Academic journal article Air & Space Power Journal

Weather and the Calculated Risk: Exploiting Forecast Uncertainty for Operational Risk Management

Academic journal article Air & Space Power Journal

Weather and the Calculated Risk: Exploiting Forecast Uncertainty for Operational Risk Management

Article excerpt

Editorial Abstract:

Today's standard weather support lacks a description of forecast uncertainty, thus limiting the forecast's utility. However, significant scientific and technological advances now make it possible to overcome that limitation by applying weather-forecast uncertainty information to the Air Force's decision-making process. The authors employ cost-effective ensemble forecasting in two different scenarios to demonstrate how principles of operational risk management can yield marked improvements in combat capability (effectiveness) and conservation of resources (efficiency).

AIR FORCE SMART Operations 21 (AFSO21) has prompted a fresh look at ways to improve combat capability, including enhancing the decision-making process.1 Highly effective and efficient operations require optimal decision making in situations that involve risk of unfavorable outcomes. Such risk exists due to uncertainty in decision inputs. Operators routinely face a variety of inexact inputs, such as intelligence reports on enemy strength, projections on available logistics, and performance of weapon systems. This article explains how the uncertainty in one such decision input-the weather forecast-can be used within the principles of operational risk management (ORM) to improve combat capability by applying a new advancement called "ensemble forecasting."

Typically, Department of Defense (DOD) missions with weather vulnerabilities consider a single weather forecast, thus largely ignoring forecast uncertainty, which can often prove significant. Focusing attention on a single forecast leads to nonoptimal decisions.2 Failure to consider an objective description of the potential forecast error leaves an operator overly vulnerable to costly mistakes and the wasting of resources-a situation analogous to betting on a horse race without considering each horse's projected odds of winning.

Clearly, the absolute best information for weather-related decisions would indeed be a consistently perfect deterministic forecast (i.e., a single-valued prediction for a weather phenomenon). Unfortunately, deterministic forecasting is anything but perfect. Forecast skill varies greatly due to the challenge of predicting the incredibly complex atmospheric system that contains nonlinear hydrodynamic, thermodynamic, radiation, chemical, and physical interactions. In fact, it is incredible that we can predict the atmosphere at all.3

The inherent uncertainty of the weather can be described with a "stochastic forecast," which expresses a distribution or range of possibilities that defines the potential error in the deterministic forecast and that can come in many different forms and from many different sources. For example, weather climatology (i.e., seasonal conditions) is normally given stochastically, such as the average, minimum, and maximum monthly expected rainfall at a location.

The idea of including uncertainty as part of a forecast is nothing new.4 People recognized the potential value for applying stochastic forecasts within Air Force operations as early as the 1960s, but we have yet to capitalize upon it.5 Today's forecasting remains primarily deterministic because (1) application of deterministic weather for decision making is straightforward, (2) benefits from and methods of applying stochastic forecasts are not widely understood, and (3) production of robust stochastic forecasts for short-term forecasts (up to a few days) has not been practical or affordable. However, since advancements in science and technology currently support production of stochastic forecasts, now is the time for the Air Force to learn and pursue the advantages of this technique.

Production and Application of Stochastic Forecasts

The primary tool for meteorologists for the past 40 years has been computer-based, numerical weather prediction (NWP) modeling. Weather observations are analyzed and then fed into a complex algorithm that simulates atmospheric behavior over time to generate a single, modeled forecast that has a varying degree of accuracy. …

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