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Our Process

An end-to-end workflow for forecasting

Our process includes data collection, modeling, cyberinfrastructure, data science, visualization, and training Learn more below!

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STEP ONE

DATA COLLECTION

We have a strong sensor development, monitoring, and field data collection focus. High-quality data are a key step in reliable forecasting.

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STEP TWO

MODELING

We are experts in developing and using environmental models for a range of ecological systems across temporal and spatial scales. We use state-of-the-art cloud computation and have developed novel cyberinfrastructure for merging data and models to update forecasts

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STEP THREE

STATISTICS

We use advanced statistical models to quantify and identify the uncertainty associated with our predictions. Our goal is to develop transparent, robust predictions that clearly communicate what we know, and what we don’t.

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STEP FOUR

FORECASTING

The environmental variables we forecast provide critical services for society: e.g., forecasts of lake water quality are needed by managers to help provision drinking water; forecasts of tree carbon stocks are needed by forest managers and carbon markets; and more.

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STEP FIVE

TRANSLATION

We co-develop and disseminate forecasts to meet the multi-faceted needs of diverse end users.  We create easy-to-understand data and forecast visualizations that can transform natural resource management. 

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STEP SIX

TRAINING

We develop cutting-edge educational tools to teach students, decision-makers, and the broader public how to interpret, analyze, and generate environmental forecasts.

Bringing it altogether

Our collaborative team unites interdisciplinary expertise to innovate the science and application of forecasting while training our community and beyond.

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Our Research

Discover key projects we're working on

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