Food and non-alcoholic beverages are highly important for individuals to continue staying alive and living healthy lives. The increase in the prices of food and non-alcoholic beverages experienced across the world ove...Food and non-alcoholic beverages are highly important for individuals to continue staying alive and living healthy lives. The increase in the prices of food and non-alcoholic beverages experienced across the world over years has continued to make food and non-alcoholic beverages not to be accessible and affordable to individuals and families having a low income. The aim of this particular research study was to identify how Kenya’s CPI of food and non-alcoholic beverages could be modelled using Autoregressive Integrated Moving Average (ARIMA) models for forecasting future values for the next two years. The data used for the study was that of Kenya’s CPI of food and non-alcoholic beverages for the period starting from February 2009 to April 2024 obtained from the International Monetary Fund (IMF) database. The best specification for the ARIMA model was identified using Akaike Information Criterion (AIC), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and mean absolute scaled error (MASE) and assessing whether residuals of the model were independent and normally distributed with a variance that is constant an whether the model has most of its coefficients being significant statistically. ARIMA (3, 1, 0) (1, 0, 0) model was identified as the best ARIMA model for modeling Kenya’s CPI of food and non-beverages for forecasting future values among the ARIMA models considered. Using this particular model, Kenya’s CPI of food and non-alcoholic beverages was forecasted to increase only slightly with time to reach a value of about 165.70 by March 2026.展开更多
The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Lium...The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.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
[Objective] The aim was to analyze characters of solar energy in photo- voltaic power stations in Shandong Province. [Method] The models of total solar radiation and scattered radiation were determined, and solar ener...[Objective] The aim was to analyze characters of solar energy in photo- voltaic power stations in Shandong Province. [Method] The models of total solar radiation and scattered radiation were determined, and solar energy resources in pho-tovoltaic power stations were evaluated based on illumination in horizontal plane and cloud data in 123 counties or cities and observed information in Jinan, Fushan and Juxian in 1988-2008. [Result] Solar energy in northern regions in Shandong proved most abundant, which is suitable for photovoltaic power generation; the optimal angle of tilt of photovoltaic array was at 35°, decreasing by 2°-3° compared with local latitude. Total solar radiation received by the slope with optimal angle of tilt exceeded 1 600 kw.h/（m2.a）, increasing by 16% compared with horizontal planes. The maximal irradiance concluded by WRF in different regions tended to be volatile in 1 020-1 060 W/m2. [Conclusion] The research provides references for construction of photovoltaic power stations in Shandong Province.展开更多
Two intense quasi-linear mesoscale convective systems（QLMCSs） in northern China were simulated using the WRF（Weather Research and Forecasting） model and the 3D-Var（three-dimensional variational） analysis system ...Two intense quasi-linear mesoscale convective systems（QLMCSs） in northern China were simulated using the WRF（Weather Research and Forecasting） model and the 3D-Var（three-dimensional variational） analysis system of the ARPS（Advanced Regional Prediction System） model.A new method in which the lightning density is calculated using both the precipitation and non-precipitation ice mass was developed to reveal the relationship between the lightning activities and QLMCS structures.Results indicate that,compared with calculating the results using two previous methods,the lightning density calculated using the new method presented in this study is in better accordance with observations.Based on the calculated lightning densities using the new method,it was found that most lightning activity was initiated on the right side and at the front of the QLMCSs,where the surface wind field converged intensely.The CAPE was much stronger ahead of the southeastward progressing QLMCS than to the back it,and their lightning events mainly occurred in regions with a large gradient of CAPE.Comparisons between lightning and non-lightning regions indicated that lightning regions featured more intense ascending motion than non-lightning regions;the vertical ranges of maximum reflectivity between lightning and non-lightning regions were very different;and the ice mixing ratio featured no significant differences between the lightning and non-lightning regions.展开更多
Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall eve...Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall event on 20–21 April 2010.The simulation output was compared with precipitation and aircraft observations.The aircraft-observed moderate-rimed dendrites and plates indicated that riming contributed significantly to ice particle growth at the mature precipitation stage.Observations of dendrite aggregation and capped columns suggested that aggregation coexisted with deposition or riming and played an important role in producing many large particles.The domain-averaged values of the 24-h surface precipitation accumulation from the two schemes were quite close to each other.However,differences existed in the temporal and spatial evolutions of the precipitation distribution.An analysis of the surface precipitation temporal evolution indicated faster precipitation in Morrison,while P3 indicated slower rainfall by shifting the precipitation pattern eastward toward what was observed.The differences in precipitation values between the two schemes were related to the cloud water content distribution and fall speeds of rimed particles.P3 simulated the stratiform precipitation event better as it captured the gradual transition in the mass-weighted fall speeds and densities from unrimed to rimed particles.展开更多
