Interannual Variability of Indian Ocean Heat Transport

2006 ◽  
Vol 19 (6) ◽  
pp. 1013-1031 ◽  
Author(s):  
Galina Chirokova ◽  
Peter J. Webster
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Heat Transport ◽  
Time Scales ◽  
Seasonal Cycle ◽  
Intraseasonal Variability ◽  
Ocean Model ◽  
Ocean Heat Transport ◽  
The Indian Ocean ◽  
One Year

Abstract The work in this paper builds upon the relatively well-studied seasonal cycle of the Indian Ocean heat transport by investigating its interannual variability over a 41-yr period (1958–98). An intermediate, two-and-a-half-layer thermodynamically active ocean model with mixed layer physics is used in the investigation. The results of the study reveal that the Indian Ocean heat transport possesses strong variability at all time scales from intraseasonal (10–90 days) to interannual (more than one year). The seasonal cycle dominates the variability at all latitudes, the amplitude of the intraseasonal variability is similar to the seasonal cycle, and the amplitude of the interannual variability is about one-tenth of the seasonal cycle. Spectral analysis shows that a significant broadband biennial component in the interannual variability exists with considerable coherence in sign across the equator. While the mean annual heat transport shows a strong maximum between 10° and 20°S, interannual variability is relatively uniform over a broad latitudinal domain between 15°N and 10°S. The heat transport variability at all time scales is well explained by the Ekman heat transport, with especially good correlations at the intraseasonal time scales. The addition of the Indonesian Throughflow does not significantly affect the heat transport variability in the northern part of the ocean.

Intraseasonal-to-Interannual Variability of South Indian Ocean Sea Level and Thermocline: Remote versus Local Forcing

2012 ◽  
Vol 42 (4) ◽  
pp. 602-627 ◽  
Author(s):  
Laurie L. Trenary ◽  
Weiqing Han
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Sea Level ◽  
Time Scales ◽  
Ekman Pumping ◽  
Remote Forcing ◽  
South Indian ◽  
The Pacific ◽  
The Indian Ocean ◽  
Thermocline Variability

Abstract The relative importance of local versus remote forcing on intraseasonal-to-interannual sea level and thermocline variability of the tropical south Indian Ocean (SIO) is systematically examined by performing a suite of controlled experiments using an ocean general circulation model and a linear ocean model. Particular emphasis is placed on the thermocline ridge of the Indian Ocean (TRIO; 5°–12°S, 50°–80°E). On interannual and seasonal time scales, sea level and thermocline variability within the TRIO region is primarily forced by winds over the Indian Ocean. Interannual variability is largely caused by westward propagating Rossby waves forced by Ekman pumping velocities east of the region. Seasonally, thermocline variability over the TRIO region is induced by a combination of local Ekman pumping and Rossby waves generated by winds from the east. Adjustment of the tropical SIO at both time scales generally follows linear theory and is captured by the first two baroclinic modes. Remote forcing from the Pacific via the oceanic bridge has significant influence on seasonal and interannual thermocline variability in the east basin of the SIO and weak impact on the TRIO region. On intraseasonal time scales, strong sea level and thermocline variability is found in the southeast tropical Indian Ocean, and it primarily arises from oceanic instabilities. In the TRIO region, intraseasonal sea level is relatively weak and results from Indian Ocean wind forcing. Forcing over the Pacific is the major cause for interannual variability of the Indonesian Throughflow (ITF) transport, whereas forcing over the Indian Ocean plays a larger role in determining seasonal and intraseasonal ITF variability.

scholarly journals Annual, Seasonal, and Interannual Variability of Air–Sea Heat Fluxes in the Indian Ocean

2007 ◽  
Vol 20 (13) ◽  
pp. 3190-3209 ◽  
Author(s):  
Lisan Yu ◽  
Xiangze Jin ◽  
Robert A. Weller
Keyword(s):  
Heat Flux ◽  
Indian Ocean ◽  
Interannual Variability ◽  
Seasonal Cycle ◽  
Arabian Sea ◽  
Heat Fluxes ◽  
The Other ◽  
Net Heat Flux ◽  
The Indian Ocean ◽  
The Mean

