Joint Probabilistic Wind–Rainfall Model for Tropical Cyclone Hazard Characterization
Publication: Journal of Structural Engineering
Volume 143, Issue 3
Abstract
Often, rainfall-induced flooding has been the greatest factor influencing property loss and loss of life in major tropical cyclone events. However, a lack of an extensive historical rainfall record has long served as an obstacle to furthering the understanding of tropical cyclone–related rainfall. Advances have been made in the last few decades in rainfall observational techniques, allowing for the development of robust statistical tropical cyclone rainfall models. However, these current models are unable to capture statistical variability in rainfall intensities (i.e., only mean rainfall rates can be predicted) or they cannot simulate rainfall over land. A new tropical cyclone rainfall model is developed herein using satellite rainfall observations, in which the tropical cyclone rainfall is modeled through a Weibull distribution conditioned upon maximum surface wind speed and sea surface temperature (SST). Satellites are able to capture rainfall observations in the most extreme events, unlike surface rain gauges, which tend to fail under high winds, thereby allowing for the consideration of the rainfall climatology of stronger tropical cyclone events. The rainfall model developed herein was then coupled with state-of-the-art probabilistic tropical cyclone models and future projected climate change scenarios, allowing for the concomitant characterization of tropical cyclone hazards (wind speed, rain rate, and storm size) and the assessment of possible changes in the tropical cyclone hazards in a future climate state. In results obtained from tropical cyclone simulations performed herein under a postulated future climate scenario, in which no technology or policies have been implemented to reduce greenhouse gas emissions, tropical cyclones are projected to intensify. The intensification seen in the simulation results is accompanied by a reduction in size, meaning the magnitude of the extreme wind and rainfall hazards are projected to increase, whereas the affected area is projected to decrease. Additionally, this simulated intensification implies events that are considered extreme in the current climate will occur more frequently in the future climate scenario, paving the way for possible exceedance of critical design values.
Get full access to this article
View all available purchase options and get full access to this article.
References
Allan, R. P., and Soden, B. J. (2008). “Atmospheric warming and the amplification of precipitation extremes.” Science, 321(5895), 1481–1484.
ASCE. (2010). “Minimum design loads for building and other structures.” ASCE Standard 7–10, Reston, VA.
Baik, J.-J., DeMaria, M., and Raman, S. (1990). “Tropical cyclone simulations with the Betts convective adjustment scheme. II: Sensitivity experiments.” Mon. Weather Rev., 118(3), 529–541.
Bender, M. A., et al. (2010). “Modeled impact of anthropogenic warming on the frequency of intense Atlantic hurricanes.” Science, 327(5964), 454–458.
Biondini, R. (1976). “Cloud motion and rainfall statistics.” J. Appl. Meteorol., 15(3), 205–224.
Clarke, L., Edmonds, J., Jacoby, H., Pitcher, H., Reilly, J., and Richels, R. (2007). “Scenarios of greenhouse gas emissions and atmospheric concentrations.”, U.S. Dept. of Energy Publications, Washington, DC.
Darling, R. W. R. (1991). “Estimating probabilities of hurricane wind speeds using a large-scale empirical model.” J. Clim., 4(10), 1035–1046.
Dudhia, J., et al. (2005). PSU/NCAR mesoscale modeling system tutorial class notes and user’s guide: MM5 modeling system version, Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, State College, PA.
Elsner, J. B., Kossin, J. P., and Jagger, T. H. (2008). “The increasing intensity of the strongest tropical cyclones.” Nature, 455(7209), 92–95.
Emanuel, K. A. (1987). “The dependence of hurricane intensity on climate.” Nature, 326(6112), 483–485.
Emanuel, K. A. (2008). “The hurricane-climate connection.” Bull. Am. Meteorol. Soc., 89(5), ES10–ES20.
Emanuel, K. A., Ravela, S., Vivant, E., and Risi, C. (2006). “A statistical deterministic approach to hurricane risk assessment.” Bull. Am. Meteorol. Soc., 87(3), 299–314.
Evans, J. L., Ryan, B. F., and McGregor, J. L. (1994). “A numerical exploration of the sensitivity of tropical cyclone rainfall intensity to sea surface temperature.” J. Clim., 7(4), 616–623.