We used a weather research and forecasting model to simulate a torrential rainstorm that occurred in Xinjiang,China during June 16–17,2016.The model successfully simulated the rainfall area,precipitation intensity,an...We used a weather research and forecasting model to simulate a torrential rainstorm that occurred in Xinjiang,China during June 16–17,2016.The model successfully simulated the rainfall area,precipitation intensity,and changes in precipitation.We identified a clear wave signal using the two-dimensional fast Fourier transform method;the waves propagated westwards,with wavelengths of 45–20 km,periods of 50–120 min,and phase velocities mainly concentrated in the-25 m/s to-10 m/s range.The results of wavelet cross-spectral analysis further confirmed that the waves were gravity waves,peaking at 11:00 UTC,June 17,2016.The gravity wave signal was identified along 79.17–79.93°E,81.35–81.45°E and 81.5–81.83°E.The gravity waves detected along 81.5–81.83°E corresponded well with precipitation that accumulated in 1 h,indicating that gravity waves could be considered a rainstorm precursor in future precipitation forecasts.展开更多
This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weat...This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.展开更多
This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between th...This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.展开更多
The central region of Argentina is known to be a source of some most extreme weather events in the world,which are partially associated with the passage of cold fronts accompanied often by extreme wind gusts.This may ...The central region of Argentina is known to be a source of some most extreme weather events in the world,which are partially associated with the passage of cold fronts accompanied often by extreme wind gusts.This may cause severe property damage and even loss of human life.Nevertheless,there is a lack of studies that evaluate the performance of the numerical weather prediction(NWP)models such as weather research and forecasting(WRF)model in anticipating this type of weather in the region.This study compares the performance of the operational WRF in Argentina using four combinations of various planetary boundary layer(PBL)and microphysics parameterization schemes under varied lead times in predicting an extreme wind event(gusts>30 m s^(-1))in Central Argentina.The results demonstrate that the WRF model is capable of providing an acceptable prediction of wind speed during an extreme event.It is found that no single combination outperforms the others,although there is a slight tendency for Combination A,which utilizes the Mellor-Yamada-Janjic(MYJ)parameterization for the PBL and the Eta similarity parameterization for the surface layer,to more accurately capture the extreme wind speed.Compared with wind gust observations at five weather stations,the wind gust parameterization predicted the intensity and occurrence time of the peak wind,with an acceptable bias(time of peak<±1 h).Analysis of grid configurations(resolutions of 4 vs 9/3/1 km)revealed that higher resolution does not imply an improvement in the wind gust forecast for this particular event.With regard to lead time,a shorter lead time does not necessarily result in more accurate forecasts.Nevertheless,it is beneficial to conduct multiple sensitivity runs in order to obtain and understand the dispersion of forecasted wind speeds.展开更多
The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model...The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA （China Meteorological Administration） and hourly meteorological observation data from seven sites of WATER （Watershed Airborne Telemetry Experimental Research） are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE （Mean Bias Error） of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were -0.19 ℃, -4.49 hPa, 4.08% and 0.92 m/s, the average RMSE （Root Mean Square Error） of them were 2.11 ℃, 5.37 hPa, 9.55% and 1.73 m/s, and the average R （correlation coefficient） of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were-0.16 ℃,-6.62 hPa,-5.14%, 0.26 m/s, 33.0 W/m^2 and-6.44 W/m^2, the average RMSE of them were 2.62 ℃, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m^2 and 53.5 W/m^2, and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained： （1） regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; （2） the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; （3） both wind speed and rainfall simulated from WRF model did not agree well with observation data.展开更多
With economic development and rapid urbanization,increases in Gross Domestic Product and population in fastgrowing cities since the turn of the 21st Century have led to increases in energy consumption.Anthropogenic he...With economic development and rapid urbanization,increases in Gross Domestic Product and population in fastgrowing cities since the turn of the 21st Century have led to increases in energy consumption.Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events.To investigate the effects of energy consumption on urban extreme temperature events,including extreme heat and cold events,a dynamic representation scheme of anthropogenic heat release(AHR)was implemented in the Advanced Research version of the Weather Research and Forecasting(WRF)model,and AHR data were developed based on energy consumption and population density in a case study of Beijing,China.Two simulations during 1999−2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme.It was shown that the mean temperature increased with the increase in AHR,and more frequent extreme heat events were produced,with an annual increase of 0.02−0.19 days,as well as less frequent extreme cold events,with an annual decrease of 0.26−0.56 days,based on seven extreme temperature indices in the city center.AHR increased the sensible heat flux and led to surface energy budget changes,strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter.In addition,it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.展开更多
Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions b...Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.展开更多
