Vol.25, NO.4, 2014

Display Method:
Evaluation of ASCAT Coastal Wind Product Using Nearshore Buoy Data
Xie Xiaoping, Wei Jiansu, Huang Liang
2014, 25(4): 445-453.

The new scatterometer advanced scatterometer (ASCAT) on board MetOp-A satellite provides surface wind speed and direction over global ocean. Providing accurate nearshore wind data from satellites is challenging because satellite data are unavailable very close to shore due to the contaminating effect of the land. Besides, land-sea breezes and shore topography produce small space scale and time-scale wind variations that can be smoothed by the satellite's space averaging and aliased by the satellite's twice-a-day sampling. The complexity of nearshore winds is one of the prime causes that the regions are so important. For example, over one-third of the total marine fish catch occurs within nearshore zone.The accuracy of ASCAT coastal wind product is determined through various comparisons with buoys. The nearshore buoys used in the comparisons locate in US West Coast and China Coast. As the time interval of US West Coast buoy wind is 10-minute interval and the spatial resolution of ASCAT wind product is 12.5 km, a scatterometer wind and a buoy wind measurement are considered to be collocated if the distance between the wind vector cell center and the buoy location is less than 12.5 km and if the acquisition time difference is less than 5 minutes in US West Coast. As the time interval of China Coast buoy wind is 1 hour, the acquisition time difference is less than 30 minutes in China Coast. The buoy winds at a given anemometer height are converted to 10 m neutral winds in order to enable a good comparison with the 10 m scatteromter winds. The time ranges of wind data used for comparison from US West Coast buoys and China Coast buoys are the whole year of 2012 and the first half year of 2012 individually.It shows that the accuracy of the wind speed of ASCAT product is high and the accuracy of the wind direction of ASCAT product is influenced by several factors, such as the distance from coast, wind speed and wind direction. The overall wind speed correlation coefficient between buoy data and ASCAT product is 0.94, and wind speed correlation coefficients between each buoy and ASCAT product are all above 0.9. The overall wind direction correlation coefficient between buoy and ASCAT product is 0.71, and the wind direction correlation coefficient between the nearest buoy and ASCAT product is only 0.55. Processing the satellite data by discarding observations recorded in light winds (below 3 m·s-1) can improve the accuracy of the ASCAT wind products by reducing the mean bias of wind direction from 21.89°to 11.83°, and the wind direction correlation coefficient increased from 0.71 to 0.84. In addition, the accuracy of the wind flow from land is low, while the accuracy of the wind flow from sea is higher. In most China nearshore regions, the applicability of ASCAT coastal wind product is good, but in Bohai Sea, the effect of topography on ASCAT coastal wind product is apparent.

Contrastive Study on Two Boundary Layer Parameterization Schemes Using TWP-ICE Experiment Data
Shen Xinyong, Huang Wenyan, Wang Weiguo, Guo Chunyan
2014, 25(4): 385-396.

TWP-ICE (Tropical Warm Pool International Cloud Experiment) is carried out at Darwin Station in northern Australia by Europe and the United States, observations can be used for numerical simulation study. High resolution WRF single column model is used to simulate a case during TWP-ICE with two boundary layer parameterization schemes (YSU and MYJ schemes). Simulation results of boundary layer structure, cloud and precipitation with these two boundary layer parameterization schemes are compared.The whole simulation process can be divided into two phases, which are monsoon active period and monsoon suppressed period. During monsoon active period, the boundary layer structure simulated by MYJ scheme is better than YSU scheme. Small turbulent exchange coefficient is simulated by YSU scheme leading to weak turbulent mixing and small heat flux in boundary layer during monsoon active period, which prevents the heat and moisture of surface from upward transporting. Therefore, the simulated potential temperature and vapor mixing ratio are significantly higher than observations at the bottom boundary layer, and the simulated vapor mixing ratio is lower than observation at the top of boundary layer. During monsoon suppressed period, great turbulent exchange coefficient is simulated by MYJ scheme at night, leading to strong turbulent mixing and large heat flux, and the simulated potential temperature and vapor mixing ratio variation with height are smaller than observations, so MYJ scheme cannot simulate the structure of nocturnal boundary layer well.Also, the simulation of cloud and precipitation is affected by the boundary layer parameterization schemes. During monsoon active period, weak turbulent mixing is simulated by YSU scheme, leading to the wet bias near the surface and dry bias above. As a result, YSU scheme simulates smaller cloud liquid water content and frozen water content, less cloud fraction and lower precipitation rate. During the same period, MYJ scheme simulates the boundary layer structure well, and can better simulate cloud and precipitation. During monsoon suppressed period, the cloud fraction and precipitation simulated with both schemes show no significant difference, both exceeding observations.

