On the roles of the northeast cold surge, the Borneo vortex, the Madden-Julian Oscillation, and the Indian Ocean Dipole during the extreme 2006/2007 flood in southern Peninsular Malaysia

The mid-December 2006 to late January 2007 flood in southern Peninsular Malaysia was the worst flood in a century and was caused by three extreme precipitation episodes. These extreme precipitation events were mainly associated with strong northeasterly winds over the South China Sea. In all cases, the northeasterlies penetrated anomalously far south and followed almost a straight trajectory. The elevated terrain over Sumatra and southern Peninsular Malaysia caused low-level convergence. The strong easterly winds near Java associated with the Rossby wave-type response to Madden-Julian Oscillation (MJO) inhibited the counter-clockwise turning of the northeasterlies and the formation of the Borneo vortex, which, in turn, enhanced the low-level convergence over the region. The abrupt termination of the Indian Ocean Dipole (IOD) in December 2006 played a secondary role as warmer equatorial Indian Ocean helped in the MJO formation.

Surface freshwater from Bay of Bengal runoff and Indonesian Throughflow in the Tropical Indian Ocean

According to recent estimates, the annual total continental runoff into the Bay of Bengal (BoB) is about 2950 km 3, which is more than half that into the entire tropical Indian Ocean (IO). Here we use climatological observations to trace the seasonal pathways of near surface freshwater from BoB runoff and Indonesian Throughflow (ITF) by removing the net contribution from precipitation minus evaporation. North of 20 degrees S, the amount of freshwater from BoB runoff and ITF changes with season in a manner consistent with surface currents from drifters. BoB runoff reaches remote regions of the Arabian Sea; it also crosses the equator in the east to join the ITF. This freshwater subsequently flows west across the southern tropical IO in the South Equatorial Current.

Atmospheric boundary-layer across Hadley and Ferrel cells over the Indian Ocean

A Southern Ocean Pilot cruise covering the latitudes from 10 degrees N to 56 degrees S in the open Indian Ocean was carried out during January February 2004. Surface and upper air data collected during this cruise are reported here. It is shown that the broad features of the atmosphere, in particular that of temperature, follow the tropical and mid-latitude weather expected during January February in this region. However, the atmospheric boundary-layer shows large variations, both in its height and structure between tropics and high latitudes. Strong influence of the surface heat flux on boundary layer structure is clearly seen. Humidity field reveals several local maxima and minima, suggesting a laminated atmosphere with air from different sources moving almost unmixed in adjacent layers.

Latitude variation of boundary layer height over Indian Ocean during pre- and First Field Phase (FFP-98) of INDOEX

This paper describes the results of the measurement of the Marine Boundary Layer (MBL) height from spectral analysis of the u and v components of the wind and from CLASS/radiosonde temperature profiles. The data were collected on ORV Sagar Kanya during the pre-INDOEX (27 December 1996 through 31 January 1997) and FFP-98 (18 February to 31 March 1998) over the latitude range 15 degrees N to 14 degrees S and 15 degrees N to 20 degrees S respectively. During the pre-INDOEX, the MBL heights gradually decrease from 2.5 km at 13 degrees N to around 500 to 600 m at 10 degrees S, Similar results are observed in the return track. The MBL heights (0.5 to 1 km) obtained during FFP-98 are less compared to those obtained during pre-INDOEX. The MBL heights during FFP-98 are less compared to the pre-INDOEX and are believed to be due to the presence of stratus, stratocumulus and cumulus clouds during the cruise period, compared to a relatively cloud free pre-INDOEX cruise.