The effects of different Planetary Boundary Layer（PBL） structures on pollutant dispersion processes within two idealized street canyon configurations and a realistic urban area were numerically examined by a Computa...The effects of different Planetary Boundary Layer（PBL） structures on pollutant dispersion processes within two idealized street canyon configurations and a realistic urban area were numerically examined by a Computational Fluid Dynamics（CFD） model. The boundary conditions of different PBL structures/conditions were provided by simulations of the Weather Researching and Forecasting model. The simulated results of the idealized 2D and 3D street canyon experiments showed that the increment of PBL instability favored the downward transport of momentum from the upper flow above the roof to the pedestrian level within the street canyon. As a result, the flow and turbulent fields within the street canyon under the more unstable PBL condition are stronger. Therefore, more pollutants within the street canyon would be removed by the stronger advection and turbulent diffusion processes under the unstable PBL condition. On the contrary, more pollutants would be concentrated in the street canyon under the stable PBL condition. In addition, the simulations of the realistic building cluster experiments showed that the density of buildings was a crucial factor determining the dynamic effects of the PBL structure on the flow patterns. The momentum field within a denser building configuration was mostly transported from the upper flow, and was more sensitive to the PBL structures than that of the sparser building configuration. Finally, it was recommended to use the Mellor-Yamada-Nakanishi-Niino（MYNN） PBL scheme, which can explicitly output the needed turbulent variables, to provide the boundary conditions to the CFD simulation.展开更多
The weather research and forecasting（WRF） model is a new generation mesoscale numerical model with a fine grid resolution（2 km）, making it ideal to simulate the macro-and micro-physical processes and latent heatin...The weather research and forecasting（WRF） model is a new generation mesoscale numerical model with a fine grid resolution（2 km）, making it ideal to simulate the macro-and micro-physical processes and latent heating within Typhoon Molave（2009）. Simulations based on a single-moment, six-class microphysical scheme are shown to be reasonable, following verification of results for the typhoon track, wind intensity, precipitation pattern, as well as inner-core thermodynamic and dynamic structures. After calculating latent heating rate, it is concluded that the total latent heat is mainly derived from condensation below the zero degree isotherm, and from deposition above this isotherm. It is revealed that cloud microphysical processes related to graupel are the most important contributors to the total latent heat. Other important latent heat contributors in the simulated Typhoon Molave are condensation of cloud water, deposition of cloud ice, deposition of snow, initiation of cloud ice crystals, deposition of graupel, accretion of cloud water by graupel, evaporation of cloud water and rainwater,sublimation of snow, sublimation of graupel, melting of graupel, and sublimation of cloud ice. In essence, the simulated latent heat profile is similar to ones recorded by the Tropical Rainfall Measuring Mission, although specific values differ slightly.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
The maximum height of the convective boundary layer(CBL)over the Taklimakan Desert can exceed 5000 m during summer and plays a crucial role in the regional circulation and weather.We combined the Weather Research and ...The maximum height of the convective boundary layer(CBL)over the Taklimakan Desert can exceed 5000 m during summer and plays a crucial role in the regional circulation and weather.We combined the Weather Research and Forecasting Large Eddy Simulation(WRF-LES)with data from Global Positioning System(GPS)radiosondes and from eddy covariance stations to evaluate the performance of the WRF-LES in simulating the characteristics of the deep CBL over the central Taklimakan Desert.The model reproduced the evolution of the CBL processes reasonably well,but the simulations generated warmer and moister conditions than the observation as a result of the over-prediction of surface fluxes and large-scale advection.Further simulations were performed with multiple configurations and sensitivity tests.The sensitivity tests for the lateral boundary conditions(LBCs)showed that the model results are sensitive to changes in the time resolution and domain size of the specified LBCs.A larger domain size varies the distance of the area of interest from the LBCs and reduces the influence of large forecast errors near the LBCs.Comparing the model results using the original parameterization of sensible heat flux with the Noah land surface scheme and those of the sensitivity experiments showed that the desert CBL is sensitive to the sensible heat flux produced by the land surface scheme during daytime in summer.A reduction in the sensible heat flux can correct overestimates of the potential temperature profile.However,increasing the sensible heat flux significantly reduces the total time needed to increase the CBL to a relatively low altitude(<3 km)in the middle and initial stages of the development of the CBL rather than producing a higher CBL in the later stages.展开更多
This study investigated the performance of the mesoscale Weather Research and Forecasting(WRF) model in predicting near-surface atmospheric temperature and wind for a complex underlying surface in Northwest China in J...This study investigated the performance of the mesoscale Weather Research and Forecasting(WRF) model in predicting near-surface atmospheric temperature and wind for a complex underlying surface in Northwest China in June and December 2015. The spatial distribution of the monthly average bias errors in the forecasts of 2-m temperature and 10-m wind speed is analyzed first. It is found that the forecast errors for 2-m temperature and 10-m wind speed in June are strongly correlated with the terrain distribution. However, this type of correlation is not apparent in December, perhaps due to the inaccurate specification of the surface albedo and freezing-thawing process of frozen soil in winter in Northwest China in the WRF model. In addition, the WRF model is able to reproduce the diurnal variation in 2-m temperature and 10-m wind speed, although with weakened magnitude. Elevations and land-use types have strong influences on the forecast of near-surface variables with seasonal variations. The overall results imply that accurate specification of the complex underlying surface and seasonal changes in land cover is necessary for improving near-surface forecasts over Northwest China.展开更多
