ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 44,Issue 12,2018 Table of Contents
2018, 44(12):1509-1517.
DOI: 10.7519/j.issn.10000526.2018.12.001
Abstract:
The highly dense observations are used in the regional analysis, so the regional data assimilation may produce more accurate smallscale analysis. However, the largescale aspect of a global analysis is superior to that of a regional analysis for assimilating more observations of the satellite observations and is not affected by lateral boundaries. To improve the forecast qualities of regional model, a blending method to merge the T639 global analysis with the regional analysis from the GRAPESMeso analysis system is implemented using discrete cosine transform (DCT) filter. The experiments show that the simulated kinetic energy spectrum of GRAPES analysis is a little bigger than T639 analysis in the smallmeso scale. Meanwhile, the simulated kinetic energy spectrum of blending analysis is the closest to the atmospheric kinetic energy spectrum in the smallmeso scale. The results indicate the qualities of geopotential height, temperature and wind of blending analysis are obviously improved, the forecast of wind within 6 h is improved, and the ETS verification of accumulated precipitation of blending analysis is higher than the regional analysis.
The highly dense observations are used in the regional analysis, so the regional data assimilation may produce more accurate smallscale analysis. However, the largescale aspect of a global analysis is superior to that of a regional analysis for assimilating more observations of the satellite observations and is not affected by lateral boundaries. To improve the forecast qualities of regional model, a blending method to merge the T639 global analysis with the regional analysis from the GRAPESMeso analysis system is implemented using discrete cosine transform (DCT) filter. The experiments show that the simulated kinetic energy spectrum of GRAPES analysis is a little bigger than T639 analysis in the smallmeso scale. Meanwhile, the simulated kinetic energy spectrum of blending analysis is the closest to the atmospheric kinetic energy spectrum in the smallmeso scale. The results indicate the qualities of geopotential height, temperature and wind of blending analysis are obviously improved, the forecast of wind within 6 h is improved, and the ETS verification of accumulated precipitation of blending analysis is higher than the regional analysis.
2018, 44(12):1518-1528.
DOI: 10.7519/j.issn.10000526.2018.12.002
Abstract:
Using the mesoscale regional model GRAPES_Meso, this paper simulates a frontal rain band which occurred in North China during August 2-4 2015. The simulated results are in good agreement with the observations. The convective stability, inertial stability and conditionally symmetric instability (CSI) during the precipitation process are analyzed using the model output data, and the CSI region is diagnosed. The results show that: (1) The development of CSI was accompanied by the weakening of convective instability and the enhancement of inertial instability. (2) According to the change of instability, the precipitation is divided into three stages. In the first stage, the precipitation was mainly affected by convective instability; in the second stage, convective instability, inertial instability and CSI got enhanced, and precipitation at this stage was affected by three types of instability; in the third stage, the three types of instability gradually weakened, but still affected the sustainability of precipitation. (3) In the vigorous developing stage, CSI showed a bandlike distribution in the plane. In the profile, the CSI is active in the lower troposphere. (4) In diagnosing CSI, the method with MPV and convective instability is more effective than the one with M-θe.
Using the mesoscale regional model GRAPES_Meso, this paper simulates a frontal rain band which occurred in North China during August 2-4 2015. The simulated results are in good agreement with the observations. The convective stability, inertial stability and conditionally symmetric instability (CSI) during the precipitation process are analyzed using the model output data, and the CSI region is diagnosed. The results show that: (1) The development of CSI was accompanied by the weakening of convective instability and the enhancement of inertial instability. (2) According to the change of instability, the precipitation is divided into three stages. In the first stage, the precipitation was mainly affected by convective instability; in the second stage, convective instability, inertial instability and CSI got enhanced, and precipitation at this stage was affected by three types of instability; in the third stage, the three types of instability gradually weakened, but still affected the sustainability of precipitation. (3) In the vigorous developing stage, CSI showed a bandlike distribution in the plane. In the profile, the CSI is active in the lower troposphere. (4) In diagnosing CSI, the method with MPV and convective instability is more effective than the one with M-θe.
2018, 44(12):1529-1541.