Fujino, J., Nair, R., Kainuma, M., Masui, T., and Matsuoka, Y. (2006). “Multi-gas mitigation analysis on stabilization scenarios using aim global model.” Energy J., 27(3), 343–353.
Groisman, P. Y., et al. (1999). “Changes in the probability of heavy precipitation: Important indicators of climatic change.” Clim. Change, 42(1), 243–283.
Hagen, A. B., Strahan-Sakoskie, D., and Luckett, C. (2012). “A reanalysis of the 1944–53 Atlantic hurricane seasons—The first decade of aircraft reconnaissance.” J. Clim., 25(13), 4441–4460.
Hijioka, Y., Matsuoka, Y., Nishimoto, H., Masui, T., and Kainuma, M. (2008). “Global GHG emission scenarios under GHG concentration stabilization targets.” J. Global Environ. Eng., 13(1), 97–108.
Huffman, G. J., Adler, R. F., Bolvin, D. T., and Nelkin, E. J. (2010). “The TRMM multi-satellite precipitation analysis (TMPA).” Satellite rainfall applications for surface hydrology, M. Gebremichael and F. Hossain, eds., Springer, Greenbelt, MD, 3–22.
International Code Council. (2012). International plumbing code, Delmar Cengage Learning, Country Club Hills, IL.
Jarvinen, B., Neumann, C., and Davis, M. (1984). “A tropical cyclone data type for the north Atlantic basin, 1886-1983: Contents, limitations, and uses.”, National Oceanic and Atmospheric Administration, Miami.
Kaplan, J., and DeMaria, M. (1995). “A simple empirical model for predicting the decay of tropical cyclone winds after landfall.” J. Appl. Meteorol., 34(11), 2499–2512.
Knutson, T. R., et al. (2010). “Tropical cyclones and climate change.” Nat. Geosci., 3(3), 157–163.
Knutson, T. R., and Tuleya, R. E. (2004). “Impact of CO2 induced warming on simulated hurricane intensity and precipitation: Sensitivity to the choice of climate model and convective parameterization.” J. Clim., 17(18), 3477–3495.
Koutsoyiannis, D. (2004). “Statistics of extremes and estimation of extreme rainfall. I: Theoretical investigation.” Hydrol. Sci. J., 49(4), 575–590.
Kurihara, Y., Tuleya, R. E., and Bender, M. A. (1998). “The GFDL hurricane prediction system and its performance in the 1995 hurricane season.” Mon. Weather Rev., 126(5), 1306–1322.
Landsea, C. W. (2000). “Climate variability of tropical cyclones: Past, present and future.” Storms, Vol. 1, Routledge Press, London, 220–241.
Landsea, C. W., et al. (2004a). “The Atlantic hurricane database reanalysis project: Documentation for the 1851–1910 alterations and additions to the HURDAT database.” Hurricanes and typhoons: Past, present and future, R. J. Murname and K. B. Liu, eds., Columbia University Press, New York, 177–221.
Landsea, C. W., et al. (2004b). “A reanalysis of hurricane Andrew’s intensity.” Bull. Am. Meteorol. Soc., 85(11), 1699–1712.
Landsea, C. W., et al. (2008). “A reanalysis of the 1911-20 Atlantic hurricane database.” J. Clim., 21(10), 2138–2168.
Landsea, C. W., et al. (2012). “A reanalysis of the 1921-30 Atlantic hurricane database.” J. Clim., 25(3), 865–885.
Langousis, A., and Veneziano, D. (2009). “Theoretical model of rainfall in tropical cyclones for the assessment of long-term risk.” J. Geophys. Res. Atmos., 114(D2), 1–11.
Levinson, D., Vickery, P., and Resio, D. (2010). “A review of the climatological characteristics of landfalling gulf hurricanes for wind, wave, and surge hazard estimation.” Ocean Eng., 37(1), 13–25.
Li, X., and Gao, S. (2012). Precipitation modeling and quantitative analysis, Springer, Berlin.
Lonfat, M., Marks, F. D., and Chen, S. S. (2004). “Precipitation distribution in tropical cyclones using the tropical rainfall measuring mission (TRMM) microwave imager: A global perspective.” Mon. Weather Rev., 132(7), 1645–1660.
Lonfat, M., Rogers, R., Marchok, T., and Marks, F. D., Jr. (2007). “A parametric model for predicting hurricane rainfall.” Mon. Weather Rev., 135(9), 3086–3097.
