The airflow and dispersion of a pollutant in a complex urban area of Beijing, China, were numerically examined by coupling a Computational Fluid Dynamics （CFD） model with a mesoscale weather model. The models used w...The airflow and dispersion of a pollutant in a complex urban area of Beijing, China, were numerically examined by coupling a Computational Fluid Dynamics （CFD） model with a mesoscale weather model. The models used were Open Source Field Operation and Manipulation （OpenFOAM） software package and Weather Research and Forecasting （WRF） model. OpenFOAM was firstly validated against wind-tunnel experiment data. Then, the WRF model was integrated for 42 h starting from 0800 LST 08 September 2009, and the coupled model was used to compute the flow fields at 1000 LST and 1400 LST 09 September 2009. During the WRF-simulated period, a high pressure system was dominant over the Beijing area. The WRF-simulated local circulations were characterized by mountain valley winds, which matched well with observations. Results from the coupled model simulation demonstrated that the airflows around actual buildings were quite different from the ambient wind on the boundary provided by the WRF model, and the pollutant dispersion pattern was complicated under the influence of buildings. A higher concentration level of the pollutant near the surface was found in both the step-down and step-up notches, but the reason for this higher level in each configurations was different： in the former, it was caused by weaker vertical flow, while in the latter it was caused by a downward-shifted vortex. Overall, the results of this study suggest that the coupled WRF-OpenFOAM model is an important tool that can be used for studying and predicting urban flow and dispersions in densely built-up areas.展开更多
Enhancing the ability of the WRF model in simulating a large area covering the West Pacific Ocean, China's Mainland, and the East Indian Ocean is very important to improve prediction of the East Asian monsoon clim...Enhancing the ability of the WRF model in simulating a large area covering the West Pacific Ocean, China's Mainland, and the East Indian Ocean is very important to improve prediction of the East Asian monsoon climate. The objective of this study is to identify a reasonable configuration of physical parameterization schemes to simulate the precipitation and temperature in this large area. The Mellor-Yamada-Janjic （MYJ） and Yonsei University （YSU） PBL schemes, the WSM3 and WSM5 microphysics schemes, and the Betts-Miller-Janjic （BMJ） and Tiedtke cumulus schemes are compared through simulation of the regional climate of summer 2008. All cases exhibit a similar spatial distribution of temperature as observed, and the spatial correlation coefficients are all higher than 0.95. The cases combining MY J, WSM3/WSM5, and BMJ have the smallest biases of temperature. The choice of PBL scheme has a significant effect on precipitation in such a large area. The cases with MYJ reproduce a better distribution of rain belts, while YSU strongly overestimates the precipitation intensity. The precipitation simulated using WSM3 is similar to that using WSM5. The BMJ cumulus scheme combined with the MYJ PBL scheme has a smaller bias of precipitation. However, the Tiedtke scheme reproduces the precipitation pattern better, especially over the ITCZ.展开更多
On 21 September 2010, heavy rainfall with a local maximum of 259 mm d-1 occurred near Seoul, South Korea. We examined the ability of the Weather Research and Forecasting （WRF） model in reproducing this disastrous ra...On 21 September 2010, heavy rainfall with a local maximum of 259 mm d-1 occurred near Seoul, South Korea. We examined the ability of the Weather Research and Forecasting （WRF） model in reproducing this disastrous rainfall event and identified the role of two physical processes： planetary boundary layer （PBL） and microphysics （MPS） processes. The WRF model was forced by 6-hourly National Centers for Environmental Prediction （NCEP） Final analysis （FNL） data for 36 hours form 1200 UTC 20 to 0000 UTC 22 September 2010. Twenty-five experiments were performed, consisting of five different PBL schemes--Yonsei University （YSU）, Mellor-Yamada-Janjic （MYJ）, Quasi Normal Scale Elimination （QNSE）, Bougeault and Lacarrere （BouLac）, and University of Washington （UW）--and five different MPS schemes--WRF Single- Moment 6-class （WSM6）, Goddard, Thompson, Milbrandt 2-moments, and Morrison 2-moments. As expected, there was a specific combination of MPS and PBL schemes that showed good skill in forecasting the precipitation. However, there was no specific PBL or MPS scheme that outperformed the others in all aspects. The experiments with the UW PBL or Thompson MPS scheme showed a relatively small amount of precipitation. Analyses form the sensitivity experiments confirmed that the spatial distribution of the simulated precipitation was dominated by the PBL processes, whereas the MPS processes determined the amount of rainfall. It was also found that the temporal evolution of the precipitation was influenced more by the PBL processes than by the MPS processes.展开更多
Previous studies showed that 4 D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4 D-Var to influence the future path of a tropical cyclone by cal...Previous studies showed that 4 D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4 D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4 D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously,and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4 D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation,which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4 D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper.展开更多
Assessing wind energy is a key step in selecting a site for a wind farm. The accuracy of the assessment is essential for the future operation of the wind farm. There are two main methods for assessing wind power: one ...Assessing wind energy is a key step in selecting a site for a wind farm. The accuracy of the assessment is essential for the future operation of the wind farm. There are two main methods for assessing wind power: one is based on observational data and the other relies on mesoscale numerical weather prediction(NWP). In this study, the wind power of the Liaoning coastal wind farm was evaluated using observations from an anemometer tower and simulations by the Weather Research and Forecasting(WRF) model, to see whether the WRF model can produce a valid assessment of the wind power and whether the downscaling process can provide a better evaluation. The paper presents long-term wind data analysis in terms of annual, seasonal, and diurnal variations at the wind farm, which is located on the east coast of Liaoning Province. The results showed that, in spring and summer, the wind speed, wind direction, wind power density, and other main indicators were consistent between the two methods. However, the values of these parameters from the WRF model were significantly higher than the observations from the anemometer tower. Therefore, the causes of the differences between the two methods were further analyzed. There was much more deviation in the original material, National Centers for Environmental Prediction(NCEP) final(FNL) Operational Global Analysis data, in autumn and winter than in spring and summer. As the region is vulnerable to cold-air outbreaks and windy weather in autumn and winter, and the model usually forecasted stronger high or low systems with a longer duration, the predicted wind speed from the WRF model was too large.展开更多
