Current Issue

Vol.34, NO.3, 2023

Special Column on Evaluation of Fengyun Satellite Level 2 Products
FY-4A/AGRI Sea Surface Temperature Product and Quality Validation
Cui Peng, Wang Sujuan, Lu Feng, Xiao Meng
2023, 34(3): 257-269. DOI: 10.11898/1001-7313.20230301
Fengyun-4A (FY-4A) is the first satellite of China's second-generation geostationary orbit meteorological satellites. The advanced geostationary radiation imager (AGRI), a multiple channel radiation imager, is one of the primary payloads onboard FY-4A. As one basic quantitative remote sensing product, the operational sea surface temperature (SST) is derived with the split-window nonlinear SST (NLSST) algorithm in real time. The operational NLSST procedures and products are described in detail. The FY-4A/AGRI SST products provide full-disk SST with spatial resolution of 4 km at the nadir. The quality level information is delivered with each pixel to provide information about the conditions of the processing. Quality level for each pixel information is defined as follows: Excellent, good, bad and unprocessed (cloud, land, no satellite data etc.). The users can select the SST data with certain quality level according to their application purposes (e.g., for climate-related studies, only the SST data with the excellent quality level in the time series are used, and for identifying and tracking specific ocean features, users may be more tolerant of lower-quality SST data). The accuracy of FY-4A/AGRI SST algorithm is assessed by determining the standard deviation and bias errors from the regression procedure of the matchup database between satellite data and quality controlled SST data from NOAA in situ SST quality monitor, from July 2021 to June 2022. The validation methods and results are described in detail. The matchup database combining FY-4A/AGRI measurements and in situ SST have been built on a routine basis. At the stage of the matchup database in association with the drifter temperatures, the matchup database is composed of pixels under clear sky conditions. The FY-4A/AGRI SST data with excellent quality level are compared with drifting and tropical moored buoy data. The matchup space-time window is 4 km and 30 min from the buoy location to the center of the SST pixel. The comparison shows a bias of -0.45 to -0.42℃ and a standard deviation of 0.81-0.88℃ for FY-4A/AGRI SST with excellent quality. The correlation coefficients between FY-4A/AGRI SST and buoy SST are better than 0.985. The FY-4A/AGRI SST are also compared with the ACSPO SST produced at NOAA/STAR from the Himawari-8/AHI (advanced Himawari imager). The comparison shows a bias of -0.26 to -0.07℃ and a standard deviation of 0.68-0.82℃ with excellent quality level. The correlation coefficients between FY-4A/AGRI SST and Himawari-8/AHI are better than 0.985. The correlation coefficients shows that there is a good correlation between FY-4A/AGRI SST and Himawari-8/AHI SST.
Accuracy and Stability of Radio Occultation Dry Temperature Profiles from Fengyun Satellites
Liao Mi, Zhang Peng, Liu Jian, Liu Congliang, Bai Weihua, Xu Na, Chen Lin
2023, 34(3): 270-281. DOI: 10.11898/1001-7313.20230302
The earth's climate has undergone significant changes due to the combined effects of natural changes and human activities. To understand the impact of climate change, the most fundamental work is to establish high-quality data required for climate purposes. Currently, the long series observations mainly come from satellites and sites. However, most satellite sensors are designed for short-term and imminent weather monitoring and numerical prediction, rather than long-term climate monitoring. To meet future research needs, more efforts are needed in data reprocessing such as satellite calibration and multi-source data fusion.Global Navigation Satellite System Radio Occultation (GNSS-RO) is a system that carries a receiver on low orbit satellite to receive radio signals transmitted by the global navigation satellite system. GNSS-RO detects the earth's atmosphere in a borderline manner during relative motion. When propagating in non-vacuum atmosphere, radio signals may appear bent or delay due to different atmospheric physical characteristics. After complex processing, physical parameters such as atmospheric temperature, humidity, and density can be inverted. Each receiver observes approximately 500 occultation events per day, which are almost randomly distributed on the earth and not affected