ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 45,Issue 4,2019 Table of Contents
JIN Ronghua
,
DAI Kan
,
ZHAO Ruixia
,
CAO Yong
,
XUE Feng
,
LIU Couhua
,
ZHAO Shengrong
,
LI Yong
,
WEI Qing
2019, 45(4):445-457.
DOI: 10.7519/j.issn.1000-0526.2019.04.001
Abstract:
This paper reviews the development of the technology for seamless fine gridded weather forecasting in China since 2014. And the key technical difficulties in the future development are analyzed. It is pointed out that the high spatiotemporal resolution observations capturing the fine structure of weather systems, the analysis products by multisource data fusion, the realtime rapid updating assimilation and prediction system, the high resolution regional model providing shorttime and shortterm weather prediction, the global numerical forecast model providing 10 days’ weather forecasting, and the oceanatmosphere coupled ensemble prediction system providing 46 days’ weather prediction, have jointly established the premise and foundation of the seamless gridded weather forecasts. After nearly 5 years’ exploration and constant efforts, the technology system of seamless fine gridded forecasting with different temporal resolutions has been established. The highfrequency lagrangian extrapolation skills are used for 0-4 h forecasting based on GRAPESMeso model forecast products and radar data over China. For the 4 h to 30 d leadtime forecasting, it mainly depends on the downscaling, error correction, model output statistics and postprocessing methodologies based on regional and global models of different spatiotemporal resolutions to improve forecast skills and resolution. At the same time, automatic and intelligent interactive forecasting platform is developed to meet the demand of combining efficient objective forecasting with forecasters’ subjective intelligence. In order to assess and track the performance of high resolution gridded forecasting, a spatial analysis verification method based on gridded observation data is developed. It is also stressed that the future gridded forecasting technology system should be able to reflect the latest technology development including the artificial intelligence application, more advanced statistical postprocessing skills, key technics for consistency forecasting and unified complete technical architecture and standards.
This paper reviews the development of the technology for seamless fine gridded weather forecasting in China since 2014. And the key technical difficulties in the future development are analyzed. It is pointed out that the high spatiotemporal resolution observations capturing the fine structure of weather systems, the analysis products by multisource data fusion, the realtime rapid updating assimilation and prediction system, the high resolution regional model providing shorttime and shortterm weather prediction, the global numerical forecast model providing 10 days’ weather forecasting, and the oceanatmosphere coupled ensemble prediction system providing 46 days’ weather prediction, have jointly established the premise and foundation of the seamless gridded weather forecasts. After nearly 5 years’ exploration and constant efforts, the technology system of seamless fine gridded forecasting with different temporal resolutions has been established. The highfrequency lagrangian extrapolation skills are used for 0-4 h forecasting based on GRAPESMeso model forecast products and radar data over China. For the 4 h to 30 d leadtime forecasting, it mainly depends on the downscaling, error correction, model output statistics and postprocessing methodologies based on regional and global models of different spatiotemporal resolutions to improve forecast skills and resolution. At the same time, automatic and intelligent interactive forecasting platform is developed to meet the demand of combining efficient objective forecasting with forecasters’ subjective intelligence. In order to assess and track the performance of high resolution gridded forecasting, a spatial analysis verification method based on gridded observation data is developed. It is also stressed that the future gridded forecasting technology system should be able to reflect the latest technology development including the artificial intelligence application, more advanced statistical postprocessing skills, key technics for consistency forecasting and unified complete technical architecture and standards.
2019, 45(4):458-468.
DOI: 10.7519/j.issn.1000-0526.2019.04.002
Abstract:
Atmospheric motion vectors (AMVs) can supply plenty of useful information for numerical weather prediction. With the launch of the Chinese next generation geostationary meteorological satellite FY-4A in December 2016, it is necessary to evaluate the quality of FY-4A AMVs for the analysis field and precipitation forecast by GRAPES of CMA. In this study, by comparing with the background field based on NCEP FNL data, the qualities of FY-4A AMVs were assessed, and the results suggested that the distribution of FY-4A is stable and the quality of FY-4A infrared AMVs is better than FY-4A water vapor AMVs. Based on GRAPES_RAFS, three numerical experiments were conducted to examine the impact on analysis and forecast for severe Typhoon Hato at 0000 UTC 23 August 2017. The findings showed that assimilating FY-4A AMVs, especially FY-4A water vapor AMVs, has certain adjusting effect on wind and height analysis fields. Furthermore, due to the improvement of the initial fields for the model prediction, the performance of the precipitaion forecast was improved. Conclusively, the FY-4A AMVs have positive impact on analysis field and precipitation forecast of GRAPES.
