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 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.

scholarly journals Systematic Errors in South Asian Monsoon Simulation: Importance of Equatorial Indian Ocean Processes

2017 ◽  
Vol 30 (20) ◽  
pp. 8159-8178 ◽  
Author(s):  
H. Annamalai ◽  
Bunmei Taguchi ◽  
Julian P. McCreary ◽  
Motoki Nagura ◽  
Toru Miyama
Keyword(s):  
Indian Ocean ◽  
South Asia ◽  
South Asian ◽  
Coupled Model ◽  
Equatorial Indian Ocean ◽  
Coupled Processes ◽  
Cmip5 Models ◽  
Model Errors ◽  
Bjerknes Feedback ◽  
Sst Bias

Abstract Forecasting monsoon rainfall using dynamical climate models has met with little success, partly due to models’ inability to represent the monsoon climatological state accurately. In this article the nature and dynamical causes of their biases are investigated. The approach is to analyze errors in multimodel-mean climatological fields determined from CMIP5, and to carry out sensitivity experiments using a coupled model [the Coupled Model for the Earth Simulator (CFES)] that does represent the monsoon realistically. Precipitation errors in the CMIP5 models persist throughout the annual cycle, with positive (negative) errors occurring over the near-equatorial western Indian Ocean (South Asia). Model errors indicate that an easterly wind stress bias Δτ along the equator begins during April–May and peaks during November; the severity of the Δτ is that the Wyrtki jets, eastward-flowing equatorial currents during the intermonsoon seasons (April–May and October–November), are almost eliminated. An erroneous east–west SST gradient (warm west and cold east) develops in June. The structure of the model errors indicates that they arise from Bjerknes feedback in the equatorial Indian Ocean (EIO). Vertically integrated moisture and moist static energy budgets confirm that warm SST bias in the western EIO anchors moist processes that cause the positive precipitation bias there. In CFES sensitivity experiments in which Δτ or warm SST bias over the western EIO is artificially introduced, errors in the EIO are similar to those in the CMIP5 models; moreover, precipitation over South Asia is reduced. An overall implication of these results is that South Asian rainfall errors in CMIP5 models are linked to errors of coupled processes in the western EIO, and in coupled models correct representation of EIO coupled processes (Bjerknes feedback) is a necessary condition for realistic monsoon simulation.

scholarly journals Moist Dynamics of Extended Monsoon Breaks over South Asia

2012 ◽  
Vol 25 (11) ◽  
pp. 3810-3831 ◽  
Author(s):  
V. Prasanna ◽  
H. Annamalai
Keyword(s):  
Indian Ocean ◽  
South Asia ◽  
Coupled Model ◽  
Equatorial Indian Ocean ◽  
Hadley Circulation ◽  
Central India ◽  
Radiative Heating ◽  
Moisture Distribution ◽  
Advection Equation ◽  
Circulation Anomalies

In the present research to identify moist processes that initiate and maintain extended monsoon breaks over South Asia moisture and moist static energy (MSE) budgets are performed on the newly available European Centre for Medium-Range Weather Forecasts Interim reanalysis (ERA-Interim) and ensemble integrations from a coupled model. The hypothesis that interaction between moist physics and regional circulation and the role of cloud–radiation feedbacks are important is tested. Budget diagnostics show that dry advection is the principal moist process to initiate extended breaks. Its sources are (i) regional anticyclonic circulation anomalies forced by equatorial Indian Ocean negative rainfall anomalies advect low MSE air from north to central India, and (ii) rainfall enhancement over tropical west Pacific forces cyclonic circulation anomalies to its northwest as a Rossby wave response, and the northerlies at the poleward flank of this circulation advect air of low MSE content from north. The dominance of anomalous wind acting on climatological moisture gradient is confirmed from an examination of the moisture advection equation. A partition of various flux terms indicates that over central India, due to an increase in upwelling shortwave and longwave fluxes, radiative cooling increases during extended breaks. Here, enhanced rainfall over the equatorial Indian Ocean promotes anomalous radiative warming due to trapping of upwelling fluxes. The differential radiative heating anchors a local Hadley circulation with descent over central India. A direct implication of this research is that observational efforts are necessary to monitor the three-dimensional moisture distribution and cloud–radiation interaction over the monsoon region that would aid in better understanding, modeling, and predicting extended monsoon breaks.