The impact of topography on heavy rainfall during two rain seasons was investigated in order to explain their mechanisms on rainfall distribution over Rwanda. Weather Research and Forecasting (WRF-ARW) model was used ...The impact of topography on heavy rainfall during two rain seasons was investigated in order to explain their mechanisms on rainfall distribution over Rwanda. Weather Research and Forecasting (WRF-ARW) model was used to study two historical cases of heavy rainfall which took place over Rwanda during two rain seasons, March to May (MAM) and September to December (SOND), from April 7 to 9, 2012 (for MAM) and from October 29 to 31, 2012 (during SOND). The control experiment was done with actual topography, whereas sensitivity experiment was carried out with topography reduced by half. Results show that rainfall distribution over Rwanda significantly changes when topography is reduced. The reduction in topography leads to a decrease in rainfall amounts in both MAM and SOND seasons, with varying magnitudes. This reveals the importance of orography in determining rainfall amounts and distribution over the region. The accumulated rainfall amount from WRF underestimate or overestimate rain gauge stations data by region and by season, but there is good agreement especially in altitude below 1490 m and above 1554 m during April and October respectively. The results may motivate modelling carters to further improve parameterization schemes in the mountainous regions.展开更多
The Weather Research Forecast model (WRF) configured with high resolution and NCEP 1°×1° reanalysis data were used to simulate the development of a tropical deep convection over the Tiwi Islands,norther...The Weather Research Forecast model (WRF) configured with high resolution and NCEP 1°×1° reanalysis data were used to simulate the development of a tropical deep convection over the Tiwi Islands,northern Australia,and to investigate the sensitivity of model results to model configuration and parameterization schemes of microphysical processes.The simulation results were compared with available measurements.The results show that the model can reproduce most of the important characteristics of the observed diurnal evolution of the convection,including the initiation of convection along the sea-breeze front,which is then reinforced by downdraft outflows,merging of cells and the formation of a deep convective system.However,further improvement is needed to simulate more accurately the location and the time for initiation of the deep convective system.Sensitivity tests show that double-nesting schemes are more accurate than the non-nesting schemes in predicting the distribution and intensity of precipitation as far as this particular case is concerned.Additionally,microphysical schemes also have an effect on the simulated amount of precipitation.It is shown that the best agreement is reached between the simulation results and observations when the Purdue Lin scheme is used.展开更多
Vehicular pollution is becoming significant in urban areas because of increasing population. This is at ground level, so it gives high population exposure. In this study, Chembur, which is the most polluted area in Mu...Vehicular pollution is becoming significant in urban areas because of increasing population. This is at ground level, so it gives high population exposure. In this study, Chembur, which is the most polluted area in Mumbai city due to industrial and vehicular sources, is selected for vehicular pollution modeling using AMS/EPA Regulatory Model (AERMOD). Meteorological parameters, land use surface characteristics and source emission data are collected as required by AERMOD. The results of modelling depend upon reliability of input data and meteorological data has a vital role in the performance of the model. Generally, temporally and spatially interpolated meteorological data is used in modeling. This is generally collected from nearby meteorological station but this causes inaccuracy of the results. In this paper, the Weather Research and Forecasting (WRF) model has been used to generate onsite data on nine meteorological parameters. The modeling of six roads of Chembur has been performed using above meteorological data. This approach gives good results of traffic modeling. The results of AERMOD are compared with observed air quality which has contribution from all sources in the region and relative contribution of vehicular sources identified.展开更多
We investigated the performance of 12 different physics configurations of the climate version of the Weather, Research and Forecasting (WRF) Model over the Middle East and North Africa (MENA) domain. Possible combinat...We investigated the performance of 12 different physics configurations of the climate version of the Weather, Research and Forecasting (WRF) Model over the Middle East and North Africa (MENA) domain. Possible combinations among two Planetary Boundary Layer (PBL), three Cumulus (CUM) and two Microphysics (MIC) schemes were tested. The 2-year simulations (December 1988-November 1990) have been compared with gridded observational data and station measurements for several variables, including total precipitation and maximum and minimum 2-meter air temperature. An objective ranking method of the 12 different simulations and the selection procedure of the best performing configuration for the MENA domain are based on several statistical metrics and carried out for relevant sub-domains and individual stations. The setup for cloud microphysics is found to have the strongest impact on temperature biases while precipitation is most sensitive to the cumulus parameterization scheme and mainly in the tropics.展开更多
Meteorological inputs are of great importance when implementing an air quality prediction system. In this contribution, the Weather Research and Forecast (WRF-ARW) model was used to compare the performance of the diff...Meteorological inputs are of great importance when implementing an air quality prediction system. In this contribution, the Weather Research and Forecast (WRF-ARW) model was used to compare the performance of the different cumulus, microphysics and Planet Boundary Layer parameterizations over Bogotá, Colombia. Surface observations were used for comparison and the evaluated meteorological variables include temperature, wind speed and direction and relative humidity. Differences between parameterizations were observed in meteorological variables and Betts-Miller-Janjic, Morrison 2-moment and BouLac schemes proved to be the best parameterizations for cumulus, microphysics and PBL, respectively. As a complement to this study, a WRF-Large Eddy Simulation was conducted in order to evaluate model results with finer horizontal resolution for air quality purposes.展开更多
