2020 Vol. 26, No. 1
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2020, 26(1): .
Abstract:
2020, 26(1): 1-13.
doi: 10.16555/j.1006-8775.2020.001
Abstract:
Following previous studies of the rainfall forecast in Shenzhen owing to landfalling tropical cyclones (TCs), a nonparametric statistical scheme based on the classification of the landfalling TCs is applied to analyze and forecast the rainfall induced by landfalling TCs in the coastal area of Guangdong province, China. All the TCs landfalling with the distance less than 700 kilometers to the 8 coastal stations in Guangdong province during 1950—2013 are categorized according to their landfalling position and intensity. The daily rainfall records of all the 8 meteorological stations are obtained and analyzed. The maximum daily rainfall and the maximum 3 days’accumulated rainfall at the 8 coastal stations induced by each category of TCs during the TC landfall period (a couple of days before and after TC landfalling time) from 1950 to 2013 are computed by the percentile estimation and illustrated by boxplots. These boxplots can be used to estimate the rainfall induced by landfalling TC of the same category in the future. The statistical boxplot scheme is further coupled with the model outputs from the European Centre for Medium-Range Weather Forecasts (ECMWF) to predict the rainfall induced by landfalling TCs along the coastal area. The TCs landfalling in south China from 2014 to 2017 and the corresponding rainfall at the 8 stations area are used to evaluate the performance of these boxplots and coupled boxplots schemes. Results show that the statistical boxplots scheme and coupled boxplots scheme can perform better than ECMWF model in the operational rainfall forecast along the coastal area in south China.
Following previous studies of the rainfall forecast in Shenzhen owing to landfalling tropical cyclones (TCs), a nonparametric statistical scheme based on the classification of the landfalling TCs is applied to analyze and forecast the rainfall induced by landfalling TCs in the coastal area of Guangdong province, China. All the TCs landfalling with the distance less than 700 kilometers to the 8 coastal stations in Guangdong province during 1950—2013 are categorized according to their landfalling position and intensity. The daily rainfall records of all the 8 meteorological stations are obtained and analyzed. The maximum daily rainfall and the maximum 3 days’accumulated rainfall at the 8 coastal stations induced by each category of TCs during the TC landfall period (a couple of days before and after TC landfalling time) from 1950 to 2013 are computed by the percentile estimation and illustrated by boxplots. These boxplots can be used to estimate the rainfall induced by landfalling TC of the same category in the future. The statistical boxplot scheme is further coupled with the model outputs from the European Centre for Medium-Range Weather Forecasts (ECMWF) to predict the rainfall induced by landfalling TCs along the coastal area. The TCs landfalling in south China from 2014 to 2017 and the corresponding rainfall at the 8 stations area are used to evaluate the performance of these boxplots and coupled boxplots schemes. Results show that the statistical boxplots scheme and coupled boxplots scheme can perform better than ECMWF model in the operational rainfall forecast along the coastal area in south China.
2020, 26(1): 14-26.
doi: 10.16555/j.1006-8775.2020.002
Abstract:
Nowadays, ensemble forecasting is popular in numerical weather prediction (NWP). However, an ensemble may not produce a perfect Gaussian probability distribution due to limited members and the fact that some members significantly deviate from the true atmospheric state. Therefore, event samples with small probabilities may downgrade the accuracy of an ensemble forecast. In this study, the evolution of tropical storms (weak typhoon) was investigated and an observed tropical storm track was used to limit the probability distribution of samples. The ensemble forecast method used pure observation data instead of assimilated data. In addition, the prediction results for three tropical storm systems, Merbok, Mawar, and Guchol, showed that track and intensity errors could be reduced through sample optimization. In the research, the vertical structures of these tropical storms were compared, and the existence of different thermal structures was discovered. One possible reason for structural differences is sample optimization, and it may affect storm intensity and track.