Indian Ocean Dipole Response to Global Warming in the CMIP5 Multimodel Ensemble*

2013 ◽  
Vol 26 (16) ◽  
pp. 6067-6080 ◽  
Author(s):  
Xiao-Tong Zheng ◽  
Shang-Ping Xie ◽  
Yan Du ◽  
Lin Liu ◽  
Gang Huang ◽  
...  
Keyword(s):  
Global Warming ◽  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Coupled Model ◽  
Equatorial Indian Ocean ◽  
Easterly Wind ◽  
Thermocline Feedback ◽  
Intercomparison Project ◽  
Eastern Equatorial Indian Ocean ◽  
Dipole Response

Abstract The response of the Indian Ocean dipole (IOD) mode to global warming is investigated based on simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). In response to increased greenhouse gases, an IOD-like warming pattern appears in the equatorial Indian Ocean, with reduced (enhanced) warming in the east (west), an easterly wind trend, and thermocline shoaling in the east. Despite a shoaling thermocline and strengthened thermocline feedback in the eastern equatorial Indian Ocean, the interannual variance of the IOD mode remains largely unchanged in sea surface temperature (SST) as atmospheric feedback and zonal wind variance weaken under global warming. The negative skewness in eastern Indian Ocean SST is reduced as a result of the shoaling thermocline. The change in interannual IOD variance exhibits some variability among models, and this intermodel variability is correlated with the change in thermocline feedback. The results herein illustrate that mean state changes modulate interannual modes, and suggest that recent changes in the IOD mode are likely due to natural variations.

Impact of horizontal resolution on sea surface temperature bias and air–sea interactions over the tropical Indian Ocean in CFSv2 coupled model

2020 ◽  
Vol 40 (11) ◽  
pp. 4903-4921
Author(s):  
Hari Prasad KBRR ◽  
Sreenivas Pentakota ◽  
Suryachandra Rao Anguluri ◽  
Gibies George ◽  
Kiran Salunke ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Horizontal Resolution ◽  
Sea Surface ◽  
Temperature Bias

scholarly journals Correlation between subsurface salinity anomalies in the Bay of Bengal and the Indian Ocean Dipole and governing mechanisms

2020 ◽  
Author(s):  
Zheen Zhang ◽  
Thomas Pohlmann ◽  
Xueen Chen
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Indian Ocean Dipole ◽  
Equatorial Indian Ocean ◽  
Ocean Model ◽  
Subsurface Temperature ◽  
Remote Forcing ◽  
Salinity Variability ◽  
Eastern Equatorial Indian Ocean ◽  
The Indian Ocean

Abstract. Lead-lag correlations between the subsurface temperature/salinity anomalies in the Bay of Bengal (BoB) and the Indian Ocean Dipole (IOD) are revealed in model results, ocean synthesis, and observations. Mechanisms for such correlations are further investigated using the Hamburg Shelf Ocean Model (HAMSOM), mainly on the salinity variability. It is found that the subsurface salinity anomaly of the BoB positively correlates to the IOD with a lag of three months on average, while the subsurface temperature anomaly negatively correlates. The model results suggest the remote forcing from the equatorial Indian Ocean dominates the interannual subsurface salinity variability in the BoB. The coastal Kelvin waves carry signals of positive (negative) salinity anomalies from the eastern equatorial Indian Ocean and propagate counterclockwise along the coasts of the BoB during positive (negative) IOD events. Subsequently westward Rossby waves propagate these signals to the basin at a relatively slow speed, which causes a considerable delay of the subsurface salinity anomalies in the correlation. By analyzing the salinity budget of the BoB, it is found that the diffusion dominates the salinity changes near the surface, while the advection dominates the subsurface; the vertical advection of salinity contributes positively to this correlation, while the horizontal advection contributes negatively. These results suggest that the IOD plays a crucial role in the interannual subsurface salinity variability in the BoB.