Abstract This study investigated the accuracy and physical representation of air–sea surface heat flux estimates for the Indian Ocean on annual, seasonal, and interannual time scales. Six heat flux products were analyzed, including the newly developed latent and sensible heat fluxes from the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project and net shortwave and longwave radiation results from the International Satellite Cloud Climatology Project (ISCCP), the heat flux analysis from the Southampton Oceanography Centre (SOC), the National Centers for Environmental Prediction reanalysis 1 (NCEP1) and reanalysis-2 (NCEP2) datasets, and the European Centre for Medium-Range Weather Forecasts operational (ECMWF-OP) and 40-yr Re-Analysis (ERA-40) products. This paper presents the analysis of the six products in depicting the mean, the seasonal cycle, and the interannual variability of the net heat flux into the ocean. Two time series of in situ flux measurements, one taken from a 1-yr Arabian Sea Experiment field program and the other from a 1-month Joint Air–Sea Monsoon Interaction Experiment (JASMINE) field program in the Bay of Bengal were used to evaluate the statistical properties of the flux products over the measurement periods. The consistency between the six products on seasonal and interannual time scales was investigated using a standard deviation analysis and a physically based correlation analysis. The study has three findings. First of all, large differences exist in the mean value of the six heat flux products. Part of the differences may be attributable to the bias in the numerical weather prediction (NWP) models that underestimates the net heat flux into the Indian Ocean. Along the JASMINE ship tracks, the four NWP modeled mean fluxes all have a sign opposite to the observations, with NCEP1 being underestimated by 53 W m−2 (the least biased) and ECMWF-OP by 108 W m−2 (the most biased). At the Arabian Sea buoy site, the NWP mean fluxes also have an underestimation bias, with the smallest bias of 26 W m−2 (ERA-40) and the largest bias of 69 W m−2 (NCEP1). On the other hand, the OAFlux+ISCCP has the best comparison at both measurement sites. Second, the bias effect changes with the time scale. Despite the fact that the mean is biased significantly, there is no major bias in the seasonal cycle of all the products except for ECMWF-OP. The latter does not have a fixed mean due to the frequent updates of the model platform. Finally, among the four products (OAFlux+ISCCP, ERA-40, NCEP1, and NCEP2) that can be used for studying interannual variability, OAFlux+ISCCP and ERA-40 Qnet have good consistency as judged from both statistical and physical measures. NCEP1 shows broad agreement with the two products, with varying details. By comparison, NCEP2 is the least representative of the Qnet variabilities over the basin scale.

A Model-Based Assessment and Design of a Tropical Indian Ocean Mooring Array

2007 ◽  
Vol 20 (13) ◽  
pp. 3269-3283 ◽  
Author(s):  
Peter R. Oke ◽  
Andreas Schiller
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Time Scales ◽  
Ocean Circulation ◽  
Mixed Layer Depth ◽  
Intraseasonal Variability ◽  
Circulation Model ◽  
Tropical Indian Ocean ◽  
Empirical Orthogonal Functions ◽  
Analysis System

Abstract A series of observing system simulation experiments (OSSEs) are performed for the tropical Indian Ocean (±15° from the equator) using a simple analysis system. The analysis system projects an array of observations onto the dominant empirical orthogonal functions (EOFs) derived from an intermediate-resolution (2° × 0.5°) ocean circulation model. This system produces maps of the depth of the 20°C isotherm (D20), representing interannual variability, and the high-pass-filtered mixed layer depth (MLD), representing intraseasonal variability. The OSSEs are designed to assess the suitability of the proposed Indian Ocean surface mooring array for resolving intraseasonal to interannual variability. While the proposed array does a reasonable job of resolving the interannual time scales, it may not adequately resolve the intraseasonal time scales. A procedure is developed to rank the importance of observation locations by determining the observation array that best projects onto the EOFs used in the analysis system. OSSEs using an optimal array clearly outperform the OSSEs using the proposed array. The configuration of the optimal array is sensitive to the number of EOFs considered. The optimal array is also different for D20 and MLD, and depends on whether fixed observations are included that represent an idealized Argo array. Therefore, a relative frequency map of observation locations identified in 24 different OSSEs is compiled and a single, albeit less optimal, array that is referred to as a consolidated array is objectively determined. The consolidated array reflects the general features of the individual optimal arrays derived from all OSSEs. It is found that, in general, observations south of 8°S and off of the Indonesian coast are most important for resolving the interannual variability, while observations a few degrees south of the equator, and west of 75°E, and a few degrees north of the equator, and east of 75°E, are important for resolving the intraseasonal variability. In a series of OSSEs, the consolidated array is shown to outperform the proposed array for all configurations of the analysis system for both D20 and MLD.

scholarly journals An Intrinsic Mode of Interannual Variability in the Indian Ocean

2017 ◽  
Vol 47 (3) ◽  
pp. 701-719 ◽  
Author(s):  
Christopher L. Wolfe ◽  
Paola Cessi ◽  
Bruce D. Cornuelle
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Ocean Circulation ◽  
Baroclinic Instability ◽  
Ocean Model ◽  
South Atlantic ◽  
Global Ocean ◽  
Leeuwin Current ◽  
The Indian Ocean ◽  
Atmospheric State

