1. March 31, 2016
Characterization of High- to Medium-Frequency
Gravity Waves in the Mesosphere Lower
Thermosphere Region using WACCM
Alan Sánchez
Chu Research Group
Cooperative Institute for Research in Environmental Sciences
2. Atmospheric Gravity Waves
Initial disturbance
Airflow over mountains
Tropospheric jet streams
Buoyancy force in atmosphere due to
vertically varying density
Attempts to restore equilibrium in air, resulting in wave
Carry large amounts of energy/momentum
Affect mean circulation
Affect mean temperature and winds antarctica.gov.au
nasa.gov
2
3. Mesoscale Gravity Waves
Defined as GWs with:
1-4 hr period
Horizontal wavelength 50-500 km
Typically created by lower atmosphere
activities
Propagate upwards and affect MLT activities,
weather systems, and space weather
Scarcely studied because of instrumental
limitations
ucar.edu
nasa.gov
3
4. Instrumental Limitations
There exists no single technique to completely obtain a GW’s parameters
Requires coordinated study with multiple instruments
Airglow imagers - λx, λy
LIDAR - λz
Radar - λz
LIDAR systems are limited to range of ~ 80-110 km
Much left to be discovered on origins and behavior in upper atmosphere
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5. Whole Atmosphere Community Climate Model (WACCM)
Comprehensive numerical model spanning the range of altitude from Earth’s surface
to the thermosphere
15 minute temporal resolution
¼ degree spatial resolution (~20 km)
Given 8 days of data from February 04-11, 2015
Latitude: ~39 to ~41°N
Longitude: 100 to 120 °W
Geopotential Height: ~80km to ~110km
Zonal wind (U), Meridional wind (V), Temperature (T), Vertical wind (W) 5
6. Initial Process
1. Analyze entire 8 day span from February 04-11 in search of high- to medium-
frequency GWs
2. Analyze data wrt time and one other dimension (i.e. time vs z)
a. Raw data
b. Raw data - perturbation (mean at each altitude)
c. Filtered data
i. Butterworth filter, high pass was used for initial investigation (up to 4hr period)
d. “Smoothed”
i. Subtract (smooth(U_pert(j,:),8)) from perturbation 6
7. Raw fields - Not particularly useful (besides in W)
7
11. Continued the study focusing on February 8
Choose wave(s) to characterize
Period
Phase
Vertical wavelength
Horizontal Wavelength
Searching for GW near Boulder region at ~98 km with period of ~ 2 hr
11
12. Decent results, but GW not clear enough/long enough to analyze.
Opted to check other latitudes/longitudes where this wave may be at a lower
altitude because it seems to be propagating upwards
Still looking for roughly 2 hr period wave around hr 13 of February 8, 2015
12
17. Characterizing a 3-dimensional, time-variant wave
Make wave a function of time and one other parameter
Obtain wave characteristics in wrt that dimension only
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18. Wave event fit to the proper form
Place appropriate limits on wave parameters
Fit all U, V, T, and W data in time and Z to this wave
equation
Derive amplitude (average)
Derive phase (average)
Derive λz
Obtain plots of fitted parameters
1818
23. Results (to be continued)
23
T [hr] 1.02 ± 0.10
λz [km] 13.63 ± 0.021
24. Conclusions, Broader Impacts, and Future Work
Preliminary results match well with experimental observations
First validation of newly refined WACCM
Enables an unprecedented study of source of GWs,as well as behavior in upper
atmosphere, by eliminating instrumental limitations,
Request lower altitude/higher altitude data from NCAR
Continue studying this GW
Expand study to other GWs
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Antarctica - from ground
NASA - from ISS looking over Atlantic Ocean
energy/momentum == change in mean circulation and mean temperature/winds
Antarctica - from ground
NASA - from ISS looking over Atlantic Ocean
energy/momentum == change in mean circulation and mean temperature/winds
Lidars usually operate around 80 to 110 km, STAR Lidar can reach 120 km
AMTM only at 87 km
WACCM - from NCAR’s Whole Atmoshp Working Group
Longitude 10x better
Latitude 8x better
80x better in horizontal
Vertical - 4x better
300x increase of resolution
2015 model resolution was improved substantially - model needs to be validated
Mention how taken average across 8 day span is very succeptible to error. Was only used to find day where strong wave events are present
Include W
Easy to see in W, not easy in T, U, V, bc larger scale waves are more dominant in these parameters
Why? Intrinsic property of waves
Higher better manifest in W
Use MATLAB function butter(). Type of signal processing filter designed to have as flat a frequency response as possible
Obtain parameters b,a
Use filtfilt()
zero-phase digital filtering by processing the input data, x, in both the forward and reverse directions
1.762 hr peak period
Peak period not found at 80km, rather at 85km
High pass filter with 1.5 max period
Trial and error process to figure out how narrow… used 1.02 pm 0.1 h
Change xlabel
Fits GW to a single period -- looks identical to filtered data bc of how narrow the filter applied was +/- 0.1 hr