Standard WRF output in NetCDF format. This dataset is not publicly accessible because: The dataset consist of 59 WRF output files totaling a size of about 90 Gb. It can be accessed through the following means: US EPA Atmos tape drive archive: /asm/MOD3DEV/met/ALPACA/wrf_outputs/ALL_OBS_TWEAKS_FDDA9. Format: Raw WRF outputs in NetCDF format. This dataset is associated with the following publication: Brett, N., K. Law, S. Arnold, J.G. Fochesatto, J. Raut, T. Onishi, R. Gilliam, K. Fahey, D. Huff, G. Pouliot, B. Barret, E. Dieudonné, R. Pohorsky, J. Schmale, A. Baccarini, S. Bekki, G. Pappaccogli, F. Scoto, S. Decesari, A. Donateo, M. Cesler-Maloney, W. Simpson, P. Medina, B. D'Anna, B. Temime-Roussel, J. Savarino, S. Albertin, J. Mao, B. Alexander, A. Moon, P. DeCarlo, V. Selimovic, R. Yokelson, and E.S. Robinson. Investigating processes influencing simulation of local Arctic wintertime anthropogenic pollution in Fairbanks, Alaska during ALPACA-2022. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 25(2): 1063–1104, (2025).

The modeled data in these archives are in the NetCDF format (https://www.unidata.ucar.edu/software/netcdf/). NetCDF (Network Common Data Form) is a set of software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. It is also a community standard for sharing scientific data. The Unidata Program Center supports and maintains netCDF programming interfaces for C, C++, Java, and Fortran. Programming interfaces are also available for Python, IDL, MATLAB, R, Ruby, and Perl. Data in netCDF format is: • Self-Describing. A netCDF file includes information about the data it contains. • Portable. A netCDF file can be accessed by computers with different ways of storing integers, characters, and floating-point numbers. • Scalable. Small subsets of large datasets in various formats may be accessed efficiently through netCDF interfaces, even from remote servers. • Appendable. Data may be appended to a properly structured netCDF file without copying the dataset or redefining its structure. • Sharable. One writer and multiple readers may simultaneously access the same netCDF file. • Archivable. Access to all earlier forms of netCDF data will be supported by current and future versions of the software. Pub_figures.tar.zip Contains the NCL scripts for figures 1-5 and Chesapeake Bay Airshed shapefile. The directory structure of the archive is ./Pub_figures/Fig#_data. Where # is the figure number from 1-5. EMISS.data.tar.zip This archive contains two NetCDF files that contain the emission totals for 2011ec and 2040ei emission inventories. The name of the files contain the year of the inventory and the file header contains a description of each variable and the variable units. EPIC.data.tar.zip contains the monthly mean EPIC data in NetCDF format for ammonium fertilizer application (files with ANH3 in the name) and soil ammonium concentration (files with NH3 in the name) for historical (Hist directory) and future (RCP-4.5 directory) simulations. WRF.data.tar.zip contains mean monthly and seasonal data from the 36km downscaled WRF simulations in the NetCDF format for the historical (Hist directory) and future (RCP-4.5 directory) simulations. CMAQ.data.tar.zip contains the mean monthly and seasonal data in NetCDF format from the 36km CMAQ simulations for the historical (Hist directory), future (RCP-4.5 directory) and future with historical emissions (RCP-4.5-hist-emiss directory). This dataset is associated with the following publication: Campbell, P., J. Bash, C. Nolte, T. Spero, E. Cooter, K. Hinson, and L. Linker. Projections of Atmospheric Nitrogen Deposition to the Chesapeake Bay Watershed. Journal of Geophysical Research - Biogeosciences. American Geophysical Union, Washington, DC, USA, 12(11): 3307-3326, (2019).

