11 research outputs found

    Combined influence of oceanic and atmospheric circulations on Greenland sea ice concentration

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    The amount and spatial extent of Greenland Sea (GS) ice are primarily controlled by the sea ice export across the Fram Strait (FS) and by local seasonal sea ice formation, melting, and sea ice dynamics. In this study, using satellite passive microwave sea ice observations, atmospheric and a coupled ocean-sea ice reanalysis system, TOPAZ4, we show that both the atmospheric and oceanic circulation in the Nordic Seas (NS) act in tandem to explain the SIC variability in the south-western GS. Northerly wind anomalies associated with anomalously low sea level pressure (SLP) over the NS reduce the sea ice export in the south-western GS due to westward Ekman drift of sea ice. On the other hand, the positive wind stress curl strengthens the cyclonic Greenland Sea Gyre (GSG) circulation in the central GS. An intensified GSG circulation may result in stronger Ekman divergence of surface cold and fresh waters away from the south-western GS. Both of these processes can reduce the freshwater content and weaken the upper-ocean stratification in the south-western GS. At the same time, warm and saline Atlantic Water (AW) anomalies are recirculated from the FS region to the south-western GS by a stronger GSG circulation. Under weakly stratified conditions, enhanced vertical mixing of these subsurface AW anomalies can warm the surface waters and inhibit new sea ice formation, further reducing the SIC in the south-western GS.publishedVersio

    On the non-parametric changepoint detection of flow regimes in cyclone Amphan

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    The Bay of Bengal was witness to a severe cyclone named Amphan during the summer of the year 2020. The National Institute of Ocean Technology (NIOT), INDIA moorings BD08 and BD09 happened to be in the vicinity of the cyclone. The highly instrumented mooring recorded near-surface meteorological parameters like wind speed, sea surface temperature, and near-surface pressure. This article explores the possibility of using a non-parametric algorithm to identify different flow regimes using a one-month long time-series data of the near-surface parameters. The changes in the structure of the time series signal were statistically segmented using an unconstrained non-parametric algorithm. The non-parametric changepoint method was applied to time series of near-surface winds, sea surface temperature, sea level pressure, air temperature and salinity and the segmentations are consistent with visual observations. Identifying different data segments and their simple parameterization is a crucial component and relating them to different flow regimes is useful for the development of parametrization schemes in weather and climate models. The segmentations can considerably simplify the parametrization schemes when expressed as linear functions. Moreover, the usefulness of non-parametric automatic detection of data segments of similar statistical properties shall be more apparent when dealing with relatively long time series data

    Combined influence of oceanic and atmospheric circulations on Greenland sea ice concentration

    No full text
    The amount and spatial extent of Greenland Sea (GS) ice are primarily controlled by the sea ice export across the Fram Strait (FS) and by local seasonal sea ice formation, melting, and sea ice dynamics. In this study, using satellite passive microwave sea ice observations, atmospheric and a coupled ocean-sea ice reanalysis system, TOPAZ4, we show that both the atmospheric and oceanic circulation in the Nordic Seas (NS) act in tandem to explain the SIC variability in the south-western GS. Northerly wind anomalies associated with anomalously low sea level pressure (SLP) over the NS reduce the sea ice export in the south-western GS due to westward Ekman drift of sea ice. On the other hand, the positive wind stress curl strengthens the cyclonic Greenland Sea Gyre (GSG) circulation in the central GS. An intensified GSG circulation may result in stronger Ekman divergence of surface cold and fresh waters away from the south-western GS. Both of these processes can reduce the freshwater content and weaken the upper-ocean stratification in the south-western GS. At the same time, warm and saline Atlantic Water (AW) anomalies are recirculated from the FS region to the south-western GS by a stronger GSG circulation. Under weakly stratified conditions, enhanced vertical mixing of these subsurface AW anomalies can warm the surface waters and inhibit new sea ice formation, further reducing the SIC in the south-western GS

    Ocean- Atmosphere Interactions During Cyclone Nargis

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    Cyclone Nargis (Figure 1a) made landfall in Myanmar (formerly Burma) on 2 May 2008 with sustained winds of approximately 210 kilometers per hour, equivalent to a category 3–4 hurricane. In addition, Nargis brought approximately 600 millimeters of rain and a storm surge of 3–4 meters to the low-lying and densely populated Irrawaddy River delta. In its wake, the storm left an estimated 130,000 dead or missing and more than $10 billion in economic losses. It was the worst natural disaster to strike the Indian Ocean region since the 26 December 2004 tsunami and the worst recorded natural disaster ever to affect Myanmar

    Argo THE CHALLENGE OF CONTINUING 10 YEARS OF PROGRESS

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    ISSN: 1042-8275International audienceIn only 10 years, the Argo Program has grown from an idea into a functioning global observing system for the subsurface ocean. More than 3000 Argo floats now cover the world ocean. With these instruments operating on 10-day cycles, the array provides 9000 temperature/salinity/depth profiles every month that are quickly available via the Global Telecommunications System and the Internet. Argo is recognized as a major advance for oceanography, and a success for Argo's parent programs, the Global Ocean Data Assimilation Experiment and Climate Variability and Predictability, and for the Global Earth Observation System of Systems. The value of Argo data in ocean data assimilation (ODA) and other applications is being demonstrated, and will grow as the data set is extended in time and as experience in using the data set leads to new applications. The spatial coverage and quality of the Argo data set are improving, with consideration being given to sampling under seasonal ice at higher latitudes, in additional marginal seas, and to greater depths. Argo data products of value in ODA modeling are under development, and Argo data are being tested to confirm their consistency with related satellite and in situ data. Maintenance of the Argo Program for the next decade and longer is needed for a broad range of climate and oceanographic research and for many operational applications in ocean state estimation and prediction
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