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15 results for “AMIP”
amip-piForcing and HadSST-piForcing simulation data
<p>Global-annual-mean dT and dN from the amip-piForcing, hadSST-piForcing and abrupt-4xCO2 simulations used in Andrews et al. (2022, JGR; <a href="https://www.essoar.org/doi/10.1002/essoar.10510623.3">https://www.essoar.org/doi/10.1002/essoar.10510623.3</a>)</p>
Domain Nesting in ICON and its Application to AMIP Experiments with Regional Refinement
<p>Model output generated with the new configuration of ICON-A described in the corresponding publication submitted to the Journal of Advances in Modeling the Earth System (American Geophysical Union). Data from the reference experiment is included as well.</p>
Clear-sky Outgoing Longwave Radiation Fluxes from Offline RTE-RRTMGP for AMIP Simulation of CMIP6 Models
<p>This study utilizes RTE-RRTMGP (<a href="https://doi.org/10.1029/2019MS001621">https://doi.org/10.1029/2019MS001621</a>) to compute clear-sky, aerosol-free outgoing longwave radiation (OLR) fluxes for AMIP simulation of CMIP6 models, using 36-year average of monthly-mean temperature and humidity profiles at 19 pressure level as an input. This dataset is used to investigate the cause of inter-model spread in OLR when the same set of radiative transfer schemes is used.</p>
AMIP and AMIP-P4K simulation dataset with Park-RH and Gauss-PDF cloud scheme
<p>This dataset includes AMIP and AMIP-P4K simulations using Park-RH and Gauss-PDF cloud schemes, respectively. </p> <p>Park-RH cloud scheme is the default cloud macrophysical scheme in NCAR CAM5. </p> <p>Gauss-PDF cloud scheme is a statistical cloud scheme, developed by Qin et al. (2018). </p> <p>All simulations are AMIP-type simulations from 1979 to 1988. The monthly output is archived here. </p> <p>Details of the model setup and the difference of two cloud schemes could be found in its related submitted manuscript. </p>
AMIP simulations of iCAM5 and SPEEDY-IER
<p>This repository contains AMIP simulations of isotope-enabled models iCAM5 (1971-2005) and SPEEDY-IER (1966-2000) for the JGR-Atmosphere paper "Impact of convective activity on precipitation <span class="math-tex">\(\delta^{18}O\)</span> in isotope-enabled general circulation models". These simulations are forced by the modern sea surface temperature and sea ice following the AMIP protocol. The file "attmAG1_1966-2000.nc" has all outputs from SPEEDY-IER. Other files are iCAM5 outputs, which include convective (PRECC) /large-scale precipitation (PRECL), precipitation isotopes (PRECT_H216O, PRECT_H218O), water vapor isotopes (H216OV, H218OV, HDOV). </p>
ACE AMIP climatology
<p>This dataset contains the seasonaly climatology from an AMIP run using ACE and PCMDI SST and sea ice forcings. </p>
NICAM AMIP-type simulation data for the article "Deceleration of Madden–Julian Oscillation Speed in NICAM AMIP-type Simulation Associated with Biases in the Walker Circulation Strength"
<p>This data set includes data from 30-year integration on nonhydrostatic icosahedral atmospheric model (NICAM) following an atmospheric model intercomparison project (AMIP) protocol with a slab ocean model from 1 June 1978 to 6 January 2009 (c.f. Kodama et al. 2015), and their GrADs description ctl files. All outputs are daily averages on 2.5 x 2.5 degrees resolution. Output variables are outgoing longwave radiation (W m<sup>-2</sup>), skin temperature (K), sea surface temperature (K), and zonal wind (m s<sup>-1</sup>) on pressure levels.</p>
AMIP-data
<p>"PUBLISH AS IS".</p>
Archive of the MIROC6 AMIP-trend experiments for 1979-2013
<p>Archive of the MIROC6 AMIP-{0K-4K}trend experiment for 1979-2013 (member 1-3) used in Watanabe et al. (2023, GRL). The data format is not netCDF so please ask Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp) when you would like to analyze them. Alternatvely, the Fortran codes and GrADS scripts for converting the data are available at https://ccsr.aori.u-tokyo.ac.jp/~hiro/data/amip-trend/.</p>
