ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 44,Issue 10,2018 Table of Contents
2018, 44(10):1245-1254.
DOI: 10.7519/j.issn.1000-0526.2018.10.001
Abstract:
High resolution data of Himawari8 (H8 for short) have been used in China since 2016, and forecasters have been concerning for its superiority in monitoring convective clouds because heavy and extreme rain processes occurred frequently in 2016. In the current forecasting operation, the delay time of acquiring H8, FY2 and radar data are 15 min, 35 min and 6 min, respectively. In this article, the H8 infrared data and surface precipitation are used to analyze the initiation of each target convective clouds of 27 heavy rain processes in the 2016 flood season. By comparing with FY2 satellite and radar observations, we conclude that the observation data of H8 and FY2 at the same moment have little difference, and their time variation trends are almost the same. However, H8 depicts convection strength more detailedly due to its higher resolution, and it has obvious superiority in monitoring heavy rain convective clouds. It can find the initiation convective clouds 23 min earlier than FY2 averagely, and 33 min earlier than radar. Combined with hourly and 10 min precipitation data, the 20 July 2016 extreme heavy rain event in North China is analyzed in detail. It is found that there is a remarkable negative correlation between temperature of brightness blackbody (TBB) and surface precipitation, and the amplitude of precipitation varies much larger than TBB. When the peak of TBB moves towards the colder side, the corresponding precipitation magnitude increases, and the type of precipitation turns to coldcloud precipitation gradually.
High resolution data of Himawari8 (H8 for short) have been used in China since 2016, and forecasters have been concerning for its superiority in monitoring convective clouds because heavy and extreme rain processes occurred frequently in 2016. In the current forecasting operation, the delay time of acquiring H8, FY2 and radar data are 15 min, 35 min and 6 min, respectively. In this article, the H8 infrared data and surface precipitation are used to analyze the initiation of each target convective clouds of 27 heavy rain processes in the 2016 flood season. By comparing with FY2 satellite and radar observations, we conclude that the observation data of H8 and FY2 at the same moment have little difference, and their time variation trends are almost the same. However, H8 depicts convection strength more detailedly due to its higher resolution, and it has obvious superiority in monitoring heavy rain convective clouds. It can find the initiation convective clouds 23 min earlier than FY2 averagely, and 33 min earlier than radar. Combined with hourly and 10 min precipitation data, the 20 July 2016 extreme heavy rain event in North China is analyzed in detail. It is found that there is a remarkable negative correlation between temperature of brightness blackbody (TBB) and surface precipitation, and the amplitude of precipitation varies much larger than TBB. When the peak of TBB moves towards the colder side, the corresponding precipitation magnitude increases, and the type of precipitation turns to coldcloud precipitation gradually.
2018, 44(10):1255-1266.
DOI: 10.7519/j.issn.1000-0526.2018.10.002
Abstract:
A shorttime torrential rain occurred in the afternoon of 24 July 2016, from the central and eastern part of Hebei Province to southern Tianjin, which was the torrential rain center. For this torrential rain both the objective and forecasters subjective forecasts had biases. In this paper the causes of the precipitation are analyzed, especially the initiation and propagation mechanism of the torrential rain, which is the most critical problem, by using the conventional surface and upperair observation, satellite images, radar data and VDRAS data that assimilated the radar and AWS data. The results show that: (1) the torrential rain occurred as the subtropical high strengthened and extended northward. From the perspective of traditional identification, the circulation pattern didnt favor the northwest upper trough at the edge of subtropical high moving eastward and influencing the southeast of North China. It was a warmsector torrential rain which occurred under the control of the 588 dagpm. It was a nontypical circulation pattern shorttime severe rainfall, difficult to forecast. (2) Although the distance from Tianjin to Xingtai is farther than from Tianjin to Beijing, Xingtai Sounding Station located in the southwest of the torrential rain zone has more reference value under the influence of southwest airflow which is on the northwest side of subtropical high. At 11:00 BT, Xingtai sounding data showed that the atmosphere was extremely unstable and the lowlevel water vapor was deep and unusually vigorous. The CAPE value was 3874 J·kg-1, CIN was 22 J·kg-1 and the height of 8 g·kg-1 specific humidity extended to 600 hPa. The surface dewpoint temperature was nearly 30℃. (3) Near the 850 hPa warm shear line, the two surface shear lines merged and mesoscale frontogenesis was the key factor of initiation. Two cloud bands were also visible on the satellite image, enhancing convergence. So cumulus clouds developed in the convergence zone, and small cumulus clouds developed in the morning near the warm shear line. As the convergence was strengthened, the mesoscale convective system was formed in the eastwest direction. (4) After thunderstorm is triggered, its movement and propagation are the difficulties of forecasting, because it determines the lasting time of convective precipitation. In this case, under the influence of the convergence line and the storm gusts, new thunderstorm initiation in the west part of the shear line, and the northsouth cloud street met the shear line on the south side of the shear line, causing the thunderstorm to spread westward and move southward. So the propagation direction was west by south. Under the influence of southwest airflow, the convective cells moved northeastward, namely, the advection direction was east, which was opposite to the direction of propagation. Thus, the “train effect” was formed. Cloud streets showed that there was a supplement of the south warm and humid air flow under the inversion layer in the south of the shear line. In addition, the convective storm gusts triggered new thunderstorms again, making convective storms sustained.