Atmospheric motion vectors (AMVs) can supply plenty of useful information for numerical weather prediction. With the launch of the Chinese next generation geostationary meteorological satellite FY-4A in December 2016, it is necessary to evaluate the quality of FY-4A AMVs for the analysis field and precipitation forecast by GRAPES of CMA. In this study, by comparing with the background field based on NCEP FNL data, the qualities of FY-4A AMVs were assessed, and the results suggested that the distribution of FY-4A is stable and the quality of FY-4A infrared AMVs is better than FY-4A water vapor AMVs. Based on GRAPES_RAFS, three numerical experiments were conducted to examine the impact on analysis and forecast for severe Typhoon Hato at 0000 UTC 23 August 2017. The findings showed that assimilating FY-4A AMVs, especially FY-4A water vapor AMVs, has certain adjusting effect on wind and height analysis fields. Furthermore, due to the improvement of the initial fields for the model prediction, the performance of the precipitaion forecast was improved. Conclusively, the FY-4A AMVs have positive impact on analysis field and precipitation forecast of GRAPES.
2019, 45(4):469-482.
DOI: 10.7519/j.issn.1000-0526.2019.04.003
Abstract:
Based on the realtime forecast and analysis data of 2 m temperature from the T639 ensemble forecast system in China, the climatic percentile distribution is estimated for both realtime forecast and analysis data, and the forecasts of extreme high temperature events and extreme low temperature at typical stations over China in 2016 are verified and evaluated. The analysis results show that the forecasted climate percentile distribution at different lead time is basically the same as the percentile distribution of the analysis for a given station site, but they are different to some degree between different regions and different seasons. The results of the Talagrand distribution show that there is a warm bias in the forecasts of Harbin and Changsha Stations by the T639 ensemble system and a cold bias in the predictions of Beijing and Lhasa Stations. The other typical stations show a low ensemble spread. Based on the definition of historical climate percentile, the 2016 extreme temperature identified, forecasted and verified. The results of TS score show that the T639 ensemble system has a certain forecasting performance for extreme temperatures in China, but the prediction skill has apparent difference in different regions. The extreme high temperature has higher prediction skills in the south to the Yangtze River and the Northeast China, and the extreme low temperature has higher prediction skills in the northern and southern parts of China. The comparisons of different forecasting methods show that the ensemble mean method has a smoothing effect on the extreme signals and the overall prediction skill is low. The ensemble model method improves obviously the extreme low temperature skill, while the method of using maximum or minimum in all ensemble members can amplify the extreme signals and increase significantly the prediction skill of extreme high temperature, but not clear for low temperature. Thus, we can see that proper extraction of extreme information in ensemble forecasting is of crucial importance.
Based on the realtime forecast and analysis data of 2 m temperature from the T639 ensemble forecast system in China, the climatic percentile distribution is estimated for both realtime forecast and analysis data, and the forecasts of extreme high temperature events and extreme low temperature at typical stations over China in 2016 are verified and evaluated. The analysis results show that the forecasted climate percentile distribution at different lead time is basically the same as the percentile distribution of the analysis for a given station site, but they are different to some degree between different regions and different seasons. The results of the Talagrand distribution show that there is a warm bias in the forecasts of Harbin and Changsha Stations by the T639 ensemble system and a cold bias in the predictions of Beijing and Lhasa Stations. The other typical stations show a low ensemble spread. Based on the definition of historical climate percentile, the 2016 extreme temperature identified, forecasted and verified. The results of TS score show that the T639 ensemble system has a certain forecasting performance for extreme temperatures in China, but the prediction skill has apparent difference in different regions. The extreme high temperature has higher prediction skills in the south to the Yangtze River and the Northeast China, and the extreme low temperature has higher prediction skills in the northern and southern parts of China. The comparisons of different forecasting methods show that the ensemble mean method has a smoothing effect on the extreme signals and the overall prediction skill is low. The ensemble model method improves obviously the extreme low temperature skill, while the method of using maximum or minimum in all ensemble members can amplify the extreme signals and increase significantly the prediction skill of extreme high temperature, but not clear for low temperature. Thus, we can see that proper extraction of extreme information in ensemble forecasting is of crucial importance.
2019, 45(4):483-495.