Nowadays, ensemble forecasting is popular in numerical weather prediction (NWP). However, an ensemble may not produce a perfect Gaussian probability distribution due to limited members and the fact that some members significantly deviate from the true atmospheric state. Therefore, event samples with small probabilities may downgrade the accuracy of an ensemble forecast. In this study, the evolution of tropical storms (weak typhoon) was investigated and an observed tropical storm track was used to limit the probability distribution of samples. The ensemble forecast method used pure observation data instead of assimilated data. In addition, the prediction results for three tropical storm systems, Merbok, Mawar, and Guchol, showed that track and intensity errors could be reduced through sample optimization. In the research, the vertical structures of these tropical storms were compared, and the existence of different thermal structures was discovered. One possible reason for structural differences is sample optimization, and it may affect storm intensity and track.
2020, 26(1): 27-34.
doi: 10.16555/j.1006-8775.2020.003
Abstract:
This paper aims to assess the performances of different model initialization conditions (ICs) and lateral boundary conditions between two global models (GMs), i. e., the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP), on the accuracy of the Global / Regional Assimilation and Prediction System (GRAPES) forecasts for south China. A total of 3-month simulations during the rainy season were examined and a specific case of torrential rain over Guangdong Province was verified. Both ICs exhibited cold biases over south China, as well as a strong dry bias over the Pearl River Delta (PRD). In particular, the ICs from the ECMWF had a stronger cold bias over the PRD region and a more detailed structure than NCEP. In general, the NCEP provided a realistic surface temperature compared to the ECMWF over south China. Moreover, GRAPES initialized by the NCEP had better simulations of both location and intensity of precipitation than by the ECWMF. The results presented in this paper could be used as a general guideline to the operational numerical weather prediction that uses regional models driven by the GMs.
This paper aims to assess the performances of different model initialization conditions (ICs) and lateral boundary conditions between two global models (GMs), i. e., the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP), on the accuracy of the Global / Regional Assimilation and Prediction System (GRAPES) forecasts for south China. A total of 3-month simulations during the rainy season were examined and a specific case of torrential rain over Guangdong Province was verified. Both ICs exhibited cold biases over south China, as well as a strong dry bias over the Pearl River Delta (PRD). In particular, the ICs from the ECMWF had a stronger cold bias over the PRD region and a more detailed structure than NCEP. In general, the NCEP provided a realistic surface temperature compared to the ECMWF over south China. Moreover, GRAPES initialized by the NCEP had better simulations of both location and intensity of precipitation than by the ECWMF. The results presented in this paper could be used as a general guideline to the operational numerical weather prediction that uses regional models driven by the GMs.
2020, 26(1): 35-46.
doi: 10.16555/j.1006-8775.2020.004
Abstract:
Persistent Heavy Rainfall (PHR) is the most influential extreme weather event in Asia in summer, and thus it has attracted intensive interests of many scientists. In this study, operational global ensemble forecasts from China Meteorological Administration(CMA) are used, and a new verification method applied to evaluate the predictability of PHR is investigated. A metrics called Index of Composite Predictability (ICP) established on basic verification indicators, i. e., Equitable Threat Score(ETS) of 24h accumulated precipitation and Root Mean Square Error(RMSE) of Height at 500hPa, are selected in this study to distinguish“good”and“poor”prediction from all ensemble members. With the use of the metrics of ICP, the predictability of two typical PHR events in June 2010 and June 2011 is estimated. The results show that the“good member”and“poor member”can be identified by ICP and there is an obvious discrepancy in their ability to predict the key weather system that affects PHR.“Good member”shows a higher predictability both in synoptic scale and mesoscale weather system in their location, duration and the movement. The growth errors for “poor” members is mainly due to errors of initial conditions in northern polar region. The growth of perturbation errors and the reason for better or worse performance of ensemble member also have great value for future model improvement and further research.
