., Falkenmark, M., Hirsch, R.M., Kundzewicz, Z.W., Lettenmaier, D.P., Stouffer, R.J., Dettinger, M.D., Krysanova, V., On Critiques of “Stationarity is Dead: Whither Water Management?”. Water Resour. Res. 51 (2015), 7785–7789, 10.1002/2015WR017408.
66. Molnar, P., Burlando, P., Preservation of rainfall properties in stochastic disaggregation by a simple random cascade model. Atmos. Res. 77 (2005), 137–151, 10.1016/j.atmosres.2004.10.024.
67. Montanari, A., Brath, A., Maximum likelihood estimation for the seasonal Neyman-Scott rectangular pulses model for rainfall. Claps, P., Siccardi, F., (eds.) Mediterranean Storms, Proceedings of the Plinius Conference ’99. GNDCI Publication No. 2012, 2000, Editoriale Bios, Cosenza, Italy, 297–310.
68. Moseley, C., Berg, P., Haerter, J.O., Probing the precipitation life cycle by iterative rain cell tracking. J. Geophys. Res. Atmos. 118 (2013), 13361–13370, 10.1002/2013JD020868.
69. O'Gorman, P.A., Precipitation extremes under climate change. Curr. Clim. Chang. Reports 1 (2015), 49–59, 10.1007/s40641-015-0009-3.
70. Onof, C., Chandler, R.E., Kakou, a., Northrop, P., Wheater, H.S., Isham, V., Rainfall modelling using Poisson-cluster processes: a review of developments. Stoch. Environ. Res. Risk Assess. 14 (2000), 0384–0411, 10.1007/s004770000043.
71. Panthou, G., Mailhot, A., Laurence, E., Talbot, G., Relationship between surface temperature and extreme rainfalls: a multi-time-scale and event-based analysis. J. Hydrometeorol. 15 (2014), 1999–2011, 10.1175/JHM-D-14-0020.1.
72. Paschalis, A., Molnar, P., Fatichi, S., Burlando, P., On temporal stochastic modeling of precipitation, nesting models across scales. Adv. Water Resour. 63 (2014), 152–166, 10.1016/j.advwatres.2013.11.006.
73. Paschalis, A., Molnar, P., Fatichi, S., Burlando, P., A stochastic model for high-resolution space-time precipitation simulation. Water Resour. Res. 49 (2013), 8400–8417, 10.1002/2013WR014437.
74. Pathiraja, S., Westra, S., Sharma, A., Why continuous simulation? The role of antecedent moisture in design flood estimation. Water Resour. Res., 48, 2012, W06534, 10.1029/2011WR010997.
75. Peel, M., Finlayson, B., McMahon, T., Updated world map of the Köppen-Geiger climate classification. Hydrol. Earth Syst. Sci. 11 (2007), 1633–1644.
76. Pegram, G.G.S., Clothier, A.N., Downscaling rainfields in space and time, using the String of Beads model in time series mode. Hydrol. Earth Syst. Sci. 5 (2001), 175–186, 10.5194/hess-5-175-2001.
77. Peleg, N., Morin, E., Stochastic convective rain-field simulation using a high-resolution synoptically conditioned weather generator (HiReS-WG). Water Resour. Res. 50 (2014), 2124–2139, 10.1002/2013WR014836.
78. Prudhomme, C., Reynard, N., Crooks, S., Downscaling of global climate models for flood frequency analysis: where are we now?. Hydrol. Process. 16 (2002), 1137–1150, 10.1002/hyp.1054.
79. Pui, A., Sharma, A., Mehrotra, R., Sivakumar, B., Jeremiah, E., A comparison of alternatives for daily to sub-daily rainfall disaggregation. J. Hydrol. 470–471 (2012), 138–157, 10.1016/j.jhydrol.2012.08.041.
80. Pui, A., Sharma, A., Santoso, A., Westra, S., Impact of the El Niño-southern oscillation, Indian Ocean dipole, and Southern annular mode on daily to subdaily rainfall characteristics in East Australia. Mon. Weather Rev. 140 (2012), 1665–1682, 10.1175/MWR-D-11-00238.1.
81. R Core Team, 2013. R: A Language and Environment for Statistical Computing.
82. Rodriguez-Iturbe, I., Cox, D.R., Isham, V., A point process model for rainfall: further developments. Proc. R. Soc. A Math. Phys. Eng. Sci. 417 (1988), 283–298, 10.1098/rspa.1988.0061.
83. Rodriguez-Iturbe, I., Cox, D.R., Isham, V., some models for rainfall based on stochastic point processes. Proc. R. Soc. A Math. Phys. Eng. Sci. 410 (1987), 269–288, 10.1098/rspa.1987.0039.
84. Schoof, J.T., Pryor, S.C., Downscaling temperature and precipitation: a comparison of regression-based methods and artificial neural networks. Int. J. Climatol. 21 (2001), 773–790, 10.1002/joc.655.
85. Sharma, A., Srikanthan, S., Continuous rainfall simulation: a nonparametric alternative. 30th Hydrology & Water Resources Symposium. 4–7 December 2006, Launceston, Tasmania, 2006, 86–91.
86. Sillmann, J., Kharin, V.V., Zwiers, F.W., Zhang, X., Bronaugh, D., Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J. Geophys. Res. Atmos. 118 (2013), 2473–2493, 10.1002/jgrd.50188.
