WRF Model Output Research Articles

Evaluation of global reanalysis winds and high‐resolution regional model outputs with the 205 MHz stratosphere–troposphere wind profiler radar observations

AbstractA stratosphere–troposphere (ST) wind profiler radar operating at a high VHF range (205 MHz) installed at Cochin (10.03°N, 76.33°E), India, provides high‐resolution winds in time and altitude extending from 315 m to 20 km. We evaluated the horizontal and vertical winds obtained from atmospheric global reanalyses (ERA5, ERA‐Interim, MERRA‐2 and NCEP) data and the high‐resolution regional model (WRF) output winds with the ST radar (STR) wind observations at Cochin. The data for one whole year, from 1 August 2018 to 31 July 2019, for 0600 UTC and 1200 UTC were used. Wind data appraisal has been carried out at 24 levels from 315 m to 18.5 km altitude for the reanalyses datasets and 29 levels for model‐simulated winds in different seasons. Vertical profiles of horizontal winds from reanalysis and model‐simulated data somewhat catch the major changes observed from STR. The zonal winds match very well with the STR, whereas meridional winds show moderate similarity. Higher correlations in zonal winds are found during the summer monsoon, whereas meridional winds show apparent likeness during winter. The ERA5, ERA‐Interim, and model‐simulated winds have better agreement with the STR winds. Observed vertical winds from STR displays large fluctuations, while the estimated vertical winds in reanalysis are highly smoothed. Vertical profiles of vertical winds from the reanalysis datasets are not uniform. The reliability of vertical winds in reanalysis and WRF model output values are dubious compared to that of the directly observed winds from STR. The study indicates that improved quality of vertical and meridional winds in reanalysis data is needed by assimilating directly observed data from the available advanced facilities.

Investigating the Transition from Elevated Multicellular Convection to Surface-Based Supercells during the Tornado Outbreak of 24 August 2016 Using a WRF Model Simulation

Abstract On 24 August 2016, a tornado outbreak impacted Indiana, Ohio, and Ontario with 26 confirmed tornadoes. Elevated multicellular convection developed into surface-based supercells that produced several tornadoes, particularly near a differential heating boundary. This convective mode transition is of particular interest owing to its relatively rare occurrence. A WRF Model simulation accurately captures the environment and storm evolution during this outbreak. Trajectory analyses indicate that the multicellular updrafts were initially elevated. Since nearly all of the vertical wind shear was confined to the lowest 1 km, significant rotation did not develop via tilting of horizontal vorticity until the storms began ingesting near-surface air. Near-surface vertical wind shear decreased outside of cloud cover owing to vertical mixing, while it was preserved under the anvil, allowing for large values of 0–1-km storm-relative helicity to persist north of a differential heating boundary. Analysis of the perturbation pressure field from the WRF Model output indicates that the development of relatively large nonlinear vertical perturbation pressure gradients coincided with when near-surface air began to enter the updrafts, resulting in upward accelerations in the lowest 2 km, below the level of maximum rotation. In strengthening updrafts, upward-directed buoyancy perturbation pressure accelerations may have offset the downward-directed nonlinear perturbation pressure accelerations above the level of maximum rotation, allowing the updrafts to intensify further.

A predictive study of heat wave characteristics and their spatio-temporal trends in climatic zones of Nigeria

Heat waves (HWs) have always been the silent natural disaster but the most impactful, especially concerning health and agriculture. A crucial question is being asked after the evidence has shown increases in the climate extreme events especially the temperature: how will the future climate conditions be? The present investigation examines and analyzes the future occurrence and trend of HWs in the five climatic zones of Nigeria. WRF model output extracted from CORDEX-Africa for the period 2018–2100 was compiled using maximum and minimum temperatures under RCP4.5 and RCP8.5. Different HW characteristics were studied: the heat wave number, the duration, the frequency, the amplitude and the magnitude exploiting four different definitions, the temperature based 90th percentile thresholds (TN90 and TX90), the Excess Heat Factor (EHF) and the Heat Wave Magnitude Index daily (HWMId). The prediction under the two scenarios RCP4.5 and RCP8.5 has shown a spatial increase in the frequency and magnitude of HWs during different periods. In the 2050s, there will be a spatial increase and also an increase in the duration of HWs in the study area. The HWMId revealed Ultra extreme HWs when the Coastal zone will be having Super extreme HWs. The RCP8.5 revealed more dramatic and dreadful HWs from 2073. The trend showed significant increasing trends in the major parts of the country.

