Advanced Research WRF Research Articles

Evaluating Ice Phase Microphysics in the Simulation of a Snowstorm Over Northern China

AbstractThe complexity of ice particles in the atmosphere makes it difficult to model microphysical growth processes accurately. In this study, we simulated a snowfall case over Northern China Plain using two different microphysics schemes, that is, Thompson and Morrison schemes, in the Advanced Research WRF (Weather Research and Forecasting) model. Both schemes are able to reproduce the event, albeit with a slightly weaker precipitation compared with the surface observation. However, the radar reflectivity factor in Morrison simulation is higher than the radar observation to ∼10 dBZ. Further analysis reveals that such stronger radar reflectivity in the Morrison simulation might be caused by larger collection efficiency, which would lead to more active self‐aggregation process in prediction of snow number concentration and then larger snow particle size. Sensitivity tests show that using an alternative formula of collection efficiency produces smaller radar reflectivity that is in better agreement with observations. This study highlights the accurate representation of self‐aggregation process and underscores the needs of further improvement of ice microphysics schemes for the better snowfall simulations.

Indirect Effects of Binary Typhoons on an Extreme Rainfall Event in Henan Province, China From 19 to 21 July 2021. 3. Sensitivities to Microphysics Schemes

AbstractPrevious numerical studies have focused on the direct impact of microphysics schemes on multiscale atmospheric systems that produce rainfall. However, the indirect impact of microphysics schemes on the key large‐scale circulation around areas of extreme rainfall has not yet been examined systematically. We used the ARW‐WRF (Advanced Research WRF (Weather Research and Forecasting) Model) to simulate the extreme rainfall event in Henan province, China from 19 to 21 July 2021. Experiments were conducted to investigate the sensitivity of the simulation to the three popular double‐moment microphysics parameterizations: the Thompson, Morrison and WDM6 (WRF Double‐Moment 6‐Class Microphysics Schemes). We found significant sensitivity to the microphysics parameterization, with the maximum precipitation varying by up to 400 mm and the area‐averaged precipitation by 33 mm. The Thompson and Morrison microphysics schemes produced the largest amount of precipitation, whereas the WDM6 scheme produced the smallest amount of precipitation. The simulated southerly flow varied substantially between the different microphysics schemes. This is due to the ability of the microphysics schemes to produce latent heat, which enhances the southerly flow, leading to more intense precipitation. The higher the parameterized latent heat, the stronger and more obvious the southerly flow over southern Henan province, with the WDM6 scheme simulating a much weaker southerly flow and the Thompson scheme producing the strongest southerly flow. These results indicate that the indirect effects on the key circulation patterns can be just as sensitive to the formulation of the microphysics scheme as the direct effects on extreme rainfall. These results may help to improve the prediction of extreme rainfall events.

Development of an Automated Algorithm to Detect and Track Developing and Mesoscale Convective Systems

An objective algorithm is developed which is capable of identifying convective cloud clusters (CCCs) at the point of initiation, tracking any selected of all identified CCCs to maturity (MCS) and then to the point of dissipation and thereby accumulating some physical, morphological and radiative properties. The technique is able to account for periods of growth, propagating, merging, splitting and decaying, which take place during the lifetime of an individual cluster. The algorithm was tested using brightness temperature from merged infrared images of at least eight reporting geostationary satellites or channels at a spatial resolution of 4 Km and temporal resolutions of 30 minutes. The model data used is Weather Research and Forecasting (WRF) with the Advanced Research WRF (ARW) core simulated using the same spatial and temporal resolution with the satellite data for uniform comparison. This was the first attempt of developing such algorithm taking into consideration the uniqueness of West African convective systems. The algorithm loads an input (text) file where necessary inputs as preferred by the user, takes input file of satellite data or model’s output in netcdf file format. The good graphical interface for interacting with user makes it very flexible and easy to use with little computer knowledge. Good results from the comparison and validation shows a good agreement between the model’s output and satellite data shows the consistency in the tracking algorithm. The algorithm can hence be used for comparison or evaluating the performances of different Physics parameterizations/schemes in same model with the observed. It can also be used for comparison or evaluating performances of different models in simulating convective systems of the West Africa sub-region. Keywords : convective systems, tracking, properties, propagation, growth and decaying. DOI: 10.7176/JNSR/13-18-06 Publication date: October 31 st 2022