This data set contains the original model output data submissions from the 24 terrestrial biosphere models (TBM) that participated in the North American Carbon Program (NACP) Site-Level Synthesis. The model teams generated estimates for, but not limited to, a minimum of six variables, including gross primary productivity (GPP), net ecosystem exchange (NEE), leaf area index (LAI), ecosystem respiration (Re), latent heat flux (LE), and sensible heat flux (H) for each of 47 selected eddy covariance flux tower sites across North America. Participating modeling teams followed the NACP Site Synthesis Protocol (site_synthesis_protocol_v7.pdf), which covers procedures, plans, and infrastructure for the site-level analyses. File format and units conversions of several data submissions were made by the MAST-DC to produce NetCDF files of consistent content and structure for all 24 TBM outputs. The model outputs are structured as described in Appendix A: Model Output Variables, of the Site Synthesis Protocol. In addition, MAST-DC processed these original model submissions to derive uniquely processed and formatted data files for model inter-comparison and evaluation (NACP Site: Terrestrial Biosphere Model and Aggregated Flux Data in Standard Format). This related data set provides GPP, NEE, LAI, Re, LE, and sensible heat (H) model output variables at the native half-hourly time step, and in daily, monthly, and annual aggregations. The related data set also contains gap-filled observations and total uncertainty estimates at the same time steps.There are 24 compressed (*.zip) files with this data set -- one file for each model. When expanded, the .zip files contain model output data files for flux tower sites in NetCDF and some in text formats.

The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan's Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) Version 1 data product was also generated. The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in both a Cloud Optimized GeoTIFF (COG) and NetCDF4 format through NASA Earthdata Search and in standard GeoTIFF format through the LP DAAC Data Pool. Data are projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area. Provided in the ASTER GDEM product are layers for DEM and number of scenes (NUM). The NUM layer indicates the number of scenes that were processed for each pixel and the source of the data.While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications. Known Issues ASTER GDEM Version 3 tiles overlap by one pixel to the north, south, east, and west of the tile perimeter. In most cases the overlapping edge pixels have identical pixel values, but it is possible that in some instances values will differ. * ASTER GDEM Version 3 is considered to be void free except for Greenland and Antarctica. Users are reminded that because there are known inaccuracies and artifacts in the dataset, to use the product with awareness of these limitations. The data are provided "as is" and neither NASA nor METI/Earth Resources Satellite Data Analysis Center (ERSDAC) will be responsible for any damages resulting from use of the data.Improvements/Changes from Previous Version Expansion of acquisition coverage to increase the amount of cloud free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3. Separation of rivers from lakes in the water body processing.* Minimum water body detection size decreased from 1 square kilometer (km²) to 0.2 km².

Monthly mean values of surface sensible heat flux (CF standard name: surface_upward_sensible_heat_flux). The model output was prepared for ENSEMBLES and corresponds to the IPCC AR4 20C3M experiment. See experiment summary for further details. These data are in netCDF format.

This dataset comprises monthly mean data from a global, transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 2015 to 2070. WACCM-X is a global atmosphere model covering altitudes from the surface up to ~500 km, i.e., including the troposphere, stratosphere, mesosphere and thermosphere. WACCM-X version 2.0 (Liu et al., 2018) was used, part of the Community Earth System Model (CESM) release 2.1.0 (http://www.cesm.ucar.edu/models/cesm2) made available by the National Center for Atmospheric Research. The model was run in free-running mode with a horizontal resolution of 1.9 degrees latitude and 2.5 degrees longitude (giving 96 latitude points and 144 longitude points) and 126 vertical levels. Further description of the model and simulation setup is provided by Cnossen (2022) and references therein. A large number of variables is included on standard monthly mean output files on the model grid, while selected variables are also offered interpolated to a constant height grid or vertically integrated in height (details below). Zonal mean and global mean output files are included as well.

The data are provided in NetCDF format and file names have the following structure:

f.e210.FXHIST.f19_f19.h1a.cam.h0.[YYYY]-[MM][DFT].nc

where [YYYY] gives the year with 4 digits, [MM] gives the month (2 digits) and [DFT] specifies the data file type. The following data file types are included:

1) Monthly mean output on the full grid for the full set of variables; [DFT] = 2) Zonal mean monthly mean output for the full set of variables; [DFT] = _zm
3) Global mean monthly mean output for the full set of variables; [DFT] = _gm 4) Height-interpolated/-integrated output on the full grid for selected variables; [DFT] = _ht

A cos(latitude) weighting was used when calculating the global means.

