复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流...复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流体动力学(computational fluid dynamics,CFD)技术,构建一套WRF-CFD模式耦合的复杂地形风电场非定常仿真方法。以国际经典案例Askervein山和Bolund岛为验证对象,研究复杂地形流场中平均风速和湍流强度的分布特征,并简要分析复杂地形中风力机布置策略。结果表明,基于WRF-CFD模式的数值模拟结果与实验观测值有较好的一致性,且优于中尺度数值模拟结果,在选取的特征点位置,风速绝对误差均在2 m/s以内。结果可为风力机的设计、布局、载荷评估及风电场运行控制提供一定参考。展开更多
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
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
Accurate wind modeling is important for wind resources assessment and wind power forecasting. To improve the WRF model configuration for the offshore wind modeling over the Baltic Sea, this study performed a sensitivi...Accurate wind modeling is important for wind resources assessment and wind power forecasting. To improve the WRF model configuration for the offshore wind modeling over the Baltic Sea, this study performed a sensitivity study of the WRF model to multiple model configurations, including domain setup,grid resolution, sea surface temperature, land surface data, and atmosphere-wave coupling. The simulated offshore wind was evaluated against LiDAR observations under different wind directions, atmospheric stabilities, and sea status. Generally, the simulated wind profiles matched observations, despite systematic underestimations. Strengthening the forcing from the reanalysis data through reducing the number of nested domains played the largest role in improving wind modeling. Atmosphere-wave coupling further improved the simulated wind, especially under the growing and mature sea conditions.Increasing the vertical resolution, and updating the sea surface temperature and the land surface information only had a slight impact, mainly visible during very stable conditions. Increasing the horizontal resolution also only had a slight impact, most visible during unstable conditions. Our study can help to improve the wind resources assessment and wind power forecasting over the Baltic Sea.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
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
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
Generation of waves is affected by forces that exerted constantly in the oceans. The most obvious reason for the appearance of surface-waves is a process of interaction between atmosphere and sea surface that results ...Generation of waves is affected by forces that exerted constantly in the oceans. The most obvious reason for the appearance of surface-waves is a process of interaction between atmosphere and sea surface that results in wind generation. Wave predictions are usually issued for a maximum of a few days for using in different fields such as shipping, fishing, oil industry, tourism, and to increase the safety of seafarers and beach habitants, maintaining economic assets and optimal utilization of natural resources. In this study, SWAN model has been run for this research over the Oman sea and the Persian Gulf. For implementation of SWAN, another dynamic model with prediction ability of 99-hours also has been used. In this example, wind field is obtained from the outputs of the WRF model converted to the required format for SWAN model. The computational network of SWAN model has been set to spatial grid points of 6 minutes with 1-hour temporal scale. Standard validation ways, including experimental verification, Multiplicative Bias, Mean Error and Root Mean Square Error are used in this study by comparing together for evaluation of accuracy of the model outputs. The results show that the prediction of wave heights by the model for 9 to 24-hour prediction could be the most accurate.展开更多
A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale ...A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.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
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
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
Two land surface models, Community Land Model (CLM3.5) and NOAH model, have been coupled to the Weather Research and Forecasting (WRF) model and been used to simulate the precipitation, temperature, and circulation fi...Two land surface models, Community Land Model (CLM3.5) and NOAH model, have been coupled to the Weather Research and Forecasting (WRF) model and been used to simulate the precipitation, temperature, and circulation fields, respectively, over eastern China in a typical flood year (1998). The purpose of this study is to reveal the effects of land surface changes on regional climate modeling. Comparisons of simulated results and observation data indicate that changes in land surface processes have significant impact on spatial and temporal distribution of precipitation and temperature patterns in eastern China. Coupling of the CLM3.5 to the WRF model (experiment WRF-C) substantially improves the simulation results over eastern China relative to an older version of WRF coupled to the NOAH-LSM (experiment WRF-N). It is found that the simulation of the spatial pattern of summer precipitation in WRF-C is better than in WRF-N. WRF-C also significantly reduces the summer positive bias of surface air temperature, and its simulated surface air temperature matches more closely to observations than WRF-N does, which is associated with lower sensible heat fluxes and higher latent heat fluxes in WRF-C.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