Prediction of Track of Super Cyclone Amphan using WRF-ARW Model

An attempt has been made to study the prediction of the track of Super Cyclone (SuC) Amphan that formed on 13 May over Southeast Bay of Bengal (BoB) and made landfall to West Bengal-Bangladesh Coast on 20 May 2020 using Advanced Research WRF (ARW) dynamics of Weather Research and Forecasting (WRF) model. Model integration has been carried out using two-way interactive nesting domains with resolutions of 27 km for domain 1 and 9 km for domain 2 respectively covering the Bay of Bengal. Simulations are performed at an interval of 6 hours with ICs using the National Centre for Environmental Prediction (NCEP) global forecast system (GFS) 0.25° analysis and forecasts. To understand the applicability of the model in predicting the track along with landfall position and landfall time, nine real-time numerical forecasts have been carried out with model simulation starting at 00 UTC of 13 May, 14 May, 15 May, 16 May, 17 May, 18 May, 19 May, 20 May and 21 May 2020. The experiments with initial time on 16 May, 17 May, 18 May, 19 May, and 20 May 2020 have produced the best performance for the track and intensity prediction which are comparable to those provided by Bangladesh Meteorological Department (BMD) and Regional Specialized Meteorological Centre (RSMC). The tracks are produced based on the distribution of sea level pressure and vorticity. The model shows that the track prediction accuracy increases as the lead time decreases with the updated ICs. The results obtained from the model are in good agreement with the reported data. The experiment of SuCAmphan produced better track and intensity predictions with lead-time of 144, 120, 96, 48, and 24 hours. The results demonstrate that the model is capable to produce the track of SuCAmphan with reasonable accuracy. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 10(2), 2021, P 35-42

Regional Climate Modelling using Advanced Research WRF for simulation of long term rainfall in Uttarakhand Himalaya in CORDEX framework

Abstract: With the most fragile and complex environment having rich repository of biodiversity and water, the terrains of Uttarakhand Himalaya is always challenging for regional climate modelling. In this work, three different versions of land surface schemes are used to simulate the climate over this complex terrain for the period of 1995-2010 with a horizontal resolution of 0.440 , using the Advanced Weather Research and Forecasting (WRF-ARW) model.

Object-based analysis of simulated thunderstorms in Switzerland: application and validation of automated thunderstorm tracking with simulation data

Abstract. We present a feasibility study for an object-based method to characterise thunderstorm properties in simulation data from convection-permitting weather models. An existing thunderstorm tracker, the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) algorithm, was applied to thunderstorms simulated by the Advanced Research Weather Research and Forecasting (AR-WRF) weather model at convection-permitting resolution for a domain centred on Switzerland. Three WRF microphysics parameterisations were tested. The results are compared to independent radar-based observations of thunderstorms derived using the MeteoSwiss Thunderstorms Radar Tracking (TRT) algorithm. TRT was specifically designed to track thunderstorms over the complex Alpine topography of Switzerland. The object-based approach produces statistics on the simulated thunderstorms that can be compared to object-based observation data. The results indicate that the simulations underestimated the occurrence of severe and very large hail compared to the observations. Other properties, including the number of storm cells per day, geographical storm hotspots, thunderstorm diurnal cycles, and storm movement directions and velocities, provide a reasonable match to the observations, which shows the feasibility of the technique for characterisation of simulated thunderstorms over complex terrain.