DOI: 10.7519/j.issn.10000526.2018.12.003
Abstract:
To investigate the environmental characteristics, storm structures and formation mechanism of the thunderstorm that occurred on 27 July 2016 in Beijing Area, the data of conventional observation, wind profile, Doppler weather radar, Variational Doppler Radar Analysis System (VDRAS) and automatic weather station (AWS) data are analyzed. The case analysis shows that this windstorm developed under a weak synoptic forcing background. The unstable thermodynamic condition enhanced the development of linear convection into bow echo, resulting in thunderstorm. The characteristic in sounding data such as the temperature laps rate in the lower troposphere was almost equal to the dryadiabatanda sudden increase of DCAPE, which are indicative of windstorm weather. The cold pool outflow and warmmoist southerly flow at front of the mountain formed a convergence zone in the western region of Beijing. Under the combined action of significant disturbance temperature gradient and topographic forcing new thunderstorms were triggered. Because of the uplift of mountain area, the lifting of thunderstorm cold pool outflow caused significant disturbance temperature gradient, contributing to the development of the thermal instability, and triggered unstable energy, enhancing thunderstorm intensity in the process of coming down the hill. The Doppler radar product also showed a strong reflectivity core, an overhanging echo, boundary weak echo range and a bookend vortex in radial velocity images. Under the combined action of the intensive cold pool and the bookend vortex, the rear inflow was intensified, becoming rearinflow jet, which was characterized by a strong wind zone in the lowelevation radial velocity images. The dry and cold air were trapped into the cloud by the rearinflow, creating a negative buoyancy through evaporation. Combined with the dragging of precipitation particles, eventually, strong surface winds were formed.
To investigate the environmental characteristics, storm structures and formation mechanism of the thunderstorm that occurred on 27 July 2016 in Beijing Area, the data of conventional observation, wind profile, Doppler weather radar, Variational Doppler Radar Analysis System (VDRAS) and automatic weather station (AWS) data are analyzed. The case analysis shows that this windstorm developed under a weak synoptic forcing background. The unstable thermodynamic condition enhanced the development of linear convection into bow echo, resulting in thunderstorm. The characteristic in sounding data such as the temperature laps rate in the lower troposphere was almost equal to the dryadiabatanda sudden increase of DCAPE, which are indicative of windstorm weather. The cold pool outflow and warmmoist southerly flow at front of the mountain formed a convergence zone in the western region of Beijing. Under the combined action of significant disturbance temperature gradient and topographic forcing new thunderstorms were triggered. Because of the uplift of mountain area, the lifting of thunderstorm cold pool outflow caused significant disturbance temperature gradient, contributing to the development of the thermal instability, and triggered unstable energy, enhancing thunderstorm intensity in the process of coming down the hill. The Doppler radar product also showed a strong reflectivity core, an overhanging echo, boundary weak echo range and a bookend vortex in radial velocity images. Under the combined action of the intensive cold pool and the bookend vortex, the rear inflow was intensified, becoming rearinflow jet, which was characterized by a strong wind zone in the lowelevation radial velocity images. The dry and cold air were trapped into the cloud by the rearinflow, creating a negative buoyancy through evaporation. Combined with the dragging of precipitation particles, eventually, strong surface winds were formed.
2018, 44(12):1542-1554.
DOI: 10.7519/j.issn.10000526.2018.12.004
Abstract:
Using the shorttime severe rainfall data collected by 125 national automatic weather stations and 3400 regional stations in Yunnan Province, and based on the basic idea of “ingredients”, the analysis of mesoscale characteristics was done by choosing typical shorttime severe railfall cases from May to October in 2012-2016. Then, five types of shorttime severe rainfall conceptual models suitable to Yunnan Province were worked out. The results show that the shorttime severe rainfall in Yunnan concentrates from June to August and there are two obvious peaks a day. The strong dry and cold advection and windy weather at high altitude are important bases to discriminate the upper cold advection category. Cold airs affect Yunnan mainly through two routes. Critical systems for the lowlevel warm advection category are monsoon trough and low pressure at the Bay of Bengal, which mainly affects the central and south areas of Yunnan. The surface front has the feature of baroclinic frontogenesis category. This kind of heavy rain is mainly located in the front of 700 hPa shear and 850 hPa temperature fronts and near the surface front. The quasibarotropic A category shorttime severe rainfall is mainly influenced by the interaction between the westerly trough and subtropical high. Its precipitation areas are scattered and very difficult to forecast. The quasibarotropic B category is affected by the reduced low pressure after the typhoon landing and peripheral structures, and the severe rainfall is located in the area influenced by the 700 hPa wet tongue, 850 hPa warm ridge and the surface convergence line (usually located in the south area of central Yunnan).
