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17 results for “Aquaplanet”
Extra-tropical cyclone statistics from OpenIFS aquaplanet simulations
<p>This data set is derived from three idealised modelling experiments that were performed with the global numerical weather prediction model, OpenIFS. Three aqua-planet experiments were performed that differed only in their sea surface temperatures. There was a control simulation, case where the sea surface temperatures were warmed everywhere by 4K and a case where the polar sea surface temperatures were increased by 5K. In all three experiments, the extra-tropical cyclones were identified. The data presented in this data set is the maximum vorticity and precipitation of all of these extra-tropical cyclones. This data set is used by Sinclair and Catto (2023) in their study.</p> <p>Sinclair, V. A. and Catto, J. L.: The relationship between extra-tropical cyclone intensity and precipitation in idealised current and future climates, Weather Clim. Dynam. Discuss. [preprint], https://doi.org/10.5194/wcd-2022-62, in review, 2022.</p>
Response of convectively coupled Kelvin waves to surface temperature forcing in aquaplanet simulations: data and code
<p>This is the data and code used for a journal paper entitled "Response of convectively coupled Kelvin waves to surface temperature forcing in aquaplanet simulations", written by Mu-Ting Chien and Daehyun Kim in 2024. This paper is in minor revision in the Journal of Advances in Modeling Earth System. The submitted paper is here: (https://essopenarchive.org/doi/full/10.22541/essoar.171322728.86206700/v1).</p>
Ocean and ice with waves data for role of surface gravity waves in aquaplanet ocean climates
<p>This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021).</p> <p>In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force.</p> <p>This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice with waves component is 564 GB. See below for further details.</p> <p>See the related works section for the corresponding datasets.</p>
Ocean and ice without waves data for role of surface gravity waves in aquaplanet ocean climates
<p>This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021).</p> <p>In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force.</p> <p>This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice without waves component is 484 GB. See below for further details.</p> <p>See the related works section for the corresponding datasets.</p>
Ocean and ice without waves data for role of surface gravity waves in aquaplanet ocean climates
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Ocean and ice with waves data for role of surface gravity waves in aquaplanet ocean climates
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Ocean and ice spin-up data for role of surface gravity waves in aquaplanet ocean climates
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Atmospheric and surface gravity wave data for role of surface gravity waves in aquaplanet ocean climates
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Supporting data for Aquaplanets as a framework for examination of aerosol effects
<p>Monthly average data from Community Earth System Model version 2 needed to reproduce analysis in "Aquaplanets as a framework for examination of aerosol effects" (https://dx.doi.org/10.1029/2019MS001874). Each file contains several monthly averaged fields with dimensions of time, latitude, and longitude; some fields also have a vertical level dimension (lev). All simulations used the finite volume dynamical core with a 0.9° latitude by 1.25° longitude grid and 32 vertical hybrid-sigma levels. Files are divided by simulation, with the beginning of the file name indicating the experiment:</p> <ul> <li>glb_qpc6_cesm2p1p2.nc -- aquaplanet, pre-industrial emissions uniformly distributed</li> <li>hemi_qpc6_cesm2p1p2.nc -- aquaplanet, pre-industrial emissions in northern hemisphere</li> <li>quad_qpc6_cesm2p1p2.nc -- aquaplanet, pre-industrial emissions in northern hemisphere, 0-90° longitude</li> <li>salt_qpc6_cesm2p1p2.nc -- aquaplanet, no emissions except diagnostic sea-salt</li> <li>trop_qpc6_cesm2p1p2.nc -- aquaplanet, pre-industrial emissions in tropics (-30°-30° latitude)</li> <li>wedge_qpc6_cesm2p1p2.nc -- aquaplanet, pre-industrial emissions 0-30° longitude</li> <li>xtrop_qpc6_cesm2p1p2.nc -- aquaplanet, pre-industrial emissions poleward of 30°</li> <li>PD_emis_qpc6_cesm2p1p2.nc -- aquaplanet, year 2000 emissions</li> <li>PI_emis_qpc6_cesm2p1p2.nc -- aquaplanet, realistic pre-industrial emissions</li> <li>amip_F2000_cesm2.nc -- Earth configuration, year 2000 SST, year 2000 aerosol emissions</li> <li>amip_PI_F2000_cesm2.nc -- Earth configuration, year 2000 SST, pre-industrial aerosol emissions</li> </ul> <p>Files are netCDF4 using compression. They were produced from model-native netCDF3 monthly files using NCO to concatenate months for the selected variables.</p>
Output of aquaplanet idealized GCM simulations under perpetual solstice-like forcing from Singh 2019, J. Atmos. Sci.
