A Real-Time Regional Forecasting System Established for the South China Sea and Its Performance in the Track Forecasts of Tropical Cyclones during 2011–13

Abstract

A real-time regional forecasting system for the South China Sea (SCS), called the Experimental Platform of Marine Environment Forecasting (EPMEF), is introduced in this paper. EPMEF consists of a regional atmosphere model, a regional ocean model, and a wave model, and performs a real-time run four times a day. Output from the Global Forecast System (GFS) from the National Centers for Environmental Prediction (NCEP) is used as the initial and boundary conditions of two nested domains of the atmosphere model, which can exert a constraint on the development of small-and mesoscale atmospheric perturbations through dynamical downscaling. The forecasted winds at 10-m height from the atmosphere model are used to drive the ocean and wave models. As an initial evaluation, a census on the track predictions of 44 tropical cyclones (TCs) during 2011-13 indicates that the performance of EPMEF is very encouraging and comparable to those of other official agencies worldwide. In particular, EPMEF successfully predicted several abnormal typhoon tracks including the sharp recurving of Megi (2010) and the looping of Roke (2011). Further analysis reveals that the dynamically downscaled GFS forecasts from the most updated forecast cycle and the optimal combination of different microphysics and PBL schemes primarily contribute to the good performance of EPMEF in TC track forecasting. EPMEF, established primarily for research purposes with the potential to be implemented into operations, provides valuable information not only to the operational forecasters of local marine/meteorological agencies or international TC forecast centers, but also to other stakeholders such as the fishing industry and insurance companies.

Influence of water vapor distribution on the simulated track of Typhoon Hato (2017)

“…As shown in Fig. 7, the steering flow, estimated based on the approach of Peng et al (2015), was similar in CTL and Con_Q because the lateral boundary conditions were similar. However, unlike the horizontal WVC in the lower layer, the steering flow in Double_ SQ was not similar to that in CTL and Con_Q.…”

Analysis of the Gale in the Bohai Sea Caused by Tropical Cyclone “Yagi”

“…e outer layer included mideastern China and the Northwest Pacific, while the inner layer included North China as well as the Bohai Sea and Yellow Sea. e parameter settings used in the simulation, as found in Peng et al's study [35], are listed in Table 2 In order to analyze the effects of the underlying surface changes on the development of tropical depression Yagi, in the control experiment (CE), we ran the model without any changes. In sensitivity experiment 1 (SE_1), we changed the land use categories in the Bohai Sea and Yellow Sea from water to cropland in domain 2 (Figures 1(b) and 1(c)).…”

The Track and Accompanying Sea Wave Forecasts of the Supertyphoon Mangkhut (2018) by a Real-Time Regional Forecast System

“…RFSSME was established by the State Key Laboratory of Tropical Oceanology (LTO), SCSIO in 2016. With the newly developed forecasting technologies incorporated, RFSSME was developed from an older version of a real-time air-seawave forecasting system, which was also known as the Experimental Platform of Marine Environment Forecasting (EPMEF) (Peng et al 2015). RFSSME is an atmosphereocean-wave forecast system, which consists of three main subsystems: the atmosphere forecast (AF), the ocean forecast (OF) and the wave forecast (WF), with their data assimilation schemes incorporated, as schematically shown in Fig.…”

“…However, considerable forecast uncertainty still exists. Various factors, such as poor understanding of the physical processes (Fraedrich and Leslie 1989;Plu 2011;Peng et al 2014), inaccurate initial conditions (Leslie et al 1998;Bender et al 2007;Hsiao et al 2009), incomplete parameterization schemes (Rao and Prasad 2007;Khain and Lynn 2011), as well as their combination (Zhou et al 2013), contribute to the errors of TC track forecast. For instance, in 2015, the errors of TC track forecasts of 24, 48, and 72-h from the National Hurricane Center (NHC) are 50, 70 and 100 km, respectively, and those from the China Meteorological Administration (CMA) are 60, 120 and 180 km, respectively.…”