Structure of Atmosphere. (University of Washington ESS, 2015)

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2 Structure of Atmosphere (University of Washington ESS, 2015)

3 Motivation and Current State of Knowledge Spatial and temporal variations in ionospheric parameters cannot be explained by solar forcing Solid evidence of connections between the stratosphere and electron density in the equatorial ionosphere (observations + modeling) Limited and controversial evidence of temperature effects Several mechanisms suggested; roles are under debate Observations: Cooling by K1,2,3 Observations: Cooling + warming4 Modeling: no effects5 Modeling: complex temperature effects at high latitude6 Understanding what drives temperature changes in the upper thermosphere and ionosphere can lead to discovery of new mechanisms governing the behavior of planetary atmospheres Research strategy: examine ionospheric behavior during different states of the stratosphere (average vs. disturbed)

4 Largest stratospheric disturbance: Sudden Stratospheric Warming (SSW) Sudden changes in the winter hemisphere s westerly winds that result in an increase in stratospheric temperatures Thought to be produced by interaction between east-west winds and planetary waves Frequent feature of wintertime hemisphere Δ westerly winds easterly winds Polar vortex shape 15 to 8 days prior Normal polar vortex 7 to 0 days prior Polar vortex distorted; cold and warm cells 1 to 8 days after Polar vortex broken; warm cells

5 Data Used Ionosphere: Sondrestrom Incoherent Scatter Radar (ISR) Located in Greenland High latitude, 67 N Stratosphere: Modern Era Retrospective Analysis for Research and Applications (MERRA) Assimilative model based on decades of stratospheric data Nearly vertical magnetic field lines Proximity to polar vortex 32m fully steerable antenna Does not continuously take data (AMISR, 2007) MERRA-2 ( ) High lat/lon/time resolution gridded data Covers 0 - ~80 km (troposphere, stratosphere, mesosphere) Zonal mean winds (averaged over all longitudes) temperatures Planetary wave activity Temperature Geopotential height

6 Project Goals and Questions Goal: test hypothesis on a relationship between ionospheric anomalies and stratospheric anomalies What kinds of ionospheric anomalies are observed in incoherent scatter radar data during Sudden Stratospheric Warmings (SSWs) that could not be related to solar and geomagnetic drivers? What are their characteristics (magnitude, temporal, and spatial extent)? How do these anomalies vary with respect to the lifecycle of SSWs? How do these anomalies compare over multiple years?

7 Creating an Ionospheric Database Retrieved data from Madrigal Database Selected positions close to overhead Database spans winters dates ~5130 hours Reduce noise and eliminate short-term variations in ionospheric parameters Cubic smoothing spline fit

8 Creating a Database of Ionospheric Anomalies Sondrestrom Winter Ionosphere Model (SWIM) Empirical model based off of last several decades of data Produces electron density (Ne), electron temperature (Te), and ion temperature (Ti) given altitude, day of year, solar local time, f107, and ap3 Expected to remove daily and seasonal variations Eliminate solar and geomagnetic forcing

9 Data-Model Differences Summary Geomagnetically quiet days Focus on ion temperature because: Included data with Ap3 < 12 It provides direct evidence of energy coupling between different layers, It is close to neutral temperature1 Main feature: UT dependence Temperatures are higher than expected during nighttime and lower than expected during daytime Local Time = UT - 3 Altitude = 300km Lower Ti at daytime is consistent with long-term thermospheric cooling

10 Investigating Outliers UT = 19, Altitude = 70km Positive correlation between stratospheric wind anomalies and ionospheric temperature anomalies UT = 19 Altitude = UT = 4, Altitude = 40km Negative correlation between stratospheric planetary wave activity and ionospheric temperature anomalies

11 Investigating Outliers (cont.) Local time = UT - 3 Daytime UT: strong positive correlation between Ti and outliers in wind differences Observed in a large range of altitudes, stratosphere to mesosphere Negative correlation between Ti and outliers in planetary wave amplitude Nighttime pattern is more difficult to understand

12 Summary Sondrestrom ISR database of ionospheric anomalies created for winters Found consistent differences between data collected in and empirical ionospheric model ( ) MATLAB scripts and functions are generalizable to other ISR Cooler temperatures during daytime are consistent with long-term trends Warmer temperatures during nighttime are not explained Positive correlation between ion temperature anomalies and wind anomalies in altitude and time Negative correlation between ion temperature anomalies and wave amplitude anomalies Indication of connection between the state of upper thermosphere and the state of stratosphere

13 Future Work Continue analyzing the stratospheric winds-ion temperature relationship and planetary wave amplitude-ion temperature relationship Investigate: Use local stratosphere/mesosphere wind conditions instead of zonal mean Strong negative correlation at 7-8 UT Dependence of temperature anomalies on interplanetary magnetic field Effects of altitude UT variation found in data-model summary Repeat analysis for other high-latitude ISRs, such as Poker Flat in Alaska, EISCAT-Tromso, EISCAT-Svalbard

14 Acknowledgements Big thanks to: Larisa, for being a wonderful mentor and role model. Shunrong, for SWIM and for being kind and understanding during all those days I was tired and sleepy. Phil, for teaching us about ISR and space weather. Lynn Harvey, for providing MERRA-(1&2) data. MA Space Grant Consortium and NSF for funding. The entire Haystack community, for being so welcoming and friendly!!

15 References Goncharenko, L., and S.-R. Zhang (2008), Ionospheric signatures of sudden stratospheric warming: Ion temperature at middle latitude, Geophys. Res. Lett., 35, L21103, doi: /2008GL Conde, M. G., & Nicolls, M. J. (2010). Thermospheric temperatures above Poker Flat, Alaska, during the stratospheric warming event of January and February Journal of Geophysical Research: Atmospheres, 115(D3). Liu, H., Doornbos, E., Yamamoto, M., & Tulasi Ram, S. (2011). Strong thermospheric cooling during the 2009 major stratosphere warming.geophysical Research Letters, 38(12). Funke, B., López Puertas, M., Bermejo Pantaleón, D., García Comas, M., Stiller, G. P., von Clarmann, T.,... & Linden, A. (2010). Evidence for dynamical coupling from the lower atmosphere to the thermosphere during a major stratospheric warming. Geophysical Research Letters, 37(13). Fuller Rowell, T., Wu, F., Akmaev, R., Fang, T. W., & Araujo Pradere, E. (2010). A whole atmosphere model simulation of the impact of a sudden stratospheric warming on thermosphere dynamics and electrodynamics.journal of Geophysical Research: Space Physics, 115(A10). Yiğit, E., Medvedev, A. S., England, S. L., & Immel, T. J. (2014). Simulated variability of the high latitude thermosphere induced by small scale gravity waves during a sudden stratospheric warming. Journal of Geophysical Research: Space Physics, 119(1), Holzworth, R., McCarthy, M., Zheng, H., & Anderson, T. (n.d.). Atmospheric Layers and Solar Input: Summary [Digital image]. Retrieved August 8, 2016, from Incoherent Scatter Radar Dish at Sondrestrom Research Facility [Digital image]. (n.d.). Retrieved August 8, 2016, from Butler, A. H., Seidel, D. J., Hardiman, S. C., Butchart, N., Birner, T., & Match, A. (2015). Defining sudden stratospheric warmings. Bulletin of the American Meteorological Society, 96(11), Coy, L., and Pawson, S. (2013). GEOS-5 Analyses and Forecasts of the Major Stratospheric Sudden Warming of January Retrieved August 8, 2016, from