DOI: 10.7519/j.issn.1000-0526.2019.04.004
Abstract:
Based on NCEP (National Centers of Environmental Prediction) analyses data and various observations from automatic weather stations, cloud-to-ground lightning positioning system, stationary meteo-rological satellites, and weather radars, this paper uses “ingredient-based method” to have comprehensively analyzed environmental conditions, evolution characteristics, trigger and development mechanisms, and forecasting difficulties of a long-lived arc-shaped squall line which swept the southeastern part of Hebei Province and most of Shandong Province on 30 June 2016. Convective available potential energy (CAPE) above 4000 J·kg-1 and 0-6 km vertical wind shear with moderate intensity were very favorable for the development of supercell storms, large hail, high winds and the maintenance of squall line. Level of the wet bulb temperature zero (WBZ) at 3.6 km altitude was in favor of large hail. Low relative humidity, dewpoint deficit of the middle troposphere up to 28℃, larger vertical temperature lapse rate and downdraft convective available potential energy (DCAPE) favored very much bow echoes and high winds. Convective inhibition energy (CIN) ≥200 J·kg-1 inhibited the earlier convection. The convection initiation of the squall line was triggered from a cumulus line under the impacts together with higher CAPE and less CIN made by increased surface temperature and humidity, significantly enhanced surface convergence line by the outflow of existing convective storms, enhanced convergence of boundary layer by the low-level southwesterly jet and the moving eastwards low-level northwesterly. Infrared temperature of black body (TBB) shows that the squall line developed from a linear cumulus line to a quasi-circular mesoscale convective complex, with mainly positive lightning and high winds in the low TBB area. Visible cloud images show that it had coarse texture, significant overshooting and rotation feature. Radar observations show that the squall line developed from a meso-β scale linear convective system to a meso-α-scale arc-shaped squall line with significant overhang echoes, bounded weak echo regions, mesocyclones, mesovortices, strong rear inflows, rear inflow notches, front inflow notches, mid-altitude radial convergences in mature stage, and extreme value of vertical integrated liquid, which are characteristics of storms producing large hail and high winds. And it was organized into an asymmetric carrot-like mode in the mature stage because of new convective storms initiated along the west side and the upper-level diffluent flows. Intense downdraft induced by high dewpoint deficit of the middle troposphere and strong rear inflow were the main cause for the formation of the bow echoes. The main causes of maintaining the squall line and bow echoes were the intense front inflow formed behind leading convergence line of the squall line. Weaker 500 hPa winds in the initial stage, larger CIN in the early morning, later CIN sharply decreasing, and weaker trigger condition were the difficulties of forecasting the squall line.
Based on NCEP (National Centers of Environmental Prediction) analyses data and various observations from automatic weather stations, cloud-to-ground lightning positioning system, stationary meteo-rological satellites, and weather radars, this paper uses “ingredient-based method” to have comprehensively analyzed environmental conditions, evolution characteristics, trigger and development mechanisms, and forecasting difficulties of a long-lived arc-shaped squall line which swept the southeastern part of Hebei Province and most of Shandong Province on 30 June 2016. Convective available potential energy (CAPE) above 4000 J·kg-1 and 0-6 km vertical wind shear with moderate intensity were very favorable for the development of supercell storms, large hail, high winds and the maintenance of squall line. Level of the wet bulb temperature zero (WBZ) at 3.6 km altitude was in favor of large hail. Low relative humidity, dewpoint deficit of the middle troposphere up to 28℃, larger vertical temperature lapse rate and downdraft convective available potential energy (DCAPE) favored very much bow echoes and high winds. Convective inhibition energy (CIN) ≥200 J·kg-1 inhibited the earlier convection. The convection initiation of the squall line was triggered from a cumulus line under the impacts together with higher CAPE and less CIN made by increased surface temperature and humidity, significantly enhanced surface convergence line by the outflow of existing convective storms, enhanced convergence of boundary layer by the low-level southwesterly jet and the moving eastwards low-level northwesterly. Infrared temperature of black body (TBB) shows that the squall line developed from a linear cumulus line to a quasi-circular mesoscale convective complex, with mainly positive lightning and high winds in the low TBB area. Visible cloud images show that it had coarse texture, significant overshooting and rotation feature. Radar observations show that the squall line developed from a meso-β scale linear convective system to a meso-α-scale arc-shaped squall line with significant overhang echoes, bounded weak echo regions, mesocyclones, mesovortices, strong rear inflows, rear inflow notches, front inflow notches, mid-altitude radial convergences in mature stage, and extreme value of vertical integrated liquid, which are characteristics of storms producing large hail and high winds. And it was organized into an asymmetric carrot-like mode in the mature stage because of new convective storms initiated along the west side and the upper-level diffluent flows. Intense downdraft induced by high dewpoint deficit of the middle troposphere and strong rear inflow were the main cause for the formation of the bow echoes. The main causes of maintaining the squall line and bow echoes were the intense front inflow formed behind leading convergence line of the squall line. Weaker 500 hPa winds in the initial stage, larger CIN in the early morning, later CIN sharply decreasing, and weaker trigger condition were the difficulties of forecasting the squall line.