by clouds and underlying surfaces. These data provide a source of observational information with high vertical resolution and long-term stability, extending from near surface to upper stratosphere. The original occultation observation is based on time and position measurements, needing no calibration, which has advantages in climate change study.The occultation receiver on FY-3C/3D/3E meteorological satellite can receive GPS and Beidou Navigation Satellite System (BDS) signals, and the records are almost nine years long. To analyze the accuracy and stability of temperature records from multiple radio occultation, the mean and standard deviation of the dry temperature of FY-3C/3D/3E GPS and BDS radio occultation are studied using ERA5 data. It demonstrats that the accuracy of the dry temperature profile is the highest between 200 hPa and 20 hPa and the error characteristics of GPS and BDS radio occultation are similar. The stability of the average temperature deviation of FY-3C GPS for 5-year time series is very good, which is -0.0055 K·a-1. After several algorithm improvements, the standard deviation of FY-3C GPS dry temperature decreased to about 1 K at the beginning of 2018. BDS radio occultation products are operationally provided since April 2021, and there is a good consistency between FY-3C/3E and between GPS and BDS radio occultation. Due to the algorithm adjustment at the beginning of 2021, the average deviation between FY-3D radio occultation and ERA5 data shows a significant jump. In general, the stability of multiple radio occultation dry temperature records is good and promising for climate change monitoring and research. It is necessary to carry out homogeneity reprocessing.
FY-4A/AGRI Cloud Detection Method Based on Naive Bayesian Algorithm
Guo Xuexing, Qu Jianhua, Ye Lingmeng, Han Min, Shi Mojie
2023, 34(3): 282-294. DOI: 10.11898/1001-7313.20230303
Optical remote sensing cloud detection is the foundation for subsequent quantitative remote sensing and applications. A cloud detection method based on naive Bayesian algorithm is studied and applied to the advanced geostationary orbital radioimager (AGRI) on Fengyun-4A satellite. Cloud detection method considering radiation physics of visible light channels is discontinuous between day and night. To avoid the direct impact of solar radiation, the spectral data of 7 infrared channels loaded by AGRI are analyzed to construct 10 cloud detection feature classifiers. Using cloud polarized lidar with orthogonal polarization (CALIOP) data as the true value of cloud detection, and using its spatiotemporal matching data with AGRI, classification training and validation are conducted for datasets of different surface types and different seasons. The cloud detection results and CALIOP data cross-verification show that the cloud recognition accuracy over snow is about 81%, the cloud recognition accuracy rate over the deep sea, shallow water, land and desert is higher than 92%, the false positive rate is basically less than 10%, and the overall cloud recognition accuracy reaches 90%. Compared with MODIS level 2 cloud detection products in October of 2021 and January, April and July of 2022, the recognition accuracy rate of deep-sea and shallow water clouds is above 88%, and the false positive rate is lower than 3% and 10%, respectively. The overall cloud recognition accuracy rate in four seasons is more than 86%, of which the summer cloud recognition effect is the best, and the overall cloud recognition accuracy rate is as high as 90%. The recognition effects of the method are good during both day and night, ensuring not only the accuracy of day and night cloud detection, but also the continuity of cloud detection in the morning and evening transition zone. Due to the use of dynamic surface type files and sufficient training sample sizes for deep and shallow waters, the overall cloud recognition accuracy of the method is relatively ideal in four seasons, with the best performance in summer and autumn. The cloud recognition accuracy of deep and shallow water is generally high, but there are still omissions and misjudgments. The method can output classification results of cloud including probable cloud, probable clear sky, and clear sky, and it also outputs the uncertainty probability value of each feature and a comprehensive feature cloud detection classifier, which can provide important reference for cloud and surface related detection products.
