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主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

Table of Content

    28 August 2022, Volume 38 Issue 4 Previous Issue    Next Issue
    Articles
    Analysis of strong precipitation in the urban area of Shenyang under the Northeast Cold Vortex background
    Yun-xia DUAN,De-qin LI,Yong-ming JI,Wei-long BAN,Yu-tong WU,Xiao-ou LI
    2022, 38 (4):  1-10.  doi: 10.3969/j.issn.1673-503X.2022.04.001
    Abstract ( 371 )   HTML ( 23 )   PDF (4370KB) ( 168 )   Save

    Using Liaoning province automatic station observational data, upper-air observation data, Doppler Radar data, and ECMWF reanalysis data, weather characteristics and predictability of the urban local short-term heavy rain process were analyzed under the background of cold vortex weather in Shenyang on June 30, 2016.The results show that the weather process is a typical afternoon strong convective weather.During the day, solar radiation heating results in the urban temperature higher than the surrounding areas and there is significant unstable energy in the middle and low-level with a high humidity environment.Southwest airflows from the ground to 300 hPa height have increased continuously since 2 hours before the rainstorm, meanwhile, the exit area of the low-level jet is depressurized, leading to intensifying the vertical movement and the ascending movement reaching the tropopause, which is beneficial to trigger and strengthen convection.Southwesterly wind pulsation and the weakening and disappearance of jets at heights from 1.5 km to 3.0 km and with the speed of 16 m·s-1 have a good indication of the occurrence and end of precipitation.The unstable stratification resulting from low-level convergence and high-level divergence in the afternoon is also established 2 hours before the heavy precipitation, and the maximum divergence corresponds well to the heavy precipitation.Radar observations indicate that the precipitation is dominated by low-centroid warm clouds with high precipitation efficiency.The surface convergence line triggers convection, which gradually develops into a belt-shaped convective system.Judging from the results of the numerical forecast, the model failed to report the impact of the city's underlying surface on meteorological elements, and the forecasting surface convergence line was lagging and weak, leading to the forecasting difficulties of heavy precipitation.

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    Cause analysis and spatial test of multi-mode numerical prediction on regional rainstorms in Liaoning province
    Yue YU, Ming-lin BI, Qi YAN, Hai-feng LIN, Dong-lei FENG, Fan-yue YU
    2022, 38 (4):  11-18.  doi: 10.3969/j.issn.1673-503X.2022.04.002
    Abstract ( 373 )   HTML ( 13 )   PDF (2536KB) ( 67 )   Save

    Based on the actual precipitation of three source fusion grid, the observation data from intensive automatic station, the basic radar reflectivity factors, high-resolution numerical prediction products, and FNL reanalysis data, the synoptic system classification tests on twelve regional rainstorm processes during flood season of 2020 in Liaoning province were carried out, and it was shown that the predictability of the cyclone rainstorm was low.Then the typical cyclonic rainstorm during July 12-14 was selected for further analysis.Using the object-oriented spatial test method, SAL (Structure, Amplitude, Location), combined with the traditional test method, the causes of prediction errors in different models were quantitatively analyzed from three aspects including structure, strength, and position.The results show that the rainstorm area is concentrated and presents double rain belt distribution.Rain intensity in the local area is significant and the reasons for precipitation are different in the areas of east and west of Liaoning province.The TS scores of CMA regional model are higher than those of the global model.SAL space test shows that CMA regional model well represented the internal structure of the rain belt, whereas the structural errors in the global model mainly due to the forecasting weakness of extreme precipitation.The strength tests show that the predicted rainfall intensities appear close to the actual situation in CMA-MESO3km, followed by EC_THIN, and insufficient in CMA_GFS.In general, the rainstorm area in each model is credible with the best result in CMA-MESO3km.The prediction errors in the rainstorm area mainly result from the significant discrepancies between the model prediction focus and the actual situation.

