Upper ocean high resolution regional modeling of the Arabian Sea and Bay of Bengal

Dwivedi, Suneet; Mishra, Alok Kumar; Srivastava, Atul

doi:10.1007/s13131-019-1439-x

Cited by 19 publications

(8 citation statements)

References 72 publications

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“…In contrast to this, the poleward increasing tendency is noticed. These features are captured in both simulations which is consistent with the previous studies (Rao and Sivakumar 2000;Shenoi et al 2002;Prasad 2004;Dwivedi et al 2019).The spatial evolution of the seasonal cycle of the AS SST as observed in TMI-SST is reasonably captured by both models (Figure 2). The highest SST is obtained during the Monsoon months of JJASandthe lowest SST during the winter months of NDJF.…”

Section: Resultssupporting

confidence: 90%

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Demonstrating the potential of Regional Ocean Model System in simulating the upper ocean characteristic over Arabian Sea: impact of horizontal resolution

Kushwaha

Pandey

2021

Preprint

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This study attempted to demonstrate the skill of the regional ocean model system (ROMS) is simulating the hydrographic property of the Arabian Sea (AS). Additionally, the impact of horizontal resolution is investigated. In this regard, ROMS is integrated over AS covering [30˚E-80˚E; 5˚N-30N˚] at two different horizontal resolutions 1/6˚(~ 17km) and 1/4˚(~ 25km) for ten years. The comparison of model results with available observation and reanalysis indicates reasonable resemblances in reproducing the spatial-temporal distribution of surface and subsurface hydrographic property i.e. sea surface temperature (SST), sea surface salinity (SSS), sea surface currents, and subsurface temperature and salinity at both resolutions. The increasing resolution shows minimal improvement, indicating the fact that its not always guaranty to enhance the performance towards increasing resolution for every aspect.

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Section: Resultssupporting

confidence: 90%

“…The high SST bias with respect to TMI in the northern AS except in the southern AS. The bias shown along the coasts, it may be ignored since TMI has known problems along the coasts (Wang et al, 2011;Dwivedi et Al. 2019).…”

Section: Resultsmentioning

confidence: 99%

Demonstrating the potential of Regional Ocean Model System in simulating the upper ocean characteristic over Arabian Sea: impact of horizontal resolution

Kushwaha

Pandey

2021

Preprint

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“…ROM simulated values closely agree with observations over the homogeneous rainfall zones. We notice that the root mean square error (RMSE) between the model and observation is relatively less than the observed rainfall standard deviation for all zone except SPI, thus demonstrating our simulation's quality as a lesser RMSE of the model than observed variability (standard deviation) is good skill score to measure the quality of the model (Srivastava et al, 2016(Srivastava et al, , 2018Dwivedi et al, 2018Dwivedi et al, , 2019Mishra et al, 2020a) Noticeably, the increasing resolution results in improving the model's performance over most of the study regions except SPI where performance is found to degrade with increasing resolution. The ISM undergoes enhanced and suppressed rainfall activity over India on an intraseasonal time scale (Goswami and Ajaya Mohan, 2001;Dwivedi et al, 2006;Shahi et al, 2018).…”

Section: Spatiotemporal Variability Of Ismrmentioning

confidence: 68%

Impact of horizontal resolution on monsoon precipitation for CORDEX-South Asia: A regional earth system model assessment

Mishra

Kumar

Dubey

et al. 2021

Atmospheric Research

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For the first time for CORDEX-South Asia, a high-resolution regional earth system model (ROM) is adopted to assess the impact of horizontal resolution (0.22 • and 0.11 • ) in simulating the Indian summer monsoon rainfall (ISMR) and the underlying spatiotemporal variability. ROM at both resolutions bears a close resemblance to observations in simulating the mean precipitation climatology compared to other regional climate models (RCMs) participated in CORDEX-South Asia. ROM shows substantial improvement relative to the ensemble mean of the RCMs included in CORDEX-South Asia. While comparing both simulations with observations, some systematic wet and dry bias over Central India (CI) and Northern Western Ghats is noticed. In general, the wet/dry bias over India is mainly associated with the overestimation/underestimation of the large-scale/convective component. Increasing horizontal resolution from 0.22 • to 0.11 • significantly adds value in simulating the JJAS mean precipitation by reducing the wet bias over western central India (WCI) and southern peninsular India and dry bias over eastern CI. The reduction in wet/dry bias is mainly associated with suppression/enhancement of the large scale/convective precipitation. This improvement in mean precipitation is partially due to the improved representation of the propagation of mesoscale systems such as boreal summer intraseasonal oscillation (eastward and northward). Despite the above improvements, the wet precipitation bias, particularly over WCI, persists. The weaker Findlater Jet associated with weaker land-ocean thermal contrast caused by the warm sea surface temperature (SST) bias over the western Arabian Sea (AS) suggests that AS moisture transport does not contribute to the wet bias over India. The wet bias is possibly associated with favourable atmospheric conditions (atmospheric instability).

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“…Suneet et al. (2019) demonstrated that air‐sea fluxes contribute the most to the ML heat budget in the Arabian Sea. The surface heat budget is characterized by winter net heat loss and spring net heat gain due to an increase of Q SW , which drives a positive buoyancy flux in the upper ocean, resulting in different stratification regimes between seasons (Figures 3 and 4).…”

Section: Discussionmentioning

confidence: 99%

Seasonal to Intraseasonal Variability of the Upper Ocean Mixed Layer in the Gulf of Oman

2022

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High‐resolution underwater glider data collected in the Gulf of Oman (2015–2016), combined with reanalysis data sets, describe the spatial and temporal variability of the mixed layer during winter and spring. We assess the effect of surface forcing and submesoscale processes on upper ocean buoyancy and their effects on mixed layer stratification. Episodic strong and dry wind events from the northwest (Shamals) drive rapid latent heat loss events which lead to intraseasonal deepening of the mixed layer. Comparatively, the prevailing southeasterly winds in the region are more humid, and do not lead to significant heat loss, thereby reducing intraseasonal upper ocean variability in stratification. We use this unique data set to investigate the presence and strength of submesoscale flows, particularly in winter, during deep mixed layers. These submesoscale instabilities act mainly to restratify the upper ocean during winter through mixed layer eddies. The timing of the spring restratification differs by three weeks between 2015 and 2016 and matches the sign change of the net heat flux entering the ocean and the presence of restratifying submesoscale fluxes. These findings describe key high temporal and spatial resolution drivers of upper ocean variability, with downstream effects on phytoplankton bloom dynamics and ventilation of the oxygen minimum zone.

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Upper ocean high resolution regional modeling of the Arabian Sea and Bay of Bengal

Cited by 19 publications

References 72 publications

Demonstrating the potential of Regional Ocean Model System in simulating the upper ocean characteristic over Arabian Sea: impact of horizontal resolution

Demonstrating the potential of Regional Ocean Model System in simulating the upper ocean characteristic over Arabian Sea: impact of horizontal resolution

Impact of horizontal resolution on monsoon precipitation for CORDEX-South Asia: A regional earth system model assessment

Seasonal to Intraseasonal Variability of the Upper Ocean Mixed Layer in the Gulf of Oman

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