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103 results for “WRF Simulations”
Irrigation-induced potential evapotranspiration decrease in the Heihe River Basin, Northwest China, as simulated by the WRF model
<p>This dataset is for the plots in the article titled "Irrigation-induced potential evapotranspiration decrease in the Heihe River Basin, Northwest China, as simulated by the WRF model", which was published by Journal of Geophysical Research: Atmospheres. There are totally nine files in the ".mat" format for Matlab. The nine data files are corresponding to nine Figures in the article.</p>
High resolution WRF simulation of Hurricane Sandy (2012) wind during landfall
<p>A 96-hour high-resolution simulation of Hurricane Sandy was conducted using the Advanced Research version 3.3.1 of the Weather Research and Forecasting (WRF) model initialized at 1200 UTC 26 October 2012 (Johnsen et al., 2013) and using a horizontal resolution of 500 m. Domain size was 2,660x2,500 km with 150 vertical layers. The Yonsei University planetary boundary layer (PBL) scheme, the Noah land model, and the MM5 Monin-Obukhov similarity theory surface layer model were used. Cloud physics was modeled using WSM6 6-class microphysics with graupel. Convection parameterization was not used for this high-spatial-resolution simulation. National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analyses were used for initialization and boundary conditions, with the latter updated every 6 hours.</p> <p>Data herein is a landfall-regime subset (Schiavone et al., 2016) of the full simulation. The spatial domain is 500x500 km containing the 50 lowest layers, with a time domain that spans the 12-hour period beginning at1200 UTC 29 October 2012 and with 3-hour time steps. Format is NetCDF containing detailed metadata. Three-dimensional meteorological field variables include the 3 wind components, potential temperature, water vapor mixing ratio, geopotential, and atmospheric pressure. Two-dimensional variables include horizontal wind components at 10 m AGL, potential temperature and water vapor mixing ratio at 2 m AGL, atmospheric pressure at the surface, terrain height, and the Coriolis sine latitude term, which is required to calculate potential vorticity.</p> <p>These WRF simulation data were used, along with WSR-88D Doppler radar data and surface wind observations, to demonstrate that roll vortices occurred in the atmospheric boundary layer over the landfall region during Hurricane Sandy's landfall period (Schiavone et al., 2020).</p>
WRF-Hydro simulated hydrographs for Jan-1989 and Nov-1994 extreme events (Cyprus)
<p>WRF-Hydro simulation results for two extreme events occurred in Cyprus in January 1989 and November 1994. For specific information on simulation setup and study area, please refer to:</p> <p>Camera, C., Bruggeman A., Zittis, G., Sofokleous, I., Arnault, J., 2020. Simulation of extreme rainfall and streamflow events in small Mediterranean watersheds with a one-way coupled atmospheric-hydrologic modelling system. NHESSD, https://doi.org/10.5194/nhess-2020-43.</p>
Compound extremes WRF simulations
<p>All the data are available in the daily timestep. The extension with irrigation-on and irrigation-off represent two different simulations.<br> All variable details;<br> SLP- Sea Level Pressure<br> SKINTEMP- Land Surface Temperature<br> T2- Air Temperature<br> LHF - Latent Heat Flux<br> SHF - Sensible Heat Flux<br> LHFSHF - Latent Heat Flux + Sensible Heat Flux<br> SH - Specific Humidity<br> PBLH - Planetary Boundary Layer Height<br> SMOIS - Soil Moisture (0-60 cm)<br> VPD - Vapour Pressure Deficit<br> vq_Integrated uq_Integrated - u and v Component of Vertically Integrated Moisture</p>
Important contribution of N2O5 hydrolysis to the daytime nitrate in Xi'an, China during haze periods: isotopic analysis and WRF-Chem model simulation
<p>To quantify the contributions of major formation pathways to nitrate, a field observation, coupling with a WRF-Chem model simulation, was conducted in Xi’an, an inland megacity of China. Here is the dataset of ions, stable isotope compositions of nitrogen and oxygen of nitrate, T, RH and the results simulated by WRF-Chem model.</p>
WRF-Chem output- concentrations for the 4 simulations: reference, urbanization, extension of agricultural areas and more urban parks
