cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26024/yw4w-1w27
title: CESM2 Single Forcing Large Ensemble Project

description: The CESM2 "Single Forcing" Large Ensemble Project is a publicly available set of climate model simulations useful for addressing the roles of individual forcings in historical and future climate change. This simulations use the same model and forcings as the CESM2 Large Ensemble Project and, therefore, can be used to parse the relative roles of different forcings in responses found in that ensemble where all forcings are applied together. The ensemble members are initialized from 1850 from the same initial conditions that were used to initialize the "macro" members of the CESM2 Large Ensemble and they extend to 2050, following CMIP6 historical forcings prior to 2015 and SSP3-7.0 forcings, thereafter. Note that the smoothed biomass burning emissions that were used in the second 50 members of the CESM2 large ensemble are used, so these simulations should be compared with the second 50 members of the CESM2 large ensemble. Four primary ensembles are available in which different forcings are time evolving while all other forcings are held fixed at 1850's values, that is, the "only" method is used. Note that this differs from the CESM1 Large Ensemble which used the "all-but-one" method where all forcings were evolving except the one of interest. In the CESM2 ensembles, only the forcing of interest is evolving. Four ensembles are available using the following time-evolving forcings: * GHG = only greenhouse gases evolving (15 members) * AAER = Only anthropogenic aerosols evolving (20 members) * BMB = Only biomass burning aerosols evolving (15 members) * EE = everything else evolving i.e., all forcings other than those that are time evolving in GHG, AAER or BMB are time evolving. Greenhouse gases and anthropogenic and biomass burning aerosols are held fixed (15 members)Note that by "anthropogenic aerosols" here we refer to all industrial, agricultural, domestic and transport related emissions and acknowledge that this does not include any anthropogenic influences on biomass burning, which is instead present in the BMB ensemble. Each forcing that is time evolving in the CESM2 Large Ensemble is time evolving in one of these four sub-ensembles to allow additivity to be tested. As discussed in the release paper cited below, substantial non-linearities are present in the CESM2 Single Forcing Large Ensemble. As part of the investigation into this non-linearity, an additional ensemble was performed which was initialized in 1920 of the CESM2 Large Ensemble members and run with all forcings except anthropogenic aerosols i.e., following the same "all-but-one" approach that was used in CESM1. This demonstrated that there is considerable sensitivity of the anthropogenic aerosol forced response to the method used i.e., "all-but-one" versus "only". We have, therefore, expanded this ensemble to a 10 member ensemble, referred to as xAER, so that any sensitivity of the anthropogenic aerosol influence to the method used can be tested.xAER = Everything time evolving except anthropogenic aerosols (10 members)
DOI: 10.5065/ary8-ry81
title: Ensemble Downscaled Climate Dataset for Alaska and Hawaii Under Historical and Future Conditions

description: While high-resolution future climate data are increasingly available for the contiguous United States, there has been limited focus on Alaska and Hawaii. Our study provides high temporal and spatial resolution climate data (daily precipitation and temperature on spatial grids of 10 km for Alaska and 1 km for Hawaii) based on 23 climate models from the Coupled Model Intercomparison Project Phase 6 and four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). These datasets include different statistical downscaling and bias correction techniques (seven for precipitation, six for temperature). While one method (i.e., empirical quantile mapping) generally outperforms the others, its performance can vary by climate quantity, region, or climate model, motivating our aim to provide an ensemble dataset of bias-corrected outputs. This community dataset will permit investigations into the sources of climate uncertainty and climate change uncertainty at the local scale. They may also be used for climate risk assessment across a range of societal sectors. A primary reason for their development by the authors is to drive hydrologic models and explore questions of hydrologic change in these underexplored regions. These data are described in a paper under review in the journal Scientific Data.
DOI: 10.5065/f3pw-a676
title: Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP)

description: The community Atmospheric Potential Oxygen forward Model Intercomparison Project (APO-MIP) generated a suite of forward atmospheric transport model simulations of APO and its components (atmospheric O2, CO2, and N2), using different models and flux fields, to 1) evaluate global atmospheric transport models, 2) evaluate air-sea O2 and APO flux products, 3) support quantification of seasonal air-sea APO fluxes from airborne campaign observations, and 4) evaluate long-term trends in O2:CO2 ratios over the Southern Ocean using shipboard and station measurements. Seven international modeling groups submitted output from a total of eight different transport models for 10 different flux tracers. This repository includes the required and optional model output, the prescribed surface fluxes, and processing code used for preparing the flux fields and post-processing the required model output.
DOI: 10.5065/z7hr-0777
title: WRF-Chem simulations with and without the SMAP soil moisture retrievals and different levels of dust emissions

