应用气象学报

2016, 27(4)

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Abstract:

Meteorological Disaster Index and Risk Assessment of Frost Injury During Apple Florescence

Qu Zhenjiang, Zhou Guangsheng, Wei Qinping

2016, 27(4): 385-395. DOI: 10.11898/1001-7313.20160401

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Abstract:
Frost injury during the florescence is one of the most serious meteorological disasters affecting the production and quality of apple. In temperate regions, effects of frost damage on deciduous fruit trees during florescence exceed effects of winter freeze. The risk of frost injury in the apple florescence depends on the developmental stage and disaster-causing factors. The minimum temperatures or frost days are usually adopted as disaster-causing factors, but single index cannot reflect combined effects of meteorological factors on frost injury.The disaster exposure index and the dominant disaster-causing factors are determined based on the geographical distribution of frost injury during the apple florescence, meteorological data, together with the maximum entropy (MaxEnt) model and ArcGIS spatial analysis technique. An assessment is carried out on the main cultivated area using meteorological data from 2084 meteorological stations during 1981-2013. Results indicate that the frost injury occurs when the effective accumulated temperature (daily maximum air temperature is no less than 6℃) reaches 420-550℃·d before flower-beginning. The dominant disaster-causing factors and their thresholds to the frost injury in influence descending order are listed as follows: The maximum diurnal range of temperature (no less than 22℃), the extreme minimum temperature (no more than-2℃), the precipitation (no more than 5 mm) and the accumulated daily minimum temperature below 0℃ (no more than-14℃·d) in processes of strong cold air. The higher risk areas include northern Xinjiang, western and northern Loess Plateau, especially the plateau area of the western Sichuan, while risks in areas around the Bohai Bay and the Old Course of the Yellow River are lower. The distribution of risk areas are related with the apple phenophase and routes of cold air. The disaster affected degree also varies according to different cultivars.

Early-warning of Low-temperature Disaster Levels on Double-cropping Rice in Southern China Based on Fisher's Discriminant

Wu Li, Huo Zhiguo, Yang Jianying, Xiao Jingjing, Zhang Lei, Yu Caixia, Zhang Guixiang

2016, 27(4): 396-406. DOI: 10.11898/1001-7313.20160402

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Abstract:
Rice is the main food crop in southern China. So far, low-temperature disaster has become one of the main agricultural meteorological disasters which influence the production of rice. Spring low-temperature disaster of early rice and autumn cold dew wind of late rice are the main low-temperature disasters in double-cropping rice growing areas in southern China. However, the frequency of low-temperature disaster has decreased in some regions while increased in other regions, and the damage to the rice yield even increases under the background of global warming. In order to reduce the yield loss and build comprehensive forecasting and early-warning technical architecture, the low-temperature disaster is deeply looked into. Using the software SPSS and methods of factor puffing, correlation analysis and Fisher's discriminant, a series of data are analyzed, including daily meteorological data, rice growing period data from 708 weather stations located in the planting region of double-cropping rice in the south during 1961-2010, together with meteorological industry standards. An early-warning model is established to forecast low-temperature disasters for spring rice in high risk areas (area Ⅰ) 10 days in advance, and for autumn rice in both high risk areas (areaⅠ) and main disaster areas (area Ⅱ) 5 days in advance.Based on data during 1961-2009, the model constructed is used for hindcast, and data of 2010 is used for evaluation. The average basically consistent accuracy of the early-warning model in area Ⅰ of early rice, late japonica rice and late indica rice is 90.5%, 74.2% and 80.3%, respectively. As for area Ⅱ of late japonica rice and late indica rice, the average basically consistent accuracy of the early-warning model is 89.4% and 80.3%, respectively. On the whole, the average basically consistent accuracy of the early-warning model is above 80%, and the error is within one level, showing good efficiency.