<p>We use the WRF-Chem air-quality model with an urban canopy scheme to investigate how land use (urban, agriculture, parks) affects the urban climate and chemical processes (dry deposition, biogenic emissions), resulting in changes in air quality for scenarios proposed by the Urban Master Plan of the Metropolitan Area of Barcelona. We selected a heatwave period, 4th-7th July 2015, with maximum temperatures reaching 40 °C in the interior of the AMB and 35 °C on the coast. Here we provide averaged model output for the heatwave period for the different pollutants, surface temperature, wind speed, PBLH, deposition, and biogenic emissions under different urban scenarios: reference (REF), urbanization (URB), extension of agriculture (AGR), and increase in urban parks (PARK).<br><br>The results for a period before the heatwave (1-3 July 2015), with temperatures 3-4 degrees lower than during the heatwave, are also provided. <br><br>Land-use and irrigation is also provided for each scenaio. </p>
Simulations of FLEXPART-WRF used for testing TRansport Of water VApor (TROVA) software (Part II)
<p>Necessary data for carrying out the tests using TRansport Of water VApor (TROVA) software for backward in time. The TROVA software, was developed in Python and Fortran for the study of moisture sources and sinks. <span><span><span>In addition, the Python code is provided for the representation of the results.</span></span></span></p>
WRF simulation data
<p>We have investigated the impact of varying physics parameterization schemes on the real-time short-term forecasts for the recent typhoon cases that affected South Korea. <br> These files contain the main variables in WRF output data for 3-day forecasts of typhoons Trami (init:2018092700UTC) and Faxai (init:2019090600UTC).<br> The domain spatial resolutions are 12X12km (D01) and 1.33X1.33km (D03). The data format is NetCDF containing detailed metadata. <br> Three-dimensional meteorological field variables include the 10m wind components, accumulated rain, sea-level pressure, latitude, and longitude.<br> Four-dimensional meteorological field variables include the U, V, T, Qc, Qr, Qi, Qs, and Qg.<br> </p>
Data for Cloud resolving WRF simulations of precipitation and soil moisture over the central Tibetan Plateau: an assessment of various physics options
<p>This dataset accompanies the submitted paper in the Earth and Space Science:Cloud resolving WRF simulations of precipitation and soil moisture over the central Tibetan Plateau: an assessment of various physics options.</p>
radar observations and WRF simulations of Typhoon Yagi (2024)
<p>This data set contains radar observations and WRF modal simulations (with Thompson and WDM6 microphysics schemes) of super Typhoon Yagi (2024).</p>
Storm-scale and fine-scale boundary layer structures of tropical cyclones simulated with the WRF-LES framework
<p>The numerical simulations were carried out on the Tianhe Supercomputer, China. The TCBL data used in this study are uploaded here. Due to the large number, the original simulation data are available on request (liuqy@cma.gov.cn or liguangwu@fudan.edu.cn).</p>
WRF-Noah/Alpine3D simulations for 2018-2021 snow seasons in Italian Central Apennines
<p>This dataset contains the results of two numerical simulations over Italian Central Apennines at 3 km resolution for the three snow seasons 2018/19, 2019/20 and 2020/21. The file wrf-noah_2018-2021.nc contains the WRF-Noah model output, while the file wrf-alpine3d_2018-2021.nc contains the WRF-Alpine3D model output.</p>
Scenario Configurations for Simulating Organic Aerosol in Delhi using WRF-Chem and a VBS Approach
<p>Parameter configuration files for a study into the sensitivity of model predictions (in this case WRF-Chem) of organic aerosol mass loadings, and composition, to organic aerosol production processes.</p> <p>The production processes for both anthropogenic (ANTH) and biomass burning (BB) generated organic aerosols are investigated. 5 production processes are perturbed for each, making a total of 10 parameters for the whole study.</p> <p>The production processes are:</p> <ol> <li>VBS aging rate (VBS_AGERATE): the reaction rate of VBS compounds with OH. Expressed as a reaction rate in cm<sup>3</sup> molec.<sup>-1</sup> s<sup>-1</sup>.</li> <li>SVOC volatility distribution (SVOC_VOLDIST): expressed in terms of an equivalent age (dimensionless between 0-1). This is translated using a simple aging model into a volatility distribution for the emitted VBS compounds.