On the Importance of a Consistent Treatment of Prognostic Moisture Variables between Convective and Microphysical Parameterizations

Abstract Analysis of WRF Model output from experiments using two double-moment microphysics schemes is carried out to demonstrate that there can be an inconsistency between the predicted mass and number concentrations when a single-moment convective parameterization is used together with a double-moment microphysics scheme. This inconsistency may arise because the grid-scale and subgrid-scale cloud schemes generally apply different levels of complexity to the parameterized microphysical processes. In particular, when a multimoment formulation is used in the microphysics scheme and other physical parameterizations modify only the mass-related moment while the values of the second (or higher) moment for individual hydrometeors remain unchanged, an unintended modification of the particle size distribution occurs. Simulated radar reflectivity is shown to be a valuable tool in diagnosing this inconsistency. In addition, potential ways to minimize the problem are explored by including number concentration calculations in the cumulus parameterization that are consistent with the assumptions of hydrometeor sizes in the microphysics parameterization. The results of this study indicate that it is physically preferable to unify microphysical assumptions between the grid-resolved and subgrid cloud parameterization schemes in weather and climate simulation models.

Ensemble using different Planetary Boundary Layer schemes in WRF model for wind speed and direction prediction over Apulia region

Abstract. The Weather Research and Forecasting mesoscale model (WRF) was used to simulate hourly 10 m wind speed and direction over the city of Taranto, Apulia region (south-eastern Italy). This area is characterized by a large industrial complex including the largest European steel plant and is subject to a Regional Air Quality Recovery Plan. This plan constrains industries in the area to reduce by 10 % the mean daily emissions by diffuse and point sources during specific meteorological conditions named wind days. According to the Recovery Plan, the Regional Environmental Agency ARPA-PUGLIA is responsible for forecasting these specific meteorological conditions with 72 h in advance and possibly issue the early warning. In particular, an accurate wind simulation is required. Unfortunately, numerical weather prediction models suffer from errors, especially for what concerns near-surface fields. These errors depend primarily on uncertainties in the initial and boundary conditions provided by global models and secondly on the model formulation, in particular the physical parametrizations used to represent processes such as turbulence, radiation exchange, cumulus and microphysics. In our work, we tried to compensate for the latter limitation by using different Planetary Boundary Layer (PBL) parameterization schemes. Five combinations of PBL and Surface Layer (SL) schemes were considered. Simulations are implemented in a real-time configuration since our intention is to analyze the same configuration implemented by ARPA-PUGLIA for operational runs; the validation is focused over a time range extending from 49 to 72 h with hourly time resolution. The assessment of the performance was computed by comparing the WRF model output with ground data measured at a weather monitoring station in Taranto, near the steel plant. After the analysis of the simulations performed with different PBL schemes, both simple (e.g. average) and more complex post-processing methods (e.g. weighted average, linear and nonlinear regression, and artificial neural network) are adopted to improve the performances with respect to the output of each single setup. The neural network approach comes out as the most promising method.

Validación de simulaciones de los modelos CALMET/CALPUFF en el entorno de una gran chimenea de central térmica

