Performance of WRF-Chem over Indian region: Comparison with measurements

The aerosol mass concentrations over several Indian regions have been simulated using the online chemistry transport model, WRF-Chem, for two distinct seasons of 2011, representing the pre-monsoon (May) and post-monsoon (October) periods during the Indo-US joint experiment `Ganges Valley Aerosol Experiment (GVAX)'. The simulated values were compared with concurrent measurements. It is found that the model systematically underestimates near-surface BC mass concentrations as well as columnar Aerosol Optical Depths (AODs) from the measurements. Examining this in the light of the model-simulated meteorological parameters, we notice the model overestimates both planetary boundary layer height (PBLH) and surface wind speeds, leading to deeper mixing and dispersion and hence lower surface concentrations of aerosols. Shortcoming in simulating rainfall pattern also has an impact through the scavenging effect. It also appears that the columnar AODs are influenced by the unrealistic emission scenarios in the model. Comparison with vertical profiles of BC obtained from aircraft-based measurements also shows a systematic underestimation by the model at all levels. It is seen that concentration of other aerosols, viz., dust and sea-salt are closely linked with meteorological conditions prevailing over the region. Dust is higher during pre-monsoon periods due to the prevalence of north-westerly winds that advect dust from deserts of west Asia into the Indo-Gangetic plain. Winds and rainfall influence sea-salt concentrations. Thus, the unrealistic simulation of wind and rainfall leads to model simulated dust and sea-salt also to deviate from the real values; which together with BC also causes underperformance of the model with regard to columnar AOD. It appears that for better simulations of aerosols over Indian region, the model needs an improvement in the simulation of the meteorology.

Improvement in the Accuracy of Back Trajectories Using WRF to Identify Pollen Sources in Southern Iberian Peninsula

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Application of WRF-Chem to Forecasting PM10 Concentration over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one way nested domains using the GFS meteorological data and the TNO MACC II emissions. Forecasts, with 48h lead time, were run for a winter and summer period 2014. WRF-Chem in general captures the variability in observed PM10 concentrations, but underestimates some peak concentrations during winter-time. The peaks coincide with either stable atmospheric condition during nighttime in the lower part of the planetary boundary layer or on days with very low surface temperatures. Such episodes lead to increased combustion in residential heating, where hard coal is the main fuel in Poland. This suggests that a key to improvement in the model performance for the peak concentrations is to focus on the simulation of PBL processes and the distribution of emissions with high resolution in WRF-Chem.

Application of the WRF-Chem Model for a High Ozone Episode in SW Poland – Preliminary Results

The Weather Research and Forecasting model, integrated online with chemistry module, is a multi-scale model suitable for both research and operational forecasts of meteorology and air quality. It is used by many institutions for a variety of applications. In this study, the WRF v3.5 with chemistry (WRF-Chem) is applied to the area of Poland, for a period of 3-20 July 2006, when high concentrations of ground level ozone were observed. The meteorological and chemistry simulations were initiated with ERA-Interim reanalysis and TNO MACC II emissions database, respectively. The model physical parameterization includes RRTM shortwave radiation, Kain-Fritsch cumulus scheme, Purdue Lin microphysics and ACM2 PBL, established previously as the optimal configuration. Chemical mechanism used for the study was RADM2 with MADE/SORGAM aerosols. Simulations were performed for three one-way nested domains covering Europe (36 km x 36 km), Central Europe (12 km x 12 km) and Poland (4 km x 4 km). The results from the innermost domain were analyzed and compared to measurements of ozone concentration at three stations in different environments. The results show underestimation of observed values and daily amplitude of ozone concentrations.

A sensitivity study of the WRF model in wind simulation for an area of high wind energy

The performance of the Weather Research and Forecast (WRF) model in wind simulation was evaluated under different numerical and physical options for an area of Portugal, located in complex terrain and characterized by its significant wind energy resource. The grid nudging and integration time of the simulations were the tested numerical options. Since the goal is to simulate the near-surface wind, the physical parameterization schemes regarding the boundary layer were the ones under evaluation. Also, the influences of the local terrain complexity and simulation domain resolution on the model results were also studied. Data from three wind measuring stations located within the chosen area were compared with the model results, in terms of Root Mean Square Error, Standard Deviation Error and Bias. Wind speed histograms, occurrences and energy wind roses were also used for model evaluation. Globally, the model accurately reproduced the local wind regime, despite a significant underestimation of the wind speed. The wind direction is reasonably simulated by the model especially in wind regimes where there is a clear dominant sector, but in the presence of low wind speeds the characterization of the wind direction (observed and simulated) is very subjective and led to higher deviations between simulations and observations. Within the tested options, results show that the use of grid nudging in simulations that should not exceed an integration time of 2 days is the best numerical configuration, and the parameterization set composed by the physical schemes MM5–Yonsei University–Noah are the most suitable for this site. Results were poorer in sites with higher terrain complexity, mainly due to limitations of the terrain data supplied to the model. The increase of the simulation domain resolution alone is not enough to significantly improve the model performance. Results suggest that error minimization in the wind simulation can be achieved by testing and choosing a suitable numerical and physical configuration for the region of interest together with the use of high resolution terrain data, if available.

