Large-Scale Air-Sea Coupling Processes in the Bay of Bengal Using Space-Borne Observations

Sharma, Rashmi; Agarwal, Neeraj; Chakraborty, Abhisek; Mallick, Subrat Kumar; Buckley, Jared; Shesu, V.; Tandon, Amit

doi:10.5670/oceanog.2016.51

Cited by 12 publications

(7 citation statements)

References 43 publications

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“…SSS data from NASA's SMAP mission were taken from the Physical Oceanography Distributed Active Archive Center (PO.DAAC) at NASA's Jet Propulsion Lab (JPL) and is processed with the Combined Active Passive (CAP) algorithm as SMAPv4.2 (Entekhabi et al, 2010;Fore et al, 2016). SMAP SSS is available from April 2015 through present on a 0.25°grid globally and is found to resolve salinity variability in the Indian Ocean, including around coastlines (Agarwal et al, 2016;Prend et al, 2018;Subrahmanyam et al, 2018). SMAP-CAP was chosen because the addition of the CAP algorithm has been shown to significantly improve ISO identification, particularly along the coast (Shoup et al, 2019) and has the daily temporal resolution necessary to resolve higher frequency ISOs.…”

Section: Ocean Parametersmentioning

confidence: 99%

Monitoring Intraseasonal Oscillations in the Indian Ocean Using Satellite Observations

2020

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Intraseasonal oscillations (ISOs) in the Indian Ocean play a significant role in determining the active (wet) and break (dry) cycles of the southwest monsoon rainfall. In this study, we use satellite‐derived precipitation, sea level anomalies (SLAs), sea surface salinity (SSS), sea surface temperature, and surface winds to monitor the 30‐90‐day, 10‐20‐day, and 3‐7‐day ISOs, and how they influence local dynamics. The main focus of this work, however, is showing the importance of using SLA and SSS to monitor ISOs. Mixed Rossby gravity waves were found to induce convection associated with the southern cell of the 10‐20‐day mode, with surface winds from the northern cell modulating coastal Kelvin waves in the Bay of Bengal. The 10‐20‐day SSS response is instead more closely related to wind‐induced upwelling in the central Bay of Bengal and river runoff in the northern Bay. The 3‐7‐day mode was found to have a weak oceanic signal, as the monsoon trough is mainly positioned over land, though SSS captured the structure of the signal most clearly. This study highlights the need for high spatial resolution SLA in order to adequately capture 3‐7‐day oscillations in the monsoon trough.

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Section: Ocean Parametersmentioning

confidence: 99%

Monitoring Intraseasonal Oscillations in the Indian Ocean Using Satellite Observations

2020

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“…Since 2010, the Soil Moisture and Ocean Salinity (SMOS) satellite provides SSS measurements consistent with in situ observations of the equatorial and southern Indian Ocean from the RAMA array; however, large biases in the Bay of Bengal and Arabian Sea are likely caused by errors in the SSS retrieval due to land contamination and strong winds (Sharma et al 2016). With new satellite missions, remotely sensed SSS measurements will hopefully improve in their utility for marginal seas and coastal regions (Sharma et al 2016).…”

Section: The Indian Ocean's Influence On Regional Hydroclimatementioning

confidence: 99%

Untitled

2020

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THIS EDITION of Exchanges focuses on the recent decadal review of the Indian Ocean Observing System (IndOOS) and its outcomes. IndOOS was established in 2006 under the visionary leadership of Dr. Gary Meyers (1941-2016), the founding chair of the CLIVAR/IOC-GOOS Indian Ocean Regional Panel (IORP), to address the need for a sustained observing system that consists of a variety of observing platforms to support weather and climate research and prediction. Key founding components of the IndOOS were a tropical basin-wide mooring array-the Research moored Array for African Asian Australian Monsoon Analysis and Prediction (RAMA)-and a network of repeat expendable bathythermograph (XBT) lines. Broad international participation and support, facilitated and coordinated by the regional GOOS alliance (IO-GOOS) and the IndOOS Resources Forum (IRF), have played a crucial role in maximizing the limited resources available to implement the IndOOS. IndOOS has now passed the 10-year milestone. A full decadal review report has recently been released as the outcome of a three-year review effort led by the IORP co-chairs, Lisa Beal, Jérôme Vialard, and Mathew Koll Roxy, with a writing team comprising more than 60 scientific experts. As highlighted in their article in this issue, the decadal review has generated 136 actionable recommendations and led to a roadmap of an enhanced observing system for the next decade (2020-2030). This second phase, IndOOS-2 (Figure 1, cover page), is designed to meet the current and future societal needs for seamless prediction of Indian Ocean climate and ecosystems across a wide range of timescales, from days to seasons to years to decades to centuries and beyond. Achieving goals of IndOOS-2 will depend critically on capacity building, resource management, regional partnerships, and information sharing. It is becoming more important than ever that the scientific community actively engages with stakeholders, policy makers, and civil society in the Indian Ocean rim countries to build and sustain IndOOS-2, and to address the grand challenges identified by the World Climate Research Program and the societal outcomes envisioned under the UN Decade of Ocean Science for Sustainable Development. The main body of this edition is a condensed version of the full IndOOS-2 report, reorganized under five main science themes: natural and anthropogenic warming of the Indian Ocean, monsoon and regional airsea interaction, ocean processes and modelling, physical and biogeochemical processes and interactions, and climate information and prediction across timescales. These themed articles, written by many lead authors of the full report, are meant to provide collective reviews that address the progress made and the gaps that still exist in understanding the complex dynamical and biogeochemical processes in the Indian Ocean, and in improving prediction skills for weather, climate, and ecosystems. The OceanObs'19 (16-21 September 2019, Hawaii) called for new cooperative models for Observing System Governance to better align...