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

scholarly journals Correlation between subsurface salinity anomalies in the Bay of Bengal and the Indian Ocean Dipole and governing mechanisms

Ocean Science ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 393-409
Author(s):  
Zheen Zhang ◽  
Thomas Pohlmann ◽  
Xueen Chen
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Indian Ocean Dipole ◽  
Equatorial Indian Ocean ◽  
Ocean Model ◽  
Subsurface Temperature ◽  
Remote Forcing ◽  
Salinity Variability ◽  
Eastern Equatorial Indian Ocean ◽  
The Indian Ocean

Abstract. Lead–lag correlations between the subsurface temperature and salinity anomalies in the Bay of Bengal (BoB) and the Indian Ocean Dipole (IOD) are revealed in model results, ocean synthesis, and observations. Mechanisms for such correlations are further investigated using the Hamburg Shelf Ocean Model (HAMSOM), mainly relating to the salinity variability. It is found that the subsurface salinity anomaly of the BoB positively correlates to the IOD, with a lag of 3 months on average, while the subsurface temperature anomaly correlates negatively. The model results suggest the remote forcing from the equatorial Indian Ocean dominates the interannual subsurface salinity variability in the BoB. The coastal Kelvin waves carry signals of positive (negative) salinity anomalies from the eastern equatorial Indian Ocean and propagate counterclockwise along the coasts of the BoB during positive (negative) IOD events. Subsequently, westward Rossby waves propagate these signals to the basin at a relatively slow speed, which causes a considerable delay of the subsurface salinity anomalies in the correlation. By analyzing the salinity budget of the BoB, it is found that diffusion dominates the salinity changes near the surface, while advection dominates the subsurface; the vertical advection of salinity contributes positively to this correlation, while the horizontal advection contributes negatively. These results suggest that the IOD plays a crucial role in the interannual subsurface salinity variability in the BoB.

scholarly journals Simulation of Indian summer monsoon rainfall, interannual variability and teleconnections: Evaluation of CMIP6 models

2021 ◽  
Author(s):  
Kavirajan Rajendran ◽  
Sajani Surendran ◽  
Stella Jes Varghese ◽  
Anjali Sathyanath
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Summer Monsoon ◽  
Inverse Relationship ◽  
Monsoon Rainfall ◽  
Coupled Model ◽  
Equatorial Indian Ocean ◽  
Summer Monsoon Rainfall ◽  
Boreal Summer ◽  
Model Intercomparison

Abstract We analyse the performance of global climate models of 6th generation of Coupled Model Intercomparison Project (CMIP6) in simulating climatological summer monsoon rainfall over India, interannual variability (IAV) of all-India summer monsoon rainfall (ISMR) and its teleconnections with rainfall variability over equatorial Pacific and Indian Oceans. The multimodel ensemble mean (MME) of 61 CMIP6 models shows the best skill in simulating mean monsoon rainfall over India compared to the MMEs of 6th generation atmosphere-only models (AMIP6) and the previous generations of Atmospheric and Coupled Model Intercomparison Projects (AMIPs and CMIPs). Systematic improvement and reduction in bias are evident from lower to higher AMIPs/CMIPs. Still, there exists dry bias over a narrow region of the monsoon zone of central India besides wet and cold bias over the surrounding oceans. The persistence of errors in atmosphere-only models hints that the source of errors could be with atmosphere models. Fifteen CMIP6 models selected through objective criteria, perform the best in simulating mean monsoon, IAV of ISMR, the strong inverse relationship between ISMR and Boreal summer El Nino-Southern Oscillation (ENSO), and the inverse relationship between all-India rainfall and north-west tropical Pacific rainfall in June. Several models reproduce the dipole structure of Equatorial Indian Ocean Oscillation (EQUINOO) with the centres over western and eastern equatorial Indian Ocean. But, ISMR-EQUINOO relationship in many of them is opposite to the observed. Our analysis implies the need for capturing ISMR-EQUINOO link to improve the simulation of IAV of ISMR which is crucial for reliable monsoon prediction and projection.

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