Air pollution is an issue of great concern in any urban region due to its serious health implications.The capital of India,New Delhi continues to be in the list of most polluted cities since 2014.The air quality of an...Air pollution is an issue of great concern in any urban region due to its serious health implications.The capital of India,New Delhi continues to be in the list of most polluted cities since 2014.The air quality of any region depends on the ability of dispersion of air pollutants.The height or depth of the atmospheric boundary layer(ABL)is one measure of dispersion of air pollutants.Ventilation coefficient is another crucial parameter in determining the air quality of any region.Both of these parameters are obtained over Delhi from the operational global numerical weather prediction(NWP)model of National Centre for Medium Range Weather forecasting(NCMRWF)known as NCMRWF Unified Model(NCUM).The height of ABL over Delhi,is also obtained from radiosonde observations using the parcel method.A good agreement is found between the observed and predicted values of ABL height.The maximum height of ABL is obtained during summer season and minimum is obtained in winter season.High values of air pollutants are found when the values of ABL height and ventilation coefficient are low.展开更多
Surface soil moisture has great impact on both meso-and microscale atmospheric processes,especially on severe local convection processes and on the dynamics of short-lived torrential rains.To promote the performance o...Surface soil moisture has great impact on both meso-and microscale atmospheric processes,especially on severe local convection processes and on the dynamics of short-lived torrential rains.To promote the performance of the land surface model (LSM) in surface soil moisture simulations,a hybrid hydrologic runoff parameterization scheme based upon the essential modeling theories of the Xin'anjiang model and Topography based hydrological Model (TOPMODEL) was developed in preference to the simple water balance model (SWB) in the Noah LSM.Using a strategy for coupling and integrating this modified Noah LSM to the Global/Regional Assimilation and Prediction System (GRAPES) analogous to that used with the standard Noah LSM,a simulation of atmosphere-land surface interactions for a torrential event during 2007 in Shandong was attempted.The results suggested that the surface,10-cm depth soil moisture simulated by GRAPES using the modified hydrologic approach agrees well with the observations.Improvements from the simulated results were found,especially over eastern Shandong.The simulated results,compared with the products of the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) soil moisture datasets,indicated a consistent spatial pattern over all of China.The temporal variation of surface soil moisture was validated with the data at an observation station,also demonstrated that GRAPES with modified Noah LSM exhibits a more reasonable response to precipitation events,even though biases and systematic trends may still exist.展开更多
Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variabl...Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August.For this study,the operational analyses and short-term forecasts from two numerical weather prediction(NWP)models(ECMWF and HIRLAM)were extracted for the Tara drift trajectory.We compared the IMB,meteorological and surface flux observations against the NWP products,also applying a one-dimensional thermodynamic sea ice model(HIGHTSI)to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing.The modelled snow depth time series,controlled by NWP-based precipitation,was in line with the observed one.HIGHTSI reproduced well the snowmelt onset,the progress of the melt,and the first date of snow-free conditions.HIGHTSI performed well also in the late August freezing season.Challenges remain to model the“false bottom”observed during the melting season.The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results.During the melting period,the nonlinear ice temperature profile was successfully modelled with both forcing options.During spring and the melting season,total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation,followed by the downward shortwave radiation,air temperature,and wind speed.展开更多
In the present study, the imitation of heavy rainfall event which occurred over Jharkhand during 18 August 2016 was taken as a case study. Weather Research and Forecasting (WRF) model has been utilized for this study....In the present study, the imitation of heavy rainfall event which occurred over Jharkhand during 18 August 2016 was taken as a case study. Weather Research and Forecasting (WRF) model has been utilized for this study. National Centers for Environmental Prediction (NCEP) analysis data is compared with GSMaP data with different combination of physical parameterization scheme like microphysics (MP) and cumulus parameterization (CP). In the present study, three MP schemes: Kessler scheme, Lin et al. scheme and WRF Single-moment 6-class scheme with combination of three CP schemes: Betts-Miller-Janjic scheme, Multi-scale Kain-Fritsch scheme and New simplified Arakawa-Schubert scheme have been used. The model predicted humidity, temperature and precipitation were compared with the GSMaP product. The model nicely depicted the cloud pattern and recognized the rain event spatially. The obtained result shows that the model overestimates the precipitation for all the schemes.展开更多
Accurate predictions of wind power generation several months in advance are crucial for the effective operation and maintenance of wind farms and for facilitating efficient power purchase planning.This study evaluates...Accurate predictions of wind power generation several months in advance are crucial for the effective operation and maintenance of wind farms and for facilitating efficient power purchase planning.This study evaluates the performance of the seasonal prediction system of the National Centre for Medium-Range Weather Forecasting in forecasting near-surface winds.An analysis of 23 years of hindcast data,from 1993 to 2015,indicates that the seasonal prediction system effectively captures the inter-annual variability of near-surface winds.Specifically,predictions initialized in May demonstrate notable accuracy,with a skill score of 0.78 in predicting the sign of wind speed anomalies aggregated across various wind farms during the high wind season(June to August).Additionally,we critically examine the peculiarity of a case study from 2020,when the Indian wind industry experienced low power generation.To enhance forecasting accuracy,we employ statistical techniques to produce bias-corrected forecasts on a seasonal scale.This approach improves the accuracy of wind speed predictions at turbine hub height.Our assessment,based on root mean square error,reveals that bias-corrected wind speed forecasts show a significant improvement,ranging from 54%to 93%.展开更多
文摘Air pollution is an issue of great concern in any urban region due to its serious health implications.The capital of India,New Delhi continues to be in the list of most polluted cities since 2014.The air quality of any region depends on the ability of dispersion of air pollutants.The height or depth of the atmospheric boundary layer(ABL)is one measure of dispersion of air pollutants.Ventilation coefficient is another crucial parameter in determining the air quality of any region.Both of these parameters are obtained over Delhi from the operational global numerical weather prediction(NWP)model of National Centre for Medium Range Weather forecasting(NCMRWF)known as NCMRWF Unified Model(NCUM).The height of ABL over Delhi,is also obtained from radiosonde observations using the parcel method.A good agreement is found between the observed and predicted values of ABL height.The maximum height of ABL is obtained during summer season and minimum is obtained in winter season.High values of air pollutants are found when the values of ABL height and ventilation coefficient are low.
