Vol.31, NO.1, 2020

Display Method:
Advances of Surface Wind Speed Changes over China Under Global Warming
Ding Yihui, Li Xiao, Li Qiaoping
2020, 31(1): 1-12. DOI: 10.11898/1001-7313.20200101
Previous studies indicate that surface wind speed (SWS) over China is declining continuously during past decades under global warming, and this has significant impact on wind energy resources. Based on a series of researches, spatial and temporal characteristics of SWS and its main causes are discussed. Overall, the SWS over China significantly weakens during the past fifty years. The average decreasing rate is 0.1-0.22 m·s-1 per 10 years, but there are obvious differences in season, region and wind speed. The largest decreasing rate occurs in spring and winter while the smallest occurs in summer. Wind speed of north and east coast areas dropped more sharply than southwest. Furthermore, top percentiles of wind speed dropped more sharply than the bottom percentiles. The change of large-scale pressure gradient force (PGF) is a direct cause of the decrease of SWS, and climate warming exacerbates the weakening of PGF. This is mainly due to increases of surface temperature in the middle and high latitudes of Eurasia continent, which is more significant than that in low latitudes and the western Pacific. In particular, the weakening Siberian high (SH) caused by warming reduces the PGF between land and the adjacent ocean, which is the main factor leading to the weakening of the East Asian winter monsoon (EAWM). For the deficit of East Asian summer monsoon (EASM), phase transition of the Pacific decadal oscillation (PDO) and the Atlantic multi-decadal oscillation (AMO) from cold/warm to the opposite is the main cause, and surface cooling of East China Plain caused by the aerosol radiation effect may also play an important role. Besides, some researches indicate that aerosols can reduce the EAWM through thermodynamic process. Thus, the variability of East Asia Monsoon is the result of synergistic effects of climate factors at different spatial and time scales. Controlled experiments show that the SWS of China will decline more sharply as the greenhouse gases (GHG) emission increases. The weakened SWS influences wind energy development significantly, low speed wind technology boomed, and more wind farms will be developed in low latitudes as regions with abundance wind resources in North China experienced severe SWS deficit. To assess risks precisely, confidence probability of long-term electricity production should be considered during the decision making process of the investment of wind farms.
Refractive Index Quality Control and Comparative Analysis of Multi-source Occultation Based on Sounding Observation
Guo Qiyun, Yang Rongkang, Cheng Kaiqi, Li Changxing
2020, 31(1): 13-26. DOI: 10.11898/1001-7313.20200102
Three occultation refractive index data of COSMIC, Metop-A and FY-3C from 1 September 2017 to 31 August 2018 are divided into four climate zones according to climate characteristics, so that the dataset is more consistent with the normal distribution. Occultation refractive index data and the deviation from the sounding are statistically analyzed. According to statistical results, the occultation refractive index data are quality controlled. Results show that the double-weighted mean and the double-weight standard deviation of three occultations refractive index are relatively close, and the overall trends are gradually decreasing with height. There are differences between the double-weighted mean and the double-weighted standard deviation in four climate zones. The subtropical monsoon climate zone is rich in water vapor in the lower troposphere, so its double weight mean and standard deviation are larger than those in other three climate zones. In the statistical calculation of the deviation from the sounding, the COSMIC is negative below 5 km, the subtropical monsoon climate zone has large deviation. The deviation of FY-3C in subtropical monsoon climate zone is positive below 2 km, negative between 2-6 km, positive again above 6 km, and the overall deviation is within 2 N. According to different statistical characteristics of deviations in four climate zones, different quality control standards are formulated, and error data and suspicious data are screened out. The threshold value of the correlation coefficient between the occultation and the sounding refractive index determined by statistical calculation is 0.44, and suspiciousness smaller than 0.44 is taken as wrong data. Below 1 km, the proportion of error data in quality control of occultation itself is 5%-10%. Above 1 km, within 5%, three occultations are relatively close. After importing the sounding observation reference, quality control data of Metop-A occultation in the plateau mountain climate area are increasing, while the others are about 6%. Comparing the correlation coefficient between occultations and the sounding before and after quality control, the value is smaller before the quality control. After error data being eliminated, the correlation between the occultations and the sounding refractive index is improved, mostly above 0.9. The control is effective, and the quality of the occultation data is improved.