A shorttime torrential rain occurred in the afternoon of 24 July 2016, from the central and eastern part of Hebei Province to southern Tianjin, which was the torrential rain center. For this torrential rain both the objective and forecasters subjective forecasts had biases. In this paper the causes of the precipitation are analyzed, especially the initiation and propagation mechanism of the torrential rain, which is the most critical problem, by using the conventional surface and upperair observation, satellite images, radar data and VDRAS data that assimilated the radar and AWS data. The results show that: (1) the torrential rain occurred as the subtropical high strengthened and extended northward. From the perspective of traditional identification, the circulation pattern didnt favor the northwest upper trough at the edge of subtropical high moving eastward and influencing the southeast of North China. It was a warmsector torrential rain which occurred under the control of the 588 dagpm. It was a nontypical circulation pattern shorttime severe rainfall, difficult to forecast. (2) Although the distance from Tianjin to Xingtai is farther than from Tianjin to Beijing, Xingtai Sounding Station located in the southwest of the torrential rain zone has more reference value under the influence of southwest airflow which is on the northwest side of subtropical high. At 11:00 BT, Xingtai sounding data showed that the atmosphere was extremely unstable and the lowlevel water vapor was deep and unusually vigorous. The CAPE value was 3874 J·kg-1, CIN was 22 J·kg-1 and the height of 8 g·kg-1 specific humidity extended to 600 hPa. The surface dewpoint temperature was nearly 30℃. (3) Near the 850 hPa warm shear line, the two surface shear lines merged and mesoscale frontogenesis was the key factor of initiation. Two cloud bands were also visible on the satellite image, enhancing convergence. So cumulus clouds developed in the convergence zone, and small cumulus clouds developed in the morning near the warm shear line. As the convergence was strengthened, the mesoscale convective system was formed in the eastwest direction. (4) After thunderstorm is triggered, its movement and propagation are the difficulties of forecasting, because it determines the lasting time of convective precipitation. In this case, under the influence of the convergence line and the storm gusts, new thunderstorm initiation in the west part of the shear line, and the northsouth cloud street met the shear line on the south side of the shear line, causing the thunderstorm to spread westward and move southward. So the propagation direction was west by south. Under the influence of southwest airflow, the convective cells moved northeastward, namely, the advection direction was east, which was opposite to the direction of propagation. Thus, the “train effect” was formed. Cloud streets showed that there was a supplement of the south warm and humid air flow under the inversion layer in the south of the shear line. In addition, the convective storm gusts triggered new thunderstorms again, making convective storms sustained.
3 Analysis of Moisture Source and Transport of Snowstorm in Hooked Cloud Area of an Occluded Cyclone
2018, 44(10):1267-1274.
DOI: 10.7519/j.issn.1000-0526.2018.10.003
Abstract:
The snowstorm that occurred with an occluded cyclone on 25 November 2013 was analyzed using conventional observations, FY2E satellite images and NCEP reanalysis data. The 120 h backwrad trajectories ending at 08:00 BT 25 November 2013 were simulated with HYSPLIT model. The results showed that the snowstorm was located in hooked cloud area of an occluded cyclone with mesoscale features. Of the 6 backward trajectories at each release point, only one trajectory came from the upper troposphere over the region to the west of Xinjiang and 5 trajectories originated from the lowmiddle troposphere over Mongolia or northern China. The air parcels along trajectory moved horizontally with weak descending towards eastern or southeastern regions. Then the air parcels in the lowmiddle troposphere went through Bohai Sea and Sea of Japan during 72-24 h while the air parcels in the middleupper troposphere passed over Yellow Sea or East Sea of China. Finally all parcels went up to snow area in several hours. Sea of Japan was an important source of moisture and Bohai Sea was the second source with airsea interaction while air parcels from East Asia land contained less water vapour. The longer distance and persisting time in Sea of Japan, the more moisture of the air parcel. The air parcels with high specific humidity and relative humidity moving quickly with southerly or southeast winds resulted in the snowstorm event.
The snowstorm that occurred with an occluded cyclone on 25 November 2013 was analyzed using conventional observations, FY2E satellite images and NCEP reanalysis data. The 120 h backwrad trajectories ending at 08:00 BT 25 November 2013 were simulated with HYSPLIT model. The results showed that the snowstorm was located in hooked cloud area of an occluded cyclone with mesoscale features. Of the 6 backward trajectories at each release point, only one trajectory came from the upper troposphere over the region to the west of Xinjiang and 5 trajectories originated from the lowmiddle troposphere over Mongolia or northern China. The air parcels along trajectory moved horizontally with weak descending towards eastern or southeastern regions. Then the air parcels in the lowmiddle troposphere went through Bohai Sea and Sea of Japan during 72-24 h while the air parcels in the middleupper troposphere passed over Yellow Sea or East Sea of China. Finally all parcels went up to snow area in several hours. Sea of Japan was an important source of moisture and Bohai Sea was the second source with airsea interaction while air parcels from East Asia land contained less water vapour. The longer distance and persisting time in Sea of Japan, the more moisture of the air parcel. The air parcels with high specific humidity and relative humidity moving quickly with southerly or southeast winds resulted in the snowstorm event.