2020, 26(1): 47-56.
doi: 10.16555/j.1006-8775.2020.005
Abstract:
Accurate simulation of tropical cyclone tracks is a prerequisite for tropical cyclone risk assessment. Against the spatial characteristics of tropical cyclone tracks in the Northwest Pacific region, stochastic simulation method based on classification model is used to simulate tropical cyclone tracks in this region. Such simulation includes the classification method, the genesis model, the traveling model, and the lysis model. Tropical cyclone tracks in the Northwest Pacific region are classified into five categories on the basis of its movement characteristics and steering positions. In the genesis model, Gaussian kernel probability density functions with the biased cross validation method are used to simulate the annual occurrence number and genesis positions. The traveling model is established on the basis of the mean and mean square error of the historical 6h latitude and longitude displacements. The termination probability is used as the discrimination standard in the lysis model. Then, this stochastic simulation method of tropical cyclone tracks is applied and qualitatively evaluated with different diagnostics. Results show that the tropical cyclone tracks in Northwest Pacific can be satisfactorily simulated with this classification model.
Accurate simulation of tropical cyclone tracks is a prerequisite for tropical cyclone risk assessment. Against the spatial characteristics of tropical cyclone tracks in the Northwest Pacific region, stochastic simulation method based on classification model is used to simulate tropical cyclone tracks in this region. Such simulation includes the classification method, the genesis model, the traveling model, and the lysis model. Tropical cyclone tracks in the Northwest Pacific region are classified into five categories on the basis of its movement characteristics and steering positions. In the genesis model, Gaussian kernel probability density functions with the biased cross validation method are used to simulate the annual occurrence number and genesis positions. The traveling model is established on the basis of the mean and mean square error of the historical 6h latitude and longitude displacements. The termination probability is used as the discrimination standard in the lysis model. Then, this stochastic simulation method of tropical cyclone tracks is applied and qualitatively evaluated with different diagnostics. Results show that the tropical cyclone tracks in Northwest Pacific can be satisfactorily simulated with this classification model.
2020, 26(1): 57-70.
doi: 10.16555/j.1006-8775.2020.006
Abstract:
In order to study the impacts of wind field variations in the middle and lower troposphere on the development and structure of storms, we carried out numerical experiments on cases of severe convection in the Jianghuai area under the background of cold vortex on April 28, 2015. The results show that the structure and development of convective storms are highly sensitive to the changes of wind fields, and the adjustment of wind fields in the middle or lower troposphere will lead to significant changes in the development and structure of storms. When the wind field in the middle or lower troposphere is weakened, the development of convective storms attenuates to some extent compared with that in the control experiment, and the ways of attenuation in the two experiments are different. In the attenuation test of wind field at the middle level, convective storms obviously weaken at all stages in its development, while for the wind field at the low level, the convective storms weaken only in the initial stage of storm. On the contrary, the enhancement of the wind field in the middle or lower troposphere is conducive to the development of convection, especially the enhancement in the middle troposphere. In contrast, the convective storms develop rapidly in this test, as the most intensive one. The wind field variations have significant impacts on the structure and organization of the storm. The enhancement of wind field in the middle troposphere facilitates the intension of the middle-level rotation in convective storm, the reduction of the storm scale, and the organized evolution of convective storms. The strengthening of the wind field in the lower troposphere is conducive to the development of the low-level secondary circulation of the storm and the cyclonic vorticity at the middle and low levels on the inflowing side of the storms.
In order to study the impacts of wind field variations in the middle and lower troposphere on the development and structure of storms, we carried out numerical experiments on cases of severe convection in the Jianghuai area under the background of cold vortex on April 28, 2015. The results show that the structure and development of convective storms are highly sensitive to the changes of wind fields, and the adjustment of wind fields in the middle or lower troposphere will lead to significant changes in the development and structure of storms. When the wind field in the middle or lower troposphere is weakened, the development of convective storms attenuates to some extent compared with that in the control experiment, and the ways of attenuation in the two experiments are different. In the attenuation test of wind field at the middle level, convective storms obviously weaken at all stages in its development, while for the wind field at the low level, the convective storms weaken only in the initial stage of storm. On the contrary, the enhancement of the wind field in the middle or lower troposphere is conducive to the development of convection, especially the enhancement in the middle troposphere. In contrast, the convective storms develop rapidly in this test, as the most intensive one. The wind field variations have significant impacts on the structure and organization of the storm. The enhancement of wind field in the middle troposphere facilitates the intension of the middle-level rotation in convective storm, the reduction of the storm scale, and the organized evolution of convective storms. The strengthening of the wind field in the lower troposphere is conducive to the development of the low-level secondary circulation of the storm and the cyclonic vorticity at the middle and low levels on the inflowing side of the storms.
