OS1.9

In recent decades, worldwide marine heat wave events have become stronger and more frequent. Especially in the Indian Ocean, where occurs the most significant sea surface temperature warming trend. We use observation and reanalysis data to extract the Indian Ocean marine heatwave events since 1981. And then analyzing the temporal and spatial characteristics of marine heatwave events through feature indicators. According to the different period of the development of the marine heatwave, the sources of predictability from the atmospheric and ocean circulation anomaly are revealed. Then five representative heat wave events will be selected, and multi-member ensemble hindcast with different lead times will be conducted for each event with CESM2 model. Based on the hindcast results, we evaluate the prediction skills for the Indian Ocean marine heatwaves. The capability of models to simulate the sub-seasonal to seasonal signals that affect the heat wave event will be examined eventually.

How to cite: Yu, Y.: The subseasonal to seasoanl predictability of marine heatwave in Indian Ocean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9751, https://doi.org/10.5194/egusphere-egu22-9751, 2022.

Based on SODA reanalysis data set from 1980 to 2016, this paper combined with a variety of mathematical statistical methods to study the intraseasonal variability characteristics of barrier layer thickness and its physical correlation with climate modes in the Bay of Bengal, and quantitatively explored the dynamic mechanism of intraseasonal variability of barrier layer in different sea areas in the Bay of Bengal by means of Marine dynamic diagnosis method. The relative contributions of different physical processes, such as oceanic advection, Kelvin waves, Rossby waves and freshwater fluxes (rainfall and river runoff), to the barrier layer were evaluated. The physical relationship between the seasonal variation of barrier layer thickness and the Indian Ocean dipole (IOD) is also discussed. The results show that the thickness of the barrier layer varies most obviously in the northern coast of the bay of Bengal and the western coast of Sumatra, and the maximum value of the barrier layer occurs in November ~ December every year, while the variation of the barrier layer in the northern coast is more regular than that in the southern coast. Horizontal advance and entrainment affect the thickness of barrier layer by affecting the salinity of the mixed layer. However, the thickness of barrier layer is mainly caused by the change of isothermal layer due to the obvious stratification of sea surface salinity in the Bay of Bengal. In the southern part of the Bay of Bengal near the equator, during the positive IOD events, the isothermal layer shallowness was caused by the negative anomaly of equatorial zonal wind stress from October to December. In negative IOD events, the equatorial zonal wind stress appears positive abnormality after June, which leads to the increase of isothermal layer in this period. As a result, the thickness of barrier layer In positive IOD years is smaller than that in normal years from October to December, and that in negative IOD years is greater than that in normal years from June to September. However, in the northern Bay of Bengal, the seasonal variability of barrier layer caused by different IOD events was not obvious. At the same time, the net heat flux upward at the air-sea interface will lead to instability and deepen the local mixed layer.

How to cite: Li, Y. and Wang, X.: Intraseasonal Variability in Barrier Layer Thickness in the Bay of Bengal and its Causes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3453, https://doi.org/10.5194/egusphere-egu22-3453, 2022.

According to Food and Agriculture Organization (FAO), the fisheries sector is a major contributor to coastal economy, ensuring nutritional security and generating employment opportunities is the central Indian Ocean covering Lakshadweep (India), Maldives and Sri Lanka. Harvesting of fish in this region happens mainly in coastal waters up to 100m depth. The fishing pressure on the stock in these waters has increased? Considerably and the deep-sea fishery has become an area for expansion in developed countries (FAO). However, fisheries in high seas pose scientific and technical challenges. High value fish are strongly influenced by the physical environment such as temperature, currents etc. Being able to predict this environment with high degree of accuracy is an invaluable tool for assisting on this expansion.

In order to help forecast the physical environment in the Lakshadweep Sea at medium to high resolutions we have developed two pre-operational data assimilating models at 1/20 (called LD20) and 1/60 (LD60) degrees of resolution based on with NEMO v3.6 as an engine. Both models have 50 geopotential computational levels with full steps in the vertical, they use Smagorinsky scheme for horizontal diffusion, bi-Laplacian viscosity for momentum, and k −epsilon turbulence scheme. The models use time-splitting algorithm with the ratio of baroclinic to barotropic time steps equal to 20. The Galperin parametrization is used to preserve the stratification. The models take initial and boundary conditions as well as data for assimilation from a global model at 1/12 degree resolution available from EU Copernicus Marine Service (CMEMS). The bathymetry is taken from GEBCO_2021. Meteorological forcing comes from the Met Office global model (NWPn768 and NWPn1280), and the tides are forced using OTIS tidal scheme (https://www.tpxo.net/otis). Both models run within Rose/Cylc software environment (https://metomi.github.io/rose/2019.01.2/html/index.html), a toolkit for orchestrating the running models that automatically executes tasks according to their schedules and dependencies.