Study of surface-based temperature inversions in the city of Nadym (Western Siberia) with direct measurements and numerical simulation

Frequent surface-based inversions are persistent features of climate in the Arctic and, in particular, in its Russian part. Most favourable conditions for temperature inversion formation during the winter period in this region are observed. Surface-based inversions formed in cities are most interesting for research, because of their impact on people’s health. Besides, “urban” surface-based inversions differ from “rural” ones, because of interactions with the urban heat island (UHI). Actually, urban surface-based inversions in the Arctic are weakly understood due to poor meteo monitoring equipment of most Arctic regions and because the reanalysis resolution is too low for the cities. To estimate the frequency of surface-based inversions and spatial distributions in the city of Nadym (Western Siberia), measurements with gradient complexes during the period from 18.12.2018 to 15.10.2019 have been conducted, and a numerical experiment with a model Advanced Research WRF (ARW) has been performed for the coldest days of the period. In the research, first statistic microclimatic data of vertical temperature distributions in the city of Nadym have been obtained. Such model experiments are realized for that region, and the results obtained for the rural area are compared with microwave temperature profiler MTP-5 measurements.

Sensitivity of Microphysical Schemes on the Simulation of Post-Monsoon Tropical Cyclones over the North Indian Ocean

Tropical Cyclones (TCs) are the most disastrous natural weather phenomenon, that have a significant impact on the socioeconomic development of the country. In the past two decades, Numerical Weather Prediction (NWP) models (e.g., Advanced Research WRF (ARW)) have been used for the prediction of TCs. Extensive studies were carried out on the prediction of TCs using the ARW model. However, these studies are limited to a single cyclone with varying physics schemes, or single physics schemes to more than one cyclone. Hence, there is a need to compare different physics schemes on multiple TCs to understand their effectiveness. In the present study, a total of 56 sensitivity experiments are conducted to investigate the impact of seven microphysical parameterization schemes on eight post-monsoon TCs formed over the North Indian Ocean (NIO) using the ARW model. The performance of the Ferrier, Lin, Morrison, Thompson, WSM3, WSM5, and WSM6 are evaluated using error metrics, namely Mean Absolute Error (MAE), Mean Square Error (MSE), Skill Score (SS), and average track error. The results are compared with Indian Meteorological Department (IMD) observations. From the sensitivity experiments, it is observed that the WSM3 scheme simulated the cyclones Nilofar, Kyant, Daye, and Phethai well, whereas the cyclones Hudhud, Titli, and Ockhi are best simulated by WSM6. The present study suggests that the WSM3 scheme can be used as the first best scheme for the prediction of post-monsoon tropical cyclones over the NIO.

Study on Sensitivity of Microphysics for the Simulation of Rainfall for the Month of May 2015 over Bangladesh using High Resolution WRF-ARW Model

In this research the Advanced Research WRF (ARW) model v3.8.1 has been used to simulate the rainfall of May 2015 all over Bangladesh. The model was configured in nested domain with 18 and 6 km horizontal grid spacing with 100 × 96 and 103 × 127 grids in the east-west and north-south directions, respectively with 30 vertical levels. The Lin et al., WSM6, Thomson, Morrison Double-Moment (M-2Mom), Stony Brook University (SBU), and WDM6 microphysics schemes coupling with Kain-Fritsch (KF) cumulus parameterization (CP) scheme have been used to simulate the monthly total rainfall, heavy rainfall, monthly rainy days and heavy rainy days for the month of May 2015 at all meteorological stations of Bangladesh. The simulated results are compared with the observed results of 33 meteorological stations of Bangladesh Meteorological Department (BMD) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) output. Relative standard deviation of all observed, PERSIANN and model simulated parameters have been analyzed and compared. The maximum monthly observed rain in May 2015 at Sylhet was 752 mm but WSM6, M-2Mom and WDM6 schemes have simulated 831, 788 and 742 mm for day 1 prediction; WSM6, WDM6 and SBU-Lin schemes have simulated 757, 916 and 981 mm for day 2 prediction and WSM6 and WDM6 schemes have simulated 741 and 925 mm for day 3 prediction, respectively and all other MPs have simulated much higher rainfall at domain (D1). The WDM6, M-2Mom and Lin et al. schemes have simulated 744, 807 and 923 mm for day 1 prediction, WSM6 and WDM6 schemes have simulated 714 and 877 mm for day 2 predictions and WSM6, SBU-Lin and Lin et al. schemes have simulated 802 and 913 and 998 mm, respectively for day 3 predictions at domain (D2). The relative standard deviation (RSD) has minimum at D1 and D2 for WDM6 scheme for day 1 prediction and WSM6 scheme for day 2 and day 3 predictions for the monthly total rainfall and heavy rainfall of May 2015. The results suggest that as the forecast time increased the amount of total rain and also heavy rain is increased. As a result RSD is also increased for all MPs. WDM6 scheme gives the better performance of rainfall and rainy days all over the country.
 Journal of Engineering Science 11(1), 2020, 43-60