2020, 26(1): 71-81.
doi: 10.16555/j.1006-8775.2020.007
Abstract:
The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top, refining the vertical resolution, and the assimilation of operationally available observations, including conventional and satellite observations, on continental U. S. winter short-range weather forecasting, were investigated in this study. The initial and predicted wind and temperature profiles were analyzed against conventional observations. Generally, the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used. Negative impacts were also observed in both the initial wind and temperature profiles, over the lower troposphere. Different from the results by only raising the model top, the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used. Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill. The major improvements caused by raising the model top with refined vertical resolution, as well as those caused by data assimilation, were in both cases located in the tropopause and lower stratosphere. Negative impacts were also observed in the predicted near surface wind and lower-tropospheric temperature. These negative impacts were related to the uncertainties caused by more stratospheric information, as well as to some physical processes. A case study shows that when we raise the model top, put more vertical layers in stratosphere and apply data assimilation, the precipitation scores can be slightly improved. However, more analysis is needed due to uncertainties brought by data assimilation.
The impacts of stratospheric initial conditions and vertical resolution on the stratosphere by raising the model top, refining the vertical resolution, and the assimilation of operationally available observations, including conventional and satellite observations, on continental U. S. winter short-range weather forecasting, were investigated in this study. The initial and predicted wind and temperature profiles were analyzed against conventional observations. Generally, the initial wind and temperature bias profiles were better adjusted when a higher model top and refined vertical resolution were used. Negative impacts were also observed in both the initial wind and temperature profiles, over the lower troposphere. Different from the results by only raising the model top, the assimilation of operationally available observations led to significant improvements in both the troposphere and stratosphere initial conditions when a higher top was used. Predictions made with the adjusted stratospheric initial conditions and refined vertical resolutions showed generally better forecasting skill. The major improvements caused by raising the model top with refined vertical resolution, as well as those caused by data assimilation, were in both cases located in the tropopause and lower stratosphere. Negative impacts were also observed in the predicted near surface wind and lower-tropospheric temperature. These negative impacts were related to the uncertainties caused by more stratospheric information, as well as to some physical processes. A case study shows that when we raise the model top, put more vertical layers in stratosphere and apply data assimilation, the precipitation scores can be slightly improved. However, more analysis is needed due to uncertainties brought by data assimilation.
2020, 26(1): 82-92.
doi: 10.16555/j.1006-8775.2020.008
Abstract:
Meteorological conditions, particularly the vertical wind field structure, have a direct influence on the PM2.5 concentrations over the Pearl River Delta (PRD). In October 2012, an exceptional air pollution event occurred in the PRD, and a high concentration of PM2.5 was registered at some stations. During days with PM2.5 air pollution, the wind speed was less than 3 m s-1 at the surface, and the vertical wind field featured a weak wind layer (WWL) with a thickness of approximately 1000 m. The mean atmospheric boundary layer height was less than 500 m during pollution days, but it was greater than 1400 m during non-pollution days. A strong negative correlation was detected between the PM2.5 concentration and the ventilation index (VI). The VI was less than 2000 m2 s-1 during PM2.5 air pollution days. Because of the weak wind, sea-land breezes occurred frequently, the recirculation factor (RF) values were small at a height of 800 m during pollution days, and the zones with the lowest RF values always occurred between the heights of 300 and 600 m. The RF values during PM2.5 pollution days were approximately 0.4 to 0.6 below a height of 800 m, reducing the transportation capacity of the wind field to only 40% to 60%. The RF and wind profile characteristics indicated that sea-land breezes were highly important in the accumulation of PM2.5 air pollution in the PRD. The sea breezes may transport pollutants back inland and may result in the peak PM2.5 concentrations at night.