2018, 44(10):1275-1285.
DOI: 10.7519/j.issn.1000-0526.2018.10.004
Abstract:
This paper analyses the convergence characteristics of explosive spiral cloud band of Typhoon Saola by using variety of observation data, wind decomposing, ShumanShapiro filtering and TREC (Tracking Radar Echoes by Correlation) wind inversion methods. The results indicate that spiral cloud band formed in the background of largescale convergence from the mesoscale filter wind, variation wind and divergent wind after decomposition. The lowlevel rotational wind was the major contributor to the horizontal kinetic energy input, which strengthened the lowlayer momentum accumulation. Besides, the divergent wind strengthened the convergence. The upper divergent wind was the major contributor to kinetic energy output, which strengthened the upper divergence. The rotational and divergent wind strengthened the vertical motion, promoting the development of severe spiral cloud band. After surface mesoscale filtering, we could see obvious mesoscale convergence or vortex in the two areas, which were also reflected in higher levels. Thus, the mesoscale convergence zone and spiral cloud band affect each other.
This paper analyses the convergence characteristics of explosive spiral cloud band of Typhoon Saola by using variety of observation data, wind decomposing, ShumanShapiro filtering and TREC (Tracking Radar Echoes by Correlation) wind inversion methods. The results indicate that spiral cloud band formed in the background of largescale convergence from the mesoscale filter wind, variation wind and divergent wind after decomposition. The lowlevel rotational wind was the major contributor to the horizontal kinetic energy input, which strengthened the lowlayer momentum accumulation. Besides, the divergent wind strengthened the convergence. The upper divergent wind was the major contributor to kinetic energy output, which strengthened the upper divergence. The rotational and divergent wind strengthened the vertical motion, promoting the development of severe spiral cloud band. After surface mesoscale filtering, we could see obvious mesoscale convergence or vortex in the two areas, which were also reflected in higher levels. Thus, the mesoscale convergence zone and spiral cloud band affect each other.
2018, 44(10):1286-1294.
DOI: 10.7519/j.issn.1000-0526.2018.10.005
Abstract:
Using the monthly mean temperature observation data from 17 meteorological observation stations in Hainan Province in last 40 years, according to “the Warm Winter Grade” national standard, the temporal and spatial distribution of cold winter is analyzed in this paper. On this basis, using 74 kinds of circulation index data provided by the National Climate Centre and NCEP/NCAR reanalysis datasets from 1977 to 2017, and the NOAA ERSST data, and the Ni〖AKn~D〗o3.4 and AO index data, this paper analyzes the causes of the cold winter over Hainan. The results show that the winter temperature over Hainan has the interdecadal characteristics in the last 40 years. In recent years, cold winter has happened frequently and appeared 12 times. The frequency of cold winter in southern Hainan is more than that in northern and central parts. The strength of the cold winter in northern area is stronger than that in southern. In cold winter, atmospheric circulation is abnormal in troposphere. Siberian high pressure and East Asian winter monsoon are strong, correspondingly the subtropical high pressure is weak, lying on an eastward position. All these reasons result in the winter temperature lower than average. In addition, the sea temperature of South China Sea is lower than average. The collective effect of cold phase of ENSO index and positive phase of AO index is beneficial to induce the anomalies of atmospheric circulation in troposphere, leading to low temperature over Hainan. Thus, cold winter appears.
Using the monthly mean temperature observation data from 17 meteorological observation stations in Hainan Province in last 40 years, according to “the Warm Winter Grade” national standard, the temporal and spatial distribution of cold winter is analyzed in this paper. On this basis, using 74 kinds of circulation index data provided by the National Climate Centre and NCEP/NCAR reanalysis datasets from 1977 to 2017, and the NOAA ERSST data, and the Ni〖AKn~D〗o3.4 and AO index data, this paper analyzes the causes of the cold winter over Hainan. The results show that the winter temperature over Hainan has the interdecadal characteristics in the last 40 years. In recent years, cold winter has happened frequently and appeared 12 times. The frequency of cold winter in southern Hainan is more than that in northern and central parts. The strength of the cold winter in northern area is stronger than that in southern. In cold winter, atmospheric circulation is abnormal in troposphere. Siberian high pressure and East Asian winter monsoon are strong, correspondingly the subtropical high pressure is weak, lying on an eastward position. All these reasons result in the winter temperature lower than average. In addition, the sea temperature of South China Sea is lower than average. The collective effect of cold phase of ENSO index and positive phase of AO index is beneficial to induce the anomalies of atmospheric circulation in troposphere, leading to low temperature over Hainan. Thus, cold winter appears.
2018, 44(10):1295-1305.
