UA-ICON Current-Climate Simulation: East Asia Gravity Wave Forcing (EA)

doi:10.26050/WDCC/UAICON_GW_EA

Mehrdad, Sina; Marjani, Sajedeh; Jacobi, Christoph

ExperimentDOI
Summary
This experiment provides output from a six-member ensemble simulation using the UA-ICON (Upper Atmosphere ICON) general circulation model, version 2.6.6. The model setup uses a high-top configuration with 120 vertical levels extending to ~150 km altitude and a horizontal resolution of ICON R2B4 (~160 km), allowing detailed representation of processes in the troposphere, stratosphere, mesosphere, and lower thermosphere. The experiment uses a time step of 360 seconds and includes a comprehensive physics package (ICON numerical weather prediction, NWP, package), notably gravity wave (GW) parameterizations for both subgrid-scale orographic (SSO) and non-orographic (NO) sources. Radiative transfer is handled via the ecRad radiation scheme.

The experiment includes six ensemble members to account for internal atmospheric variability. Initial conditions are based on ERA5 climatology (1979–2022). Ensemble 1 uses the mean January 1 state from ERA5 data (1979–2022), while ensembles 2–6 each exclude one year (1984, 1992, 2000, 2008, or 2016) to introduce slight variations in the initial conditions. Each ensemble simulation spans 30 years, with the first year treated as spin-up and excluded from output, resulting in a data range from 1991-01-01 to 2019-12-31 (arbitrarily numbered dates). All simulations are conducted under seasonally repeating boundary conditions to represent a stationary present-day climate. Sea surface temperature and sea ice are based on ERA5 climatology (1979–2022), greenhouse gas concentrations follow CMIP6 historical means (1979–2020), and ozone climatology is derived from MACC and GEMS datasets.

The key experimental perturbation is an artificial tenfold enhancement of the stratospheric SSO drag component within the East Asia region (EA: 30°–60°N, 110°–175°E). The scaling factor of 10 was determined experimentally, ensuring that the enhanced drag remains within the range of natural variability and preserves realistic dynamical forcing. It is the only applied external perturbation in this experiment. This approach is designed to isolate the influence of this known GW hotspot on atmospheric dynamics and circulation patterns. The dataset is well-suited for studying East Asia stratospheric GW forcing effects on stratospheric variability, polar vortex dynamics, and for quantifying signal-to-noise characteristics via ensemble analysis.

Daily-mean atmospheric fields are stored as monthly NetCDF files over the global domain on model levels. Variables include 3D fields (temperature, winds, pressure, vertical velocity), GW drag tendencies (SSO and NO), and surface values such as 2-meter temperature and surface pressure.
Project
CC-LGWF (UA-ICON Current-Climate Simulations with Localized Gravity Wave Forcing Sensitivity Experiments)
Contact
Sina Mehrdad (
 sina.mehrdad@nulluni-leipzig.de
0000-0003-3951-4415)

Prof. Christoph Jacobi (
 jacobi@nullrz.uni-leipzig.de
0000-0002-7878-0110)
Spatial Coverage
Longitude 0 to 360 Latitude -90 to 90 Altitude: 0 m to 150000 m
Temporal Coverage
1991-01-01 to 2019-12-31 (calendrical, arbitrary numbered years)
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Size
8.84 TiB (9714834713280 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2035-06-22
Cite as
Mehrdad, Sina; Marjani, Sajedeh; Jacobi, Christoph (2025). UA-ICON Current-Climate Simulation: East Asia Gravity Wave Forcing (EA). World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/UAICON_GW_EA

BibTeX RIS
Funding
German Research Foundation
Grant/Award No: 268020496 – TRR 172 - Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)³”
German Research Foundation
Grant/Award No: KA 5835/3-1 - ThE causes and consequences of exceptioNally strong stRatospherIc ArCtic polar vortices and the associated ozone Holes (ENRICH)
Description
Summary:
Findable: 6 of 7 level;
Accessible: 2 of 3 level;
Interoperable: 4 of 4 level;
Reusable: 6 of 10 level
Method
F-UJI online v3.5.0 automated
Method Description
Checks performed by WDCC. Metrics documentation: https://doi.org/10.5281/zenodo.15045911 Metric Version: metrics_v0.8
Method Url
Result Date
2025-07-04
Result Date
2025-06-27
Description
1. Number of data sets is correct and > 0: passed;
2. Size of every data set is > 0: passed;
3. The data sets and corresponding metadata are accessible: passed;
4. The data sizes are controlled and correct: passed;
5. The spatial-temporal coverage description (metadata) is consistent to the data: passed;
6. The format is correct: passed;
7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
Method Url
Result Date
2025-06-27
Contact typePersonORCIDOrganization
-

