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Probabilistic Ocean Prediction with Data Assimilation

The ocean plays a leading role in shaping our climate and weather patterns like precipitation, extreme heat, and cold. Even though the ocean plays a role in everything from the air we breathe to daily weather and climate patterns, we know very little about our ocean. Ocean models are numerical models with a focus on the properties of oceans and their circulation.

Challenges in ocean modelling

Uncertainties 

  • IC; BC; Terms; Equations

  • Sparse and Gappy Data

  • Intermittent Features

  • Non-stationary, non-Gaussian statistics.

 

Nonlinear multiscale ocean dynamics

  • Tides, Internal waves, river inflow, fronts, eddies, upwelling, etc.

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Some important Questions

  • What are the appropriate initial conditions for synoptic forecasting?

  • What are the features in the north Indian ocean that need to be modeled?

  • What are the data assimilation methods are suitable to generate correct initial conditions?

Projects

Bias Correction

The Coupled Model Intercomparison Project, now in its sixth phase (CMIP6), is a global effort to project future climate scenarios on following certain shared socioeconomic pathways (SSP). For the period 1950-2014, CMIP6 provides a historical model output. From 2015 future projections with four different SSP scenarios, viz. SSP126, 245, 370 and 585 are available. From 2015-2023, we also have reanalysis of the actual ocean and atmosphere variables in these years. 

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Our goal is to develop an accurate method (AONet) to correct this bias and provide updated future projections for scientific analysis. To this end, we developed a two phase deep neural network model that accepts monthly fields from the CMIP6 projections (all four SSP scenarios), and outputs a bias corrected field.

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Ocean Modelling

Development and applications of stochastic and deterministic primitive equation ocean modeling systems. Currently, we are using the Regional Ocean Modeling System (ROMS) and Multidisciplinary Simulation, Estimation, and Assimilation Systems (MSEAS) for the synoptic-scale regional prediction for the different parts of the Northern Indian Ocean.

Crucially, regional ocean forecasting with primitive equations has several sources of uncertainty which affect the forecast and introduce erros. To minimize these errors an accurate estimation of initial and boundary conditions, parametrizations etc is essential.

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Andaman Sea (published)

The Andaman Sea region is of major importance for India from a security and conservation viewpoint. Describing this region's salinity variability is fundamental for understanding its dynamics. We study the inter-annual salinity variability of the Andaman Sea during the Boreal summer using NEMO reanalysis data (1993-2018), focusing on its causal factors and impact. 

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We found that significant salinity is being transported into the Andaman Sea by SMC using EOF analysis. Particle trajectories experiment is conducted to understand the path of high salinity water of SMC. 

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Major features in the Bay of Bengal during the summer monsoon.

Data Assimilation (published)

Feature Oriented Regional Modelling System

Andaman Sea is inextricably linked to the Indian Ocean and plays a vital role in connecting the equatorial Indian Ocean to the Bay of Bengal. Figure shows the Andaman Sea region with the bathymetry. Very few studies exist in which data assimilative forecasts of this important region is attempted. Towards this end, first we create data-driven initial conditions of the region using feature models and Bayesian assimilation techniques. Thereafter we employ primitive equation ocean modelling systems  with data assimilation to forecast the ocean state in the region.

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Publications

  1. Pasula, Abhishek, and Deepak N. Subramani. "Cause and impact of Andaman Sea's salinity variability: A modeling Study." Deep Sea Research Part II: Topical Studies in Oceanography (2023): 105291. https://doi.org/10.1016/j.dsr2.2023.105291 

  2. Pasula Abhishek, Deepak N Subramani. “4D-Var Data Assimilation of Sea Surface Temperature in a Regional Model of the Andaman Sea” IEEE Oceans 2022. https://doi.org/10.1109/OCEANS47191.2022.9977119.

  3. Pasula Abhishek, and Sourav Sil. "Validation of Multi-Scale Ultra-High Resolution (MUR) Sea Surface Temperature with Coastal Buoys Observations and Applications for Coastal Fronts in the Bay of Bengal." In 2019 URSI Asia-Pacific Radio Science Conference (AP-RASC), pp. 1-4. IEEE, 2019, 10.23919/URSIAP-RASC.2019.8738356. https://doi.org/10.23919/URSIAP-RASC.2019.8738356

  4. Pasula, Abhishek, and Deepak N. Subramani. "A two-phase Neural Model for CMIP6 bias correction" Climate change (ready to submit).

Conferences

  1. Pasula Abhishek, Deepak N Subramani (2021),” AI-based correction of CMIP6 ocean projections”, Ocean Sciences Meeting 2024, Feb 16-23, 2024.

  2. Pasula Abhishek, Deepak N Subramani. “4D-Var Data Assimilation of Sea Surface Temperature in a Regional Model of the Andaman Sea” IEEE Oceans 2022.

  3. Pasula Abhishek, Deepak N Subramani (2021),” Cause and Impact of Andaman Sea’s Salinity Variability: A Modeling Study”, Ocean Sciences Meeting 2022, Feb 24- Mar 4, 2022.

  4. Deepak N. Subramani, Ratnakar Gadi, Abhishek P (2020), “Bayesian Estimation and Data Assimilation for Probabilistic Regional Forecasts in the northern Indian Ocean”, Ocean Sciences Meeting, San Diego, 16-21 Feb, 2020.

  5. Abhishek Pasula, and Sourav Sil (2019), “Validation of Multi-Scale Ultra-High Resolution (MUR) Sea Surface Temperature with Coastal Buoys Observations and Applications for Coastal Fronts in the Bay of Bengal”, URSI Asia-Pacific Radio Science Conference (AP-RASC 2019) New Delhi, 09-15 Mar, 2019.

  6. Abhishek Pasula, Samiran Mandal, Sourav Sil (2018), Observed Frontal eddies in the Coastal Bay of Bengal using HF Radar and High-Resolution SST data, Abstract [OS21D-1601] presented at 2018 Fall Meeting, American Geophysical Union, Washington, D.C., 10-14 Dec 2018.

  7. Abhishek Pasula, Samiran Mandal, Sourav Sil (2018), “East India Coastal Current and Frontal Eddies during Fall 2010: A study using HF Radar Currents and High-Resolution SST”, National Oceanography Workshop 2018, Indian National Centre for Ocean Information Services (INCOIS)-2018 at Hyderabad, 14-16 Nov 2018.

  8. Participated in the TROPICAL METEROLOGY-2018 by INDIAN METEROLOGICAL SOCIETY-National Symposium on understanding weather and climate variability: Research for Society at Banaras Hindu University- Varanasi. 24- 27 Oct 2018.

  9. Attended the Coastal Vulnerability Workshop by National Institute of Ocean Technology (NIOT) Chennai during December 2017.

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