Using the shorttime severe rainfall data collected by 125 national automatic weather stations and 3400 regional stations in Yunnan Province, and based on the basic idea of “ingredients”, the analysis of mesoscale characteristics was done by choosing typical shorttime severe railfall cases from May to October in 2012-2016. Then, five types of shorttime severe rainfall conceptual models suitable to Yunnan Province were worked out. The results show that the shorttime severe rainfall in Yunnan concentrates from June to August and there are two obvious peaks a day. The strong dry and cold advection and windy weather at high altitude are important bases to discriminate the upper cold advection category. Cold airs affect Yunnan mainly through two routes. Critical systems for the lowlevel warm advection category are monsoon trough and low pressure at the Bay of Bengal, which mainly affects the central and south areas of Yunnan. The surface front has the feature of baroclinic frontogenesis category. This kind of heavy rain is mainly located in the front of 700 hPa shear and 850 hPa temperature fronts and near the surface front. The quasibarotropic A category shorttime severe rainfall is mainly influenced by the interaction between the westerly trough and subtropical high. Its precipitation areas are scattered and very difficult to forecast. The quasibarotropic B category is affected by the reduced low pressure after the typhoon landing and peripheral structures, and the severe rainfall is located in the area influenced by the 700 hPa wet tongue, 850 hPa warm ridge and the surface convergence line (usually located in the south area of central Yunnan).
2018, 44(12):1555-1564.
DOI: 10.7519/j.issn.10000526.2018.12.005
Abstract:
The random forest algorithm is currently one of the more widely used machine learning methods, featuring high prediction accuracy, stable training results and generalization ability, and has obvious advantages in solving the problem of multiclassification. This paper applies the random forest algorithm to the prediction and classification of severe convective weather, which is divided into four categories: shorttime heavy rainfall, thunderstorm gale, hail and no severe convection. Then, based on the data of convection index and physics calculated from the NCEP data of 2005-2016, the training, 0-12 h forecasting and testing of classified severe convection are carried out. The results show that the whole misjudgment rate is 21.9% that is calculated out of the independent data of 2015-2016. It has almost no omission in 85 examples of severe convective weather and the model is especially suitable for larger range of severe convective weather. The physical meaning of the factors used in random forest algorithm is relatively clear, and basically consistent with the subjective forecasting experience. It can be used in daily forecasting operation.
The random forest algorithm is currently one of the more widely used machine learning methods, featuring high prediction accuracy, stable training results and generalization ability, and has obvious advantages in solving the problem of multiclassification. This paper applies the random forest algorithm to the prediction and classification of severe convective weather, which is divided into four categories: shorttime heavy rainfall, thunderstorm gale, hail and no severe convection. Then, based on the data of convection index and physics calculated from the NCEP data of 2005-2016, the training, 0-12 h forecasting and testing of classified severe convection are carried out. The results show that the whole misjudgment rate is 21.9% that is calculated out of the independent data of 2015-2016. It has almost no omission in 85 examples of severe convective weather and the model is especially suitable for larger range of severe convective weather. The physical meaning of the factors used in random forest algorithm is relatively clear, and basically consistent with the subjective forecasting experience. It can be used in daily forecasting operation.
2018, 44(12):1565-1574.
