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248 results for “wrf”
Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for October-December 2017
<p>Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for October-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for October-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for October-December 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for July-September 2017
<p>Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for July-September 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for July-September 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for July-September 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for January-March 2017
<p>Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for January-March 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for January-March 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for January-March 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for April-June 2017
<p>Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for April-June 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for April-June 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for April-June 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for January-March 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for January-March 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for January-March 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for January-March 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for October-December 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for October-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for October-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for October-December 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for July-September 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for July-September 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for July-September 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for July-September 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for April-June 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for April-June 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for April-June 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for April-June 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for October-December 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for October-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for October-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for October-December 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for July-September 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for July-September 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for July-September 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for July-September 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for January-March 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for January-March 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for January-March 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for January-March 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for April-June 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for April-June 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for April-June 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for April-June 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
WRF model configuration and data used for the NHESS manuscript "Heat wave characteristics: evaluation of regional climate model performances for Germany"
<p>The file contains:</p> <ul> <li>the namelist.input document with the description of the WRF model configuration used in Warscher et al. (2019)</li> <li>WRF simulation outputs from the reanalysis run: daily values of maximum temperature for the time period 1980-2009 from the innermost (5 km grid resolution) and second innermost (15 km) domain; from both domains the same section, relevant for the study, was taken; the data was bilineraily interpolated to 12.5 km horizontal grid resolution to match the EUR-11 CORDEX format</li> </ul>
WRF_NOx_output
<p>WRF model outputs</p>
WRF-Chem output- concentrations for the two simulations: Business as Usual and COVID for the two periods, March-April and May
<p>The WRF-Chem model was utilized to calculate the changes in O3 chemistry during the COVID lockdown period. We ran two simulations: (1) Business As Usual (BAU) and (2) COVID for the lockdown (30 March to 12 April 2020) and relaxation (18- 25 to 30 May 2020) periods. </p> <p>Here, we provide modelled concentrations for several chemical and physical species for 30 March to 12 April (only weekdays) and 18 to 30 May (only weekdays) for both simulations, BAU and COVID, over the AMB area during the morning (6-8 UTC), afternoon (13-15 UTC) and evening (19-21 UTC) hours. </p> <p>We also provide the WRF-Chem output used to create the air parcel trajectories and the ozone concentrations from the Metropolitan Area of Barcelona to the Pyrenees. </p>
Simulation performance of different planetary boundary layer schemes in WRF V4.3.1 on wind field over Sichuan Basin within "Gray zone" resolution
<p>Weather Research and Forecasting (WRF) model was <span>used</span> to <span>investigate the performance of different planetary </span>boundary layer <span>(PBL) </span>parameteri<span>z</span>ation schemes <span>on </span>simulat<span>ing</span> surface wind <span>fields over Sichuan Basin</span> at a spatial resolution of <span>0.33</span>km<span>.</span> <span>T</span>he <span>experiment</span> is based on <span>multi-</span>case stud<span>ies, so</span> 2<span>8 near-surface </span>wind events from 2021 to 2022 <span>were selected, and</span> <span>a</span> total of 112 <span>sensitivity </span>simulations were <span>carried out by</span> employing four common<span>ly used</span> <span>PBL </span>schemes: YSU, MYJ, MYNN2, and QNSE<span>, and</span> compared to observations.</p> <p>The mean 10 minutes observations of wind speed and direction during the study period from the Guanghan Airport are stored in one seperate txt file named OBS-28cases-every10min-10m-wind-Guanghan-Airoprt.txt.</p> <p>Wind field (U10, V10) at the central point from the WRF simulations of inner domain from all the PBL simulations are investigated, which are stored in txt format (.txt), and all the results are available from the first author(yuet@mail.iap.ac.cn).</p>