description: Hourly WRF-Chem simulations at 9 km grid spacing over the contiguous U.S. (CONUS) of several variables including the aerosol optical depth and the soil moisture using GOCART and GOCART-AFWA dust emission parameterizations. The simulations with GOCART-AFWA have different levels of dust emissions (five). There are two simulations for each case with and without SMAP soil moisture retrievals. There is also a simulation with no dust but including SMAP soil moisture. All the simulations are continuous runs of the WRF-Chem model. The simulations span the one year period from 1 April 2015 to March 31 2016.
DOI: 10.5065/7j5p-mc95
title: The WRF Model coupled with Chemistry (WRF-Chem) Forecast Output over CONUS

description: The Weather Research and Forecasting (WRF) model coupled with Chemistry version 3.9.1 is used to generate a 48-hour air quality forecast daily at 12 km grid spacing over the CONUS. The first 24 forecast files are available here. This WRF-Chem model simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. These forecasts are used to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts at the WRF Chemistry Forecast Maps [https://www.acom.ucar.edu/firex-aq/forecast.shtml].
DOI: 10.5065/vp7z-yg52
title: 20CRv3-WRF - High-resolution WRF climate simulation for southern Alaska using the 20CRv3

description: Currently, mass loss from Alaskan glaciers contributes to about a third of global mean sea level rise. The 20CRv3-WRF, a high-resolution (4 km) climate dataset, covers southern Alaska and spans from 1837 to 2015, providing extensive temporal coverage for studying long-term climate trends in this highly climate-sensitive region. The dataset was created by downscaling the NOAA-CIRES-DOE 20th Century Reanalysis (20CRv3) using the Weather Research and Forecasting model (WRF). The downscaling dataset was evaluated for the modern-day period (1981-2015) against the GSOD and PRISM observational datasets for Alaska and compared to ERA5 reanalysis output. The 20CRv3-WRF dataset includes surface variables at 3-hourly intervals (e.g., temperature, precipitation, wind) and atmospheric variables at 6-hourly intervals (e.g., pressure, wind). The primary motivation was to investigate the climate control on tidewater glaciers within southern Alaska, where long-term meteorological records are sparse. However, the 20CRv3-WRF dataset's applicability extends to various fields, including glaciology, hydrology, and biology, offering a valuable resource for diverse climate change studies and research applications. With its high resolution, it can be used as input data for various types of glacier modeling.
DOI: 10.5065/5474-sg54
title: DCMIP 2016 Datasets

description: The Dynamical Core Model Intercomparison Project (DCMIP) in 2016 focused on non-hydrostatic global models, physics-dynamics coupling, and variable-resolution modeling. The required test cases including moist baroclinic wave with terminator chemistry, idealized tropical cyclone and supercell scenarios. The intercomparison results are archived and used to establish new atmospheric model test cases of intermediate complexity incorporating simplified physics parameterizations for global climate and weather models.
DOI: 10.5065/gqyf-yq95
title: Non-precipitating shallow cumulus simulations with FastEddy (LES intercomparisons)

description: The dataset contains numerical results from FastEddy simulations of two different non-precipitating shallow cumulus clouds scenarios. including a static forcing and a time-dependent forcing case. The FastEddy model used is extended to include moist dynamics processes alongside a simple scheme for condensation/evaporation. The inter-comparison exercises of the results agree with those from Siebesma et al. 2003 (oceanic static forcing), and Brown et al. 2002 (diurnal evolution over land).
DOI: 10.5065/rxae-ab06
title: WACCM Specified Chemistry simulations with the spectral element NE120 F2000 July

description: These are high-resolution WACCM specified chemistry (SC) simulations with the spectral element (SE) dynamical core. The code base of the model is CESM1 with CAM5 physics (described in Liu et al., 2014). The horizontal resolution is about 25 km interpolated on longitude/latitude grid (1152 x 768 horizontal grid points), and the vertical resolution is ~0.1 scale height (209 levels). The simulation was part of a NCAR Strategic Capability (NSC) project. The request is for a subset of the simulation that has been used for a paper to be submitted to GRL.
DOI: 10.5065/5jz0-0n57
title: Observed humidity trends in dry regions contradict climate models

description: This dataset contains post-processed observation-based and model-based data between 1980 and 2020 to support the study the humidity trends. The intercomparison indicates that the observed humidity trends in dry regions contradict the climate model simulations. This may indicate a major gap of hydroclimate-related processes in the climate models.
DOI: 10.5065/jkcq-jq33
title: CAM7 Vertical Resolution

description: This dataset contains the raw data and post-processed fields necessary to reproduce the figures from Simpson et al. (2025) "The path toward vertical grid options for the Community Atmosphere Model version 7: the impact of vertical resolution on the QBO and tropical waves", Journal of Advances in Modeling Earth Systems. The data can be used in conjunction with the scripts linked below to reproduce the analysis for this paper.
DOI: 10.5065/cfya-4g50
title: CONUS air quality reanalysis dataset (2005-2018)