Accuracy Validation of FY-4A Temperature Profile Based on Microwave Radiometer and Radiosonde
Wang Hong, Zhou Houfu, Wang Chen, Xia Yinan
2023, 34(3): 295-308. DOI: 10.11898/1001-7313.20230304
To take full advantage of FY-4A temperature profile data to understand the evolutions of weather processes and nowcasting, based on the atmospheric temperature profile of radiosonde, microwave radiometer and FY-4A satellite from 1 January 2021 to 31 March 2022, 897 samples are matched and their deviation characteristics are evaluated. The results show that the correlation coefficient between FY-4A satellite temperature and that of microwave radiometer is 0.9891, and the correlation coefficient between FY-4A satellite temperature and that of radiosonde is 0.9820. The mean temperature of FY-4A satellite is 0.51℃ smaller than that of the radiosonde below 10 km height, and the standard deviation is 0.50℃. The mean temperature of FY-4A satellite is 0.53℃ larger than that of the microwave radiometer below 10 km, and the standard deviation is 0.75℃. FY-4A temperature is consistent with the mean deviation trend of the radiosonde at 0000 UTC and 1200 UTC. Compared with 0000 UTC, the deviation sample of FY-4A at 1200 UTC is less discrete. When there is precipitation, the temperature deviation of microwave radiometer and FY-4A gradually increases above 600 m height, and the deviation reaches the maximum (about 9.35℃) near 1500 m height. In the range of 3000-8500 m height, the deviation ranges from 1.35℃ to 5.10℃, and the standard deviation ranges from 1.41℃ to 4.99℃. In the case of precipitation, the deviation values and standard deviations of FY-4A temperature and radiosonde are small. Although the deviation values and standard deviations of FY-4A temperature and radiosonde are different at different heights in the whole layer, the deviation is between -0.31 and 3.60℃. When there are clouds, the mean deviation between FY-4A temperature and that of microwave radiometer is -0.40℃, and the mean standard deviation is 3.79℃. The overall mean deviation between FY-4A temperature and radiosonde is 0.31℃, and the mean standard deviation is 2.66℃. Both the deviation and standard deviation between FY-4A temperature and that of microwave radiometer are larger than those between FY-4A and radiosonde when there are clouds. The deviation and standard deviation of microwave radiometer temperature and that of radiosonde with FY-4A are small in clear sky. The above conclusions can provide reference for the further use of FY-4A satellite data, as well as for the quality control of FY-4A satellite data and its application in weather analysis and forecast.
Application of the 2σ Lightning Jump Algorithm Based on DBSCAN Cluster
Tian Ye, Pang Wenjing, Chen Zefang, He Na, Zhao Sen, Ji Yan, Hao Rui, Zhang Tianming, Yan Di
2023, 34(3): 309-323. DOI: 10.11898/1001-7313.20230305
A DBSCAN (density-based spatial clustering of applications with noise) cluster of lightning data is proposed as the substitute for radar products to solve the problem of beam blockage in radar observation and the delay of radar products in service operations. Two lightning data, BJTLS (Beijing Total Lightning System) and upgraded National Lightning Positioning Network (DDW1), are used and the 2σ lightning jump algorithm is applied to perform severe weather nowcasting on 4 June and 12 June in 2022. The nowcasting effects of the strong convective cell identification method and the DBSCAN clustering method are further compared and analyzed. Based on a determined search radius (R) for neighboring lightning data and a determined minimum number of location results (number of minimum points) in R, the DBSCAN's clustering effect on lightning location data corresponds well with the strong convective radar echo. The ideal parameter combinations for BJTLS, R is 0.05, number of minimum points is 5; and for DDW1 data R is 0.22 and number of minimum points is 3. The results show that both methods and two kinds of data could effectively be used in severe weather nowcast. For BJTLS data, the effects of two methods are equivalent. The probability of detection, false alarm rate, critical success index and lead time of two methods are 100% and 100%, 11.9% and 13.3%, 88.1% and 86.7%, 38.9 min and 42.8 min, respectively. The 2σ lightning jump algorithm can be applied for nowcasting with lightning data, reducing the dependence on radar products. For DDW1 lightning data, compared with the identification method, the start time of the clustering method delays, leading to missing alarms. Since the flash rate of the DDW1 lightning data is low, there will be more missed cases if the flash rate threshold is set to trigger the lightning jump. But without the threshold, there will be more false alarms in operation. Therefore, BJTLS data is more suitable than DDW1 data for applying the 2σ lightning jump algorithm in the service operation. The detection efficiency of BJTLS in Beijing is high and it is necessary to further improve the detection efficiency of DDW1. In conclusion, the DBSCAN clustering method provides a new idea for the service operation of the 2σ lightning jump algorithm.
