Structure of Atmosphere

(University of Washington ESS, 2015)

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)

○ Several mechanisms suggested; roles are under debate● Limited and controversial evidence of temperature effects

○ Observations: Cooling by 30-100K1,2,3 ○ 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)

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

15 to 8 days prior“Normal” polar

vortex

7 to 0 days priorPolar vortex distorted;

cold and warm cells

1 to 8 days afterPolar vortex broken;

warm cells

→ westerly winds → easterly winds Polar vortex shape

Data Used Ionosphere:

Sondrestrom Incoherent Scatter Radar (ISR)

● Located in Greenland● High latitude, 67°N

○ Nearly vertical magnetic field lines○ Proximity to polar vortex

● 32m fully steerable antenna● Does not continuously take data

(AMISR, 2007)

Stratosphere: Modern Era Retrospective Analysis for Research and

Applications (MERRA)Assimilative model based on decades of

stratospheric data

● MERRA-2 (1990-2016)● 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

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?

Creating an Ionospheric Database● Retrieved data from Madrigal Database● Selected positions close to overhead ● Database spans winters 2001-2016

○ 369 dates○ ~5130 hours

● Reduce noise and eliminate short-term variations in ionospheric parameters

○ Cubic smoothing spline fit

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

Data-Model Differences Summary● Geomagnetically quiet days

○ Included data with Ap3 < 12

● Focus on ion temperature because:

○ 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

○ Lower Ti at daytime is consistent

with long-term thermospheric cooling

● Local Time = UT - 3● Altitude = 300km

Investigating Outliers

● UT = 19● Altitude =

● UT = 19, Altitude = 70km● Positive correlation between

stratospheric wind anomalies and ionospheric temperature anomalies

● UT = 4, Altitude = 40km● Negative correlation between

stratospheric planetary wave activity and ionospheric temperature anomalies

Investigating Outliers (cont.)● Local time = UT - 3● Daytime 12-20 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

Summary● Sondrestrom ISR database of ionospheric anomalies created for winters

2001-2016○ MATLAB scripts and functions are generalizable to other ISR

● Found consistent differences between data collected in 2001-2016 and empirical ionospheric model (1990-2015)

○ 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

Future Work● Continue analyzing the stratospheric winds-ion temperature relationship

and planetary wave amplitude-ion temperature relationship○ Use local stratosphere/mesosphere wind conditions instead of zonal mean

● Investigate:○ 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

AcknowledgementsBig 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!!

References1. Goncharenko, L., and S.-R. Zhang (2008), Ionospheric signatures of sudden stratospheric warming: Ion temperature at middle

latitude, Geophys. Res. Lett., 35, L21103, doi: 10.1029/2008GL035684.2. Conde, M. G., & Nicolls, M. J. (2010). Thermospheric temperatures above Poker Flat, Alaska, during the stratospheric warming event of

January and February 2009. Journal of Geophysical Research: Atmospheres, 115(D3).3. Liu, H., Doornbos, E., Yamamoto, M., & Tulasi Ram, S. (2011). Strong thermospheric cooling during the 2009 major stratosphere

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5. 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).

6. 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), 357-365.

7. Holzworth, R., McCarthy, M., Zheng, H., & Anderson, T. (n.d.). Atmospheric Layers and Solar Input: Summary [Digital image]. Retrieved August 8, 2016, from http://earthweb.ess.washington.edu/space/ESS205/upperatmweb.pdf

8. Incoherent Scatter Radar Dish at Sondrestrom Research Facility [Digital image]. (n.d.). Retrieved August 8, 2016, from http://isr.sri.com/iono/amisr/amisr_downloads/amisr/Sondre_300dpi.jpg

9. 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), 1913-1928.

10. Coy, L., and Pawson, S. (2013). GEOS-5 Analyses and Forecasts of the Major Stratospheric Sudden Warming of January 2013. Retrieved August 8, 2016, from https://gmao.gsfc.nasa.gov/researchhighlights/SSW/