Is documented by

[1] DOI Lott, François; Miller, Martin J. (1997). A new subgrid-scale orographic drag parametrization: Its formulation and testing. doi:10.1002/qj.49712353704
[2] DOI Warner, C. D.; McIntyre, M. E. (1996). On the Propagation and Dissipation of Gravity Wave Spectra through a Realistic Middle Atmosphere. doi:10.1175/1520-0469(1996)053<3213:otpado>2.0.co;2
[3] DOI Scinocca, John F. (2003). An Accurate Spectral Nonorographic Gravity Wave Drag Parameterization for General Circulation Models. doi:10.1175/1520-0469(2003)060<0667:aasngw>2.0.co;2
[4] DOI Hogan, Robin J.; Bozzo, Alessio. (2018). A Flexible and Efficient Radiation Scheme for the ECMWF Model. doi:10.1029/2018ms001364
[5] DOI McLandress, Charles; Scinocca, John F. (2005). The GCM Response to Current Parameterizations of Nonorographic Gravity Wave Drag. doi:10.1175/jas3483.1

Is compiled by

[1] DOI Zängl, Günther; Reinert, Daniel; Rípodas, Pilar; Baldauf, Michael. (2014). The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core. doi:10.1002/qj.2378
[2] DOI Borchert, Sebastian; Zhou, Guidi; Baldauf, Michael; Schmidt, Hauke; Zängl, Günther; Reinert, Daniel. (2019). The upper-atmosphere extension of the ICON general circulation model (version: ua-icon-1.0). doi:10.5194/gmd-12-3541-2019

Is derived from

[1] DOI Meinshausen, Malte; Vogel, Elisabeth; Nauels, Alexander; Lorbacher, Katja; Meinshausen, Nicolai; Etheridge, David M.; Fraser, Paul J.; Montzka, Stephen A.; Rayner, Peter J.; Trudinger, Cathy M.; Krummel, Paul B.; Beyerle, Urs; Canadell, Josep G.; Daniel, John S.; Enting, Ian G.; Law, Rachel M.; Lunder, Chris R.; O'Doherty, Simon; Prinn, Ron G.; Reimann, Stefan; Rubino, Mauro; Velders, Guus J. M.; Vollmer, Martin K.; Wang, Ray H. J.; Weiss, Ray. (2017). Historical greenhouse gas concentrations for climate modelling (CMIP6). doi:10.5194/gmd-10-2057-2017
[2] DOI Hersbach, Hans; Bell, Bill; Berrisford, Paul; Hirahara, Shoji; Horányi, András; Muñoz‐Sabater, Joaquín; Nicolas, Julien; Peubey, Carole; Radu, Raluca; Schepers, Dinand; Simmons, Adrian; Soci, Cornel; Abdalla, Saleh; Abellan, Xavier; Balsamo, Gianpaolo; Bechtold, Peter; Biavati, Gionata; Bidlot, Jean; Bonavita, Massimo; Chiara, Giovanna; Dahlgren, Per; Dee, Dick; Diamantakis, Michail; Dragani, Rossana; Flemming, Johannes; Forbes, Richard; Fuentes, Manuel; Geer, Alan; Haimberger, Leo; Healy, Sean; Hogan, Robin J.; Hólm, Elías; Janisková, Marta; Keeley, Sarah; Laloyaux, Patrick; Lopez, Philippe; Lupu, Cristina; Radnoti, Gabor; Rosnay, Patricia; Rozum, Iryna; Vamborg, Freja; Villaume, Sebastien; Thépaut, Jean‐Noël. (2020). The ERA5 global reanalysis. doi:10.1002/qj.3803
[3] DOI Hollingsworth, A.; Engelen, R. J.; Textor, C.; Benedetti, A.; Boucher, O.; Chevallier, F.; Dethof, A.; Elbern, H.; Eskes, H.; Flemming, J.; Granier, C.; Kaiser, J. W.; Morcrette, J.-J.; Rayner, P.; Peuch, V.-H.; Rouil, L.; Schultz, M. G.; Simmons, A. J.; undefined, undefined. (2008). TOWARD A MONITORING AND FORECASTING SYSTEM FOR ATMOSPHERIC COMPOSITION. doi:10.1175/2008bams2355.1
[4] DOI Inness, A.; Baier, F.; Benedetti, A.; Bouarar, I.; Chabrillat, S.; Clark, H.; Clerbaux, C.; Coheur, P.; Engelen, R. J.; Errera, Q.; Flemming, J.; George, M.; Granier, C.; Hadji-Lazaro, J.; Huijnen, V.; Hurtmans, D.; Jones, L.; Kaiser, J. W.; Kapsomenakis, J.; Lefever, K.; Leitão, J.; Razinger, M.; Richter, A.; Schultz, M. G.; Simmons, A. J.; Suttie, M.; Stein, O.; Thépaut, J.-N.; Thouret, V.; Vrekoussis, M.; Zerefos, C.; undefined, undefined. (2013). The MACC reanalysis: an 8 yr data set of atmospheric composition. doi:10.5194/acp-13-4073-2013

Attached Datasets ( 6 )

Details for selected entry
[Entry acronym: UAICON_GW_EA] [Entry id: 5285863]