53 resultados para Equatorial Indian Ocean Oscillation (EQUINOO)
em Indian Institute of Science - Bangalore - Índia
Resumo:
It is now well known that there is a strong association of the extremes of the Indian summer monsoon rainfall (ISMR) with the El Nio and southern oscillation (ENSO) and the Equatorial Indian Ocean Oscillation (EQUINOO), later being an east-west oscillation in convection anomaly over the equatorial Indian Ocean. So far, the index used for EQUINOO is EQWIN, which is based on the surface zonal wind over the central equatorial Indian Ocean. Since the most important attribute of EQUINOO is the oscillation in convection/precipitation, we believe that the indices based on convection or precipitation would be more appropriate. Continuous and reliable data on outgoing longwave radiation (OLR), and satellite derived precipitation are now available from 1979 onwards. Hence, in this paper, we introduce new indices for EQUINOO, based on the difference in the anomaly of OLR/precipitation between eastern and western parts of the equatorial Indian Ocean. We show that the strong association of extremes of the Indian summer monsoon with ENSO and EQUINOO is also seen when the new indices are used to represent EQUINOO.
Resumo:
Interannual variation of Indian summer monsoon rainfall (ISMR) is linked to El Nino-Southern oscillation (ENSO) as well as the Equatorial Indian Ocean oscillation (EQUINOO) with the link with the seasonal value of the ENSO index being stronger than that with the EQUINOO index. We show that the variation of a composite index determined through bivariate analysis, explains 54% of ISMR variance, suggesting a strong dependence of the skill of monsoon prediction on the skill of prediction of ENSO and EQUINOO. We explored the possibility of prediction of the Indian rainfall during the summer monsoon season on the basis of prior values of the indices. We find that such predictions are possible for July-September rainfall on the basis of June indices and for August-September rainfall based on the July indices. This will be a useful input for second and later stage forecasts made after the commencement of the monsoon season.
Resumo:
An analysis of the retrospective predictions by seven coupled ocean atmosphere models from major forecasting centres of Europe and USA, aimed at assessing their ability in predicting the interannual variation of the Indian summer monsoon rainfall (ISMR), particularly the extremes (i.e. droughts and excess rainfall seasons) is presented in this article. On the whole, the skill in prediction of extremes is not bad since most of the models are able to predict the sign of the ISMR anomaly for a majority of the extremes. There is a remarkable coherence between the models in successes and failures of the predictions, with all the models generating loud false alarms for the normal monsoon season of 1997 and the excess monsoon season of 1983. It is well known that the El Nino and Southern Oscillation (ENSO) and the Equatorial Indian Ocean Oscillation (EQUINOO) play an important role in the interannual variation of ISMR and particularly the extremes. The prediction of the phases of these modes and their link with the monsoon has also been assessed. It is found that models are able to simulate ENSO-monsoon link realistically, whereas the EQUINOO-ISMR link is simulated realistically by only one model the ECMWF model. Furthermore, it is found that in most models this link is opposite to the observed, with the predicted ISMR being negatively (instead of positively) correlated with the rainfall over the western equatorial Indian Ocean and positively (instead of negatively) correlated with the rainfall over the eastern equatorial Indian Ocean. Analysis of the seasons for which the predictions of almost all the models have large errors has suggested the facets of ENSO and EQUINOO and the links with the monsoon that need to be improved for improving monsoon predictions by these models.
Resumo:
The Indian summer monsoon season of 2009 commenced with a massive deficit in all-India rainfall of 48% of the average rainfall in June. The all-India rainfall in July was close to the normal but that in August was deficit by 27%. In this paper, we first focus on June 2009, elucidating the special features and attempting to identify the factors that could have led to the large deficit in rainfall. In June 2009, the phase of the two important modes, viz., El Nino and Southern Oscillation (ENSO) and the equatorial Indian Ocean Oscillation (EQUINOO) was unfavourable. Also, the eastern equatorial Indian Ocean (EEIO) was warmer than in other years and much warmer than the Bay. In almost all the years, the opposite is true, i.e., the Bay is warmer than EEIO in June. It appears that this SST gradient gave an edge to the tropical convergence zone over the eastern equatorial Indian Ocean, in competition with the organized convection over the Bay. Thus, convection was not sustained for more than three or four days over the Bay and no northward propagations occurred. We suggest that the reversal of the sea surface temperature (SST) gradient between the Bay of Bengal and EEIO, played a critical role in the rainfall deficit over the Bay and hence the Indian region. We also suggest that suppression of convection over EEIO in association with the El Nino led to a positive phase of EQUINOO in July and hence revival of the monsoon despite the El Nino. It appears that the transition to a negative phase of EQUINOO in August and the associated large deficit in monsoon rainfall can also be attributed to the El Nino.
