SWG5: Data Assimilation Across Disciplines

Overview

The Data Assimilation Across Disciplines working group is a cross-disciplinary group, including scientists from HAO and CISL, dedicated to the development and utilization of data assimilation for the betterment of understanding that ultimately leads to better forecast skill across the solar and geospace disciplines. The group works to develop solar and ionosphere-thermosphere data assimilation models. These models are subsequently used to address outstanding scientific questions, assess the limits of practical predictability, and improve space weather modelling and forecasting.

Objectives

  • Development of data assimilation into solar and geospace models in order to support scientific research, and enhance space weather forecasting capabilities
  • Application of data assimilation to estimate unknown model parameters and improve fundamental understanding of the solar and geospace systems
  • Understand the predictability of the upper atmosphere and how it relates to variable lower atmosphere and solar forcing
  • Test the predictability of quasi-periodic bursty "seasons" in space weather by assimilating solar magnetogram and helioseismic far-side data into solar TNO (Tachocline Nonlinear Oscillation) models
  • Promote HAO developed data assimilation models and products for adoption by the broader solar and geospace communities

Research Highlight

Development of a whole atmosphere-ionosphere data assimilation model

Sample template image
The total electron content at 75°W longitude and 1800 local time. Results are shown for the WACCMX+DART forecast initialized on January 15 (top panel), WACCMX+DART analysis fields (middle panel), and ground-based GPS observations (bottom panel).

Members

Graduate Research Assistant
Software Engineer/Programmer III
Senior Scientist and Section Head
Senior Scientist Emeritus
Project Scientist
Senior Scientist
Project Scientist II
Associate Scientist III
Postdoctoral Fellow
Project Scientist II
Visitor
Project Scientist III
Project Scientist IV