Numerical simulations of four weak cyclonic storms [two cases of pre-monsoon cyclones: Laila (2010), Aila (2009) and two cases of post-monsoon cyclones: Jal (2010), SCS (2003)] are carried out using WRF-ARW mesoscale ...Numerical simulations of four weak cyclonic storms [two cases of pre-monsoon cyclones: Laila (2010), Aila (2009) and two cases of post-monsoon cyclones: Jal (2010), SCS (2003)] are carried out using WRF-ARW mesoscale model. Betts-Miller-Janjic (BMJ) as cumulus parameterization (CP) scheme, Yonsei University(YSU) planetary boundary layer (PBL) scheme and WRF single moment 6 class (WSM6) microphysics (MP) scheme is kept same for all the cyclone cases. Three two-way interactive nested domains [60 km,20 kmand6.6 km] are used with initial and boundary conditions from NCEP Final Analysis data. The model integration is performed to evaluate the track, landfall time and position as well as intensity in terms of Central Sea Level Pressure (CSLP) and Maximum Surface Wind speed (MSW) of the storm. The track and landfall (time and position) of almost all cyclones are well predicted by the model (except for SCS cyclone case) which may be because of the accurate presentation of the steering flow by CP scheme. Irrespective of season, the intensity is overestimated in all the cases of cyclone, mainly because of the lower tropospheric and mid-tropospheric parameters are overestimated. YSU PBL scheme used here is responsible for the deep convection in and above PBL. Concentration of frozen hydrometeors at the mid-tropospheric levels and thus the latent heat released during auto conversion of hydrometeors is also responsible for overestimation of intensity.展开更多
An accurate simulation of air temperature at local scales is crucial for the vast majority of weather and climate applications.In this work,a hybrid statistical–dynamical downscaling method and a high-resolution dyna...An accurate simulation of air temperature at local scales is crucial for the vast majority of weather and climate applications.In this work,a hybrid statistical–dynamical downscaling method and a high-resolution dynamical-only downscaling method are applied to daily mean,minimum and maximum air temperatures to investigate the quality of localscale estimates produced by downscaling.These two downscaling approaches are evaluated using station observation data obtained from the Finnish Meteorological Institute over a near-coastal region of western Finland.The dynamical downscaling is performed with the Weather Research and Forecasting(WRF)model,and the statistical downscaling method implemented is the Cumulative Distribution Function-transform(CDF-t).The CDF-t is trained using 20 years of WRF-downscaled Climate Forecast System Reanalysis data over the region at a 3-km spatial resolution for the central month of each season.The performance of the two methods is assessed qualitatively,by inspection of quantile-quantile plots,and quantitatively,through the Cramer-von Mises,mean absolute error,and root-mean-square error diagnostics.The hybrid approach is found to provide significantly more skillful forecasts of the observed daily mean and maximum air temperatures than those of the dynamical-only downscaling(for all seasons).The hybrid method proves to be less computationally expensive,and also to give more skillful temperature forecasts(at least for the Finnish near-coastal region).展开更多
The runoff calculation scheme in the Weather Research and Forecasting(WRF)model is based on an infiltrationexcess surface runoff scheme,which likely leads to an overestimation of soil moisture and an underestimation o...The runoff calculation scheme in the Weather Research and Forecasting(WRF)model is based on an infiltrationexcess surface runoff scheme,which likely leads to an overestimation of soil moisture and an underestimation of surface runoff when heavy rainfall occurs in areas with complex terrain.To overcome this defect,we considered the overland flow process on the grid scale of the WRF model for the first time by coupling a two-dimensional diffusion wave equation into the WRF Noah land surface model(LSM),called the WRF_Overland Flow(WRF_OLF)model.The new WRF model was then utilized to simulate the extreme rainfall that occurred during 19–22 July 2021 near the city of Zhengzhou in central China,which led to an extreme flood event.The results showed that the new WRF model simulated well the convergence and accumulation of overland flow in low-lying areas,changing the distributions of surface runoff and soil moisture and thereby influencing the exchanges of heat and water vapor between the surface and the atmosphere.The local change in non-adiabatic heating at the surface contributed to a decrease in surface pressure and then affected the development of the weather systems associated with the heavy rainfall event.Relative to a remarkable underestimation of rainfall in the original WRF simulation,the maximum rainfall intensity and the cumulative rainfall in the simulation with the new WRF configuration increased by 54.7%and 49.5%,respectively,bringing them closer to their observations.Concurrently,the new WRF model increased the skill for flood prediction.The results of this study provide new insights into the mechanisms of interaction between the land surface and the atmosphere and their roles in helping to predict heavy rainfall and associated flooding in areas of complex topography.展开更多
A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advec- tion fog event over Shanghai Pudong International Airport （ZSPD） with the Weather Research and Fore...A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advec- tion fog event over Shanghai Pudong International Airport （ZSPD） with the Weather Research and Forecasting （WRF） model. Using the current operational settings at the Meteorological Center of East China Air Traffic Manage- ment Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are per- formed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation （both longwave and shortwave） processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, sug- gesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physi- cal processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.展开更多
The Weather Research and Forecasting （WRF） model is used in a regional climate model configuration to simulate past precipitation climate of China during the rainy season （May-September） of 1981-2000, and to inves...The Weather Research and Forecasting （WRF） model is used in a regional climate model configuration to simulate past precipitation climate of China during the rainy season （May-September） of 1981-2000, and to investigate potential future （2041-2060 and 2081-2100） changes in precipitation over China relative to the reference period 1981-2000. WRF is run with initial conditions from a coupled general circulation model, i.e., the high-resolution version of MIROC （Model for Interdisciplinary Research on Climate）. WRF reproduces the observed distribution of rainy season precipitation in 1981-2000 and its interannual variations better than MIROC. MIROC projects increases in rainy season precipitation over most parts of China and decreases of more than 25 mm over parts of Taiwan and central Tibet by the mid-21st century. WRF projects decreases in rainfall over southern Tibetan Plateau, Southwest China, and northwestern part of Northeast China, and increases in rainfall by more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River during 2041-2060. MIROC projects further increases in rainfall over most of China by the end of the 21st century, although simulated rainfall decreases by more than 25 mm over parts of Taiwan, Guangxi, Guizhou, and central Tibet. WRF projects increased rainfall of more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River and decreased rainfall over Southwest China, and southern Tibetan Plateau by the end of the 21st century.展开更多