DOI: 10.7519/j.issn.1000-0526.2018.10.006
Abstract:
With the recent 58 summers data from 1958-2015, including precipitation from 55 observing stations over the Yellow River Valley and height field of NCEP/NCAR reanalysis 1 data etc., the characteristics of interannual variations for the summer rainfall in the Yellow River Valley and their causes associated with the synchronous variations of atmospheric circulations are analyzed by MannKendall test, composite analysis and MonteCarlo test methods in this paper. The results show that the reasons why the summer rainfall in the Yellow River Valley has been decreasing since 1958, in particular, significantly decreasing trend in the northern bend of Yellow River, are derived from the rising isobaric surface and weakened westerlies over the midhigh latitude of Eurasia. The climatic changes of the 58year rainfall in Yellow River Valley is divided into three different periods by two abrupt points in 1975 and 1996 according to natural changes in itself. During the period of 1958-1975, the low pressure circulations with stronger cold air dominated the Yellow River Valley and led to the larger interannual variations of anomalous precipitation whatever the above and below normal. In the phase 1976-1995, the reasons why the above normal rainfall happened to most sections of Yellow River Valley, are the development of Ural blocking high, and the negative height anomalies in troposphere dominated the regions from Baikal to Okhotsk, creating a deep trough over the Yellow River Valley. In addition, the warm and moist flow from South became stronger. In the recent 20 years, 1996-2015, most regions of Yellow River Valley suffered less rainfall, mainly due to the decreased heights of circulations over the northern Ural, and meanwhile the isobaric surface rising together over the areas from Caspian Sea to Baikal and to Okhotsk accompanied with weakened westerlies, which resulted in the weakened cold air and enhanced high pressure circulations controlling the Yellow River Valley. Moreover, the correlation analyses of rainfall in four basins of the Yellow River Valley with midhigh latitude blocking highs and the subtropical high in three different decades evidence the above conclusion further.
With the recent 58 summers data from 1958-2015, including precipitation from 55 observing stations over the Yellow River Valley and height field of NCEP/NCAR reanalysis 1 data etc., the characteristics of interannual variations for the summer rainfall in the Yellow River Valley and their causes associated with the synchronous variations of atmospheric circulations are analyzed by MannKendall test, composite analysis and MonteCarlo test methods in this paper. The results show that the reasons why the summer rainfall in the Yellow River Valley has been decreasing since 1958, in particular, significantly decreasing trend in the northern bend of Yellow River, are derived from the rising isobaric surface and weakened westerlies over the midhigh latitude of Eurasia. The climatic changes of the 58year rainfall in Yellow River Valley is divided into three different periods by two abrupt points in 1975 and 1996 according to natural changes in itself. During the period of 1958-1975, the low pressure circulations with stronger cold air dominated the Yellow River Valley and led to the larger interannual variations of anomalous precipitation whatever the above and below normal. In the phase 1976-1995, the reasons why the above normal rainfall happened to most sections of Yellow River Valley, are the development of Ural blocking high, and the negative height anomalies in troposphere dominated the regions from Baikal to Okhotsk, creating a deep trough over the Yellow River Valley. In addition, the warm and moist flow from South became stronger. In the recent 20 years, 1996-2015, most regions of Yellow River Valley suffered less rainfall, mainly due to the decreased heights of circulations over the northern Ural, and meanwhile the isobaric surface rising together over the areas from Caspian Sea to Baikal and to Okhotsk accompanied with weakened westerlies, which resulted in the weakened cold air and enhanced high pressure circulations controlling the Yellow River Valley. Moreover, the correlation analyses of rainfall in four basins of the Yellow River Valley with midhigh latitude blocking highs and the subtropical high in three different decades evidence the above conclusion further.
2018, 44(10):1306-1317.
DOI: 10.7519/j.issn.1000-0526.2018.10.007
Abstract:
The data from 18 sites of TCCON are used for the validation of GOSAT XCO2 products from 2009 to 2017, which show a consistency between satellite data and groundbased measurements. Biases between the satellite data and groundbased measurements in East Asia, North America, Europe and Oceania are 2.23±2.69, 2.19±2.19, 2.01±2.49， 1.59±1.79 ppm, respectively, and the correlation coefficient is not less than 0.75. The accuracy of satellite products is higher in the range of 30°S-60°N, but slightly lower in high latitudes. In addition, authors also use GOSAT L2 XCO2 products to analyze the change of global atmospheric CO2 in longterm sequence. The results show that the concentration of global atmospheric CO2 shows a continuous upward trend from 2009 to 2017, and the global average annual growth rate is 2.22 ppm·a-1. There are some fastgrowing countries and regions, including China, the United States, India, and Africa. Influenced by natural emissions of El Ni〖AKn~D〗o, the concentration of atmospheric CO2 grew the fastest in 2016, with the growth rate being more than 3 ppm·a-1.
The data from 18 sites of TCCON are used for the validation of GOSAT XCO2 products from 2009 to 2017, which show a consistency between satellite data and groundbased measurements. Biases between the satellite data and groundbased measurements in East Asia, North America, Europe and Oceania are 2.23±2.69, 2.19±2.19, 2.01±2.49， 1.59±1.79 ppm, respectively, and the correlation coefficient is not less than 0.75. The accuracy of satellite products is higher in the range of 30°S-60°N, but slightly lower in high latitudes. In addition, authors also use GOSAT L2 XCO2 products to analyze the change of global atmospheric CO2 in longterm sequence. The results show that the concentration of global atmospheric CO2 shows a continuous upward trend from 2009 to 2017, and the global average annual growth rate is 2.22 ppm·a-1. There are some fastgrowing countries and regions, including China, the United States, India, and Africa. Influenced by natural emissions of El Ni〖AKn~D〗o, the concentration of atmospheric CO2 grew the fastest in 2016, with the growth rate being more than 3 ppm·a-1.