Mudd, L., Wang, Y., Letchford, C., and Rosowsky, D. (2014). “Assessing climate change impact on the U.S. East Coast Hurricane hazard: Temperature, frequency, and track.” Nat. Hazards Rev., 04014001.
Nateghi, R., Guikema, S., and Quiring, S. M. (2014). “Power outage estimation for tropical cyclones: Improved accuracy with simpler models.” Risk Anal., 34(6), 1069–1078.
Pachauri, R. K. (2008). “Climate change 2007: Synthesis report. “,” Intergovernmental Panel on Climate Change, Geneva.
Pachauri, R. K. (2014). “Climate change 2014: Synthesis report. “,” Intergovernmental Panel on Climate Change, Geneva.
Rappaport, E. N. (2000). “Loss of life in the United States associated with recent Atlantic tropical cyclones.” Bull. Am. Meteorol. Soc., 81(9), 2065–2073.
Rayner, N., et al. (2003). “Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century.” J. Geophys. Res. Atmos. (1984-2012), 108(D14), 1–37.
Riahi, K., Grubler, A., and Nakicenovic, N. (2007). “Scenarios of long-term socioeconomic and environmental development under climate stabilization.” Technol. Forecasting Soc. Change, 74(7), 887–935.
Smith, S. J., and Wigley, T. (2006). “Multi-gas forcing stabilization with minicam.” Energy J., 27(3), 373–391.
Sugi, M., Noda, A., and Sato, N. (2002). “Influence of the global warming on tropical cyclone climatology: An experiment with the JMA global model.” J. Meteorol. Soc. Jpn., 80(2), 249–272.
Tokioka, T., et al. (1995). “A transient CO2 experiment with the MRI CGCM: Quick report.” J. Meteorol. Soc. Jpn., 73(4), 817–826.
Tuleya, R. E., DeMaria, M., and Kuligowski, R. J. (2007). “Evaluation of GFDL and simple statistical model rainfall forecasts for US landfalling tropical storms.” Weather Forecasting, 22(1), 56–70.
U.S. Census Bureau. (2011). “2010 Census demographic profile summary file.” U.S. Dept. of Commerce, Washington, DC.
Van de Brink, H., and Konnen, G. (2011). “Estimating 10000-year return values from short time series.” Int. J. Climatol., 31(1), 115–126.
Van Vuuren, D. P., et al. (2007). “Stabilizing greenhouse gas concentrations at low levels: An assessment of reduction strategies and costs.” Clim. Change, 81(2), 119–159.
Vickery, P. J., and Lavelle, F. M. (2014). “The effects of warm Atlantic Ocean sea surface temperatures on the ASCE 7-10 design wind speeds.” Proc., Conf. on Advances in Hurricane Engineering, Applied Technology Council, Structural Engineering Institute, Reston, VA, 13–22.
Vickery, P. J., Skerlj, P., and Twisdale, L. (2000). “Simulation of hurricane risk in the US using empirical track model.” J. Struct. Eng., 1222–1237.
Watson, C. C., and Johnson, M. E. (2004). “Hurricane loss estimation models: Opportunities for improving the state of the art.” Bull. Am. Meteorol. Soc., 85(11), 1713–1726.
Wilks, D. S. (1989). “Rainfall intensity, the Weibull distribution, and estimation of daily surface runoff.” J. Appl. Meteorol., 28(1), 52–58.
Wilson, P., and Toumi, R. (2005). “A fundamental probability distribution for heavy rainfall.” Geophys. Res. Lett., 32(14), 1–4.
Wise, M., et al. (2009). “Implications of limiting CO2 concentrations for land use and energy.” Science, 324(5931), 1183–1186.
Woolhiser, D. A., and Roldan, J. (1982). “Stochastic daily precipitation models. II: A comparison of distributions of amounts.” Water Resour. Res., 18(5), 1461–1468.
Information & Authors
Information
Published In
Journal of Structural Engineering
Volume 143 • Issue 3 • March 2017
Copyright
©2016 American Society of Civil Engineers.
History
Received: Oct 28, 2015
Accepted: Sep 1, 2016
Published online: Oct 18, 2016
Published in print: Mar 1, 2017
Discussion open until: Mar 18, 2017
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.