Biases in the Tropical Indian Ocean subsurface temperature variability in a coupled model

2018 ◽  
Vol 52 (9-10) ◽  
pp. 5325-5344 ◽  
Author(s):  
Rashmi Kakatkar ◽  
C. Gnanaseelan ◽  
Jasti S. Chowdary ◽  
J. S. Deepa ◽  
Anant Parekh
Keyword(s):  
Indian Ocean ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Temperature Variability ◽  
Subsurface Temperature

Asymmetry in the tropical Indian Ocean subsurface temperature variability

2020 ◽  
Vol 90 ◽  
pp. 101142
Author(s):  
Rashmi Kakatkar ◽  
C. Gnanaseelan ◽  
J.S. Chowdary
Keyword(s):  
Indian Ocean ◽  
Tropical Indian Ocean ◽  
Temperature Variability ◽  
Subsurface Temperature

scholarly journals Processes Associated with the Tropical Indian Ocean Subsurface Temperature Bias in a Coupled Model

2016 ◽  
Vol 46 (9) ◽  
pp. 2863-2875 ◽  
Author(s):  
J. S. Chowdary ◽  
Anant Parekh ◽  
G. Srinivas ◽  
C. Gnanaseelan ◽  
T.S. Fousiya ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Subsurface Water ◽  
Upper Ocean ◽  
Subsurface Temperature ◽  
Seasonal Forecasts ◽  
Coupled Models ◽  
Warm Bias ◽  
Temperature Bias

AbstractSubsurface temperature biases in coupled models can seriously impair their capability in generating skillful seasonal forecasts. The National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), coupled model, which is used for seasonal forecast in several countries including India, displays warm (cold) subsurface (surface) temperature bias in the tropical Indian Ocean (TIO), with deeper than observed mixed layer and thermocline. In the model, the maximum warm bias is reported between 150- and 200-m depth. Detailed analysis reveals that the enhanced vertical mixing by strong vertical shear of horizontal currents is primarily responsible for TIO subsurface warming. Weak upper-ocean stability corroborated by surface cold and subsurface warm bias further strengthens the subsurface warm bias in the model. Excess inflow of warm subsurface water from Indonesian Throughflow to the TIO region is partially contributing to the warm bias mainly over the southern TIO region. Over the north Indian Ocean, Ekman convergence and downwelling due to wind stress bias deepen the thermocline, which do favor subsurface warming. Further, upper-ocean meridional and zonal cells are deeper in CFSv2 compared to the Ocean Reanalysis System data manifesting the deeper mixing. This study outlines the need for accurate representation of vertical structure in horizontal currents and associated vertical gradients to simulate subsurface temperatures for skillful seasonal forecasts.

Association between mean and interannual equatorial Indian Ocean subsurface temperature bias in a coupled model

2017 ◽  
Vol 50 (5-6) ◽  
pp. 1659-1673 ◽  
Author(s):  
G. Srinivas ◽  
Jasti S. Chowdary ◽  
C. Gnanaseelan ◽  
K. V. S. R. Prasad ◽  
Ananya Karmakar ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Coupled Model ◽  
Equatorial Indian Ocean ◽  
Subsurface Temperature ◽  
Temperature Bias

scholarly journals Characteristics of Subsurface Ocean Response to ENSO Assessed from Simulations with the NCEP Climate Forecast System

2013 ◽  
Vol 26 (20) ◽  
pp. 8065-8083 ◽  
Author(s):  
Hui Wang ◽  
Arun Kumar ◽  
Wanqiu Wang
Keyword(s):  
Indian Ocean ◽  
North Pacific ◽  
Temperature Response ◽  
Tropical Indian Ocean ◽  
Tropical Atlantic ◽  
Subsurface Temperature ◽  
The North ◽  
Subsurface Ocean ◽  
The North Pacific ◽  
The Tropical Pacific

Abstract The subsurface ocean temperature response to El Niño–Southern Oscillation (ENSO) is examined based on 31-yr (1981–2011) simulations with the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) coupled model. The model sea surface temperature (SST) in the tropical Pacific is relaxed to observations to ensure realistic ENSO variability in the simulations. In the tropical Pacific, the subsurface temperature response to the ENSO SST is closely related to the variability of thermocline. The subsurface response is stronger and deeper in the tropical Indian Ocean than in the tropical Atlantic. The analysis at three selected locations reveals that the peak response of the subsurface temperature to ENSO lags the Niño-3.4 SST by 3, 6, and 6 months, respectively, in the southern tropical Indian Ocean, the northern tropical Atlantic, and the North Pacific, where SSTs are also known to be strongly influenced by ENSO. The ENSO-forced temperature anomalies gradually penetrate to the deeper ocean with time in the North Pacific and the tropical Atlantic, but not in the tropical Indian Ocean where the subsurface response at different depths peaks almost at the same time (i.e., at about 3–4 months following ENSO). It is demonstrated that the ENSO-induced surface wind stress plays an important role in determining the time scale and strength of the subsurface temperature response to ENSO in the North Pacific and the northern tropical Atlantic. Additionally, the ENSO-related local surface latent heat flux also contributes to the subsurface response to ENSO in these two regions.