Characteristics of the Preliminary Breakdown in Inverted-polarity Intracloud Lightning Flashes
Gao Panliang, Shi Dongdong, Wu Ting, Wang Daohong, Ji Xiaoling
2023, 34(3): 324-335. DOI: 10.11898/1001-7313.20230306
The intracloud (IC) flashes can be classified into normal and inverted-polarity types according to their initial leader propagation directions. Due to the rare occurrence of inverted-polarity IC flashes with downward preliminary breakdown (PB) processes, the corresponding PB characteristics are much less understood than those in normal IC flashes.Based on the lightning data observed by a low-frequency lightning mapping system FALMA (fast antenna lightning mapping array) deployed in Ningxia, the characteristics of the PB process in 312 inverted-polarity IC flashes are statistically analyzed. The parameters of PB waveforms show that the arithmetical mean (AM) of the PB duration is 9.8 ms. The pulse shape is characterized by rise time, half-peak width, fall time, and pulse width, respectively, with AM values of 7.3 μs, 4.5 μs, 5.6 μs, and 24.7 μs. The pulse rate and pulse interval are 5.7 ms-1 and 169.2 μs.The statistical results for PB channels show that the inverted-polarity IC flashes are usually initiated at the AM altitude about 6.9 km, obviously higher than the initiation altitude of normal-polarity IC flashes. The difference indicates that there could be an inverted dipolar charge structure in the thunderclouds of Ningxia. The superposition of PB locations on the radar reflectivity suggests that these inverted IC flashes tend to be initiated in the region with radar echoes weaker than normal IC flashes (19.3 versus 27.8 dBZ). The vertical length and speed of PB channels are 2.0 km and 2.8×105 m·s-1.Furthermore, PB parameters show significant correlations with the initiation altitude. Specifically, both vertical speed and pulse rate decrease with the initiation altitude, and the correlation coefficients are -0.44 and -0.53, respectively. However, both PB durations and vertical distances show positive correlations with the initiation altitude, with the coefficients of 0.64 and 0.46, respectively.In general, the PB characteristics of inverted IC flashes present both similarities and differences to the PB processes in other flash types. It is believed more lightning observations in the northwest inland of China can facilitate the interpretation of these similarities and differences.
Distribution Characteristics of Raindrop Spectrum at Changbai Mountain Foothills in Summer of 2021
Sun Qinhong, Ma Hongbo, Qi Yanbin, Wang Xiujuan
2023, 34(3): 336-347. DOI: 10.11898/1001-7313.20230307
In order to better understand the distribution characteristics of raindrop particle spectrum at Changbai Mountain foothills in summer, the raindrop size distribution with different rainfall types and different rainfall intensities are analyzed based on the observations of Parsivel2 disdrometer at Jingyu, Jilin Province from June to August in 2021. The distribution characteristics of raindrop spectrum are also compared with relevant research results at home and abroad. The results show that the frequency of stratiform cloud rainfall is much higher than that of convective rainfall (88.16% vs 11.84%) in summer at Changbai Mountain foothills, but convective rainfall contributes more to the total rainfall intensity (47.78% vs 52.22%). The contribution of raindrop diameter to rainfall in summer increases first and then decreases, while the diameter of raindrop makes a greater contribution to rainfall ranging from 0.812 mm to 2.375 mm. For large particles (diameter D≥2.75 mm), the contribution of raindrops to rainfall also increase as rainfall intensity increasing. The spectra of convective rainfall has a larger spectrum width, mean number concentration and mean diameter than stratiform precipitation. The Gamma fitting curve underestimates the number concentrations of raindrops larger than 4.25 mm, especially for weak precipitation. Comparing with classical convective raindrop spectra, the normalized intercept parameter lgNw and the mass equivalent diameter parameter Dm of convective rainfall at Changbai Mountain foothills are closer to the oceanic-like cluster. The summer raindrops here have smaller diameter and higher number concentration compared with those of Yanqing and Daxing in North China, and Chuzhou and Pukou in East China. The reflectivity factor Z and rain rate R fitted relationships between convective rainfall and stratiform rainfall at Changbai Mountain foothills are Z=290.64R1.27 and Z=193.36R1.65, respectively. The rainfall of estimation using classical Z-R relationship (Z=300R1.40) is underestimated in this area, especially for heavy rainfall. The shape parameter μ and the slope parameter Λ of Gamma fitting function satisfy binomial relationship, while the parameter Λ increases with the increase of parameter μ. Besides, the shape parameter μ of raindrop spectrum at Changbai Mountain foothills is less than that in North China, East China and South China on the whole, when the slope parameter Λ is equal.