The relationship between the radar reflectivity factor （Z） and the rainfall rate （R） is recalculated based on radar ob- servations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather ...The relationship between the radar reflectivity factor （Z） and the rainfall rate （R） is recalculated based on radar ob- servations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather stations over the Yangtze-Huaihe River basin. The data were collected by the National 973 Project from June to July 2013 for severe convective weather events. The Z-R relationship is combined with an empirical qr-R relationship to obtain a new Z-qr relationship, which is then used to correct the observational operator for radar reflectivity in the three-dimensional variational （3DVar） data assimilation system of the Weather Research and Forecasting （WRF） model to im-prove the analysis and prediction of severe convective weather over the Yangtze--Huaihe River basin. The perform- ance of the corrected reflectivity operator used in the WRF 3DVar data assimilation system is tested with a heavy rain event that occurred over Jiangsu and Anhui provinces and the surrounding regions on 23 June 2013. It is noted that the observations for this event are not included in the calculation of the Z-R relationship. Three experiments are conducted with the WRF model and its 3DVar system, including a control run without the assimilation of reflectivity data and two assimilation experiments with the original and corrected refleetivity operators. The experimental results show that the assimilation of radar reflectivity data has a positive impact on the rainfall forecast within a few hours with either the original or corrected reflectivity operators, but the corrected reflectivity operator achieves a better per-forrnance on the rainfall forecast than the original operator. The corrected reflectivity operator extends the effective time of radar data assimilation for the prediction of strong reflectivity. The physical variables analyzed with the corrected reflectivity operator present more reasonable mesoscale structures than those obtained with the original re-flectivity operator. This suggests that the new statistical Z-R relationship is more suitable for predicting severe con- vective weather over the Yangtze-Huaihe River basin than the Z-R relationships currently in use.展开更多
Land use data with building characteristics are important for modeling the impacts of urban morphology on local climate.In this study,an extreme heat event in Shanghai,China,was simulated by using a WRF/BEP+BEM(Weathe...Land use data with building characteristics are important for modeling the impacts of urban morphology on local climate.In this study,an extreme heat event in Shanghai,China,was simulated by using a WRF/BEP+BEM(Weather Research and Forecasting/Building Effect Parameterization+Building Energy Model)model.We incorporated local climate zone(LCZ)land use data that resolved urban morphology using 10 classes of building parameters.The simulation was compared to a control case based on MODIS(Moderate-resolution Imaging Spectroradiometer)land use data.The findings are as follows:(1)the LCZ data performed better than the MODIS data for simulating 10-m wind speed.An increase in building height led to the wind speed to decrease by 0.6-1.4 m s^(-1)in the daytime and by 0.2-0.7 m s^(-1)at nighttime.(2)High-rise buildings warmed the air by trapping radiation in the urban canyon.This warming effect was partially offset by the cooling effect of building shadows in the day.As a result,the 2-m temperature increased by 0.8℃ at night but only by 0.4℃ during the day.(3)Heterogeneous urban surfaces increased the 50-m turbulent kinetic energy by 0.4 m^(2) s^(-2),decreased the 10-m wind speed by 1.8 m s^(-1)in the daytime,increased the surface net radiation by 45.1 W m^(2)-,and increased the 2-m temperature by 1.5℃ at nighttime.(4)The LCZ data modified the atmospheric circulation between land and ocean.The shadowing effect reduced the air temperature differences between land and ocean and weakened the sea breeze.Moreover,high-rise buildings obstructed sea breezes,restricting their impact to a smaller portion(10 km along the wind direction)of inland areas compared to that with MODIS.展开更多
文摘Food and non-alcoholic beverages are highly important for individuals to continue staying alive and living healthy lives. The increase in the prices of food and non-alcoholic beverages experienced across the world over years has continued to make food and non-alcoholic beverages not to be accessible and affordable to individuals and families having a low income. The aim of this particular research study was to identify how Kenya’s CPI of food and non-alcoholic beverages could be modelled using Autoregressive Integrated Moving Average (ARIMA) models for forecasting future values for the next two years. The data used for the study was that of Kenya’s CPI of food and non-alcoholic beverages for the period starting from February 2009 to April 2024 obtained from the International Monetary Fund (IMF) database. The best specification for the ARIMA model was identified using Akaike Information Criterion (AIC), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and mean absolute scaled error (MASE) and assessing whether residuals of the model were independent and normally distributed with a variance that is constant an whether the model has most of its coefficients being significant statistically. ARIMA (3, 1, 0) (1, 0, 0) model was identified as the best ARIMA model for modeling Kenya’s CPI of food and non-beverages for forecasting future values among the ARIMA models considered. Using this particular model, Kenya’s CPI of food and non-alcoholic beverages was forecasted to increase only slightly with time to reach a value of about 165.70 by March 2026.