Application of a Bias Correction Method to Meteorological Forecast for the Pyeongchang Winter Olympic Games
Zhang Yutao, Tong Hua, Sun Jian
2020, 31(1): 27-41. DOI: 10.11898/1001-7313.20200103
The 23rd Winter Olympics Games and the 13th Winter Paralympic Games are held in Pyeongchang, South Korea during 9-25 February 2018 and 8-18 March 2018. Supported by the WMO(World Meteorological Organization) WWRP(World Weather Research Project Group), ICE-POP 2018(International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games) is organized by KMA (Korea Meteorological Administration), which aims to improve the forecasting ability of convective scale numerical models for high-impact weather system under complex terrain and to support weather forecasting and meteorological services during the Winter Olympics through international cooperation. GRAPES_3 km, a high-resolution model independently developed by CMA (China Meteorological Administration), participated in this project and provided real-time forecasting products at the specific sites during the Winter Olympics Games. In order to improve the forecasting ability of GRAPES_3 km, a bias correction method named one-order adaptive Kalman filtering is applied, which compensate for the fact that the resolution of GRAPES_3 km is not sufficient to simulate the complex terrain of the Winter Olympic Games and GRAPES_3 km doesn't assimilate Korea's observations due to some objective reasons such as data transmission. 1-24-hour calibration products are provided twice a day, including 2 m temperature, 2 m relative humidity, 10 m wind speed, and 10 m wind direction on sixteen sites. The verification and evaluation are carried out in two aspects. First, it is to check whether the bias correction improves the accuracy of GRAPES_3 km, examined from the model's diurnal cycle, daily variation and the forecast ability of complex terrain. Second, to the performance of calibrated GRAPES_3 km during the Winter Olympic Games is and examined compared to LDAPS model from KMA and NU-WRF from NASA, which shows that the high-resolution GRAPES_3 km model has abilities to simulate the near-ground elements in this service and the bias correction technology makes model products better and effective. After bias correction, the root mean square error of model products is reduced to about 2℃ for the temperature, about 2 m·s-1 for the wind speed, and less than 20% for the relative humidity is reduced to. Compared with, NU-WRF and LDAPS models, the corrected GRAPES_3 km has the best wind speed forecast capability and root mean square error of the wind speed is significantly reduced. For the wind direction forecast of complex terrain, although all numerical models have limited capabilities, and their wind direction forecasting of all the stations are almost dominated by westerly during the Winter Games, the corrected GRAPES_3 km perform relatively well in some non-westerly dominated stations. However, GRAPES_3 km has no significant advantage in temperature and humidity compared with the other two models although they are improved more obviously than wind after the calibration. In addition, the bias correction can attenuate the diurnal variation characteristics of GRPAES_3 km, and to some extent, improve the simulation capability for complex terrain. In short, the application of the bias correction in the Pyeongchang Winter Olympic Games is an effective way for GRAPES_3 km.
Occurrence Characteristics of Early Rice Heat Disaster in Jiangxi Province
Yang Jianying, Huo Zhiguo, Wang Peijuan, Wu Dingrong
2020, 31(1): 42-51. DOI: 10.11898/1001-7313.20200104
Increasing of extreme hot weather has been witnessed in China in the past several decades. Rice is generally considered to be seriously threatened by hot weather, especial frequent occurrences of extreme hot weather. Though the rice heat disaster is widely studied, researches on temporal characteristics of early rice heat are lacking. It is of great merit to explore the rice heat-lead characteristics of hot weather processes, and highlight the particular period severely hit by rice heat to provide support for rice heat monitoring, prevention, and mitigation. Therefore, maximum temperature, disaster and phenological data on rice in Jiangxi are integrated to construct the historical early rice heat samples from 1981 to 2016. Nine sets of rice heat samples are built in the context of combinations of different hot weather duration (3-5 d, 6-8 d and more than 8 d) and heat levels (light, moderate and severe). Afterwards, Kolmogorov-Smirnov (K-S) and information diffusion method are adopted to analyze starting and ending dates of rice heat and their orders comparing with heading, and to explore rice heat occurring possibility and characteristics of rice heat in different level. Results show that the occurrence time of heat disaster is approximately 6 d before heading stage to 20 d after heading stage. It is with great possibility of 36.73% for heat disaster to start in 1-5 d after heading and 18.37% in -4 d-0 before heading and 6-10 d after heading. Effects of high temperature on early rice gradually decrease as the mature stage starts, with 5.61% rice heat occurring in 15 d after rice heading. The probability of moderate and light heat damage is more than 80% when 3-5 d of hot weather occurs and increases to 98.77% when more than 5 d of hot weather occurs during heading-flowering stage. It is identified that light rice heat mainly occurs in 3-17 d after heading, moderate rice heat occurs in 2-12 d after heading and severe rice heat occurs 2 d before heading and 9 d after heading. Converting to early rice phenological data, the above is concluded that major occurrence periods for light rice heat is from heading to mid-grouting stage, moderate rice heat in stage of heading to early-mid grouting and severe rice heat from booting to early grouting stage.