CALMET/CALPUFF modeling system is frequently used in the study of atmospheric processes and pollution, and several validation tests were performed until now; nevertheless, most of them were based on experiments with a large compilation of surface and aloft meteorological measurements, rarely available. At the same time, the use of a large operational smokestack as tracer/pollutant source is not usual. In this work, first CALMET meteorological diagnostic model is nested to WRF meteorological prognostic model simulations (3x3 km2 horizontal resolution) over a complex terrain and coastal domain at NW Spain, covering 100x100 km2, with a coal-fired power plant emitting SO2. Simulations were performed during three different periods when SO2 hourly glc peaks were observed. NCEP reanalysis were applied as initial and boundary conditions. Yong Sei University-Pleim-Chang (YSU) PBL scheme was selected in the WRF model to provide the best input to three different CALMET horizontal resolutions, 1x1 km2, 0.5x0.5 km2, and 0.2x0.2 km2. The best results, very similar between them, were achieved using the last two resolutions; therefore, the 0.5x0.5 km2 resolution was selected to test different CALMET meteorological inputs, using several combinations of WRF outputs and/or surface and upper-air measurements available in the simulation domain. With respect to meteorological aloft models output, CALMET PBL depth estimations are very similar to PBL depth estimations using upper-air measurements (rawinsondes), and significantly better than WRF PBL depth results. Regarding surface models surface output, the available meteorological sites were divided in two groups, one to provide meteorological input to CALMET (when applied), and another to models validation. Comparing WRF and CALMET outputs against surface measurements (from sites for models validation) the lowest RMSE was achieved using as CALMET input dataset WRF output combined with surface measurements (from sites for CALMET model input). Following, CALPUFF model was applied to simulate the local atmospheric diffusion of SO2 (as an inert tracer) from a large power plant smokestack (with four parallel independent liners), considering two different stack configurations (one single point source as a summa of four liners vs. one point source per liner) and two different CALMET meteorological simulations (using as input dataset only the WRF model output vs. only surface and upper-air meteorological measurements). Comparison of those CALPUFF simulations results against the hourly average ground level concentration (glc) measurements shows that the best model performance was obtained by using only WRF model output as CALMET input; also, better glc results are obtained considering one point source per liner in CALPUFF simulations.

Simulation of plume dispersion using different stack configurations and meteorological inputs

The application of CALMET/CALPUFF modelling system is well known, and several validation tests were performed until now; however, most of them were based on experiments with a large compilation of surface and aloft meteorological measurements, not always available. Also, the use of an operational large smokestack as tracer source is not so usual. In this work, CALPUFF model is applied to simulate the local dispersion of SO 2 (as a tracer) from the large smokestack (with four parallel liners) of a coal-fired power plant emitting SO 2 (as a tracer), considering both different stack configurations (one single point source vs. one point source per liner) and meteorological inputs (WRF model output vs. measurements). Comparison of CALPUFF results against glc measurements along three different periods shows that the best model performance was obtained by using WRF model output; better results, but not so significant, are obtained considering one point source per liner.

Surface energy partitioning over four dominant vegetation types across the United States in a coupled regional climate model (Weather Research and Forecasting Model 3–Community Land Model 3.5)

Accurate representation of surface energy partitioning is crucial for studying land surface processes and the climatic influence of land cover and land use change using coupled climate‐land surface models. A critical question for these models, especially for newly coupled ones, is whether they can adequately distinguish differences in surface energy partitioning among different vegetation types. We evaluated 3 years (2004–2006) of surface energy partitioning and surface climate over four dominant vegetation types (cropland, grassland, needleleaf evergreen forest, and broadleaf deciduous forest) across the United States in a recently coupled regional climate model, Weather Research and Forecasting Model 3–Community Land Model 3.5 (WRF3‐CLM3.5), by comparing model output to observations (AmeriFlux, Clouds and the Earth's Radiant Energy System (CERES), and Parameter‐elevation Regressions on Independent Slopes Model (PRISM) data) and to standard WRF model output. We found that WRF3‐CLM3.5 can capture the seasonal pattern in energy partitioning for needleleaf evergreen forest but needs improvements in cropland, grassland, and broadleaf deciduous forest. Correcting the leaf area index representation for cropland and grassland could immediately improve the simulation of latent heat flux and hence the energy partitioning. Adding an irrigation scheme is especially important for cropland in the Midwest, where the strongly coupled soil moisture and precipitation can form a positive feedback that reduces latent heat flux and increases the warm bias. For deciduous forest, the simulated excess latent heat flux before leaf emergence is mainly from soil evaporation, requiring further improvement in the soil evaporation scheme. Finally, the domain‐wide overestimated net radiation contributes to positive biases in sensible, latent, and ground heat flux, as well as surface temperature. The standard WRF simulation has a similar warm bias, implicating errors in modules other than the land surface code. A sensitivity test suggests that improved simulation of downward solar radiation could reduce the energy flux and temperature biases. After adding irrigation process and correcting the leaf area index, WRF3‐CLM3.5 appears reliable for studying conversions between natural grassland and irrigated cropland and between needleleaf evergreen forest and grassland.