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    Articles
    Micrometeorological characteristics and dust transport during a blowing sand event in the spring of 2020 over northern China
    Yi-meng ZHANG,Xiao-lan LI,Hong-sheng ZHANG,Ye HONG
    2022, 38 (4):  19-26.  doi: 10.3969/j.issn.1673-503X.2022.04.003
    Abstract ( 133 )   HTML ( 6 )   PDF (2000KB) ( 61 )   Save

    Based on multilevel observations of meteorological variables and surface atmospheric particulate matter (i.e.PM2.5 and PM10 in this study) mass concentration in Horqin Sandy Land area and Shenyang, we analyzed the characteristics of micro-meteorology and dust transportation during a blowing dust event on May 10, 2020, in northern China.The results indicate that during the blowing dust event affected by large-scale synoptic systems, wind speed at different heights (< 20 m) over the Horqin Sandy Land area increases significantly and ambient relative humidity at each level and surface water content both decrease.Enhanced turbulent dynamic activity along with dry air and soil conditions is conducive to the release of massive dust particles from the surface of sand source areas into the atmosphere.Thereafter, these dust particles are transported to the downstream areas with the strong northwesterly airflow, concentrating at altitudes below 2 km.Due to the long-range transport of dust particles, the hourly mean PM10 concentration in Shenyang on May 10 increased up to 817 μg·m-3, and the visibility decreased to 3.7 km.During the dust emission period in the Horqin Sandy Land area, visibility exhibits a significant negative correlation with friction velocity (correlation coefficient R2=0.93) and a weaker negative correlation with kinetic turbulent vertical heat flux, meaning that the turbulent dynamic effect plays a leading role in the dust emission process.

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    Evaluation and projection of temperature and precipitation change in the Liaohe River Basin based on BCC-CSM2-MR model CMIP6 test
    Qing-fei ZHAI,Feng-hua SUN,Xue AO,Shu-jiang GENG,Cheng-long LI,Yao LI,Ming-yu LI
    2022, 38 (4):  27-36.  doi: 10.3969/j.issn.1673-503X.2022.04.004
    Abstract ( 321 )   HTML ( 14 )   PDF (2349KB) ( 43 )   Save

    Based on the simulation results from the Coupled Model Intercomparison Project Phase Sixth (CMIP6) carried out by the medium resolution climate model BCC-CSM-MR from National Climate Center, we first evaluated the simulation capability of the model using the data from 80 meteorological stations in the Liaohe River Basin.Then we analyzed the trends of temperature and precipitation under the Shared Social-Economic Pathways (SSPs) in the future.The results show that the model can well simulate the monthly, seasonal, and annual variations of temperature and precipitation.The simulated temperature is lower than the observations, while the simulated precipitation is slightly overestimated.The simulation performances of temperature are significantly better in autumn and winter than in summer and spring, and those of precipitation are better in summer than in other seasons.The model well reproduces the zonal temperature variations of high in the south and low in the north, and the spatial variations of precipitation gradually decrease from southeast to northwest.The model also simulates well the location of the warm and cold center in the Liaohe River Basin, and the simulated areas with less precipitation are located in the sparse water system areas.Compared with the base period (1995-2014), the temperature and precipitation in the Liaohe River Basin will generally increase in the future, and the increase in various future scenarios from high to low is average minimum temperature, average temperature, and average maximum temperature, respectively.The temperature increase appears more significant in winter and spring, whereas the precipitation increase appears more significant in summer.With the increase in emission scenario, the average temperature and average minimum/maximum temperature increase continuously, and the significant warming areas are concentrated in the northeast of Liaohe River Basin.Under the SSP1-2.6 and SSP2-4.5 scenarios, the increase in precipitation is estimated to decrease from southwest to northeast, and the area with a large precipitation increase is located in the west of Liaoning province.Under the SSP3-7.0 and SSP5-8.5 scenarios, the increase in precipitation presents a meridional distribution with gradual decreases from west to east, and the significant precipitation increase areas are located in Inner Mongolia and western Liaoning province in the upper reaches of the Liaohe River Basin.

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    Multi-model comparison and evaluation of forecast statistics and spatial verification for different precipitation types caused by Typhoon Bavi
    Dong-dong WANG,Li SUN,Lei YANG,Li-du SHEN,Shu WANG,Yu CHEN
    2022, 38 (4):  37-46.  doi: 10.3969/j.issn.1673-503X.2022.04.005
    Abstract ( 230 )   HTML ( 3 )   PDF (2269KB) ( 52 )   Save