5 Mechanism Analysis of Propagation and Extension of an Extensive Dense Fog Event over Eastern China
2019, 45(4):496-510.
DOI: 10.7519/j.issn.1000-0526.2019.04.005
Abstract:
Based on conventional observation data, NCEP reanalysis data, a massive dense fog process lasting from 31 December 2016 to 4 January 2017 in Eastern China are analyzed with the focus on propagation and extension mechanism. The results show that the dense fog process took cold anticyclone moving south on the evening of 1 January as a demarcation point. Before the cold anticyclone moved south, dense fog was limited to southern and central part of Hebei Province. After the cold anticyclone moved south, dense fog enhanced and spread widely, affecting many provinces including Jiangsu, Anhui, Henan, Hebei and Shandong, etc. The dense fog spread in a large range by cold anticyclone moving south, causing the lowlevel temperature inversion to be strengthened and the range of the inversion area to be expanded. The water vapor transport from the sea through Jiangsu, Anhui and Henan to Hebei provided sufficient water vapor for the wide spread of the dense fog.
Based on conventional observation data, NCEP reanalysis data, a massive dense fog process lasting from 31 December 2016 to 4 January 2017 in Eastern China are analyzed with the focus on propagation and extension mechanism. The results show that the dense fog process took cold anticyclone moving south on the evening of 1 January as a demarcation point. Before the cold anticyclone moved south, dense fog was limited to southern and central part of Hebei Province. After the cold anticyclone moved south, dense fog enhanced and spread widely, affecting many provinces including Jiangsu, Anhui, Henan, Hebei and Shandong, etc. The dense fog spread in a large range by cold anticyclone moving south, causing the lowlevel temperature inversion to be strengthened and the range of the inversion area to be expanded. The water vapor transport from the sea through Jiangsu, Anhui and Henan to Hebei provided sufficient water vapor for the wide spread of the dense fog.
2019, 45(4):511-521.
DOI: 10.7519/j.issn.1000-0526.2019.04.006
Abstract:
In order to investigate the reliability of total atmospheric water vapor data from L-band radiosonde observations (RS PW), the atmospheric water vapor of GNSS/MET remote sensing (GNSS PW) is taken as the reference standard in this paper to comparatively analyze and correct the observed RS PW at Shantou Station in 2013 and Nagqu Station from June 2016 to May 2017. Research and analysis show that RS PWs at the two stations are obviously smaller than GNSS PW, and the deviations are 7.4% and 9.8%, respectively. The deviation has obvious seasonal and diurnal variation characteristics. In summer it is most obvious, and is more obvious at 0000 UTC than at 1200 UTC. Solar radiation heating and air temperature changes in the daily and seasonal variations are important reasons for the deviation. According to solar radiation bias correction formula, the L bias correction algorithm is proposed and used for correction. Then the deviation is reduced obviously after correction.
In order to investigate the reliability of total atmospheric water vapor data from L-band radiosonde observations (RS PW), the atmospheric water vapor of GNSS/MET remote sensing (GNSS PW) is taken as the reference standard in this paper to comparatively analyze and correct the observed RS PW at Shantou Station in 2013 and Nagqu Station from June 2016 to May 2017. Research and analysis show that RS PWs at the two stations are obviously smaller than GNSS PW, and the deviations are 7.4% and 9.8%, respectively. The deviation has obvious seasonal and diurnal variation characteristics. In summer it is most obvious, and is more obvious at 0000 UTC than at 1200 UTC. Solar radiation heating and air temperature changes in the daily and seasonal variations are important reasons for the deviation. According to solar radiation bias correction formula, the L bias correction algorithm is proposed and used for correction. Then the deviation is reduced obviously after correction.
2019, 45(4):522-532.
