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<strong>Water</strong> <strong>Utility</strong> <strong>Climate</strong> Alliance White Paper<br />

<strong>Options</strong> <strong>for</strong> <strong>Improving</strong> <strong>Climate</strong> <strong>Modeling</strong> <strong>to</strong> <strong>Assist</strong> <strong>Water</strong> <strong>Utility</strong> Planning <strong>for</strong> <strong>Climate</strong> Change<br />

Executive Summary<br />

This report, which was commissioned by the <strong>Water</strong> <strong>Utility</strong> <strong>Climate</strong> Alliance (WUCA), concerns<br />

how investments in the science of climate change, and in particular climate modeling, can best<br />

be directed <strong>to</strong> help improve the quality of science so that it may be more useful <strong>to</strong> water utilities<br />

and other possible users in adapting <strong>to</strong> climate change. The main focus of this report is the<br />

identification of investments in the science of climate change that, in the opinion of the authors,<br />

can best improve the science <strong>to</strong> support adaptation.<br />

How utilities are studying climate change and in<strong>for</strong>mation needs<br />

A number of WUCA members including Denver <strong>Water</strong>, the New York City Department of<br />

Environmental Protection, the Portland <strong>Water</strong> Bureau, and Seattle Public Utilities have examined<br />

climate change impacts within their water management systems. Many have used the “scenario<br />

approach,” meaning they have selected at least three global climate models (GCMs), often under<br />

different greenhouse gas emissions scenarios, in conjunction with statistical and dynamic<br />

downscaling methods <strong>to</strong> capture a wide range of potential changes in climate in specific<br />

locations. Reflecting current confidence in the state of the science, most utilities did not examine<br />

probabilities of changes in climate at the watershed scale or changes in extreme events.<br />

In general, WUCA members prefer <strong>to</strong> have climate model projections at the same space and time<br />

scales as their system models <strong>to</strong> best capture the physical processes and operations associated<br />

with their supplies. Table S.1 summarizes the scale in<strong>for</strong>mation from the utilities. These spatial<br />

scales range from a few kilometers <strong>to</strong> thousands of kilometers. Most of the utility models <strong>for</strong><br />

which we obtained in<strong>for</strong>mation run on daily time steps. Even if scales aligned, many utilities<br />

would need hydrologic models <strong>to</strong> convert temperature and precipitation projections from the<br />

models <strong>to</strong> estimates of runoff and other attributes of water resources.<br />

The science of climate modeling<br />

GCMs model, as their title implies, global climate. They use computer codes that solve<br />

mathematical equations based on scientific understanding of the processes which govern the<br />

Earth’s climate and model the atmosphere, the oceans, the land surface, and sea ice. Because of<br />

the complexity of modeling, GCMs divide the world in<strong>to</strong> grid cells that are typically one hundred<br />

<strong>to</strong> a few hundred kilometers across. With such large grids, important climate processes such as<br />

thunders<strong>to</strong>rms are unresolved and modeled via simplified process models. However, such<br />

processes are incorporated in<strong>to</strong> GCM downscaling <strong>to</strong>ols.

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