Performance of Domestically Made Surface Solar Radiation Observation System at Zhongshan Station, Antarctica
Zheng Xiangdong, Zhao Yong
2023, 34(3): 348-361. DOI: 10.11898/1001-7313.20230308
Solar irradiance is one important element in conventional meteorology observations. Long-term observations of solar radiation by using China-made wide-band pyranometers have been carried out. However, the performance of instrumental systems is not sufficiently evaluated or analyzed, especially in the polar regions where harsh condition and large seasonal variations of solar elevation causes dramatic variation of surface solar irradiance. To fill this gap, the performance of the domestically made solar radiation observation systems at Zhongshan Station, Antarctica in 2017, including global solar radiation (GSR), direct solar radiation (DIR) and the diffuse solar radiation (DIF) measurements, is evaluated. The averaged nighttime thermal offsets of two domestic FS-6A pyranometers, respectively for GSR and DIF observations, are both less than 3 W·m-2, and their temporal variations are highly consistent. Compared with CM21 or CM22 pyranometer that reach the requirement of the second-class standard and are globally deployed, the additional heating effect of the auxiliary ventilation heater of FS-6A pyranometers significantly reduces the inherently physically-based correlation coefficient between the night thermal offset and the net longwave radiation, and the absolute values of FS-6A thermal offset significantly increase but are within 5 W·m-2 under higher wind speeds (noless than 15 m·s-1). The temporal variations of solar DIF irradiances from two FS-6A pyranometers are highly consistent under cloudy overcast condition, and their solar irradiance values are systemically lower (about -6 W·m-2 or -1%) than that of CM22 as the solar DIF irradiance is about 500 W·m-2 from CM22. However, the absolute (relative) difference is respectively lower than 2.6 W·m-2 (4.0%) as the solar zenith angle (θ) is less than 86 °. The GSR close examination suggests that the ratio of FS-6A GSR absolute difference from the sum of horizontally projected DIR and DIF meeting the requirement of threshold value (less than 2% or 15 W·m-2 with θ≤ 80°) proposed by the baseline surface radiation network (BSRN) is more than 80%. But only 44% samples meet the requirement of the BSRN threshold value (less than 3.5% or 20 W·m-2 with θ> 80°) when the four-quadrant tracking solar disk model is applied in operation. Under cloud-free condition, the measurements of GSR, DIR and DIF from the domestically made instruments are well comparable with the simulations from the parameterized solar radiation model that has been extensively applied in middle-low latitudes, and the correlation coefficients between the simulations and observations are more than 0.95. However, the observations are significantly higher than the simulations as the solar irradiance increases. The results suggest that China domestically made solar radiation observation system is fully qualified for the routine observation in polar regions.