基金Ministry of Science and Technology of China(2017YFC1501406)National Key Research and Development Plan Program of China(2017YFA0604500)CMA Youth Founding Program(Q201706&NWPC-QNJJ-201702)
文摘The basic structure and cloud features of Typhoon Nida(2016) are simulated using a new microphysics scheme(Liuma) within the Weather Research and Forecasting(WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly-used microphysics scheme(WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme,it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.
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.
基金Supported by Shandong Meteorological Bureau Key Project (2010sdqxj105)~~
文摘[Objective] The aim was to analyze characters of solar energy in photo- voltaic power stations in Shandong Province. [Method] The models of total solar radiation and scattered radiation were determined, and solar energy resources in pho-tovoltaic power stations were evaluated based on illumination in horizontal plane and cloud data in 123 counties or cities and observed information in Jinan, Fushan and Juxian in 1988-2008. [Result] Solar energy in northern regions in Shandong proved most abundant, which is suitable for photovoltaic power generation; the optimal angle of tilt of photovoltaic array was at 35°, decreasing by 2°-3° compared with local latitude. Total solar radiation received by the slope with optimal angle of tilt exceeded 1 600 kw.h/（m2.a）, increasing by 16% compared with horizontal planes. The maximal irradiance concluded by WRF in different regions tended to be volatile in 1 020-1 060 W/m2. [Conclusion] The research provides references for construction of photovoltaic power stations in Shandong Province.
基金supported jointly by the National Key Basic Research and Development (973) Program of China (Grant No. 2014CB441401)the National Natural Science Foundation of China (Grant Nos. 41405007, 41175043, 41475002, and 41205027)
文摘Two intense quasi-linear mesoscale convective systems（QLMCSs） in northern China were simulated using the WRF（Weather Research and Forecasting） model and the 3D-Var（three-dimensional variational） analysis system of the ARPS（Advanced Regional Prediction System） model.A new method in which the lightning density is calculated using both the precipitation and non-precipitation ice mass was developed to reveal the relationship between the lightning activities and QLMCS structures.Results indicate that,compared with calculating the results using two previous methods,the lightning density calculated using the new method presented in this study is in better accordance with observations.Based on the calculated lightning densities using the new method,it was found that most lightning activity was initiated on the right side and at the front of the QLMCSs,where the surface wind field converged intensely.The CAPE was much stronger ahead of the southeastward progressing QLMCS than to the back it,and their lightning events mainly occurred in regions with a large gradient of CAPE.Comparisons between lightning and non-lightning regions indicated that lightning regions featured more intense ascending motion than non-lightning regions;the vertical ranges of maximum reflectivity between lightning and non-lightning regions were very different;and the ice mixing ratio featured no significant differences between the lightning and non-lightning regions.
基金supported by the National Key Research and Development Program of China (Grant No. 2018YFC1507900)the National Natural Science Foundation of China (Grant Nos. 41575131, 41530427 and 41875172)
文摘Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall event on 20–21 April 2010.The simulation output was compared with precipitation and aircraft observations.The aircraft-observed moderate-rimed dendrites and plates indicated that riming contributed significantly to ice particle growth at the mature precipitation stage.Observations of dendrite aggregation and capped columns suggested that aggregation coexisted with deposition or riming and played an important role in producing many large particles.The domain-averaged values of the 24-h surface precipitation accumulation from the two schemes were quite close to each other.However,differences existed in the temporal and spatial evolutions of the precipitation distribution.An analysis of the surface precipitation temporal evolution indicated faster precipitation in Morrison,while P3 indicated slower rainfall by shifting the precipitation pattern eastward toward what was observed.The differences in precipitation values between the two schemes were related to the cloud water content distribution and fall speeds of rimed particles.P3 simulated the stratiform precipitation event better as it captured the gradual transition in the mass-weighted fall speeds and densities from unrimed to rimed particles.
基金Project supported by China Special Fund for Meteorological Research in the Public Interest(Grant No.GYHY201406002)the National Natural Science Foundation of China(Grant Nos.41575065 and 41405049)+1 种基金the National Natural Science Foundation International Cooperation Project,China(Grant No.41661144024)Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA17010100)
文摘We used a weather research and forecasting model to simulate a torrential rainstorm that occurred in Xinjiang,China during June 16–17,2016.The model successfully simulated the rainfall area,precipitation intensity,and changes in precipitation.We identified a clear wave signal using the two-dimensional fast Fourier transform method;the waves propagated westwards,with wavelengths of 45–20 km,periods of 50–120 min,and phase velocities mainly concentrated in the-25 m/s to-10 m/s range.The results of wavelet cross-spectral analysis further confirmed that the waves were gravity waves,peaking at 11:00 UTC,June 17,2016.The gravity wave signal was identified along 79.17–79.93°E,81.35–81.45°E and 81.5–81.83°E.The gravity waves detected along 81.5–81.83°E corresponded well with precipitation that accumulated in 1 h,indicating that gravity waves could be considered a rainstorm precursor in future precipitation forecasts.