AbstractAn intrinsic mode of self-sustained, interannual variability is identified in a coarse-resolution ocean model forced by an annually repeating atmospheric state. The variability has maximum loading in the Indian Ocean, with a significant projection into the South Atlantic Ocean. It is argued that this intrinsic mode is caused by baroclinic instability of the model’s Leeuwin Current, which radiates out to the tropical Indian and South Atlantic Oceans as long Rossby waves at a period of 4 yr. This previously undescribed mode has a remarkably narrowband time series. However, the variability is not synchronized with the annual cycle; the phase of the oscillation varies chaotically on decadal time scales. The presence of this internal mode reduces the predictability of the ocean circulation by obscuring the response to forcing or initial condition perturbations. The signature of this mode can be seen in higher-resolution global ocean models driven by high-frequency atmospheric forcing, but altimeter and assimilation analyses do not show obvious signatures of such a mode, perhaps because of insufficient duration.

scholarly journals Verification of reanalysis data for the tropical zone of the Indian ocean. Part 2. Characteristics of the averaged seasonal cycle and interannual variability

2020 ◽  
pp. 119-126
Author(s):  
A.B. Polonsky ◽  
◽  
A.V. Torbinskii ◽  
A.V. Gubarev ◽  
◽  
...  
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Seasonal Cycle ◽  
Potential Temperature ◽  
Tropical Indian Ocean ◽  
Reanalysis Data ◽  
Tropical Zone ◽  
Current Vector ◽  
Zonal Component ◽  
The Indian Ocean

The aim of the study is to evaluate the performance of ORAS5/SODA3/GLORYS re-analyses using the RAMA in the tropical Indian Ocean. To assess the reproducibility of the seasonal cycle and characteristics of interannual variability, we used the data on the potential temperature, salinity, and zonal component of the current vector obtained south of the equator for the period 2010–2014. It is shown that at 55°E south of the equator, the GLORYS re-analysis better reproduces the five-year averaged seasonal cycle and interannual variability than the SODA3 and ORAS5 re-analyses.

Seasonal-to-Interannual Time-Scale Dynamics of the Equatorial Undercurrent in the Indian Ocean

2015 ◽  
Vol 45 (6) ◽  
pp. 1532-1553 ◽  
Author(s):  
Gengxin Chen ◽  
Weiqing Han ◽  
Yuanlong Li ◽  
Dongxiao Wang ◽  
Michael J. McPhaden
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Rossby Waves ◽  
Ocean Model ◽  
Western Basin ◽  
Equatorial Undercurrent ◽  
Eastern Basin ◽  
Eastern Boundary ◽  
The Indian Ocean ◽  
Core Depth

AbstractThis paper investigates the structure and dynamics of the Equatorial Undercurrent (EUC) of the Indian Ocean by analyzing in situ observations and reanalysis data and performing ocean model experiments using an ocean general circulation model and a linear continuously stratified ocean model. The results show that the EUC regularly occurs in each boreal winter and spring, particularly during February and April, consistent with existing studies. The EUC generally has a core depth near the 20°C isotherm and can be present across the equatorial basin. The EUC reappears during summer–fall of most years, with core depth located at different longitudes and depths. In the western basin, the EUC results primarily from equatorial Kelvin and Rossby waves directly forced by equatorial easterly winds. In the central and eastern basin, however, reflected Rossby waves from the eastern boundary play a crucial role. While the first two baroclinic modes make the largest contribution, intermediate modes 3–8 are also important. The summer–fall EUC tends to occur in the western basin but exhibits obvious interannual variability in the eastern basin. During positive Indian Ocean dipole (IOD) years, the eastern basin EUC results largely from Rossby waves reflected from the eastern boundary, with directly forced Kelvin and Rossby waves also having significant contributions. However, the eastern basin EUC disappears during negative IOD and normal years because westerly wind anomalies force a westward pressure gradient force and thus westward subsurface current, which cancels the eastward subsurface flow induced by eastern boundary–reflected Rossby waves. Interannual variability of zonal equatorial wind that drives the EUC variability is dominated by the zonal sea surface temperature (SST) gradients associated with IOD and is much less influenced by equatorial wind associated with Indian monsoon rainfall strength.

scholarly journals Evolution of the Distribution of Upper-Tropospheric Humidity over the Indian Ocean: Connection with Large-Scale Advection and Local Cloudiness

2017 ◽  
Vol 56 (7) ◽  
pp. 2035-2052 ◽  
Author(s):  
Thomas Garot ◽  
Hélène Brogniez ◽  
Renaud Fallourd ◽  
Nicolas Viltard
Keyword(s):  
Indian Ocean ◽  
Large Scale ◽  
Transport Model ◽  
Intraseasonal Variability ◽  
Back Trajectory ◽  
Time Step ◽  
Air Masses ◽  
Upper Troposphere ◽  
Upper Tropospheric Humidity ◽  
The Indian Ocean