Instability indices and forecasting thunderstorms: the case of 30 April 2009

Abstract. In this paper, one meteorological case study for two Iranian airports are presented. Attempts have been made to study the predefined threshold amounts of some instability indices such as vertical velocity and relative humidity. Two important output variables from a numerical weather prediction model have been used to survey thunderstorms. The climatological state of thunder days in Iran has been determined to aid in choosing the airports for the case studies. The synoptic pattern, atmospheric thermodynamics and output from a numerical weather prediction model have been studied to evaluate the occurrence of storms and to verify the threshold instability indices that are based on Gordon and Albert (2000) and Miller (1972). Using data from the Statistics and Data Center of the Iran Meteorological Organization, 195 synoptic stations were used to study the climatological pattern of thunderstorm days in Iran during a 15-yr period (1991–2005). Synoptic weather maps and thermodynamic diagrams have been drawn using data from synoptic stations and radiosonde data. A 15-km resolution version of the WRF numerical model has been implemented for the Middle East region with the assistance of global data from University Corporation for Atmospheric Research (UCAR). The Tabriz airport weather station has been selected for further study due to its high frequency of thunderstorms (more than 35 thunderstorm days per year) and the existence of an upper air station. Despite the fact that storms occur less often at the Tehran weather station, the station has been chosen as the second case study site due to its large amount of air traffic. Using these two case studies (Tehran at 00:00 UTC, 31 April 2009 and Tabriz at 12:00 UTC, 31 April 2009), the results of this research show that the threshold amounts of 30 °C for KI, −2 °C for LI and −3 °C for SI suggests the occurrence and non-occurrence of thunderstorms at the Tehran and Tabriz stations, respectively. The WRF model output of vertical velocity and relative humidity are the two most important indices for examining storm occurrence, and they have a numerical threshold of 1 m s−1 and 80%, respectively. These results are comparable to other studies that have examined thunderstorm occurrence.

Evaluation of WRF Model Output for Severe Weather Forecasting from the 2008 NOAA Hazardous Weather Testbed Spring Experiment

Abstract This study assesses forecasts of the preconvective and near-storm environments from the convection-allowing models run for the 2008 National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) spring experiment. Evaluating the performance of convection-allowing models (CAMs) is important for encouraging their appropriate use and development for both research and operations. Systematic errors in the CAM forecasts included a cold bias in mean 2-m and 850-hPa temperatures over most of the United States and smaller than observed vertical wind shear and 850-hPa moisture over the high plains. The placement of airmass boundaries was similar in forecasts from the CAMs and the operational North American Mesoscale (NAM) model that provided the initial and boundary conditions. This correspondence contributed to similar characteristics for spatial and temporal mean error patterns. However, substantial errors were found in the CAM forecasts away from airmass boundaries. The result is that the deterministic CAMs do not predict the environment as well as the NAM. It is suggested that parameterized processes used at convection-allowing grid lengths, particularly in the boundary layer, may be contributing to these errors. It is also shown that mean forecasts from an ensemble of CAMs were substantially more accurate than forecasts from deterministic CAMs. If the improvement seen in the CAM forecasts when going from a deterministic framework to an ensemble framework is comparable to improvements in mesoscale model forecasts when going from a deterministic to an ensemble framework, then an ensemble of mesoscale model forecasts could predict the environment even better than an ensemble of CAMs. Therefore, it is suggested that the combination of mesoscale (convection parameterizing) and CAM configurations is an appropriate avenue to explore for optimizing the use of limited computer resources for severe weather forecasting applications.

Doppler lidar observations of sensible heat flux and intercomparisons with a ground-based energy balance station and WRF model output

This is an open access article - Copyright @ 2009 E. Schweizerbart'sche Verlagsbuchhandlung