description: This 14 year hourly air quality reanalysis dataset is generated through daily assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) and the Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO) retrievals in the Community Multiscale Air Quality Model (CMAQ) from 01 January 2005 to 31 December 2018. The production of this air quality reanalysis is funded by the Atmospheric Composition Modeling and Analysis Program (ACMAP) under the project entitled 'Quantification and attribution of past (2005-2018) air quality trends over the Contiguous United States (CONUS) via assimilation of NASA atmospheric composition'. This data can be used to (1) develop products and metrics for assessing the long-term impact of air pollution on public health, agriculture, and economy as well as for quantifying air quality changes in unmonitored areas and benefits of emission control policies.
DOI: 10.26024/kgmp-c556
title: CESM2 Large Ensemble

description: The CESM2 Large Ensemble consists of 100 members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Two separate sets of biomass burning emissions forcing files were used within the ensemble. Members 1-50 were forced with CMIP6 protocols identical to those used in Danabasoglu et al. (2020) in the paper for CESM2. For members 51-100, the most relevant species for biomass burning fluxes from the CMIP6 protocols were smoothed with an 11-year running mean filter, impacting the fluxes over the years 1990-2020.The CESM2 Large Ensemble uses a combination of different oceanic and atmospheric initial states to create ensemble spread as follows: Members 1-10: These begin from years 1001, 1021, 1041, 1061, 1081, 1101, 1121, 1141, 1161, and 1181 of the 1400-year pre-industrial control simulation. This segment of the control simulation was chosen to minimize drift.Members 11-90: These begin from 4 pre-selected years of the pre-industrial control simulation based on the phase of the Atlantic Meridional Overturning Circulation (AMOC). For each of the 4 initial states, there are 20 ensemble members created by randomly perturbing the atmospheric temperature field on the order of -14K. The chosen start dates (model years 1231, 1251, 1281, and 1301) sample AMOC and Sea Surface Height (SSH) in the Labrador Sea at their maximum, minimum and transition states.Members 91-100: These begin from years 1011, 1031, 1051, 1071, 1091, 1111, 1131, 1151, 1171, and 1191 of the 1400-year pre-industrial control simulation. This set includes the extensive "MOAR" output, which can be used to drive regional climate models.The initialization design allows assessment of oceanic (AMOC) and atmospheric contributions to ensemble spread, and the impact of AMOC initial-condition memory on the global earth system.
DOI: 10.5065/3qfn-gn70
title: Long Simulations of the Miocene Climatic Optimum

description: The global warmth of the Miocene Climatic Optimum (MCO, ~15 Ma) offers valuable insights into warm climate dynamics and future climate change, providing a real-world testbed for validating climate models. However, it remains unclear how warm the MCO was given the scarcity and uncertainties of surface temperature proxy records. Three iCESM1.3 long simulations are constructed to estimate the Miocene global mean surface temperature (GMST). The three simulations included: preindustrial (PI), 1.5x CO2, 3x CO2. Each simulation case includes long time series files with a monthly temporal resolution and a NE16 G16 spatial resolution (~2 degree atmosphere and ~1 degree ocean), covering the last 100 model years of the global climate fields.
DOI: 10.5065/h9gg-5a31
title: CESM ensemble consistency test atmospheric data

description: Community Atmosphere Model (CAM) data from the 1.3 release series of CESM, using a present-day F compset (active atmosphere and land, data ocean, and prescribed ice concentration) and CAM5 physics. This spectral-element version of CAM uses a ne30 resolution, which corresponds approximately to a 1 degree global grid containing a total of 48,602 horizontal grid points and 30 vertical levels. Each simulation is 1 year in length. The files are CAM history files in NetCDF format. Each file contains two time slices: the first contains the initial condition and the second contains the annual average. There are 343 files in total, each containing 134 2D and 3D variables. (548M each).
DOI: 10.15468/dl.vjg2tq
title: Occurrence Download

description: A dataset containing 5467 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Carex humilis, Carex humilis, Carex humilis)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 5467 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012596-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5065/tgbj-yv18
title: Community MUSICAv0 CONUS Simulations

description: The Community MUSICAv0 CONUS simulations have been produced using the Community Earth System Model Release Version 2.2.0 with comprehensive tropospheric and stratospheric TS1 chemistry, using the spectral element (SE) dynamical core, with regional refinement over the contiguous U.S., having a grid mesh with approximately 1-degree horizontal grid spacing over most of the globe that refines to 1/8 degree (~14 km) over the U.S. We also provide a model simulation without the regional refinement for comparison, link to follow.The file names are as follows: *.cam.h0*.nc files are monthly mean output fields on the 0.9 x 1.25 degrees regular horizontal grid; *.cam.h1*.nc files are monthly mean output fields on the native grid; *.cam.h2*.nc files are daily mean output fields on the native grid.
DOI: 10.5065/x4kb-xj98
title: GPCP Version 3.2 Daily Satellite-Gauge (SG) Combined Precipitation Data Set

