Thursday, 10 January 2013: 3:45 PM
Ballroom B (Austin Convention Center)
In this study, projections of possible future changes in ocean surface significant wave heights (Hs) that correspond to changes in mean sea level pressure (MSLP) as simulated in the CMIP5 experiments are obtained statistically. A multivariate regression model with lagged dependent variable is used to represent the relationship between 6-hourly ocean surface significant wave heights (Hs) and the corresponding 6-hourly MSLP fields (including a geostrophic wind energy index). Being positive values and not normally distributed, both wave heights and the geostrophic wind energy index are separately subjected to a data adaptive Box-Cox transformation before being used in the model fitting. The statistical model is calibrated using the ERA-Interim reanalysis of Hs and MSLP fields for 1981-2000, and is validated using the ERA-Interim reanalysis of Hs and MSLP for 2001-2010. The relationship is then used to project 6-hourly Hs using 6-hourly MSLP fields taken from the CMIP5 archive. Annual means and maxima of Hs are derived from the resulting 6-hourly Hs and then analyzed to infer changes therein. Historical, RCP4.5 and RCP8.5 scenario simulations by 20 global climate models are analysed in this study. The use of multi-model, multi-scenario simulations makes it possible for us to assess the robustness of climate change signal, and to quantify the inter-model and forcing-scenario uncertainties in the resulting projections.
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