Sensitivity of WRF-simulated 10 m wind over the Persian Gulf to different boundary conditions and PBL parameterization schemes

A sensitivity analysis of the Weather Research and Forecasting (WRF) mesoscale model with the Advanced Research WRF (ARW) dynamical solver for wind simulation at 10 m above ground level was conducted through different initial and boundary conditions datasets, and various planetary boundary layer (PBL) schemes throughout the year 2017 over the Persian Gulf region. Owing to the wide variety of approaches and development periods of analysis and reanalysis data (e.g. assimilation system) as well as different methods for PBL parameterization (closure formulations), this paper aims to obtain an efficient set up of the WRF model configuration in terms of the lowest error in simulating surface wind. Three datasets including ERA-Interim reanalysis, NCEP-R2 reanalysis, and NCEP-FNL analysis as initial and boundary conditions to the model and six PBL schemes including ACM2, BouLac, MYJ, MYNN, QNSE, and YSU accompanied by their relevant surface-layer schemes were used to accomplish this goal. Available observational wind data including 23 synoptic weather stations located in the region were used to compare the model wind simulation. Comparing WRF wind simulations with observations at synoptic weather stations indicates that; irrespective of the type of PBL scheme, ERA-Interim, and NCEP-FNL datasets exhibit better performance than the NCEP-R2. In addition, in the case of considering PBL schemes, results show that the configuration including the YSU scheme and ERA-Interim reanalysis data leads to the best estimation of wind speed and configuration including YSU and NCEP-FNL data produces the least error for wind direction. The performance of the model in summer shows higher errors compared to the winter season. It is due to the obvious differences between initial and boundary conditions data with observation data. The success of the YSU scheme in comparison with other schemes is rooted in the nonlocal closure of this scheme, which includes local gradients correction and entrainment sentences.

Effects of Microphysical Latent Heating on the Rapid Intensification of Typhoon Hato (2017)

A 72-h cloud-resolving numerical simulation of Typhoon Hato (2017) is performed by using the Weather Research and Forecasting (WRF) model with the Advanced Research WRF (ARW) core (V3.8.1) on a horizontal resolution of 2 km. To enhance the background tropical cyclone structure and intensity, a vortex dynamic initialization scheme with a terrain-filtering algorithm is utilized. The model reproduces reasonably well the track, structure, and intensity change of Typhoon Hato. More specifically, the change trend of simulated maximum wind speed is consistent with that of best-track analysis, and the simulated maximum wind of 49 m s−1 is close to that (52 m s−1) of the best-track analysis, indicating that the model has successfully captured the rapid intensification (RI) of Typhoon Hato (2017). Analyses of the model outputs reveal that the total microphysical latent heating of the inner-core region associated with enhanced vertical upward motion reaches its maximum at 9-km height in the upper troposphere during the RI stage. The dominant microphysical processes with positive latent heat contributions (i.e., heating effect) are water vapor condensation into cloud water (67.6%), depositional growth of ice (12.9%), and generation (nucleation) of ice from vapor (7.9%). Those with negative latent heat contributions (cooling effect) are evaporation of rain (47.6%), melting of snow (27.7%), and melting of graupel (9.8%). Sensitivity experiments further show that the intensification speed and peak intensity of this typhoon are highly correlated to the dominant heating effect. A significant increase in graupel over 5-10-km height and snow at 10–14-km height in the inner-core region of Typhoon Hato corresponds well with its RI stage, and the latent heating from nucleation and depositional growth is crucial to the RI of simulated Hato.