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
为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Envi...为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)的FNL全球再分析资料(Final Operational Global Analysis)、先进星载热发射和反射辐射仪全球数字高程模型以及兰州中川机场的实况观测资料,采用中尺度数值天气预报模式(Weather Research and Forecasting Model,WRF)、WRF结合计算流体动力学(Computational Fluid Dynamics,CFD)方法、长短期神经网络(Long Short-Term Memory,LSTM)方法,对2021年4月15-16日兰州中川机场的两次风切变过程进行模拟分析。结果表明:(1)在小于1 km的网格中使用大涡模拟,WRF模式在单个站点风速模拟任务中表现更好,但在近地面水平风场风速模拟效果上,不如WRF模式结合计算流体力学模型方案;(2)对于飞机降落过程中遭遇的两次低空风切变的模拟,WRF-LES和WRF-CFD两种模式都可以模拟出第一次低空风切变,而第二次受传入模式的WRF风速数据值较小的影响,两种模式风速差都没有达到阈值,需要在后续工作中进一步验证;(3)低风速条件(6 m·s^(-1))下,基于LSTM的单变量风速预测模型平均绝对误差基本维持在0.59 m·s^(-1),能较好地把握不同地形与环流背景条件下风速变化的非线性关系,虽然受到WRF误差和观测要素不全的限制,多变量风速预测能在保证平均绝对百分比误差小于6.60%的情况下,以更高的计算效率和泛化能力实现风速预测。本文不仅验证了WRF-CFD和WRF-LES耦合方案在风场和低空风切变预报中的差异,还探讨了基于LSTM的风速预测的可行性和准确性,期望为提高风场模拟精度,缩短精细风场模拟时间提供新的视角和方法。展开更多
文摘复杂地形风电场流动具有强烈的非定常现象和多尺度特征,其准确模拟是风资源精细化评估的难点。为兼顾宏观中尺度大气环流和微观非定常流动细节,该文结合中尺度气象研究与预报(weather research and forecasting,WRF)模式和微尺度计算流体动力学(computational fluid dynamics,CFD)技术,构建一套WRF-CFD模式耦合的复杂地形风电场非定常仿真方法。以国际经典案例Askervein山和Bolund岛为验证对象,研究复杂地形流场中平均风速和湍流强度的分布特征,并简要分析复杂地形中风力机布置策略。结果表明,基于WRF-CFD模式的数值模拟结果与实验观测值有较好的一致性,且优于中尺度数值模拟结果,在选取的特征点位置,风速绝对误差均在2 m/s以内。结果可为风力机的设计、布局、载荷评估及风电场运行控制提供一定参考。
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.
基金This project was funded by Energimyndigheten[Grant No.47054-1]funded by the Swedish Research Council[Grant No.2012-03902]+4 种基金Uppsala Universitypart of the Swedish strategic research program StandUp for Windsupported by Formas project[2017-00516]Laboratory for Regional Oceanography and Numerical Modeling,Qingdao National Laboratory for Marine Science and Technology[No.2019B04)partially funded by the Swedish Research Council through grant agreement[No.2018-05973]。
文摘Accurate wind modeling is important for wind resources assessment and wind power forecasting. To improve the WRF model configuration for the offshore wind modeling over the Baltic Sea, this study performed a sensitivity study of the WRF model to multiple model configurations, including domain setup,grid resolution, sea surface temperature, land surface data, and atmosphere-wave coupling. The simulated offshore wind was evaluated against LiDAR observations under different wind directions, atmospheric stabilities, and sea status. Generally, the simulated wind profiles matched observations, despite systematic underestimations. Strengthening the forcing from the reanalysis data through reducing the number of nested domains played the largest role in improving wind modeling. Atmosphere-wave coupling further improved the simulated wind, especially under the growing and mature sea conditions.Increasing the vertical resolution, and updating the sea surface temperature and the land surface information only had a slight impact, mainly visible during very stable conditions. Increasing the horizontal resolution also only had a slight impact, most visible during unstable conditions. Our study can help to improve the wind resources assessment and wind power forecasting over the Baltic Sea.
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.
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.
文摘Generation of waves is affected by forces that exerted constantly in the oceans. The most obvious reason for the appearance of surface-waves is a process of interaction between atmosphere and sea surface that results in wind generation. Wave predictions are usually issued for a maximum of a few days for using in different fields such as shipping, fishing, oil industry, tourism, and to increase the safety of seafarers and beach habitants, maintaining economic assets and optimal utilization of natural resources. In this study, SWAN model has been run for this research over the Oman sea and the Persian Gulf. For implementation of SWAN, another dynamic model with prediction ability of 99-hours also has been used. In this example, wind field is obtained from the outputs of the WRF model converted to the required format for SWAN model. The computational network of SWAN model has been set to spatial grid points of 6 minutes with 1-hour temporal scale. Standard validation ways, including experimental verification, Multiplicative Bias, Mean Error and Root Mean Square Error are used in this study by comparing together for evaluation of accuracy of the model outputs. The results show that the prediction of wave heights by the model for 9 to 24-hour prediction could be the most accurate.
