Weather and Climate Dynamics
Weather and Climate Dynamics
Weather and Climate Dynamics
Articles | Volume 1, issue 2
Weather Clim. Dynam., 1, 481–495, 2020
https://doi.org/10.5194/wcd-1-481-2020
Weather Clim. Dynam., 1, 481–495, 2020
https://doi.org/10.5194/wcd-1-481-2020

Research article 29 Sep 2020

Research article | 29 Sep 2020

On the intermittency of orographic gravity wave hotspots and its importance for middle atmosphere dynamics

Ales Kuchar et al.

Data sets

Accompanying data to <q>On the intermittency of orographic gravity wave hotspots and its importance for middle atmosphere dynamics</q> A. Kuchar https://doi.org/10.17632/j3hj7f9t67.2

S-RIP: Zonal-mean dynamical variables of global atmospheric reanalyses on pressure levels P. Martineau https://doi.org/10.5285/b241a7f536a244749662360bd7839312

CMAM30 Data Canadian Centre for Climate Modelling and Analysis http://climate-modelling.canada.ca/climatemodeldata/cmam/output/CMAM/CMAM30-SD/index.shtml

Web Interface Subsetter NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) http://disc.sci.gsfc.nasa.gov/daac-bin/FTPSubset2.pl

Japanese 55-year Reanalysis project Japan Meteorological Agency http://jra.kishou.go.jp/JRA-55/index_en.html

GRACILE: A comprehensive climatology of atmospheric gravity wave parameters based on satellite limb soundings, link to data in NetCDF format M. Ern, Q. T. Trinh, P. Preusse, J. C. Gille, M. G. Mlynczak, J. M. Russell III, and M. Riese https://doi.org/10.1594/PANGAEA.879658

Model code and software

kuchaale/wcd_2020: Third release of my WCD code repository A. Kuchar https://doi.org/10.5281/zenodo.3780101

mjucker/aostools: aostools v2.1.5 M. Jucker https://doi.org/10.5281/zenodo.1252733

Cartopy: a cartographic python library with a matplotlib interface Met Office http://scitools.org.uk/cartopy

detecta: A Python module to detect events in data M. Duarte https://github.com/demotu/detecta

seaborn: v0.7.1 (June 2016) M. Waskom, O. Botvinnik, Drewokane, P. Hobson, Y. David, Halchenko, S. Lukauskas, J. B. Cole, J. Warmenhoven, J. de Ruiter, S. Hoyer, J. Vanderplas, S. Villalba, G. Kunter, E. Quintero, M. Martin, A. Miles, K. Meyer, T. Augspurger, T. Yarkoni, P. Bachant, M. Williams, C. Evans, C. Fitzgerald, Brian, D. Wehner, G. Hitz, E. Ziegler, A. Qalieh, and A. Lee https://doi.org/10.5281/zenodo.54844

xarray: v0.8.0 S. Hoyer, C. Fitzgerald, J. Hamman, Akleeman, T. Kluyver, M. Roos, J. J. Helmus, Markel, P. Cable, F. Maussion, A. Miles, T. Kanmae, P. Wolfram, S. Sinclair, B. Bovy, Ebrevdo, R. Guedes, R. Abernathey, Filipe, S. Hill, N. Richards, A. Lee, N. Koldunov, M. Graham, Maciekswat, J. Gerard, I. Babuschkin, C. Deil, E. Welch, and A. Hilboll https://doi.org/10.5281/zenodo.59499

Ouranosinc/xclim: v0.15.0 D. Huard, T. J. Smith, T. Logan, P. Bourgault, Sbiner, D. Caron, P. Roy, Jwenfai, G. Rondeau, C. Whelan, and A. Stephens https://doi.org/10.5281/zenodo.3708391

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Short summary
Our study focuses on the impact of topographic structures such as the Himalayas and Rocky Mountains, so-called orographic gravity-wave hotspots. These hotspots play an important role in the dynamics of the middle atmosphere, in particular in the lower stratosphere. We study intermittency and zonally asymmetric character of these hotspots and their effects on the upper stratosphere and mesosphere using a new detection method in various modeling and observational datasets.