Remote Sensing Inversion of Leaf and Canopy Water Content in Different Growth Stages of Summer Maize
Liu Erhua, Zhou Guangsheng, Zhou Li, Zhang Feng
2020, 31(1): 52-62. DOI: 10.11898/1001-7313.20200105
Hyperspectral remote sensing technology is an important method for crop water monitoring, aiming to understand crop growth status. In order to achieve rapid, refined and comprehensive monitoring for the leaf and canopy water content of summer maize in different growth stages, controlled experiments are implemented during different growth stages of the summer maize with different irrigation water drought simulation test in North China. The water content of vegetation index (WI), water stress index (MSI), global vegetation moisture index (GVMI), compound ratio index (WNV and WCG) and reflectance curve area (Darea) of summer maize are defined for inversion models of equivalent water thickness for canopy (EWTC) and fuel moisture content for leaf (FMC). The hyperspectral remote sensing inversion models of moisture content of summer maize in 2014 are verified by using drought simulation data of different irrigation water amount during different growth periods in 2015. Results show that WI, MSI, GVMI, WNV, WCG and Darea for inversion EWTC of summer maize at the three-leaf stage doesn't pass the significance test of 0.05 level, but all the indices estimation EWTC models after the three-leaf stage pass the significance test of 0.01 level. The model accuracy for different stages from high to low are as follows: Tasseling stage, knotting stage, filling stage, mature stage, and seven-leaf stage. FMC at the seven-leaf stage and jointing stage is retrieved by 6 special indicators and all of them pass the significance test of 0.01 level. FMC at the three-leaf stage is retrieved by WNV index, but 6 spectral indicators after jointing stage cannot retrieve FMC of summer maize. In summary, the difference of precision of the same spectral indicator to retrieve the water content of summer maize is obvious in different growth stages. The retrieved water content precision is higher for middle summer maize growth period, but relatively lower for early and late remote sensing. Although canopy and leaf scale water content indices can reflect the drought situation of summer maize, considering the precision of spectral indicator retrieval of two scale water content indices of summer maize is closely related to the growth period of summer maize, a retrieval model of water content is proposed for different growth stages of summer maize to provide accurate simulation of water content in summer maiz growth.
Spatial and Temporal Distributions of Apple Drought in Northern China
Cheng Xue, Sun Shuang, Zhang Fangliang, Zhang Zhentao, Liu Zhijuan, Wang Peijuan, Huo Zhiguo, Yang Xiaoguang
2020, 31(1): 63-73. DOI: 10.11898/1001-7313.20200106
Clarifying the spatial-temporal distribution and the periodic law of drought during different growth stages of apple in northern China can provide a scientific basis for disaster prevention and mitigation and high yield and quality. Based on daily meteorological data of 144 meteorological stations in north of China from 1981 to 2016, precipitation, water requirement, continuous no-precipitation days and the drought index during different growth stages of apple are calculated. Spatial distribution characteristics and temporal trends of apple drought in the study area are clarified. Finally, the periodic law of drought during different growth stages of apple in northern China is revealed with wavelet analysis. Results show that the spatial distribution of precipitation during different growth stages of apple is consistent with the spatial distribution of drought index. The precipitation exhibits an increasing trend from northwest to southeast during different growth stages. The precipitation during fruit tree sprouts to flower buds and flowering to maturity show a decreasing trend and the precipitation in stages from flower buds sprout to flower full bloom and from mature to fallen leaves exhibit an increasing trend from 1981 to 2016. The apple water requirement during stages from fruit tree sprouts to flower buds and from flower bud sprout to flower full bloom exhibit an increasing trend, while the other growing stages exhibit a decreasing trend from 1981 to 2016. High values for drought index are mainly distributed in Gansu, Ningxia, Hebei and Beijing. The drought index during the stage from fruit tree sprouts to flower buds shows an increasing trend, while during the other growth stages the drought index shows a decreasing trend from 1981 to 2016. There are three different scales of periodic variation for apple drought during different growth stages.Above all, areas with the most serious drought are mainly concentrated in Gansu, Ningxia, Hebei and Beijing. The drought is the most serious during the stage from flower bud sprout to flower full bloom, and the drought index during the growth stage from fruit tree sprouts to flower buds shows an increasing trend.