2018, 44(10):1318-1324.
DOI: 10.7519/j.issn.1000-0526.2018.10.008
Abstract:
Based on the new generation weather radar data of Zhengzhou from May to September during 2009-2016, this paper checked the storm tracking information products of 5615 cell echoes according to different forecast time, different life cycles and different types of severe convection, processes, and also systematically analyzed the distance errors and direction errors of storm tracking information products of cell echoes and discussed the direction deviation between real condition and forecast products. The results show that the distance errors of 30 and 60 min products are 9.3 and 16.9 km respectively, and the direction error is not so big. The error of distance increases 〖JP2〗with the extension of lead time of forecasts; The average〖JP〗 distance error of the 30 min forecast products of cell echoes with life cycles less than 1 h, 1-2 h and more than 2 h are 9.8, 8.8 and 7.7 km, and the azimuth errors are 25.5°, 25.7° and 22.8° 〖JP2〗respectively. The ave〖JP〗rage distance error of the 60 min forecast products with life cycles of 1-2 h and more than 2 h are 17.3 and 15.9 km, and the direction errors are 24.4° and 22.7°, respectively. With the extension of life cycles of the cells, the errors of direction and distance are decreasing, the errors of northwest airflow type and the southwest airflow type are entirety the same, and the direction and distance errors of the two types of echoes are almost the same in 30 and 60 min. The errors of the southwest airflow type are slightly smaller than those of the northwest airflow type. The number of different types and forecast efficiency are that the observation data biased to the right of the forecast path are more than that of the left side, and the proportion of 30 and 60 min biased to right are 57.5% and 55.6%, respectively.
Based on the new generation weather radar data of Zhengzhou from May to September during 2009-2016, this paper checked the storm tracking information products of 5615 cell echoes according to different forecast time, different life cycles and different types of severe convection, processes, and also systematically analyzed the distance errors and direction errors of storm tracking information products of cell echoes and discussed the direction deviation between real condition and forecast products. The results show that the distance errors of 30 and 60 min products are 9.3 and 16.9 km respectively, and the direction error is not so big. The error of distance increases 〖JP2〗with the extension of lead time of forecasts; The average〖JP〗 distance error of the 30 min forecast products of cell echoes with life cycles less than 1 h, 1-2 h and more than 2 h are 9.8, 8.8 and 7.7 km, and the azimuth errors are 25.5°, 25.7° and 22.8° 〖JP2〗respectively. The ave〖JP〗rage distance error of the 60 min forecast products with life cycles of 1-2 h and more than 2 h are 17.3 and 15.9 km, and the direction errors are 24.4° and 22.7°, respectively. With the extension of life cycles of the cells, the errors of direction and distance are decreasing, the errors of northwest airflow type and the southwest airflow type are entirety the same, and the direction and distance errors of the two types of echoes are almost the same in 30 and 60 min. The errors of the southwest airflow type are slightly smaller than those of the northwest airflow type. The number of different types and forecast efficiency are that the observation data biased to the right of the forecast path are more than that of the left side, and the proportion of 30 and 60 min biased to right are 57.5% and 55.6%, respectively.
2018, 44(10):1325-1331.
DOI: 10.7519/j.issn.1000-0526.2018.10.009
Abstract:
The observation data of satellite CloudSat are used to analyze the mechanisms of freezing rain in Guizhou Province. The results show that, for the freezing rain under icephased mechanism, reflectivity of cloud profile radar, ice water content and temperature profile of CloudSat data could describe the process of icephased particles melting into liquid clearly. Bright bands of reflectivity at the 0℃ layer of cloud profile radar are the direct reflection of the melting process, and ice water content data could represent the melting process in melting layer as well. For the freezing rain under the supercooled warm rain mechanism, CloudSat data could depict the falling process of precipitation particles kept in the supercooled liquid in environment of temperature below 0℃ vertically. This research proves that the Guizhou freezing rain has warm rain mechanism with melting layer based on observation of cloudphysics. With the existence of temperature inversion in vertical temperature profile, precipitation particles exist in the liquid state in melting layer but remain supercooled in environment of temperature below 0℃. The supercooled liquid precipitation particles could be heated when falling into melting layer, getting frosted into supercooled droplets in freezing layer below, colliding with surface objects and forming freezing rain with temperature below 0℃ at last. Thus, melting layer could not be used to distinguish the formation mechanism of freezing rain.
