Wave Hindcast for the Neighbouring Seas of Korea Based on Loosely Coupled Wave-Tide-Surge Model

A hindcast simulation of 75 typhoons and winter monsoons which affected the coastal areas of Korean Peninsula is performed by use of a third generation ocean wave prediction model, WAM-cycle 4 model, loosely coupled with a com-bined tide and surge model. Typhoon wind fields are derived from the planetary marine boundary layer model for effective neutral winds embedding the vortical storm wind from the parameterized Rankin vortex type model in the limited areas of the overall modeled region. The hindcasted results illustrate that significant wave heights (SWH) considering the wave-tide-surge coupled process are significantly different from the results via the decoupled case especially in the region of the estuaries of the Changjiang Estuary, The Hangzhou Bay, and the southwestern tip of Korean Peninsula. This extensive model simulation is the first attempt to investigate the strong wave-tide-surge interaction for the shallow depth area along the coasts of the Yellow Sea and the East China Sea Continental shelf.

Utilize cloud computing to support dust storm forecasting

The simulations and potential forecasting of dust storms are of significant interest to public health and environment sciences.Dust storms have interannual variabilities and are typical disruptive events.The computing platform for a dust storm forecasting operational system should support a disruptive fashion by scaling up to enable high-resolution forecasting and massive public access when dust storms come and scaling down when no dust storm events occur to save energy and costs.With the capability of providing a large,elastic,and virtualized pool of computational resources,cloud computing becomes a new and advantageous computing paradigm to resolve scientific problems traditionally requiring a large-scale and high-performance cluster.This paper examines the viability for cloud computing to support dust storm forecasting.Through a holistic study by systematically comparing cloud computing using Amazon EC2 to traditional high performance computing(HPC)cluster,we find that cloud computing is emerging as a credible solution for(1)supporting dust storm forecasting in spinning off a large group of computing resources in a few minutes to satisfy the disruptive computing requirements of dust storm forecasting,(2)performing high-resolution dust storm forecasting when required,(3)supporting concurrent computing requirements,(4)supporting real dust storm event forecasting for a large geographic domain by using recent dust storm event in Phoniex,05 July 2011 as example,and(5)reducing cost by maintaining low computing support when there is no dust storm events while invoking a large amount of computing resource to perform high-resolution forecasting and responding to large amount of concurrent public accesses.