A running mean bias(RMB) correction approach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the norther...A running mean bias(RMB) correction approach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the northern China region. To determine a proper training window length for calculating RMB, window lengths from 2 to 20 days were evaluated, and 16 days was taken as an optimal window length, since it receives most of the benefit from extending the window length. The raw and 16-day RMB corrected ensembles were then evaluated for their ensemble mean forecast skills. The results show that the raw ensemble has obvious bias in all near-surface variables. The RMB correction can remove the bias reasonably well, and generate an unbiased ensemble. The bias correction not only reduces the ensemble mean forecast error, but also results in a better spreaderror relationship. Moreover, two methods for computing calibrated probabilistic forecast(PF) were also evaluated through the 57 case dates: 1) using the relative frequency from the RMB-corrected ensemble; 2) computing the forecasting probabilities based on a historical rank histogram. The first method outperforms the second one, as it can improve both the reliability and the resolution of the PFs, while the second method only has a small effect on the reliability, indicating the necessity and importance of removing the systematic errors from the ensemble.展开更多
The ice water content(IWC) distribution in a mixed-phase cloud system was investigated using Cloud-Sat data,aircraft measurements,and the Weather Research and Forecasting(WRF) model.Simulated precipitation and IWC wer...The ice water content(IWC) distribution in a mixed-phase cloud system was investigated using Cloud-Sat data,aircraft measurements,and the Weather Research and Forecasting(WRF) model.Simulated precipitation and IWC were in general agreement with rain gauge,sat-ellite,and aircraft observations.The cloud case was char-acterized by a predominant cold layer and high IWC throughout the cloud-development and precipitation stages.The CloudSat-retrieved products suggested that the IWC was distributed from 4.0 to 8.0 km,with the maximum values(up to 0.5 g m-3) at 5.0-6.0 km at the earlymature stage of cloud development.High IWC(up to 0.8 g m-3) was also detected by airborne probes at 4.2 and 3.6 km at the late-mature stage.The WRF model simulation re-vealed that the predominant riming facilitated rapid ac-cumulation of high IWC at 3.0-6.0 km.展开更多
In this research,a novel dual-model system,one-dimensional stratiform cold cloud model(1DSC) coupled to Weather Research and Forecast(WRF) model(WRF-1DSC for short),was employed to investigate the effects of cloud see...In this research,a novel dual-model system,one-dimensional stratiform cold cloud model(1DSC) coupled to Weather Research and Forecast(WRF) model(WRF-1DSC for short),was employed to investigate the effects of cloud seeding by silver iodide(AgI) on rain enhancement.Driven by changing environmental conditions extracted from the WRF model,WRF-1DSC could be used to assess the cloud seeding effects quantitatively.The employment of WRF-1DSC,in place of a one-dimensional two-moment cloud seeding model applied to a three-dimensional mesoscale cloud-resolving model,was found to result in massive reduction of computational resources.Numerical experiments with WRF-1DSC were conducted for a real stratiform precipitation event observed on 4-5 July 2004,in Northeast China.A good agreement between the observed and modeled cloud system ensured the ability of WRF-1DSC to simulate the observed precipitation process efficiently.Sensitivity tests were performed with different seeding times,locations,and amounts.Experimental results showed that the optimum seeding effect(defined as the percentage of rain enhancement or rain enhancement rate) could be achieved through proper seeding at locations of maximum cloud water content when the updraft was strong.The optimum seeding effect was found to increase by 5.61% when the cloud was seeded at 5.5 km above ground level around 2300 UTC 4 July 2004,with the maximum AgI mixing ratio(X s) equaling 15 ng kg 1.On the other hand,for an overseeded cloud,a significant reduction occurred in the accumulated precipitation(-12.42%) as X s reached 100 ng kg 1.This study demonstrates the potential of WRF1DSC in determining the optimal AgI seeding strategy in practical operations of precipitation enhancement.展开更多
This paper outlines a one-dimensional,heightdependent bin model with detailed microphysical processes in which ice splinters are produced by a riming process.The model is then applied to simulate the shift of particle...This paper outlines a one-dimensional,heightdependent bin model with detailed microphysical processes in which ice splinters are produced by a riming process.The model is then applied to simulate the shift of particle size distribution effected by the secondary ice production process within clouds with different generating cells and cloud top temperatures.The result of model simulations reveals the general effects of cloud updrafts on increasing ice particle concentration by extending the residence time of ice particles in clouds and providing sufficiently large supercooled water droplets.The rimesplintering mechanism is more effective in clouds with lower ice seeding rates than those with higher rates.Evolutions of hydrometeor size distribution triggered by the rime-splintering mechanism indicate that the interaction between large ice particles and supercooled water drops adds a "second maximum" to the primary ice spectra.展开更多
基金supported by the National Basic Research Program of China(973 Program)[Grant 2014CB441403]the National Natural Science Foundation of China [Grants41275147]+1 种基金the National Key Research and Development Program of China [2016YFC0209000]Ningxia scientific supporting program [Grants 2015KJHM31]
基金supported by a project of the National Natural Science Foundation of China (Grant No. 41305099)
文摘A running mean bias(RMB) correction approach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the northern China region. To determine a proper training window length for calculating RMB, window lengths from 2 to 20 days were evaluated, and 16 days was taken as an optimal window length, since it receives most of the benefit from extending the window length. The raw and 16-day RMB corrected ensembles were then evaluated for their ensemble mean forecast skills. The results show that the raw ensemble has obvious bias in all near-surface variables. The RMB correction can remove the bias reasonably well, and generate an unbiased ensemble. The bias correction not only reduces the ensemble mean forecast error, but also results in a better spreaderror relationship. Moreover, two methods for computing calibrated probabilistic forecast(PF) were also evaluated through the 57 case dates: 1) using the relative frequency from the RMB-corrected ensemble; 2) computing the forecasting probabilities based on a historical rank histogram. The first method outperforms the second one, as it can improve both the reliability and the resolution of the PFs, while the second method only has a small effect on the reliability, indicating the necessity and importance of removing the systematic errors from the ensemble.