A Method of Improving Error Covariances in EnKF and Its Application to Data Assimilation
Liang Xiao, Zheng Xiaogu, Dai Yongjiu, Shi Chunxiang
2014, 25(4): 397-405.

In the ensemble Kalman filter (EnKF), the forecast error covariance matrix is estimated as the sampling covariance matrix of the forecast ensemble. However, previous studies suggest that the sampling error resulting from finite-size ensembles may make such estimations far from the true forecast error covariance, and finally degrade the performance of EnKF. A common way to address this problem is covariance inflation with a time-constant inflation factor. A time-dependent infiation approach on forecast error covariance matrix (i.e., MLE method) is developed based on the maximum likelihood estimation theory, so as to improve estimates of forecast error covariances. At Delgertsgot (DGS) Station in the Mongolian Plateau reference site, point observations of ground temperature and soil temperature at the depth of 10 cm are assimilated into the Common Land Model (CoLM) with a frequency of every 12 hours, using two assimilation algorithms (EnKF method and MLE method), in order to test the effectivity of MLE in practical assimilation. In this way, a soil temperature assimilation system is constructed on the point scale.Results indicate that MLE method performs better than EnKF method for ground temperature and soil temperatures at most depths (especially for soil temperatures at deeper depths). Moreover, considering differences between soil temperatures at shallower depths and those at deeper depths, different inflation factors are adopted to them when implementing MLE method. Compared to results of MLE using a single scalar inflation factor, it shows that multiple-factor inflation is able to alleviate the unreasonable inflation of soil temperatures at deeper depths and therefore get better assimilation results. In addition, the leaf area index (LAI) in the CoLM is updated dynamically by MODIS LAI products, and results derived using MODIS LAI are compared to those derived using LAI computed by experiential formula, so as to study the effect of the LAI accuracy on simulated and assimilated soil temperatures. It shows that using MODIS LAI can get better simulation of soil temperature at depths of 0 cm and 3 cm, as well as more accurate assimilation of soil temperature at most depths.The inflation factor is set to be variable in time, but constant in space. However, variables such as soil temperature and soil moisture behave quite differently at shallow surfaces and deep depths, and observations may be unevenly distributed in space in regional assimilation researches. Therefore, it is necessary to adopt different inflation factors to different variables or to the same variable at different locations. In the future, it is necessary to develop a time-and-space dependent inflation method and test its capability in real applications.

The Measurement Influence of Reflectivity Factor Caused by Scanning Mode from Phased Array Radar
Wu Chong, Liu Liping, Wang Xudong, Fan Hui, Liu Qi
2014, 25(4): 406-414.

The beam design of active phased array weather radar is flexible, and this variable beam width and multi-beam mode can satisfy the requirement of various tasks and get much higher temporal resolution than general weather radar. However, the performance of active phased array weather radar can be hardly kept consistent due to the massive digital T/R components, and any variations of antenna parameters between the beam direction and axis normal would be a huge challenge for radar calibration. The X-band phased-array weather radar (X-PAR) developed by State Key Laboratory of Severe Weather of Chinese Academy of Meteorological Sciences and Anhui Sun-create Electronic Co Ltd is tested for the first time from April to June in 2013. The X-PAR and C-band polarization weather radar (C-POL) are installed at the same site, so their observations provide reflectivity measure deviation information and correction scheme for radar debugging and calibration of antenna parameters.During the operation of X-PAR, 3 kinds of observing modes with different beam width are applied, each using different parameters in their radar equations of calibration algorithm. Observations from C-POL and X-PAR (fine mode) with single scanning beam, X-PAR (quick mode) with multi scanning beams and X-PAR (fine Mode) are contrasted in detail. In order to reduce the comparison bias, severe convection and attenuation should be avoided. Results from statistical analysis indicate that observations from each elevation of X-PAR (fine mode) is 3 dB higher than C-POL, the measurement deviation between quick mode and fine mode changes along 4° regularly, and is inconsistent in higher elevation. The deviation source of X-PAR (fine mode) and C-POL comes from differences between the antenna parameter and the effective cross section, and the fast mode is also influenced by beam pattern, gaining in different elevation. A correction scheme based on data statistics and fitting is proposed to decrease the bias within 1 dB. By the comparison through vertical structures, the dependability of the above method is testified, and the resolution of X-PAR is also higher than C-POL, which is significant for convective precipitation research.The actual performance of phased array antenna could not keep strictly consistent with theoretical value because of its complicated structure. The result suggests that antenna measurement and digital T/R test during the factory inspection and acceptance are very indispensable. In the future field experiments, a well-calibrated radar should be installed at the same position to correct the X-PAR observation bias.

