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248 results for “wrf”
WRF Output for 1 km Simulation of Spiral Gravity Waves with 25 Levels
<p>WRF Output for 1 km Simulation of Spiral Gravity Waves with 25 Levels</p>
WRF Output for 1.5 km Simulation of Spiral Gravity Waves
<p>WRF Output for 1.5 km Simulation of Spiral Gravity Waves</p>
WRF Output for 1 km Simulation of Spiral Gravity Waves
<p>WRF Output for 1 km Simulation of Spiral Gravity Waves, gzipped.</p>
Code for GMD publication - Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018
<p>In this repository, we include the source codes for WRF microphysics parameterization used in the GMD publication "Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018."</p> <p>The four 2-moment bulk microphysical parameterization codes, WDM6, WDM7, Thompson, and Morrison, are divided into 3 WDM, Thompson, and Morrison codes, and each code has been modified so that detailed microphysical processes can be checked in wrfout.</p> <p>The WDM6 and WDM7 schemes include numerical errors for ice microphysical parameterization (Kim and lim, 2021) and for cloud evaporation and melting processes (Lei et al., 2020).</p> <p>Namelist files shows the namelist.input for each case.</p> <p> </p> <p> </p>
Code for JAMES publication - Implementation of prognostic cloud ice number concentrations for the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme.
<p>In this repository, we include the source codes for WRF microphysics parameterization used in the JAMES publication "Implementation of prognostic cloud ice number concentrations for the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme"</p> <p> </p> <p>The revised WDM6 code, which predicts the number concentration of cloud ice, and the original WDM6 code are uploaded. Each code is modified so that detailed microphysical processes can be found in wrfout.</p> <p> </p> <p>Namelist files shows the namelist.input for each case.</p> <p> </p> <p>Scripts file for figures in this manuscript are uploaded</p>
WRF simulation data
<p>We have investigated the impact of the (non)scale-aware cumulus parameterization scheme on the simulation for heavy rainfall events in South Korea. <br> These files contian the WRF simulation data of main variables, which is used in this paper. The spatial domain is 4x4 km (D03) and 1.33x1.33km (D04), with a time domain that spans the 10 hours period beginning at 1800 UTC 15 July 2017 and with 1-hour time steps. Format is NetCDF containing detailed metadata. Three-dimensional meteorological field variables include the 2 wind components (i.e., x- and y- directions), water vapor mixing ratio, and temperature. Two-dimensional variables include convective precipitation and non-convective precipitation.</p>
WRF Simulation Files
<p>All WRF and WPS files (compiled fortran files and namelists) for a convection-permitting simulation performed on a tropical cyclone-milatitude waveguide interaction involving Irma in 2017. </p>
Effects of convective mergers on the evolution of microphysical and electrical activity in a severe squall line simulated by WRF coupled with explicit electrification scheme
<p>These are important data supporting the conclusion of the paper are available in the main text.The STORM973 dataset including BLNET data and radar data are provided here.Some of the E-WRF outputs are also provided here. The corresponding scripts are based on NCL (version 6.6.2.).</p>
WRF model configuration and data used for the NHESS manuscript "Droughts in Germany: Performance of Regional Climate Models in reproducing observed characteristics"
<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: monthly values for the time period 1980-2009 of precipitation, maximum and minimum temperature (needed for the SPEI calculation) 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> <p> </p>
WRF simulation of atmospheric pressure and temperature around flight 08 of the SOUTHTRAC Campaign
<p>Atmospheric pressure (p) and temperature (T) from numerical model WRF every 15 min and at 0.5 / 3 km vertical / horizontal resolution up to 60 km height are included. The whole time and geographical area of the flight are covered. Zipped netcdf format.</p>
WRF simulation of atmospheric velocity components around flight 08 of the SOUTHTRAC Campaign
<p>The three atmospheric velocity components (zonal u, meridional v, vertical w) from numerical model WRF every 15 min and at 0.5 / 3 km vertical / horizontal resolution up to 60 km height are included. The whole time and geographical area of the flight are covered. Zipped netcdf format.</p>
WRF-Chem ozone tagging output
<p>Chemical reactions file (mozart_tag.eqn) for an ozone tagging mechanism within the WRF-Chem model used to track tropospheric ozone from European NOx sources.</p>