DOI: 10.7519/j.issn.1000-0526.2019.04.007
Abstract:
The extreme precipitation event (EPE) is defined by relative index method of percent. This paper analyzes spatio-temporal characteristics by the indicators of threshold, frequency and intensity based on the daily rainfall data during growing season of rice in Heilongjiang from 1971 to 2016. The results show that high value of EPE threshold appears mainly in Central South Songnen Plain. The EPE happens mainly from May to September during growing season of rice, especially in the key reproductive growth stage of rice. During the 46 years, frequency of the EPE ranges from 18 to 72 days, showing the characteristics of meridional distribution and decreasing gradually from the east to the west. Usually, frequency of the EPE is the highest in late July over central and western regions, and that is the highest in May and September for the eastern regions. The lowest frequency of EPE is in June, so June is a safe period for rice production. As for the interdecadal difference from 1971 to 2016, the frequency is the most in recent 6 years, and the intensity is the largest for EPE, but in 1970s the situation is opposite. Thus, there is a high correlation between frequency and intensity of EPE. For small regions with rainfall observation, flood di-saster can mostly be designated with EPE, and emergence of EPE possibly indicate flood disaster.
The extreme precipitation event (EPE) is defined by relative index method of percent. This paper analyzes spatio-temporal characteristics by the indicators of threshold, frequency and intensity based on the daily rainfall data during growing season of rice in Heilongjiang from 1971 to 2016. The results show that high value of EPE threshold appears mainly in Central South Songnen Plain. The EPE happens mainly from May to September during growing season of rice, especially in the key reproductive growth stage of rice. During the 46 years, frequency of the EPE ranges from 18 to 72 days, showing the characteristics of meridional distribution and decreasing gradually from the east to the west. Usually, frequency of the EPE is the highest in late July over central and western regions, and that is the highest in May and September for the eastern regions. The lowest frequency of EPE is in June, so June is a safe period for rice production. As for the interdecadal difference from 1971 to 2016, the frequency is the most in recent 6 years, and the intensity is the largest for EPE, but in 1970s the situation is opposite. Thus, there is a high correlation between frequency and intensity of EPE. For small regions with rainfall observation, flood di-saster can mostly be designated with EPE, and emergence of EPE possibly indicate flood disaster.
2019, 45(4):533-542.
DOI: 10.7519/j.issn.1000-0526.2019.04.008
Abstract:
The concentration of greenhouse gases kept increasing in 2018, while the global mean temperatures were 0.99℃ above preindustrial levels, which was the fourth warmest year on record. The total amonnt of global glacier has been decreasing continuously for 31 years, and the sea ice extent of Arctic sea and Antarctic lay at a low level on record throughout the year. Global sea surface temperatures were positive above the 1981-2010 average, and the global mean sea level was rising steadily. The ocean heat content reached a new record highs, with the intensified impact of ocean acidification. Many significant weather and climate events occurred in 2018 and caused serious human casualties and socioeconomic losses, including a very active tropical cyclone season in Northern Hemisphere, the persistent dry and hot summer in large parts of Europe, the severe floods in Southwest India, the severe drought in eastern Australia, the cold and heavy snowstorms in Europe and America, as well as the wildfires and severe convective weather events in many parts of the world. This paper systematically summarizes the major global weather and climate events in 2018 and their impacts, and focuses on the possible causes of the worst flooding in India in the recent 100 years and the explosive low temperature, rainsnow and freezing events on the east coast of the United States, the two typical weather events analysis results show that under the combined action of the strengthening and persistent South Asia summer monsoon, northwestward monsoon trough position and strengthening Somali jet in August, the water vapor transport to India was in great quantities from southern Indian Ocean and Arabian Sea, causing continuous heavy rainfall and resulting in the worst flooding in India in recent 100 years. In early January, under the combined influence of coupled jet structure, strong ocean temperature gradient and high temperature surrounding cyclones, the winter windstorm Grayson intensified explosively, resulting in severe coldwave and snowstorm in the east coast of the United States.
The concentration of greenhouse gases kept increasing in 2018, while the global mean temperatures were 0.99℃ above preindustrial levels, which was the fourth warmest year on record. The total amonnt of global glacier has been decreasing continuously for 31 years, and the sea ice extent of Arctic sea and Antarctic lay at a low level on record throughout the year. Global sea surface temperatures were positive above the 1981-2010 average, and the global mean sea level was rising steadily. The ocean heat content reached a new record highs, with the intensified impact of ocean acidification. Many significant weather and climate events occurred in 2018 and caused serious human casualties and socioeconomic losses, including a very active tropical cyclone season in Northern Hemisphere, the persistent dry and hot summer in large parts of Europe, the severe floods in Southwest India, the severe drought in eastern Australia, the cold and heavy snowstorms in Europe and America, as well as the wildfires and severe convective weather events in many parts of the world. This paper systematically summarizes the major global weather and climate events in 2018 and their impacts, and focuses on the possible causes of the worst flooding in India in the recent 100 years and the explosive low temperature, rainsnow and freezing events on the east coast of the United States, the two typical weather events analysis results show that under the combined action of the strengthening and persistent South Asia summer monsoon, northwestward monsoon trough position and strengthening Somali jet in August, the water vapor transport to India was in great quantities from southern Indian Ocean and Arabian Sea, causing continuous heavy rainfall and resulting in the worst flooding in India in recent 100 years. In early January, under the combined influence of coupled jet structure, strong ocean temperature gradient and high temperature surrounding cyclones, the winter windstorm Grayson intensified explosively, resulting in severe coldwave and snowstorm in the east coast of the United States.
