ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 47,Issue 12,2021 Table of Contents
2021, 47(12):1433-1443.
DOI: 10.7519/j.issn.1000-0526.2021.12.001
Abstract:
Extreme precipitation struck Zhejiang Province induced by Typhoon Lekima in 2019. It was found that the spiral rainbelt staggering on the coast of Zhejiang Province during the daytime of 9 August, and rainfall was enhanced significantly due to inner-core convection during Lekima’s landing period over the night. Rainfall centers were significantly related to the near-shore of Tiantai Mountain, Kuocang Mountain and Yandang Mountain in Zhejiang Province. Based on analysis of GPM (Global Precipitation Measure) retrieval cloud parameters, Lekima’s spiral rainbands were dominant by mixed cumulus-stratus precipitation, while eyewall was dominated by tropical warm cloud precipitation. With larger effective diameter of raindrops and the higher density of raindrop particles, extreme rainfall intensity was formed in Lekima’s eyewall. Spiral rainbelt was enhanced due to the low-level frontogenesis and coast convergence during the landing of Lekima. Lekima’s inner-core convection was more intense on the left direction, leading to heavier rainfall on the left side of typhoon’s landing position. By comparing precipitation rate evolution between mountainous and plain areas via statistics with minute-interval automatic weather station observation, it was preliminarily proved that the topographic rainfall enhancing mechanism and the asymmetric inner-core convective structure have almost the same impact on precipitation intensity, both favoring the asymmetrical rainfall concentrating on the left side to Lekima’s forwarding direction.
Extreme precipitation struck Zhejiang Province induced by Typhoon Lekima in 2019. It was found that the spiral rainbelt staggering on the coast of Zhejiang Province during the daytime of 9 August, and rainfall was enhanced significantly due to inner-core convection during Lekima’s landing period over the night. Rainfall centers were significantly related to the near-shore of Tiantai Mountain, Kuocang Mountain and Yandang Mountain in Zhejiang Province. Based on analysis of GPM (Global Precipitation Measure) retrieval cloud parameters, Lekima’s spiral rainbands were dominant by mixed cumulus-stratus precipitation, while eyewall was dominated by tropical warm cloud precipitation. With larger effective diameter of raindrops and the higher density of raindrop particles, extreme rainfall intensity was formed in Lekima’s eyewall. Spiral rainbelt was enhanced due to the low-level frontogenesis and coast convergence during the landing of Lekima. Lekima’s inner-core convection was more intense on the left direction, leading to heavier rainfall on the left side of typhoon’s landing position. By comparing precipitation rate evolution between mountainous and plain areas via statistics with minute-interval automatic weather station observation, it was preliminarily proved that the topographic rainfall enhancing mechanism and the asymmetric inner-core convective structure have almost the same impact on precipitation intensity, both favoring the asymmetrical rainfall concentrating on the left side to Lekima’s forwarding direction.
2021, 47(12):1444-1456.
DOI: 10.7519/j.issn.1000-0526.2021.12.002
Abstract:
The evaluation results of ECMWF and GFS on the track and strength forecasts of typhoons affecting Zhejiang from 2016 to 2019 show that ECMWF is better than GFS for track forecasting, and GFS has more advantages for strength forecasting. On this basis, the paper proposes a feasible typhoon initialization scheme to improve the performance of typhoon forecasting skill. Based on ECMWF and GFS analysis fields and oceanic typhoon observation data, as well as typhoon vortex separation, the vortex field is obtained by separating the GFS analysis field, and after vortex relocation and maximum wind speed adjustment procedure, it is superimposed with the large-scale environmental field separated from the ECMWF analysis field, realizing the reconstruction of typhoon initial field. For 14 typhoons affecting Zhejiang in recent years, the hindcasting results of the mesoscale numerical weather forecast model which uses the new reconstruction scheme demonstrate that the new scheme gives full play to the ECMWF’s advantages in track forecasting and GFS’s advantages in strength forecasting, improving the forecast accuracy of typhoon track and strength effectively. The absolute error of track forecast is reduced by 21 km and the standard deviation by 26.6 km compared with the prediction of the GFS-driven mesoscale model. Compared with the forecast result of the ECMWF driven mesoscale model, the absolute error of strength forecast is reduced by 1.7 m·s-1 and the standard deviation by 2.3 m·s-1. The analysis of the typical case of Super Typhoon Lekima (2019) further indicates that the initial field reconstruction technology has a better forecasting ability for atmospheric circulation characteristics and typhoon’s warm core structure.