A Comparative Study of Convective Parameterization Schemes in WRF-NMM Model

Severe local storms, including tornadoes, damaging hail and wind gusts, frequently occur over the eastern and northeastern states of India during the pre-monsoon season (March-May). Forecasting thunderstorms is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent non-linearity of their dynamics and physics. In this paper, sensitivity experiments are conducted with the WRF-NMM model to test the impact of convective parameterization schemes on simulating severe thunderstorms that occurred over Kolkata on 20 May 2006 and 21 May 2007 and validated the model results with observation. In addition, a simulation without convective parameterization scheme was performed for each case to determine if the model could simulate the convection explicitly. A statistical analysis based on mean absolute error, root mean square error and correlation coefficient is performed for comparisons between the simulated and observed data with different convective schemes. This study shows that the prediction of thunderstorm affected parameters is sensitive to convective schemes. The Grell-Devenyi cloud ensemble convective scheme is well simulated the thunderstorm activities in terms of time, intensity and the region of occurrence of the events as compared to other convective schemes and also explicit scheme

The diagnosis of severe thunderstorms with high-resolution WRF model

Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere. A common feature of the weather during the pre-monsoon season over the Indo-Gangetic Plain and northeast India is the outburst of severe local convective storms, commonly known as ‘Nor’westers’(as they move from northwest to southeast). The severe thunderstorms associated with thunder, squall lines, lightning and hail cause extensive losses in agricultural, damage to structure and also loss of life. In this paper, sensitivity experiments have been conducted with the Non-hydrostatic Mesoscale Model (NMM) to test the impact of three microphysical schemes in capturing the severe thunderstorm event occurred over Kolkata on 15 May 2009. The results show that the WRF-NMM model with Ferrier microphysical scheme appears to reproduce the cloud and precipitation processes more realistically than other schemes. Also, we have made an attempt to diagnose four severe thunderstorms that occurred during pre-monsoon seasons of 2006, 2007 and 2008 through the simulated radar reflectivity fields from NMM model with Ferrier microphysics scheme and validated the model results with Kolkata Doppler Weather Radar (DWR) observations. Composite radar reflectivity simulated by WRF-NMM model clearly shows the severe thunderstorm movement as observed by DWR imageries, but failed to capture the intensity as in observations. The results of these analyses demonstrated the capability of high resolution WRF-NMM model in the simulation of severe thunderstorm events and determined that the 3 km model improve upon current abilities when it comes to simulating severe thunderstorms over east Indian region

Trade-offs and responsiveness of the single-layer urban canopy parametrization in WRF: an offline evaluation using the MOSCEM optimization algorithm and field observations

For an increasing number of applications, mesoscale modelling systems now aim to better represent urban areas. The complexity of processes resolved by urban parametrization schemes varies with the application. The concept of fitness-for-purpose is therefore critical for both the choice of parametrizations and the way in which the scheme should be evaluated. A systematic and objective model response analysis procedure (Multiobjective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm) is used to assess the fitness of the single-layer urban canopy parametrization implemented in the Weather Research and Forecasting (WRF) model. The scheme is evaluated regarding its ability to simulate observed surface energy fluxes and the sensitivity to input parameters. Recent amendments are described, focussing on features which improve its applicability to numerical weather prediction, such as a reduced and physically more meaningful list of input parameters. The study shows a high sensitivity of the scheme to parameters characterizing roof properties in contrast to a low response to road-related ones. Problems in partitioning of energy between turbulent sensible and latent heat fluxes are also emphasized. Some initial guidelines to prioritize efforts to obtain urban land-cover class characteristics in WRF are provided. Copyright © 2010 Royal Meteorological Society and Crown Copyright.