Resumo:
Under the project `Seasonal Prediction of the Indian Monsoon' (SPIM), the prediction of Indian summer monsoon rainfall by five atmospheric general circulation models (AGCMs) during 1985-2004 was assessed. The project was a collaborative effort of the coordinators and scientists from the different modelling groups across the country. All the runs were made at the Centre for Development of Advanced Computing (CDAC) at Bangalore on the PARAM Padma supercomputing system. Two sets of simulations were made for this purpose. In the first set, the AGCMs were forced by the observed sea surface temperature (SST) for May-September during 1985-2004. In the second set, runs were made for 1987, 1988, 1994, 1997 and 2002 forced by SST which was obtained by assuming that the April anomalies persist during May-September. The results of the first set of runs show, as expected from earlier studies, that none of the models were able to simulate the correct sign of the anomaly of the Indian summer monsoon rainfall for all the years. However, among the five models, one simulated the correct sign in the largest number of years and the second model showed maximum skill in the simulation of the extremes (i.e. droughts or excess rainfall years). The first set of runs showed some common bias which could arise either from an excessive sensitivity of the models to El Nino Southern Oscillation (ENSO) or an inability of the models to simulate the link of the Indian monsoon rainfall to Equatorial Indian Ocean Oscillation (EQUINOO), or both. Analysis of the second set of runs showed that with a weaker ENSO forcing, some models could simulate the link with EQUINOO, suggesting that the errors in the monsoon simulations with observed SST by these models could be attributed to unrealistically high sensitivity to ENSO.
Resumo:
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.
Resumo:
In this study, the nature of basin-scale hydroclimatic association for Indian subcontinent is investigated. It is found that, the large-scale circulation information from Indian Ocean is also equally important in addition to the El Nino-Southern Oscillation (ENSO), owing to the geographical location of Indian subcontinent. The hydroclimatic association of the variation of monsoon inflow into the Hirakud reservoir in India is investigated using ENSO and EQUatorial INdian Ocean Oscillation (EQUINOO, the atmospheric part of Indian Ocean Dipole mode) as the large-scale circulation information from tropical Pacific Ocean and Indian Ocean regions respectively. Individual associations of ENSO & EQUINOO indices with inflow into Hirakud reservoir are also assessed and found to be weak. However, the association of inflows into Hirakud reservoir with the composite index (CI) of ENSO and EQUINOO is quite strong. Thus, the large-scale circulation information from Indian Ocean is also important apart form the ENSO. The potential of the combined information of ENSO and EQUINOO for predicting the inflows during monsoon is also investigated with promising results. The results of this study will be helpful to water resources managers due to fact that the nature of monsoon inflow is becoming available as an early prediction.
Resumo:
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.
Resumo:
Equatorial Indian Ocean is warmer in the east, has a deeper thermocline and mixed layer, and supports a more convective atmosphere than in the west. During certain years, the eastern Indian Ocean becomes unusually cold, anomalous winds blow from east to west along the equator and southeastward off the coast of Sumatra, thermocline and mixed layer lift up and the atmospheric convection gets suppressed. At the same time, western Indian Ocean becomes warmer and enhances atmospheric convection. This coupled ocean-atmospheric phenomenon in which convection, winds, sea surface temperature (SST) and thermocline take part actively is known as the Indian Ocean Dipole (IOD). Propagation of baroclinic Kelvin and Rossby waves excited by anomalous winds, play an important role in the development of SST anomalies associated with the IOD. Since mean thermocline in the Indian Ocean is deep compared to the Pacific, it was believed for a long time that the Indian Ocean is passive and merely responds to the atmospheric forcing. Discovery of the IOD and studies that followed demonstrate that the Indian Ocean can sustain its own intrinsic coupled ocean-atmosphere processes. About 50% percent of the IOD events in the past 100 years have co-occurred with El Nino Southern Oscillation (ENSO) and the other half independently. Coupled models have been able to reproduce IOD events and process experiments by such models – switching ENSO on and off – support the hypothesis based on observations that IOD events develop either in the presence or absence of ENSO. There is a general consensus among different coupled models as well as analysis of data that IOD events co-occurring during the ENSO are forced by a zonal shift in the descending branch of Walker cell over to the eastern Indian Ocean. Processes that initiate the IOD in the absence of ENSO are not clear, although several studies suggest that anomalies of Hadley circulation are the most probable forcing function. Impact of the IOD is felt in the vicinity of Indian Ocean as well as in remote regions. During IOD events, biological productivity of the eastern Indian Ocean increases and this in turn leads to death of corals over a large area.Moreover, the IOD affects rainfall over the maritime continent, Indian subcontinent, Australia and eastern Africa. The maritime continent and Australia suffer from deficit rainfall whereas India and east Africa receive excess. Despite the successful hindcast of the 2006 IOD by a coupled model, forecasting IOD events and their implications to rainfall variability remains a major challenge as understanding reasons behind an increase in frequency of IOD events in recent decades.