The evaluation results of ECMWF and GFS on the track and strength forecasts of typhoons affecting Zhejiang from 2016 to 2019 show that ECMWF is better than GFS for track forecasting, and GFS has more advantages for strength forecasting. On this basis, the paper proposes a feasible typhoon initialization scheme to improve the performance of typhoon forecasting skill. Based on ECMWF and GFS analysis fields and oceanic typhoon observation data, as well as typhoon vortex separation, the vortex field is obtained by separating the GFS analysis field, and after vortex relocation and maximum wind speed adjustment procedure, it is superimposed with the large-scale environmental field separated from the ECMWF analysis field, realizing the reconstruction of typhoon initial field. For 14 typhoons affecting Zhejiang in recent years, the hindcasting results of the mesoscale numerical weather forecast model which uses the new reconstruction scheme demonstrate that the new scheme gives full play to the ECMWF’s advantages in track forecasting and GFS’s advantages in strength forecasting, improving the forecast accuracy of typhoon track and strength effectively. The absolute error of track forecast is reduced by 21 km and the standard deviation by 26.6 km compared with the prediction of the GFS-driven mesoscale model. Compared with the forecast result of the ECMWF driven mesoscale model, the absolute error of strength forecast is reduced by 1.7 m·s-1 and the standard deviation by 2.3 m·s-1. The analysis of the typical case of Super Typhoon Lekima (2019) further indicates that the initial field reconstruction technology has a better forecasting ability for atmospheric circulation characteristics and typhoon’s warm core structure.
2021, 47(12):1457-1468.
DOI: 10.7519/j.issn.1000-0526.2021.12.003
Abstract:
In this study, the key area of upwind southwest wind speed is established, which is closely associated with spring persistent rains in Hunan (SPRH). The monitoring indicators of SPRH from 1980 to 2014 are defined. The temporal and spatial patterns of SPRH rainfall are analyzed. Besides, the anomaly of the atmospheric circulations during the strong/weak SPRH period and sea surface temperature (SST) during the early period are discussed. Results show that the climate average of SPRH occurs from the 13th pentad to the 27th pentad, whereas the starting date and ending date of SPRH vary in different years. The rainfall of SPRH exceeded normal conditions during the periods before the mid-1980s and after 2014, but it was lower than normal conditions during the periods of the mid-1980s to 2013. The rainfall of SPRH decreased from south to north and from east to west in spatial distribution. The spatial pattern of more (less) precipitation in the whole province can show the main spatial distribution of SPRH. In the strong SPRH years in whole province, the Western Pacific subtropical high (WPSH) remarkably becomes stronger and westward, the Indo-Burmese trough tends to become weaker, and an anomalous anticyclone exists in the southern Yangtze River regions in low-level wind field. Hunan is located in the center of anomalous anticyclone, causing heavy SPRH. However, in the weak SPRH years, WPSH evidently becomes weaker, the Indo-Burmese trough tends to become stronger, and an anomalous anticyclone is found in southern China. Additionally, Hunan is located in the center of anomalous water vapor divergence, resulting in weaker SPRH in whole province. In the following year of the occurrence of El Ni〖AKn~D〗o events, SPRH starts earlier, persists longer and has more intensive rainfall amount compared with the normal years. On the contrary, during the following year of the occurrence of La Ni〖AKn~D〗a, SPRH starts later, has short rainy periods, lower rainfall amount and weaker rainfall intensity compared with the normal years.