AMIP experiments with EC-Earth3-Veg
<p>Each file contains the global annal mean net radiation at TOA (tnr).<br> <br> Constant forcing (piControl or year 2100):<br> r610 piControl<br> r612 ssp585-2100<br> r613 ssp370-2100<br> r614 ssp245-2100<br> r615 ssp126-2100<br> r616 ssp119-2100</p> <p>Sensitivity eperiments:<br> r51[0,2,4,5] as r61[0,2,4,5], but GHG concentrations from corresponding RCP<br> r31[0,2] as r61[0,2], but GHG, aerosol, solar and volcanic forcing from R<br> CP</p>
CNRM-CM6-conv5 AMIP simulation monthly output (pr, ts, areacella)
<p>The present dataset consists in monthly output of an AMIP simulation performed with the CNRM-CM6-conv5 model, covering the period 1979-2008.</p> <p>CNRM-CM6-conv5 is the same model as CNRM-CM6-1 (<a href="https://doi.org/10.1029/2019MS001683">Voldoire et al. 2019</a>, <a href="http://www.umr-cnrm.fr/cmip6/references">http://www.umr-cnrm.fr/cmip6/references</a>) except that the convection scheme was replaced by the one previously used in CNRM-CM5.1 (<a href="https://doi.org/10.1007/s00382-011-1259-y">Voldoire et al. 2013</a>), namely the convection scheme developed by <a href="https://doi.org/10.1175/1520-0493(1985)113<2108:ASPOTL>2.0.CO;2">Bougeault (1985)</a>. The details of the atmospheric component of CNRM-CM6-1 (ARPEGE-Climat 6.3) and those of the AMIP simulation are discussed in <a href="https://doi.org/10.1029/2020MS002075">Roehrig et al. (2020)</a>.</p> <p>3 netCDF files are provided in this dataset, corresponding to surface precipitation (pr), surface temperature (ts) and model grid cell area (areacella). The netCDF file format follow the CF-1.7 and CMIP-6.2 conventions.</p>
CESM2.1-CAM6-CLM4 2-degree amip-LGM
<p>Monthly mean RFMIP-like data from a 30-year simulation of CESM2 configured with CAM6 with finite-volume dynamical core on 2-degree grid and CLM4 as land model. Boundary conditions from Pedro DiNezio for last glacial maximum. </p> <p>The new gravity wave scheme in CAM6 is <strong>disabled</strong> in these simulations because the topography file used is incompatible.</p> <p>Compset: </p> <pre><code class="language-bash">1850_CAM60_CLM40%SP_CICE%PRES_DOCN%DOM_RTM_SGLC_SWAV</code></pre> <p>CAM namelist changes:</p> <pre><code class="language-bash">bnd_topo = "/glade/work/brianpm/model_data/topo_21ka_remap_19x25.mod.170428.sm9.nc" ch4vmr = 360e-9 co2vmr = 190e-6 f11vmr = 0.0 f12vmr = 0.0 n2ovmr = 240e-9 ! avoid new gravity wave scheme use_gw_oro = .true. use_gw_rdg_beta = .false.</code></pre> <p>CLM namelist changes:</p> <pre><code class="language-bash">fsurdat = '/glade/work/brianpm/model_data/surfdata_1.9x2.5_21ka.170505.modshelves.nc' urban_hac = 'OFF' finidat = 'b.e12.21ka.002.clm2.r.0301-01-01-00000.nc'</code></pre> <p>Coupler namelist changes:</p> <pre><code class="language-xml">&seq_infodata_inparm orb_iyear = -19050 orb_mode = 'fixed_year' /</code></pre> <p> </p>
GRIST SCM and AMIP data
<p>Model output data </p>
Transformed Eulerian mean data from CMIP5 EC-Earth v2.3 AMIP experiment
<p>Data are derived from EC-Earth atmosphere-only experiment outputs for CMIP5 (identifier SA07), following the procedure described in a paper currently in preparation.</p> <p>Files are organized in one .tar file for each variable and temporal aggregation (monthly and daily).</p> <p>The simulation was done by the Swedish Meteorological and hydrological Institute (SMHI) on resources provided by the Swedish National Infrastructure for Computing (SNIC).</p>
Cloud feedback components from CMIP6 AMIP model
<p>Cloud feedback components from CMIP6 AMIP model (2002-2014)</p>
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