DOI: 10.7519/j.issn.10000526.2018.12.006
Abstract:
Utilizing upperair, surface data and dual polarization weather radar data, a hailstorm and shorttime severe rainfall weather occurred in the southeast coast of Fujian in 21-22 December 2016 is analyzed. The results show that the hailstorm in the afternoon 21 December is induced by the southwest warm advection forcing sector severe convection. The shorttime severe rainfall at night is the baroclinic frontogenesis severe convection. We analyze the hail phase state evolution based on the dual polarization weather radar products. The obvious hail features (ZDR≤0, echo intensity ≥55 dBz) appear around 0℃ level height firstly, then develop upward and downward. The TBSS (threebody scattering spike) occurs at high level. But because the level of the wetbulb temperature zero (WBZ) is the same as the level of drybulb temperature zero (DBZ), the melting level of hail is thick. In the afternoon the surface temperature is above 20℃. During the falling process of hails, the values of differential reflectivity (ZDR) and differential phase shift (KDP) change from negative to positive, which shows that the hails melt into big raindrops or outsourcing water film hails. The value ZDR changes from negative extreme to positive extreme and correlation coefficient (CC) is smaller than 0.7 where the area TBSS of echo intensity is 15-20 dBz, which are the characteristics of nonmeteorological echoes. ZDR and KDP of shorttime severe rainfall increase with the intensity of reflectivity, and the value of CC is above 0.97, which indicate that a large amount of relatively largesized raindrops are the main cause for this shorttime severe rainfall.
Utilizing upperair, surface data and dual polarization weather radar data, a hailstorm and shorttime severe rainfall weather occurred in the southeast coast of Fujian in 21-22 December 2016 is analyzed. The results show that the hailstorm in the afternoon 21 December is induced by the southwest warm advection forcing sector severe convection. The shorttime severe rainfall at night is the baroclinic frontogenesis severe convection. We analyze the hail phase state evolution based on the dual polarization weather radar products. The obvious hail features (ZDR≤0, echo intensity ≥55 dBz) appear around 0℃ level height firstly, then develop upward and downward. The TBSS (threebody scattering spike) occurs at high level. But because the level of the wetbulb temperature zero (WBZ) is the same as the level of drybulb temperature zero (DBZ), the melting level of hail is thick. In the afternoon the surface temperature is above 20℃. During the falling process of hails, the values of differential reflectivity (ZDR) and differential phase shift (KDP) change from negative to positive, which shows that the hails melt into big raindrops or outsourcing water film hails. The value ZDR changes from negative extreme to positive extreme and correlation coefficient (CC) is smaller than 0.7 where the area TBSS of echo intensity is 15-20 dBz, which are the characteristics of nonmeteorological echoes. ZDR and KDP of shorttime severe rainfall increase with the intensity of reflectivity, and the value of CC is above 0.97, which indicate that a large amount of relatively largesized raindrops are the main cause for this shorttime severe rainfall.
2018, 44(12):1575-1582.
DOI: 10.7519/j.issn.10000526.2018.12.007
Abstract:
The Beidou Groundbased Augment System is the important infrastructure of the Beidou Satellite Navigation System. To obtain water vapor products with high precision and resolution is the demand for numerical forecasting, space weather monitoring and early warning services. This paper, using the data from three kinds of water vapor patterns of Beidou, GPS and GPS + BD in Beidou Groundbased Augment System, combined with the radiosonde observation, makes detailed comparative analysis among Beidou, GPS and sounding systems. The results show that: (1) The data provided by the Beidou Groundbased Augment System can be effectively used to retrieve the total vapor content of the atmospheric column, and the average deviation is less than 1 mm, which is basically consistent with the GPS and the sounding system and has some indication to numerical forecast. (2) Compared with the GPS system, the mean square error of GPS/PWV and GPS+BD/PWV is less than 2 mm, and the correlation coefficient is more than 97%, which indicates that the accuracy is similar to GPS system. However, the mean square error of Beidou/PWV is 3-6 mm, and the relative variance is 15%-20%, which shows that there is a certain difference of accuracy between Beidou and GPS system. (3) Compared with sounding system, the Beidou/PWV has some inconsistency with the situation in individual time changes, which the mean square error is 2.14-6.12 mm and the relative variance is 15.32%-20.84%. The errors may be due to factors such as the detection system errors, while the GPS+BD/PWV and GPS/PWV will be more stable.