To improve the weather forecasting over the Beijing area for the 2008 Olympic Games,a triple-nested(27/9/3km) WRFVar/WRF system with 3-h update cycle was established.Experiments have been done for a convective event t...To improve the weather forecasting over the Beijing area for the 2008 Olympic Games,a triple-nested(27/9/3km) WRFVar/WRF system with 3-h update cycle was established.Experiments have been done for a convective event that occurred on August 1,2006.The results showed that the high-resolution rapid update cycle gave a good precipitation forecast;the tunings of background error statistics(BES) and observation-error statistics in WRFVar improved the skill of the precipitation forecast;the BES for the fine domain(3 km) obtained by interpolation from its parent domain(9 km) can be used in 3 km WRFVar as a reasonable approximation.The user can now save a great deal of work related to the derivation of the fine mesh BES from the forecast over a period of time;the rapid update cycle with 3-h frequency has satisfied the forecast,and the update cycle with 1-h frequency was not necessary.展开更多
This work use the global WRF model containing quadruply nesting with which the highest resolution reached 10 km to simulate the typhoons landed on the coast of China in 2011.The model is driven by the reanalysis data ...This work use the global WRF model containing quadruply nesting with which the highest resolution reached 10 km to simulate the typhoons landed on the coast of China in 2011.The model is driven by the reanalysis data fnl with the resolution of 1°x 1°.The study assess the feasibility and applicability of the global WRF model in the 1-7 days prediction of Tropical Cyclone(TC)track by comparing it with the regional WRF model containing the same setting(physical scheme,dynamical frame,model resolution and nesting grid domain).The global model obtain a similar forecast accuracy to the regional model in 1-7 days,with a difference less than 50 km.The forecast accuracy of the global model for 1,2,3,4,5,6 and 7 days is about 70 km,120 km,180 km,240 km,320 km,400 km,and 500 km,respectively.The reason of the significant TC track errors in the forecast more than 3 or 4 days is analyzed,it is due to the poor representation of typhoon and its steering flow under the situation of binary typhoon system.The study show that the global WRF model can be exploited to proceed the high resolution TC simulation and make the TC track forecast up to 7 days but not in the case of multiple typhoon.展开更多
[Objective]Precipitation events caused by Super Typhoon Doksuri in Fujian Province were simulated and evaluated based on the WRF model to provide a reference for typhoon precipitation simulation and forecasting in sou...[Objective]Precipitation events caused by Super Typhoon Doksuri in Fujian Province were simulated and evaluated based on the WRF model to provide a reference for typhoon precipitation simulation and forecasting in southeast coastal areas of China.[Methods]The next-generation mesoscale numerical weather prediction model WRF V4.3(The Weather Research and Forecasting Model)was used to simulate the precipitation caused by Typhoon Doksuri in Fujian Province in 2023.Observations from 86 meteorological stations with hourly rainfall records were used to evaluate the model’s performance.Six evaluation indices were used,including the correlation coefficient(R),root mean square error(RMSE),mean absolute error(MAE),equitable threat score(ETS),probability of detection(POD),and false alarm ratio(FAR).[Results](1)The temporal and spatial evolution of precipitation during Typhoon Doksuri was effectively captured by the WRF model.Precipitation intensity increased gradually from July 27 to 29,2023,with the heaviest rainfall concentrated in the northern and eastern coastal areas of Fujian Province.(2)Significant differences in model performance were observed in terms of R,RMSE,and MAE.The largest errors occurred in Putian City,while smaller errors were found in southwestern Fujian Province.The evaluation result of all six indices showed that the WRF model performed best in simulating daily precipitation compared to hourly,three-hourly,six-hourly,and twelve-hourly precipitation.(3)The R95p index indicated that the WRF model successfully captured the overall spatial distribution of extreme precipitation.However,extreme precipitation intensity was overestimated in certain coastal areas.(4)Despite accurately identifying the coastal regions of Fujian as being most affected,the WRF model failed to accurately simulate the spatial distribution and intensity of precipitation.The simulated precipitation centers showed discrepancies when compared with the observed centers.[Conclusion]Although the WRF model underestimated hourly precipitation,it successfully captured the temporal evolution and spatial distribution of rainfall caused by Typhoon Doksuri in Fujian Province.It reproduced the heavy rainfall centers in central Fujian Province,with daily precipitation peaks reaching up to 350 mm.This highlighted the severity of extreme rainfall caused by Typhoon Doksuri.展开更多
The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(Ca...The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.展开更多
基金supported by the Public Welfare Special Fund Program(Meteorology)of the Chinese Ministry of Finance under Grant No.GYHY201106033
文摘The airflow and dispersion of a pollutant in a complex urban area of Beijing, China, were numerically examined by coupling a Computational Fluid Dynamics （CFD） model with a mesoscale weather model. The models used were Open Source Field Operation and Manipulation （OpenFOAM） software package and Weather Research and Forecasting （WRF） model. OpenFOAM was firstly validated against wind-tunnel experiment data. Then, the WRF model was integrated for 42 h starting from 0800 LST 08 September 2009, and the coupled model was used to compute the flow fields at 1000 LST and 1400 LST 09 September 2009. During the WRF-simulated period, a high pressure system was dominant over the Beijing area. The WRF-simulated local circulations were characterized by mountain valley winds, which matched well with observations. Results from the coupled model simulation demonstrated that the airflows around actual buildings were quite different from the ambient wind on the boundary provided by the WRF model, and the pollutant dispersion pattern was complicated under the influence of buildings. A higher concentration level of the pollutant near the surface was found in both the step-down and step-up notches, but the reason for this higher level in each configurations was different： in the former, it was caused by weaker vertical flow, while in the latter it was caused by a downward-shifted vortex. Overall, the results of this study suggest that the coupled WRF-OpenFOAM model is an important tool that can be used for studying and predicting urban flow and dispersions in densely built-up areas.