The observation data of satellite CloudSat are used to analyze the mechanisms of freezing rain in Guizhou Province. The results show that, for the freezing rain under icephased mechanism, reflectivity of cloud profile radar, ice water content and temperature profile of CloudSat data could describe the process of icephased particles melting into liquid clearly. Bright bands of reflectivity at the 0℃ layer of cloud profile radar are the direct reflection of the melting process, and ice water content data could represent the melting process in melting layer as well. For the freezing rain under the supercooled warm rain mechanism, CloudSat data could depict the falling process of precipitation particles kept in the supercooled liquid in environment of temperature below 0℃ vertically. This research proves that the Guizhou freezing rain has warm rain mechanism with melting layer based on observation of cloudphysics. With the existence of temperature inversion in vertical temperature profile, precipitation particles exist in the liquid state in melting layer but remain supercooled in environment of temperature below 0℃. The supercooled liquid precipitation particles could be heated when falling into melting layer, getting frosted into supercooled droplets in freezing layer below, colliding with surface objects and forming freezing rain with temperature below 0℃ at last. Thus, melting layer could not be used to distinguish the formation mechanism of freezing rain.
2018, 44(10):1332-1341.
DOI: 10.7519/j.issn.1000-0526.2018.10.010
Abstract:
The historical monthly mean surface relative humidity at 13 observation stations in Tianjin are homogenized by two methods establishing reference series of NCEP/DOE AMIPⅡ Reanalysis (R2) specific humidity data and observed relative humidity data. The results indicate that nine stations have significant breakpoints, accounting for 69% of Tianjins total stations. The main reason for the abrupt change is the automation referring to metadata information, and then is the relocation and instrument change. For the correction amplitude, the proportion of negative QuantileMatching (QM) correction is nearly 96.3%, ranging in -5.0%～-1.5% which accounts for more than 80% of the total correction. Here the changes of variances and trends of monthly mean surface relative humidity series before and after corrections are compared, implying that the artificialities due to some inhomogeneity factors in the series are largely corrected, and have reduced the abnormal dry tendency in relative humidity for a long time. Moreover, error analysis reveals that there is much higher consistency between the two datasets here and the data by Zhu Yani et al. (2015) by setting the latter as the reference. However, due to some subjective factors, the error values of MAE and SE between the two datasets are more than 3.0% at some individual stations, resulting in only above 84.6% and 76.9% stations with error values of MAE and SE from 0 to 2.0%, respectively. Accordingly, the technology of data processing used in this paper is more superior to those before to a certain extent.
The historical monthly mean surface relative humidity at 13 observation stations in Tianjin are homogenized by two methods establishing reference series of NCEP/DOE AMIPⅡ Reanalysis (R2) specific humidity data and observed relative humidity data. The results indicate that nine stations have significant breakpoints, accounting for 69% of Tianjins total stations. The main reason for the abrupt change is the automation referring to metadata information, and then is the relocation and instrument change. For the correction amplitude, the proportion of negative QuantileMatching (QM) correction is nearly 96.3%, ranging in -5.0%～-1.5% which accounts for more than 80% of the total correction. Here the changes of variances and trends of monthly mean surface relative humidity series before and after corrections are compared, implying that the artificialities due to some inhomogeneity factors in the series are largely corrected, and have reduced the abnormal dry tendency in relative humidity for a long time. Moreover, error analysis reveals that there is much higher consistency between the two datasets here and the data by Zhu Yani et al. (2015) by setting the latter as the reference. However, due to some subjective factors, the error values of MAE and SE between the two datasets are more than 3.0% at some individual stations, resulting in only above 84.6% and 76.9% stations with error values of MAE and SE from 0 to 2.0%, respectively. Accordingly, the technology of data processing used in this paper is more superior to those before to a certain extent.
2018, 44(10):1342-1351.
DOI: 10.7519/j.issn.1000-0526.2018.10.011
Abstract:
During 3-5 March 2016, a large range of sea fog continuously occurred over most areas of the Yellow Sea and Bohai Sea. In this article, satellite remote sensing monitoring data are used to analyze the morphological variation of the sea fog event during the three stages of generation, development and extinction, and also the lack of sea fog over southeast coast of Shandong Peninsula and the causes for the evolution of the sea fog this time are discussed. The results show that (1) in the early stage of the sea fog formation, there was no sea fog under the southerly wind on the southeast coast of Shandong Peninsula as a result of weak cyclone, instability of atmospheric stratification, and low humidity. Affected by low pressure, no water vapor converged. (2) During the mature period of the sea fog, the air temperature was lower than that on the sea surface. This condition was caused by the longwave radiation from the top of the fog within the 0-1℃ temperature difference between the air and sea surface. The southerly heating low air from the Northwest Pacific Ocean was beneficial to the formation of sea fog. The water vapor convergence was monitored obviously in this area. (3) The effect of vertical wind shear especially from 925 hPa to 1000 hPa was positive to the maintenance of inversion layer and the development of vertical height of the sea fog, eventually forming the typical sea fog with the certain thickness.