Methods for Yield Forecast Based on Crop Model with Incomplete Weather Observations

Qin Pengcheng, Liu Min, Wan Suqin, Su Rongrui

2016, 27(4): 407-416. DOI: 10.11898/1001-7313.20160403

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Abstract:
Crop simulation models are important tools for identifying climate-crop relationships as well as for yield prediction, while complete daily weather data for whole growing season is required for running crop model, which cannot be satisfied only by weather observations in the real-time operation. Formal studies have generally used averages of daily weather calculated from the historical weather database as replacement, which may destroy its temporal distribution, and thus introduce another source of bias. Aiming at preparing meteorological data after the forecasting day that required by the crop model in the real-time yield forecasting operation, the climate analogues methodology is proposed, which can generate new climate series for the desired period from history observations that with similar climates across space and time, based on a distance metric such as Euclidean, and the new proposed methodology is tested with the CERES-Rice model for its predictability and error distribution, comparing with a general arithmetic mean method. Results show that rice yield is sensitivity to meteorological conditions during two months before maturity, yield forecasting with CERES-Rice model driven by weather data at two-month lead-time leads to a more than 60% prediction probability with an error no more than 5%, and such predictability increases steadily with weather observations updated, showing considerable potential for operational application. Considering there is no priori knowledge on the climate trend for the remainder growing season, using a multi-year mean weather data instead, there is a 60% prediction probability when forecasted at two months before maturity and a 70% prediction probability one month before, however, obvious systematic overestimate is observed, and there exist systematic errors among different decades using 30-year means due to the climate trend under global warning, by using the latest 10-year or 5-year means, the decadal systematic errors decrease while the predictability increase for the poor ability in representing climate variability among years. Finally, using the historical analogue approach that generating downscaled daily weather data from historical observations, the prediction probabilities increase slightly, while the systematic errors reduce considerably compared with that of using the general arithmetic average approach, in addition, the historical analogues approach allows to include climate trend for the upcoming growing season, and by doing so, the predictability increases to more than 80% at two month in advance, much higher than that with multi-year mean. It is concluded that the analogue approach has great potential in bridging the gap between crop model and climate forecasting.

Experimental Study on Crop Coefficient of Spring Maize in Hetao Irrigation District of Inner Mongolia

Hou Qiong, Wang Haimei, Yun Wenli, Li Jianjun

2016, 27(4): 417-425. DOI: 10.11898/1001-7313.20160404

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Abstract:
The crop coefficient curve is an important parameter for estimating the change of water consumption in growing season, and it plays an important role in water management, such as the simulation of evapotranspiration, irrigation forecasting and irrigation decision-making. Previous crop coefficient studies mainly concentrate on the average value of growth period, while rarely focus on daily changes. A crop coefficient simulation method is in need to improve spring maze irrigation forecasting business in Hetao area. Based on the field moisture test data and meteorological station historical observations, the crop coefficient of spring maize is calculated with water balance method, and a dynamic simulation equation is established considering the variation during growing season. It's then evaluated using results of the United Nations Food and Agriculture Organization (FAO) piecewise linear method, and daily rolling estimation of crop evapotranspiration is achieved. At the same time, the leaf area correction method is put forward to estimate the soil moisture content under the water stress, which can provide basis for the development of maize irrigation forecast. Results show that the crop coefficient of spring maize can be described by three curves of the development process, and the change trend of crop coefficient has nothing to do with the output level, but the variation range increases with the increase of output. Considering heat index can reduce the influence of geographical factors on crop coefficient, the simulation equation of maize coefficient are established based on relative accumulative temperature as time variable after emergence, and the decision coefficient are all above 0.92. The maximum (1.30-1.48) and average (0.831-0.919) maize coefficients of each site are calculated by simulation, results are basically the same as the 3 typical values and interval values got by FAO segmentation method, and the range of averaged relative error during growth period is 3.4%-7.2%. Through the analysis, it is concluded that K_c and relative leaf area index are better described by exponential function, and the calculation method of the standard leaf area index is proposed, which can calculate the crop coefficient in any production condition. The simulated soil moisture is consistent with the measured value with average relative error of 6.3%, and less than 15% for 95.8% circumstance, indicating good application prospects. As the soil moisture supply below 1 m is not considered yet, the model should be improved in the future to explore the calculation method of the lower layer water supply.