    Typhoon Bavi (2008) is the first one to affect Liaoning province at a typhoon level in history and resulted in a persistent precipitation event over wide regions.In this study, the methods of traditional verification and object-based diagnosis evaluation (MODE) were used to evaluate the multi-model (ECMWF, CMA_MESO 10KM, CMA_MESO 3km and RMAPS-Dongbei) forecasts for different types of precipitation during Typhoon Bavi.The result indicated that convective precipitation and stable precipitation occur in Liaoning province due to Bavi's remote and own effects.The evaluation results from traditional verification and the MODE showed that the multi-model forecast performance for convective precipitation is better than that for stable precipitation.This is probably due to a large deviation in forecast intensity of influencing systems related to stable precipitation when the typhoon moves northward and becomes weakened.In the future, more attention should be paid to the impact of forecast deviation of typhoon intensity on stable precipitation.According to the traditional verification, the CMA_MESO 3km and ECMWF models have higher scores, with the best performance on the shape, extent, centroid distance, and intersection area of convective precipitation bands.The ECMWF model also has a high target similarity score for stable precipitation.Although the RMAPS-Dongbei model has a low threat score (TS) mainly due to the high false alarm rate and detection failure ratio for precipitation above 10.0 mm, the center position, precipitation intensity, and areas of heavy precipitation belts predicted by this model are close to the observations based on the MODE results.The RMAPS-Dongbei model has a higher target similarity score, which reaches 1.00 during the convective-precipitation stage and can provide a good reference for the prediction of convective precipitation.

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    Prediction model of first-frost date in Liaoning province using machine learning methods
    Tao WANG,Yi-shu WANG,Chun-yu ZHAO,Xiao-tao WANG,Mei-ou QIN,Yu-min SHEN,Yi-ling HOU,Jian-yun ZHAO
    2022, 38 (4):  47-56.  doi: 10.3969/j.issn.1673-503X.2022.04.006
    Abstract ( 174 )   HTML ( 11 )   PDF (2212KB) ( 162 )   Save

    Based on ERA5 monthly reanalysis data, the first-frost date in Liaoning province was predicted and evaluated using three machine learning algorithms (Lasso Regression, Random Forest, and Neural Network). The Lasso Regression algorithm was applied to identify the feature sets of meteorological parameters that have important indications for the prediction of the first-frost date, and the prediction model for the first-frost date was established after cross-validation and hyperparameter-tuning processes. Finally, the performance of first-frost prediction was evaluated quantitatively and qualitatively using the root mean square error (RMSE) and the rate with the same sign of an anomaly. The results showed that the feature sets of meteorological parameters after feature selection can improve the generalization ability, interpretability, and robustness of the model. The prediction performance of the Lasso Regression model performs best with prediction starting from April (with RMSE of 6-8 d), the Neural Network model has the best performance with prediction starting from May (with RMSE 6-9 d), and the Random Forest model performs best with prediction starting from March (with RMSE 8-9 d). The rate with the same sign of anomaly ranges from 50% to 70% at most stations in Liaoning province, with the Lasso Regression and Neural Network models reaching a maximum rate (about 68%) with prediction starting from May and with the Random Forest model reaching a maximum rate (about 62%) with prediction starting from March. Results from feature selection and sensitivity experiments indicated that the low vegetation coverage scale is the key predictor. High vegetation coverage favors the maintenance of surface water content, and frost is more likely to occur with lowered temperatures, leading to an earlier first-frost date. The model has a poor performance after excluding the low vegetation coverage scale factor, which is the key among previous factors. In short, machine learning algorithms have high skills in the quantitative and qualitative prediction of the first-frost date.

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    Comparison of spatial interpolation methods of meteorological elements over Chongqing mountainous region
    Chun-hua YANG,Li ZHENG,He-qing HUANG,Bo LEI,Shuo YANG,Jian-hui LIU,Ming-yang ZHANG,Qiu-yan DUAN
    2022, 38 (4):  57-66.  doi: 10.3969/j.issn.1673-503X.2022.04.007
    Abstract ( 133 )   HTML ( 2 )   PDF (1793KB) ( 246 )   Save

