A Systems Perspective on the Environmental Prediction Enterprise

Our success to date with environmental prediction could be considered among humankind’s most remarkable developments over the past fifty years (Bauer et al. 2015). At present levels of prediction skill, the availability of useable prediction information has become a core capability and expectation of our society. Grounded in science and engineering, and aided by an array of cooperative agreements and data exchanges, it protects our lives and property, and helps us advance the general well-being of society. The guidance that flows from this enterprise is used in a myriad of our personal decisions and provides critical information to our agriculture, transportation, energy, business, and recreational sectors – that further act to safeguard and advance both our individual well-being as well as our grander societal interests. Considering 0-7 day “weather” forecasts alone, it is safe to say that this portion of the prediction enterprise impacts on the order of a billion people or more on a daily basis either through their direct decision making or via the support these forecasts provides for managing key resources and infrastructure. These benefits, which also include monetary components easily measured in $100Bs or more, is compounded when considering the developing skill, growing demand for, and use of environmental prediction guidance across additional and larger decision-support dimensions that include lead times ranging from weeks-decades, and that are typically applied to decisions concerning our long-term security, sustainability and prosperity.

Vast changes have occurred in the recent decade to the complexity and scope of our so-called “weather” enterprise. Given its everyday importance to the individual and foundational importance to society, there is reason to optimize our approaches for advancing the scope and capabilities of the “weather enterprise”. This essay highlights the following three points that may help to facilitate this optimization:

• The term “Weather”, as indicative of a narrow part of Earth System Science and a narrow part of the U.S.’s, and many other countries’, programmatic models, often represents a limiting perspective and factor to making progress on what has become more aptly described as Environmental Prediction (EP).
• The complexity and coupling of the social, programmatic, observation, modeling, analytic and multiple science discipline landscapes within the EP Enterprise necessitates a system engineeringapproach to optimize outcomes and limit vulnerabilities.
• The consideration of the enterprise as a data to information flow problem highlights opportunities and focal points to leverage that could considerably advance the societal benefits derived from the EP Enterprise.

A more generalized perspective on the advancement of Earth science and environmental prediction is offered by framing a simple equation involving the synthesis of observations, models and programmatics, that in turn yield science and applications benefits. Simplifications and derivatives of this equation can be used to highlight evolutionary developments in Earth System Science and Earth System Applications, help to distill key challenges and opportunities for further advances, and be used to motivate a recommendation for a milestone/decadal study focused on Earth System Applications, namely on optimizing the systems of observations, models and programmatics that deliver benefits from the broader EP enterprise.