In this study, the key area of upwind southwest wind speed is established, which is closely associated with spring persistent rains in Hunan (SPRH). The monitoring indicators of SPRH from 1980 to 2014 are defined. The temporal and spatial patterns of SPRH rainfall are analyzed. Besides, the anomaly of the atmospheric circulations during the strong/weak SPRH period and sea surface temperature (SST) during the early period are discussed. Results show that the climate average of SPRH occurs from the 13th pentad to the 27th pentad, whereas the starting date and ending date of SPRH vary in different years. The rainfall of SPRH exceeded normal conditions during the periods before the mid-1980s and after 2014, but it was lower than normal conditions during the periods of the mid-1980s to 2013. The rainfall of SPRH decreased from south to north and from east to west in spatial distribution. The spatial pattern of more (less) precipitation in the whole province can show the main spatial distribution of SPRH. In the strong SPRH years in whole province, the Western Pacific subtropical high (WPSH) remarkably becomes stronger and westward, the Indo-Burmese trough tends to become weaker, and an anomalous anticyclone exists in the southern Yangtze River regions in low-level wind field. Hunan is located in the center of anomalous anticyclone, causing heavy SPRH. However, in the weak SPRH years, WPSH evidently becomes weaker, the Indo-Burmese trough tends to become stronger, and an anomalous anticyclone is found in southern China. Additionally, Hunan is located in the center of anomalous water vapor divergence, resulting in weaker SPRH in whole province. In the following year of the occurrence of El Ni〖AKn~D〗o events, SPRH starts earlier, persists longer and has more intensive rainfall amount compared with the normal years. On the contrary, during the following year of the occurrence of La Ni〖AKn~D〗a, SPRH starts later, has short rainy periods, lower rainfall amount and weaker rainfall intensity compared with the normal years.
WANG Hong
,
WANG Xiuming
,
JIANG Yunyan
,
GAO Yanchun
,
YANG Jie
,
YOU Guojun
,
FENG Yubo
,
HU Qilu
,
LI Zhaoqi
,
ZHANG Yujie
2021, 47(12):1469-1483.
DOI: 10.7519/j.issn.1000-0526.2021.12.004
Abstract:
146 short-time severe precipitation cases in summer (JJA) were selected to analyze the distribution characteristics of short-time severe precipitation in Chengde from 2008 to 2017 based on the multiple data of automatic weather station, meteorological satellite, Doppler radar and NCEP reanalysis. The results show that the synoptic circulation patterns controlling severe precipitation in the Chengde Montains can be divided into the cold vortex type (45%), westerly trough type (34%) and edge of the western Pacific subtropical high (WPSH) type (21%). The short-time severe rainfall in June mostly occurs under the background of cold vortex circulations, with scattered rain falling areas. The dominant circulation pattern in the early-mid July is the westerly trough type but turns to be the edge of WPSH type after the late July. The severe precipitation under both the westerly trough type and the edge of WPSH type are generally distributed on the windward slope of Yanshan Mountain in the southern edge of Chengde. Differing from the traditional rainy season in North China, which is influenced by the position of subtropical high, the concentrated period of the short-term severe precipitation in Chengde is from late June to late July, and the peak appears when the cold vortex and the westerly trough circulations take action together. Mesoscale convective systems which are responsible for short-time severe precipitation move in Chengde mainly through southwest (northeastern Beijing) and northwest (Inner Mongolia) channels. In addition, a considerable number of convective storms are born locally in Chengde. The short-time severe precipitation in Chengde are often along with less water vapor and poor transportation compared with that in conventional rainy season. The water vapor content of cold vortex type is only 8 g·kg-1 at 850 hPa. The median of the area averaged atmospheric precipitable water (PW) is 33 mm in the Chengde Mountains and is only 29 mm under the cold vortex circulation. Even if the median of PW under the edge of WPSH type gets to 38 mm, it is still 15 mm lower than that in the south plain areas. The short-time severe precipitation often occurrs in extremely unstable stratification. The medians of temperature difference between 850 hPa and 500 hPa of cold vortex type and the westerly trough type are 28.6℃ and 27.9℃ respectively, while the others are below 25℃ in most of areas (including mountainous areas) of China.