During 3-5 March 2016, a large range of sea fog continuously occurred over most areas of the Yellow Sea and Bohai Sea. In this article, satellite remote sensing monitoring data are used to analyze the morphological variation of the sea fog event during the three stages of generation, development and extinction, and also the lack of sea fog over southeast coast of Shandong Peninsula and the causes for the evolution of the sea fog this time are discussed. The results show that (1) in the early stage of the sea fog formation, there was no sea fog under the southerly wind on the southeast coast of Shandong Peninsula as a result of weak cyclone, instability of atmospheric stratification, and low humidity. Affected by low pressure, no water vapor converged. (2) During the mature period of the sea fog, the air temperature was lower than that on the sea surface. This condition was caused by the longwave radiation from the top of the fog within the 0-1℃ temperature difference between the air and sea surface. The southerly heating low air from the Northwest Pacific Ocean was beneficial to the formation of sea fog. The water vapor convergence was monitored obviously in this area. (3) The effect of vertical wind shear especially from 925 hPa to 1000 hPa was positive to the maintenance of inversion layer and the development of vertical height of the sea fog, eventually forming the typical sea fog with the certain thickness.
2018, 44(10):1352-1359.
DOI: 10.7519/j.issn.1000-0526.2018.10.012
Abstract:
The experimental data from Baicheng Station, Jilin Province, are used to calibrate the parameters in crop model WOFOST, and the independent observation data including development stages, leaf area index, biomass for each organ are adopted to verify and evaluate the adaption. The parameters from Baicheng and Yushu Stations represent the parameters in the western and central parts of Jilin Province. The developmental phase data, weather data and daily soil moisture data under optimization from automatic soil observation stations are used in the simulation of WOFOST model. To improve the simulation accuracy of WOFOST, the volume content of soil calculated based on precipitation is replaced by the volume content of soil calculated based on the observed soil moisture data, which was used in the nextstep computing of model to simulate the biomass from 2001 to 2016. The improvement rate of volume content of soil (PD) is constructed to analyze the different changes by using soil moisture data and precipitation data. The results showed that (1) the model simulation is more accurate for the growth period, leaf area, total biomass and leaf biomass of spring maize at Baicheng Station, while the simulation effect of spike biomass is general. (2) From the perspective of the typical Baicheng Station, there is a significant positive correlation between the simulated value of spike biomass and precipitation, and the simulation effect of soil in years with less precipitation is significantly better than that driven by precipitation. (3) Regionally speaking, the driving effect of soil moisture in regions dominated by salinealkali soil or with less precipitation years is better than that driven by precipitation. In the region where the soil type is backland and in the year with more precipitation, the simulation results of the two are similar. (4) In general, the WOFOST model can significantly improve the simulation accuracy by replacing precipitation with observed soil moisture.
The experimental data from Baicheng Station, Jilin Province, are used to calibrate the parameters in crop model WOFOST, and the independent observation data including development stages, leaf area index, biomass for each organ are adopted to verify and evaluate the adaption. The parameters from Baicheng and Yushu Stations represent the parameters in the western and central parts of Jilin Province. The developmental phase data, weather data and daily soil moisture data under optimization from automatic soil observation stations are used in the simulation of WOFOST model. To improve the simulation accuracy of WOFOST, the volume content of soil calculated based on precipitation is replaced by the volume content of soil calculated based on the observed soil moisture data, which was used in the nextstep computing of model to simulate the biomass from 2001 to 2016. The improvement rate of volume content of soil (PD) is constructed to analyze the different changes by using soil moisture data and precipitation data. The results showed that (1) the model simulation is more accurate for the growth period, leaf area, total biomass and leaf biomass of spring maize at Baicheng Station, while the simulation effect of spike biomass is general. (2) From the perspective of the typical Baicheng Station, there is a significant positive correlation between the simulated value of spike biomass and precipitation, and the simulation effect of soil in years with less precipitation is significantly better than that driven by precipitation. (3) Regionally speaking, the driving effect of soil moisture in regions dominated by salinealkali soil or with less precipitation years is better than that driven by precipitation. In the region where the soil type is backland and in the year with more precipitation, the simulation results of the two are similar. (4) In general, the WOFOST model can significantly improve the simulation accuracy by replacing precipitation with observed soil moisture.
2018, 44(10):1360-1369.
DOI: 10.7519/j.issn.1000-0526.2018.10.013
Abstract:
From March to May 2018, the mean temperature in China ranks the highest since 1961. The temperature is almost above normal in China, with the warmest regions located to the south of the Yangtze River and the central part of northern China. The mean precipitation of China is a little above normal. For eastern China, the precipitation is more than normal to the north of Yangtze River while it is less than normal to the south. As for western China, the positive anomalies of precipitation are observed in most parts of Southwest China, southeastern part of Northwest China and northern and western Xinjiang, while the negative anomalies are mainly in southern Xinjiang, western Qinghai and northwestern Gansu. The zonal wave train stretching from North Atlantic to Northeast Asia via Eurasia Continent at the midhigh latitudes mainly contributes to the climate anomalies in China from March to May 2018, with the trough to the east of Ural Mountains and the ridge over Northeast Asia occupying the key circulations. The anomalous high pressure, especially the ridge over Northeast Asia controls the extensive regions over the midlow latitudes of Asia to cause the higherthannormal temperature over most China from March to May 2018. The trough to the east of Ural Mountains favors the southward outbreak of the cold air, while the ridge over Northeast Asia leads the moisture to transport westward and northward from the western Pacific. Then, the cold and dry air mass merges with the warm and moist one to form the above normal precipitation over the region to the north of the Yangtze River and West China. Meanwhile, the anomalous cyclonic circulation over the South China Sea and the tropical western Pacific contributes to the belownormal precipitation from the region to the south of the Yangtze River to South China. Though a weak La Ni〖AKn~D〗a event occurs during the winter of 2017/2018 and the positive phase of North Atlantic Triple (NAT) mode persists from March to May 2018, they put limited impacts on the 2018s spring rainfall anomalies in China but the circulations dominate. Further analyses present that the intensity of the the trough to the east of Ural Mountains and the ridge over Northeast Asia has high correlations with both temperature and precipitation of China during spring, favoring the abovenormal temperature in most of China and morethannormal precipitation in West China and to the north of the Yangtze River but lessthannormal precipitation to the south. Significant negative correlation exists between the intensity of the two circulations and they are both closely connected with the Eurasian (EU) teleconnection pattern. Moreover, the ridge over Northeast Asia is also highly correlated with the positive phase of AO.