The LD20 and LD60 models use a novel model-to-model data assimilation scheme (Shapiro and Ondina, 2021) by which the observations are assimilated indirectly, via a data assimilating parent model (CMEMS for LD20 and LD20 for LD60). The models have been run for 5 years from 01.01.2015. As expected, the models reveal more granularity of temperature, salinity and currents, particularly in the coastal areas. The model skill was assessed against The Operational Sea Surface Temperature and Ice Analysis (OSTIA) system. The results show improvement of the bias and Root-mean-square-error in the higher-resolution models compared to the lower-resolution ones. The model outputs can be helpful in the identification of small-scale ocean fronts which are linked to Potential Fishing Zones (Solanki et al, 2005)

References

Shapiro, GI. and Gonzalez-Ondina, JM., 2021. Model-to-model data assimilation method for fine resolution ocean modelling, Ocean Sci. Discuss. https://doi.org/10.5194/os-2021-77, in review.

Solanki HU, Mankodi PC, Nayak SR, Somvanshi VS. 2005. Evaluation of remote-sensing-based potential fishing zones (PFZs) forecast methodology. Continental Shelf Research. 25, (18):2163–2173

How to cite: Poovadiyil, M. S., Ondina, J. M. G., Tu, J., Asif, M., and Shapiro, G. I.: Pre-operational high-resolution ocean models of the Lakshadweep Sea (Indian Ocean), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-656, https://doi.org/10.5194/egusphere-egu22-656, 2022.

The tropical Indian Ocean (TIO) basin-wide warming occurred in 2020, following an extreme positive Indian Ocean Dipole (IOD) event instead of an El Niño event, which is the first record since the 1960s. The extreme 2019 IOD induced the oceanic downwelling Rossby waves and thermocline warming in the southwest TIO, leading to sea surface warming via thermocline-SST feedback during late 2019 to early 2020. The southwest TIO warming triggered equatorially antisymmetric SST, precipitation, and surface wind patterns from spring to early summer. Subsequently, the cross-equatorial “C-shaped” wind anomaly, with northeasterly–northwesterly wind anomaly north–south of the equator, led to basin-wide warming through wind-evaporation-SST feedback in summer.

The TIO warming excited a strong and westward extend anomalous anticyclone on the western North Pacific (WNPAC). The WNPAC is usually associated with strong El Niño-Southern Oscillation (ENSO), except for the 2020 case. In 2020, the anomalous winds in the northwestern flank of the WNPAC bring excess water vapor into central China. The water vapor, mainly carried from the western tropical Pacific, converges in central China and result in heavy rainfall. Unlike extreme events in 1983, 1998, and 2016, the extreme rainfall in 2020 was the first and only event during 1979-2020 that followed an extreme positive IOD rather than a strong El Niño. A theory of regional ocean-atmosphere interaction can well explain the processes, called the Indo-Western Pacific Ocean Capacitor (IPOC) effect. This study reveals the importance of IOD in the IPOC effect, which can dramatically influence the East Asian climate even without involving the ENSO in the Pacific.

How to cite: Du, Y., Cai, Y., Chen, Z., and Zhang, Y.: Extreme IOD induced IOB warming and its impacts on western North Pacific anomalous anticyclonic circulation transport in early summer 2020: without significant El Nino influence, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5055, https://doi.org/10.5194/egusphere-egu22-5055, 2022.

The El Niño-Southern Oscillation (ENSO) has great impacts on the Indian Ocean sea surface temperature (SST). In fact, two major modes of the Indian Ocean SST namely the Indian Ocean Basin (IOB) and Indian Ocean Dipole (IOD) modes, exerting strong influences on the IO rim countries, are both influenced by the ENSO. Based on a combined linear regression method, this study quantifies the ENSO impacts on the IOB and IOD during ENSO concurrent, developing, and decaying stages. After removing the ENSO impacts, the spring peak of the IOB disappears along with significant decrease in number of events, while the number of events is only slightly reduced and the autumn peak remains for the IOD. By isolating the ENSO impacts during each stage, this study reveals that the leading impacts of ENSO contribute to the IOD development, while the delayed impacts facilitate the IOD phase switch and prompt the IOB development. Besides, the decadal variations of ENSO impacts are various during each stage and over different regions. These imply that merely removing the concurrent ENSO impacts would not be sufficient to investigate intrinsic climate variability of the Indian Ocean, and the present method may be useful to study climate variabilities independent of ENSO.