Climatology of Sundowner Winds in Coastal Santa Barbara, California, Based on 30 yr High Resolution WRF Downscaling
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Modeling the impact of a potential shale gas industry in Germany and the United Kingdom on ozone with WRF-Chem
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Data from: Prediction of three years of annual rain attenuation statistics at Ka-band in French Guiana using the Numerical Weather Prediction model WRF
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Realtime WRF Large-Eddy Simulation Data
<p>Sample data files from realtime micro-scale weather simulations that were performed to support UAV (Unmanned Aerial Vehicles) flights during ISARRA Lower Atmospheric Process Studies at Elevation – Remotely-piloted Aircraft Team Experiment (LAPSE-RATE) field experiment. Two types of data are available: (1) ascii files that contain profiles and surface variables at select grid points that correspond with 3 key observing locations, (2) grib2 files contain 2D and 3D grids of variables described below and stored on levels AGL as described more below. The sample data includes all leadtimes from both domains. Domain 01 (1 km grid spacing) is initialized at 0400 UTC, lead times = 00h00m to 18h00m by 10m increments (108 files) and DO2 is initialized at 1000 UTC with leadtimes of 06h00m-18h00m by 10 min increments (72 files). Each grib2 file from the WRF-LES domain (D02) are around 100 MB per lead time. The full dataset is available here: <a href="https://doi.org/10.5065/83r2-0579">https://doi.org/10.5065/83r2-0579</a></p> <p>These simulations were performed by driving a nested grid configuration of the Weather Research and Forecasting model with its innermost mesh being run at 111 m grid spacing. The innermost grid was nested within a grid with 1 km grid spacing. The outermost grid being driven using operational forecast models data as described below. While the MYNN2 PBL scheme is used to parameterize turbulence in the 1 km grid, the PBL scheme is turned off within the 111 m grid, thus, allowing large-scale turbulent eddies to be resolved by WRF primitive equations. Subgrid-scale turbulence is diagnosed and stored within the TKE variable using Lilly (1966, 1967).<br> <br> The realtime simulations were produced twice per day in order to support mission planning and UAVs flight operations. A next-day simulation was run using forcing data from NCEP's Global Forecast System (GFS) while a day-of simulation was run using data from the High Resolution Rapid Refresh (HRRR). Both simulations were valid between 04:00 and 16:00 local time providing an opportunity to explore the impact of lateral boundary conditions on forecast skill. The dataset consists of a series of two sets of files: 3D grids and point profiles. The 3D grids consist of all relevant basic state parameters (p,T,U,RH) and diagnostics (e.g., sub-grid scale TKE, ceiling height, visibility) that have been interpolated to flight levels AGL using the Unified Post-Processor (UPP). The UPP was used to de-stagger the mass and wind fields (and compute wind in earth-relative coordinates), interpolate forecast data to flight levels AGL and to compute diagnostics such as visibility, ceiling height, and radar reflectivity.</p> <p>Profile and surface data are stored in ascii format for select grid points coincident with up to 3 fixed observation sites set up during LAPSE-RATE (i.e., Saguache, Moffat and Leach Airfield) with a time resolution of 0.666 sec. See README files for details. The 3D output files are stored in grib2 format which are available every 10 min. The grib2 data can be converted to netCDF using a variety of tools such as ncl_convert2nc command available on many linuxOS.</p> <p>---------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>Details of ascii file names:</p> <p>XXX.dnn.VV.yyyymmddhh.gz</p> <p>where</p> <p>XXX is the location name (SAG - Saguache, MOF - Moffat, LEA - Leach)</p> <p>nn is the domain number (01,02,03)</p> <p>VV is the variable (see readme file for details)</p> <p>yyyymmddhh is the model initialization time (UTC)</p> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>Details of grib2 data files:</p> <p>Data are stored as follows: one file per forecast lead time using the following file naming convention:</p> <p>WRFPRS_YYYYMMDDhhmm_dnn.lh_lm</p> <p>where</p> <p>hhmm is the hour and minute of the day the model run was initialize</p> <p>nn = domain number</p> <p>lh = forecast outlook hour</p> <p>lm = forecast outlook min</p> <p>valid_time = hhmm + lhlm</p> <p>zlevels = (30,80,150,300,500,750,1000,1250,1500,1750,2000,2500,3000,3500,4000,4500,5000 m AGL)<br> <br> DatasetTemporalCoverage: 14 - 19 July 2018<br> Forecasts were issued twice per-day and valid between 04:00 and 16:00 LT (10:00 and 22:00 UTC)</p> <p>Gridded data are stored at 10 min intervals</p> <p><br> Interpolated 3D Variables: temperature,pressure,u,v,w,RH,sub-gridscale turbulence kinetic energy, energy dissipation, etc at selected heights AGL<br> <br> 2D Diagnosed variables:<br> Ceiling height, visibility, precip rate, accumulated precip, precipitable water, vertically- integrated condensed water, downwelling shortwave and longwave radiation at surface, sensible and latent heat flux, 10 m U and V, 2 m T and specific humidity<br> </p>
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