A Dynamic Decision Model Applied to Hurricane Landfall

Abstract

The decision to prepare for an oncoming hurricane is typically framed as a static cost:loss problem, based on a strike-probability forecast. The value of waiting for updated forecasts is therefore neglected. In this paper, the problem is reframed as a sequence of interrelated decisions that more accurately represents the situation faced by a decision maker monitoring an evolving tropical cyclone. A key feature of the decision model is that the decision maker explicitly anticipates and plans for future forecasts whose accuracy improves as lead time declines. A discrete Markov model of hurricane travel is derived from historical tropical cyclone tracks and combined with the dynamic decision model to estimate the additional value that can be extracted from existing forecasts by anticipating updated forecasts, rather than incurring an irreversible preparation cost based on the instantaneous strike probability. The value of anticipating forecasts depends on the specific alternatives and cost profile of each decision maker, but conceptual examples for targets at Norfolk, Virginia, and Galveston, Texas, yield expected savings ranging up to 8% relative to repeated static decisions. In real-time decision making, forecasts of improving information quality could be used in combination with strike-probability forecasts to evaluate the trade-off between lead time and forecast accuracy, estimate the value of waiting for improving forecasts, and thereby reduce the frequency of false alarms.

Is It Time to Go Yet? Understanding Household Hurricane Evacuation Decisions from a Dynamic Perspective

“…Lastly, we explicitly address the costs of evacuation in a household's evacuation decision. Although Regnier and Harr (2006) have developed an analogous dynamic evacuation decision model, they have done so from an emergency management perspective as opposed to the household standpoint as we have here.…”

Supply chain planning for hurricane response with wind speed information updates

“…Examples include a simulation based optimization approach to hurricane evacuation planning for Ocean City, Maryland [11], a methodology for establishing evacuation zones in the New Orleans, Louisiana area [12], and a Markov decision model that uses hurricane predictions to determine when and if an evacuation should be ordered [13]. For a comprehensive review of hurricane evacuation planning and management protocols, the reader is referred to [14,15].…”

Diagnosing the Relative Impact of “Sneaks,” “Phantoms,” and Volatility in Sequences of Lagged Ensemble Probability Forecasts with a Simple Dynamic Decision Model

“…Lagged forecasts as a general concept have been investigated in a handful of contexts (e.g., Hoffman and Kalnay 1983;Dalcher et al 1988;Elsberry and Dobos 1990;Hamill 2003;Regnier and Harr 2006;Lawrence and Hansen 2007;Lu et al 2007;Mittermaier 2007;McLay 2008;Pinson et al 2009;Yuan et al 2009;Zsoter et al 2009). 1 McLay (2008) specifically investigates sequences of lagged numerical weather prediction (NWP) ensemble-derived probability forecasts.…”

“…The value of dynamic decision models for meteorological problems has been demonstrated by a number of studies (e.g., Katz and Murphy 1982;Murphy et al 1985;Epstein and Murphy 1988;Wilks 1991;Katz 1993;Regnier and Harr 2006). However, a sequence of lagged NWP probability forecasts is a medium for dynamic decision making that has received little attention [only Regnier and Harr (2006) and McLay (2008) analyze decision making specific to this medium].…”