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climate

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  • This dataset includes the CNRM-CM5-LRA-LRO model output prepared for SPECS horizlResImpact (1993-2009). These data were prepared by the Centre National de Recherches Meteorologiques, as part of the SPECS project. Model id is CNRM-CM5-LRA-LRO, frequency is daily, associated model is atmo LR ocean LR. Arpege V5.1 is the underlying model (CNRM-CM5 2013 atmosphere:Arpege (tl127l31r); ocean:Nemo (Orca1); sea-ice:none; land:isba). variables available are: - Precipitation flux (pr) in kg m-2 s-1 - Air Temperature (tas) in deg K - Max Air temperature (tasmax) deg K - Min Air temperature (tasmin) deg K - Geopotential height (zg) in metres - Air Pressure at sea level (psl) in Pa

  • This dataset includes the CNRM-CM5-HRA-LRO model output prepared for SPECS horizlResImpact (1993-2009). These data were prepared by the Centre National de Recherches Meteorologiques, as part of the SPECS project. Model id is CNRM-CM5-HRA-LRO, frequency is daily, associated model is atmo HR ocean LR. Arpege V5.1 is the underlying model (CNRM-CM5 2013 atmosphere:Arpege (tl359l31r); ocean:Nemo (Orca1); sea-ice:none; land:isba). variables available are: - Precipitation flux (pr) in kg m-2 s-1 - Air Temperature (tas) in deg K - Max Air temperature (tasmax) deg K - Min Air temperature (tasmin) deg K - Geopotential height (zg) in metres - Air Pressure at sea level (psl) in Pa

  • This dataset includes the CNRM-CM5-HRA-HRO model output prepared for SPECS horizlResImpact (1993-2009). These data were prepared by the Centre National de Recherches Meteorologiques, as part of the SPECS project. Model id is CNRM-CM5-HRA-HRO, frequency is daily, associated model is atmo HR ocean HR. Arpege V5.1 is the underlying model (CNRM-CM5 2013 atmosphere:Arpege (tl359l31r); ocean:Nemo (Orca0.25); sea-ice:none; land:isba). variables available are: - Precipitation flux (pr) in kg m-2 s-1 - Air Temperature (tas) in degree Kelvin - Geopotential height (zg) in metres

  • This dataset contains methane concentrations from a chemistry-climate model, focusing on year 2000 and year 2100. The present-day forcings were used for the 2000 simulation, while for year 2100 the Representative Concentration Pathway (RCP) RCP8.5 pathway were used. All experiments were run as perpetual timeslice experiments and are global model simulations made using the Met Office Unified Model at vn7.3 based on the HadGEM3-A science configuration. The model was run in atmosphere-only mode with a horizontal resolution of 2.5 degree latitude by 3.75 degree longitude, 60 vertical levels up to 84 km, and prescribed sea surface temperatures and sea ice extents. SST, sea ice and other forcings from earlier model experiments were used, e.g. Banerjee et al. (doi:/10.5194/acp-14-9871-2014). For the year 2000 experiments, greenhouse gas, ozone depleting substances and ozone precursor emissions are taken from the Coupled Model Intercomparison Project - Phase 5 (CMIP5) reference forcings, as in Lamarque, 2010 (doi.org/10.5194/acp-10-7017-2010). The data comprise a series of separate experiments designed to test the performance of methane emissions in this model and to compare against the default that uses a prescribed concentration at the surface, with a view to assessing the performance of the more physically realist emissions treatment. For year 2000, the model was run for three experiments: the first (BASE) experiments employ a set of emissions derived from EDGAR v4 to describe anthropogenic methane emissions, with biognenic emissions taken from the chemistry-transport model (CTM) intercomparison experiment (TransCom-CH4) paper of Patra et al, (DOI:10.5194/acp-11-12813-2011), a second set of experiments used identical emissions to BASE except that CO emissions were increased by 50% globally from the emissions of Lamarque, this is called Delta_CO, and a third year 2000 experiment used CMIP5 methane emissions from Lamarque (as above) rather than EDGAR and biogenic emissions derived from Melton et al. (https://doi.org/10.5194/bg-10-753-2013) rather than Patra. These experiments test the model skill in simulating methane based on the model treatment of emissions and establish the sensitivity to emissions. Three future climate experiments were also performed using climate forcings appropriate to year 2100 following the RCP8.5 pathway. We looked at the climate drivers in turn that arise as the climate changes. In the first, DELTA_CC, climate forcings were adjusted from greenhouse gases to year 2100 values, but kept methane and other anthropogenic forcings at year 2000 values, a second experiment, DELTA_CH4, adjusted CH4 to Year 2100 values from the emissions database as above, a third was an all-forcings experiments in which greenhouse gases, methane and ozone precursors were adjusted to RCP8.5 levels. This gave three separate experiments which explore how methane responds to these changes in the climate drivers.