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“…The role of air–sea feedbacks in the Indian summer monsoon and its intraseasonal variability have gained attention in recent years, given the availability of high‐resolution models and new BoB observations as part of the joint Air–Sea Interactions Regional Initiative (ASIRI) and Ocean Mixing and Monsoon (OMM) programs (e.g., Lucas et al ., 2014; Mahadevan et al ., 2016; Wijesekera et al ., 2016). Several studies have investigated the processes responsible for the intraseasonal SST response in the BoB in both observations and models (e.g., Vecchi and Harrison, 2002; Shankar et al ., 2007; Sharma et al ., 2016). One‐dimensional processes are generally regarded to dominate the BoB upper‐ocean heat budget, particularly in the northern bay, where a shallow surface mixed layer responds quickly to changes in surface heat fluxes (e.g., Agarwal et al ., 2007; Weller et al ., 2016).…”

Section: Introductionmentioning

confidence: 99%

The influence of air–sea coupling on forecasts of the 2016 Indian summer monsoon and its intraseasonal variability

Valdivieso

Peatman

Klingaman

2020

Quart J Royal Meteoro Soc

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Daily initialized coupled and uncoupled numerical weather prediction (NWP) forecasts from the global Met Office Unified Model (MetUM) are compared for the 2016 Indian summer monsoon. Three MetUM configurations are used: atmosphere only (ATM), coupled to a mixed-layer ocean model (KPP), and coupled to a dynamical ocean model (NEMO). The analysis focuses on the impact of air-sea coupling, particularly in the Bay of Bengal (BoB), on NWP for monsoon rainfall. Seasonal-mean biases in all three configurations are highly consistent and driven by errors in atmospheric processes. Rainfall is initially overestimated over India, but underestimated over the BoB, the latter associated with too much shortwave radiation and too little cloud cover in MetUM. The excess shortwave radiation (>40 W⋅m −2 over the northwest BoB) is partially compensated by additional latent cooling, primarily due to overestimated surface wind speeds. In NEMO and KPP, coupling improves the timing of intraseasonal active and break phases over India, primarily the end of these phases, which are systematically too late in ATM. NEMO and KPP show a more realistic intraseasonal local phase relationship between sea surface temperature (SST) and rainfall throughout the BoB, but no configuration reproduces the observed significant lagged relationship between BoB SST and Indian rainfall. The lack of this relationship may be partly attributed to weak heat flux feedbacks to northern BoB SST, with the forecast shortwave feedback having systematically the wrong sign (positive) compared to satellite radiation, and thus contributing to SST warming at all lead times. Based on these MetUM forecasts, there is a limited impact of coupling on NWP for monsoon rainfall, both for the mean rainfall and intraseasonal variability. Further research to improve NWP for monsoon rainfall should focus on reducing MetUM atmospheric systematical biases. K E Y W O R D S air-sea coupling, atmospheric convection, Bay of Bengal, Indian monsoon, intraseasonal variability, weather forecasting This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Large-Scale Air-Sea Coupling Processes in the Bay of Bengal Using Space-Borne Observations

Cited by 12 publications

References 43 publications

Monitoring Intraseasonal Oscillations in the Indian Ocean Using Satellite Observations

Monitoring Intraseasonal Oscillations in the Indian Ocean Using Satellite Observations

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The influence of air–sea coupling on forecasts of the 2016 Indian summer monsoon and its intraseasonal variability

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