The terrestrial atmospheric region between the altitudes of 90 km and 600 km is known as the thermosphere. The thermosphere is continuously modulated by particle emissions and magnetic fields that originate from the sun. These fields and emissions are intensified during events known as geomagnetic storms which alter the state of the thermosphere by dumping gigawatts of energy.
This energy is mostly deposited in the lower thermospheric regions of 150 km and below and can have potential hazardous repercussions on the technological assets of mankind. These storms can disrupt radio communication systems, interrupt electric power systems, threaten the safety of astronauts, and disrupt global position systems (GPS), all of which can wreck havoc on the technology-dependent human society. Hence, it is essential that we understand and predict the influence of these storms on the terrestrial thermosphere.
Our current understanding of the thermospheric response to the geomagnetic storms energy is limited to the observations of the thermospheric state at orbital altitudes of 400 km and above. The state of the terrestrial thermosphere at altitudes of 150 km and below during geomagnetic storms is largely unknown. This lower thermospheric response is instrumental in understanding and predicting the thermospheric state during geomagnetic storms. My research bridges this gap in understanding of the thermospheric response to storms by observing the change in lower thermospheric state in the event of geomagnetic storm occurrences.
To understand the thermospheric state, I use temperature data from SABER instrument on-board the TIMED satellite. What’s cool about SABER data is that it gives us global measurements of the lower thermosphere and has been operational since 2002, enabling statistical studies. I construct data driven models from SABER to understand what factors influence the storm response, what are the spatial and temporal attributes of the storm response, and, how do the existing physics and empirical models fare when compared to our data-driven modeling.
One of the aspects of this work involves separating all non-storm trends and modulations from the data to isolate storm response alone. To do so, we have built a “quiet time variation model” of the thermosphere. Using this model, we have been able to isolate storm response and understand how the internal state of the thermosphere gets altered by the storm. Here is a snapshot of the results from our study which provide a first ever global lower thermosperic storm response.
My research also deals with understanding how do the different features of the sun and thermosphere control this interaction between the storm energy and the thermosphere. For instance, how does the phase of the solar cycle control the thermospheric response? , how does the duration of the storm influence the thermospheric behavior?. To study this, we use machine learning to construct predictive models of the storm response and look at the models to figure out the influence of the feature space ( solar cycle, storm strength, storm duration etc.) . Below is a decision tree from one of our studies that shows the influence of various storm predictors in describing the presence or absence of delay in thermospheric response to storm energy (The numbers in red are resubstitution errors.)
This work has able to answer several outstanding questions on lower thermospheric response, such as, the time taken by the storm energy to overcome the thermsopheric inertia, the expected temperature increase for different classes of storms, how long does it take for the atmosphere to recover following a storm. You can read more about our findings and the models here.
Some of the places this work has been presented at:
- Suresh and C. M. Swenson, Study of Thermosphere Temperature Response to Geomagnetic Storms, EOS Trans. AGU Abstract SA21A-4048 (Presented at 2014 Fall Meeting, AGU, San Francisco, Calif.)
- Suresh, H. Godinez, R. Linares, and A. Walker, Global Thermospheric Density Response to a Geomagnetic Storms, 2014 LANL Summer School Reports.
- Suresh and C. M. Swenson, Measurement Of Lower Thermosphere Using the Optical Profiling of the Atmospheric Limb (OPAL) Cubesat Experiment, 2014 USNC-URSI National Radio Science Meeting.
- Suresh and C. M. Swenson, Study of Global Storm Time Energy Transport in the Lower Thermosphere using SABER Temperatures, EOS Trans. AGU Abstract SA31A-1973 (Presented at 2013 Fall Meeting, AGU, San Francisco, Calif. 9-13Dec), 2013.
- Suresh and C. M. Swenson, Global Thermosphere Temperature Response to Geomagnetic Storms, CEDAR MLT Poster Session, June 2013.
- Suresh and C. M. Swenson, Statistical Study of Storm-Time thermosphere Temperature, EOS Trans. AGU Abstract SA51A-2155 (Presented at 2012 Fall Meeting, AGU, San Francisco, Calif. 3-7 Dec), 2012.
- Suresh, C. M. Swenson, C. J. Mertens, and A. B. Christensen. Global thermospheric temperature response to geomagnetic storms. EOS Trans. AGU, Abstract SA11A-1566 (Presented at 2011 Fall Meeting, AGU, San Francisco, Calif. 5-9 Dec.), 2011.
- P Suresh, C. Swenson, and A.B. Christensen. A statistical nighttime analysis of the equatorial ionization anomaly. EOS Trans. AGU , Abstract SA51B-1638 (Presented at 2010 Fall Meeting, AGU, San Francisco, Calif. 13-17 Dec.), 2010.