Abstract

For over years, fundamental component and dataset in climate projection had been covered by general circulation models (GCMs) output mainly from the Coupled Model Inter-comparison Project (CMIP). Marine surface winds are an important output of GCMs and they provide input to marine forecasts and warning systems. Their accuracy have direct implications for marine safety, air-sea fluxes, and wave and ocean modellings. Western North Pacific (WNP) is known as a highly vulnerable region to oceanic and atmospheric hazards, such as storm surges, waves and typhoons. Therefore, this study aims to examine the quality of marine surface winds from CMIP5 and CMIP6 GCMs in the WNP and its sub-regions with respect to a reference data, and presents bias correction of marine surface winds for contributing to wave and ocean modelling communities.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/750mqrERbS8

Highlights

  • For over years, fundamental component and dataset in climate projection had been covered by general circulation models (GCMs) output mainly from the Coupled Model Inter-comparison Project (CMIP)

  • DATA AND METHOD Monthly marine surface winds for 30 years from January 1979 to December 2008 of the historical datasets from CMIP5 and CMIP6 GCMs are retrieved from the IPCC (Talyor et al, 2012). 60 ensembles from 21 GCMs for CMIP5 and 32 ensembles from 7 GCMs for CMIP6 are considered in the analysis

  • Due to the different resolutions of GCMs and ERA-Interim considered, the surface winds are regridded onto the same resolution (1o x 1o) over the domain

Read more

Summary

Introduction

Fundamental component and dataset in climate projection had been covered by general circulation models (GCMs) output mainly from the Coupled Model Inter-comparison Project (CMIP). DATA AND METHOD Monthly marine surface winds for 30 years from January 1979 to December 2008 of the historical datasets from CMIP5 and CMIP6 GCMs are retrieved from the IPCC (Talyor et al, 2012). 60 ensembles from 21 GCMs for CMIP5 and 32 ensembles from 7 GCMs for CMIP6 are considered in the analysis.

Objectives
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call