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WACCEM: Water Cycle and Climate Extremes Modeling

This work aims to advance predictive understanding

predictive understanding

Predictive understanding refers to the ability of a system, typically an artificial intelligence or machine learning model, to anticipate future events or outcomes based on historical data and patterns.

Source: Source

of water cycle processes and their variations and changes. Our ultimate goal is to improve predictability of water availability and understand society’s vulnerability to extreme water events. Guided by three overarching science questions, our research focuses on large-scale circulation, mesoscale convective systems,

mesoscale convective system (MCS)

A collection of thunderstorms that act as a system. An MCS can spread across an entire state and may appear as a solid line, a broken line, or a cluster of cells that can last more than 12 hours.

Source: NOAA Source

and multiscale interactions between convection and large-scale circulation.

Keywords	atmospheric circulation, climate extremes, climate extreme Significant deviations or anomalies from typical weather patterns and conditions, observed over extended periods such as seasons or even longer durations. Source: National LIbrary of Medicine Source mesoscale mesoscale Size scale referring to weather systems smaller than synoptic-scale systems but larger than storm-scale systems. Horizontal dimensions generally range from around 50 miles to several hundred miles. Squall lines, MCCs, and MCSs are examples of mesoscale weather systems Source: NOAA Source convection, multiscale interactions, numerical models, precipitation, water cycle
TYPE	Scientific Focus Area

Keywords

atmospheric circulation, climate extremes, mesoscale convection, multiscale interactions, numerical models, precipitation, water cycle

TYPE

Scientific Focus Area

Principal Investigator (PI)

Ruby Leung

Lead Institution

Other Collaborators

National Center for Atmospheric Research Pennsylvania State University University of Maryland

Methods for better evaluating how well climate models simulate storms require tracking the modeled storms. Photo by Zhe Feng, Pacific Northwest National Laboratory. (Image credit: Zhe Feng, Pacific Northwest National Laboratory)

For more information

Ruby Leung
Pacific Northwest National Laboratory

https://climatemodeling.science.energy.gov/projects/water-cycle-and-climate-extremes-modeling