基金funded by the National Natural Science Foundation of China[General Project,grant number 41275108]the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA11010404]
文摘Enhancing the ability of the WRF model in simulating a large area covering the West Pacific Ocean, China's Mainland, and the East Indian Ocean is very important to improve prediction of the East Asian monsoon climate. The objective of this study is to identify a reasonable configuration of physical parameterization schemes to simulate the precipitation and temperature in this large area. The Mellor-Yamada-Janjic （MYJ） and Yonsei University （YSU） PBL schemes, the WSM3 and WSM5 microphysics schemes, and the Betts-Miller-Janjic （BMJ） and Tiedtke cumulus schemes are compared through simulation of the regional climate of summer 2008. All cases exhibit a similar spatial distribution of temperature as observed, and the spatial correlation coefficients are all higher than 0.95. The cases combining MY J, WSM3/WSM5, and BMJ have the smallest biases of temperature. The choice of PBL scheme has a significant effect on precipitation in such a large area. The cases with MYJ reproduce a better distribution of rain belts, while YSU strongly overestimates the precipitation intensity. The precipitation simulated using WSM3 is similar to that using WSM5. The BMJ cumulus scheme combined with the MYJ PBL scheme has a smaller bias of precipitation. However, the Tiedtke scheme reproduces the precipitation pattern better, especially over the ITCZ.
基金an R&D project on the development of global numerical weather prediction systems at the Korea Institute of Atmospheric Prediction Systems (KIAPS)Grant CATER 2012-3035 funded by the Korea Meteorological Administration (KMA)
文摘On 21 September 2010, heavy rainfall with a local maximum of 259 mm d-1 occurred near Seoul, South Korea. We examined the ability of the Weather Research and Forecasting （WRF） model in reproducing this disastrous rainfall event and identified the role of two physical processes： planetary boundary layer （PBL） and microphysics （MPS） processes. The WRF model was forced by 6-hourly National Centers for Environmental Prediction （NCEP） Final analysis （FNL） data for 36 hours form 1200 UTC 20 to 0000 UTC 22 September 2010. Twenty-five experiments were performed, consisting of five different PBL schemes--Yonsei University （YSU）, Mellor-Yamada-Janjic （MYJ）, Quasi Normal Scale Elimination （QNSE）, Bougeault and Lacarrere （BouLac）, and University of Washington （UW）--and five different MPS schemes--WRF Single- Moment 6-class （WSM6）, Goddard, Thompson, Milbrandt 2-moments, and Morrison 2-moments. As expected, there was a specific combination of MPS and PBL schemes that showed good skill in forecasting the precipitation. However, there was no specific PBL or MPS scheme that outperformed the others in all aspects. The experiments with the UW PBL or Thompson MPS scheme showed a relatively small amount of precipitation. Analyses form the sensitivity experiments confirmed that the spatial distribution of the simulated precipitation was dominated by the PBL processes, whereas the MPS processes determined the amount of rainfall. It was also found that the temporal evolution of the precipitation was influenced more by the PBL processes than by the MPS processes.
基金National Natural Science Foundation of China(41405062, 41775017)。
文摘Previous studies showed that 4 D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4 D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4 D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously,and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4 D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation,which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4 D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA05110305)
文摘Assessing wind energy is a key step in selecting a site for a wind farm. The accuracy of the assessment is essential for the future operation of the wind farm. There are two main methods for assessing wind power: one is based on observational data and the other relies on mesoscale numerical weather prediction(NWP). In this study, the wind power of the Liaoning coastal wind farm was evaluated using observations from an anemometer tower and simulations by the Weather Research and Forecasting(WRF) model, to see whether the WRF model can produce a valid assessment of the wind power and whether the downscaling process can provide a better evaluation. The paper presents long-term wind data analysis in terms of annual, seasonal, and diurnal variations at the wind farm, which is located on the east coast of Liaoning Province. The results showed that, in spring and summer, the wind speed, wind direction, wind power density, and other main indicators were consistent between the two methods. However, the values of these parameters from the WRF model were significantly higher than the observations from the anemometer tower. Therefore, the causes of the differences between the two methods were further analyzed. There was much more deviation in the original material, National Centers for Environmental Prediction(NCEP) final(FNL) Operational Global Analysis data, in autumn and winter than in spring and summer. As the region is vulnerable to cold-air outbreaks and windy weather in autumn and winter, and the model usually forecasted stronger high or low systems with a longer duration, the predicted wind speed from the WRF model was too large.