From March to May 2018, the mean temperature in China ranks the highest since 1961. The temperature is almost above normal in China, with the warmest regions located to the south of the Yangtze River and the central part of northern China. The mean precipitation of China is a little above normal. For eastern China, the precipitation is more than normal to the north of Yangtze River while it is less than normal to the south. As for western China, the positive anomalies of precipitation are observed in most parts of Southwest China, southeastern part of Northwest China and northern and western Xinjiang, while the negative anomalies are mainly in southern Xinjiang, western Qinghai and northwestern Gansu. The zonal wave train stretching from North Atlantic to Northeast Asia via Eurasia Continent at the midhigh latitudes mainly contributes to the climate anomalies in China from March to May 2018, with the trough to the east of Ural Mountains and the ridge over Northeast Asia occupying the key circulations. The anomalous high pressure, especially the ridge over Northeast Asia controls the extensive regions over the midlow latitudes of Asia to cause the higherthannormal temperature over most China from March to May 2018. The trough to the east of Ural Mountains favors the southward outbreak of the cold air, while the ridge over Northeast Asia leads the moisture to transport westward and northward from the western Pacific. Then, the cold and dry air mass merges with the warm and moist one to form the above normal precipitation over the region to the north of the Yangtze River and West China. Meanwhile, the anomalous cyclonic circulation over the South China Sea and the tropical western Pacific contributes to the belownormal precipitation from the region to the south of the Yangtze River to South China. Though a weak La Ni〖AKn~D〗a event occurs during the winter of 2017/2018 and the positive phase of North Atlantic Triple (NAT) mode persists from March to May 2018, they put limited impacts on the 2018s spring rainfall anomalies in China but the circulations dominate. Further analyses present that the intensity of the the trough to the east of Ural Mountains and the ridge over Northeast Asia has high correlations with both temperature and precipitation of China during spring, favoring the abovenormal temperature in most of China and morethannormal precipitation in West China and to the north of the Yangtze River but lessthannormal precipitation to the south. Significant negative correlation exists between the intensity of the two circulations and they are both closely connected with the Eurasian (EU) teleconnection pattern. Moreover, the ridge over Northeast Asia is also highly correlated with the positive phase of AO.
2018, 44(10):1370-1376.
DOI: 10.7519/j.issn.1000-0526.2018.10.014
Abstract:
The main characteristics of the general atmospheric circulation in July 2018 are as follows. There was one polar vortex center in the Northern Hemisphere, which was stronger than usual. The 500 hPa geopotential height presented the distribution of a 4wave pattern in the midhigh latitude of the Northern Hemisphere. The strength of western Pacific subtropical high was much stronger and its location was by north compared to normal years. The monthly mean temperature was 22.9℃, 1.1℃ higher than normal, which ranks the third highest since 1961. The monthly mean precipitation amount over the whole country was 133.8 mm, which is more than normal (120.6 mm) by 11%. For the distribution of precipitation, northern China received more rain than usual, but the south had less. Seven rainfall processes with some extreme records occurred in China this month. Five tropical cyclones were active over the Northwest Pacific and the South China Sea, and three of them landed. The total and landing numbers of tropical cyclones were more than usual. The longlasting high temperature events happened in central and eastern China. Meanwhile, severe convective events occurred frequently, influencing a wide range of areas.
The main characteristics of the general atmospheric circulation in July 2018 are as follows. There was one polar vortex center in the Northern Hemisphere, which was stronger than usual. The 500 hPa geopotential height presented the distribution of a 4wave pattern in the midhigh latitude of the Northern Hemisphere. The strength of western Pacific subtropical high was much stronger and its location was by north compared to normal years. The monthly mean temperature was 22.9℃, 1.1℃ higher than normal, which ranks the third highest since 1961. The monthly mean precipitation amount over the whole country was 133.8 mm, which is more than normal (120.6 mm) by 11%. For the distribution of precipitation, northern China received more rain than usual, but the south had less. Seven rainfall processes with some extreme records occurred in China this month. Five tropical cyclones were active over the Northwest Pacific and the South China Sea, and three of them landed. The total and landing numbers of tropical cyclones were more than usual. The longlasting high temperature events happened in central and eastern China. Meanwhile, severe convective events occurred frequently, influencing a wide range of areas.
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