| Name: | Soumyaranjan Dash |
| Affiliation: | University of Hawwaii |
| Conference ID : | ASI2024_767 |
| Title : | Utilization of Ensemble Kalman Filter Data Assimilation Technique to Infer the Surface Flows with Surface Flux Transport model |
| Authors : | Soumyaranjan Dash1, Marc DeRosa2, Mausumi Dikpati3, Xudong Sun1,
Sushant Mahajan4, and Yang Liu4 |
| Authors Affiliation: | 1 Soumyaranjan Dash, Xudong Sun Affiliation (Institute for Astronomy, University of Hawaii, USA)
2 Marc DeRosa Affiliation (Lockheed Martin Solar and Astrophysics Laboratory, Palo Alto, CA, USA)
3 Mausumi Dikpati Affiliation (NCAR/High Altitude Observatory (HAO), CO, USA)
4 Sushant Mahajan, Yang Liu Affiliation (Stanford University, Stanford, CA, USA) |
| Mode of Presentation: | Poster |
| Abstract Category : | Sun, Solar System, Exoplanets, and Astrobiology |
| Abstract : | Constraining solar surface flows is crucial to understanding solar magnetic activity at different time scales. The build-up and dynamics of magnetic fluxes near the polar region play an important role in solar cycle predictions, solar wind dynamics, and open flux distribution. However, direct observation of the polar fields is still challenging due to high projection effects and data-driven models play an important role in estimating the distribution of polar fields more accurately. The north-south component of the Sun’s global flow, i.e. the meridional circulation that transports the flux from low latitudes and helps build up the polar field is utilized in surface flux transport (SFT) models to simulate photospheric magnetic field distribution. Since forecasting polar fields requires the forecast of the flow at a future time, it is necessary to reconstruct the flow behavior at the current time, so that future flow-patterns can be estimated. Data assimilation techniques like Ensemble Kalman Filter (EnKF) which utilizes observational data points to constrain the time advancement of a set of equations that govern the evolution of the physical system, has been adopted to reconstruct the meridional flow speed with solar dynamo modeling. In this study, we demonstrate using a ”toy model”, such as a simple harmonic oscillator with a randomly varying restoring force, how the EnKF techniques can reconstruct the time-dependent state vector. We additionally show how such EnKF methods, when used with a surface-flux transport model that captures the evolution of the solar photospheric magnetic field, can be used to make ensemble estimates of flow into the future that will be used to drive the model forward to forecast polar fields. |