ZHOU Xingyan
,
ZENG Hongling
,
WANG Zunya
,
SUN Shao
,
CHEN Xianyan
,
LIU Yanju
,
ZOU Xukai
,
WANG Ling
,
ZHAO Lin
,
HOU Wei
,
WANG Youmin
,
ZHU Xiaojin
,
ZHONG Hailing
,
GUO Yanjun
,
HUANG Dapeng
,
LI Ying
,
ZHANG Yingxian
,
CAI Wenyue
,
SUN Leng
,
ZHANG Daquan
,
GU Wei
,
LI Duo
,
CUI Tong
,
SHI Shuai
2019, 45(4):543-552.
DOI: 10.7519/j.issn.1000-0526.2019.04.009
Abstract:
Climate in China was at a normal level in 2018 when fewer climate disasters occurred, relatively. Annual mean temperature (10.09℃) over China was 0.54℃ higher than normal. The temperature in spring and summer reached a record high, while the temperatures in autumn and winter were close to the normal. The annual mean precipitation over China was 673.8 mm with 7.0% more than normal. The seasonal precipitation was below normal in winter, near normal in spring, but above normal in summer and autumn respectively. The first rainy season in South China started later and ended earlier than normal with deficient precipitation. The dates of beginning and end of the rainy season in Southwest China were close to the climatological dates with more heavy precipitation. Meiyu season started later and ended earlier than normal with less precipitation during the rainy period. The rainy season in North China started earlier and ended earlier than normal with more rainfall. The autumn rain in West China started and ended late, with less rainfall. The dates of start and end of the rainy season in Northeast China were near the normal time with less rainfall during the rainy period. In 2018, the generated and landed typhoons were more than normal, featuring northward landing locations and severe disaster damage. Lowtemperature freezing and snow disasters occurred frequently, causing heavy losses in China. Comparatively, 〖JP2〗the effects of other disas〖JP〗ters such as torrential rains, floods, drought, severe convection, and dust were light.
Climate in China was at a normal level in 2018 when fewer climate disasters occurred, relatively. Annual mean temperature (10.09℃) over China was 0.54℃ higher than normal. The temperature in spring and summer reached a record high, while the temperatures in autumn and winter were close to the normal. The annual mean precipitation over China was 673.8 mm with 7.0% more than normal. The seasonal precipitation was below normal in winter, near normal in spring, but above normal in summer and autumn respectively. The first rainy season in South China started later and ended earlier than normal with deficient precipitation. The dates of beginning and end of the rainy season in Southwest China were close to the climatological dates with more heavy precipitation. Meiyu season started later and ended earlier than normal with less precipitation during the rainy period. The rainy season in North China started earlier and ended earlier than normal with more rainfall. The autumn rain in West China started and ended late, with less rainfall. The dates of start and end of the rainy season in Northeast China were near the normal time with less rainfall during the rainy period. In 2018, the generated and landed typhoons were more than normal, featuring northward landing locations and severe disaster damage. Lowtemperature freezing and snow disasters occurred frequently, causing heavy losses in China. Comparatively, 〖JP2〗the effects of other disas〖JP〗ters such as torrential rains, floods, drought, severe convection, and dust were light.
2019, 45(4):553-564.