The Response of the Indian Ocean Dipole Asymmetry to Anthropogenic Aerosols and Greenhouse Gases

2015 ◽  
Vol 28 (7) ◽  
pp. 2564-2583 ◽  
Author(s):  
Tim Cowan ◽  
Wenju Cai ◽  
Benjamin Ng ◽  
Matthew England
Keyword(s):  
Indian Ocean ◽  
Greenhouse Gases ◽  
Indian Ocean Dipole ◽  
Climate Models ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Cmip5 Models ◽  
Anthropogenic Aerosols ◽  
The West ◽  
The Indian Ocean

Abstract The tropical Indian Ocean has experienced a faster warming rate in the west than in the east over the twentieth century. The warming pattern resembles a positive Indian Ocean dipole (IOD) that is well captured by climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), forced with the two main anthropogenic forcings, long-lived greenhouse gases (GHGs), and aerosols. However, much less is known about how GHGs and aerosols influence the IOD asymmetry, including the negative sea surface temperature (SST) skewness in the east IOD pole (IODE). Here, it is shown that the IODE SST negative skewness is more enhanced by aerosols than by GHGs using single-factor forcing experiments from 10 CMIP5 models. Aerosols induce a greater mean zonal thermocline gradient along the tropical Indian Ocean than that forced by GHGs, whereby the thermocline is deeper in the east relative to the west. This generates strong asymmetry in the SST response to thermocline anomalies between warm and cool IODE phases in the aerosol-only experiments, enhancing the negative IODE SST skewness. Other feedback processes involving zonal wind, precipitation, and evaporation cannot solely explain the enhanced SST skewness by aerosols. An interexperiment comparison in one model with strong skewness confirms that the mean zonal thermocline gradient across the Indian Ocean determines the magnitude of the SST–thermocline asymmetry, which in turn controls the SST skewness strength. The findings suggest that as aerosol emissions decline and GHGs increase, this will likely contribute to a future weakening of the IODE SST skewness.

scholarly journals Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

2017 ◽  
Vol 30 (21) ◽  
pp. 8517-8537 ◽  
Author(s):  
Fuyao Wang ◽  
Yan Yu ◽  
Michael Notaro ◽  
Jiafu Mao ◽  
Xiaoying Shi ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Statistical Method ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Ocean Basin ◽  
Climate Projections ◽  
Atmospheric Response ◽  
Statistical Assessment

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled control run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.

ENSO response to changes in the tropical Indian ocean temperature

2021 ◽  
Author(s):  
Brady Ferster ◽  
Alexey Fedorov ◽  
Juliette Mignot ◽  
Eric Guilyardi
Keyword(s):  
Indian Ocean ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Equatorial Pacific ◽  
Central Pacific ◽  
Trade Winds ◽  
Enso Variability ◽  
The Mean ◽  
Ensemble Experiments

<p>Since the start of the 21st century, El Niño-Southern Oscillation (ENSO) variability has changed, supporting generally weaker Central Pacific El Niño events. Recent studies suggest that stronger trade winds in the equatorial Pacific could be a key driving force contributing to this shift. One possible mechanism to drive such changes in the mean tropical Pacific climate state is the enhanced warming trends in the tropical Indian Ocean (TIO) relative to the rest of the tropics. TIO warming can affect the Walker circulation in both the Pacific and Atlantic basins by inducing quasi-stationary Kelvin and Rossby wave patterns. Using the latest coupled-model from Insitut Pierre Simon Laplace (IPSL-CM6), ensemble experiments are conducted to investigate the effect of TIO sea surface temperature (SST) on ENSO variability. Applying a weak SST nudging over the TIO region, in four ensemble experiments we change mean Indian ocean SST by -1.4°C, -0.7°C, +0.7°C, and +1.4°C and find that TIO warming changes the magnitude of the mean equatorial Pacific zonal wind stress proportionally to the imposed forcing, with stronger trades winds corresponding to a warmer TIO. Surprisingly, ENSO variability increases in both TIO cooling and warming experiments, relative to the control. While a stronger ENSO for weaker trade winds, associated with TIO cooling, is expected from previous studies, we argue that the ENSO strengthening for stronger trade winds, associated with TIO cooling, is related to the induced changes in ocean stratification. We illustrate this effect by computing different contributions to the Bjerknes stability index. Thus, our results suggest that the tropical Indian ocean temperatures are an important regulator of TIO mean state and ENSO dynamics.</p>

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