The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems

To bridge the gaps between traditional mesoscale modelling and microscale modelling, the National Center for Atmospheric Research, in collaboration with other agencies and research groups, has developed an integrated urban modelling system coupled to the weather research and forecasting (WRF) model as a community tool to address urban environmental issues. The core of this WRF/urban modelling system consists of the following: (1) three methods with different degrees of freedom to parameterize urban surface processes, ranging from a simple bulk parameterization to a sophisticated multi-layer urban canopy model with an indoor–outdoor exchange sub-model that directly interacts with the atmospheric boundary layer, (2) coupling to fine-scale computational fluid dynamic Reynolds-averaged Navier–Stokes and Large-Eddy simulation models for transport and dispersion (T&D) applications, (3) procedures to incorporate high-resolution urban land use, building morphology, and anthropogenic heating data using the National Urban Database and Access Portal Tool (NUDAPT), and (4) an urbanized high-resolution land data assimilation system. This paper provides an overview of this modelling system; addresses the daunting challenges of initializing the coupled WRF/urban model and of specifying the potentially vast number of parameters required to execute the WRF/urban model; explores the model sensitivity to these urban parameters; and evaluates the ability of WRF/urban to capture urban heat islands, complex boundary-layer structures aloft, and urban plume T&D for several major metropolitan regions. Recent applications of this modelling system illustrate its promising utility, as a regional climate-modelling tool, to investigate impacts of future urbanization on regional meteorological conditions and on air quality under future climate change scenarios. Copyright © 2010 Royal Meteorological Society

Investigating the sensitivity of hurricane intensity and trajectory to sea surface temperatures using the regional model WRF

The influence of sea surface temperature (SST) anomalies on the hurricane characteristics are investigated in a set of sensitivity experiments employing the Weather Research and Forecasting (WRF) model. The idealised experiments are performed for the case of Hurricane Katrina in 2005. The first set of sensitivity experiments with basin-wide changes of the SST magnitude shows that the intensity goes along with changes in the SST, i.e., an increase in SST leads to an intensification of Katrina. Additionally, the trajectory is shifted to the west (east), with increasing (decreasing) SSTs. The main reason is a strengthening of the background flow. The second set of experiments investigates the influence of Loop Current eddies idealised by localised SST anomalies. The intensity of Hurricane Katrina is enhanced with increasing SSTs close to the core of a tropical cyclone. Negative nearby SST anomalies reduce the intensity. The trajectory only changes if positive SST anomalies are located west or north of the hurricane centre. In this case the hurricane is attracted by the SST anomaly which causes an additional moisture source and increased vertical winds.

Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain

Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a set-up of the Weather Research and Forecasting Model (WRF) model that minimises system- atic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable set-up: the horizontal resolution, the planetary boundary layer (PBL) parameterisation scheme and the way the WRF is nested to the driving data set. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model set-ups, but sharing the same driving data set. The results show that the lack of representation of the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis nudging, spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model performance is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.

Atmospheric water parameters measured by a ground-based microwave radiometer and compared with the WRF model

The microwave radiometer TROWARA measures integrated water vapour (IWV) and integrated cloud liquid water (ILW) at Bern since 1994 with a time resolution of 7 s. In this study, we compare TROWARA measurements with a simulation of summer 2012 in Switzerland performed with the Weather Research and Forecasting (WRF) model. It is found that the WRF model agrees very well with TROWARA’s IWV variations with a mean bias of only 0.7 mm. The ILW distribution of the WRF model, although similar in shape to TROWARA’s distribution, overestimates the fraction of clear sky periods (83% compared to 60%).

Development and assessment of traffic-related emission abatement measures for the Madrid city (Spain) through the WRF-SMOKE-CMAQ modelling system

The achievement of the limit values established in the European legislation pose an important handicap for large urban areas with intense road traffic, such as Madrid (Spain). Despite permanent measures included in air quality plans it is important to assess additional measures that may be temporally applied under unfavourable conditions. This paper reports on the simulation of different traffic restriction strategies in Madrid for high-pollution episodes.

Assessment of urban parameterizations in the WRF model for air quality modelling purposes in Madrid (Spain)

This study aims to assess the performance or multi-layer canopy parameterizations implemented in the mesoscale WRF model in order to understand their potential contribution to improve the description of energy fluxes and wind fields in the Madrid city. It was found that the Building Energy Model (BEP+BEM) parameterization yielded better results than the bulk standard scheme implemented in the Noah LSM, but very close to those of the Building Energy Parameterization (BEP). The later was deemed as the best option since data requirements and CPU time were smaller. Two annual runs were made to feed the CMAQ chemical-transport model to assess the impact of this feature in routinely air quality modelling activities.