Observational and Modelling Study of a Major Downburst Event in Liguria: The 14 October 2016 Case

Downbursts are very disruptive weather events that can produce large amounts of damage. The most studied downbursts are those occurring in the United States and continental Europe, but they can happen globally. This work is an observational and modelling analysis of a major downburst event that occurred on 14 October 2016 over eastern Liguria (Italy). This downburst affected an area 30 km long and 10 km wide, producing observed wind gusts of 40 m/s with major impacts to railways, trees, and houses, with more than 2.5 million euros of damage. First, the general environment influencing this downburst is identified and analyzed, then the event is reproduced with a small multi-physics high-resolution ensemble using the Weather Research and Forecasting (WRF)–advanced research WRF (ARW) model, with 1 km horizontal grid spacing. The event was poorly predicted beforehand, and the difficulty in forecasting this event is confirmed by the fact that so few ensemble members suggested the occurrence of damaging winds over eastern Liguria. However, one of the eight members performed well and its output helped to reveal the primary mechanisms for the downburst, suggesting that high-resolution ensembles using mixed physics may be a useful tool for improving the prediction of similar extreme events in the Mediterranean region in the future.

Influence of cumulus convection and cloud microphysics parameterizations on the prediction of Western Disturbances

The western disturbances (WD) form over the Mediterranean region as extra-tropical low-pressure systems and lose the frontal structure while moving eastward to reach India. These systems bring cold waves, snowfalls, hailstorms and rain over north and north-west India during post monsoon and winter months. The first part (Part A) of the present paper investigates the performance of Advanced Research WRF (ARW) model with 8 combinations of cloud microphysics and cumulus convection schemes in simulating 20 WD cases. These 20 cases were simulated using a single-domain WRF model of horizontal resolution 27 km. The combination of Lin et al. cloud microphysics scheme and Betts–Miller–Janjic cumulus convection scheme (mp2cu2) performs better than other combinations in simulating temperature at 2 m height and precipitation. The performance of the combination of Ferrier (new Eta) microphysics scheme and Betts-Miller-Janjic cumulus convection scheme (mp3cu2) is very close to that of mp2cu2 combination. Analysis of box-whisker plot also shows that the combinations mp2cu2 and mp3cu2 perform better than others. In the second part (Part B) 10 cases are simulated using a double-nested WRF model with inner and outer domain resolutions 9 km and 27 km, respectively. Four cases of part B are simulated with (mp2cu2 and mp3cu2) and without (mp2cu0 and mp3cu0) cumulus convection schemes to understand the response of cloud microphysics to explicit convection and also to select the best combination of cloud microphysics and cumulus convection scheme. The combination mp2cu2 has lower RMSE of precipitation than other combinations. Remaining six cases were then simulated with the combination of mp2cu2 using the double-nested model. Spatial distribution of model simulated and TRMM estimated precipitation agree well in most of the cases. The domain-averaged RMSE of model-simulated precipitation with respect to TRMM 3B42 V7 estimated precipitation varies from 2.89 to 4.12 cm for the six WD cases. The box-whisker diagram shows that the model overestimates the maximum rainfall amount in most of the cases but it is consistent in simulating precipitation over the model domain for all the six cases.

WRF-CMake: integrating CMake support into the Advanced Research WRF (ARW) modelling system

WRF-CMake: integrating CMake support into the Advanced Research WRF (ARW) modelling system

Evaluation of WRF-DART (ARW v3.9.1.1 and DART Manhattan release) multiphase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment

Abstract. Numerical weather prediction models tend to underestimate cloud presence and therefore often overestimate global horizontal irradiance (GHI). The assimilation of cloud water path (CWP) retrievals from geostationary satellites using an ensemble Kalman filter (EnKF) led to improved short-term GHI forecasts of the Weather Research and Forecasting (WRF) model in midlatitudes in case studies. An evaluation of the method under tropical conditions and a quantification of this improvement for study periods of more than a few days are still missing. This paper focuses on the assimilation of CWP retrievals in three phases (ice, supercooled, and liquid) in a 6-hourly cycling procedure and on the impact of this method on short-term forecasts of GHI for Réunion Island, a tropical island in the southwest Indian Ocean. The multilayer gridded cloud properties of NASA Langley's Satellite ClOud and Radiation Property retrieval System (SatCORPS) are assimilated using the EnKF of the Data Assimilation Research Testbed (DART) Manhattan release (revision 12002) and the advanced research WRF (ARW) v3.9.1.1. The ability of the method to improve cloud analyses and GHI forecasts is demonstrated, and a comparison using independent radiosoundings shows a reduction of specific humidity bias in the WRF analyses, especially in the low and middle troposphere. Ground-based GHI observations at 12 sites on Réunion Island are used to quantify the impact of CWP DA. Over a total of 44 d during austral summertime, when averaged over all sites, CWP data assimilation has a positive impact on GHI forecasts for all lead times between 5 and 14 h. Root mean square error and mean absolute error are reduced by 4 % and 3 %, respectively.

Modeling the Seasonal Dynamics of the Diurnal Variation of the Global Electric Circuit

On the basis of a parametrization of the ionospheric potential (IP), the seasonal dynamics of the diurnal IP variation for 2016–2017 is simulated for the first time using the Weather Research and Forecasting (WRF)-Advanced Research WRF (WRF-ARW) model. The diurnal IP variation averaged over the annual simulation period shows good agreement with the classical Carnegie curve, suggesting that the proposed parametrization correctly reproduces the basic characteristics of stationary global electric circuit generators. The annual variation shows no precise repeatability from year to year, but there is a lower IP in the Northern Hemisphere winter and a higher value in the summer. The model-derived diurnal variation demonstrates stable seasonal trends, with only one distinct IP maximum of 120% of the average at 16:00 to 18:00 UTC in the Northern Hemisphere winter and two much lower maxima (~107% of the average) in the summer: a morning maximum at 08:00 to 09:00 UTC and an evening maximum at 18:00 to 20:00 UTC. The model annual dynamics of the diurnal variation agrees with the experimental data of surface field measurements in Antarctica in 2006–2011. The proposed parameterization and the modeling technique made it possible to correctly simulate the times of IP variation maxima, their seasonal variability, and а decrease in the variation amplitude during the Northern Hemisphere summer.

Impact of Moisture Transport and Boundary Layer Processes on a Very Severe Cyclonic Storm Using the WRF Model

In this work the very severe cyclonic storm Thane which formed over the Bay of Bengal during 25–31 December 2011 and struck the East coast of India was simulated using the Weather Research and Forecasting (WRF)-Advanced Research WRF (WRF-ARW) mesoscale model. Normally, very severe cyclones rarely form in this late season. The moisture transport, intensity, track and structure of the cyclone is analyzed through vertically integrated moisture flux convergence and planetary boundary layer physics of the Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ) and Asymmetrical Convective Model version 2 (ACM2) schemes. Cyclonic circulation and moisture convergence are seen 6 days ahead of the development of the cyclone and strengthened by the transport of moisture advected from the South China Sea. From the three planetary boundary layer (PBL) schemes, the YSU scheme gives better results both qualitatively and quantitatively for the moisture flux convergence. The MYJ scheme produced the least errors for cyclone intensity from genesis to the landfall stage, while the ACM2 scheme gave better results after landfall. The track of the cyclone with the YSU scheme produced the least errors throughout the life cycle which gives the least landfall error. The structure of the cyclone in terms of tangential winds, the spatial distribution of cloud bands, vertical cross section of temperature anomaly, relative humidity and vertical winds was well simulated by the ACM2 scheme.