146 short-time severe precipitation cases in summer (JJA) were selected to analyze the distribution characteristics of short-time severe precipitation in Chengde from 2008 to 2017 based on the multiple data of automatic weather station, meteorological satellite, Doppler radar and NCEP reanalysis. The results show that the synoptic circulation patterns controlling severe precipitation in the Chengde Montains can be divided into the cold vortex type (45%), westerly trough type (34%) and edge of the western Pacific subtropical high (WPSH) type (21%). The short-time severe rainfall in June mostly occurs under the background of cold vortex circulations, with scattered rain falling areas. The dominant circulation pattern in the early-mid July is the westerly trough type but turns to be the edge of WPSH type after the late July. The severe precipitation under both the westerly trough type and the edge of WPSH type are generally distributed on the windward slope of Yanshan Mountain in the southern edge of Chengde. Differing from the traditional rainy season in North China, which is influenced by the position of subtropical high, the concentrated period of the short-term severe precipitation in Chengde is from late June to late July, and the peak appears when the cold vortex and the westerly trough circulations take action together. Mesoscale convective systems which are responsible for short-time severe precipitation move in Chengde mainly through southwest (northeastern Beijing) and northwest (Inner Mongolia) channels. In addition, a considerable number of convective storms are born locally in Chengde. The short-time severe precipitation in Chengde are often along with less water vapor and poor transportation compared with that in conventional rainy season. The water vapor content of cold vortex type is only 8 g·kg-1 at 850 hPa. The median of the area averaged atmospheric precipitable water (PW) is 33 mm in the Chengde Mountains and is only 29 mm under the cold vortex circulation. Even if the median of PW under the edge of WPSH type gets to 38 mm, it is still 15 mm lower than that in the south plain areas. The short-time severe precipitation often occurrs in extremely unstable stratification. The medians of temperature difference between 850 hPa and 500 hPa of cold vortex type and the westerly trough type are 28.6℃ and 27.9℃ respectively, while the others are below 25℃ in most of areas (including mountainous areas) of China.
2021, 47(12):1484-1500.
DOI: 10.7519/j.issn.1000-0526.2021.12.005
Abstract:
The urban hydrological model is introduced into the urban flash flood forecasts and warning operation. The data of land use and land cover types and gridded urban drainage network capacity are parameterized in the model. Forced by the radar rainfall estimates, the model simulates the urban surface hydrological response and hydraulic processes. The hydraulic model is based on the shallow water equation, and the alternating-direction-implicit is used to solve the differential equation by two steps in the x direction and y direction, respectively. This solution comprises the back water effects in simulation and indirectly emulates the multiple flow direction methods, recalling the surface water dispersion in turbulence or diffusional effects. The case study demonstrates the online and offline running of the urban hydrological model for the purpose of flash flood warning, partially for the model validation. The online hydrological model takes the case study on the 21 July 2012 thunderstorm in Beijing, in which the radar quantitative-rainfall estimates are forced on the model for reproducing the gridded inundation mappings. The model simulation results resemble the flash flood scenarios of the waterloggings and water inundations on the 21 July 2012 thunderstorm day. The offline model simulation addresses measuring the rainfall intensity threshold for the ranked risks of the storm producing flash floods, especially the rainfall intensity thresholds for floods-susceptible places (FSPs). Therefore, the hydrological model simulation deduces the 1 h, 3 h and 6 h cumulative rainfall thresholds inducing water inundation depths over 0.2 m, 0.5 m, 0.8 m and 1.2 m in more than 49 FSPs, which are the rainfall intensity thresholds of the flash flood warning in the blue, yellow, orange and red signals, respectively.
The urban hydrological model is introduced into the urban flash flood forecasts and warning operation. The data of land use and land cover types and gridded urban drainage network capacity are parameterized in the model. Forced by the radar rainfall estimates, the model simulates the urban surface hydrological response and hydraulic processes. The hydraulic model is based on the shallow water equation, and the alternating-direction-implicit is used to solve the differential equation by two steps in the x direction and y direction, respectively. This solution comprises the back water effects in simulation and indirectly emulates the multiple flow direction methods, recalling the surface water dispersion in turbulence or diffusional effects. The case study demonstrates the online and offline running of the urban hydrological model for the purpose of flash flood warning, partially for the model validation. The online hydrological model takes the case study on the 21 July 2012 thunderstorm in Beijing, in which the radar quantitative-rainfall estimates are forced on the model for reproducing the gridded inundation mappings. The model simulation results resemble the flash flood scenarios of the waterloggings and water inundations on the 21 July 2012 thunderstorm day. The offline model simulation addresses measuring the rainfall intensity threshold for the ranked risks of the storm producing flash floods, especially the rainfall intensity thresholds for floods-susceptible places (FSPs). Therefore, the hydrological model simulation deduces the 1 h, 3 h and 6 h cumulative rainfall thresholds inducing water inundation depths over 0.2 m, 0.5 m, 0.8 m and 1.2 m in more than 49 FSPs, which are the rainfall intensity thresholds of the flash flood warning in the blue, yellow, orange and red signals, respectively.