Comparative Study on Main Crop Yield Separation Methods
Li Xinyi, Zhang Yi, Zhao Yanxia, Du Zixuan, Yang Shenbin
2020, 31(1): 74-82. DOI: 10.11898/1001-7313.20200107
Crop yield separation is one of the important steps in analyzing the impact of meteorological factors on yield. Statistical rice yield data for 1985-2018 from 24 counties in Jiangsu are used to analyze the rationality of different separation methods. Six separation methods are 3-year moving mean, 5-year moving mean, five-point quadratic smoothing, quadratic exponential smoothing, HP filter and year-to-year increment. Consistencies and differences are analyzed from aspects of trend yield and meteorological yield. In order to select better methods that could accurately capture the yield variation caused by meteorological factors, the meteorological yield based on different methods are compared with the typical annual increase and decrease of rice yield records. Finally, as mentioned above, the selected methods are calibrated by the rationality of the relationship between meteorological factors and yield. Results show that the trend yield curves fitted by different methods are in line with the process of social technology development. Compared with the average trend yield, almost all the consistency correlation coefficients are greater than 0.5. It suggests that different methods do not differ much in trend fitting. Characteristics of meteorological yield separated by 3-year moving mean, 5-year moving mean, five-point quadratic smoothing and quadratic exponential smoothing in each county are simultaneously increasing or decreasing. And their standard deviation values are significantly smaller than HP filter method and year-to-year increment method. The result suggests that the rationality of separating the meteorological yields by 3-year moving mean, 5-year moving mean, five-point quadratic smoothing, and quadratic exponential smoothing is higher than the other two methods. Five-point quadratic smoothing method and 3-year moving mean method can capture almost 100% of typical annual meteorological yield changes in the whole research area. Further verification results show that the positive and negative effects of meteorological factors captured by 3-year moving mean and five-point quadratic smoothing method are more consistent with the response to meteorological factors. Overall, separation methods of five-point quadratic smoothing method and 3-year moving mean method are more suitable for this research area and match well with meteorological factors.
Experiments of Water Stress on Root/Shoot Growth and Yield of Summer Maize
Li Yan, Wang Zhiwei, Huo Zhiguo, Chen Chen
2020, 31(1): 83-94. DOI: 10.11898/1001-7313.20200108
Drought is one of the most important meteorological disasters affecting the growth and production of maize. Dynamic changes and cumulative effect of the drought are closely related to the degree of drought, duration, and growth stages. In order to investigate effects of drought stress on maize, artificial control experiments are carried out in Yuncheng of Shanxi, Xiajin of Shandong and Gucheng of Hebei from 2013 to 2015, in which relative soil moistures are 31%-40%, 41%-50%, 51%-60%, 61%-70% and CK (71%-100%), and the growth stages are seedling-jointing, jointing-tasseling, tasseling-maturity and jointing-maturity. The root/shoot growth and yield of maize are analyzed at different drought levels, effects of rapid water consuming stage and drought maintenance stage under different drought degrees are also analyzed. The growth stage and critical thresholds sensitive to drought stress are determined. Results show that with equivalent drought level, jointing to tasseling stage is the key growth stage affecting the shoot and yield, and the tasseling stage is sensitive to drought stress. The key growth stage of root and root/shoot ratio is from emergence to jointing stage, especially the jointing stage. Under different drought degree, the dry weight of the shoot and root and root/shoot ratio all show down trend at the rapid water consuming stage, which are respectively reduced by 11.7%-67.8%, 35.2%-85.8% and 15%-62% compared to control