基金jointly supported by the Main Direction Program of Knowledge Innovation of the Chinese Academy of Sciences(Grant No.KZCX2EW203)the National Key Basic Research Program of China(Grant No.2013CB430105)the National Department of Public Benefit Research Foundation(Grant No.GYHY201006031)
文摘A new method for driving a One-Dimensional Stratiform Cold （1DSC） cloud model with Weather Research and Fore casting （WRF） model outputs was developed by conducting numerical experiments for a typical large-scale stratiform rainfall event that took place on 4-5 July 2004 in Changchun, China. Sensitivity test results suggested that, with hydrometeor pro files extracted from the WRF outputs as the initial input, and with continuous updating of soundings and vertical velocities （including downdraft） derived from the WRF model, the new WRF-driven 1DSC modeling system （WRF-1DSC） was able to successfully reproduce both the generation and dissipation processes of the precipitation event. The simulated rainfall intensity showed a time-lag behind that observed, which could have been caused by simulation errors of soundings, vertical velocities and hydrometeor profiles in the WRF output. Taking into consideration the simulated and observed movement path of the precipitation system, a nearby grid point was found to possess more accurate environmental fields in terms of their similarity to those observed in Changchun Station. Using profiles from this nearby grid point, WRF-1DSC was able to repro duce a realistic precipitation pattern. This study demonstrates that 1D cloud-seeding models do indeed have the potential to predict realistic precipitation patterns when properly driven by accurate atmospheric profiles derived from a regional short range forecasting system, This opens a novel and important approach to developing an ensemble-based rain enhancement prediction and operation system under a probabilistic framework concept.
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.
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.
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 Basic Research Program of China (2012CB956203)State Key Program of National Natural Science of China (40830956)
文摘Two land surface models, Community Land Model (CLM3.5) and NOAH model, have been coupled to the Weather Research and Forecasting (WRF) model and been used to simulate the precipitation, temperature, and circulation fields, respectively, over eastern China in a typical flood year (1998). The purpose of this study is to reveal the effects of land surface changes on regional climate modeling. Comparisons of simulated results and observation data indicate that changes in land surface processes have significant impact on spatial and temporal distribution of precipitation and temperature patterns in eastern China. Coupling of the CLM3.5 to the WRF model (experiment WRF-C) substantially improves the simulation results over eastern China relative to an older version of WRF coupled to the NOAH-LSM (experiment WRF-N). It is found that the simulation of the spatial pattern of summer precipitation in WRF-C is better than in WRF-N. WRF-C also significantly reduces the summer positive bias of surface air temperature, and its simulated surface air temperature matches more closely to observations than WRF-N does, which is associated with lower sensible heat fluxes and higher latent heat fluxes in WRF-C.
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.
文摘为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)的FNL全球再分析资料(Final Operational Global Analysis)、先进星载热发射和反射辐射仪全球数字高程模型以及兰州中川机场的实况观测资料,采用中尺度数值天气预报模式(Weather Research and Forecasting Model,WRF)、WRF结合计算流体动力学(Computational Fluid Dynamics,CFD)方法、长短期神经网络(Long Short-Term Memory,LSTM)方法,对2021年4月15-16日兰州中川机场的两次风切变过程进行模拟分析。结果表明:(1)在小于1 km的网格中使用大涡模拟,WRF模式在单个站点风速模拟任务中表现更好,但在近地面水平风场风速模拟效果上,不如WRF模式结合计算流体力学模型方案;(2)对于飞机降落过程中遭遇的两次低空风切变的模拟,WRF-LES和WRF-CFD两种模式都可以模拟出第一次低空风切变,而第二次受传入模式的WRF风速数据值较小的影响,两种模式风速差都没有达到阈值,需要在后续工作中进一步验证;(3)低风速条件(6 m·s^(-1))下,基于LSTM的单变量风速预测模型平均绝对误差基本维持在0.59 m·s^(-1),能较好地把握不同地形与环流背景条件下风速变化的非线性关系,虽然受到WRF误差和观测要素不全的限制,多变量风速预测能在保证平均绝对百分比误差小于6.60%的情况下,以更高的计算效率和泛化能力实现风速预测。本文不仅验证了WRF-CFD和WRF-LES耦合方案在风场和低空风切变预报中的差异,还探讨了基于LSTM的风速预测的可行性和准确性,期望为提高风场模拟精度,缩短精细风场模拟时间提供新的视角和方法。