The Beidou Groundbased Augment System is the important infrastructure of the Beidou Satellite Navigation System. To obtain water vapor products with high precision and resolution is the demand for numerical forecasting, space weather monitoring and early warning services. This paper, using the data from three kinds of water vapor patterns of Beidou, GPS and GPS + BD in Beidou Groundbased Augment System, combined with the radiosonde observation, makes detailed comparative analysis among Beidou, GPS and sounding systems. The results show that: (1) The data provided by the Beidou Groundbased Augment System can be effectively used to retrieve the total vapor content of the atmospheric column, and the average deviation is less than 1 mm, which is basically consistent with the GPS and the sounding system and has some indication to numerical forecast. (2) Compared with the GPS system, the mean square error of GPS/PWV and GPS+BD/PWV is less than 2 mm, and the correlation coefficient is more than 97%, which indicates that the accuracy is similar to GPS system. However, the mean square error of Beidou/PWV is 3-6 mm, and the relative variance is 15%-20%, which shows that there is a certain difference of accuracy between Beidou and GPS system. (3) Compared with sounding system, the Beidou/PWV has some inconsistency with the situation in individual time changes, which the mean square error is 2.14-6.12 mm and the relative variance is 15.32%-20.84%. The errors may be due to factors such as the detection system errors, while the GPS+BD/PWV and GPS/PWV will be more stable.
2018, 44(12):1583-1592.
DOI: 10.7519/j.issn.10000526.2018.12.008
Abstract:
Under the climatic background of rare precipitation in dry season of Yunnan, the prediction of abnormal drought or flood climate events has been one of the most challenging problems in shortterm climate prediction. It is of great significance to improve the accuracy of climate prediction by analyzing the climatic causes of abnormal precipitation in dry season. In January, the main period of midwinter, the rainfall in Yunnan is characterized by skewness distribution and the interannual change is very significant. The general circulations between more and less rainfall year in Yunnan in January are quite different. There are four significant impact areas in the 500 hPa field which are closely associated with the rainfall in Yunnan in January. Three of them which are located in the middle or high latitude area respectively correspond to the three centers of Scandinavia Teleconnection Pattern, and the last one lies in low latitude Arab Sea whose geopotential height indicates the intensity of trough in Bengal Bay. When the Scandinavia Teleconnection Pattern is in positive (negative) phase and the geopotential height of Arab Sea is negative (positive), the Yunnan rainfall in January is likely to be less (more). There are two significant impact areas of SST, one is located in the southeast Pacific and the other is in middlewest area of North Atlantic. Through affecting the circulations in East Asia and South Asia, the SST has an influence on the precipitation in Yunnan in January. By employing the data of significant impact areas of 500 hPa and SST field, the combined sequences of height field and SST field are synthesized respectively. Both combination sequences have higher correlation coefficients and better corresponding rates of anomaly sign with rainfall in Yunnan in January than those of single impact area data. Based on the combined sequences of 500 hPa and SST field in each year from 1961 to 2017, the scatter graph is drawn. Nearly 80% of the total years is located in the first and third quadrants, where the functions of height field and SST field are consistent with rainfall in Yunnan in January. In this case, the location of the falling zone corresponds well to the anomaly sign of rainfall. The remaining 20% years are located in the second and the fourth quadrants, where the height field and the SST field have opposite functions, and the location of the falling zone corresponds poorly to the anomaly sign of precipitation.
Under the climatic background of rare precipitation in dry season of Yunnan, the prediction of abnormal drought or flood climate events has been one of the most challenging problems in shortterm climate prediction. It is of great significance to improve the accuracy of climate prediction by analyzing the climatic causes of abnormal precipitation in dry season. In January, the main period of midwinter, the rainfall in Yunnan is characterized by skewness distribution and the interannual change is very significant. The general circulations between more and less rainfall year in Yunnan in January are quite different. There are four significant impact areas in the 500 hPa field which are closely associated with the rainfall in Yunnan in January. Three of them which are located in the middle or high latitude area respectively correspond to the three centers of Scandinavia Teleconnection Pattern, and the last one lies in low latitude Arab Sea whose geopotential height indicates the intensity of trough in Bengal Bay. When the Scandinavia Teleconnection Pattern is in positive (negative) phase and the geopotential height of Arab Sea is negative (positive), the Yunnan rainfall in January is likely to be less (more). There are two significant impact areas of SST, one is located in the southeast Pacific and the other is in middlewest area of North Atlantic. Through affecting the circulations in East Asia and South Asia, the SST has an influence on the precipitation in Yunnan in January. By employing the data of significant impact areas of 500 hPa and SST field, the combined sequences of height field and SST field are synthesized respectively. Both combination sequences have higher correlation coefficients and better corresponding rates of anomaly sign with rainfall in Yunnan in January than those of single impact area data. Based on the combined sequences of 500 hPa and SST field in each year from 1961 to 2017, the scatter graph is drawn. Nearly 80% of the total years is located in the first and third quadrants, where the functions of height field and SST field are consistent with rainfall in Yunnan in January. In this case, the location of the falling zone corresponds well to the anomaly sign of rainfall. The remaining 20% years are located in the second and the fourth quadrants, where the height field and the SST field have opposite functions, and the location of the falling zone corresponds poorly to the anomaly sign of precipitation.