87. Singleton, A., Toumi, R., Super-Clausius-Clapeyron scaling of rainfall in a model squall line. Q. J. R. Meteorol. Soc. 139 (2013), 334–339, 10.1002/qj.1919.
88. Srikanthan, R., McMahon, T.A., Stochastic generation of annual, monthly and daily climate data: a review. Hydrol. Earth Syst. Sci. 5 (2001), 653–670, 10.5194/hess-5-653-2001.
89. Stephens, E., Day, J.J., Pappenberger, F., Cloke, H., Precipitation and floodiness. Geophys. Res. Lett. 42 (2015), 10316–10323, 10.1002/2015GL066779.
90. Stephens, G.L., L'Ecuyer, T., Forbes, R., Gettlemen, A., Golaz, J.-C., Bodas-Salcedo, A., Suzuki, K., Gabriel, P., Haynes, J., Dreary state of precipitation in global models. J. Geophys. Res., 115, 2010, D24211, 10.1029/2010JD014532.
91. Stern, R.D., Coe, R., A model fitting analysis of daily rainfall data. J. R. Stat. Soc. Ser. A, 147, 1984, 1, 10.2307/2981736.
92. Trenberth, K.E., Changes in precipitation with climate change. Clim. Res. 47 (2011), 123–138, 10.3354/cr00953.
93. Trenberth, K.E., Dai, A., Rasmussen, R.M., Parsons, D.B., The changing character of precipitation. Bull. Am. Meteorol. Soc. 84 (2003), 1205–1217, 10.1175/BAMS-84-9-1205.
94. Trenberth, K.E., Shea, D.J., Relationships between precipitation and surface temperature. Geophys. Res. Lett., 32, 2005, L14703, 10.1029/2005GL022760.
95. Utsumi, N., Seto, S., Kanae, S., Maeda, E.E., Oki, T., Does higher surface temperature intensify extreme precipitation?. Geophys. Res. Lett., 38, 2011, L16708, 10.1029/2011GL048426.
96. Wasko, C., Pui, A., Sharma, A., Mehrotra, R., Jeremiah, E., Representing low-frequency variability in continuous rainfall simulations: a hierarchical random Bartlett Lewis continuous rainfall generation model. Water Resour. Res. 51 (2015), 9995–10007, 10.1002/2015WR017469.
97. Wasko, C., Sharma, A., Steeper temporal distribution of rain intensity at higher temperatures within Australian storms. Nat. Geosci. 8 (2015), 527–529, 10.1038/ngeo2456.
98. Wasko, C., Sharma, A., Quantile regression for investigating scaling of extreme precipitation with temperature. Water Resour. Res. 50 (2014), 3608–3614, 10.1002/2013WR015194.
99. Wasko, C., Sharma, A., Johnson, F., Does storm duration modulate the extreme precipitation-temperature scaling relationship?. Geophys. Res. Lett. 42 (2015), 8783–8790, 10.1002/2015GL066274.
100. Wasko, C., Sharma, A., Westra, S., Reduced spatial extent of extreme storms at higher temperatures. Geophys. Res. Lett. 43 (2016), 4026–4032, 10.1002/2016GL068509.
101. Westra, S., Alexander, L., Zwiers, F., Global increasing trends in annual maximum daily precipitation. J. Clim. 26 (2013), 3904–3918, 10.1175/JCLI-D-12-00502.1.
102. Westra, S., Evans, J.P., Mehrotra, R., Sharma, A., A conditional disaggregation algorithm for generating fine time-scale rainfall data in a warmer climate. J. Hydrol. 479 (2013), 86–99, 10.1016/j.jhydrol.2012.11.033.
103. Westra, S., Fowler, H.J., Evans, J.P., Alexander, L., Berg, P., Johnson, F., Kendon, E.J., Lenderink, G., Roberts, N.M., Future changes to the intensity and frequency of short-duration extreme rainfall. Rev. Geophys. 52 (2014), 522–555, 10.1002/2014RG000464.
104. Westra, S., Mehrotra, R., Sharma, A., Srikanthan, R., Continuous rainfall simulation: 1. A regionalized subdaily disaggregation approach. Water Resour. Res., 48, 2012, W01535, 10.1029/2011WR010489.
105. Westra, S., Sisson, S.A., Detection of non-stationarity in precipitation extremes using a max-stable process model. J. Hydrol. 406 (2011), 119–128, 10.1016/j.jhydrol.2011.06.014.
106. Wilks, D.S., Use of stochastic weathergenerators for precipitation downscaling. Wiley Interdiscip. Rev. Clim. Chang. 1 (2010), 898–907, 10.1002/wcc.85.
107. Wilks, D.S., Multisite generalization of a daily stochastic precipitation generation model. J. Hydrol. 210 (1998), 178–191, 10.1016/S0022-1694(98)00186-3.
108. World Meteorological Organization, 2011. Guide to Climatological Practices. Geneva.
109. Zhao, W., Khalil, M.A.K., The relationship between precipitation and temperature over the contiguous United States. J. Clim. 6 (1993), 1232–1236, 10.1175/1520-0442(1993) 006<1232:TRBPAT>2.0.CO;2.
110. Zheng, F., Westra, S., Leonard, M., Opposing local precipitation extremes. Nat. Clim. Chang. 5 (2015), 389–390, 10.1038/nclimate2579.