文摘The impact of topography on heavy rainfall during two rain seasons was investigated in order to explain their mechanisms on rainfall distribution over Rwanda. Weather Research and Forecasting (WRF-ARW) model was used to study two historical cases of heavy rainfall which took place over Rwanda during two rain seasons, March to May (MAM) and September to December (SOND), from April 7 to 9, 2012 (for MAM) and from October 29 to 31, 2012 (during SOND). The control experiment was done with actual topography, whereas sensitivity experiment was carried out with topography reduced by half. Results show that rainfall distribution over Rwanda significantly changes when topography is reduced. The reduction in topography leads to a decrease in rainfall amounts in both MAM and SOND seasons, with varying magnitudes. This reveals the importance of orography in determining rainfall amounts and distribution over the region. The accumulated rainfall amount from WRF underestimate or overestimate rain gauge stations data by region and by season, but there is good agreement especially in altitude below 1490 m and above 1554 m during April and October respectively. The results may motivate modelling carters to further improve parameterization schemes in the mountainous regions.
基金National Natural Science Foundation (40675005)Science Foundation (QD52)Natural Science Foundation for High Education in Jiangsu Province (06KJB170047)
文摘The Weather Research Forecast model (WRF) configured with high resolution and NCEP 1°×1° reanalysis data were used to simulate the development of a tropical deep convection over the Tiwi Islands,northern Australia,and to investigate the sensitivity of model results to model configuration and parameterization schemes of microphysical processes.The simulation results were compared with available measurements.The results show that the model can reproduce most of the important characteristics of the observed diurnal evolution of the convection,including the initiation of convection along the sea-breeze front,which is then reinforced by downdraft outflows,merging of cells and the formation of a deep convective system.However,further improvement is needed to simulate more accurately the location and the time for initiation of the deep convective system.Sensitivity tests show that double-nesting schemes are more accurate than the non-nesting schemes in predicting the distribution and intensity of precipitation as far as this particular case is concerned.Additionally,microphysical schemes also have an effect on the simulated amount of precipitation.It is shown that the best agreement is reached between the simulation results and observations when the Purdue Lin scheme is used.
文摘Vehicular pollution is becoming significant in urban areas because of increasing population. This is at ground level, so it gives high population exposure. In this study, Chembur, which is the most polluted area in Mumbai city due to industrial and vehicular sources, is selected for vehicular pollution modeling using AMS/EPA Regulatory Model (AERMOD). Meteorological parameters, land use surface characteristics and source emission data are collected as required by AERMOD. The results of modelling depend upon reliability of input data and meteorological data has a vital role in the performance of the model. Generally, temporally and spatially interpolated meteorological data is used in modeling. This is generally collected from nearby meteorological station but this causes inaccuracy of the results. In this paper, the Weather Research and Forecasting (WRF) model has been used to generate onsite data on nine meteorological parameters. The modeling of six roads of Chembur has been performed using above meteorological data. This approach gives good results of traffic modeling. The results of AERMOD are compared with observed air quality which has contribution from all sources in the region and relative contribution of vehicular sources identified.
文摘We investigated the performance of 12 different physics configurations of the climate version of the Weather, Research and Forecasting (WRF) Model over the Middle East and North Africa (MENA) domain. Possible combinations among two Planetary Boundary Layer (PBL), three Cumulus (CUM) and two Microphysics (MIC) schemes were tested. The 2-year simulations (December 1988-November 1990) have been compared with gridded observational data and station measurements for several variables, including total precipitation and maximum and minimum 2-meter air temperature. An objective ranking method of the 12 different simulations and the selection procedure of the best performing configuration for the MENA domain are based on several statistical metrics and carried out for relevant sub-domains and individual stations. The setup for cloud microphysics is found to have the strongest impact on temperature biases while precipitation is most sensitive to the cumulus parameterization scheme and mainly in the tropics.
文摘Meteorological inputs are of great importance when implementing an air quality prediction system. In this contribution, the Weather Research and Forecast (WRF-ARW) model was used to compare the performance of the different cumulus, microphysics and Planet Boundary Layer parameterizations over Bogotá, Colombia. Surface observations were used for comparison and the evaluated meteorological variables include temperature, wind speed and direction and relative humidity. Differences between parameterizations were observed in meteorological variables and Betts-Miller-Janjic, Morrison 2-moment and BouLac schemes proved to be the best parameterizations for cumulus, microphysics and PBL, respectively. As a complement to this study, a WRF-Large Eddy Simulation was conducted in order to evaluate model results with finer horizontal resolution for air quality purposes.