2018, 44(12):1593-1603.
DOI: 10.7519/j.issn.10000526.2018.12.009
Abstract:
Recently, an extendedrange (10-30 days) forecast method, namely the spatialtemporal projection model (STPM) has been applied in predicting the lowfrequency precipitation in tropics and shows comparable skills. Based on the daily precipitation data from 11 weather stations in Shanghai, and the daily MJO index (RMM1 and RMM2) provided by Australian Meteorological Bureau during 2011-2010, the STPM model for the extendedrange forecast of precipitation during Meiyu season in Shanghai was constructed. Depending on the relationship between the quasiperiod MJO activities and the precipitation, the coupled patterns between temporal varying realtime multivariate MJO (RMM) index and regional lowfrequency precipitation during Meiyu season is derived based on the singular value decomposition (SVD). Therefore, using the MJO index as predictor and projecting it onto the spatialtemporal coupled patterns, the forecast of regional lowfrequency precipitation is obtained. The STPM model is then used in the precipitation prediction during 2011-2016. The evaluation demonstrates that the prediction of the STPM model achieves a useful skill at a lead time of 25 days. Three quarters of precipitation occurrences and intensity during Meiyu season can usually be predicted. Among them, the STPM model attains a higher skill in the prediction of 10-20 d lead time. Generally, the STPM model provides a useful method in the extendedrange forecast during Meiyu season in Shanghai.
Recently, an extendedrange (10-30 days) forecast method, namely the spatialtemporal projection model (STPM) has been applied in predicting the lowfrequency precipitation in tropics and shows comparable skills. Based on the daily precipitation data from 11 weather stations in Shanghai, and the daily MJO index (RMM1 and RMM2) provided by Australian Meteorological Bureau during 2011-2010, the STPM model for the extendedrange forecast of precipitation during Meiyu season in Shanghai was constructed. Depending on the relationship between the quasiperiod MJO activities and the precipitation, the coupled patterns between temporal varying realtime multivariate MJO (RMM) index and regional lowfrequency precipitation during Meiyu season is derived based on the singular value decomposition (SVD). Therefore, using the MJO index as predictor and projecting it onto the spatialtemporal coupled patterns, the forecast of regional lowfrequency precipitation is obtained. The STPM model is then used in the precipitation prediction during 2011-2016. The evaluation demonstrates that the prediction of the STPM model achieves a useful skill at a lead time of 25 days. Three quarters of precipitation occurrences and intensity during Meiyu season can usually be predicted. Among them, the STPM model attains a higher skill in the prediction of 10-20 d lead time. Generally, the STPM model provides a useful method in the extendedrange forecast during Meiyu season in Shanghai.
2018, 44(12):1604-1611.
DOI: 10.7519/j.issn.10000526.2018.12.010
Abstract:
By using the brightness temperature value of the microwave radiometer, the corresponding reflectivity factor of the cloud radar and the Lband radiosonde data in the CMA Meteorological Observation Centre, the BP (back propagation) neural network is used as the inversion tool, and the atmospheric humidity profile is retrieved. The weather condition is divided into clear day, low cloud, middle cloud, high cloud as four cases. The inversions of the humidity profiles without reflectivity factor are compared, and the root mean square errors by the two inversion methods in each altitude layer are analyzed. The comparison results show that the correlation coefficient of the inversed humidity profile with the reflectivity factor is 0.862, the root mean square error is 14.9%. On the contrary, the correlation coefficient of the inversed humidity profile without the reflectivity factor is 0.763, and the root mean square error is 19.2%.
