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35 results for “E3SM”
E3SM simulation results and associated python analysis scripts
<p>This archive contains E3SM Land Model simulation results associated with the <em>Journal of Advances in Modeling Earth Systems (JAMES)</em><em> </em>article titled "More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM)," by Adam M. Schneider, Charles S. Zender, and Stephen F. Price. Also included in the archive are python scripts used to analyze associated data and an offline, statistical firn model.</p>
Development and evaluation of E3SM-MOSAIC: Spatial distributions and radiative effects of nitrate aerosol
<p>FC20TR-MOZ_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MZT_PD</p> <p>FC20TR-MOZ_MOSAIC_AIKDST_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MTC_SLOW_PD</p> <p>FC20TR-MOZ_MOSAIC_AIKDST_MTC_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MTC_WGT_PD</p> <p>FC20TR-MOZ_MOSAIC_AIKDST_MTC-SPLC_NUG_PD_V2beta4_ANN_200501_201412_climo.nc 10-yr mean for MTC_SPLC_PD</p> <p> </p> <p>NO3_TM_2005-2014.nc 10-yr mean nitrate burden</p> <p>NO3_AQCH_GAEX_2005-2014.nc 10-yr mean for nitrate chemistry production</p> <p>NO3_DRF_2005-2014.nc 10-yr mean nitrate direct forcing between PD and PI</p> <p>NO3_INDRF_2005-2014.nc 10-yr mean nitrate indirect forcing between PD and PI</p> <p> </p> <p>NH4_TM_2005-2014.nc 10-yr mean for ammonium burden</p> <p>NH4_DRF_2005-2014.nc 10-yr mean ammonium direct forcing between PD and PI</p> <p> </p> <p>SO4_TM_2005-2014.nc 10-yr mean for sulfate burden</p> <p>SO4_DRF_2005-2014.nc 10-yr mean sulfate direct forcing between PD and PI</p> <p> </p> <p>CCN3_1850.nc Cloud condensation nuclei number concentrations at 0.1% super saturation at PI</p> <p>CCN3_2005-2014.nc CCN3 at PD</p> <p>CCN3_NONO3_1850.nc CCN3 at PI without nitrate formation</p> <p>CCN3_NONO3_2005-2014.nc CCN3 at PD without nitrate formation</p> <p> </p> <p>CDNC_*.nc cloud droplet number concentrations</p> <p>CLDFRC_*.nc cloud fraction</p> <p>CWP_*.nc cloud liquid water path</p> <p> </p> <p> </p>
Dataset for "Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions"
<p>This dataset is a part of the paper "Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions", accepted for publication in the Journal of Advances in Modeling Earth Systems (JAMES).</p> <h2>Contents</h2> <p>This dataset includes:</p> <ul> <li><strong>lhs-gen-190.csv</strong>: Training input LHS samples generated by <code>lhsgen.py</code>.</li> <li><strong>lhs-gen-50-test.csv</strong>: Test input LHS samples generated by <code>lhsgen.py</code>.</li> <li><strong>190-elm-samples.csv</strong>: Training input perturbed parameter samples for performing ELM simulations.</li> <li><strong>50-elm-test-samples.csv</strong>: Test input perturbed parameter samples for performing ELM simulations.</li> <li><strong>train_CH-CHA.csv</strong>: Contains the five ELM simulation output flux values for 240 samples (190 train + 50 test).</li> <li><strong>lhsgen.py</strong>: Script for generating Latin Hypercube Samples.</li> <li><strong>gpr-fit-new.py</strong>: Script for fitting Gaussian Process Regression (GPR) models.</li> <li><strong>sobol-new.py</strong>: Script for performing Sobol sensitivity analysis.</li> </ul> <h2>Usage</h2> <ol> <li><strong>lhsgen.py</strong>: <ul> <li>Use this script to generate the Latin Hypercube Samples for parameter sampling.</li> </ul> </li> <li><strong>gpr-fit-new.py</strong>: <ul> <li>This script fits GPR models using the training samples provided in <code>lhs-gen-190.csv</code>.</li> <li>It tests the models using the input testing samples in <code>lhs-gen-50-test.csv</code>.</li> <li>The fitted GPR models are stored as <code>.joblib</code> files in the <code>gpr_models</code> directory.</li> <li>Corresponding cross-validation and R-squared values are stored in <code>.xlsx</code> files.</li> </ul> </li> <li><strong>sobol-new.py</strong>: <ul> <li>This script performs Sobol sensitivity analysis using the fitted GPR models by reading the .joblib files.</li> <li>The Sobol indices are written to <code>.xlsx</code> files in the <code>results</code> directory.</li> </ul> </li> </ol>