Data were interpolated to a set of constant heights (61 levels in total) using the Z3GM variable (for variables output on midpoints, with 'lev' as the vertical coordinate) or the Z3GMI variable (for variables output on interfaces, with ilev as the vertical coordinate) stored on the original output files (type 1 above). Interpolation was done separately for each longitude, latitude and time.

Mass density (DEN [g/cm3]) was calculated from the M_dens, N2_vmr, O2, and O variables on the original data files before interpolation to constant height levels.

The Joule heating power QJ [W/m3] was calculated using Q_J = (sigma_P*B^2)*((u_i - U_n)^2 + (v_i-v_n)^2 + (w_i-w_n)^2) with sigma_P = Pedersen conductivity[S], B = geomagnetic field strength [T], ui, vi, and wi = zonal, meridional, and vertical ion velocities [m/s] and un, vn, and wn = neutral wind velocities [m/s]. QJ was integrated vertically in height (using a 2.5 km height grid spacing rather than the 61 levels on output file type 4) to give the JHH variable on the type 4 data files. The QJOULE variable also given is the Joule heating rate [K/s] at each of the 61 height levels.

All data are provided as monthly mean files with one time record per file, giving 672 files for each data file type for the period 2015-2070 (56 years).

References:

Cnossen, I. (2022), A realistic projection of climate change in the upper atmosphere into the 21st century, in preparation.

Liu, H.-L., C.G. Bardeen, B.T. Foster, et al. (2018), Development and validation of the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X 2.0), Journal of Advances in Modeling Earth Systems, 10(2), 381-402, doi:10.1002/2017ms001232.

Output from a model run of a modified version of WRF-Chem, which we refer to as WRF-Chem Volcano (WCV). At the time of submission of this dataset, these data were the basis of the modelling part of a paper in preparation, working title: "WRF-Chem modelling and TROPOMI observations of halogen chemistry within the plume of Etna's Christmas 2018 eruption".

The code of WCV is maintained here. Development of this code will continue after the submission of this repository, This branch is a permanent record of the code as used to create this dataset. This is a simulation of the chemistry of the plume of the 2018 eruption of Mount Etna. This simulation includes bromine, chlorine and mercury chemistry. The time period covered is the 24-27 December, however please note that the author considers the first 24 hours of simulation to be "spin up", and that the modelled volcanic fluxes were assigned based on observations at midday on the 25th, and were not calibrated specifically for the 26th or 27th.

"Run L2" refers the internal serial number assigned to this model run.

Overview of files

Output files: wrfout_d0*_YYYY-MM-DD_HH:MM:SS

Output data is contained in NetCDF files. Each file contains hourly snapshots of the 3D simulation with fields for various parameters. Most of the 4D (three spatial dimensions and time) variables record modelled mixing ratios of various species (in units ppm). Many other variables are standard WRF-Chem output variables; please see WRF-Chem's documentation. If the meaning of a variable is unclear, please contact the author.

Files are separated by model domain and by time. The "d0x" value specifies the model domain. Domain 1 is the full extent of the modelled area and has grid cells of 30 km × 30 km. Domains 2, 3, 4 each model a successively smaller area subset at a 3x greater resolution than their parent domain. Please see the ACPD paper for further details on this. For operational reasons, the number of hours in different output files is slightly irregular:

Files wrfout_d0x_2018-12-24_00:00:00 contain 24 hourly snapshots from 2018-12-24_00:00:00 -- 2018-12-24_23:00:00

Files wrfout_d0x_2018-12-25_00:00:00 contain 24 hourly snapshots from 2018-12-25_00:00:00 -- 2018-12-25_23:00:00

Files wrfout_d0x_2018-12-26_00:00:00 contain 1 snapshot, 2018-12-26_00:00:00 only

Files wrfout_d0x_2018-12-26_01:00:00 contain 24 hourly snapshots from 2018-12-26_01:00:00 -- 2018-12-27_00:00:00

Files wrfout_d0x_2018-12-27_01:00:00 contain 24 hourly snapshots from 2018-12-27_01:00:00 -- 2018-12-28_00:00:00