By using the brightness temperature value of the microwave radiometer, the corresponding reflectivity factor of the cloud radar and the Lband radiosonde data in the CMA Meteorological Observation Centre, the BP (back propagation) neural network is used as the inversion tool, and the atmospheric humidity profile is retrieved. The weather condition is divided into clear day, low cloud, middle cloud, high cloud as four cases. The inversions of the humidity profiles without reflectivity factor are compared, and the root mean square errors by the two inversion methods in each altitude layer are analyzed. The comparison results show that the correlation coefficient of the inversed humidity profile with the reflectivity factor is 0.862, the root mean square error is 14.9%. On the contrary, the correlation coefficient of the inversed humidity profile without the reflectivity factor is 0.763, and the root mean square error is 19.2%.
2018, 44(12):1612-1617.
DOI: 10.7519/j.issn.10000526.2018.12.011
Abstract:
This paper is to explore the different anti oxidant and inflammation effects of short time high dose and long time low dose fine particular matter (PM2.5) on rats. Forty eight healthy male C57BL/6 rats were randomly divided into six groups, eight in each. Low dose group, moderate dose group and high dose group were exposed to PM2.5at 100 μg·m-3, 150 μg·m-3 and 250 μg·m-3 on average, respectively, using the artificial climate environment expose cabinet. 〖JP2〗Meanwhile, three blank 〖JP〗groups were also set. After exposure, C reactive protein (CRP), constructivenitric oxide synthase (cNOS), homocysteine (HCY), interleukin8 (IL 8) were analyzed. The results showed that the levels of CRP, HCY and IL 8 in long term low dose group are significantly higher than those in the short term 〖JP2〗highdose group (P<0.05, P<0.01). 〖JP〗The inhibition level of cNOS in the lowdose group is also significantly higher than that in the short term highdose group (P<0.05, P<0.01). The ranking of PM2.5 exposure to health damage effect is low dose 72 h, moderate dose 48 h and high dose 28.8 h when the PM2.5 exposure dose is same.
This paper is to explore the different anti oxidant and inflammation effects of short time high dose and long time low dose fine particular matter (PM2.5) on rats. Forty eight healthy male C57BL/6 rats were randomly divided into six groups, eight in each. Low dose group, moderate dose group and high dose group were exposed to PM2.5at 100 μg·m-3, 150 μg·m-3 and 250 μg·m-3 on average, respectively, using the artificial climate environment expose cabinet. 〖JP2〗Meanwhile, three blank 〖JP〗groups were also set. After exposure, C reactive protein (CRP), constructivenitric oxide synthase (cNOS), homocysteine (HCY), interleukin8 (IL 8) were analyzed. The results showed that the levels of CRP, HCY and IL 8 in long term low dose group are significantly higher than those in the short term 〖JP2〗highdose group (P<0.05, P<0.01). 〖JP〗The inhibition level of cNOS in the lowdose group is also significantly higher than that in the short term highdose group (P<0.05, P<0.01). The ranking of PM2.5 exposure to health damage effect is low dose 72 h, moderate dose 48 h and high dose 28.8 h when the PM2.5 exposure dose is same.
2018, 44(12):1618-1627.
DOI: 10.7519/j.issn.10000526.2018.12.012
Abstract:
To evaluate the method improvements on the blind sample preparation and the data calculation, this paper describes the method of the blind samples intercomparison study, which is conducted annually among the Acid Rain Monitoring Network of China Meteorological Administration (ARMN/CMA), and presents analysis on the pH and conductivity measurement deviations from 376 stations since early 1990s. The analysis indicates that the blind samples prepared during 2007-2017 by the improved method, which is inconsistent with WMO GAW protocol, cover the coincident ranges of pH, conductivity and ionic composition with the actual precipitation. The improved data calculation method adopted since 2005, which derives the statistical true value and the standard deviation of the pH measurement and conductivity measurement of the blind samples, shows obviously an improvement in reflecting overall status and annual performance changes of ARMN/CMA stations in pH and conductivity measurement. The annual blind samples intercomparison study is playing a key role in the ARMN/CMA quality management system.