文摘This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.
基金National Natural Science Foundation of China(42275030, U2242206, 41730964)Joint Research Project for Meteorological Capacity Improvement (22NLTSZ002)+4 种基金National Key Research and Development Program (2018YFC1506006)China Meteorological Administration Project for Innovation and Development (CXFZ2022J009, CXFZ2022J031)Key Innovation Team of Climate Prediction of China Meteorological Ministration (CMA2023ZD03)Shandong Provincial Natural Science Foundation (ZR2023QD086)UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund。
文摘This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.
基金Supported by the Hydrometeorological Observatory of the Province of Córdoba(OHMC),the Ministry of Public Services of the Province of Córdoba.
文摘The central region of Argentina is known to be a source of some most extreme weather events in the world,which are partially associated with the passage of cold fronts accompanied often by extreme wind gusts.This may cause severe property damage and even loss of human life.Nevertheless,there is a lack of studies that evaluate the performance of the numerical weather prediction(NWP)models such as weather research and forecasting(WRF)model in anticipating this type of weather in the region.This study compares the performance of the operational WRF in Argentina using four combinations of various planetary boundary layer(PBL)and microphysics parameterization schemes under varied lead times in predicting an extreme wind event(gusts>30 m s^(-1))in Central Argentina.The results demonstrate that the WRF model is capable of providing an acceptable prediction of wind speed during an extreme event.It is found that no single combination outperforms the others,although there is a slight tendency for Combination A,which utilizes the Mellor-Yamada-Janjic(MYJ)parameterization for the PBL and the Eta similarity parameterization for the surface layer,to more accurately capture the extreme wind speed.Compared with wind gust observations at five weather stations,the wind gust parameterization predicted the intensity and occurrence time of the peak wind,with an acceptable bias(time of peak<±1 h).Analysis of grid configurations(resolutions of 4 vs 9/3/1 km)revealed that higher resolution does not imply an improvement in the wind gust forecast for this particular event.With regard to lead time,a shorter lead time does not necessarily result in more accurate forecasts.Nevertheless,it is beneficial to conduct multiple sensitivity runs in order to obtain and understand the dispersion of forecasted wind speeds.
基金supported by grant from the National High Technology Research and Development Program (863) of China (Grant No.2009AA122104)grants from the National Natural Science Foundation of China (No.40901202, No.40925004)+1 种基金supported by the CAS Action Plan for West Development Program (Grant No.KZCX2-XB2-09)Chinese State Key Basic Research Project (Grant No.2007CB714400)
文摘The research of coupling WRF （Weather Research and Forecasting Model） with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA （China Meteorological Administration） and hourly meteorological observation data from seven sites of WATER （Watershed Airborne Telemetry Experimental Research） are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE （Mean Bias Error） of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were -0.19 ℃, -4.49 hPa, 4.08% and 0.92 m/s, the average RMSE （Root Mean Square Error） of them were 2.11 ℃, 5.37 hPa, 9.55% and 1.73 m/s, and the average R （correlation coefficient） of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were-0.16 ℃,-6.62 hPa,-5.14%, 0.26 m/s, 33.0 W/m^2 and-6.44 W/m^2, the average RMSE of them were 2.62 ℃, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m^2 and 53.5 W/m^2, and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained： （1） regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; （2） the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; （3） both wind speed and rainfall simulated from WRF model did not agree well with observation data.
基金This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA23090102)the National Natural Science Foundation of China(Grant No.41830967)+2 种基金the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.QYZDY-SSW-DQC012)the National Key Research and Development Program of China(Grant Nos.2018YFC1506602 and 2020YFA0608203)We also thank the National Meteorological Information Center,China Meteorological Administration,for data support.
文摘With economic development and rapid urbanization,increases in Gross Domestic Product and population in fastgrowing cities since the turn of the 21st Century have led to increases in energy consumption.Anthropogenic heat flux released to the near-surface atmosphere has led to changes in urban thermal environments and severe extreme temperature events.To investigate the effects of energy consumption on urban extreme temperature events,including extreme heat and cold events,a dynamic representation scheme of anthropogenic heat release(AHR)was implemented in the Advanced Research version of the Weather Research and Forecasting(WRF)model,and AHR data were developed based on energy consumption and population density in a case study of Beijing,China.Two simulations during 1999−2017 were then conducted using the developed WRF model with 3-km resolution with and without the AHR scheme.It was shown that the mean temperature increased with the increase in AHR,and more frequent extreme heat events were produced,with an annual increase of 0.02−0.19 days,as well as less frequent extreme cold events,with an annual decrease of 0.26−0.56 days,based on seven extreme temperature indices in the city center.AHR increased the sensible heat flux and led to surface energy budget changes,strengthening the dynamic processes in the atmospheric boundary layer that reduce AHR heating efficiency more in summer than in winter.In addition,it was concluded that suitable energy management might help to mitigate the impact of extreme temperature events in different seasons.
