Wave climate simulation for southern region of the South China Sea

This study investigates long-term variability and wave characteristic trends in the southern region of the South China Sea (SCS). We implemented the state-of-the art WAVEWATCH III spectral wave model to simulate a 31-year wave hindcast. The simulation results were used to assess the inter-annual variability and long-term changes in the SCS wave climate for the period 1979 to 2009. The model was forced with Climate Forecast System Reanalysis winds and validated against altimeter data and limited available measurements from an Acoustic Wave and Current recorder located offshore of Terengganu, Malaysia. The mean annual significant wave height and peak wave period indicate the occurrence of higher wave heights and wave periods in the central SCS and lower in the Sunda shelf region. Consistent with wind patterns, the wave direction also shows southeasterly (northwesterly) waves during the summer (winter) monsoon. This detailed hindcast demonstrates strong inter-annual variability of wave heights, especially during the winter months in the SCS. Significant wave height correlated negatively with Niño3.4 index during winter, spring and autumn seasons but became positive in the summer monsoon. Such correlations correspond well with surface wind anomalies over the SCS during El Nino events. During El Niño Modoki, the summer time positive correlation extends northeastwards to cover the entire domain. Although significant positive trends were found at 95 % confidence levels during May, July and September, there is significant negative trend in December covering the Sunda shelf region. However, the trend appears to be largely influenced by large El Niño signals.     

Prediction of salinity intrusion in the sheltered estuary of Terengganu River in Malaysia using 1-D empirical intrusion model

Generally one dimensional(1-D) empirical salinity intrusion model is limited to natural alluvial estuary. However,this study attempts to investigate its ability to model a sheltered alluvial estuary of the Terengganu River in Malaysia. The constructed breakwater at the mouth of the river shelters the estuary from direct influence of the open sea. The salinity density along the estuary was collected during the wet and dry seasons for scenarios before and after the constructed breakwater. Moreover, the freshwater discharges, tidal elevations and bathymetry data were also measured as model inputs. A good fit was demonstrated between simulated and observed variables,namely salinity distribution and intrusion length for both scenarios. Thus, the results show that 1-D empirical salinity model can be utilized for sheltered estuarine condition at the Terengganu Estuary, but with an appropriate determination of an initial point. Furthermore, it was observed that the salinity intrusion in the study area is largely dependent on the freshwater discharge rather than tidal elevation fluctuations. The scale of the salinity intrusion length in the study area is proportional to the river discharge of the –1/2 power. It was appeared that the two lines of the 1-D empirical salinity model and discharge power based equation fitted well to each other, with the average predicted minimum freshwater discharge of 150 m3/s is going to be required to maintain acceptable salinity levels during high water slack(HWS) near the water intake station, which is located at 10.63 km from river mouth.     

Forecasting the equatorial Pacific sea surface temperatures by neural network models

We used neural network models to seasonally forecast the tropical Pacific sea surface temperature anomalies (SSTA) in the Ni?o 3.4 region (6 ^°S–6 ^°N, 120 ^°W–170 ^°W). The inputs to the neural networks (i.e., the predictors) were the first seven wind stress empirical orthogonal function (EOF) modes of the tropical Pacific (20 ^°S–20 ^°N, 120 ^°E–70 ^°W) for four seasons and the Ni?o 3.4 SSTA itself for the final season. The period of 1952–1981 was used for training the neural network models, and the period 1982–1992 for forecast validation. At 6-month lead time, neural networks attained forecast skills comparable to the other El Ni?o-Southern Oscillation (ENSO) models. Our results suggested that neural network models were viable for ENSO forecasting even at longer lead times of 9 to 12 months. We hypothesized that at these longer leads, the underlying relationship between the wind stress and Ni?o 3.4 SSTA became increasingly nonlinear. The neural network results were interpreted in light of current theories, e.g., the role of the “off-equatorial” Rossby waves in triggering the onset of an ENSO event and the delayed-oscillator theory in the development and termination of an ENSO event. Received: 31 October 1995 / Accepted: 25 July 1996     

Numerical case study of an extreme rainfall event during 9–11 December 2004 over the east coast of Peninsular Malaysia

Summary An exceptional rainstorm affected the eastern coast of Peninsular Malaysia during 9–11 December 2004 as a result of a westward propagating tropical disturbance known as the Borneo vortex. Rainfall totals near the storm center exceeded 600 mm and led to flash floods, loss of life and severe damage in the area. This study presents the results of a numerical simulation of this event using the fifth generation of the Penn State – NCAR Mesoscale Model (MM5). The model successfully simulated the synoptic circulation and reproduced the episode with comparable spatial patterns and total accumulated amount of precipitation to the observed. Various sensitivity experiments showed that the local topography is decisive in shaping the rainfall distribution during the storm episode. The role of the terrain elevation appears to be to block the westward progression of the system and inhibit excessive rainfall in the inland areas of Peninsular Malaysia. To the north of the storm center where coastal terrain elevation is relatively high, orography plays an important role in the rainfall by providing an additional forcing for moist air lifting. An additional fake dry simulation suggested that latent heat release is crucial for the development of the storm. Without latent heating, the vertical coupling of low-level convergence and upper level divergence is weakened and the vertical motion associated with the storm is suppressed.     

Simulation of tropical cyclone Vamei (2001) using the PSU/NCAR MM5 model

Summary In this study, a rare tropical cyclone Vamei was simulated using the non-hydrostatic version 3.6 of the Penn State University (PSU) – National Center for Atmospheric Research (NCAR) mesoscale model MM5. This unusual cyclone was generated on 26 December 2001 in an area close to the equator in the southern part of the South China Sea. The model was integrated for 80 h from 0000 UTC 26 December 2001 to 1800 UTC 29 December 2001. To examine the model performance, several important simulated fields including sea-level pressure, surface wind speed and precipitation were compared to observations. The model simulated track of the cyclone was also compared to the best track provided by the Joint Typhoon Warning Center (JWTC). Overall, the model performed reasonably well, particularly in simulating the cyclone track and precipitation amount and spatial distribution. The analysis of the model output indicated the important role of the latent heat flux in the genesis and intensification of tropical cyclone Vamei.     

Present-day regional climate simulation over Malaysia and western Maritime Continent region using PRECIS forced with ERA40 reanalysis

This study examines the performance of the regional climate model, PRECIS, in reproducing the historical seasonal mean climatology over the Malaysian region. The performance of the model in simulating the seasonal climate pattern of the temperature, precipitation and large-scale circulation was reasonably good. The biases of temperature are less than 2 °C in general, while the seasonal cycles match the observed pattern despite some differences in certain regions. However, the biases for precipitation were greater, particularly over the mountainous areas. These biases could be associated with the deficiencies of the model physics, related to the misrepresentation of the land–surface interaction and convective scheme. Furthermore, the model fails to simulate the mean sea-level pressure over the interior part of Borneo with a significant low-pressure centre. A higher magnitude of the moisture convergence and divergence simulated by the model also contributed to the biases of precipitation over Malaysia.