    Mountainous terrain is one typical and complex land surface, and the accurate simulation and acquisition of meteorological elements over mountainous regions are facing challenges due to a limited number of meteorological stations. Based on the meteorological data over the studied area in 1999 and 2018, we used four methods of thin-plate smoothing splines (ANUS), Co-Kriging (CK), ordinary Kriging (OK), and inverse distance weighting (IDW) to spatially interpolate air temperature, precipitation, and total solar radiation on annual and monthly scales. Using a cross-validation method, mean absolute error (MAE), magnitude of relative error (MRE), and root mean square error (RMSE) are used to evaluate the interpolation accuracy and determine the optimal interpolation method for each meteorological element. The results showed that ANUS is the optimal interpolation method for air temperature and total solar radiation, while IDW is the optimal interpolation method for precipitation. The interpolation accuracy for air temperature and total solar radiation is better during the months with high air temperature and total solar radiation than that during months with their low values, and the trend is opposite for the precipitation. The interpolation accuracy for the three elements is better on an annual scale than on a monthly scale. The MRE values showed that the interpolation accuracy for the three elements is in order of air temperature > total solar radiation > precipitation, being 1.86%, 4.6%, and 6.87% on an annual scale in 1999 and being 2.79%, 5.82%, and 17.42% on a monthly scale, respectively. In 2018, the interpolation accuracy for total solar radiation is 3.03% and 4.88% on the annual and monthly scales, respectively. After using data at regional encryption stations, the interpolation accuracy for air temperature and precipitation can reach 2.03% and 11.2% on the annual scale and 3.2% and 23.14% on the monthly scale, respectively. Our research can provide scientific reference and a basis for the spatialization of meteorological elements in similar complex terrain areas.

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    Variation of haze days in Northeast China in autumn and winter and its relationship with Arctic sea ice from 1981 to 2018
    Di WANG,Zhen WANG,Lan LI,Li SUN,Xin MENG,Nan-shu XIAO,Dong-jun YANG
    2022, 38 (4):  67-75.  doi: 10.3969/j.issn.1673-503X.2022.04.008
    Abstract ( 113 )   HTML ( 3 )   PDF (3170KB) ( 41 )   Save

    Using observational data at 166 meteorological stations in Northeast China from 1981 to 2018, we defined a haze-day index in autumn and winter in Northeast China and analyzed the internal relationship between the number of haze days and the atmospheric circulation anomalies. The results indicated that the haze-day index in autumn and winter in Northeast China exhibits a significant interannual variation.The configuration of atmospheric circulation anomalies such as the negative phase of the Eurasia-Pacific Teleconnection Pattern (EUP) and the weak East Asian trough leads to the increase in the occurrence frequency of haze events during autumn and winter in Northeast China. The Barents Sea and the northern Kara Sea are key areas of sea ice that affect the interannual variation of haze days in autumn and winter over Northeast China. The area of sea ice in this region has a significantly negative correlation with the number of haze days. The atmospheric circulation indirectly affects the occurrence frequency of haze events in autumn and winter in Northeast China. When the area of Arctic sea ice is anomalously low, East Asian winter monsoon is relatively weak, near-surface wind speed is low, and ambient humidity is high. Meanwhile, Northeast China is controlled by the abnormal southerly winds on the western side of the Northeast Asian abnormal anticyclone and is influenced by the negative phase mode of EUP, and the large trough in East Asia is weakened, which favors the transport of air pollutants and water vapor to Northeast China, increasing the frequency of haze events in autumn and winter in this region.

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    Spatiotemporal characteristics of heat and rainfall resources during the growth period of spring maize in Shenyang from 1981 to 2020
    Shan JIANG,Hai-xu ZHANG,Jing ZHANG,Xiao-wei SONG,Shi LI,Lu YU,Xin-xiu WANG
    2022, 38 (4):  76-84.  doi: 10.3969/j.issn.1673-503X.2022.04.009
    Abstract ( 150 )   HTML ( 3 )   PDF (2048KB) ( 63 )   Save

    Based on the daily meteorological data and growth period data of spring maize from seven meteorological stations in Shenyang, the spatiotemporal change characteristics of the growing degree days (GDD), heating degree days (HDD), precipitation, and climatic tendency rate of spring maize during sowing, seeding, elongation, heading, maturation, and whole growing periods were analyzed. The results indicate that the GDD of spring maize shows an upward trend during the whole growing period. The spatial distribution difference of GDD during different growth periods is not significant, which demonstrates an ascending trend from the north to the south, with the high value mainly distributed in Hunnan and Sujiatun Districts, and the low value in Kangping and Faku counties. The HDD of spring maize during the whole growing period increases progressively. Except for Kangping, which shows a decreasing trend during the mature period, the HDD in other regions shows an increasing trend during the growing period, increasing from northwest to southeast in space. In the last 40 years, the whole growing period of spring maize in the Shenyang area shows a decreasing trend, and the spatial trend is decreasing from southeast to northwest. At the seedling stage, the precipitation in all regions shows an increasing trend, and the other periods show a decreasing trend. During the whole growing period of spring maize in Shenyang, the heat resources show increasing trends, but the precipitation shows a decreasing trend, which will increase the risk of extremely high temperature and meteorological drought in the region.