</li> <li>SVOC oxidation rate (SVOC_OXRATE): the degree of oxidation that occurs with, or is induced by, each reaction with an OH molecule. Range is 0.075 (one extra oxygen atom) to 0.45 (six extra oxygen atoms).</li> <li>IVOC scaling (IVOC_SC): scaling factor for emissions of IVOC's alongside the SVOC's. Initial IVOC emitted amount is taken to be x1.5 the non-volatile OA mass in the emission inventory. This scaling factor, ranging from 0 to 3, modifies that initial emitted amount, to give the final IVOC fraction to add.</li> <li>SVOC scaling (SVOC_SC): scaling factor for emissions of SVOCs. This applied to the volatility distribution generated from the SVOC volatility distribution. For anthropogenic emissions this ranges from 0.1 to 4. For biomass burning emissions this ranges from 0.5 to 4.</li> </ol> <p>SVOC_VOLDIST, IVOC_SC, and SVOC_SC combine to give the VBS_FRAC_[X] fractional volatility distributions. These volatility bins start at Ci*=-2 , and increase decadally to Ci*=6.</p> <p>The template namelist into which these parameters are inserted is included too. This is for a modified version of WRF-Chem 3.8.1 - it will not work with the standard WRF-Chem model.</p> <p> </p>
Data used to simulations in the GMD manuscript "Inter-comparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1-CMAQ v5.3.1, WRF-Chem v4.1.1 and WRF v3.7.1-CHIMERE v2020r1) in eastern China"
<p>This dataset contains input data of simulations by WRF-CMAQ, WRF-Chem and WRF-CHIMERE in the GMD manuscript "Inter-comparison of multiple two-way coupled meteorology and air quality models (WRF v4.1.1-CMAQ v5.3.1, WRF-Chem v4.1.1 and WRF v3.7.1-CHIMERE v2020r1) in eastern China", as follows:</p> <p>1. WRF-CMAQ input data including emission, ICs and lateral BCs of meteorology and air quality:</p> <p>YYYYMM.zip represents the input data for each month for simulations. Due to the large size of the compressed file containing input data each month, there may be interruptions when uploading it to Zenodo. Therefore, we will split each compressed file into 50MB. If users want to browse the file, they can download the segmented files, and then merge them into the YYYYMM.zip file using the Linux command line "unzip 'YYYYMM.zip.*' -d combined"</p>
Part 2 of simulation output for WRF-Chem with enabling ARI and ACI
<p>Part 2 of simulation output for WRF-Chem in eastern China with enabling aerosol-radiation interactions (ARI) and aerosol-cloud interactions (ACI) during 2017.</p>
Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during January-March 2017
<p>Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during January-March 2017 including meteorology and air quality, which are in wrfout_YYYY-MM-DD_00_00_00 file on each day during January-March 2017. The file 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, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during October-December 2017
<p>Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during October-December 2017 including meteorology and air quality, which are in wrfout_YYYY-MM-DD_00_00_00 file on each day during October-December 2017. The file contains these variables:</p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.
Simulation results from WRF-Chem without aerosol feedbacks in eastern China for April-June 2017
<p>Simulation results from WRF-Chem without aerosol feedbacks in eastern China for April-June 2017 including meteorology and air quality,which are in wrfout_YYYY-MM-DD_00_00_00 file on each day for April-June 2017. The file 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, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during April-June 2017
<p>Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during April-June 2017 including meteorology and air quality, which are in wrfout_YYYY-MM-DD_00_00_00 file on each day during April-June 2017. The file 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, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during July-September 2017
<p>Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during July-September 2017 including meteorology and air quality, which are in wrfout_YYYY-MM-DD_00_00_00 file on each day during July-September 2017. The file 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, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
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