How to cite: Zhang, L. and Du, Y.: Revisiting ENSO impacts on the Indian Ocean SST based on a combined linear regression method, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6704, https://doi.org/10.5194/egusphere-egu22-6704, 2022.

The role of the Indian Ocean heating anomalies in the ENSO teleconnection to South Asia and North Atlantic/European regions are investigated in the early winter season. Using re-analysis data, CMIP5 simulations and idealized numerical model experiments it is shown that the ENSO teleconnections in early winter in these regions are dominated by an ENSO-induced heating dipole in the Indian Ocean region. The Indian Ocean heating dipole leads to a Gill-type response in the South Asian region through Sverdrup balance. For a warm ENSO event, this response is a cyclonic upper-level anomaly that shifts the subtropical South Asian jet southward and increases precipitation in the that region. The cyclonic anomaly is the starting point of a stationary Rossby wavetrain that traverses the North Pacific and North American region and eventually reaches the North Atlantic. Here transient eddy feedbacks are likely to strengthen a response that spatially projects on the positive phase of the NAO and negative phase of the Atlantic ridge patterns. For cold ENSO events these anomalies are roughly opposite. The importance of the Indian Ocean heating dipole decreases towards late Winter due to a southward shift of the Indian Ocean rainfall climatology and a more dominant direct wavetrain from the central Pacific region.

How to cite: Kucharski, F., Abid, M. A., Joshi, M. K., Ashfaq, M., and Evans, K. J.: Role of Indian Ocean heating anomalies in the early winter ENSO teleconnection to the South Asian and North Atlantic regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9122, https://doi.org/10.5194/egusphere-egu22-9122, 2022.

In this study, the possible associations between the precipitation in the Southeastern Africa (SEAF, in this study area between 10°S to 25°S and 25°E to 53°E,) and the Antarctic Oscillation (AAO) in seasons from October to March (DJFM) was investigated. A statistically significant three-month lag correlation between them was found. After removing the El Niño/Southern Oscillation and Indian Ocean dipole signals, AAO from August to October (ASO-AAO) and DJFM-precipitation was significantly correlated, and the interannual correlation coefficients calculated by CMAP, GPCP, CRU, and GPCC were +0.63, +0.42, +0.59, and +0.53 (p<0.05), respectively. The positive correlation suggests that an enhancing (weakening) ASO‐AAO could be conducive to increases (decreases) of DJFM-precipitation in SEAF in austral summer. Further analyze the corresponding water vapor and circulation conditions. The responses of local and regional meteorological conditions to the ASO‐AAO support the AAO-precipitation links. During positive ASO-AAO years, in the troposphere low level is a cyclonic flow field in the high level is an anticyclonic circulation, accompanied by an enhanced ascending motion, and such a structure is favor to rainfall. A preliminary mechanism analysis shows that a positive ASO-AAO may induce a sea surface temperature warming tendency in Western Equatorial Indian Ocean.  This warming then enhances the regional ascending motion in SEAF and enhances the convection precipitation on the northwest SEAF. Moreover, the anomalous sensible and latent heating, in turn, intensifies the cyclone through a Gill-type response of the atmosphere. Through this positive feedback, the tropical atmosphere and SST patterns sustain their strength from spring to summer and eventually the SEAF precipitation.Note that’s for simplicity, the AAO index was multiplied by −1 throughout this study.

How to cite: Du, C. and Gong, D.: Influence of Antarctic Oscillation on the Southeastern Africa summer precipitation during 1979-2018, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5207, https://doi.org/10.5194/egusphere-egu22-5207, 2022.

The Bay of Bengal is under the influence of the monsoon and has a highly contrasted and variable Sea Surface Salinity (SSS). In situ salinity data is however too sparse to reconstruct interannual SSS variability of the Bay of Bengal prior to synoptic SSS mapping of SMOS launched in 2009.

