We utilize the ICON version 2.6.3 with upper-atmosphere extension as distributed by the German weather service (DWD). The ICON model is a collaborative project of DWD and the Max Planck Institute for Meteorology, striving at providing a unified modeling system to seamlessly allow simulations from climatological time scales to large-eddy simulations as well as for global numerical weather prediction (Zangl et al., 2015). In addition to the upper-atmosphere physics package implemented in UA-ICON, the dynamical core is extended from the shallow to deep atmosphere dynamics (Borchert et al., 2019). In our setup, the UA-ICON model is set up with the horizontal resolution of R2B4, which corresponds to a grid mesh of approximately 160 km with 120 levels up to a height of approximately 147 km. The time step of the simulation is 360s. The data output interval is set to 6 h, which is essential in the calculations of the Eliassen-Palm (EP) flux divergence. The mid-monthly sea surface temperature (SST) and sea ice concentration (SIC) values produced by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for the Atmosphere Model Intercomparison Project (AMIP, Taylor et al. (2000)) served as lower boundary condition data. Interactive chemistry was not used in the current simulation. Instead, the concentrations of CO2, CH4, N2O, CFC-11, and CFC-12 were taken from the historical greenhouse gas volume mixing ratios for CMIP6 (Meinshausen et al., 2017). The atmospheric ozone concentrations were prescribed based on the input4MIPs project (https://esgf-node.llnl.gov/search/input4mips). Here we conduct 30-year long time-slice experiments with the UA-ICON model by employing repeated annual cycles of SST, SIC, and greenhouse gases of the year 1985. This year is appointed as both El-Nino southern oscillation and Pacific decadal oscillation were in their neutral phase and no major volcano eruption has occurred, hence conditions in this year can serve as a useful proxy for the multi-year mean conditions and an estimate of their internal variability. The control run is carried out where both the sub-grid scale orography (SSO) scheme and non-orographic gravity waves scheme are used. In UA-ICON, the entire SSO drag is treated after Lott and Miller (1997), and the non-orographic GW drag parameterization is based on Warner and McIntyre (1996) and Scinocca (2003). It is worthwhile to mention that in addition to the orographic GWD, the SSO scheme used in UA-ICON also contains the effect of low-level blocking and wake drag. As the simulations are the time-slice experiments, only the months , days and hours have their true/usual meanings and years in the name of output files do not have their true/usual meaning. In other words, all the outputs files with different years (1986, 1987, ..., 2015) are identical to year 1985 as identical boundary conditions as year 1985 are used to simulate them. For example, 0001 and 0002 represent the first and second years of simulations, respectively and 0030 is the last (30) year.

We utilize the ICON version 2.6.3 with upper-atmosphere extension as distributed by the German weather service (DWD). The ICON model is a collaborative project of DWD and the Max Planck Institute for Meteorology, striving at providing a unified modeling system to seamlessly allow simulations from climatological time scales to large-eddy simulations as well as for global numerical weather prediction (Zangl et al., 2015). In addition to the upper-atmosphere physics package implemented in UA-ICON, the dynamical core is extended from the shallow to deep atmosphere dynamics (Borchert et al., 2019). In our setup, the UA-ICON model is set up with the horizontal resolution of R2B4, which corresponds to a grid mesh of approximately 160 km with 120 levels up to a height of approximately 147 km. The time step of the simulation is 360s. The data output interval is set to 6 h, which is essential in the calculations of the Eliassen-Palm (EP) flux divergence. The mid-monthly sea surface temperature (SST) and sea ice concentration (SIC) values produced by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for the Atmosphere Model Intercomparison Project (AMIP, Taylor et al. (2000)) served as lower boundary condition data. Interactive chemistry was not used in the current simulation. Instead, the concentrations of CO2, CH4, N2O, CFC-11, and CFC-12 were taken from the historical greenhouse gas volume mixing ratios for CMIP6 (Meinshausen et al., 2017). The atmospheric ozone concentrations were prescribed based on the input4MIPs project (https://esgf-node.llnl.gov/search/input4mips). Here we conduct 30-year long time-slice experiments with the UA-ICON model by employing repeated annual cycles of SST, SIC, and greenhouse gases of the year 1985. This year is appointed as both El-Nino southern oscillation and Pacific decadal oscillation were in their neutral phase and no major volcano eruption has occurred, hence conditions in this year can serve as a useful proxy for the multi-year mean conditions and an estimate of their internal variability. The non-orographic gravity waves scheme is not used in this simulation. In UA-ICON, the entire SSO drag is treated after Lott and Miller (1997), and the non-orographic GW drag parameterization is based on Warner and McIntyre (1996) and Scinocca (2003). It is worthwhile to mention that in addition to the orographic GWD, the SSO scheme used in UA-ICON also contains the effect of low-level blocking and wake drag. As the simulations are the time-slice experiments, only the months, days and hours have their true/usual meanings and years in the name of output files do not have their true/usual meaning. In other words, all the outputs files with different years (1986, 1987, ..., 2015) are identical to year 1985 as identical boundary conditions as year 1985 are used to simulate them. For example, 0001 and 0002 represent the first and second years of simulations, respectively and 0030 is the last (30) year.