Indian Ocean dipole mode events in an ocean general circulation model

The evolution of the dipole mode (DM) events in the Indian Ocean is examined using an ocean model that is driven by the NCEP fluxes for the period 1975-1998. The positive DM events during 1997, 1994 and 1982 and negative DM events during 1996 and 1984-1985 are captured by the model and it reproduces both the surface and subsurface features associated with these events. In its positive phase, the DM is characterized by warmer than normal SST in the western Indian Ocean and cooler than normal SST in the eastern Indian Ocean. The DM events are accompanied by easterly wind anomalies along the equatorial Indian Ocean and upwelling-favorable alongshore wind anomalies along the coast of Sumatra. The Wyrtki jets are weak during positive DM events, and the thermocline is shallower than normal in the eastern Indian Ocean and deeper in the west. This anomaly pattern reverses during negative DM events. During the positive phase of the DM easterly wind anomalies excite an upwelling equatorial Kelvin wave. This Kelvin wave reflects from the eastern boundary as an upwelling Rossby wave which propagates westward across the equatorial Indian Ocean. The anomalies in the eastern Indian Ocean weaken after the Rossby wave passes. A similar process excites a downwelling Rossby wave during the negative phase. This Rossby wave is much weaker but wind forcing in the central equatorial Indian Ocean amplifies the downwelling and increases its westward phase speed. This Rossby wave initiates the deepening of the thermocline in the western Indian Ocean during the following positive phase of the DM. Rossby wave generated in the southern tropical Indian Ocean by Ekman pumping contributes to this warming. Concurrently, the temperature equation of the model shows upwelling and downwelling to be the most important mechanism during both positive events of 1994 and 1997. (C) 2002 Elsevier Science Ltd. All rights reserved.

Longwave radiative forcing of Indian Ocean tropospheric aerosol

A spectrally resolved discrete-ordinates radiative transfer model is used to calculate the change in downwelling surface and top-of-the-atmosphere (TOA) outgoing longwave (3.9-500 mum) radiative fluxes induced by tropospheric aerosols of the type observed over the Indian Ocean during the Indian Ocean Experiment (INDOEX). Both external and internal aerosol mixtures were considered. Throughout the longwave, the aerosol volume extinction depends more strongly on relative humidity than in most of the shortwave (0.28-3.9 mum), implying that particle growth factors and realistic relative humidity profiles must be taken into account when modeling the longwave radiative effects of aerosols. A typical boundary layer aerosol loading, with a 500-nm optical depth of 0.3, will increase the downwelling longwave flux at the surface by 7.7 W m(-2) over the clean air case while decreasing the outgoing longwave radiation by 1.3 W m(-2). A more vertically extended aerosol loading, exhibiting a high opacity plume between 2 and 3 km above the surface and having a typical 500-nm optical depth of 0.7, will increase the downwelling longwave flux at the surface by 11.2 W m(-2) over the clean air case while decreasing the outgoing longwave radiation by 2.7 W m(-2). For a vertically extended aerosol profile, approximately 30% of the TOA radiative forcing comes from sea salt and approximately 60% of the forcing comes from the combination of sea salt and dust. The remaining forcing is from anthropogenic constituents. These results are for the external mixture. For an internal mixture, TOA longwave forcings can be up to a factor of two larger. Therefore, to complete our understanding of this region's longwave aerosol radiative properties, more detailed information is needed about aerosol mixing states. These longwave radiative effects partially offset the large shortwave aerosol radiative forcing and should be included in regional and global climate modeling simulations.

Modeling Indian Ocean circulation: Bay of Bengal fresh water plume and the Arabian Sea Mini Warm Pool