AbstractThe spatial and temporal distribution of upper-tropospheric humidity (UTH) observed by the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometry (SAPHIR)/Megha-Tropiques radiometer is analyzed over two subregions of the Indian Ocean during October–December over 2011–14. The properties of the distribution of UTH were studied with regard to the phase of the Madden–Julian oscillation (active or suppressed) and large-scale advection versus local production of moisture. To address these topics, first, a Lagrangian back-trajectory transport model was used to assess the role of the large-scale transport of air masses in the intraseasonal variability of UTH. Second, the temporal evolution of the distribution of UTH is analyzed using the computation of the higher moments of its probability distribution function (PDF) defined for each time step over the domain. The results highlight significant differences in the PDF of UTH depending on the phase of the MJO. The modeled trajectories ending in the considered domain originate from an area that strongly varies depending on the phases of the MJO: during the active phases, the air masses are spatially constrained within the tropical Indian Ocean domain, whereas a distinct upper-tropospheric (200–150 hPa) westerly flow guides the intraseasonal variability of UTH during the suppressed phases. Statistical relationships between the cloud fractions and the UTH PDF moments of are found to be very similar regardless of the convective activity. However, the occurrence of thin cirrus clouds is associated with a drying of the upper troposphere (enhanced during suppressed phases), whereas the occurrence of thick cirrus anvil clouds appears to be significantly related to a moistening of the upper troposphere.

Implementation and Validating of the Regional Ocean Model System (ROMS) for the Sunda Strait connecting the Java Sea to the Indian Ocean

2021 ◽  
Author(s):  
Subekti Mujiasih ◽  
Jean-Marie Beckers ◽  
Alexander Barth
Keyword(s):  
Time Series ◽  
Indian Ocean ◽  
Vertical Profile ◽  
Ocean Model ◽  
Model System ◽  
Satellite Sst ◽  
Regional Ocean Model System ◽  
Regional Ocean Model ◽  
The Indian Ocean ◽  
Java Sea

<p>Regional Ocean Model System (ROMS) has been simulated for the Sunda Strait, the Java Sea, and the Indian Ocean. The simulation was undertaken for thirteen months of data period (August 2013 – August 2014). However, we only used four months period for validation, namely September – December 2013. The input data involved the HYbrid Coordinate Ocean Model (HYCOM) ocean model output by considering atmospheric forcing from the European Centre for Medium-Range Weather Forecasts (ECMWF), without and with tides forcing from TPXO and rivers. The output included vertical profile temperature and salinity, sea surface temperature (SST), seas surface height (SSH), zonal (u), and meridional (v) velocity. We compared the model SST to satellite SST in time series, SSH to tides gauges data in time series, the model u and v component velocity to High Frequency (HF) radial velocity. The vertical profile temperature and salinity were compared to Argo float data and XBT. Besides, we validated the amplitude and phase of the ROMS seas surface height to amplitude and phase of the tides-gauges, including four constituents (M2, S2, K1, O1).</p>

Interannual Variability in Sea Surface Height at Southern Midlatitudes of the Indian Ocean

2021 ◽  
Vol 51 (5) ◽  
pp. 1595-1609
Author(s):  
Motoki Nagura ◽  
Michael J. McPhaden
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Sea Surface Height ◽  
Wind Forcing ◽  
Sea Surface ◽  
The South ◽  
South Indian Ocean ◽  
Eastern Boundary ◽  
South Indian ◽  
The Indian Ocean

AbstractThis study examines interannual variability in sea surface height (SSH) at southern midlatitudes of the Indian Ocean (10°–35°S). Our focus is on the relative role of local wind forcing and remote forcing from the equatorial Pacific Ocean. We use satellite altimetry measurements, an atmospheric reanalysis, and a one-dimensional wave model tuned to simulate observed SSH anomalies. The model solution is decomposed into the part driven by local winds and that driven by SSH variability radiated from the western coast of Australia. Results show that variability radiated from the Australian coast is larger in amplitude than variability driven by local winds in the central and eastern parts of the south Indian Ocean at midlatitudes (between 19° and 33°S), whereas the influence from eastern boundary forcing is confined to the eastern basin at lower latitudes (10° and 17°S). The relative importance of eastern boundary forcing at midlatitudes is due to the weakness of wind stress curl anomalies in the interior of the south Indian Ocean. Our analysis further suggests that SSH variability along the west coast of Australia originates from remote wind forcing in the tropical Pacific, as is pointed out by previous studies. The zonal gradient of SSH between the western and eastern parts of the south Indian Ocean is also mostly controlled by variability radiated from the Australian coast, indicating that interannual variability in meridional geostrophic transport is driven principally by Pacific winds.

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