<p># Overview</p> <p>This directory contains the output from simulations in the idealized aquaplanet GCM that were originally reported in Singh 2019, J. Atmos Sci. The contents are as follows:</p> <p>```<br> ├── Omega0.125_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega0.25_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega0.5_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega0.66_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega0.75_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega1.5_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega1_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega2_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega3_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega4_y0005-y0010.mean.1x5days.zonal_avg.nc<br> ├── Omega8_y0005-y0010.mean.1x5days.zonal_avg.nc<br> └── README.md<br> ```</p> <p>where `Omega*x` indicates the rotation rate multiplicative factor, with 1x being Earth's rotation rate. All simulations are performed with time-invariant northern solstice insolation. A full description of the simulation setups is available in Singh 2019.</p> <p># References</p> <p>Idealized GCM formulation: Frierson, Dargan M. W., Isaac M. Held, and Pablo Zurita-Gotor. “A Gray-Radiation Aquaplanet Moist GCM. Part I: Static Stability and Eddy Scale.” Journal of the Atmospheric Sciences 63, no. 10 (October 1, 2006): 2548–66. https://doi.org/10.1175/JAS3753.1.</p> <p>Simulations: Singh, Martin S. “Limits on the Extent of the Solsticial Hadley Cell: The Role of Planetary Rotation.” Journal of the Atmospheric Sciences 76, no. 7 (April 30, 2019): 1989–2004. https://doi.org/10.1175/JAS-D-18-0341.1.</p>
Response of atmospheric river width and intensity to aquaplanet warming: A detection algorithm- and background moisture-independent approach
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Aquaplanet simulations using CAM5.4-MPAS4 with two different deep convection schemes
This dataset includes model output from aquaplanet simulations using the Communitiy Atmosphere Model (CAM) version 5.4 with the nonhydrostatic Model for Prediction Across Scales (MPAS) version 4 dynamical core. The aquaplanet simulations has been performed with a global quasi-uniform resolution mesh with ~120 km grid spacing and a variable resolution mesh employing a circular refined region with ~30 km grid spacing centering at the equator and ~120 km elsewhere. Specifically, these simulations are produced for evaluating the Grell-Freitas deep convection scheme (GF), which has been implemented in the CAM5.4 recently, for the quasi-uniform resolution and the variable resolution meshes, compared with the Zhang-McFarlane scheme deep convection scheme (ZM) in CAM. The four simulations are run for three years, but the datasets are only for the last 30 months because the first six months are regarded as spinup. The model output was interpolated to a 1-degree by 1-degree latitude-longitude grid. Details of the simulations will be documented in a manuscript submitted to the Journal of Advances in Modeling Earth Systems (JAMES). The dataset will be shared with readers without restrictions by the journal's data policy.
Heat Tagging Data For Idealized Isca Aquaplanets
<p>Heat Tag tracer calculations described in</p> <p>Fajber and Kushner (2021): Using “Heat Tagging” to Understand the Remote Influence of Atmospheric Diabatic Heating through Long-Range Transport, Journal of Atmospheric Sciences, 2161–2176 . https://doi.org/10.1175/JAS-D-20-0290.1</p> <p>Calculated using the Isca model: https://execlim.github.io/IscaWebsite/</p> <p>Data suppliment for the paper</p> <p>Fajber, Donohoe, Ragen, Armour, and Kushner (2022): The Hydrologic cycle drives Atmospheric Heat Transport, PNAS, submitted.<br> <br> The data is zonal mean monthly averages, but many quadratic products are included for budget calculations.</p>
Data supporting 'Assessing the Spurious Impacts of Ice-Constraining Methods on the Climate Response to Sea-Ice Loss using an Idealized Aquaplanet GCM' by Neil T Lewis et al.
