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@ARTICLE{Xu:1020214,
author = {Xu, Shuang and Carstens, Justin N. and France, Jeff A. and
Randall, Cora E. and Yue, Jia and Harvey, V. Lynn and Gong,
Jie and Lumpe, Jerry and Hoffmann, Lars and Russell, James
M.},
title = {{S}easonal {D}istribution of {G}ravity {W}aves {N}ear the
{S}tratopause in 2019–2022},
journal = {Earth and Space Science},
volume = {11},
number = {1},
issn = {2333-5084},
address = {Malden, Mass.},
publisher = {American Geophysical Union},
reportid = {FZJ-2023-05881},
pages = {e2023EA003076},
year = {2024},
abstract = {The cloud imaging and particle size (CIPS) instrument
onboard the Aeronomy of Ice in the Mesosphere satellite
provides images of gravity waves (GWs) near the stratopause
and lowermost mesosphere (altitudes of 50–55 km). GW
identification is based on Rayleigh Albedo Anomaly (RAA)
variances, which are derived from GW-induced fluctuations in
Rayleigh scattering at 265 nm. Based on 3 years of CIPS RAA
variance data from 2019 to 2022, we report for the first
time the seasonal distribution of GWs entering the
mesosphere with high (7.5 km) horizontal resolution on a
near-global scale. Seasonally averaged GW variances clearly
show spatial and temporal patterns of GW activity, mainly
due to the seasonal variation of primary GW sources such as
convection, the polar vortices and flow over mountains.
Measurements of stratospheric GWs derived from Atmospheric
InfraRed Sounder (AIRS) observations of 4.3 μm brightness
temperature perturbations within the same 3-year time range
are compared to the CIPS results. The comparisons show that
locations of GW hotspots are similar in the CIPS and AIRS
observations. Variability in GW variances and the monthly
changes in background zonal wind suggest a strong GW-wind
correlation. This study demonstrates the utility of the CIPS
GW variance data set for statistical investigations of GWs
in the lowermost mesosphere, as well as provides a reference
for location/time selection for GW case studies.},
cin = {JSC},
ddc = {550},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511)},
pid = {G:(DE-HGF)POF4-5111},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001132904600001},
doi = {10.1029/2023EA003076},
url = {https://juser.fz-juelich.de/record/1020214},
}