Previous studies have demonstrated the ability of X minus C-band measurements, such as those of AMSR-E (May 2002-Oct 2011), to track SSS changes in high-contrast regions and at high Sea Surface Temperature (SST). Here, we apply this approach to reconstruct the Bay of Bengal SSS before 2010. We remove the effects of other geophysical variables such as SST, surface wind, and atmospheric water content using an empirical approach. SSS is then retrieved based on another empirical fit, trained on the ESA Climate Change Initiative (CCI) SSS dataset, over the AMSR-E and CCI common period (Jan 2010 to Oct 2011). Our first results are encouraging: spatial contrast between the low post-monsoon SSS values close to estuaries and along the west coast of India are reproduced. Our algorithm, however, tends to overestimate low SSS and underestimate high SSS values, possibly due to data contamination near the coast and/or a suboptimal removal of the signals from other geophysical variables. Nevertheless, the first results show a correct representation of the recognizable Indian Ocean Dipole (IOD) phenomena. Furthermore, we are currently creating and studying the use of a neuronal network with the intention to include more parameters in the algorithm.

The long-term goal of this work is to merge the C-, X-, and L-band data with in-situ measurements thus providing a long-term reconstruction of monthly SSS in the Bay of Bengal with a ~50 km resolution This dataset will be used to explore the physical processes that drive interannual SSS variability in regions where it is strong, such as near major river estuaries or along the west coast of India.

How to cite: Montero, M., Reul, N., de Boyer Montégut, C., Vialard, J., and Tournadre, J.: Towards long-term (2002-present) reconstruction of northern Indian Ocean Sea Surface Salinity based on AMSR-E and L-band Radiometer data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1749, https://doi.org/10.5194/egusphere-egu22-1749, 2022.

The Middle Pleistocene Transition (MPT) represents a critical rearrangement in the Earth’s climate state, expressed as a switch from obliquity-dominated glacial/interglacial patterns towards the quasi-periodic 100 kyr cyclicity that characterized the Earth’s recent climatic history. This fundamental reorganization in the climatic response to orbital forcing occurred without comparable changes in the astronomical rhythms before or during the MPT. Although the MPT has been intensely studied, the triggering mechanisms still remain poorly understood.

High-resolution records from the equatorial to mid-latitude shelf areas are to date rarely considered. For this reason, we investigated an expanded MPT section from International Ocean Discovery Program (IODP) Expedition 356 Site U1460A (eastern Indian Ocean, 27°22.4949′S, 112°55.4296′E, 214.5 mbsl). At Site U1460A, we combine high-resolution records of shallow marine productivity and organic matter flux (Auer et al., 2021) with new benthic and planktonic foraminifera records. By implementing this multi-proxy approach, we aim to better define the response of the Leeuwin Current System over the MPT on tropical shelf regions.

We will investigate benthic foraminifera assemblages at Site U1460A to reconstruct the bottom water community response to the Leeuwin Current System variations during the MPT. At the same time, the benthos/plankton (B/P) ratio of U1460A will be used to constrain the local impact of sea-level changes. Presently work is in progress to generate a B/P ratio for the MPT interval to better assess the impact of sea-level changes on a highly dynamic shelf setting on the western coast of Australia. Shallow coastal areas are markedly sensitive to the glacial/interglacial connected sea-level oscillations. Monitoring the variation in the B/P ratio can provide a preliminary overview of local sea-level changes along the Australian shelf which could be linked to the glacial/interglacial changes of the MPT. Higher values in this ratio indicate lowstand phases, while lower values are characteristic of higher sea level phases. The foraminifera data will be compared to a multi-proxy dataset (Auer et al., 2021) to constrain the local sea-level-driven environmental change over the MPT. Using this we will be able to untangle the impact of local versus global climatic change over the MPT.

Taxonomic identifications are underway following an extensive washing procedure developed for the sample material. Benthic foraminifera show moderate to good preservation, while the planktonic assemblage exhibits moderate to very good preservation. Foraminiferal tests appear white, opaque with apertures, and pores moderately covered by sediment. Some individuals are chipped or partially broken. Specimen preservation (plankton and benthos) decreases during glacial intervals where the abundance of planktonic foraminifera is low.

Finally, we recorded the presence of Globorotalia tosaensis at the top of our study interval at a depth of 61.72 mbsf (corresponding to sample U1460A-14F-3W, 20-24 cm). The continuous presence of this taxon indicates an age older than 0.61 Ma (Wade et al., 2011) at the top of our study interval, and therefore supports the age model of Auer et al. (2021).

How to cite: Arrigoni, A., Auer, G., Petrick, B., Mamo, B., and Piller, W. E.: Multi-proxy study of the Leeuwin Current System evolution along the northwestern coast of Australia during the Middle Pleistocene Transition, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2632, https://doi.org/10.5194/egusphere-egu22-2632, 2022.