Modeling high-impact weather and climate: lessons from a tropical cyclone perspective

Abstract

Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding and capacity to model the underlying physical processes. This challenge is driving fresh approaches to assess highimpact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be adequate to: include relevant regional climate physical processes; resolve key impact parameters; and accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters.

Recent intense hurricane response to global climate change

“…We further compare the observed changes to recent climate simulations with the dynamical downscaling results of Bender et al (2010), Done et al (2012), and Wu and Zhao (2012).…”

“…Bender et al (2010) found that for each°C of global warming the proportion of Cat 4-5 hurricanes increased by *11 % and the proportion of Cat 1-2 hurricanes decreased by *7 %. Done et al (2012) applied Weibull and Generalized Pareto distributions to assess the expected changes in future North Atlantic hurricane extremes based on changes to the mean and variance of the truncated distribution predicted by the NCAR Nested Regional Climate Model (Done et al 2012). Both approaches showed that relatively modest increases in the mean (3 %) and standard deviation of (7 %) produced an increase in the proportion of Cat 4-5 hurricanes of *15 % per°C of global warming.…”

“…It is often assumed that this means negligible change in hurricane extremes, but this can easily be shown to be incorrect by fitting an extreme distribution to the tropical cyclone PDF and examining the changes in extremes resulting from small bulk changes. For example, by fitting a Weibull distribution to the current tropical cyclone PDF [see Done et al (2012) for discussion on the method] it can readily be shown that a change of 2-3 m s -1 in both the mean and standard deviation-similar to the resolution of the IBTrACS-produces a *20 % increase in the proportion (equivalent to doubling) of Cat 4-5 hurricanes. Such a sensitivity of the extremes to relatively small changes in the mean and standard deviation is well known and has been emphasized by the IPCC (2012, their Fig.…”

“…Obviously this linear increase cannot go on indefinitely as the proportion of Cat 4-5 hurricanes cannot exceed one. Table 2 compares the different values and base periods for the North Atlantic observations with the downscaling by Bender et al (2010) and Done et al (2012). No adjustment downward was made to the observed Atlantic trend due to analysis issues since North Atlantic intensity archives are reasonably accurate over the period (Kossin et al 2007).…”

“…The increases are substantial, approaching a doubling in frequency of Cat 4 and 5 hurricanes [based on the Saffir-Simpson classification, Simpson and Rielh (1981)] for each°C in global warming (Bender et al 2010;IPCC 2012;Done et al 2012). IPCC (2007) also concluded that the current 'warming of the climate system is unequivocal'.…”