2021, 47(12):1501-1511.
DOI: 10.7519/j.issn.1000-0526.2021.12.006
Abstract:
On the basis of a quality controlled hourly rainfall dataset from 901 automatic weather stations (AWS) in 2013-2019, the fine-scale characteristics of summer rainstorm in Xinjiang are analyzed. The results show that the rainstorm days in northern Xinjiang are more than in southern Xinjiang, and the rainstorm days in mountain areas are more than in plains. In addition to the middle section of the Tianshan Mountains, parts of the northern slope of Kunlun Mountains in the southeastern part of southern Xinjiang also have rains frequently. In July (August), rainstorm days in Xinjiang are the most (fewest), and the proportion of short-time severe precipitation is the highest (lowest). In July, local convective rainstorm is the major event while in August regional systematic rainstorm is dominant. In Xinjiang, 75.3% of the stations had short-time severe precipitation during the heavy rain periods. The short-time severe precipitation events occurred frequently in the regions where the annual average number of heavy rain days was less than one day, but the regions with more heavy rain days were not hit by short-time severe precipitation very often. The proportion of short-time severe precipitation events in heavy rainfall periods in Xinjiang increases with the decrease of altitude, exceeding 85% stations below 500 m. The “daytime rain” characteristics of heavy rain in Bortala, Karamay, northern Tacheng and western Altay of northern Xinjiang are noticeable. The average rainfall time of the above-mentioned regional rainstorm days is short, and the occurrence percentage of short-time heavy rainfall events is high. The peaks of the regional average accumulated precipitation, frequency and average intensity of convective rainstorm often appear from afternoon to early evening. The average rainfall hours of rainstorm days in the Ili River Valley and the northern slope of Tianshan are more, but the short-time severe precipitation is at a low proportion. The peaks of accumulated precipitation and frequency often occur from night to morning, while the peak value of the average precipitation intensity appears from evening to the first half of the night, dominated by the systematic rainstorm. The diurnal variation of rainstorm in southern Xinjiang is more complicated than that in northern Xinjiang.
On the basis of a quality controlled hourly rainfall dataset from 901 automatic weather stations (AWS) in 2013-2019, the fine-scale characteristics of summer rainstorm in Xinjiang are analyzed. The results show that the rainstorm days in northern Xinjiang are more than in southern Xinjiang, and the rainstorm days in mountain areas are more than in plains. In addition to the middle section of the Tianshan Mountains, parts of the northern slope of Kunlun Mountains in the southeastern part of southern Xinjiang also have rains frequently. In July (August), rainstorm days in Xinjiang are the most (fewest), and the proportion of short-time severe precipitation is the highest (lowest). In July, local convective rainstorm is the major event while in August regional systematic rainstorm is dominant. In Xinjiang, 75.3% of the stations had short-time severe precipitation during the heavy rain periods. The short-time severe precipitation events occurred frequently in the regions where the annual average number of heavy rain days was less than one day, but the regions with more heavy rain days were not hit by short-time severe precipitation very often. The proportion of short-time severe precipitation events in heavy rainfall periods in Xinjiang increases with the decrease of altitude, exceeding 85% stations below 500 m. The “daytime rain” characteristics of heavy rain in Bortala, Karamay, northern Tacheng and western Altay of northern Xinjiang are noticeable. The average rainfall time of the above-mentioned regional rainstorm days is short, and the occurrence percentage of short-time heavy rainfall events is high. The peaks of the regional average accumulated precipitation, frequency and average intensity of convective rainstorm often appear from afternoon to early evening. The average rainfall hours of rainstorm days in the Ili River Valley and the northern slope of Tianshan are more, but the short-time severe precipitation is at a low proportion. The peaks of accumulated precipitation and frequency often occur from night to morning, while the peak value of the average precipitation intensity appears from evening to the first half of the night, dominated by the systematic rainstorm. The diurnal variation of rainstorm in southern Xinjiang is more complicated than that in northern Xinjiang.