experiments. At the drought maintenance stage, the dry weight of the shoot is in reduced by 24.3%-89.7%, but the root dry weight and the root/shoot ratio are less sensitive, which respectively decreases by 9.7%-80.8% and 9.6%-62% compared to control experiments. Regression models for drought level and yield reduction rate are established respectively for two drought stages, and are above at 0.05 significant level. The effect of the drought maintenance stage is slightly greater than that of rapid water consuming stage. At the emergence-jointing stage, the relative soil moisture is 60%-62%, which is the critical threshold for the growth of shoot and formation of a reasonable root/shoot ratio. The relative soil moisture is 51%-60% from the emergence to seven-leaf stage, which is conducive to root growth. The relative soil moisture value of 62% is a critical threshold, below which the yield will be influenced by drought. When the relative soil moisture is 31%-40% during the sensitive stage of jointing, tasseling, the yield reduction is more than 70%. When the relative soil moisture is 50%-60% and the duration is less than 8 days, the growth of root and shoot can be restored after rehydration, but the yield is reduced by 1.4%-6.6%. Results can provide basis for rational irrigation and drought dynamic assessment.
Spatio-temporal Characteristics of Drought in Different Growth Stages of Soybean in Heilongjiang
Gong Lijuan, Li Xiufen, Tian Baoxing, Wang Ping, Jiang Lanqi, Zhao Huiying
2020, 31(1): 95-104. DOI: 10.11898/1001-7313.20200109
Heilongjiang is one of the main growing areas of soybean in China. Due to factors such as natural geographical location and climate, drought is one of primary determinant agro-meteorological disasters which constrains growth, development and the formation of soybean yield in Heilongjiang. Utilizing soil moisture data of 32 stations and soybean growth data of 26 stations from 1981 to 2017, the frequency of different grades of droughts, average intensity of drought, and drought risk indices are calculated. Spatio-temporal characteristics are analyzed from 5 regions in Heilongjiang, based on recognized hazard indicators on disaster grades of droughts for soybean from the meteorological industry standard which is released by China Meteorological Administration in 2018. Assessment and distribution of drought risk on the basis of occurrence frequency and intensity for soybean are pertained. Results show that the occurrence frequency of light drought is higher than that of severe and excessive drought for soybean. West region is an area where drought of soybean occurs frequently, centeral region takes the second place, and the other regions have relatively fewer drought occurrences. As for drought intensity, it's the highest in centeral region, the next is in west region, and the lowest drought intensity is in norht region. Moreover, the drought intensity in three-leaf to pod-bearing stage of soybean is higher than that in early and late growth stages in east, north and west regions. While in west and south regions, drought intensity during pod-bearing to maturity stage exceeds that in early stages. Drought risk indexes are negative. The lower number of risk index correlates with greater drought risk. The highest risk area is west region, the next is centeral region, and the last is norht region. It is an opportunity to seek the use of drought risk index as an indicator of drought risk of soybean. Considering the drought risk in different growth stages of soybean, the highest drought risk periods are flowering to pod bearing stages, and the drought risk of soybean is lowest in sowing to emerging stage. Areas of medium to high drought risk lie in the west of Songnen Plain and southwest of Sanjiang Plain in space through the whole growth period of soybean. And the others are low or slight drought risk regions. These results may provide guidance for soybean drought prevention, loss reduction and planting structure adjustment in Heilongjiang. It is strongly advised to strengthen the prediction and prevention of drought, especially in critical growth stages of soybean in two main plains.