Meteorological conditions, particularly the vertical wind field structure, have a direct influence on the PM2.5 concentrations over the Pearl River Delta (PRD). In October 2012, an exceptional air pollution event occurred in the PRD, and a high concentration of PM2.5 was registered at some stations. During days with PM2.5 air pollution, the wind speed was less than 3 m s-1 at the surface, and the vertical wind field featured a weak wind layer (WWL) with a thickness of approximately 1000 m. The mean atmospheric boundary layer height was less than 500 m during pollution days, but it was greater than 1400 m during non-pollution days. A strong negative correlation was detected between the PM2.5 concentration and the ventilation index (VI). The VI was less than 2000 m2 s-1 during PM2.5 air pollution days. Because of the weak wind, sea-land breezes occurred frequently, the recirculation factor (RF) values were small at a height of 800 m during pollution days, and the zones with the lowest RF values always occurred between the heights of 300 and 600 m. The RF values during PM2.5 pollution days were approximately 0.4 to 0.6 below a height of 800 m, reducing the transportation capacity of the wind field to only 40% to 60%. The RF and wind profile characteristics indicated that sea-land breezes were highly important in the accumulation of PM2.5 air pollution in the PRD. The sea breezes may transport pollutants back inland and may result in the peak PM2.5 concentrations at night.
2020, 26(1): 93-102.
doi: 10.16555/j.1006-8775.2020.009
Abstract:
In this paper, European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis-Interim (ERA-Interim) data and daily precipitation data in China from May to October during 1981-2016 are used to study the climatic characteristics of the meridionally oriented shear lines (MSLs) over the Tibetan Plateau (TP). The relationship between the MSL and rainstorms in the eastern TP and neighboring areas of the TP during the boreal summer half-year is also investigated. An objective method, which uses a combination of three parameters, i.e. the zonal shear of the meridional wind, the relative vorticity and the zero line of meridional wind, is adopted to identify the shear line. The results show that there are two high-occurrence centers of MSL. One is over the central TP (near 90°E) and the other is over the steep slope area of the eastern TP. Fewer MSLs are found along the Yarlung Zangbo River over the western TP and the southern Tibet. There are averagely 42.2 MSL days in each boreal summer half-year. The number of MSL days reaches the maximum of 62 in 2014 and the minimum of 22 in 2006. July and October witness the maximum of 10.2 MSL days/ year and the minimum of 4.2 MSL days/year, respectively. The annual number of the MSL days shows periodicities of 2-4 and 4-6 years, which is quite similar to those of the MSL rainstorm days. In the neighboring areas of the TP, nearly 56% of the MSLs lead to rainstorms, and nearly 40% of rainstorms are caused by the MSLs, indicating a close relationship between the MSLs and rainstorms in this region.
In this paper, European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis-Interim (ERA-Interim) data and daily precipitation data in China from May to October during 1981-2016 are used to study the climatic characteristics of the meridionally oriented shear lines (MSLs) over the Tibetan Plateau (TP). The relationship between the MSL and rainstorms in the eastern TP and neighboring areas of the TP during the boreal summer half-year is also investigated. An objective method, which uses a combination of three parameters, i.e. the zonal shear of the meridional wind, the relative vorticity and the zero line of meridional wind, is adopted to identify the shear line. The results show that there are two high-occurrence centers of MSL. One is over the central TP (near 90°E) and the other is over the steep slope area of the eastern TP. Fewer MSLs are found along the Yarlung Zangbo River over the western TP and the southern Tibet. There are averagely 42.2 MSL days in each boreal summer half-year. The number of MSL days reaches the maximum of 62 in 2014 and the minimum of 22 in 2006. July and October witness the maximum of 10.2 MSL days/ year and the minimum of 4.2 MSL days/year, respectively. The annual number of the MSL days shows periodicities of 2-4 and 4-6 years, which is quite similar to those of the MSL rainstorm days. In the neighboring areas of the TP, nearly 56% of the MSLs lead to rainstorms, and nearly 40% of rainstorms are caused by the MSLs, indicating a close relationship between the MSLs and rainstorms in this region.