The Indian subcontinent divides the north Indian Ocean into two tropical basins, namely the Arabian Sea and the Bay of Bengal. The Arabian Sea has high salinity whereas the salinity of the Bay of Bengal is much lower due to the contrast in freshwater forcing of the two basins. The freshwater received by the Bay in large amounts during the summer monsoon through river discharge is flushed out annually by ocean circulation. After the withdrawal of the summer monsoon, the Ganga – Brahmaputra river plume flows first along the Indian coast and then around Sri Lanka into the Arabian Sea creating a low salinity pool in the southeastern Arabian Sea (SEAS). In the same region, during the pre-monsoon months of February – April, a warm pool, known as the Arabian Sea Mini Warm Pool (ASMWP), which is distinctly warmer than the rest of the Indian Ocean, takes shape. In fact, this is the warmest region in the world oceans during this period. Simulation of the river plume and its movement as well as its implications to thermodynamics has been a challenging problem for models of Indian Ocean. Here we address these issues using an ocean general circulation model – first we show that the model is capable of reproducing fresh plumes in the Bay of Bengal as well as its movement and then we use the model to determine the processes that lead to formation of the ASMWP. Hydrographic observations from the western Bay of Bengal have shown the presence of a fresh plume along the northern part of the Indian coast during summer monsoon. The Indian Ocean model when forced by realistic winds and climatological river discharge reproduces the fresh plume with reasonable accuracy. The fresh plume does not advect along the Indian coast until the end of summer monsoon. The North Bay Monsoon Current, which flows eastward in the northern Bay, separates the low salinity water from the more saline southern parts of the bay and thus plays an important role in the fresh water budget of the Bay of Bengal. The model also reproduces the surge of the fresh-plume along the Indian coast, into the Arabian Sea during northeast monsoon. Mechanisms that lead to the formation of the Arabian Sea Mini Warm Pool are investigated using several numerical experiments. Contrary to the existing theories, we find that salinity effects are not necessary for the formation of the ASMWP. The orographic effects of the Sahyadris (Western Ghats) and resulting reduction in wind speed leads to the formation of the ASMWP. During November – April, the SEAS behave as a low-wind heatdominated regime where the evolution of sea surface temperature is solely determined by atmospheric forcing. In such regions the evolution of surface layer temperature is not dependent on the characteristics of the subsurface ocean such as the barrier layer and temperature inversion.

Crustal Deformation and Seismic History Associated with the 2004 Indian Ocean Earthquake: A Perspective from the Andaman–Nicobar Islands

The Indian Ocean earthquake of 26 December 2004 led to significant ground deformation in the Andaman and Nicobar region, accounting for ~800 km of the rupture. Part of this article deals with coseismic changes along these islands, observable from coastal morphology, biological indicators, and Global Positioning System (GPS) data. Our studies indicate that the islands south of 10° N latitude coseismically subsided by 1–1.5 m, both on their eastern and western margins, whereas those to the north showed a mixed response. The western margin of the Middle Andaman emerged by >1 m, and the eastern margin submerged by the same amount. In the North Andaman, both western and eastern margins emerged by >1 m. We also assess the pattern of long-term deformation (uplift/subsidence) and attempt to reconstruct earthquake/tsunami history, with the available data. Geological evidence for past submergence includes dead mangrove vegetation dating to 740 ± 100 yr B.P., near Port Blair and peat layers at 2–4 m and 10–15 m depths observed in core samples from nearby locations. Preliminary paleoseismological/tsunami evidence from the Andaman and Nicobar region and from the east coast of India, suggest at least one predecessor for the 2004 earthquake 900–1000 years ago. The history of earthquakes, although incomplete at this stage, seems to imply that the 2004-type earthquakes are infrequent and follow variable intervals

Estimation of heavy rainfall during cyclonic storms from microwave observations using nonlinear approach over Indian Ocean