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    Effects of less irradiation stress on the characteristics of flowering and fruit-setting of tomato in solar greenhouse
    Ji-bo ZHANG,Nan LI,Can QIU,Xiao-ping XUE
    2022, 38 (4):  85-92.  doi: 10.3969/j.issn.1673-503X.2022.04.010
    Abstract ( 137 )   HTML ( 1 )   PDF (881KB) ( 110 )   Save

    In this study, the tomato variety "Golden Crown No.5" was used as the test material. From 2015 to 2019, the sun-shading net was used in the solar greenhouse to design different duration days (0 d, 1 d, 3 d, 5 d, 7 d, and 9 d) of less irradiation (PAR≤200 μmol·m-2 s-1). Blooming Date (BD), Number of Flowers (NoF), Flower Rate (FR), and Fruit Setting Rate (FSR) of each ear of tomato were measured after flowering. Also, the influence of less irradiation stress on the characteristics of flowering and fruit setting in tomatoes was analyzed, and the simulated model of the influence of less irradiation stress on the characteristics of flowering and fruit setting in tomatoes was established based on the accumulated photo-thermal effectiveness (APTE), which was verified using independent data, and compared with the simulation model constructed by PAR daily integral method (PAR). The results show that the flowering time of six panicles of tomato is delayed to different degrees under less irradiation stress, especially for the second and third panicles directly affected by less irradiation stress. The flowering time of the second panicles of tomato is delayed by about one week compared with CK for 7-9 days. The number of fruit per panicle and fruit setting rate of tomato decreases with the increase of the duration of less irradiation, and the longer the duration of less irradiation, the greater the decrease. The model based on APTE significantly improves the prediction accuracy of tomato flowering and fruit setting characteristics under less irradiation stress. Compared with PAR method, The standard errors (RMSE) of BDC, NoFC, FRC and FSRC regression estimation of the second and third panicles of tomato are reduced by 25.5%, 16.7%, 21.2%, 23.8% and 31.4%, 22.4%, 25.2%, 26.6%, respectively.

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    Evaluation of maize drought loss at different sowing dates of typical drought years in western Liaoning province based on WOFOST model
    Yuan FANG,Ni-na CHEN,Peng JIANG,Shi-bo GENG,Na MI,He-ran WANG,Xian-long ZHU,Yu-shu ZHANG
    2022, 38 (4):  93-101.  doi: 10.3969/j.issn.1673-503X.2022.04.011
    Abstract ( 100 )   HTML ( 0 )   PDF (767KB) ( 105 )   Save

    Aiming at the western Liaoning area where drought disasters occur frequently, taking spring maize as the research object, the WOFOST crop model was selected to study the model applicability in typical dry years and the evaluation of drought losses at different sowing dates.The model was driven by drought stress control test data, field test data and meteorological data.The results show that the WOFOST model after parameter calibration can better simulate the yield and loss of spring maize in typical dry years in western Liaoning province.Different sowing dates in western Liaoning province are affected by drought to different degrees, and the risk of drought reduction decreases with the delay of the sowing date.The average yield reduction rate caused by drought is about 59%-61% in 2015 (medium drought), 20%-39% in 2018 (light drought), and 36%-62% in 2020 (medium drought), respectively.The effect of drought on yield is different in different growth stages.In general, the continuous severe drought has the greatest effect on yield in joint-tasseling and tassel-milking stages, followed by tassel-milking and joint-tasseling stages.Drought in each growth period has the greatest impact on Chaoyang station, followed by Heishan station and Fuxin station.In western Liaoning province, the risk of moderate drought and severe drought in the jointing and tasseling stage increases with the sowing date, while the risk of moderate drought and severe drought in tasseling and milk-ripe stage decreases with the sowing date.When severe drought occurs continuously in the jointing and tasseling and milk-ripe stage, the degree of dry drought damage increases with the sowing date, and the yield reduction rate can be as high as 46%-84%.

