In this study, a three-dimensional mesoscale model was used to numerically simulate the well-known "98.7" heavy rainfall event that affected the Yangtze Valley in July 1998. Two experiments were conducted to analyze the impact of moist processes on the development of meso-β scale vortices(MβV) and their triggering by mesoscale wind perturbation(MWP). In the experiment in which the latent heat feedback(LHF) scheme was switched off, a stable low-level col field(i.e., saddle field—a region between two lows and two highs in the isobaric surface) formed, and the MWP triggered a weak MβV. However, when the LHF scheme was switched on as the MWP was introduced into the model, the MβV developed quickly and intense rainfall and a mesoscale low-level jet(mLLJ) were generated. The thickness of the air column and average temperature between 400 and 700 hPa decreased without the feedback of latent heat, whereas they increased quickly when the LHF scheme was switched on, with the air pressure falling at low levels but rising at upper levels. A schematic representation of the positive feedbacks among the mesoscale vortex, rainfall, and mLLJ shows that in the initial stage of the MβV, the MWP triggers light rainfall and the latent heat occurs at low levels, which leads to weak convergence and ageostrophic winds. In the mature stage of the MβV, convection extends to the middle-to-upper levels, resulting in an increase in the average temperature and a stretching of the air column. A low-level cyclonic circulation forms under the effect of Coriolis torque, and the m LLJ forms to the southeast of the MβV.
A convection-allowing ensemble forecast experiment on a squall line was conducted based on the breeding growth mode(BGM). Meanwhile, the probability matched mean(PMM) and neighborhood ensemble probability(NEP)methods were used to optimize the associated precipitation forecast. The ensemble forecast predicted the precipitation tendency accurately, which was closer to the observation than in the control forecast. For heavy rainfall, the precipitation center produced by the ensemble forecast was also better. The Fractions Skill Score(FSS) results indicated that the ensemble mean was skillful in light rainfall, while the PMM produced better probability distribution of precipitation for heavy rainfall. Preliminary results demonstrated that convection-allowing ensemble forecast could improve precipitation forecast skill through providing valuable probability forecasts. It is necessary to employ new methods, such as the PMM and NEP, to generate precipitation probability forecasts. Nonetheless, the lack of spread and the overprediction of precipitation by the ensemble members are still problems that need to be solved.
xiang lihongrang hechaohui chenziqing miaoshigang bai
This study aims to explore the relative role of oceanic dynamics and surface heat fluxes in the warming of southern Arabian Sea and southwest Indian Ocean during the development of Indian Ocean Dipole(IOD) events by using National Center for Environmental Prediction/National Center for Atmospheric Research(NCEP/NCAR) daily reanalysis data and Global Ocean Data Assimilation System(GODAS) monthly mean ocean reanalysis data from 1982 to2013,based on regression analysis,Empirical Orthogonal Function(EOF) analysis and combined with a 21/2layer dynamic upper-ocean model.The results show that during the initial stage of IOD events,warm downwelling Rossby waves excited by an anomalous anticyclone over the west Indian Peninsula,southwest Indian Ocean and southeast Indian Ocean lead to the warming of the mixed layer by reducing entrainment cooling.An anomalous anticyclone over the west Indian Peninsula weakens the wind over the Arabian Sea and Somali coast,which helps decrease the sea surface heat loss and shallow the surface mixed layer,and also contributes to the sea surface temperature(SST) warming in the southern Arabian Sea by inhibiting entrainment.The weakened winds increase the SST along the Somali coast by inhibiting upwelling and zonal advection.The wind and net sea surface heat flux anomalies are not significant over the southwest Indian Ocean.During the antecedent stage of IOD events,the warming of the southern Arabian Sea is closely connected with the reduction of entrainment cooling caused by the Rossby waves and the weakened wind.With the appearance of an equatorial easterly wind anomaly,the warming of the southwest Indian Ocean is not only driven by weaker entrainment cooling caused by the Rossby waves,but also by the meridional heat transport carried by Ekman flow.The anomalous sea surface heat flux plays a key role to damp the warming of the west pole of the IOD.
Based on the conventional ground observational data,a numerical simulation and moist potential vorticity( MPV) analysis has been carried on heavy rainfall event over Jiangxi province from 19 June to 20 June 2010,with a meso-scale rainstorm model. The results show that this rare rainstorm is a typical heavy rainfall over Meiyu front. The cold air flow behind North China vortex joined up the southwestern flow located in the northwest part of the strong and stable subtropical high,thus the cold air and warm air converged and maintained over the northern part of Hunan and Jiangxi province. The simulated precipitation of the high resolution model is very similar to the observational rainfall. The model has a good predictive skill for the location,intensity and center of heavy rainfall. By moist potential vorticity analysis,it is found that the distribution characteristic of MPV which heavy rainfall happens ahead has an obvious indication for precipitation forecast. The vertical overlapping of the positive and negative MPV1 areas is favorable to the generation and development of rainstorm. This zone is also the conjoint area of convective instability and baroclinic instability.
Based on the dynamic framework of Lorenz 96 model,the ensemble prediction system(EPS)containing stochastic forcing has been developed.In this system,effects of stochastic forcing on the model climate state and ensemble mean prediction have been studied.The results show that the climate mean and standard deviation provided by a new computing paradigm by means of introduction of the proper stochastic forcing into numerical model integration process are closer to that of the true value than that made by the non-stochastic forcing.In other words,numerical model integration process with stochastic forcing has positive effect on the model climate state,and the effect is found to be positive mainly in the long lead time.Meanwhile,with respect to ensemble forecast effect yielded by white noise stochastic forcing,most results are better than those provided by no-stochastic forcing,and improvements pertaining to white noise stochastic forcing vary non-monotonically with the increase of the size of white noise.Moreover,the effects made by the identical white noise stochastic forcing also are different in various non-linear systems.With respect to EPS effect yielded by red noise stochastic forcing,most results are better than those provided by no-stochastic forcing,but only a part of ensemble forecast effect influenced by red noise is superior to that influenced by white noise.Finally,improvements pertaining to red noise stochastic forcing vary non-symmetrically and non-monotonically with the distribution of coefficientΦ.Besides,the selection of correlation coefficientΦis also dependent on non-linear models.
[Objective]The aim was to discuss the heavy rainfall formation mechanism and to reveal the causes of rainstorm. [Method] Based on the conventional observational data, a numerical simulation and diagnosis analyses have been carried on heavy rainfall event over Jiangxi province from 16 June to 20 June 2010, with a meso-scale REM model. The results showed that this rare rainstorm was a typical heavy rainfall over Meiyu front. The cold air flow behind the 500 hPa East Asia trough and 700 hPa North China vortex joined up the southwestern flow located in the northwest part of the strong and stable subtropical high, thus the cold air and warm air converged and maintained over the northern part of Hunan and Jiangxi province. Since the area that cold air and warm air joined up was stable and the southwestern warm and wet flow was abnormally strong, the vapor, dynamical, and thermodynamic conditions was leading to the trigger development of meso-scale convection systems. The extraordinary rainstorm was caused by the interaction of many factors such as strong vapor and convergence ascending motion, weak cold air activities in middle-levels, the strengthening of southwestern low-level jet, the formation and maintenance of southwestern vortexes, etc. The simulated precipitation of the high resolution model was very similar with the observational rainfall. The model had a good predictive skill for the location, intensity and center of heavy rainfall. By diagnosing the physical variables, it found that the distribution characteristic of the physical variables had an obvious indication for precipitation forecast. [Conclusion] The study provided reference to improve rainstorm forecast.