Input files

This repository also contains various input files for the WRF-Chem simulation.

wrfinput_d0x (netcdf format) defines the initial conditions assigned for the beginning of the simulation (2018-12-24 00:00:00) for each of the model domains.

wrfbdy_d01 (netcdf format) defines the boundary conditions for the simulation.

wrfchemi_d0x_YYYY-MM-DD_HH:MM:SS (netcdf format) defines, for each day and domain of the simulation, anthropogenic emissions.

wrfchemv_d0x (netcdf format) defines the volcanic emissions. A file is specified for each domain.

namelist.input (text file) defines various wrf-chem runtime options

Testing new integration of gen2 ASVCO2 system on Saildrone Explorer Class USVs for the Arctic OCS Single Beam 2021 mission. acknowledgement=If you use these data in publications or presentations, please acknowledge the Moored Carbon and the Engineering Project Office of NOAA/PMEL. Also, we would appreciate receiving a preprint and/or reprint of publications utilizing the data for inclusion in our bibliography. Relevant publications should be sent to: Moored Carbon Project Office, NOAA/PMEL/OCRD, 7600 Sand Point Way NE, Seattle, WA 98115 or emailed to: adrienne.sutton@noaa.gov area=unassigned cdm_data_type=Trajectory cdm_trajectory_variables=trajectory citation=Please cite Sabine et. al. (2020) when using this dataset. Sabine, C., A.J. Sutton, K. McCabe, N. Lawrence-Slavas, S.R. Alin, R.A. Feely, R. Jenkins, S. Maenner, C. Meinig, J. Thomas, E. van Ooijen, A. Passmore, and B. Tilbrook (2020): Evaluation of a new carbon dioxide system for autonomous surface vehicles. J. Atmos. Oceanic Tech., 37(8), 1305–1317, doi: 10.1175/JTECH-D-20-0010.1 contributor_email=Stacy.maenner@noaa.gov; Nathan.anderson@noaa.gov; Noah.lawrence-slavas@noaa.gov contributor_name=Stacy Maenner; Nathan Anderson; Noah Lawrence-Slavas Conventions=CF-1.6, ACDD-1.3, COARDS data_mode=realtime description=Saildrone NetCDF Format drone_id=1067 Easternmost_Easting=-122.3021184 featureType=Trajectory funding_source=NOAA/IOOS OTT geospatial_lat_max=37.7804032 geospatial_lat_min=37.7749536 geospatial_lat_units=degrees_north geospatial_lon_max=-122.3021184 geospatial_lon_min=-122.307968 geospatial_lon_units=degrees_east history=Saildrone id=149443 infoUrl=https://saildrone.com/ institution=Saildrone interval=60.0 keywords_vocabulary=GCMD Science Keywords naming_authority=com.saildrone netcdf_version=4.6.3 nodc_template_version=NODC_NetCDF_Trajectory_Template_v2.0 Northernmost_Northing=37.7804032 platform=Saildrone principal_investigator=Dr. Adrienne Sutton principal_investigator_email=adrienne.sutton@noaa.gov principal_investigator_institution=NOAA/PMEL principal_investigator_url=https://www.pmel.noaa.gov/co2/story/Adrienne+J.+Sutton%2C+Ph.D. project=ASVCO2 Gen2 IOOS OTT:Technology Transfer of a Surface pCO2 Flux Instrument for Autonomous Platform Applications QC_indicator=Level 0, Raw Data qc_manual=No QC Performed source=Saildrone sourceUrl=(local files) Southernmost_Northing=37.7749536 standard_name_vocabulary=CF Standard Name Table v58 subsetVariables=trajectory,INSTRUMENT_STATE testOutOfDate=now-28days time_coverage_duration=P3DT2H53M time_coverage_end=2021-07-12T23:20:00Z time_coverage_resolution=PT1M time_coverage_start=2021-07-09T20:27:00Z time_in=minutes Westernmost_Easting=-122.307968 wmo_id=5801957 wmo_platform_code=unassigned

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective.