To evaluate the method improvements on the blind sample preparation and the data calculation, this paper describes the method of the blind samples intercomparison study, which is conducted annually among the Acid Rain Monitoring Network of China Meteorological Administration (ARMN/CMA), and presents analysis on the pH and conductivity measurement deviations from 376 stations since early 1990s. The analysis indicates that the blind samples prepared during 2007-2017 by the improved method, which is inconsistent with WMO GAW protocol, cover the coincident ranges of pH, conductivity and ionic composition with the actual precipitation. The improved data calculation method adopted since 2005, which derives the statistical true value and the standard deviation of the pH measurement and conductivity measurement of the blind samples, shows obviously an improvement in reflecting overall status and annual performance changes of ARMN/CMA stations in pH and conductivity measurement. The annual blind samples intercomparison study is playing a key role in the ARMN/CMA quality management system.
2018, 44(12):1628-1634.
DOI: 10.7519/j.issn.10000526.2018.12.013
Abstract:
In order to understand the level of tropical cyclone (TC) forecast in the world and the status of typhoon forecast in China, based on the TC forecast assessments of the major TC forecast services in the world, the main indicators of TC forecast and the comparisons of different forecast centers are reviewed. The results show that, in the past decades, typhoon track forecast of China has greatly improved, already ranked among the world’s top level. The improvement of TC intensity forecast has a long way to go. The assessment and development of typhoon precipitation forecast are worth expecting.
In order to understand the level of tropical cyclone (TC) forecast in the world and the status of typhoon forecast in China, based on the TC forecast assessments of the major TC forecast services in the world, the main indicators of TC forecast and the comparisons of different forecast centers are reviewed. The results show that, in the past decades, typhoon track forecast of China has greatly improved, already ranked among the world’s top level. The improvement of TC intensity forecast has a long way to go. The assessment and development of typhoon precipitation forecast are worth expecting.
2018, 44(12):1635-1640.
DOI: 10.7519/j.issn.10000526.2018.12.014
Abstract:
The main characteristics of the general atmospheric circulation in September 2018 are as follows.The polar vortex showed a dipole pattern.The circulation presented the distribution of a multiwave pattern in middlehigh latitudes.The northwestern Pacific subtropical high was weaker and remarkably more westward extended than normal.The monthly mean precipitation amount was 74.2 mm, which is 14% more than normal (65.3 mm). The monthly mean temperature was 16.7℃, 0.1℃ higher than normal. There were three largerange heavy rainfall processes over China, which happened in South China and the eastern part of Northwest China, causing serious disaster locally. Four tropical cyclones were generated over northwest Pacific Ocean and the South China Sea. Typhoon Mangkhut (1822) and Barijat (1823) landed in Guangdong Province. Moreover, Heilongjiang Province suffered from low temperature and freezing disaster. Autumn rain for West China came late, but heavy somewhat in Yunnan, southern part of Sichuan, Chongqing and Southern part of Guizhou.
The main characteristics of the general atmospheric circulation in September 2018 are as follows.The polar vortex showed a dipole pattern.The circulation presented the distribution of a multiwave pattern in middlehigh latitudes.The northwestern Pacific subtropical high was weaker and remarkably more westward extended than normal.The monthly mean precipitation amount was 74.2 mm, which is 14% more than normal (65.3 mm). The monthly mean temperature was 16.7℃, 0.1℃ higher than normal. There were three largerange heavy rainfall processes over China, which happened in South China and the eastern part of Northwest China, causing serious disaster locally. Four tropical cyclones were generated over northwest Pacific Ocean and the South China Sea. Typhoon Mangkhut (1822) and Barijat (1823) landed in Guangdong Province. Moreover, Heilongjiang Province suffered from low temperature and freezing disaster. Autumn rain for West China came late, but heavy somewhat in Yunnan, southern part of Sichuan, Chongqing and Southern part of Guizhou.
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ISSN:1000-0526 CN:11-2282/P