In this study, an effort has been made to study heavy rainfall events during cyclonic storms over Indian Ocean. This estimate is based on microwave observations from tropical rainfall measuring mission (TRMM) Microwave Imager (TMI). Regional scattering index (SI) developed for Indian region based on measurements at 19-, 21- and 85-GHz brightness temperature and polarization corrected temperature (PCT) at 85 GHz have been utilized in this study. These PCT and SI are collocated against Precipitation Radar (PR) onboard TRMM to establish a relationship between rainfall rate, PCT and SI. The retrieval technique using both linear and nonlinear regressions has been developed utilizing SI, PCT and the combination of SI and PCT. The results have been compared with the observations from PR. It was found that a nonlinear algorithm using combination of SI and PCT is more accurate than linear algorithm or nonlinear algorithm using either SI or PCT. Statistical comparison with PR exhibits the correlation coefficients (CC) of 0.68, 0.66 and 0.70, and root mean square error (RMSE) of 1.78, 1.96 and 1.68 mm/h from the observations of SI, PCT and combination of SI and PCT respectively using linear regressions. When nonlinear regression is used, the CC of 0.73, 0.71, 0.79 and RMSE of 1.64, 1.95, 1.54 mm/h are observed from the observations of SI, PCT and combination of SI and PCT, respectively. The error statistics for high rain events (above 10 mm/h) shows the CC of 0.58, 0.59, 0.60 and RMSE of 5.07, 5.47, 5.03 mm/h from the observations of SI, PCT and combination of SI and PCT, respectively, using linear regression, and on the other hand, use of nonlinear regression yields the CC of 0.66, 0.64, 0.71 and RMSE of 4.68, 5.78 and 4.02 mm/h from the observations of SI, PCT and combined SI and PCT, respectively.

Signatures of Indian ocean Dipole and El Nino-Southern Oscillation events in sea level variations in the Bay of Bengal

We investigate the impact of the Indian Ocean Dipole (IOD) and El Nino and the Southern Oscillation (ENSO) on sea level variations in the North Indian Ocean during 1957-2008. Using tide-gauge and altimeter data, we show that IOD and ENSO leave characteristic signatures in the sea level anomalies (SLAs) in the Bay of Bengal. During a positive IOD event, negative SLAs are observed during April-December, with the SLAs decreasing continuously to a peak during September-November. During El Nino, negative SLAs are observed twice (April-December and November-July), with a relaxation between the two peaks. SLA signatures during negative IOD and La Nina events are much weaker. We use a linear, continuously stratified model of the Indian Ocean to simulate their sea level patterns of IOD and ENSO events. We then separate solutions into parts that correspond to specific processes: coastal alongshore winds, remote forcing from the equator via reflected Rossby waves, and direct forcing by interior winds within the bay. During pure IOD events, the SLAs are forced both from the equator and by direct wind forcing. During ENSO events, they are primarily equatorially forced, with only a minor contribution from direct wind forcing. Using a lead/lag covariance analysis between the Nino-3.4 SST index and Indian Ocean wind stress, we derive a composite wind field for a typical El Nino event: the resulting solution has two negative SLA peaks. The IOD and ENSO signatures are not evident off the west coast of India.

The Indian Ocean forecast system

In order to meet the ever growing demand for the prediction of oceanographic parametres in the Indian Ocean for a variety of applications, the Indian National Centre for Ocean Information Services (INCOIS) has recently set-up an operational ocean forecast system, viz. the Indian Ocean Forecast System (INDOFOS). This fully automated system, based on a state-of-the-art ocean general circulation model issues six-hourly forecasts of the sea-surface temperature, surface currents and depths of the mixed layer and the thermocline up to five-days of lead time. A brief account of INDOFOS and a statistical validation of the forecasts of these parametres using in situ and remote sensing data are presented in this article. The accuracy of the sea-surface temperature forecasts by the system is high in the Bay of Bengal and the Arabian Sea, whereas it is moderate in the equatorial Indian Ocean. On the other hand, the accuracy of the depth of the thermocline and the isothermal layers and surface current forecasts are higher near the equatorial region, while it is relatively lower in the Bay of Bengal.