Animated E3SM V1 High Resolution Labrador Sea Ice Thickness and Concentration with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness and concentration for the Labrador Sea region from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled model version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. This animation shows sea thickness evolution in each frame for five model years 46 to 50, inclusive, with rendered transparency determined from sea ice concentration to demonstrate the influence of ocean eddies around the southern tip of Greenland. The coastline is the true model boundary. The animation is best viewed using a web browser.</p>
Animated E3SM V1 High Resolution Full Coupled Sea Ice Thickness and Extent with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled mo del version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. The animation shows both pan-Arctic and Southern Ocean daily sea thickness evolution in each frame for model years 46 to 55, truncated at 15% sea ice concentration, and is best viewed from within a web browser.</p>
Animated E3SM V1 High Resolution Mertz Polynya Sea Ice Thickness and Concentration with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness and concentration for the Mertz Glacier Polynya region of the East Antarctic coast from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled model version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. This animation shows sea thickness evolution in each frame for ten model years 46 to 55, inclusive, with shading transparency determined by sea ice concentration, and grid cell outlines dissappearing where there is less than 0.1% sea ice concentration. The coastline is the true model boundary. This animation is best viewed using a web browser.</p>
Data for manuscript "Modes of Variability in E3SM and CESM Large Ensembles"
An adequate characterization of internal modes of climate variability (MoV) is prerequisite for both accurate seasonal predictions and the attribution and detection of forced climate change in nature. Assessing the fidelity of climate models in simulating MoV is therefore essential; however, doing so is complicated by the large intrinsic variations in MoV and the limited span of the observational record. Large ensembles (LEs) provide a unique opportunity to assess model fidelity in simulating MoV and quantify inter-model contrasts. In this work, these goals are pursued in four recently produced LEs: the Energy Exascale Earth System Model (E3SM) versions 1 and 2 LEs, and the Community Earth System Model (CESM) versions 1 and 2 LEs. In general, the representation of MoV is found to improve across successive E3SM and CESM versions concurrent with improved simulation of the base state climate. The patterns of global coupled modes and many extratropical modes are well simulated by both E3SM2 and CESM2, though various persistent shortcomings are identified. The results both demonstrate the successes of these recent model versions and suggest the potential for continued improvement in the representation of MoV with advances in model physics.