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    A memory of soil moisture and its relation with hydrothermal climatic conditions in the Sanjiang Plain
    Fang WANG,Jing LIANG,Hong-wei SUN,Yong-gang GAO
    2022, 38 (4):  102-109.  doi: 10.3969/j.issn.1673-503X.2022.04.012
    Abstract ( 106 )   HTML ( 2 )   PDF (2198KB) ( 22 )   Save

    Based on the data on soil moisture, precipitation, and temperature at 19 national meteorological stations in Sanjiang Plain from 1982 to 2020, the correlation coefficient and autocorrelation coefficient were used to analyze the soil moisture memory and its relationship with precipitation and temperature in Sanjiang Plain of Heilongjiang province.The results show that the memory time of soil moisture in spring and summer in Sanjiang Plain varies between 10-40 days.The average memory time of soil moisture in different layers is the longest in the middle layer (10-20 cm), and the lower layer shows a decreasing trend.The average memory time of 10-20 cm soil layer in spring and summer in Sanjiang Plain is 20 days and 17 days, respectively.The memory intensity of soil moisture in summer is higher than that in spring, and the memory intensity of soil moisture in the west of Sanjiang Plain is stronger, and the memory intensity of soil moisture tends to increase with the increase of soil layer.Precipitation is the main source of soil moisture in Sanjiang Plain.Under the synergistic effect of precipitation and temperature, soil moisture in summer and autumn has a significant positive correlation with precipitation and temperature and humidity index in the same period.Soil moisture in spring is also positively correlated with precipitation in autumn and winter and negatively correlated with temperature and humidity index in the early period.The increase of temperature in autumn and winter in the early period will promote soil thawing and freezing, thus increasing soil moisture in the spring of that year.Understanding the persistence of soil moisture anomaly is beneficial to climate prediction, drought evaluation, and agricultural production.

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    Distribution characteristics of lightning in southern mountain areas and northern plains of Anhui province
    Kai WANG,Xiao-yu JU,Yang-yang QIU,Xiang-yang CHENG
    2022, 38 (4):  110-117.  doi: 10.3969/j.issn.1673-503X.2022.04.013
    Abstract ( 147 )   HTML ( 6 )   PDF (1068KB) ( 51 )   Save

    According to the detected data of the ADTD lightning location system in Anhui province from January 2011 to December 2019, the parameters associated with lightning such as frequency, polarity, current intensity, etc.in southern mountain areas and northern plains in Anhui province were comparatively analyzed.The results showed that the total lightning frequency in southern mountain areas is about 2.84 times of that in northern plains, and the positive lightning ratio is larger in northern plains than in southern mountain areas, which is related to the types of severe convective weather.In the two areas, the monthly and daily variation of lightning frequencies both present the single peak, and the incidences in spring and summer are significantly more than in autumn and winter, and the lightning is active from afternoon to evening in a day, but the fluctuation range of months and time bucket when lightning occurs at high frequency in southern mountain areas are far greater than in northern plains.The intensities of lightning current in northern plains, on the whole, is larger than in southern mountain areas, and the positive and negative lightning intensities for the former are 10.77 kA and 9.52 kA higher than those for the latter, and the peak values of positive and negative lightning intensities in the two areas both appear in February and October, respectively.The time buckets of positive and negative lightning intensity peak in southern mountain areas and negative lightning intensity peak in northern plains are opposite to those of their frequency peak.Based on the principal component analysis of the total lightning frequency in Anhui province, the cumulative variance contribution of the first five feature vectors after EOF reaches 59.136%, indicating the change trend of lightning activities in the two areas are consistent, but has obvious regional difference.

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    Quality control of seconds temperature and pressure data
    Rong-wei LIAO,Xiao-yi FANG,Huai-yu LIU,Yu-jing CAO,Dong-bin ZHANG,Yu-zhou ZHU
    2022, 38 (4):  118-126.  doi: 10.3969/j.issn.1673-503X.2022.04.014
    Abstract ( 109 )   HTML ( 1 )   PDF (1872KB) ( 104 )   Save

    Based on the high frequency observation data obtained from the automatic weather station, a threshold check algorithm developed using the percentile threshold method (PTM) was used to conduct a detection test to seconds temperature and pressure data.Specifically, six coefficient combination schemes for PTM and two standard deviation methods were adopted to conduct the detection test.Results show that the developed method has higher efficiency and lower misjudgment rate.In these tests, three schemes indicate better test results with a lower flagging percentage relative to the given statistical expected value.The number of "flagging" data for three schemes are 33, 3, and 0, the flagging percentage are 0.076 %、0.007 %, and 0.000 %, respectively.Among three schemes, the scheme combining 1-minute sliding window with a 30-minute time interval is optimal with the features of the least "flagging" data, the lowest misjudgment rate, and a small computation burden for the computer.The continuous 30-day seconds' temperature and pressure data were tested with this method, and the results are satisfying.Besides, this method is also able to test artificially constructed incorrect data.This algorithm could be applied to check those meteorological data at stations that had a short history, are newly constructed or outlying, and have bad conditions and therefore is helpful to identify the emergent problems in the data collection phase and to improve the automation level of data quality check.