文摘Numerical simulations of four weak cyclonic storms [two cases of pre-monsoon cyclones: Laila (2010), Aila (2009) and two cases of post-monsoon cyclones: Jal (2010), SCS (2003)] are carried out using WRF-ARW mesoscale model. Betts-Miller-Janjic (BMJ) as cumulus parameterization (CP) scheme, Yonsei University(YSU) planetary boundary layer (PBL) scheme and WRF single moment 6 class (WSM6) microphysics (MP) scheme is kept same for all the cyclone cases. Three two-way interactive nested domains [60 km,20 kmand6.6 km] are used with initial and boundary conditions from NCEP Final Analysis data. The model integration is performed to evaluate the track, landfall time and position as well as intensity in terms of Central Sea Level Pressure (CSLP) and Maximum Surface Wind speed (MSW) of the storm. The track and landfall (time and position) of almost all cyclones are well predicted by the model (except for SCS cyclone case) which may be because of the accurate presentation of the steering flow by CP scheme. Irrespective of season, the intensity is overestimated in all the cases of cyclone, mainly because of the lower tropospheric and mid-tropospheric parameters are overestimated. YSU PBL scheme used here is responsible for the deep convection in and above PBL. Concentration of frozen hydrometeors at the mid-tropospheric levels and thus the latent heat released during auto conversion of hydrometeors is also responsible for overestimation of intensity.
基金Botnia-Atlantica, an EU-programme financing cross border cooperation projects in Sweden, Finland and Norway, for their support of this work through the WindCoE project
文摘An accurate simulation of air temperature at local scales is crucial for the vast majority of weather and climate applications.In this work,a hybrid statistical–dynamical downscaling method and a high-resolution dynamical-only downscaling method are applied to daily mean,minimum and maximum air temperatures to investigate the quality of localscale estimates produced by downscaling.These two downscaling approaches are evaluated using station observation data obtained from the Finnish Meteorological Institute over a near-coastal region of western Finland.The dynamical downscaling is performed with the Weather Research and Forecasting(WRF)model,and the statistical downscaling method implemented is the Cumulative Distribution Function-transform(CDF-t).The CDF-t is trained using 20 years of WRF-downscaled Climate Forecast System Reanalysis data over the region at a 3-km spatial resolution for the central month of each season.The performance of the two methods is assessed qualitatively,by inspection of quantile-quantile plots,and quantitatively,through the Cramer-von Mises,mean absolute error,and root-mean-square error diagnostics.The hybrid approach is found to provide significantly more skillful forecasts of the observed daily mean and maximum air temperatures than those of the dynamical-only downscaling(for all seasons).The hybrid method proves to be less computationally expensive,and also to give more skillful temperature forecasts(at least for the Finnish near-coastal region).
基金Supported by the National Key Research and Development Program of China(2023YFF0805300)。
文摘The runoff calculation scheme in the Weather Research and Forecasting(WRF)model is based on an infiltrationexcess surface runoff scheme,which likely leads to an overestimation of soil moisture and an underestimation of surface runoff when heavy rainfall occurs in areas with complex terrain.To overcome this defect,we considered the overland flow process on the grid scale of the WRF model for the first time by coupling a two-dimensional diffusion wave equation into the WRF Noah land surface model(LSM),called the WRF_Overland Flow(WRF_OLF)model.The new WRF model was then utilized to simulate the extreme rainfall that occurred during 19–22 July 2021 near the city of Zhengzhou in central China,which led to an extreme flood event.The results showed that the new WRF model simulated well the convergence and accumulation of overland flow in low-lying areas,changing the distributions of surface runoff and soil moisture and thereby influencing the exchanges of heat and water vapor between the surface and the atmosphere.The local change in non-adiabatic heating at the surface contributed to a decrease in surface pressure and then affected the development of the weather systems associated with the heavy rainfall event.Relative to a remarkable underestimation of rainfall in the original WRF simulation,the maximum rainfall intensity and the cumulative rainfall in the simulation with the new WRF configuration increased by 54.7%and 49.5%,respectively,bringing them closer to their observations.Concurrently,the new WRF model increased the skill for flood prediction.The results of this study provide new insights into the mechanisms of interaction between the land surface and the atmosphere and their roles in helping to predict heavy rainfall and associated flooding in areas of complex topography.
基金Supported by the National Natural Science Foundation of China(4130511 and U1233138)Safety Capability Enhancement Program of Civil Aviation Administration of China(TMSA1605)
文摘A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advec- tion fog event over Shanghai Pudong International Airport （ZSPD） with the Weather Research and Forecasting （WRF） model. Using the current operational settings at the Meteorological Center of East China Air Traffic Manage- ment Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are per- formed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation （both longwave and shortwave） processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, sug- gesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physi- cal processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.
基金Supported by the National (Key) Basic Research and Development (973) Program of China (2009CB421406)Scientific Research Fund of Nanjing University of Information Science & Technology (2012X035)
文摘The Weather Research and Forecasting （WRF） model is used in a regional climate model configuration to simulate past precipitation climate of China during the rainy season （May-September） of 1981-2000, and to investigate potential future （2041-2060 and 2081-2100） changes in precipitation over China relative to the reference period 1981-2000. WRF is run with initial conditions from a coupled general circulation model, i.e., the high-resolution version of MIROC （Model for Interdisciplinary Research on Climate）. WRF reproduces the observed distribution of rainy season precipitation in 1981-2000 and its interannual variations better than MIROC. MIROC projects increases in rainy season precipitation over most parts of China and decreases of more than 25 mm over parts of Taiwan and central Tibet by the mid-21st century. WRF projects decreases in rainfall over southern Tibetan Plateau, Southwest China, and northwestern part of Northeast China, and increases in rainfall by more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River during 2041-2060. MIROC projects further increases in rainfall over most of China by the end of the 21st century, although simulated rainfall decreases by more than 25 mm over parts of Taiwan, Guangxi, Guizhou, and central Tibet. WRF projects increased rainfall of more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River and decreased rainfall over Southwest China, and southern Tibetan Plateau by the end of the 21st century.