基金supported by the Special Fund for Meteorological Scientific Research in the Public Interest (Grant No. GYHY201506002, CRA40: 40-year CMA global atmospheric reanalysis)the National Basic Research Program of China (Grant No. 2015CB953703)+1 种基金the Intergovernmental Key International S & T Innovation Cooperation Program (Grant No. 2016YFE0102400)the National Natural Science Foundation of China (Grant Nos. 41305052 & 41375139)
文摘Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.
基金supported by the China Meteorological Administration Special Public Welfare Research Fund (No. GYHY201106033)the National Natural Science Foundation of China (No. 41175004)
文摘The effects of different Planetary Boundary Layer（PBL） structures on pollutant dispersion processes within two idealized street canyon configurations and a realistic urban area were numerically examined by a Computational Fluid Dynamics（CFD） model. The boundary conditions of different PBL structures/conditions were provided by simulations of the Weather Researching and Forecasting model. The simulated results of the idealized 2D and 3D street canyon experiments showed that the increment of PBL instability favored the downward transport of momentum from the upper flow above the roof to the pedestrian level within the street canyon. As a result, the flow and turbulent fields within the street canyon under the more unstable PBL condition are stronger. Therefore, more pollutants within the street canyon would be removed by the stronger advection and turbulent diffusion processes under the unstable PBL condition. On the contrary, more pollutants would be concentrated in the street canyon under the stable PBL condition. In addition, the simulations of the realistic building cluster experiments showed that the density of buildings was a crucial factor determining the dynamic effects of the PBL structure on the flow patterns. The momentum field within a denser building configuration was mostly transported from the upper flow, and was more sensitive to the PBL structures than that of the sparser building configuration. Finally, it was recommended to use the Mellor-Yamada-Nakanishi-Niino（MYNN） PBL scheme, which can explicitly output the needed turbulent variables, to provide the boundary conditions to the CFD simulation.
基金The National Key Basic Research Program of China under contract No.2014CB953904the Natural Science Foundation of Guangdong Province under contract No.2015A030311026the National Natural Science Foundation of China under contract Nos 41275145 and 41275060
文摘The weather research and forecasting（WRF） model is a new generation mesoscale numerical model with a fine grid resolution（2 km）, making it ideal to simulate the macro-and micro-physical processes and latent heating within Typhoon Molave（2009）. Simulations based on a single-moment, six-class microphysical scheme are shown to be reasonable, following verification of results for the typhoon track, wind intensity, precipitation pattern, as well as inner-core thermodynamic and dynamic structures. After calculating latent heating rate, it is concluded that the total latent heat is mainly derived from condensation below the zero degree isotherm, and from deposition above this isotherm. It is revealed that cloud microphysical processes related to graupel are the most important contributors to the total latent heat. Other important latent heat contributors in the simulated Typhoon Molave are condensation of cloud water, deposition of cloud ice, deposition of snow, initiation of cloud ice crystals, deposition of graupel, accretion of cloud water by graupel, evaporation of cloud water and rainwater,sublimation of snow, sublimation of graupel, melting of graupel, and sublimation of cloud ice. In essence, the simulated latent heat profile is similar to ones recorded by the Tropical Rainfall Measuring Mission, although specific values differ slightly.
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(41575008 and 41775030)
文摘The maximum height of the convective boundary layer(CBL)over the Taklimakan Desert can exceed 5000 m during summer and plays a crucial role in the regional circulation and weather.We combined the Weather Research and Forecasting Large Eddy Simulation(WRF-LES)with data from Global Positioning System(GPS)radiosondes and from eddy covariance stations to evaluate the performance of the WRF-LES in simulating the characteristics of the deep CBL over the central Taklimakan Desert.The model reproduced the evolution of the CBL processes reasonably well,but the simulations generated warmer and moister conditions than the observation as a result of the over-prediction of surface fluxes and large-scale advection.Further simulations were performed with multiple configurations and sensitivity tests.The sensitivity tests for the lateral boundary conditions(LBCs)showed that the model results are sensitive to changes in the time resolution and domain size of the specified LBCs.A larger domain size varies the distance of the area of interest from the LBCs and reduces the influence of large forecast errors near the LBCs.Comparing the model results using the original parameterization of sensible heat flux with the Noah land surface scheme and those of the sensitivity experiments showed that the desert CBL is sensitive to the sensible heat flux produced by the land surface scheme during daytime in summer.A reduction in the sensible heat flux can correct overestimates of the potential temperature profile.However,increasing the sensible heat flux significantly reduces the total time needed to increase the CBL to a relatively low altitude(<3 km)in the middle and initial stages of the development of the CBL rather than producing a higher CBL in the later stages.