WRF-Chem ozone tagging output
<p>Simulation for a European domain from May to August 2015 using a tagged ozone mechanism based on MOZART-4 chemistry.</p>
Selected data analysed in the JGR Atmosphere manuscript " An application of the maximum entropy production method in the WRF Noah land surface model"
<p>The control experiment (hereafter WRF-CTL) and the MEP experiment (hereafter WRF-MEP) simulations results interpolated to the observation stations. The simulation period was 1 June to 31 August 2015 with 30 hours from 12:00 UTC (20:00 Beijing time (BJT)) each day, and the latest 24-hour outputs are provided.</p>
WRF-Tag Data by Navale and Karthikeyan 2022
<p>Data from WRF-Tag model for Paper #2022WR032605 (Navale and Karthikeyan).</p>
Input files for WRF simulations Across the the iCMV
<p>The west-east terrain cross-section along ~150km of the northern part of Israel has a coastal-plain—mountain—valley structure; hereafter denoted iCMV. The boundary layer height (BLH) evolution mechanism across the iCMV has not yet been fully understood. We use Weather Research and Forecasting (WRF) simulations and ceilometer measurements to decipher the iCMV BLH evolution mechanism during the late summertime period of 5-14 September 2017, where the daily maximum BLH at the mountainous city of Jerusalem (JrM; 800m above sea-level) varies by ~1000m. We first verify the BLH, simulated by 5 model configurations (with 4 different BL schemes). The RMSE for the 3 best configurations are around 160 and 200m for the coastal and JrM areas, respectively. An analysis of the simulated daily BL evolution reveals a general mechanism. In the early morning, the up-slope flows and synoptic forcing interact to induce a surface flow convergence (SFC) zone. During a westerly (easterly) synoptic flow, the SFC is induced east (west) of JrM. Assisted by the inland propagating sea breeze front, the SFC is advected eastwards during the afternoon, until it collapses at the valley bottom. The SFC zone is accompanied by a <a name="_Hlk110946754"></a>substantial positive vertical-wind column and a locally-elevated BLH. The more western the morning-time SFC is, the more likely the elevated BLH will pass during midday through JrM, with a higher daily maximum BLH. The exact dependence of the BLH evolution and the associated temperature and humidity variations upon the synoptic regime require further study.</p>
Summer mesoscale convective systems in convection-permitting simulation using WRF over East China
<p>Mesoscale convective systems (MCSs) are active in East China during the summer, causing significant precipitation and extreme weather. Increasing MCS frequency and intensity highlight the need for better simulation and forecasting. Traditional global and regional models with coarse resolution unable to explicitly resolve convection fail to represent MCSs and their precipitation accurately. This study conducted a 22-year (2000--2021) JJA simulation at a convection-permitting resolution (4km) using the WRF model (WRF-CPM) over East China. The data generated and the code used to analyze are uploaded here.</p>
Code for GMD publication - Introducing Graupel Density Prediction in Weather Research and Forecasting (WRF) Double-Moment 6-Class (WDM6) Microphysics and Evaluation of the Modified Scheme During the ICE-POP Field Campaign
<p>Code for GMD publication - <span>Introducing Graupel Density Prediction in Weather Research and Forecasting (WRF) Double-Moment 6-Class (WDM6) Microphysics and Evaluation of the Modified Scheme During the ICE-POP Field Campaign</span></p> <p>In this repository, we include the source codes for WRF microphysics parameterization used in the GMD publication "Simulated Prognostic approach of graupel density in a bulk-type cloud microphysics scheme and evaluation during the ICE-POP field campaign."</p> <p>The revised WDM6 code, which predicts the graupel density and the original WDM6 code are uploaded. </p> <p>Each code is modified so that detailed microphysical processes can be found in wrfout.</p> <p>Namelist files shows the namelist.input for each case.</p> <p>Furthermore, scripts for figures in the manuscript are included, along with wrfout files.</p>
WRF Model Output for a Simulation of Hurricane Laura (2020), 2.25km grid, 2020-08-26-00Z through 2020-08-26-10Z
<p>This is WRF model output for a simulation of Hurricane Laura (2020). The tar file contains gzipped netcdf files each with 6 model outputs at 20 minute intervals.</p>
WRF Model Output for a Simulation of Hurricane Laura (2020), 2.25 km grid, 2020-08-26-12Z to 2020-08-26-22Z
<p>This is WRF model output for a simulation of Hurricane Laura (2020). The tar file contains gzipped netcdf files each with 6 model outputs at 20 minute intervals.</p>
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