E3SM simulations of Hurricane Irene (Delaware River basin subset)
<p>This repository consists of the E3SM simulation outputs of Hurricane Irene (subsetted within Delaware River basin) associated with the manuscript: "Simulation of Compound Flooding using River-Ocean Two-way Coupled E3SM Ensemble on Variable-resolution Meshes". Below are the descriptions for each file:</p> <p>EAM_ensemble.nc - 25 EAM ensemble simulations.<br>MOSART_1way_baseline.nc - 25 MOSART ensemble simulations for Experiment 1way_baseline<br>MOSART_1way_datm_GSWP.nc - MOSART simulation for Experiment 1way_datm using GSWP forcing<br>MOSART_1way_datm_JRA.nc - MOSART simulation for Experiment 1way_datm using JRA forcing<br>MOSART_1way_r0125.nc - 25 MOSART ensemble simulations for Experiment 1way_r0125<br>MOSART_2way.nc - 25 MOSART ensemble simulations for Experiment 2way<br>MOSART_1way_SSH.nc - 25 MOSART ensemble simulations for Experiment 1way_SSH<br>MOSART_1way_MSL.nc - 25 MOSART ensemble simulations for Experiment 1way_MSL<br>MPASO_subset_1way_ens001.nc ~ MPASO_subset_1way_ens025.nc - 25 MPAS-O ensemble simulations for Experiment 1way_baseline<br>MPASO_subset_2way_ens001.nc ~ MPASO_subset_2way_ens001.nc - 25 MPAS-O ensemble simulations for Experiment 2way</p>
Observational dataset for "Using Satellite and ARM Observations to Evaluate Cold Air Outbreak Cloud Transitions in E3SM Global Storm-Resolving Simulations"
<p>This observational dataset include the DOE ARM ground based observations and satellite for the paper titled “Using Satellite and ARM Observations to Evaluate Cold Air Outbreak Cloud Transitions in E3SM Global Storm-Resolving Simulations” on GRL.</p> <p>For the original data source, all ARM observational data sets used in this study are publicly available from the ARM data archive site (https://adc.arm.gov/discovery/#/results/iopShortName::amf2019comble/datastream::anxarmbeatmM1.c1/datastream::anxarmbecldradM1.c1/datastream::anxarsclkazr1kolliasM1.c0). MODIS MOD06 L2 cloud product are publicly available from (https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD06 L2, DOI:10.5067/MODIS/MOD06 L2.061).</p> <p>CloudSat products can be ordered from the CloudSat Data Processing center (https://www.cloudsat.cira.colostate.edu/order/). To download CloudSat data, a new user must first create an account by filling out the signup form (https://www.cloudsat.cira.colostate.edu/accounts/signup/).</p>
Enhanced Convective Microphysics Scheme and Its Impacts on Mean Climate Simulation in E3SM
<ol> <li>Simulation data of E3SM with an enhanced convective microphysics scheme.</li> <li>Source code of E3SM with an enhanced convective microphysics scheme.</li> </ol>
Representing surface heterogeneity in land-atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime - E3SM SCM data and code
<p>This dataset contains post-processed E3SM single-column model output and code used to produce the figures in the manuscript that we are targeting Geoscientific Model Development to submit. </p>
The mechanisms in regulating the quasi-biennial oscillation in E3SM version 2
<p>The data includes time step output of convective parameters horizonal wind in heating depth (U), the depth of the heating (D) and the maximum latent heating tendency within convection (Q0max) on the spectral element grid. Also, it includes zonal wind,total precipitation and zonal wind tendency caused by gravity wave (BUTGW) at longitude-latitude grid at 45.7 hPa and 96 hPa. The time series of EP flux divergence, gravity wave drag and zonal mean zonal wind are restored.</p>
daleihao/Topographic_Effects: Codes and data for GMD paper "A Parameterization of Sub-grid Topographical Effects on Solar Radiation in the E3SM Land Model (Version 1.0): Implementation and Evaluation Over the Tibetan Plateau"
<p>Codes and data to reproduce all results and plot all figures for GMD paper "A Parameterization of Sub-grid Topographical Effects on Solar Radiation in the E3SM Land Model (Version 1.0): Implementation and Evaluation Over the Tibetan Plateau"</p>