description: This dataset contains Version 3.2 of The Global Precipitation Climatology Project (GPCP) Daily Precipitation Data Set (GPCPDAY). The variables included are precipitation and probability of liquid phase. As the follow-on to the GPCP Version 2.3 Monthly product and the Version 1.3 One Degree Daily product, GPCP Version 3 (GPCP V3.2) seeks to continue the long, homogeneous precipitation record using modern merging techniques and input data sets. The GPCP V3 suite currently consists of the 0.5-degree Monthly and 0.5-degree Daily. A follow-on 0.1-degree 3-hourly product is expected. All GPCPV3 products are constructed to be internally consistent. The Daily product spans June 2000 to the present, with roughly quarterly updates. Inputs consist of Global Precipitation Measurement (GPM) mission Integrated Multi-satellitE Retrievals for GPM (IMERG) estimates in the span 55 degrees North-South, and Television-Infrared Operational Satellite (TIROS) Operational Vertical Sounder / Advanced Infrared Sounder (TOVS/AIRS) estimates, adjusted climatologically to IMERG across the 55-degree latitude boundary, outside 55 degrees North-South. The Daily estimates are scaled to approximately sum to the Monthly value at each 0.5 degree grid box. In addition to the complete precipitation field, probability of liquid phase estimates are provided globally. GPCP Version 3 Daily was developed primarily under a current NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program (PI: Ali Behrangi, University of Arizona). The GPCP is computed as a contribution to the World Climate Research Program (WCRP) and Global Water and Energy Exchange (GEWEX) activities, and is part of the array of data sets describing the water and energy cycles of the planet. Prior versions of the GPCP analysis have been produced by a consortium of individual scientists at various government and university institutions and most recently as part of the NOAA Climate Data Record (CDR) Program. The current GPCP Daily product described here creates a global daily satellite product using the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) half-hourly Final Run product at low and middle latitudes, and daily retrievals from Television InfraRed Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) and Atmospheric Infrared Sounder (AIRS) at high latitudes, with calibration to the GPCP V3.2 Monthly SG product. For more information, see the GPCPDAY official site at NASA GES DISC [https://disc.gsfc.nasa.gov/datasets/GPCPDAY_3.2/summary].
DOI: 10.26024/s4p7-pf13
title: Atmospheric River Tracking Method Intercomparison Project Tier 2 CMIP5/6 Source Data and Catalogues

description: Atmospheric River Tracking Method Intercomparison Project (ARTMIP) Tier 2 CMIP5/6 developer catalogues and source data. Each ARTMIP method/algorithm (named by developer) submits a catalogue comprised of 0's (no AR exists) or 1's (yes AR exists) for each time slice, for each grid point, using a curated set of output from the Coupled Model Intercomparison Project 5 and 6 multi-model ensembles (see Table 1). Catalogues are created for single ensemble members from historical simulations and for RCP8.5 (CMIP5) and SSP5-8.5 (CMIP6) future simulations, for the 1950-2099 time period. Ensemble member r1i1p1f1 or r1i1p1f1 is used for each input, with the exception of the CMIP5 CCSM4 run, which uses ensemble member r6i1p1. Derived CMIP5/6 quantities required for algorithms, such as IVT or IWV, were computed by the ARTMIP project so that all methods use the exact same data.There are some exceptions to the time period noted above: output from the CMIP6 IPSL-CM6A-LR SSP5-8.5 simulation are only available through 2049, there are data corruption issues for the year 2006 in the CMIP5 CSIRO-Mk3-6-0 simulation, and there are data corruption issues for the year 2095-2099 for the TECA_BARD_v1.0 output applied to the CMIP5 IPSL-CM5B-LR simulation. The Guan_Waliser_v2 algorithm did not supply ARDT catalogues for the NorESM1-M and BCC-CSM2-MR simulations.
DOI: 10.26024/5b58-nc53
title: SD WACCM-X v2.1

description: The Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X) is a comprehensive numerical model, spanning the range of altitude from the Earth's surface to the upper thermosphere. The history files here refer to a 1980-2017 specified dynamics (SD) WACCM-X version v2.1 simulation with nudging of Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data from the surface up to approximately 50 km.long run data is an update for 1 January 2000 - 31 December 2017. The unspecified time frequency data is hs output; these files contain the variable instr_num which is set equal to 40 for the CHAMP satellite, 41 for GRACE, 42 for GOCE, 43 for SWARM-A, and 44 for SWARM-B.