文摘To improve the weather forecasting over the Beijing area for the 2008 Olympic Games,a triple-nested(27/9/3km) WRFVar/WRF system with 3-h update cycle was established.Experiments have been done for a convective event that occurred on August 1,2006.The results showed that the high-resolution rapid update cycle gave a good precipitation forecast;the tunings of background error statistics(BES) and observation-error statistics in WRFVar improved the skill of the precipitation forecast;the BES for the fine domain(3 km) obtained by interpolation from its parent domain(9 km) can be used in 3 km WRFVar as a reasonable approximation.The user can now save a great deal of work related to the derivation of the fine mesh BES from the forecast over a period of time;the rapid update cycle with 3-h frequency has satisfied the forecast,and the update cycle with 1-h frequency was not necessary.
基金sponsored by the National Key R&D Program of China(2021YFC3000800)“Research and demonstration application of key physical processes of typhoon variable resolution prediction model”.
文摘This work use the global WRF model containing quadruply nesting with which the highest resolution reached 10 km to simulate the typhoons landed on the coast of China in 2011.The model is driven by the reanalysis data fnl with the resolution of 1°x 1°.The study assess the feasibility and applicability of the global WRF model in the 1-7 days prediction of Tropical Cyclone(TC)track by comparing it with the regional WRF model containing the same setting(physical scheme,dynamical frame,model resolution and nesting grid domain).The global model obtain a similar forecast accuracy to the regional model in 1-7 days,with a difference less than 50 km.The forecast accuracy of the global model for 1,2,3,4,5,6 and 7 days is about 70 km,120 km,180 km,240 km,320 km,400 km,and 500 km,respectively.The reason of the significant TC track errors in the forecast more than 3 or 4 days is analyzed,it is due to the poor representation of typhoon and its steering flow under the situation of binary typhoon system.The study show that the global WRF model can be exploited to proceed the high resolution TC simulation and make the TC track forecast up to 7 days but not in the case of multiple typhoon.
文摘[Objective]Precipitation events caused by Super Typhoon Doksuri in Fujian Province were simulated and evaluated based on the WRF model to provide a reference for typhoon precipitation simulation and forecasting in southeast coastal areas of China.[Methods]The next-generation mesoscale numerical weather prediction model WRF V4.3(The Weather Research and Forecasting Model)was used to simulate the precipitation caused by Typhoon Doksuri in Fujian Province in 2023.Observations from 86 meteorological stations with hourly rainfall records were used to evaluate the model’s performance.Six evaluation indices were used,including the correlation coefficient(R),root mean square error(RMSE),mean absolute error(MAE),equitable threat score(ETS),probability of detection(POD),and false alarm ratio(FAR).[Results](1)The temporal and spatial evolution of precipitation during Typhoon Doksuri was effectively captured by the WRF model.Precipitation intensity increased gradually from July 27 to 29,2023,with the heaviest rainfall concentrated in the northern and eastern coastal areas of Fujian Province.(2)Significant differences in model performance were observed in terms of R,RMSE,and MAE.The largest errors occurred in Putian City,while smaller errors were found in southwestern Fujian Province.The evaluation result of all six indices showed that the WRF model performed best in simulating daily precipitation compared to hourly,three-hourly,six-hourly,and twelve-hourly precipitation.(3)The R95p index indicated that the WRF model successfully captured the overall spatial distribution of extreme precipitation.However,extreme precipitation intensity was overestimated in certain coastal areas.(4)Despite accurately identifying the coastal regions of Fujian as being most affected,the WRF model failed to accurately simulate the spatial distribution and intensity of precipitation.The simulated precipitation centers showed discrepancies when compared with the observed centers.[Conclusion]Although the WRF model underestimated hourly precipitation,it successfully captured the temporal evolution and spatial distribution of rainfall caused by Typhoon Doksuri in Fujian Province.It reproduced the heavy rainfall centers in central Fujian Province,with daily precipitation peaks reaching up to 350 mm.This highlighted the severity of extreme rainfall caused by Typhoon Doksuri.
基金National Public Benefit Research Foundation of China (2008416048GYHY201006035)
文摘The results from a hybrid approach that combines a mesoscale meteorological model with a diagnostic model to produce high-resolution wind fields in complex coastal topography are evaluated.The diagnostic wind model(California Meteorological Model,CALMET) with 100-m horizontal spacing was driven with outputs from the Weather Research and Forecasting(WRF) model to obtain near-surface winds for the 1-year period from 12 September 2003 to 11 September 2004.Results were compared with wind observations at four sites.Traditional statistical scores,including correlation coefficients,standard deviations(SDs) and mean absolute errors(MAEs),indicate that the wind estimates from the WRF/CALMET modeling system are produced reasonably well.The correlation coefficients are relatively large,ranging from 0.5 to 0.7 for the zonal wind component and from 0.75 to 0.85 for the meridional wind component.MAEs for wind speed range from 1.5 to 2.0 m s-1 at 10 meters above ground level(AGL) and from 2.0 to 2.5 m s-1 at 60 m AGL.MAEs for wind direction range from 30 to 40 degrees at both levels.A spectral decomposition of the time series of wind speed shows positive impacts of CALMET in improving the mesoscale winds.Moreover,combining the CALMET model with WRF significantly improves the spatial variability of the simulated wind fields.It can be concluded that the WRF/CALMET modeling system is capable of providing a detailed near-surface wind field,but the physics in the diagnostic CALMET model needs to be further improved.