Application of advanced research WRF model using tropical (New Tiedtke) scheme and Kain-Fritsch scheme in predicting short-term weather in Palembang and its surrounding areas

The New Tiedtke and Kain-Fritsch schemes in WRF-ARW had been applied separately for the case of short-term weather predictions in Palembang and its surroundings from 1 to 7 December 2017. The WRF-ARW predictions compared to observation data at SMB II station showed that the Kain-Fritsch scheme gave better results than the New Tiedtke scheme either for temperature (MAE = 1.24 ° C to 1.31 ° C, RMSE = 1.49 ° C to 1.60 ° C, and MAPE = 4.46 to 4.67) or for relative humidity (MAE = 6.24% to 6.54%, RMSE = 7.61 % of 8.28%, and MAPE = 8.16% for 8.61%). However, for precipitation predictions even from dichotomous test the FBI value obtained by the Kain-Fritsch scheme (FBI=2.6) is better than that by the New Tiedtke scheme (FBI=3) with a FBI value of 3, both schemes could not predict precipitation well (ACC = 0.67 to 0.64, TS = 0 to 0, POD = 0 to 0, FAR = 1 to 1).

Dynamical downscaling the impact of spring Western US land surface temperature on the 2015 flood extremes at the Southern Great Plains: effect of domain choice, dynamic cores and land surface parameterization

Recent studies have shown that spring land surface temperature (LST) and subsurface temperature (SUBT) over the high elevation areas in the western US (WUS) have significant impacts on the downstream summer droughts/floods in North America. In this paper, both the National Centers for Environmental Prediction—Global Forecast System (NCEP-GFS) general circulation model (GCM) and the weather research and forecasting (WRF) regional climate model (RCM) are employed, where RCM scenarios utilized initial and lateral boundary conditions derived from the corresponding NCEP-GFS scenarios. Here we use a late spring flood in the US Southern Great Plains (SGP) case to examine whether simulation of the LST/SUBT downstream effects is sensitive to the domain size choice, change in dynamical cores within the same model, as well as to the representation of surface processes parameterizations. Although all RCM experiments with different settings simulate reasonably geographical patterns of observed LST and precipitation anomalies, we found that the choice of the domain size is crucial for proper downscaling the LST/SUBT downstream effects to accurately produce the observed precipitation/LST anomalies over the SGP/WUS, respectively, along with the associated large-scale features. The southern boundary location has been identified to be crucial in producing the SGP Low Level Jet strength, which in turn brings more moisture from the Gulf of Mexico to the SGP and thereby resulting in a better simulation of the precipitation anomaly in that area. The sensitivity of the simulation of the LST/SUBT downstream effect to dynamical cores is assessed by inter-comparing the Non-hydrostatic Mesoscale Model (NMM) and the Advanced Research WRF dynamic cores. We find NMM was better at generating the large-scale eastward wave train, a crucial process associated with the LST/SUBT downstream effect. Meanwhile, this study also shows that the LST/SUBT downstream effects were not significantly dependent on the surface process parameterizations, although the Simplified Simple Biosphere model version 3 (SSiB3) highlighted a better performance over SSiB2.

Online coupled modeling of weather and air quality of Budapest using the WRF-Chem model

WRF-Chem is a numerical Eulerian non-hydrostatic mesoscale weather prediction model online coupled with the atmospheric chemistry model, developed mainly by the National Center for Atmospheric Research (NCAR) and the National Oceanic and Atmospheric Administration (NOAA). This model system is a frequently used tool for creating high resolution air quality simulations at different spatial and temporal scales for various air pollutants. In this study, the technical backgrounds of the WRF-Chem model applied for high resolution urban air quality forecasts in Budapest are presented. The meteorological module of the system uses the WRF-ARW (Weather Research and Forecasting – Advanced Research WRF) dynamical solver, and obtains its initial and boundary conditions from the GFS (Global Forecast System) using a horizontal resolution of 0.25 × 0.25 degree. By applying two nested model domains (with 15 × 5 km horizontal resolution), fine resolution meteorological fields can be achieved. In the chemical module, the National Emission Inventories created by the Hungarian Meteorological Service were applied, different chemical reaction sets were used and tested, and constant deposition rates were assumed. In this work, a case study for different pollutants (O3, NO, NO2, and CO) is presented for an early summer period of 2015.