We utilize the ICON version 2.6.3 with upper-atmosphere extension as distributed by the German weather service (DWD). The ICON model is a collaborative project of DWD and the Max Planck Institute for Meteorology, striving at providing a unified modeling system to seamlessly allow simulations from climatological time scales to large-eddy simulations as well as for global numerical weather prediction (Zangl et al., 2015). In addition to the upper-atmosphere physics package implemented in UA-ICON, the dynamical core is extended from the shallow to deep atmosphere dynamics (Borchert et al., 2019). In our setup, the UA-ICON model is set up with the horizontal resolution of R2B4, which corresponds to a grid mesh of approximately 160 km with 120 levels up to a height of approximately 147 km. The time step of the simulation is 360s. The data output interval is set to 6 h, which is essential in the calculations of the Eliassen-Palm (EP) flux divergence. The mid-monthly sea surface temperature (SST) and sea ice concentration (SIC) values produced by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for the Atmosphere Model Intercomparison Project (AMIP, Taylor et al. (2000)) served as lower boundary condition data. Interactive chemistry was not used in the current simulation. Instead, the concentrations of CO2, CH4, N2O, CFC-11, and CFC-12 were taken from the historical greenhouse gas volume mixing ratios for CMIP6 (Meinshausen et al., 2017). The atmospheric ozone concentrations were prescribed based on the input4MIPs project (https://esgf-node.llnl.gov/search/input4mips). Here we conduct 30-year long time-slice experiments with the UA-ICON model by employing repeated annual cycles of SST, SIC, and greenhouse gases of the year 1985. This year is appointed as both El-Nino southern oscillation and Pacific decadal oscillation were in their neutral phase and no major volcano eruption has occurred, hence conditions in this year can serve as a useful proxy for the multi-year mean conditions and an estimate of their internal variability. The non-orographic gravity waves scheme is not used in this simulation. In UA-ICON, the entire SSO drag is treated after Lott and Miller (1997), and the non-orographic GW drag parameterization is based on Warner and McIntyre (1996) and Scinocca (2003). It is worthwhile to mention that in addition to the orographic GWD, the SSO scheme used in UA-ICON also contains the effect of low-level blocking and wake drag. As the simulations are the time-slice experiments, only the months , days and hours have their true/usual meanings and years in the name of output files do not have their true/usual meaning. In other words, all the outputs files with different years (1986, 1987, ..., 2015) are identical to year 1985 as identical boundary conditions as year 1985 are used to simulate them. For example, 0001 and 0002 represent the first and second years of simulations, respectively and 0030 is the last (30) year.

This dataset contains high-resolution nested simulations conducted over Andøya, Norway (ALOMAR) with UA-ICON (ua-icon-2.1) in the context of the NASA Vorticity Experiment (VortEx) sounding rocket campaign in March 2023. UA-ICON was configured with 180 vertical levels, a model top at 150 km, and a global horizontal resolution of R2B7 (~20 km). One-way nesting was applied to achieve progressively finer resolutions of R2B8 (~10 km), R2B9 (~5 km), R2B10 (~2.5 km), and R2B11 (~1.25 km). In the global domain (~20 km resolution), the large-scale dynamics during the campaign were specified by nudging to ECMWF operational analyses up to an altitude of 50 km. At resolutions finer than 5 km, UA-ICON resolves a significant portion of the gravity wave (GW) spectrum. Consequently, GW and convective parameterizations were progressively turned off, starting from domain DOM3 (~5 km), to isolate the effects of resolved GWs. The simulations show satisfactory agreement with observations, highlighting the model’s capabilities for investigating the dynamics in the MLT region.

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 control simulation (C) was designed with no transient external forcing, serving as a reference dataset for analyzing current-climate circulation patterns and variability, especially in the middle and upper atmosphere. It also provides a foundation for sensitivity experiments targeting the role of regional orographic and non-orographic gravity wave forcing. 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.

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 Himalayan region (HI: 25°–45°N, 70°–100°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 Himalayan stratospheric gravity wave 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.

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.

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 Northwest America region (NA: 30°–60°N, 100°–130°W). 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. In this experiment, Unlike the other ensemble members, which span 30 years, ensemble member 5 terminated early in 2005 due to numerical instability. the output of the ensemble is archived from 1991 onward, excluding the spin-up year. The dataset is well-suited for studying Northwest America 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.