The Optimal Training Period Scheme of MOS Temperature Forecast

Wu Qishu, Han Mei, Guo Hong, Su Tonghua

2016, 27(4): 426-434. DOI: 10.11898/1001-7313.20160405

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Abstract:
Based on air temperature from ECMWF data, three groups of training period schemes that include original schemes, improved schemes and application schemes are designed to test and compare results of daily maximum and minimum temperature of national stations in Fujian Province twice per day from 2014 to 2015. For the quasi-symmetrical mixed running training period (QSRTP) method, several days of current year before forecasting day and equal numbers of days in last year after are adopted separately to compose an initial 1-year or multi-year dataset. When using multiple-year data, lengths of the optimal training period every year are different or the same in each scheme. From three original schemes, it is found that the methods of QSRTP are much better than other running training period methods and traditional fixed period classification, and the number of optimal training day is more stable. The QSRTP with 2-year data shows better performance than that with 1-year data for comparison of improvement schemes, and different training period lengths lead to better performance in 2-year evaluation schemes. Considering model version updating and the continuity of weather, lengths of the optimal training period before the first year are slightly longer than that in the second year. Similar to the traditional method, the optimal training period of original and improved schemes are obtained after verification rather than before forecast. Three application schemes with different terms of evaluation are designed to test the stability, the usability and seasonal patterns of the optimal training period. Based on 1-year evaluation, total samples of the training period are stable with the best forecasting score. In terms of the monthly evaluation, the best period has no significant patterns with a relatively low score. For 10-day evaluation, the best period varies greatly, but when the forecasting time becomes shorter, the forecast quality becomes better. When the weather changes suddenly, the optimal training days will be quite different. Hindcasting experiment of 2015 suggests that the MOS forecast for daily maximum and minimum temperature using the optimal training period of last year has a much higher score than the original ECMWF products, it is better than the subjective forecast, and the forecast absolute deviation is significantly reduced. With the accumulation of data in the future, the forecast quality would be improved greatly, indicating that the method of multi-year QSRTP has an important application prospect on the daily operation.

Assessing Vegetation Response to Meteorological Drought in Tibet Autonomous Region Using Vegetation Condition Index

Wang Yuanyuan, Zhaxi Yangzong

2016, 27(4): 435-444. DOI: 10.11898/1001-7313.20160406

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Abstract:
Tibetan plateau, as the third pole, is influenced by global climate change deeply. According to the 5th IPCC assessment report, temperature on the Tibetan Plateau is rising quickly, posing serious risks to agriculture, hydrological systems and so on. Drought is becoming a main hazard to agricultural production in Tibet, and therefore it's very essential to apply effective drought monitoring techniques in agriculture management in response to climate change. Although meteorological drought indices (such as standard precipitation index, SPI) are useful in drought measurement, they often have limited spatial resolution since they rely on in situ data. Satellites-based drought indices (such as vegetation condition index, VCI) can provide drought information over large areas at a higher spatial resolution, but in a different way from station-based meteorological drought indices. It has been recognized that the existing satellite-based drought indices are more associated with agricultural drought (e.g., vegetation health, crop yield, soil moisture, etc.), and the response of vegetation to meteorological drought (precipitation deficits) varies depending on the seasonal timing, land cover type, climate, soil properties, irrigation, and other factors.Correlation coefficients between VCI and SPI at different time scales for 30 meteorological stations in Tibet during 2000-2014 are calculated. First, the time scale of SPI that is most correlated with VCI is determined. Then, climatic and environmental factors are investigated to explain the spatial variation of this correlation. With considerations of inter-correlations among environmental factors, two preconditions are recognized as favorable for a strong correlation between VCI and SPI, and regions where vegetation responds to meteorological drought obviously are identified. Results are as follows. Firstly, correlations between VCI and SPI are time scale dependent, and the lag between the occurrence of precipitation and the vegetation response is about 12 weeks in Tibet. Secondly, there are obvious spatial variations in terms of the vegetation response to meteorological drought. Insensitive vegetation response is often associated with extremely dry or wet climate, forested land cover, low annual NDVI value, low multi-annual NDVI fluctuations, and water sources other than precipitation (e.g., snowmelt, irrigation). Thirdly, according to the climatic and environmental factors, vegetation in the middle southern part of Tibet responds to meteorological drought obviously, including Lhasa region, the northern part of Shannan, the eastern part of Rikaze, the middle and southwestern part of Naqu, and the southeastern part of Ali.