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    Forecast of electricity consumption in Nanjing based on meteorological factors in winter and summer
    Sheng-jie CHEN,Xin-ru TIAN,Ruan YAO,Lin JIANG
    2022, 38 (4):  127-135.  doi: 10.3969/j.issn.1673-503X.2022.04.015
    Abstract ( 155 )   HTML ( 1 )   PDF (1376KB) ( 170 )   Save

    Based on the hourly meteorological data, daily electricity consumption (EC), and hourly power load data from 2014 to 2016, the relationships between the variation of EC and meteorological factors in Nanjing were analyzed.The EC in Nanjing is featured with significant annual variation with two peaks in July-August and December-January and two valleys in April and October.Power load features a prominent 'weekend effect' in all four seasons.The diurnal variation of power load shows two peaks and two valleys.The two peak times are at 10:00 and 20:00.The two valley times vary with seasons.One is at 04:00 in both summer and winter, and the other is at 14:00 in winter and 18:00 in summer.The EC in Nanjing is closely related to the variation of weather conditions.The meteorological factors play various or even opposite roles on EC in different months.For example, in summer (autumn and winter), the greater the EC, the larger (smaller) is the daily temperature range in summer (autumn and winter).The heavier the EC, the higher (lower) is temperature in July-August (October-March).The influence of meteorological factors on the EC in summer is larger than in winter.The EC of Nanjing is mainly affected by temperature in winter, while is complicatedly affected by humidity and sunshine besides temperature in summer.The monthly forecast equation for the daily EC in winter and summer is set up by a stepwise regression method with different selected meteorological factors which show obvious inter-month variation.Forecasts of the EC in different months are conducted by considering different selected meteorological factors, providing an important reference for power dispatch.

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    Influence of the ultra-high voltage cross-regional transmission on air quality
    Xiao-hui MA,Jing XU,Zi-yin ZHANG,Zi-ming LI,Wei WEN
    2022, 38 (4):  136-144.  doi: 10.3969/j.issn.1673-503X.2022.04.016
    Abstract ( 120 )   HTML ( 0 )   PDF (2111KB) ( 119 )   Save

    According to the ultra-high voltage (UHV) transmission project of "Xilin Gol-Jinan", the change of pollutant concentration in Beijing, Hebei, and Tianjin was simulated and evaluated by the atmospheric chemical model WRF-Chem V3.7.The influence of UHV cross-regional transmission on air quality in the affected area was evaluated by setting different locations, heights, and emissions.Results show that the project has the largest impact on the atmospheric environment of Beijing in the case of southeast wind.According to the height of the virtual plant, the concentrations of PM2.5 at the height of 9 m, 27 m, 46 m, 64 m, 91 m, 130 m, 185 m, and 255 m were calculated.It is found that the greatest influence on the concentrations of PM2.5 is induced at the height of 91 m near the power plant.After long-distance transportation, the power plant has the greatest influence on the concentrations of PM2.5 below 45 m.The project of the power plant in "Xilin Go-Jinan" has little impact on the variation of pollutants concentration in Beijing.

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    Review
    Research progress on the scientific experiment of topographic cloud catalytic precipitation enhancement
    Zhuo-lin CHANG,Hao-ran ZHU,De-qin LI,Lei TIAN,Zhang-li DANG
    2022, 38 (4):  145-152.  doi: 10.3969/j.issn.1673-503X.2022.04.017
    Abstract ( 100 )   HTML ( 6 )   PDF (547KB) ( 30 )   Save

    As the most promising and feasible artificial influence cloud system, topographic clouds have been paid much attention by weather modification practitioners and researchers.In this paper, the historical process of field scientific experiments of topographic cloud catalytic precipitation enhancement at home and abroad were analyzed.The results obtained from the field scientific experiments are summarized.Several key scientific issues that need to be followed in the topographic cloud catalytic precipitation enhancement experiment are sorted out, including the analysis of the natural precipitation process of the topographic cloud, the distribution of supercooled water among the cloud in the topographic cloud system, and the evolution characteristics of the microphysical process of the mountain cloud system and its relationship with the mesoscale dynamic structure.The practice of carrying out topographic cloud field scientific experiments in Ningxia is introduced.The countermeasures and suggestions for accelerating the field scientific experiment of topographic cloud catalysis and improving the development and utilization of topographic cloud resources are put forward.It provides a way of thinking to solve the drought problem in the northwest region and promote the ecological environment protection and high-quality development of the Yellow River Basin.