DOI: 10.7519/j.issn.1000-0526.2019.04.010
Abstract:
In the summer (June to August) of 2018, precipitation was more than average over North China and South China, while it was less over the middle part of East China. Especially, floods were severe in the Yellow River Basin and droughts were observed in the Yangtze River Valley. The preflood season in South China and Meiyu season began later relatively, while the rainy season in North China began earlier. All these features were well predicted in the climate operation. The forecast also captured the anomalous features of the tropical cyclone frequency, tracks, intensity and active/inactive periods over the Northwest Pacific and South China Sea in 2018. Moreover, the forecast provided a correct prediction of the surface air temperature which was higher than average in most regions of China. Both diagnostic analyses and results from dynamic models were used to make the summer climate prediction in 2018. For the diagnostic analyses, La Ni〖AKn~D〗a event and the cold tropical Indian Ocean were considered to be important predictors. Under the influence of the tropical SSTA, the western Pacific subtropical high (WPSH) tended to stay more northward, cyclonic circulation anomaly dominated the Philippines and the East Asian summer monsoon (EASM) was stronger than normal. Dynamic climate models from Beijing Climate Centre and abroad showed similar results of the prediction for the key members of EASM system. The results of diagnostic analyses and dynamic models all indicated that the La Ni〖AKn~D〗a event and the cold tropical Indian Ocean were important precursory signals for the prediction of the climate anomaly in summer 2018, which supported less rainfall in the middle and lower reaches of the Yangtze River and more in northern part of China.
In the summer (June to August) of 2018, precipitation was more than average over North China and South China, while it was less over the middle part of East China. Especially, floods were severe in the Yellow River Basin and droughts were observed in the Yangtze River Valley. The preflood season in South China and Meiyu season began later relatively, while the rainy season in North China began earlier. All these features were well predicted in the climate operation. The forecast also captured the anomalous features of the tropical cyclone frequency, tracks, intensity and active/inactive periods over the Northwest Pacific and South China Sea in 2018. Moreover, the forecast provided a correct prediction of the surface air temperature which was higher than average in most regions of China. Both diagnostic analyses and results from dynamic models were used to make the summer climate prediction in 2018. For the diagnostic analyses, La Ni〖AKn~D〗a event and the cold tropical Indian Ocean were considered to be important predictors. Under the influence of the tropical SSTA, the western Pacific subtropical high (WPSH) tended to stay more northward, cyclonic circulation anomaly dominated the Philippines and the East Asian summer monsoon (EASM) was stronger than normal. Dynamic climate models from Beijing Climate Centre and abroad showed similar results of the prediction for the key members of EASM system. The results of diagnostic analyses and dynamic models all indicated that the La Ni〖AKn~D〗a event and the cold tropical Indian Ocean were important precursory signals for the prediction of the climate anomaly in summer 2018, which supported less rainfall in the middle and lower reaches of the Yangtze River and more in northern part of China.
2019, 45(4):565-576.
DOI: 10.7519/j.issn.1000-0526.2019.04.011
Abstract:
During the autumn of 2018, the surface air temperature was below normal in West China but above normal in East China. And the distribution of precipitation in eastern China was “more in the north and south, less in the middle”. The precipitation was above normal in the central and eastern part of Inner Mongolia, Northeast China, the southern part of the south of the Yangtze River and South China, but below normal in the region from North China to the northern part of the south of the Yangtze River. In addition, the precipitation in the south of the Yangtze River and Southwest China showed obvious seasonal reverse distribution characteristics. By analyzing the causes for the climatic anormaly, we found that in autumn, ridge and trough activities in middle and high latitudes of Eurasia were frequent, the cold air was active, the western Pacific subtropical high (WPSH) was stronger and more westward than normal, the ridges of WPSH fluctuated greatly from north to south, and the southwest water vapor transport was stronger, resulting in the abnormal distribution of precipitation in eastern China. Further studies have shown that the sea surface temperature anomaly (SSTA) was the major extermal forcing factor for the climatic anomalies in the autumn of 2018. The El Ni〖AKn~D〗o type developed from the central Pacific type (CP) El Ni〖AKn~D〗o to the eastern Pacific type (EP) El Ni〖AKn~D〗o. The positive phase of tropical Indian Ocean dipole (TIOD) turned to the positive phase of South Indian Ocean dipole (SIOD). And there was obvious response of the East Asian subtropical atmospheric circulation to the SSTA in the Pacific and Indian Ocean in autumn. Therefore, the evolution of El Ni〖AKn~D〗o and the SST in the Indian Ocean and their influence on the East Asia atmospheric circulation, together with the seasonal adjustment of the anomalous circulation in the middle and high latitudes in Eurasia, led to the obvious eastwest interseasonal changes of precipitation in southern China.
