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Water Utility Climate Alliance White Paper Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change Downscaling options Downscaling-1. Development of regional climate change ensembles. This effort would be an extension of option GCM-1 that would vastly improve the characterization of uncertainty and confidence in regional projections. The accessibility of these regional projections would be optimized by adopting the highly successful community archive approaches in use by climate research centers such as Lawrence Berkeley National Laboratory and the National Center for Atmospheric Research. Downscaling-2. Development of RCM model components. This option would focus on reducing RCM disparities in representation of region-specific climate processes such as the North American Monsoon System, given accurate large-scale conditions, through development of new model components and modeling techniques. Downscaling-3. Development of statistical downscaling techniques for probabilistic downscaling, extremes, and daily data. This effort would be best applied in tandem with option GCM-1. It would improve uncertainty estimates of local climate change for variables critical to water utilities given large-scale changes captured by using a large number of GCM projections, and it would provide a community archive as in option Downscaling-1. Table S.2 summarizes key characteristics of each option. In conclusion, we think that there are substantial opportunities to improve our understanding of regional climate change using information that is currently available and climate model runs that will be conducted for the Intergovernmental Panel on Climate Change Fifth Assessment Report/Coupled Model Intercomparison Project, Phase 5 exercises. We also think the climate models will improve in many ways that will lead to increased confidence in the realism of their output and be useful to water managers. However, sizable changes in addressing the four dimensions of improvement desired by water managers – model agreement, narrow projection range, spatial scale, and time horizon − will likely take a decade or more to be realized. Since uncertainty will always be present, water resource managers will need to use decision analysis – how to make the best decisions we can about the management of water resources given what we know and what we do not know. Page S-7
Water Utility Climate Alliance White Paper Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change Table S.2. Summary of investment options for climate models Option Pros Cons Time period Costs GCM investment options GCM-1. Develop and enhance GCM ensembles GCM-2. Improve use of observations to constrain models’ projections GCM-3. Improve tropical Pacific modeling GCM-4. Evaluate decadal predictions Provide a rich set of scenarios Improve analysis of climate signal vs. model variability Improve observations over time May be best hope for reducing uncertainties Might narrow precipitation projections for North America Provide more reliable projections for next few decades Enhance ability to integrate decadal variability with climate change More model runs require lower model resolution Storage may be limiting May take decades Data assimilation technologically complex and computationally intensive Least chance of success Most costly option Predictive skill in forecasting these phenomena may be low Many methodological issues to be worked out regarding how to initialize the models 2–7 years $3–5 M over five years for 100 km resolution First results within 2 years Ocean modeling: 5–10 years Significant improvement may take longer $10–30 M over five years for 50-km Research on statistical methods: $2–5 M/yr GCM assimilation: $2−$10 M/yr per GCM Integration of data assimilation: $2–10 M/yr 5–15 years Analysis: $1–3 M/yr Projections could be available in 2 years Modeling: $5–10 M/yr < $1 M/yr initially; more later if science makes progress Page S-8
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