P. G. Remya

Wave hindcast experiments in the Indian Ocean using MIKE 21 SW model

Wave prediction and hindcast studies are important in ocean engineering, coastal infrastructure development and management. In view of sparse and infrequent in-situ observations, model derived hindcast wave data can be used for the assessment of wave climate in offshore and coastal areas. In the present study, MIKE 21 SW Model has been used to carry out wave hindcast experiments in the Indian Ocean. Model runs have been made for the year 2005 using QuickSCAT scatterometer winds blended with ECMWF model winds. In order to study the impact of southern ocean swells, the model has been run in two different domains, with the southern boundary being shifted far south for the Domain 60S model. The model simulated wave parameters have been validated by comparing with buoy and altimeter data and various statistical yardsticks have been employed to quantify the validation. Possible reason for the poorer performance of the model in the Arabian Sea has also been pointed out.

Validation and Intercomparison of SARAL/AltiKa and PISTACH-Derived Coastal Wave Heights Using In-Situ Measurements

SARAL/AltiKa, the first Ka-band altimeter, now provides an opportunity to study wave characteristics in the worlds coastal ocean with improved accuracy. In the present work, AltiKa-derived significant wave heights (Hs) in the coastal ocean and inland water bodies have been analyzed using in-situ measurements. Analysis shows that AltiKa measured Hs agree well with the in-situ measurements with high correlation (0.98), low bias (6 cm), and low RMSE (19 cm) in the coastal ocean, and the performance is highly consistent across different coastal zones in the three tropical oceans. AltiKa performance is found to be very good (RMSE = 24 cm and correlation = 0.94) near to the coast (<;2 km). In addition to the evaluation of AltiKa Hs, another coastal altimetry product, Innovative Processing System Prototype for Coastal and Hydrology Applications (PISTACH)-derived Hs using Jason-2 altimeter, has also been validated with in-situ measurements. The OCE3 retracking algorithm provided in PISTACH is able to improve the Jason-2 Hs in the 100-25 km coastal zone. None of the retracking algorithms showed significant improvement of Hs in the 0-10 km coastal zone.

An assessment of wind forcing impact on a spectral wave model for the Indian Ocean

The focus of the present study is the assessment of the impact of wind forcing on the spectral wave model MIKE 21 SW in the Indian Ocean region. Three different wind fields, namely the ECMWF analyzed winds, the ECMWF blended winds, and the NCEP blended winds have been used to drive the model. The wave model results have been compared with in-situ observations and satellite altimeter data. This study also evaluated the performance of the wind products during local phenomenon like sea breeze, since it has a significant impact on the wave prediction in the Indian coastal region. Hence we explored the possibility of studying the impact of diurnal variation of winds on coastal waves using different wind fields. An analysis of the model performance has also been made during high wind conditions with the inference that blended winds generate more realistic wave fields in the high wind conditions and are able to produce the growth and decay of waves more realistically.

Teleconnection between the North Indian Ocean high swell events and meteorological conditions over the Southern Indian Ocean

The link between North Indian Ocean (NIO) high swell events and the meteorological conditions over the Southern Indian Ocean (SIO) is explored in this article, using a combination of in-situ measurements and model simulations for the year 2005. High waves, without any sign in the local winds, sometimes cause severe flooding events along the south-west coast of India, locally known as the Kallakkadal events and cause major societal problems along the coasts. In-situ observations report ten high swell events in NIO during 2005. Our study confirm that these events are caused by the swells propagating from south of 30°S. In all cases, 3-5 days prior to the high swell events in NIO, we observed a severe low pressure system, called the Cut-Off Low (COL) in the Southern Ocean. These COLs are quasi-stationary in nature, providing strong (∼25 ms−1) and long duration (∼3 days) surface winds over a large fetch; essential conditions for the generation of long period swells. The intense equator ward winds associated with COLs in the SIO trigger the generation of high waves, which propagate to NIO as swells. Furthermore, these swells cause high wave activity and sometimes Kallakkadal events along the NIO coastal regions, depending on the local topography, angle of incidence and tidal conditions. Our study shows that such natural hazards along the NIO coasts can be forecasted at least 2 days in advance if the meteorological conditions of the SIO are properly monitored. This article is protected by copyright. All rights reserved.

Numerical simulation and observations of very severe cyclone generated surface wave fields in the north Indian Ocean

Accurate wave forecast is most needed during tropical cyclones as it has adverse effects on the entire marine activities. The present work evaluates the performance of a wave forecasting system under very severe cyclonic conditions for the Indian Ocean. The wave model results are validated separately for the deep water and shallow water using in-situ observations. Satellite altimeter observations are also utilized for validation purpose. The results show that the model performance is accurate (SI < 26% and correlation > 0.9) and consistent during very severe cyclones (categories 4 and 5). The power of the cyclone waves which hit in the eastern Indian coastal region is also analysed and it reveals that the coastal region which lies on the right side of the cyclone track receives high amount wave energy throughout the cyclone period. The study also says that the abnormal waves mostly present on the right side of the track.

Impact Of Diurnal Variation Of Winds On Coastal Waves Off South East Coast Of India

The land-sea breeze systems, the most interesting phenomena observed at coastal regions, have significant impact on the costal wave characteristics. Present study also focuses the diurnal variations of winds and its impact on wave parameters like significant wave height and mean wave period off Ennore port located in the south east coast of India The impact of the diurnal variation of winds on complex wave patterns in the coastal regions of Indian Ocean have been addressed earlier also. In the present study an attempt has been made to explore the impact of diurnal variation of winds on coastal waves using numerical model forced with European Centre for Medium Range Weather Forecasts (ECMWF) and National Centre for Environmental Prediction (NCEP) blended wind fields. It has been observed that most of the time, the ECMWF blended wind field reproduces the diurnal variation.

Modification of a linear regression-based multi-model super-ensemble technique and its application in forecasting of wave height during extreme weather conditions

ABSTRACT In this study, we focus on the improvement of wave forecast of the Indian coastal region using a multi-model ensemble technique. Generally, a number of wave forecast are available for the same region from different wave models. The main objective of this study is to merge the wave forecasts available at Indian National Centre for Ocean Information Services from different wave models to obtain an improved wave forecast using a multi-model super-ensemble method [Krishnamurti et al. 1999. Improved weather and seasonal climate forecasts from multi-model super-ensemble. Science. 285:1548–1550] during extreme weather conditions and to modify Krishnamurthy’s techniques and validate with observations for a better prediction. Here, Multi-grid WAVEWATCH III, Simulating WAves Nearshore and MIKE 21 Spectral Waves are used for the generation of wave forecast. We propose a modification of Krishnamurthy’s linear regression-based ensemble model. By using both of these ensemble techniques, we perform a multi-model ensemble forecasting of significant wave height up to 24-h lead time in the Indian Ocean for three different cyclones (Nilofar, Hudhud and Phailin) and during the southwest monsoon. A comparison of ensemble predictions and individual model predictions with the actual observations showed generally satisfactory performance of the chosen tools. At the time of severe cyclones such as Hudhud and Phailin, our modified technique shows significantly better prediction than the linear regression-based ensemble technique.