During the autumn of 2018, the surface air temperature was below normal in West China but above normal in East China. And the distribution of precipitation in eastern China was “more in the north and south, less in the middle”. The precipitation was above normal in the central and eastern part of Inner Mongolia, Northeast China, the southern part of the south of the Yangtze River and South China, but below normal in the region from North China to the northern part of the south of the Yangtze River. In addition, the precipitation in the south of the Yangtze River and Southwest China showed obvious seasonal reverse distribution characteristics. By analyzing the causes for the climatic anormaly, we found that in autumn, ridge and trough activities in middle and high latitudes of Eurasia were frequent, the cold air was active, the western Pacific subtropical high (WPSH) was stronger and more westward than normal, the ridges of WPSH fluctuated greatly from north to south, and the southwest water vapor transport was stronger, resulting in the abnormal distribution of precipitation in eastern China. Further studies have shown that the sea surface temperature anomaly (SSTA) was the major extermal forcing factor for the climatic anomalies in the autumn of 2018. The El Ni〖AKn~D〗o type developed from the central Pacific type (CP) El Ni〖AKn~D〗o to the eastern Pacific type (EP) El Ni〖AKn~D〗o. The positive phase of tropical Indian Ocean dipole (TIOD) turned to the positive phase of South Indian Ocean dipole (SIOD). And there was obvious response of the East Asian subtropical atmospheric circulation to the SSTA in the Pacific and Indian Ocean in autumn. Therefore, the evolution of El Ni〖AKn~D〗o and the SST in the Indian Ocean and their influence on the East Asia atmospheric circulation, together with the seasonal adjustment of the anomalous circulation in the middle and high latitudes in Eurasia, led to the obvious eastwest interseasonal changes of precipitation in southern China.
2019, 45(4):577-586.
DOI: 10.7519/j.issn.1000-0526.2019.04.012
Abstract:
Operational positioning, track, intensity and landfall point forecast errors of tropical cyclones (TCs) over Western North Pacific and South China Sea in 2017 were evaluated on the base of CMA/STI’s best track dataset. The results show that the performance of TC positioning in 2017 was a little larger than in 2016, with an average error by all methods was 26.7 km. The overall track forecast accuracies within 72 h were not better than in 2015 in recent two years for both subjective and objective methods. Landfall prediction errors for the 24 h landfall point predictions of CMA were mainly less than 65 km, except for the landfall point of “Nesat” at Yilan Taiwan Province. The evaluation results could be strongly influenced by adopting different best tracks or operational realtime observed dataset from different official agencies.
Operational positioning, track, intensity and landfall point forecast errors of tropical cyclones (TCs) over Western North Pacific and South China Sea in 2017 were evaluated on the base of CMA/STI’s best track dataset. The results show that the performance of TC positioning in 2017 was a little larger than in 2016, with an average error by all methods was 26.7 km. The overall track forecast accuracies within 72 h were not better than in 2015 in recent two years for both subjective and objective methods. Landfall prediction errors for the 24 h landfall point predictions of CMA were mainly less than 65 km, except for the landfall point of “Nesat” at Yilan Taiwan Province. The evaluation results could be strongly influenced by adopting different best tracks or operational realtime observed dataset from different official agencies.
2019, 45(4):587-592.
DOI: 10.7519/j.issn.1000-0526.2019.04.013
Abstract:
The main characteristics of the general atmospheric circulation in January 2019 are as follows. There were two polar vortex centers in the Northern Hemisphere. The circulation presented a three wave pattern in middlehigh latitudes. The average south branch trough was located around 90°E. The northwestern Pacific subtropical high was stronger than normal, located more westward. Meanwhile, monthly mean precipitation over China was 14.0 mm, 4% higher than normal. And three major rainfall processes occurred in this month, and parts of the south of Yangtze River, and Southwest China saw rains obviously. Daily extreme precipitation events occurred at 35 stations. Monthly mean temperature was -4.1℃, 0.9℃ higher than normal, and there were four cold air processes in this month.Meanwhile, there were two largescale foghaze weather processes as well.
The main characteristics of the general atmospheric circulation in January 2019 are as follows. There were two polar vortex centers in the Northern Hemisphere. The circulation presented a three wave pattern in middlehigh latitudes. The average south branch trough was located around 90°E. The northwestern Pacific subtropical high was stronger than normal, located more westward. Meanwhile, monthly mean precipitation over China was 14.0 mm, 4% higher than normal. And three major rainfall processes occurred in this month, and parts of the south of Yangtze River, and Southwest China saw rains obviously. Daily extreme precipitation events occurred at 35 stations. Monthly mean temperature was -4.1℃, 0.9℃ higher than normal, and there were four cold air processes in this month.Meanwhile, there were two largescale foghaze weather processes as well.
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ISSN:1000-0526 CN:11-2282/P