Characteristics of Tropopause Height over China During East Asian Summer Monsoon

Jiang Xiaoling, Wang Donghai, Yin Jinfang, Lin Wenshi

2016, 27(4): 445-453. DOI: 10.11898/1001-7313.20160407

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Abstract:
Tropopause, as a transition layer between the troposphere and stratosphere, plays an important role on the regional and global climate and weather. Influenced by the Tibetan Plateau and monsoon, tropopause over China can even affect the global weather and climate, especially by changing aerosol distribution. Focusing on characteristics of tropopause height, 3 different sub-regions are defined in China during the East Asian summer monsoon, using high vertical resolution sounding data from year 2008 to 2014 collected by the network of L-band sounder. Results are shown as follows. Tropopause height increases with decreasing latitudes. The region with high tropopause moves northward with the maximum locating over the south of the Tibetan Plateau and the region to the southeast of the Plateau after the summer monsoon breaking. The region with large southward and eastward gradient of tropopause height moves from 30°-40°N to 40°-50°N after the summer monsoon break. There is little latitudinal difference in tropopause height over all the three sub-regions, indicating that the topography has little influence. However, tropopause height changes greatly after summer monsoon breaking: In northeast China and central-east China, the tropopause increases and in south China it slightly decreases. Influenced by the surface heat and vertical velocity, the temperature increases in the troposphere and decreases in the troposphere-stratosphere transition layer, which results in an increasing vertical temperature gradient after the summer monsoon breaking over the northeast and central-east China, resulting in higher tropopause. For northeast China, the temperature profile shows double peaks before the monsoon breaking, which is easy to form double tropopauses with a low first tropopause. In south China the temperature increases through the whole atmosphere after the summer monsoon breaking, generating slightly decreased tropopause. Limited by the coarse temporal resolution, more temporal characteristics such as daily changes cannot be studied. Further research should combine various datasets such as satellite to get a comprehensive analysis on the tropopause behavior over the mainland China.

The Relationship Between the Autumn Drought in the Eastern Part of Northwest China and the Summer Asian-Pacific Oscillation

Liu Xiaoyun, Wang Jingsong, Yang Jinhu, Tian Qingming

2016, 27(4): 454-462. DOI: 10.11898/1001-7313.20160408

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Abstract:
The eastern of Northwest China is recognized universally as a sensitive area of climate change and ecologically fragile region. Being adjacent to the Tibetan Plateau, effects of the Plateau terrain on atmospheric heating leads to thermal difference between the atmosphere above the Tibet Plateau and this area. The Asian-Pacific oscillation (APO) is defined as a zonal seesaw of the tropospheric temperature in the mid latitudes of the Asian-Pacific region. When the troposphere is cooling in mid-latitudes of the Asian continent, it is warming in mid-latitudes of the central and eastern North Pacific, and vice versa. In essence, the Tibetan Plateau thermal effects arouse likeness APO large scale teleconnection pattern. Used as an index of the thermal contrast between Asia and the North Pacific, it provides a new way to explore the Asian atmospheric circulations and climate change.Based the NCEP/NCAR reanalysis data, the monthly precipitation and temperature from 589 stations of China during 1961-2010, the relationship between the summer APO and the following autumn drought in China is examined statistically. Results show there are a significantly positive correlation between the APO index and the following autumn in the eastern part of Northwest China. A positive phase of summer APO, characterized by two high ridges strengthened located near the Ural Mountains and east of the Okhotsk Sea, respectively, and a trough deepened between the Balkhash and the Baykal. A positive phase of summer APO associated with east Asian subtropical westerly jet stream turns to be weakened and northward. These changes provide favoring conditions for enhanced wet in the eastern part of Northwest China. The situation is reversed in the negative phase of summer APO, leading to drought in this region. The east wind strengthening at the bottom of the northeastern Pacific anticyclone and the moisture transport that roots in the Arabian Sea and the Bay of Bengal strengthening has very important contribution to the variability of the atmospheric water vapor resource in the eastern part of Northwest China. Moreover, the positive phase of summer APO is followed by increased ascending vertical velocity in autumn especially during the 54th-56th pentad.Specifically, the anomalous signal of the summer APO can persist until the following autumn, accompanying with continuous high correlations between the summer APO index and that in the following autumn. Therefore, the summer APO variation provides a potential valuable signal for predicting the autumn wet/drought in the eastern part of Northwest China.