基金Supported by the China Meteorological Administration Special Public Welfare Research Fund(GYHY201506001)Northwest Regional Numerical Forecasting Innovation Team Fund(GSQXCXTD-2017-02)
文摘This study investigated the performance of the mesoscale Weather Research and Forecasting(WRF) model in predicting near-surface atmospheric temperature and wind for a complex underlying surface in Northwest China in June and December 2015. The spatial distribution of the monthly average bias errors in the forecasts of 2-m temperature and 10-m wind speed is analyzed first. It is found that the forecast errors for 2-m temperature and 10-m wind speed in June are strongly correlated with the terrain distribution. However, this type of correlation is not apparent in December, perhaps due to the inaccurate specification of the surface albedo and freezing-thawing process of frozen soil in winter in Northwest China in the WRF model. In addition, the WRF model is able to reproduce the diurnal variation in 2-m temperature and 10-m wind speed, although with weakened magnitude. Elevations and land-use types have strong influences on the forecast of near-surface variables with seasonal variations. The overall results imply that accurate specification of the complex underlying surface and seasonal changes in land cover is necessary for improving near-surface forecasts over Northwest China.
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2013CB430102)National Natural Science Foundation of China(41275102 and 41330527)
文摘The relationship between the radar reflectivity factor （Z） and the rainfall rate （R） is recalculated based on radar ob- servations from 10 Doppler radars and hourly rainfall measurements at 6529 automatic weather stations over the Yangtze-Huaihe River basin. The data were collected by the National 973 Project from June to July 2013 for severe convective weather events. The Z-R relationship is combined with an empirical qr-R relationship to obtain a new Z-qr relationship, which is then used to correct the observational operator for radar reflectivity in the three-dimensional variational （3DVar） data assimilation system of the Weather Research and Forecasting （WRF） model to im-prove the analysis and prediction of severe convective weather over the Yangtze--Huaihe River basin. The perform- ance of the corrected reflectivity operator used in the WRF 3DVar data assimilation system is tested with a heavy rain event that occurred over Jiangsu and Anhui provinces and the surrounding regions on 23 June 2013. It is noted that the observations for this event are not included in the calculation of the Z-R relationship. Three experiments are conducted with the WRF model and its 3DVar system, including a control run without the assimilation of reflectivity data and two assimilation experiments with the original and corrected refleetivity operators. The experimental results show that the assimilation of radar reflectivity data has a positive impact on the rainfall forecast within a few hours with either the original or corrected reflectivity operators, but the corrected reflectivity operator achieves a better per-forrnance on the rainfall forecast than the original operator. The corrected reflectivity operator extends the effective time of radar data assimilation for the prediction of strong reflectivity. The physical variables analyzed with the corrected reflectivity operator present more reasonable mesoscale structures than those obtained with the original re-flectivity operator. This suggests that the new statistical Z-R relationship is more suitable for predicting severe con- vective weather over the Yangtze-Huaihe River basin than the Z-R relationships currently in use.
基金Supported by the National Natural Science Foundation of China (41875059 and 41675016)。
文摘Land use data with building characteristics are important for modeling the impacts of urban morphology on local climate.In this study,an extreme heat event in Shanghai,China,was simulated by using a WRF/BEP+BEM(Weather Research and Forecasting/Building Effect Parameterization+Building Energy Model)model.We incorporated local climate zone(LCZ)land use data that resolved urban morphology using 10 classes of building parameters.The simulation was compared to a control case based on MODIS(Moderate-resolution Imaging Spectroradiometer)land use data.The findings are as follows:(1)the LCZ data performed better than the MODIS data for simulating 10-m wind speed.An increase in building height led to the wind speed to decrease by 0.6-1.4 m s^(-1)in the daytime and by 0.2-0.7 m s^(-1)at nighttime.(2)High-rise buildings warmed the air by trapping radiation in the urban canyon.This warming effect was partially offset by the cooling effect of building shadows in the day.As a result,the 2-m temperature increased by 0.8℃ at night but only by 0.4℃ during the day.(3)Heterogeneous urban surfaces increased the 50-m turbulent kinetic energy by 0.4 m^(2) s^(-2),decreased the 10-m wind speed by 1.8 m s^(-1)in the daytime,increased the surface net radiation by 45.1 W m^(2)-,and increased the 2-m temperature by 1.5℃ at nighttime.(4)The LCZ data modified the atmospheric circulation between land and ocean.The shadowing effect reduced the air temperature differences between land and ocean and weakened the sea breeze.Moreover,high-rise buildings obstructed sea breezes,restricting their impact to a smaller portion(10 km along the wind direction)of inland areas compared to that with MODIS.