2021, 47(12):1512-1524.
DOI: 10.7519/j.issn.1000-0526.2021.12.007
Abstract:
In order to further discuss the application effect of a new type of “up-drift-down” sounding data to data assimilation and numerical prediction, assimilation comparisons were carried out based on the WRF (Weather Research and Forecast) model and WRFDA (WRF data assimilation) system. In this paper, based on the quality evaluation and sparseness of the new radiosonde data, the descending data are combined and assimilated with the conventional observation data. The influence and causes of the simulated data on the rainstorm forecast quality in the middle and lower reaches of the Yangtze River are discussed. The main test results include that the accuracy of the latest test data is verified by cross-comparison of the test data with the FNL data and sounding data from the same station. The scheme of combining the characteristic layers with the specific layers can be used to sparse the ascending and descending segments of the new radiosonde, which can get better results. The rainstorm forecasting technique can be improved to some extent by assimilating the data in the descending section. The adjustment of wind field and humidity field is one of the important reasons for the improvement of rainstorm forecasting skills.
In order to further discuss the application effect of a new type of “up-drift-down” sounding data to data assimilation and numerical prediction, assimilation comparisons were carried out based on the WRF (Weather Research and Forecast) model and WRFDA (WRF data assimilation) system. In this paper, based on the quality evaluation and sparseness of the new radiosonde data, the descending data are combined and assimilated with the conventional observation data. The influence and causes of the simulated data on the rainstorm forecast quality in the middle and lower reaches of the Yangtze River are discussed. The main test results include that the accuracy of the latest test data is verified by cross-comparison of the test data with the FNL data and sounding data from the same station. The scheme of combining the characteristic layers with the specific layers can be used to sparse the ascending and descending segments of the new radiosonde, which can get better results. The rainstorm forecasting technique can be improved to some extent by assimilating the data in the descending section. The adjustment of wind field and humidity field is one of the important reasons for the improvement of rainstorm forecasting skills.
2021, 47(12):1525-1536.
DOI: 10.7519/j.issn.1000-0526.2021.12.008
Abstract:
Based on the GF-1 satellite images effectively observed in 2018 and 2019 and the chlorophyll-a concentration data in-situ observed on the lake surface, a random forest machine learning algorithm is used to quantitatively evaluate the importance measures and contribution rate of the band reflectance and select effective feature band combinations. Then a remote sensing inversion model of chlorophyll-a concentration in Taihu Lake based on in-situ automatic monitoring data is established in this paper. The results show that the green light band (0.52-0.59 μm) and the red light band (0.63-0.69 μm) are the key bands, which can be combined with other bands to estimate chlorophyll-a concentration. It is better to construct the estimation model of chlorophyll-a concentration in Taihu Lake by seasons, and the determination coefficients R2 of the spring, summer, autumn, and winter models are 0.84, 0.85, 0.96, and 0.82, respectively. The concentration of chlorophyll-a in Taihu Lake is highest in summer, followed by autumn and spring, and lowest in winter. The spatial changes of chlorophyll-a concentration in spring, autumn and summer are more obvious, while that in winter is not obvious. The areas with high chlorophyll-a concentration are mainly concentrated in the western coastal area, Zhushan Lake, Meiliang Lake and some lake core areas. Studies have shown that the random forest model can objectively determine the effective bands for chlorophyll-a concentration inversion, and achieve high-precision estimation of chlorophyll-a concentration in large inland water bodies.
Based on the GF-1 satellite images effectively observed in 2018 and 2019 and the chlorophyll-a concentration data in-situ observed on the lake surface, a random forest machine learning algorithm is used to quantitatively evaluate the importance measures and contribution rate of the band reflectance and select effective feature band combinations. Then a remote sensing inversion model of chlorophyll-a concentration in Taihu Lake based on in-situ automatic monitoring data is established in this paper. The results show that the green light band (0.52-0.59 μm) and the red light band (0.63-0.69 μm) are the key bands, which can be combined with other bands to estimate chlorophyll-a concentration. It is better to construct the estimation model of chlorophyll-a concentration in Taihu Lake by seasons, and the determination coefficients R2 of the spring, summer, autumn, and winter models are 0.84, 0.85, 0.96, and 0.82, respectively. The concentration of chlorophyll-a in Taihu Lake is highest in summer, followed by autumn and spring, and lowest in winter. The spatial changes of chlorophyll-a concentration in spring, autumn and summer are more obvious, while that in winter is not obvious. The areas with high chlorophyll-a concentration are mainly concentrated in the western coastal area, Zhushan Lake, Meiliang Lake and some lake core areas. Studies have shown that the random forest model can objectively determine the effective bands for chlorophyll-a concentration inversion, and achieve high-precision estimation of chlorophyll-a concentration in large inland water bodies.