Resumo:
The variability of the sea surface salinity (SSS) in the Indian Ocean is studied using a 100-year control simulation of the Community Climate System Model (CCSM 2.0). The monsoon-driven seasonal SSS pattern in the Indian Ocean, marked by low salinity in the east and high salinity in the west, is captured by the model. The model overestimates runoff int the Bay of Bengal due to higher rainfall over the Himalayan-Tibetan regions which drain into the Bay of Bengal through Ganga-Brahmaputra rivers. The outflow of low-salinity water from the Bay of Bengal is to strong in the model. Consequently, the model Indian Ocean SSS is about 1 less than that seen in the climatology. The seasonal Indian Ocean salt balance obtained from the model is consistent with the analysis from climatological data sets. During summer, the large freshwater input into the Bay of Bengal and its redistribution decide the spatial pattern of salinity tendency. During winter, horizontal advection is the dominant contributor to the tendency term. The interannual variability of the SSS in the Indian Ocean is about five times larger than that in coupled model simulations of the North Atlantic Ocean. Regions of large interannual standard deviations are located near river mouths in the Bay of Bengal and in the eastern equatorial Indian Ocean. Both freshwater input into the ocean and advection of this anomalous flux are responsible for the generation of these anomalies. The model simulates 20 significant Indian Ocean Dipole (IOD) events and during IOD years large salinity anomalies appear in the equatorial Indian Ocean. The anomalies exist as two zonal bands: negative salinity anomalies to the north of the equator and positive to the south. The SSS anomalies for the years in which IOD is not present and for ENSO years are much weaker than during IOD years. Significant interannual SSS anomalies appear in the Indian Ocean only during IOD years.
Resumo:
[1] The equatorial Indian Ocean (EIO) exhibited anomalous conditions characteristic of an Indian Ocean dipole (IOD) during 2006. The eastern EIO had cold sea surface temperature anomalies (SSTA), lower sea level, shallow thermocline and higher chlorophyll than normal. The anomalies in the east, restricted to the south of the equator, were highest off Sumatra. The western pole of the IOD was marked by warm SSTA and deeper thermocline with maxima on either side of the equator. An ocean general circulation model of the Indian Ocean forced by QuikSCAT winds reproduces the IOD of 2006 remarkably well. The switch over to cooling in the east and warming in the west happened during May and July respectively. In the east, airsea heat flux initiated cold SSTA in the model which were sustained later by oceanic processes. In the west, surface heat fluxes and horizontal advection caused warm SSTA and contribution by the latter decreased after August. Citation: Vinayachandran, P. N., J. Kurian, and C. P. Neema (2007), Indian Ocean response to anomalous conditions in 2006, Geophys. Res. Lett., 34, L15602, doi:10.1029/2007GL030194.
Resumo:
The equatorial Indian Ocean (EIO) exhibited anomalous conditions characteristic of an Indian Ocean dipole (IOD) during 2006. The eastern EIO had cold sea surface temperature anomalies (SSTA), lower sea level, shallow thermocline and higher chlorophyll than normal. The anomalies in the east, restricted to the south of the equator, were highest off Sumatra. The western pole of the IOD was marked by warm SSTA and deeper thermocline with maxima on either side of the equator. An ocean general circulation model of the Indian Ocean forced by QuikSCAT winds reproduces the IOD of 2006 remarkably well. The switch over to cooling in the east and warming in the west happened during May and July respectively. In the east, air-sea heat flux initiated cold SSTA in the model which were sustained later by oceanic processes. In the west, surface heat fluxes and horizontal advection caused warm SSTA and contribution by the latter decreased after August.
Resumo:
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.
Resumo:
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.
Resumo:
We present a comparison of the Global Ocean Data Assimilation System (GODAS) five-day ocean analyses against in situ daily data from Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) moorings at locations 90 degrees E, 12 degrees N; 90 degrees E, 8 degrees N; 90 degrees E, 0 degrees N and 90 degrees E, 1.5 degrees S in the equatorial Indian Ocean and the Bay of Bengal during 2002-2008. We find that the GODAS temperature analysis does not adequately capture a prominent signal of Indian Ocean dipole mode of 2006 seen in the mooring data, particularly at 90 degrees E 0 degrees N and 90 degrees E 1.5 degrees S in the eastern India Ocean. The analysis, using simple statistics such as bias and root-mean-square deviation, indicates that standard GODAS temperature has definite biases and significant differences with observations on both subseasonal and seasonal scales. Subsurface salinity has serious deficiencies as well, but this may not be surprising considering the poorly constrained fresh water forcing, and possible model deficiencies in subsurface vertical mixing. GODAS reanalysis needs improvement to make it more useful for study of climate variability and for creating ocean initial conditions for prediction.