基金supported by the National Basic Research Program of China (973 Program,Grant No.2013CB430105)the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No.KZCX2-EW-203)the National Natural Science Foundation of China (Grant No.41105095)
文摘The ice water content(IWC) distribution in a mixed-phase cloud system was investigated using Cloud-Sat data,aircraft measurements,and the Weather Research and Forecasting(WRF) model.Simulated precipitation and IWC were in general agreement with rain gauge,sat-ellite,and aircraft observations.The cloud case was char-acterized by a predominant cold layer and high IWC throughout the cloud-development and precipitation stages.The CloudSat-retrieved products suggested that the IWC was distributed from 4.0 to 8.0 km,with the maximum values(up to 0.5 g m-3) at 5.0-6.0 km at the earlymature stage of cloud development.High IWC(up to 0.8 g m-3) was also detected by airborne probes at 4.2 and 3.6 km at the late-mature stage.The WRF model simulation re-vealed that the predominant riming facilitated rapid ac-cumulation of high IWC at 3.0-6.0 km.
基金supported by the Knowledge Innovation Program of Chinese Academy of Sciences (Grant No. KZCX2-EW-203)the National Basic Research Program of China (Grant No.2013CB430105)the National Department Public Benefit Research Foundation (Grant No.GYHY201006031)
文摘In this research,a novel dual-model system,one-dimensional stratiform cold cloud model(1DSC) coupled to Weather Research and Forecast(WRF) model(WRF-1DSC for short),was employed to investigate the effects of cloud seeding by silver iodide(AgI) on rain enhancement.Driven by changing environmental conditions extracted from the WRF model,WRF-1DSC could be used to assess the cloud seeding effects quantitatively.The employment of WRF-1DSC,in place of a one-dimensional two-moment cloud seeding model applied to a three-dimensional mesoscale cloud-resolving model,was found to result in massive reduction of computational resources.Numerical experiments with WRF-1DSC were conducted for a real stratiform precipitation event observed on 4-5 July 2004,in Northeast China.A good agreement between the observed and modeled cloud system ensured the ability of WRF-1DSC to simulate the observed precipitation process efficiently.Sensitivity tests were performed with different seeding times,locations,and amounts.Experimental results showed that the optimum seeding effect(defined as the percentage of rain enhancement or rain enhancement rate) could be achieved through proper seeding at locations of maximum cloud water content when the updraft was strong.The optimum seeding effect was found to increase by 5.61% when the cloud was seeded at 5.5 km above ground level around 2300 UTC 4 July 2004,with the maximum AgI mixing ratio(X s) equaling 15 ng kg 1.On the other hand,for an overseeded cloud,a significant reduction occurred in the accumulated precipitation(-12.42%) as X s reached 100 ng kg 1.This study demonstrates the potential of WRF1DSC in determining the optimal AgI seeding strategy in practical operations of precipitation enhancement.
基金jointly supported by the Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No.KZCX2-EW-203)the National Natural Science Foundation of China(Grant No.41005073)
文摘This paper outlines a one-dimensional,heightdependent bin model with detailed microphysical processes in which ice splinters are produced by a riming process.The model is then applied to simulate the shift of particle size distribution effected by the secondary ice production process within clouds with different generating cells and cloud top temperatures.The result of model simulations reveals the general effects of cloud updrafts on increasing ice particle concentration by extending the residence time of ice particles in clouds and providing sufficiently large supercooled water droplets.The rimesplintering mechanism is more effective in clouds with lower ice seeding rates than those with higher rates.Evolutions of hydrometeor size distribution triggered by the rime-splintering mechanism indicate that the interaction between large ice particles and supercooled water drops adds a "second maximum" to the primary ice spectra.