<p>Data supporting Lewis et al., 2024. Assessing the Spurious Impacts of Ice-Constraining Methods on the Climate Response to Sea-Ice Loss using an Idealised Aquaplanet GCM. Submitted to Journal of Climate. </p> <p>All data is in NetCDF format. </p> <p>Output from each experiment is contained in its own folder (e.g., 'ALB.1'). For a description of each experiment, see the accompanying paper. </p> <p>Data files contain the following outputs: </p> <p>dyn_vars_daily_clim.nc contains day of year- and zonally-averaged atmospheric fields (u, v, T, etc). </p> <p>eddy_products.nc constains day of year- and zonally-averaged products of atmospheric fields (e.g., u'v'). </p> <p>ice_temp_daily.nc contains daily-averaged surface temperature and sea-ice thickness. </p> <p>toa_fluxes_clim.nc contains day of year-averaged top of atmosphere radiative fluxes (e.g., OLR). </p> <p>For the experiments NDG1.05, NDG1.1, and NDG1.2, nudge_daily_clim.nc is also included, and contains the day of year-averaged nudging heat flux applied to melt the ice. </p>
Dataset belonging to "The Influence of Large-scale Spatial Warming on Jet Stream Extreme Waviness on an Aquaplanet"
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Aquaplanet experiment data for Webb, M. J., & Lock, A. P. (2020). Testing a physical hypothesis for the relationship between climate sen-sitivity and double-ITCZ bias in climate models.Journal of Advances in Modeling Earth Systems, 12,e2019MS001999.https://doi.org/10.1029/2019MS001999
<p><strong>Aquaplanet experiment data from Webb and Lock (2020)</strong></p> <p><br> Webb, M. J., & Lock, A. P. (2020). Testing a physical hypothesis for the relationship between climate sen-sitivity and double-ITCZ bias in climate models.Journal of Advances in Modeling Earth Systems, 12,e2019MS001999.https://doi.org/10.1029/2019MS001999</p> <p>CSV files containing data from Figs 1(b) and 2(a-d)</p> <p>Figure 2b:</p> <p>APEQ.Precipitation_mmperday.zonal.csv<br> APEQ_2LW_Cloud.Precipitation_mmperday.zonal.csv<br> APEQ_3LW_Cloud.Precipitation_mmperday.zonal.csv</p> <p>Figure 3a:</p> <p>APEQ.w700.zonal.csv<br> APEQ_3LW_Cloud.w700.zonal.csv<br> APEQ_2LW_Cloud.w700.zonal.csv</p> <p>Figure 3b:</p> <p>APEQ.Estimated_Inversion_Strength_K.zonal.csv<br> APEQ_2LW_Cloud.Estimated_Inversion_Strength_K.zonal.csv<br> APEQ_3LW_Cloud.Estimated_Inversion_Strength_K.zonal.csv</p> <p>Figure 3c:</p> <p>APEQ.Net_CRE_Wperm2.zonal.csv<br> APEQ_2LW_Cloud.Net_CRE_Wperm2.zonal.csv<br> APEQ_3LW_Cloud.Net_CRE_Wperm2.zonal.csv</p> <p>Figure 3d:</p> <p>APEQ4K-APEQ.Net_CRE_Feedback_Wperm2perK.zonal.csv<br> APEQ4K_2LW_Cloud-APEQ_2LW_Cloud.Net_CRE_Feedback_Wperm2perK.zonal.csv<br> APEQ4K_3LW_Cloud-APEQ_3LW_Cloud.Net_CRE_Feedback_Wperm2perK.zonal.csv</p> <p>Any queries please contact Mark Webb mark.webb@metoffice.gov.uk</p> <p> </p>
The Roles of Shallow Convection and Cloud Radiative Feedback in Convectively-Coupled Kelvin Wave: MPAS-aquaplanet Model configuration
<p>We provide the model configuration for the MPAS-A aquaplanet used in our journal article titled <em>“The Roles of Shallow Convection and Cloud Radiative Feedback in Convectively-Coupled Kelvin Waves”</em> by Hsu et al., submitted to the <em>Journal of Climate</em> in 2024.</p>
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