An Assessment of the Tropical Pacific Latent Heat Flux Simulated by BCC_CSM 1.1(m)

Tang Huiqing, Zeng Gang, Huang Yue

2016, 27(4): 463-472. DOI: 10.11898/1001-7313.20160409

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Abstract:
The simulated tropical Pacific annual mean latent heat flux by BCC_CSM1.1(m) as well as 14 other CMIP5 models are analyzed and compared with observations from objectively analyzed air-sea fluxes (OAFlux). Some possible causes for annual latent heat flux trend biases in BCC_CSM1.1(m) are investigated.Biases of annual average latent heat flux between observations and BCC_CSM1.1(m) in the tropical ocean and west boundary current area is larger, while in mid-high latitudes is smaller. Annual average latent heat flux is larger than observations, and annual mean latent heat flux variance is smaller than observations. The tropical Pacific annual and zonal mean latent heat flux is quite different in different latitudes. Simulation results of BCC_CSM1.1(m) near 10°N and 8°S have relatively large biases, while the biases are rather small in equator. So BCC_CSM1.1(m) needs to focus on improving the simulation of Pacific latent heat flux near 10° in each hemisphere.Among 15 CMIP5 models, NorESM1_M gives the best simulation result, and the root mean square error is the smallest, while the root mean square error of GISS_E2_R result is the largest. The root mean square error of BCC_CSM1.1(m) result is 22.9 W·m^-2, ranking eighth among all models, which indicates a moderate simulating ability.The trend of the tropical Pacific annual mean latent heat flux in BCC_CSM1.1(m) has biases comparing with the observation, and the cause can be concluded in 3 aspects. First, the local contribution horizontal wind speed to latent heat flux trend is underestimated in BCC_CSM1.1(m). Second, there are large biases for simulated non-local contribution of horizontal wind speed in BCC_CSM1.1(m). Finally, the response to the global warming of horizontal wind speed in BCC_CSM1.1(m) has large biases as well. Therefore, the main cause for trend biases of tropical Pacific annual mean latent heat flux is the large simulation deviation of horizontal wind speed in BCC_CSM1.1(m), and therefore the model needs improving in horizontal wind speed simulation.

Characteristics of Water Vapor Content in Southwest China and Its Association with the South Asia High in Summer

Chen Dan, Zhou Changyan, Deng Mengyu

2016, 27(4): 473-479. DOI: 10.11898/1001-7313.20160410

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Abstract:

Based on ERA-interim high resolution data by ECMWF from 1979 to 2014, in terms of EOF decomposition, wavelet transform, anomaly composite and correlation analysis, spatial and temporal variations of atmospheric water vapor content in Southwest China and its relationship with the South Asia High in summer are discussed. Results indicate that the spatial distribution morphology of summer atmospheric water vapor content in Southwest basically has the same anomaly in whole type, north-south oscillation type and east-west oscillation type, and the explained variance of EOF1 is much higher than those of EOF2 and EOF3, which means the same anomaly in whole type (EOF1) can reflect the main distribution characteristic of water vapor content in Southwest China in summer. The summer atmospheric water vapor content in Southwest China shows obvious inter-annual variation characteristics, and there is obviously corresponding relationship between summer atmospheric water vapor content in Southwest China and the South Asia High. More (less) water vapor content is accompanied with stronger (weaker) South Asia High. Furthermore, there are significant positive correlations between the water vapor content in Southwest China and the South Asia High intensity index, the area index and the eastward index, which reach 0.64, 0.62 and 0.59, respectively. In addition, when the South Asia High strengthens, the subtropical high over the West Pacific extends to west, and the southwest airflow of the lower troposphere is enhanced, which is favorable for the water vapor transport to the south of China from the ocean. Meanwhile, the South Asia High enhances the upward motion in Southwest China, causing more water vapor content. On one hand, the westward extension and the strengthening of subtropical high guides the Western Pacific water vapor transport to the southwest of China; on the other hand, due to blocking effects of the subtropical high, the water vapor which transported from the South China Sea leads to increased atmospheric water vapor content in Southwest China. When the South Asia high is weakened, the situation is the opposite.