Response of Winter Wheat Tanmai 98 to Sowing Date Adjustments
Ren Sanxue, Zhao Huarong, Zhou Guangsheng, Qi Yue, Tian Xiaoli, Geng Jinjian
2023, 34(3): 362-372. DOI: 10.11898/1001-7313.20230309
Sowing date adjustments have been widely used for crop adaptation to climate change, but its impact on crop growth and development is still unclear. Based on field sowing date adjustment experiment of winter wheat Tanmai 98 in the northern part of North China Plain from 2017 to 2022, the responses of growth and development, yield formation and quality of Tanmai 98 are analyzed. The results show that delaying sowing date has no significant effect on the growth stage of overwintering stage and regreening stage of winter wheat. The total growth period is 256 days and 228 days for early sowing and late sowing based on the field experiment, and shortening 10 days to 8 days in turn, which is basically consistent with the interval of 10 d during sowing period. The shortening of whole growth period is mainly caused by the shortening of seedling growth period before overwintering. Late sowing date reduces effective panicles number and grain yield of Tanmai 98. The decrease rate of grain yield is 569.71 kg·hm-2·(10 d)-1 during the sowing date from 30 September to 30 October, but few significant effects are found on grain number and weight per spike. The delay of sowing date also affects the aboveground dry matter distribution of Tanmai 98 during maturity stage. The stem weight decreases with the delay of sowing date by 2.44%·(10 d)-1, but the spike of wheat increases by 2.44%·(10 d)-1. The harvest index increases with the delay of sowing date. The harvest index of S2, S3 and CK are all higher than 0.5000, while the harvest index of S1 is 0.4878. There is no significant effect on leaf photosynthetic characteristics and grain quality of Tanmai 98 by sowing date adjustments. Therefore, under the background of climate change, the winter wheat sowing date should be postponed in the northern part of the North China Plain from 1 October to 15 October. At the same time, the planting amount should be increased in steps, and basic seedlings should be increased, so as to offset the adverse effects of late sowing of wheat seedlings with fewer tillers and fewer panicle number, ensuring high yield. However, very late sowing date would still lead to yield reduction. The results provide information for the decision-making of winter wheat to climate change adaptation in the northern part of the North China Plain.
Short Contributions
Effects of Meteorological Conditions on the Yield of Lianyu No.1 Maize
Wang Junfang, Zhou Guangsheng, Song Yanling, Ren Sanxue
2023, 34(3): 373-378. DOI: 10.11898/1001-7313.20230310
Understanding the influence of meteorological conditions on maize yield is an important basis for ensuring stable and high yield. The effects of meteorological conditions on the yield of Lianyu No.1 maize in North China are analyzed, based on the four-year field experimental data of different sowing dates (8 June(S1), 18 June(S2), 28 June(S3) and 8 July(S4)) conducted at Hebei Gucheng Agricultural Meteorological National Field Scientific Observation and Research Station from 2018 to 2021. The results show that the delay of sowing dates leads to the extension of growing period and changes in the meteorological conditions during the growing period. When the sowing date is delayed by 20 days, the average growth period is 2.5 days longer compared with sowed 10 days earlier, and the average air temperature from emergence to jointing stages increases by 0.7℃, while the average air temperature from milk-ripening to maturity stage decreases by 5.9℃. The average yield of Lianyu No.1 maize decreases with the delay of sowing dates, and the highest yield would be achieved when the sowing date is during 8-18 June. The key meteorological factors affecting maize yield per unit area are the daily temperature range from seedling emergence to jointing stage and the average temperature from tasseling to milk-ripening stage. The results provide a reference for scientific sowing date of Lianyu No.1 maize to ensure stable and high yield.
Impact of Climate Change on Potential Planting Areas of Rubber Trees in Yunnan
Lu Weikun, Li Meng, Hu Xueqiong, Li Xiang
2023, 34(3): 379-384. DOI: 10.11898/1001-7313.20230311
Based on the meteorological observations since 1981, the impact of climate change on rubber tree planting in Yunnan is analyzed from the aspect of the climatic suitability of rubber tree. The results show that annual average temperature of the main rubber producing counties in the south and east increases by 0.6-0.8℃ in most areas, and more than 1.0℃ in most areas in the west. In January, the average temperature in most areas of the main rubber producing counties in the east of the Ailao Mountain increases by 0-1.0℃, while that in the west increases by 1.0-2.0℃ in the 2010s compared with the 1980s. At the same time, the most suitable and suitable climate area for rubber tree planting increase by 55.3% and 18.6%, respectively. The increased areas are mainly distributed in the west of the Ailao Mountain, indicating that the west area of the Ailao Mountain is more suitable for rubber tree planting due to climate change.