CLIMATE MODEL DEVELOPMENT FOR OPERATIONAL PREDICTION

For the past several decades, increasingly complex climate models of increasing spatial resolution were developed as research tools to study scientific questions regarding the processes responsible for climate variability, change, and predictability (e.g., Delworth et al., 2006; Gent et al., 2011; Kiehl et al., 1998). Other than the development of seasonal prediction tools, the motivation for these advancements was primarily, until recently, to improve understanding of processes and reduce biases, not to address any particular societal need for climate predictions, although researchers realized that the results might have societal implications (NRC, 1979). More recently climate model development has been driven more by a desire to better understand the general impacts of anthropogenic climate change, and several recent reports (e.g., NRC, 2010b, Advancing the Science of Climate Change) and the U.S. Global Change Research Program 2012-2021 strategic plan (USGCRP, 2012) have noted that both scientific advancement and addressing specific societal needs should be viewed as drivers of climate model development.

The user community needs easily accessible and comprehensible climate information updated on a regular basis. One resource for users interested in decadal and longer time scales has evolved from a series of climate model comparison (or intercomparison) projects (MIPs), organized by the international research community primarily for the purpose of advising international assessments of climate change that are conducted periodically by the Intergovernmental Panel on Climate Change (IPCC, 2007a,b,c). These MIPs are described in more detail in Chapter 8. They encourage the participating model development groups to conduct a series of numerical climate change simulations that conform to a prescribed protocol, with standardized outputs placed in a distributed quasipublic archive. These simulations are increasingly used not only by IPCC and the research community but by a broad range of users as source material for assessments of climate variability and change and as inputs to other models specialized to particular applications.

A second resource for users is “operational” climate forecasts (see Box 9.1) for lead times of months to a few years. Several weather services around the world have developed climate models specifically to provide scheduled, real-time, forecast products. For example, the U.S. National Weather Service has developed the Climate Forecast System (Saha et al., 2006, 2010) to produce operational climate predictions with lead times of up to 9 months. The second generation of this system went into operation in March 2011. The European Centre for Medium-Range Weather Forecasts has developed a seasonal climate prediction system, soon to be in its fourth generation



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