2020, 26(1): 103-110.
doi: 10.16555/j.1006-8775.2020.010
Abstract:
An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service. This paper aims to explore a technical method for determining and screening evaluation indicators. Based on public satisfaction survey data obtained in Wafangdian, China in 2010, this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index. Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators, correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer, then one indicator could be removed, or the two indicators merged. For evaluation indicators in different sub-evaluation layers, although clustering reveals attribute correlations, these indicators may not be substituted for one another. Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.
An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service. This paper aims to explore a technical method for determining and screening evaluation indicators. Based on public satisfaction survey data obtained in Wafangdian, China in 2010, this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index. Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators, correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer, then one indicator could be removed, or the two indicators merged. For evaluation indicators in different sub-evaluation layers, although clustering reveals attribute correlations, these indicators may not be substituted for one another. Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.
2020, 26(1): 111-124.
doi: 10.16555/j.1006-8775.2020.011
Abstract:
heavy rainfall event caused by a mesoscale convective system (MCS), which occurred over the Yellow River midstream area during 7-9 July 2016, was analyzed using observational, high-resolution satellite, NCEP / NCAR reanalysis, and numerical simulation data. This heavy rainfall event was caused by one mesoscale convective complex (MCC) and five MCSs successively. The MCC rainstorm occurred when southwesterly winds strengthened into a jet. The MCS rainstorms occurred when low-level wind fields weakened, but their easterly components in the lower and boundary layers increased continuously. Numerical analysis revealed that there were obvious differences between the MCC and MCS rainstorms, including their three-dimensional airflow structure, disturbances in wind fields and vapor distributions, and characteristics of energy conversion and propagation. Formation of the MCC was related to southerly conveyed water vapor and energy to the north, with obvious water vapor exchange between the free atmosphere and the boundary layer. Continuous regeneration and development of the MCSs mainly relied on maintenance of an upward extension of a positive water vapor disturbance. The MCC rainstorm was triggered by large range of convergent ascending motion caused by a southerly jet, and easterly disturbance within the boundary layer. While a southerly fluctuation and easterly disturbance in the boundary layer were important triggers of the MCS rainstorms. Maintenance and development of the MCC and MCSs were linked to secondary circulation, resulting from convergence of Ekman non-equilibrium flow in the boundary layer. Both intensity and motion of the convergence centers in MCC and MCS cases were different. Clearly, sub-synoptic scale systems in the middle troposphere played a leading role in determining precipitation distribution during this event. Although mesoscale systems triggered by the sub-synoptic scale system induced the heavy rainfall, small-scale disturbances within the boundary layer determined its intensity and location.
heavy rainfall event caused by a mesoscale convective system (MCS), which occurred over the Yellow River midstream area during 7-9 July 2016, was analyzed using observational, high-resolution satellite, NCEP / NCAR reanalysis, and numerical simulation data. This heavy rainfall event was caused by one mesoscale convective complex (MCC) and five MCSs successively. The MCC rainstorm occurred when southwesterly winds strengthened into a jet. The MCS rainstorms occurred when low-level wind fields weakened, but their easterly components in the lower and boundary layers increased continuously. Numerical analysis revealed that there were obvious differences between the MCC and MCS rainstorms, including their three-dimensional airflow structure, disturbances in wind fields and vapor distributions, and characteristics of energy conversion and propagation. Formation of the MCC was related to southerly conveyed water vapor and energy to the north, with obvious water vapor exchange between the free atmosphere and the boundary layer. Continuous regeneration and development of the MCSs mainly relied on maintenance of an upward extension of a positive water vapor disturbance. The MCC rainstorm was triggered by large range of convergent ascending motion caused by a southerly jet, and easterly disturbance within the boundary layer. While a southerly fluctuation and easterly disturbance in the boundary layer were important triggers of the MCS rainstorms. Maintenance and development of the MCC and MCSs were linked to secondary circulation, resulting from convergence of Ekman non-equilibrium flow in the boundary layer. Both intensity and motion of the convergence centers in MCC and MCS cases were different. Clearly, sub-synoptic scale systems in the middle troposphere played a leading role in determining precipitation distribution during this event. Although mesoscale systems triggered by the sub-synoptic scale system induced the heavy rainfall, small-scale disturbances within the boundary layer determined its intensity and location.
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