Yanai waves in the western equatorial Indian Ocean

Observations and models have shown the presence of intraseasonal fluctuations in 20-30-day and 10-20-day bands in the equatorial Indian Ocean west of 60 degrees E (WEIO). Their spatial and temporal structures characterize them as Yanai waves, which we label low-frequency (LFYW) and high-frequency (HFYW) Yanai waves, respectively. We explore the dynamics of these intraseasonal signals, using an ocean general circulation model (Modular Ocean Model) and a linear, continuously stratified model. Yanai waves are forced by the meridional wind tau(y) everywhere in the WEIO most strongly during the monsoon seasons. They are forced both directly in the interior ocean and by reflection of the interior response from the western boundary; interference between the interior and boundary responses results in a complex surface pattern that propagates eastward and has nodes. Yanai waves are also forced by instabilities primarily during June/July in a region offshore from the western boundary (52-55 degrees E). At that time, eddies, generated by barotropic instability of the Southern Gyre, are advected southward to the equator. There, they generate a westward-propagating, cross-equatorial flow field, v(eq), with a wave number/frequency spectrum that fits the dispersion relation of a number of Yanai waves, and these waves are efficiently excited. Typically, Yanai waves associated with several baroclinic modes are excited by both wind and eddy forcing; and typically, they superpose to create beams that carry energy vertically and eastward along ray paths. The same processes generate LFYWs and HFYWs, and hence, their responses are similar; differences are traceable to the property that HFYWs have longer wavelengths than LFYWs for each baroclinic mode.

Dynamics of the Indian-Ocean oxygen minimum zones

In the Indian Ocean, mid-depth oxygen minimum zones (OMZs) occur in the Arabian Sea and the Bay of Bengal. The lower part of the Arabian-Sea OMZ (ASOMZ; below 400 m) intensifies northward across the basin; in contrast, its upper part (above 400 m) is located in the central/eastern basin, well east of the most productive regions along the western boundary. The Bay-of-Bengal OMZ (BBOMZ), although strong, is weaker than the ASOMZ. To investigate the processes that maintain the Indian-Ocean OMZs, we obtain a suite of solutions to a coupled biological/physical model. Its physical component is a variable-density, 6 1/2-layer model, in which each layer corresponds to a distinct dynamical regime or water-mass type. Its biological component has six compartments: nutrients, phytoplankton, zooplankton, two size classes of detritus, and oxygen. Because the model grid is non-eddy resolving (0.5 degrees), the biological model also includes a parameterization of enhanced mixing based on the eddy kinetic energy derived from satellite observations. To explore further the impact of local processes on OMZs, we also obtain analytic solutions to a one-dimensional, simplified version of the biological model. Our control run is able to simulate basic features of the oxygen, nutrient, and phytoplankton fields throughout the Indian Ocean. The model OMZs result from a balance, or lack thereof, between a sink of oxygen by remineralization and subsurface oxygen sources due primarily to northward spreading of oxygenated water from the Southern Hemisphere, with a contribution from Persian-Gulf water in the northern Arabian Sea. The northward intensification of the lower ASOMZ results mostly from horizontal mixing since advection is weak in its depth range. The eastward shift of the upper ASOMZ is due primarily to enhanced advection and vertical eddy mixing in the western Arabian Sea, which spread oxygenated waters both horizontally and vertically. Advection carries small detritus from the western boundary into the central/eastern Arabian Sea, where it provides an additional source of remineralization that drives the ASOMZ to suboxic levels. The model BBOMZ is weaker than the ASOMZ because the Bay lacks a remote source of detritus from the western boundary. Although detritus has a prominent annual cycle, the model OMZs do not because there is not enough time for significant remineralization to occur.

Data assimilation using ensemble transform Kalman filter (ETKF) in ROMS model for Indian Ocean

Study of Oceans dynamics and forecast is crucial as it influences the regional climate and other marine activities. Forecasting oceanographic states like sea surface currents, Sea surface temperature (SST) and mixed layer depth at different time scales is extremely important for these activities. These forecasts are generated by various ocean general circulation models (OGCM). One such model is the Regional Ocean Modelling System (ROMS). Though ROMS can simulate several features of ocean, it cannot reproduce the thermocline of the ocean properly. Solution to this problem is to incorporates data assimilation (DA) in the model. DA system using Ensemble Transform Kalman Filter (ETKF) has been developed for ROMS model to improve the accuracy of the model forecast. To assimilate data temperature and salinity from ARGO data has been used as observation. Assimilated temperature and salinity without localization shows oscillations compared to the model run without assimilation for India Ocean. Same was also found for u and v-velocity fields. With localization we found that the state variables are diverging within the localization scale.