  • This dataset includes the CNRM-CM5 model output prepared for SPECS seaIceInit (1979-2012). These data were prepared by the Centre National de Recherches Meteorologiques, as part of the SPECS project. The model used is CNRM-CM, combining ARPEGEv6.0.3 + NEM0v3.2 + GELATO6.0.1 + SURFEX7.2, frequency is monthly. Atmospheric variables are: clt evlwr hfls hfss hus mrro mrso pr prsn psl rlds rls rlut rsds rsdt rss ta tas tasmax tasmin tauu tauv ua uas va vas zg Oceanic variables are: hfnorth mlotst msftmyz msftmyza msftmyzba sltnorth so t20d thetao tos uo vo SeaIce variables are: sic sit snld strairx strairy tsice usi vsi

  • The Climatic Research Unit (CRU) Country (CY) data version 4.00 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes. This dataset was produced in 2017 by CRU at the University of East Anglia and extends the CRU CY3.23 data to include 2015. CRU CY4.00 is a full release, differing only in methodology from the existing current release, v3.24.01. Both are released concurrently to support comparative evaluations between these two versions. The data are available as text files with the extension '.per' and can be opened by most text editors. Spatial averages are calculated using area-weighted means. CRU CY4.00 is derived directly from the CRU TS4.00 dataset. CRU CY version 4.00 spans the period 1901-2015 for 289 countries. To understand the CRU CY4.00 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.00. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.00 release notes listed in the online documentation on this record. CRU CY data are available for download to all CEDA users.

  • The Climatic Research Unit (CRU) Country (CY) data version 4.01 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes. This dataset was produced in 2017 by CRU at the University of East Anglia and extends the CRU CY4.00 data to include 2016. CRU CY4.01 is a full release, differing only in methodology from the existing current version 3 release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. The data are available as text files with the extension '.per' and can be opened by most text editors. Spatial averages are calculated using area-weighted means. CRU CY4.01 is derived directly from the CRU TS4.01 dataset. CRU CY version 4.01 spans the period 1901-2016 for 289 countries. To understand the CRU CY4.01 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.01. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.01 release notes listed in the online documentation on this record. CRU CY data are available for download to all CEDA users.

  • The CRU CY version 3.24.01 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This dataset was produced in 2016 by the Climatic Research Unit (CRU) at the University of East Anglia and replaces the withdrawn CRU CY 3.24. The data are available as text files with the extension '.per' and can be opened by most text editors. Spatial averages are calculated using area-weighted means. CRU CY3.24.01 is derived directly from the CRU TS3.24.01 dataset. CRU CY version 3.24.01 spans the period 1901-2015 for 289 countries. To understand the CRU-CY3.24.01 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS3.24.01. It is therefore recommended that all users read the Harris et al, 2014 paper listed in the online documentation on this record. CRU CY data are available for download to all CEDA users.

  • This dataset comprises monthly mean data from a global, transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 1950 to 2015. 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 made available by the US National Center for Atmospheric Research. The model was run in free-running mode with a horizontal resolution of 1.9° latitude 2.5° 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 (2020) and references therein. A large number of variables are 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 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=_P B^2 [(u_i-u_n )^2+(v_i-v_n )^2+(w_i-w_n )^2] with 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 792 files for each data file type for the period 1950-2015 (66 years).

  • This version of CRU CY is superseded by version 4.01. It is being made available to assist with users moving to the new process. No further releases of version 3 are planned. An updated set of country definitions have been introduced with this version. Please see the appropriate Release Notes. The data are available as text files with the extension '.per' and can be opened by most text editors. The CRU CY version 3.25 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This dataset was produced in 2017 by the Climatic Research Unit (CRU) at the University of East Anglia and extends CRU CY 3.24.01. Spatial averages are calculated using area-weighted means. CRU CY3.25 is derived directly from the CRU TS3.25 dataset. CRU CY version 3.25 spans the period 1901-2016 for 289 countries. To understand the CRU-CY3.25 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS3.25. It is therefore recommended that all users read the Harris et al, 2014 paper listed in the online documentation on this record. CRU CY data are available for download to all CEDA users.