Data Summary: Community Multiscale Air Quality (CMAQ) Model Version 5.0.2 output data from a 2010 CONUS simulation. Note:The datasets are on a Google Drive. The metadata associated with this DOI contain the link to the Google Drive folder and instructions for downloading the data. File Location and Download Instructions: The 2010 model output are available in two forms. The hourly datasets are a set of monthly files with surface-layer hourly concentrations for a model domain that encompasses the contiguous U.S. with a horizontal grid resolution of 12km x 12km. The daily average dataset is a single file with a year of daily average data for the same domain. Link to hourly dataLink to daily average dataDownload instructions File Format: The 2010 model output are stored as netcdf formatted files using I/O API data structures (https://www.cmascenter.org/ioapi/). Information on the model projection and grid structure is contained in the header information of the netcdf file. The output files can be opened and manipulated using I/O API utilities (e.g. M3XTRACT, M3WNDW) or other software programs that can read and write netcdf formatted files (e.g. Fortran, R, Python). Model Variables Variable names in hourly data files: Variable Name,Units,Variable Description CO, ppb, carbon monoxideNO, ppb, nitric oxideNO2, ppb, nitrogen dioxideO3, ppb, ozoneSO2, ppb, sulfur dioxideSO2_UGM3, micrograms/m^3, sulfur dioxideAECIJ, micrograms/m^3, aerosol elemental carbon (sum of i-mode and j-mode) * AOCIJ, micrograms/m^3, aerosol organic carbon (sum of i-mode and j-mode) *ANO3IJ, micrograms/m^3, aerosol nitrate (sum of i-mode and j-mode) * TNO3, micrograms/m^3, total nitrate= NO3 (ANO3IJ)+ nitric acid (HNO3) ANH4IJ,micrograms/m^3, aerosol ammonium (sum of i-mode and j-mode) * ASO4IJ,micrograms/m^3, aerosol sulfate (sum of i-mode and j-mode) * PMIJ **, micrograms/m^3, total fine particulate matter (sum of i-mode and j-mode) * PM10 **, micrograms/m^3, total particulate matter (sum of i-mode, j-mode, k-mode) * Variable names in daily data files: Note: All daily averages are computed using Local Standard Time (LST)Variable Name,Units,Variable DescriptionCO_AVG, ppb, 24-hr average carbon monoxideNO_AVG, ppb, 24-hr average nitric oxideNO2_AVG, ppb, 24-hr average nitrogen dioxideO3_AVG, ppb, 24-hr average ozoneO3_MDA8, ppb, Maximum daily 8-hr average ozone + SO2_AVG, ppb, 24-hr average sulfur dioxideSO2_UGM3_AVG, micrograms/m^3, 24-hr average sulfur dioxideAECIJ_AVG, micrograms/m^3, 24-hr average aerosol elemental carbon (sum of i-mode and j-mode) *AOCIJ_AVG, micrograms/m^3, 24-hr average aerosol organic carbon (sum of i-mode and j-mode) *ANO3IJ_AVG, micrograms/m^3, 24-hr average aerosol nitrate (sum of i-mode and j-mode) *TNO3_AVG, micrograms/m^3, 24-hr average total nitrate= NO3 (ANO3IJ)+ nitric acid (HNO3) ANH4IJ_AVG,micrograms/m^3, 24-hr average aerosol ammonium (sum of i-mode and j-mode) * ASO4IJ_AVG,micrograms/m^3, 24-hr average aerosol sulfate (sum of i-mode and j-mode) * PMIJ_AVG **, micrograms/m^3, 24-hr average total fine particulate matter (sum of i-mode and j-mode) * PM10_AVG **, micrograms/m^3, 24-hr average total particulate matter (sum of i-mode, j-mode, k-mode) * +The calculation of the MDA8 O3 variable is based on the current ozone NAAQS and is derived from the highest of the 17 consecutive 8-hr averages beginning with the 8-hr period from 7:00am to 3:00pm LST and ending with the 8-hr period from 11pm to 7am the following day. *CMAQ represents PM using three interacting lognormal distributions, or modes. Two modes, Aitken (i-mode) and accumulation (j-mode) are generally less than 2.5 microns in diameter while the coarse mode (k-mode) contains significant amounts of mass above 2.5 microns. **Note that modeled size distributions can also be used to output PM species that represent the aerosol mass that falls below a specific diameter, e.g. 2.5 um or 10um. The output variables that are based on the sharp cut-off method are typically very similar to the aggregate PMIJ (i+j mode) and PM10 (i+j+k mode) variables included in these files. Further information on particle size-composition distributions in CMAQv5.0 can be found in Nolte et al. (2015), https://doi.org/10.5194/gmd-8-2877-2015. Simulation Settings and Inputs: CMAQ Model Model version: 5.0.2 Bi-directional NH3 air-surface exchange: Massad formulation Chemical mechanism: CB05TUCL Aerosol module: aero6 Domain: Continental U.S. (CONUS) using a 12 km grid size and a Lambert Conformal projection assuming a spherical earth with radius 6370.0 km. Vertical Resolution: 35 layers from the surface to the top of the free troposphere with layer 1 nominally 19 m tall. Boundary Condition Inputs Hourly values from 2010 simulation of GEOS-Chem v8-03-02 with GEOS-5 meteorologyNLCD land cover Used in WRF: 2006 Emissions Inputs Anthropogenic emissions: Emission inventory label 2007ed_10. 2007 modeling platform based on AQMEII phase 2 emissions:...