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    Bulletins
    Research on the risk zoning of mountain torrent disasters induced by torrential rain in Liaoning province
    Shi-bo GENG,Zhe NIE,Ying WANG,Yuan FANG,Guang-liang XIAO,Hong-qiang LI,Yong-ming JI,Xian-long ZHU,Xiao-yu ZHOU
    2022, 38 (4):  153-160.  doi: 10.3969/j.issn.1673-503X.2022.04.018
    Abstract ( 131 )   HTML ( 5 )   PDF (2818KB) ( 141 )   Save

    Based on the natural disaster risk assessment theory, this paper uses the hourly precipitation observation data of 1639 automatic stations from 2005 to 2019, the basic geographic information with a resolution of 30 m of Liaoning province in 2017, and the data of mountain torrents to study the risk zoning of mountain torrent disasters induced by heavy rain.The results of risk zoning are compared with the historical flash floods.The results show that through the statistics of the correlation between mountain torrent disasters and precipitation, the 6-hour rainstorm is more suitable as the disaster-causing factor of mountain torrents in Liaoning province.Therefore, a 6-hour comprehensive utilization classification of rainstorm intensity and rainstorm frequency is constructed to finely evaluate the disaster risk of a rainstorm.Data such as elevation of mountain torrent gully, ditch-bed gradient, and river network density can effectively evaluate the environmental sensitivity of mountain torrent disasters.The two risk exposure indicators of population density and cultivated land ratio, as well as the disaster sensitivity coefficient, can generally evaluate the vulnerability of disaster-bearing bodies.Compared with the spatial and frequency distribution of the historical mountain torrent disasters, the high-incidence areas of mountain torrent disasters are consistent with the high-risk areas in this risk zoning.Based on the accurate risk zoning results of each mountain torrent gully, the risk zoning accuracy of mountain torrent disasters has been improved.It provides a valuable reference for the precise defense of induced flash flood disasters.

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    Comprehensive risk assessment and zoning of drought disasters in Tianshan Mountains, Xinjiang Uygur Autonomous Region
    Xiu-lan WU,Jing-li ZHANG,Xing-jie YU, Mayila Maimaitiaili
    2022, 38 (4):  161-167.  doi: 10.3969/j.issn.1673-503X.2022.04.019
    Abstract ( 151 )   HTML ( 4 )   PDF (2577KB) ( 89 )   Save

    Based on the four-factor theory of natural disaster risk, this study considers the natural and social-economic situation of the study area, establishes a conceptual framework and index system suitable for drought disaster risk in Tianshan Mountains, and carries out drought disaster risk assessment and zoning in the area combined with GIS technology.The results show that the areas with higher hazard factors are the Yili river valley and the northern slope of the Tianshan Mountains, while the eastern and western southern Xinjiang regions are less dangerous.The areas with high vulnerability to disaster-bearing bodies are the Yili river valley and Bole Prefecture, while Turpan, Hami, and Kizilsu Kirghiz Autonomous Prefecture belong to low vulnerability areas.The areas with high sensitivity to the disaster-pregnancy environment are mainly distributed in the line from Jinghe to Turpan on the northern slope of the Tianshan Mountains, the western Aksu area, the northern Bayingolin Mongol Autonomous Prefecture, and other places, Yili River valleys, northern Bazhou, northern Hami, and western mountainous areas in southern Xinjiang Uygur Autonomous Region are low-sensitive areas.The overall performance of disaster prevention and mitigation capacity is higher in the central and eastern regions than in the western regions.The overall drought risk in the Tianshan Mountains shows a trend of high in the middle and low at both ends.That is, the drought risk on the north and south sides of the Tianshan Mountains in the middle is higher than that in the western and eastern parts of southern Xinjiang Uygur Autonomous Region.The constructed evaluation model generally reflects the comprehensive risk level of drought disasters in the study area, which can provide a basis for disaster risk management, climate change response and drought resistance, and disaster reduction actions in the Tianshan grasslands of Xinjiang Uygur Autonomous Region.

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