Evaluation Model of Meteorological Disaster Loss with Normalized Indices Based on Projection Pursuit Regression

Li Zuoyong, Xu Yuanwei, Wang Jiayang, Liu Yun

2016, 27(4): 480-487. DOI: 10.11898/1001-7313.20160411

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Abstract:
Scientific and reasonable evaluation of meteorological disaster loss has important significance for decisions of disaster reduction and relief. A universal and general model of projection pursuit regression (PPR) is proposed with the matrix for the evaluations of different meteorological disaster systems, on the basis of gauge transformation for disaster loss indexes. Because of the "equivalence" of each normalized index, only models of NV-PPR (2) and NV-PPR (3) are necessary for the normalized index values (NV) of 2 indices and 3 indices of meteorological disaster system. Furthermore, the NV-PPR modeling for over 3 indexes of meteorological disaster system could be represented by the combinations of some NV-PPR (2) and (or) NV-PPR (3) models. Models are applied to the evaluations of typhoon disaster loss in Guangdong and 2 lightning disasters loss in Chongqing, and evaluation results of this method are compared with those of other methods. It shows that the evaluation model (NV-PPR) of meteorological disaster loss with gauged transformation based on projection pursuit regression is independent of index numbers, with features of simplicity and utility. The model can also be extended and apply to other disaster loss assessment systems.

Climatological Characteristics and Spatio-temporal Correspondence of Lightning and Precipitation over the Tibetan Plateau

Qi Pengcheng, Zheng Dong, Zhang Yijun, Gao Lina

2016, 27(4): 488-497. DOI: 10.11898/1001-7313.20160412

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Abstract:
Based on the analysis of TRMM data from 1998 to 2013, climatological characteristics of lightning activities, precipitation and their relationships over the Tibetan Plateau are investigated. The largest densities of lightning are over the central and northeast parts of the Plateau, with the maximum lightning density over the central Plateau reaching 6.2 fl·km^-2·a^-1. Nevertheless, the strongest precipitation occurs over the southeast part of the Plateau where the value is above 800 mm·a^-1. Both the lightning activity and precipition move westward in May and then retreat in September over the most parts of the Plateau, while the strong lightning activity over the northeast of the Plateau barely moves. Unlike the lightning activity, the precipitation shows a cascade change from southeast to northwest. In chosen specified areas, the lightning and precipitation show parallel changes, including their active periods from May to September and single peak patterns. Except for the west and southeast parts of the Plateau, the peak months of lightning and precipitation in other areas are the same. The geographic distribtuion of the rainfall per flash (RPF) is then investigated and exhibits that the minimum RPF appears over the central and west parts of the Plateau, ranging from 5×10⁷ to 7×10⁷ kg·fl^-1. The maximum RPF reaches above 1×10⁹ kg·fl^-1 over the area along the Himalayas, stretching to the southeast part of the Plateau, and over the northern Plateau near the Kunlun Mountains. Combined with the analysis of TRMM precipitation features (PFs), it is exposed that the lightning can be the proxy of deep convective activity over the plateau, while RPF can effectively represent the percentage of deep convective systems in all precipitation systems. In this way, the mid-west and northeast parts of the Plateau account for the largest percentage of deep convective activities in the whole precipitation system, while the southeast parts of the Plateau account for the smallest percentage, indicating that most of the precipitation over the southeast parts of the Plateau might be contributed by warm clouds.