The Smith & Reynolds Extended Reconstructed Sea Surface Temperature (ERSST) Level 4 dataset provides a historical reconstruction of monthly global ocean surface temperatures and temperature anomalies over a 2 degree spatial grid since 1854 from in-situ observations based on a consistent statistical methodology that accounts for uneven sampling distributions over time and related observational biases. Version 5 of this dataset implements release 3.0 of ICOADS (International Comprehensive Ocean-Atmosphere Data Set) and is supplemented by monthly GTS (Global Telecommunications Ship and buoy) system data. As for the prior ERSST version, v5 implements Empirical Orthogonal Teleconnection analysis (EOT) but with an improved tuning method for sparsely sampled regions and periods. ERSST anomalies are computed with respect to a 1971-2000 monthly climatology. The version 5 has been improved from previous version 4. Major improvements in v5 include: 1) Inclusion and use of new sources and new versions of input datasets, such as data from Argo floats (new source), ICOADS R3.0 (from R2.5), HadISST2 (from HadISST1) sea ice concentration, and 2) Improved methodologies, such as inclusion of additional statistical modes, less spatial-temporal smoothing, better quality control method, and bias correction with baseline to modern buoy observations. The new version improves the spatial structures and magnitudes of El Nino and La Nina events. The ERSST v5 in netCDF format contains extended reconstructed sea surface temperature, SST anomaly, and associated estimated SST error standard deviation fields, in compliance with CF1.6 standard metadata.

Monthly mean values of column integerated cloud water content (CF standard name: atmosphere_cloud_condensed_water_content). The model output was prepared for ENSEMBLES and corresponds to the IPCC AR4 SRESA1B experiment. See experiment summary for further details. These data are in netCDF format.

Monthly mean values of total cloud fraction (CF standard name: cloud_area_fraction). The model output was prepared for ENSEMBLES and corresponds to the IPCC AR4 1PCTTO2X experiment. See experiment summary for further details. These data are in netCDF format.

[ Derived from parent entry - See data hierarchy tab ]

This data of the project CORDEX includes CORDEX experiments for the domain for Europe in high resolution (EUR-11) based on DHMZ's RegCM4-2 model.
Each file contains a single variable in the format NetCDF-4 compressed with CF standard names (CF-1.4). The data are provided on the model computational (native) grid. Information on additional project naming conventions is specified in the project description.

The data include several daily, monthly and seasonal variables from the DHMZ-RegCM4-2 simulation forced by the ERA-Interim reanalysis. Data format follows CORDEX data protocol. Please contact ivan.guettler@cirus.dhz.hr for any relevant requests for this simulation.