Data for "Using an Uncertainty Quantification Framework to Calibrate the Runoff Generation Scheme in E3SM Land Model V1"
<p>The domain file and surface data file that used to run ELMv1, and processed ISIMP2a runoff data that used in <a href="https://gmd.copernicus.org/preprints/gmd-2021-401/">https://gmd.copernicus.org/preprints/gmd-2021-401/</a></p> <p>ELM_runoff_parameter_post.nc contains the ELM runoff generation relevant parameter posteriors at a global half degree spatial resolution.</p>
Aerosol activation from E3SM and cloud parcel model
<p>This dataset contains maximum supersaturation, activation fraction, temperature, pressure, relative humidity, updraft velocity, and size, number, standard deviation, and hygroscopicity of aerosol from the 4-mode version of Modal Aerosol Module (MAM4) in U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) and from a cloud parcel model.</p>
Scripts and Data for "Disentangling the Hydrological and Hydraulic Controls on Streamflow Variability in E3SM V2 – A Case Study in the Pantanal Region"
<p>Matlab scripts for processing and showing the coupled ELM-MOSART coupled simulations for Pantanal region.</p> <p>domain_lnd_Pantanal_default.nc, MOSART_Pantanal_default_c211116.nc, and surfdata_Pantanal_default_c220520.nc are the domain file, MOSART input file, and ELM surface dataset, respectively. </p> <p><a href="https://zenodo.org/api/files/6be468b6-cbfa-4ef4-bb10-0f15812be9bd/Pantanal_half_calibration_CLMCRUNCEPv7.sh">Pantanal_half_calibration_CLMCRUNCEPv7.sh</a> is the bash script to run E3SM with coupled ELM-MOSART configuration. ANd detailed instruction of running E3SMV2 can be found at: https://e3sm.org/model/running-e3sm/e3sm-quick-start/ (last access: Aug 2023).</p> <p>Pantanal_GSIM.zip contains the observed streamflow that used in this study, which is downloaded from <a href="https://doi.pangaea.de/10.1594/PANGAEA.887470">https://doi.pangaea.de/10.1594/PANGAEA.887470</a> (last access: Aug 2023). The reference is Gudmundsson, Lukas; Do, Hong Xuan; Leonard, Michael; Westra, Seth (2018): The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment. Earth System Science Data, 10(2), 787-804, https://doi.org/10.5194/essd-10-787-2018.</p> <p>BFI3.mat is the baseflow index from GSCD and processed to the study domain. The GSCD dataset was download from <a href="http://www.gloh2o.org/gscd/">http://www.gloh2o.org/gscd/</a> (last access: Aug 2023). The reference is Beck, H. E., van Dijk, A. I. J. M., Miralles, D. G., de Jeu, R. A. M., Bruijnzeel, L. A., McVicar, T. R., and Schellekens, J.: Global patterns in base flow index and recession based on streamflow observations from 3394 catchments, Water Resour Res, 49, 7843-7863, <a href="https://doi.org/10.1002/2013WR013918">https://doi.org/10.1002/2013WR013918</a>, 2013.</p> <p>runoff_uncertianty.mat contains the annual runoff time series from GRUN, LORA, and GFRF that processed to the study domain. The GRUN runoff dataset was downloaded from <a href="https://doi.org/10.6084/m9.figshare.9228176">https://doi.org/10.6084/m9.figshare.9228176</a> (last access: Aug 2023). The LORA runoff dataset was downloaded from <a href="https://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/ks32/ARCCSS_Data/LORA/v1-0/catalog.xml">https://dap.nci.org.au/thredds/remoteCatalogService?catalog=http://dapds00.nci.org.au/thredds/catalog/ks32/ARCCSS_Data/LORA/v1-0/catalog.xml</a> (last access: Aug 2023). The reference is Hobeichi, S., Abramowitz, G., Evans, J., and Beck, H. E.: Linear Optimal Runoff Aggregate (LORA): a global gridded synthesis runoff product, Hydrol. Earth Syst. Sci., 23, 851-870, 10.5194/hess-23-851-2019, 2019. The GRFR runoff was downloaded from <a href="http://hydrology.princeton.edu/data/mpan/GRFR/runoff/monthly_1deg/">http://hydrology.princeton.edu/data/mpan/GRFR/runoff/monthly_1deg/</a> (last access: Aug 2023). The reference is Yang, Y., Pan, M., Lin, P., Beck, H. E., Zeng, Z., Yamazaki, D., David, C. d. H., Lu, H., Yang, K., Hong, Y., and Wood, E. F.: Global Reach-level 3-hourly River Flood Reanalysis (1980-2019), B Am Meteorol Soc, 1-49, 10.1175/BAMS-D-20-0057.1, 2021.