2021, 47(12):1537-1545.
DOI: 10.7519/j.issn.1000-0526.2021.12.009
Abstract:
Based on land use/cover change dataset at a resolution of 30 m×30 m, the characteristics of chilling dew wind in 2020 are analyzed for double-season late rice by using the information of underlying surface, gridded monitoring degree and chilling dew wind index. It is shown that the chilling dew wind in 2020 is characterized by earlier start date, longer duration and general low-to-heavy degree occurrence across double-season rice area. There is 24.7% of late rice area exposed to chilling dew wind, which is the third largest since 2000. The area percentages of low, medium and heavy chilling dew winds are 9.7%, 12.8% and 4.9%, respectively. In terms of the statistic in provinces, it is obvious that the area percentage of late rice area affected by chilling dew wind is more than 90% in Hunan, Jiangxi and Zhejiang, but is less than 30% in other provinces. The area percentage subjected to chilling dew wind in Hunan, Hubei, Anhui and Jiangsu is the largest since 2020, and Jiangxi has the largest area percentage of heavy chilling dew wind since 2000. The light degree of chilling dew wind occurs in 〖JP2〗Zhejiang, Fujian and Guangxi, and the occurrence area of chilling dew wind in Guangdong is small. The integrated index for chilling dew wind in double-season late rice area is 4.21 in 2020, which is the second largest since 2000. Moreover, the indexes in Hunan, Jiangxi and Hubei reach 7.16, 7.16 and 12.59, which is the second largest, the largest and the largest since 2000, respectively.
Based on land use/cover change dataset at a resolution of 30 m×30 m, the characteristics of chilling dew wind in 2020 are analyzed for double-season late rice by using the information of underlying surface, gridded monitoring degree and chilling dew wind index. It is shown that the chilling dew wind in 2020 is characterized by earlier start date, longer duration and general low-to-heavy degree occurrence across double-season rice area. There is 24.7% of late rice area exposed to chilling dew wind, which is the third largest since 2000. The area percentages of low, medium and heavy chilling dew winds are 9.7%, 12.8% and 4.9%, respectively. In terms of the statistic in provinces, it is obvious that the area percentage of late rice area affected by chilling dew wind is more than 90% in Hunan, Jiangxi and Zhejiang, but is less than 30% in other provinces. The area percentage subjected to chilling dew wind in Hunan, Hubei, Anhui and Jiangsu is the largest since 2020, and Jiangxi has the largest area percentage of heavy chilling dew wind since 2000. The light degree of chilling dew wind occurs in 〖JP2〗Zhejiang, Fujian and Guangxi, and the occurrence area of chilling dew wind in Guangdong is small. The integrated index for chilling dew wind in double-season late rice area is 4.21 in 2020, which is the second largest since 2000. Moreover, the indexes in Hunan, Jiangxi and Hubei reach 7.16, 7.16 and 12.59, which is the second largest, the largest and the largest since 2000, respectively.
2021, 47(12):1546-1554.