Please refer to the publication, particularly the information in the Supplementary Information, for details on the model configuration.Footprint files:Footprints generated every 30 seconds along flight paths using different models are archived as netCDF files. Each tar.gz file contains all the netCDF footprints for a particular flight and model combination, and is named after the model combination and flight date (YYYYMMDD). For example the WRF-HYSPLIT combination for the flight on 10/19/2013 referenced in the paper is in:WRF-HYSPLIT/WRFHYS_Footprints_20131019.tar.gzMost flight footprints were run for 24 hours back in time but there are a few exceptions, so the files must be opened to see how far back the footprints go. A few flights use shorter times, and on 10/28/2013 WRF-HYSPLIT was run for 36 hours. The HYSPLIT footprint files are numbered consecutively in order of time. The location and time of the receptor is in the NetCDF file itself, not in the filename. The STILT filenames have location and time information but only to the nearest minute, so the numerical order in the filename indicates their time order, because there are two footprints each minute. STILT and HYSPLIT footprints all also contain particle trajectories. The receptor location and time is in the NetCDF file as origutctime, origlat, origlong, etc.The files include footprints from basic model runs referenced in Figures 4 and 7, that is NAMS-HYSPLIT, WRF-HYSPLIT, and WRF-STILT. WRF-STILT for flights on 3/25, 3/27, 3/30 and 10/16 uses instantaneous wind output; WRF-STILT for 10/19, 10/20, 10/25, and 10/28 flights uses averaged wind fields (see the SI in the manuscript for details). For WRF2-Flexpart footprints, please contact Wayne.Angevine@noaa.gov. For CarbonTracker Lagrange WRF-STILT footprints, contact Arlyn.Andrews@noaa.gov. For WRF-LPDM footprints, contact Thomas Lauvaux (thomas.lauvaux@lsce.ipsl.fr).WRF-Chem output files:WRF-Chem output for 4 flights in October 2013 is also included here, both in native NetCDF format and in ARL format. These contain 3-km resolution, hourly WRF-Chem output. ARL files can be used to run HYSPLIT or STILT. The NetCDF formatted files include the tracer variables for CH4 from both the EPA inventory (tracer_1 variable) and the EDF inventory used in the paper (tracer_2 variable). The third tracer (tracer_3) is using the EPA inventory but masked so that emissions outside the domain of the EDF inventory are zero (so that they can be directly compared). Only tracer_2 is used in the manuscript. The NetCDF output files are combined into tar.gz files. Please contact Thomas Lauvaux (thomas.lauvaux@lsce.ipsl.fr) for details regarding WRF-Chem.Observations:Observations from the Barnett flight campaign are made available by NOAA/ESRL, please contact Colm.Sweeney@noaa.gov.

Monthly mean values of surface latent heat flux (CF standard name: surface_upward_latent_heat_flux). The model output was prepared for ENSEMBLES and corresponds to the IPCC AR4 1PCTTO4X experiment. See experiment summary for further details. These data are in netCDF format.

[ Derived from parent entry - See data hierarchy tab ]

This data of the project CORDEX includes CORDEX experiments for the domain Europe in high resolution (EUR-11) based on KNMI's RACMO22E model.
Each file contains a single variable in the format NetCDF-4 compressed with CF standard names (CF-1.4). The data are provided on the model computational (native) grid. Information on additional project naming conventions is specified in the project description. This data was retracted due to errors in the forcing, see quality for details. The corrected data in version v2 is available at: https://cera-www.dkrz.de/WDCC/ui/Entry.jsp?acronym=CXEU11KNRA

Monthly mean values of surface sensible heat flux (CF standard name: surface_upward_sensible_heat_flux). The model output was prepared for ENSEMBLES and corresponds to the IPCC AR4 1PCTTO2X experiment. See experiment summary for further details. These data are in netCDF format.

Monthly mean values of large-scale precipitation (CF standard name: large_scale_precipitation_flux). The model output was prepared for ENSEMBLES and corresponds to the IPCC AR4 SRESB1 experiment. See experiment summary for further details. These data are in netCDF format.

Monthly mean values of evaporation (CF standard name: water_evaporation_flux). The model output was prepared for ENSEMBLES and corresponds to the IPCC AR4 SRESB1 experiment. See experiment summary for further details. These data are in netCDF format.