基金funded by the National BasicResearch Program of China (Grant No. 2010CB951404)the National Natural Science Foundation of China (Grant No. 40971024)CMA Special Meteorology Project (Grant No.GYHY200706001)
文摘Surface soil moisture has great impact on both meso-and microscale atmospheric processes,especially on severe local convection processes and on the dynamics of short-lived torrential rains.To promote the performance of the land surface model (LSM) in surface soil moisture simulations,a hybrid hydrologic runoff parameterization scheme based upon the essential modeling theories of the Xin'anjiang model and Topography based hydrological Model (TOPMODEL) was developed in preference to the simple water balance model (SWB) in the Noah LSM.Using a strategy for coupling and integrating this modified Noah LSM to the Global/Regional Assimilation and Prediction System (GRAPES) analogous to that used with the standard Noah LSM,a simulation of atmosphere-land surface interactions for a torrential event during 2007 in Shandong was attempted.The results suggested that the surface,10-cm depth soil moisture simulated by GRAPES using the modified hydrologic approach agrees well with the observations.Improvements from the simulated results were found,especially over eastern Shandong.The simulated results,compared with the products of the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) soil moisture datasets,indicated a consistent spatial pattern over all of China.The temporal variation of surface soil moisture was validated with the data at an observation station,also demonstrated that GRAPES with modified Noah LSM exhibits a more reasonable response to precipitation events,even though biases and systematic trends may still exist.
基金This study was initialized during DAMOCLES project(Grant no.18509)which was funded by the 6th Framework Programme of the European Commission+2 种基金The initial data analysis was funded by the Research Council of Norway’s AMORA project(Grant no.#193592)The modelling work has been supported by the Academy of Finland(Contract 317999)The finalization of this work was supported by the European Union’s Horizon 2020 research and innovation programme(Grant no.727890–INTAROS).
文摘Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August.For this study,the operational analyses and short-term forecasts from two numerical weather prediction(NWP)models(ECMWF and HIRLAM)were extracted for the Tara drift trajectory.We compared the IMB,meteorological and surface flux observations against the NWP products,also applying a one-dimensional thermodynamic sea ice model(HIGHTSI)to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing.The modelled snow depth time series,controlled by NWP-based precipitation,was in line with the observed one.HIGHTSI reproduced well the snowmelt onset,the progress of the melt,and the first date of snow-free conditions.HIGHTSI performed well also in the late August freezing season.Challenges remain to model the“false bottom”observed during the melting season.The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results.During the melting period,the nonlinear ice temperature profile was successfully modelled with both forcing options.During spring and the melting season,total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation,followed by the downward shortwave radiation,air temperature,and wind speed.
文摘In the present study, the imitation of heavy rainfall event which occurred over Jharkhand during 18 August 2016 was taken as a case study. Weather Research and Forecasting (WRF) model has been utilized for this study. National Centers for Environmental Prediction (NCEP) analysis data is compared with GSMaP data with different combination of physical parameterization scheme like microphysics (MP) and cumulus parameterization (CP). In the present study, three MP schemes: Kessler scheme, Lin et al. scheme and WRF Single-moment 6-class scheme with combination of three CP schemes: Betts-Miller-Janjic scheme, Multi-scale Kain-Fritsch scheme and New simplified Arakawa-Schubert scheme have been used. The model predicted humidity, temperature and precipitation were compared with the GSMaP product. The model nicely depicted the cloud pattern and recognized the rain event spatially. The obtained result shows that the model overestimates the precipitation for all the schemes.
文摘Accurate predictions of wind power generation several months in advance are crucial for the effective operation and maintenance of wind farms and for facilitating efficient power purchase planning.This study evaluates the performance of the seasonal prediction system of the National Centre for Medium-Range Weather Forecasting in forecasting near-surface winds.An analysis of 23 years of hindcast data,from 1993 to 2015,indicates that the seasonal prediction system effectively captures the inter-annual variability of near-surface winds.Specifically,predictions initialized in May demonstrate notable accuracy,with a skill score of 0.78 in predicting the sign of wind speed anomalies aggregated across various wind farms during the high wind season(June to August).Additionally,we critically examine the peculiarity of a case study from 2020,when the Indian wind industry experienced low power generation.To enhance forecasting accuracy,we employ statistical techniques to produce bias-corrected forecasts on a seasonal scale.This approach improves the accuracy of wind speed predictions at turbine hub height.Our assessment,based on root mean square error,reveals that bias-corrected wind speed forecasts show a significant improvement,ranging from 54%to 93%.