DOI: 10.7519/j.issn.1000-0526.2021.12.010
Abstract:
The observed yields of winter wheat from 123 agrometeorological observation stations and the announced yield of winter wheat at county level， where the observation station is located， are used to integrate the observed yield and announced yield at provincial and national levels by the proportion of winter wheat planting area. And the observed yield and announced yield sequences of winter wheat are compared at provincial and national levels. The observed and announced yields of winter wheat at national level are predicted based on the climate suitability index forecast method. Also, the forecast accuracy of different yield sequences is analyzed. The results show that the observed yields are higher than the announced yields at provincial level in all provinces. The correlation coefficient between the observed and announced yields is good in each province and has passed the significant test except in Xinjiang. The correlation coefficient between the observed yield and announced yield at national level reaches 0.97, and the observed yield could reflect the characteristic of announced yield. Besides, the percent of consistency statistics of trend meteorological yield of observed and announced yields remains good at national level, so it is suitable to carry out yield prediction, but it is unsuitable to carry out yield prediction at province level due to the low percent. The accuracy of different yield sequences in forecasting their own sequences is high and the accuracy of announced yield is higher than the observed yield. However, the accuracy of the forecast conversion of the announced yield by using the observed yield would be reduced. Conclusively, it is feasible to carry out yield forecast at national level based on the observed yield series because of the realtime, objectivity and representative of the observed yield. At the same time, the new yield series could provide new data support for yield prediction.
The observed yields of winter wheat from 123 agrometeorological observation stations and the announced yield of winter wheat at county level， where the observation station is located， are used to integrate the observed yield and announced yield at provincial and national levels by the proportion of winter wheat planting area. And the observed yield and announced yield sequences of winter wheat are compared at provincial and national levels. The observed and announced yields of winter wheat at national level are predicted based on the climate suitability index forecast method. Also, the forecast accuracy of different yield sequences is analyzed. The results show that the observed yields are higher than the announced yields at provincial level in all provinces. The correlation coefficient between the observed and announced yields is good in each province and has passed the significant test except in Xinjiang. The correlation coefficient between the observed yield and announced yield at national level reaches 0.97, and the observed yield could reflect the characteristic of announced yield. Besides, the percent of consistency statistics of trend meteorological yield of observed and announced yields remains good at national level, so it is suitable to carry out yield prediction, but it is unsuitable to carry out yield prediction at province level due to the low percent. The accuracy of different yield sequences in forecasting their own sequences is high and the accuracy of announced yield is higher than the observed yield. However, the accuracy of the forecast conversion of the announced yield by using the observed yield would be reduced. Conclusively, it is feasible to carry out yield forecast at national level based on the observed yield series because of the realtime, objectivity and representative of the observed yield. At the same time, the new yield series could provide new data support for yield prediction.
2021, 47(12):1555-1560.
DOI: 10.7519/j.issn.1000-0526.2021.12.011
Abstract:
The main characteristics of the general atmospheric circulation in September 2021 are as follows. The polar vortex showed a singlepole pattern. The circulation presented a threewave pattern in middlehigh latitudes. The northwestern Pacific subtropical high extended remarkably more westward than normal. The monthly mean precipitation amount was 83.8 mm, which is 28.5% more than normal (65.2 mm). The monthly mean temperature was 18.2℃, 1.6℃ higher than normal. Four largerange heavy precipitation processes occurred over China, of which Southwest China, North China and Northeast China were caught by severe precipitation, and some local areas suffered from serious disasters. Four typhoons were generated over northwestern Pacific Ocean and the South China Sea, but none landed on China. The east of Southwest China, the east of Northwest China to North China, the Huanghuai Region and other places suffered from torrential rain and flood disasters. Autumn rain in West China came earlier than normal and were stronger. The meteorological droughtin Northwest China eased but continued in South China.〖JP〗 Periodic high temperatures occurred in the south of China with some areas experiencing drought.
The main characteristics of the general atmospheric circulation in September 2021 are as follows. The polar vortex showed a singlepole pattern. The circulation presented a threewave pattern in middlehigh latitudes. The northwestern Pacific subtropical high extended remarkably more westward than normal. The monthly mean precipitation amount was 83.8 mm, which is 28.5% more than normal (65.2 mm). The monthly mean temperature was 18.2℃, 1.6℃ higher than normal. Four largerange heavy precipitation processes occurred over China, of which Southwest China, North China and Northeast China were caught by severe precipitation, and some local areas suffered from serious disasters. Four typhoons were generated over northwestern Pacific Ocean and the South China Sea, but none landed on China. The east of Southwest China, the east of Northwest China to North China, the Huanghuai Region and other places suffered from torrential rain and flood disasters. Autumn rain in West China came earlier than normal and were stronger. The meteorological droughtin Northwest China eased but continued in South China.〖JP〗 Periodic high temperatures occurred in the south of China with some areas experiencing drought.
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ISSN:1000-0526 CN:11-2282/P