Assessment of Uncertainty in Multi-Model Means of Downscaled South Florida Precipitation for Projected (2019-2099) Climate

South Florida precipitation

Assessment of Uncertainty in Multi-Model Means of Downscaled South…

South Florida resource management, particularly the Everglades restoration effort, is beginning to consider projections of precipitation from multiple climate models for decision‐making. Because precipitation changes can significantly affect the Everglades ecosystem, characterization of precipitation projection uncertainty is important for resource management decisions, and reduction of uncertainty is desired for better decision‐making. Though uncertainty of precipitation projections has been characterized for many regions, uncertainty has not been sufficiently quantified for South Florida. This study builds upon prior results for projected Florida precipitation by considering recent climate model simulations, seasonal and spatial information, and uncertainty quantification and reduction. We identify the multi‐model mean change in South Florida precipitation and characterize the uncertainty of 37 statistically downscaled Coupled Model Intercomparison Project Phase 5 models. For 2019–2045, there is a likely (over 60% of ensemble members) increase in South Florida annual mean precipitation owing to a likely to very likely (near 90% of ensemble members) increase in dry season (November, December, and January) precipitation, while wet season (June, July, and August) shows a more likely than not (over 50% of ensemble members) decrease in precipitation in the southern region and increase in precipitation in the northern region of South Florida. As South Florida agencies are on the verge of including precipitation projections in their upcoming planning horizon, this information will aid South Florida climate data users in decisions influenced by future rainfall.

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Infanti, JMKirtman, BPAumen, NGStamm, JPolsky, CAssessment of uncertainty in multi‐model means of downscaled South Florida precipitation for projected (2019–2099) climateInt J Climatol2020402764– 2777https://doi.org/10.1002/joc.6365