Simulation on the Stroke Protection Distance of Tall Buildings to Surrounding Buildings

Tan Yongbo, Chen Zhilu, Zhang Dongdong, Shi Zheng, Guo Xiufeng

2016, 27(4): 498-505. DOI: 10.11898/1001-7313.20160413

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Abstract:
Lightning is a kind of strong discharge phenomena in the atmosphere. It has a great impact on human living space especially cloud-to-ground lightning, making it widely concerned. Through a large number of lightning observation, the tip and the corner of tall buildings are usually striken rather than the relative low buildings and ground. The tall building can make surrounding atmospheric electric field produce a strong distortion effect, so that the tip and the corner of tall buildings trigger upward leader easier, connected with the downward leader. Numerous studies on single building attachment process are carried out, while in real urban environment, buildings are not isolated, and therefore, shielding effects between multiple buildings and the relationship between stroke protection distance of building and the related characteristic parameters of buildings are discussed.On the basis of the existing parameterization scheme of leader attachment process, a region near the ground is selected as study area, by changing spatial forms of lightning while keeping the other basic parameters constant. A series of lightning simulation experiment is conducted in the context of distribution of the same buildings. Results show that under the distribution of multiple buildings, the tall building is more intense in the environmental electric field distortion than the low building, upward leader is easier to be triggered. Meanwhile, the tall building has a shielding effect to the low building, and has a critical value of protection distance of the effect of low building, when the distance between tall building and low building is under the critical, the low building is safe from stroke, otherwise, the rate of low building being stroke has a upward trend. In addition, the result comes out that the critical value of protection distance and the height of tall building is positively correlated, and the height of low building is negatively correlated. Finally, the relationship between the critical value of protection distance and the building height is fitted, providing a reference value for lightning protection designing work.

The Correction of Forecast Wind Speed in a Wind Farm Based on Partitioning of the High Correlation of Wind Speed

Shi Lan, Xu Lina, Hao Yuzhu

2016, 27(4): 506-512. DOI: 10.11898/1001-7313.20160414

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Abstract:
In order to improve precision and accuracy of wind speed forecast and wind power prediction, and taking unstable factors of observations on the wind turbines into account, a refined and partitioned correction model is established for improving the quality of wind speed forecast on turbine hub height. The wind farm A, which is located in the middle of Inner Mongolia of China, is selected as the target area. Fine analysis on gradient observation, the terrain and the layout of the wind turbines is carried out, and the hourly quality-controlled wind data on the wind tower and the turbine hub height are comprehensive compared, considering the spatial-temporal correlation, deviation of wind tower and turbine wind speed, seasonal influences and wind directions (NW, SW, NE, SE). Wind turbine groups are partitioned by wind speed subsequently in wind farm A. Characteristics of wind speed of wind tower and groups that are affected by turbulence, wake flow and wake superposition are studied. Using the method of Kalman filter, through direct (from numerical model to turbine groups directly) and indirect (from numerical model to the wind tower firstly, and then to the turbine groups) correction schemes, wind speed correction is done, respectively.Results show that the division of wind turbine groups in every wind speed is high correlative. The indirect correction of turbine groups using the gradient observation of the wind tower can correct wind speed forecast more effectively than model forecast and direct correction. Correlation (R) and the absolute value of error (E) between corrected wind speed of indirect correction and observed wind speed are improved by different degrees in each wind turbine group. R increases from 0.18-0.72 to 0.67-0.91, and E is reduced from 1.6-2.9 m·s^-1 to 1.0-1.5 m·s^-1 after indirect correction, compared to R increasing to 0.39-0.87 and E decreasing to 1.2-2.1 m·s^-1 after direct correction. In addition, the indirect correction scheme plays a very good role in controlling the E of the low velocity section ( < 3 m·s^-1) and the high speed section (>9 m·s^-1). The indirect correction scheme performs better when the difference between forecast wind speed and observed wind speed are relatively larger. Therefore, this method has is a good reference for improving prediction precision and accuracy, and it should be tested and spread to more wind farms in the service.

Vol.27, NO.4, 2016