</p> <p>GLAD_Pantanal_half.mat, GLAD_Pantanal_8th.mat are the processed surface water fraction from GLAD at half and 8th spatial resoution. Specifically, The GLAD surface water dynamics was downloaded from <a href="https://console.cloud.google.com/storage/browser/earthenginepartners-hansen/water;tab=objects">https://console.cloud.google.com/storage/browser/earthenginepartners-hansen/water;tab=objects</a> (last access: Aug 2023). The reference is Pickens, A. H., Hansen, M. C., Hancher, M., Stehman, S. V., Tyukavina, A., Potapov, P., Marroquin, B., and Sherani, Z.: Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series, Remote Sens Environ, 243, 111792, <a href="https://doi.org/10.1016/j.rse.2020.111792">https://doi.org/10.1016/j.rse.2020.111792</a>, 2020.</p>
E3SM - Drake Passage Transport, 26.5 AMOC, Northward Heat Transport at 26.5N, from Hewitt et al 2020
<p>E3SM monthly output has been annually averaged and processed to derive the maximum overturning at 26.5 N, the northward heat transport at 26.5N and the drake passage transport. The model output includes the low resolution configuration and high resolution configuration. Both runs use the 1950 control from the HighResMIP protocol.</p>
CESM2 and E3SM variables used for diagnosing westerly wind events
<p>This data set contains variables needed to identify and evaluate westerly wind events (WWEs) in a simulation using the Community Earth System Model version 2 (CESM2) and a simulation using the Energy Exascale Earth System Model (E3SM). The CESM2 simulation was a historical run from 1980–1999 that was restarted from the CMIP6 historical simulation. The E3SM was a 400-year pre-industrial simulation from which we analyzed the last 39 years. Only those last 39 years are included in the E3SM files. </p> <p>For both the CESM2 and E3SM simulations, meridionally-averaged zonal wind stress from 2.5°S – 2.5°N filtered from 5–90 days was used to identify westerly wind events in the Pacific Ocean (120°E – 280°E). Events were defined as patches of zonal wind stress in the time-longitude plane with zonal wind stress values of 0.04 Nm<sup>-2</sup> or larger that lasted at least 5 days and were at least 10° longitude long. Meridional wind stress was also used along with the zonal wind stress to make spatiotemporal composite wind-stress vectors across all WWEs for each model. Outgoing longwave radiation (OLR) was also used as a proxy for convection. Again spatiotemporal composites were made of OLR centered on WWEs for each model. Finally, 1000-mb zonal wind speed was used to determine if WWEs defined by 5-90 day filtered zonal wind stress actually correspond to unfiltered westerly wind speeds.</p> <p>These simulations were part of a larger set of simulations used to evalute the fidelity of WWEs in CMIP6 simulations through a variety of model diagnostics. WWEs are important to air-sea feedbacks as they can initiate ocean Kelvin waves that then propagate eastward altering the thermodynamic structure of the upper ocean. Most importantly, these WWE-generated Kelvin waves can play an important role in El Nino Southern Oscillation dynamics.</p>
Code and Data for Atmospheric River Induced Precipitation in California as Simulated by the Regionally Refined Simple Convective Resolving E3SM Atmosphere Model Version 0
<p>Includes the code used for all simulations and grid configurations for the paper entitled "Atmospheric River Induced Precipitation in California as Simulated by the Regionally Refined Simple Convective Resolving E3SM Atmosphere Model Version 0" submitted to Geoscientific Model Development. Also included are the model output files for all cases and grid configurations used to generate the analysis and figures in the paper. </p>
E3SM high resolution simulations
<p>This dataset is E3SM simulation output with different hozitional and vertical resolutions. </p>
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