Assessment of Open Biomass Burning Impacts on Surface PM2.5 Concentration
Ke Huabing, Gong Sunling, He Jianjun, Zhou Chunhong, Zhang Lei, Zhou Yike
2020, 31(1): 105-116. DOI: 10.11898/1001-7313.20200110
Open biomass burning plays an important role in the formation of heavy pollution events during harvest seasons in China by releasing gases and particulate matters into the atmosphere. A better understanding of open biomass burning in China is required to assess its impacts on the air quality and especially on heavy haze pollution.By using datasets of MODIS fire spot, land cover, vegetation cover, biomass loading and emission factors, a biomass emission model is developed, which is then embedded to an air quality model (WRF-CUACE) to quantitatively assess impacts of biomass burning on surface PM2.5 concentration in China through sensitivity tests. Three simulation scenarios are designed to ensure that simulation results of revised scenarios are closer to actual atmospheric conditions according to the model evaluation. Results show that in October 2014, Northeast, South and Southwest China are regions of the largest contribution to biomass burning with the average monthly increased concentration of PM2.5 up to 30-60 μg·m-3, and even more than 100 μg·m-3 at local regions. In North, East and South China, biomass burning generally provides a contribution of PM2.5 concentration of 5-20 μg·m-3. In terms of the percentage of relative contribution, the value in Northeast China exceeds 50% in most regions. In South China, the relative contribution of biomass burning reaches 20%-50%, and even exceeds 60% in parts of Southwest China. While in North, Central and East China, the relative contribution of biomass burning is generally 10%-20%. In addition, the contribution of secondary aerosols in PM2.5 from biomass burning is also estimated. A group of sensitivity experiments are set up, with and without the gas emission from biomass burning. In Northeast China, the contribution concentration of secondary aerosols is only 0-10 μg·m-3, significantly lower than that in North, Central, East and South China, where the contribution concentration of secondary aerosols could reach 5-15 μg·m-3. In terms of the percentage of contribution to secondary aerosols in PM2.5 from biomass burning, the value in Northeast China is the lowest, which is less than 30% in most regions. And in South and Southwest China, the contribution percentage is relatively larger, which can reach 30%-50%. While in North, Central, East China and vast remote areas, the contribution percentage almost exceed 70%. Based on the above analysis, it is found that the percentage of secondary aerosols in PM2.5 from biomass burning drops when the biomass burning grows.
Raindrop Size Distribution Characteristics of Nanjing in Summer of 2015-2017
Mei Haixia, Liang Xinzhong, Zeng Mingjian, Li li, Zu Fan, Li Yutao
2020, 31(1): 117-128. DOI: 10.11898/1001-7313.20200111
It's of great significance to study features of raindrop size distribution (DSD) during different stages of the summer monsoon for understanding the precipitation mechanism, which is regarded as credible reference to improve and refine ainfall retrieval algorithms based on satellite and radar observations and the parameterization of microphysics scheme in numerical model. Characteristics of DSD during summer (June to August) of 2015-2017 are investigated using measurements from a ground-based disdrometer in Nanjing. Results show different micro and macro precipitation characteristics among three stages of summer monsoon. Precipitation before Meiyu is characterized by the highest (among the three stages) mean mass-weighted raindrop diameter, average minutely rainfall rate, and intense minutely and strong hourly rainfall occurrences. Despite generally weak convection intensity in this stage, the persistent support from large-scale synoptic conditions, sufficient condensation and the weakened influence from evaporation, breaking-up and entrainment processes are beneficial to produce large raindrops and improve precipitation efficiency. In contrast, precipitation after Meiyu is identified with the greatest frequency of large raindrop and extreme minutely rainfall occurrences. This is mainly caused by severe convective activities under hot and humid atmospheric conditions. Stronger convection is also associated with higher frequency of smaller raindrops. In pace with the northward advancement of the summer monsoon, the convection intensity enhances gradually and breaking-up processes of raindrops heighten as well, which lead to higher ratio of small-raindrop samples with the largest value during the stage after Meiyu. From many aspects of these raindrop and rainfall characteristics, convective precipitation during Meiyu is inferior comparing to that in the other two stages. However, rainfall rates are highest and raindrops are largest during stratiform precipitation due to sufficient coalescence processes under favorable synoptic forcing conditions. The concentration of small raindrops is usually high but the ratio of small raindrops is the lowest in this stage. Among three stages, the binomial relationship between the shape index and slope parameter also differ significantly, depending on the value of the shape index. Compared with Meiyu of 2009-2011, the frequency of intense rainfall occurrence and its contribution to total precipitation decrease while those for weak rainfall increase in terms of both minutely and hourly rainfall. Simultaneously, the binomial relationship of the shape index and slope parameter changes significantly as well.