Identification Method of Hail Weather Based on Fuzzy-logical Principle
Zhang Bingxiang, Li Guocui, Liu Liping, Li Zhe, Wang Congmei, Wang Liping
2014, 25(4): 415-426.

Based on previous researches and hail warning indexes in Hebei Province, five main radar identification indices for hail detection are given: Storm maximum reflectivity, storm maximum vertical integrated liquid water content, echo top, vertical integrated liquid (VIL) density and storm center height. The corresponding membership functions of each identification index in different seasons are also calculated. Identification method of hail on fuzzy-logical principles is established adopting the equal weight coefficient method.Based on radar mosaic data, disaster report of hail and route sounding data, 103 hail cases from 2008 to 2012 in North China are statistically analyzed and tested. The hitting rate of hail, the leading time and position of hail are given.The hitting rate, the false alarm rate and the critical success index of regional hail in North China are 73.9%, 36.4% and 51.9%, respectively, and all the scattered hail in Shijiazhuang can be identified. When the radar identification index is greater, the corresponding probability and the maximum diameter of hail is also bigger. The identification index is above 0.85 when the maximum diameter is more than 30 mm. On the spatial distribution, the area of identified storm and hail station is consistent. The hail station is nearby and around the corresponding storm monomer. The omission of hail occurs mostly in Zhangjiakou and Chengde, which may be caused by radar band range and regional characteristics. In contrast of single factor identification, the accuracy rate of comprehensive recognition is improved, and it also has a high degree of automation. The first time when the recognition criterion continuous is greater than the threshold value is always ahead of the epoch of hail, and the mean leading time is 30 minutes. By the recognition of hail in Shijiazhuang, the hitting rate, the false alarm rate and the critical success index of radar own recognition software are 100%, 78.2% and 21.8%, respectively, while the result of identification method on fuzzy-logical principles reaches 100%, 44.4% and 55.6%. Obviously, all hails are correctly identified, while the false alarm rate is significantly reduced, and the critical success index is increased.In summary, the automatic identification method based on fuzzy-logical principles is efficient and feasible, with more automatic algorithm. It can reduce the forecaster workload and has important practical guiding significance for short-term forecasting, nowcast warning and system development.

Applications of 3 Threshold Methods to the Lightning Channel Image Recognition
Yang Xinyi, Lü Weitao, Yang Jun, Zhang Ge, Ma Ying, Yao Wen, Li Qingyong
2014, 25(4): 427-435.

General digital cameras, camcorders as well as the BOYS camera specially developed for the lightning observation, are all important tools for lightning research. They are used to obtain the basic data for understanding geometry features of channels and main development processes of lightning. For a long time, extracting lightning channel coordinates from digital images is based on manual processing methods with the relatively low efficiency. With the development of the photoelectric techniques, more and more advanced optical devices are used in lightning observation, such as high-speed cameras and the Automatic Lightning Processing Feature Observation System (ALPS), and data obtained become much richer. How to automatically process these data and improve the efficiency of data extraction and analysis is an urgent need to be addressed.Considering the complexity of lightning discharges and various characteristics of the lightning channel, only one algorithm is not enough to obtain a satisfying recognition result in all situations. Therefore, 3 common threshold methods are applied jointly in the lightning channel recognition. Firstly, the impact of the uneven illumination is eliminated by subtracting the background and the contrast of the image is enhanced. Secondly, global adaptive threshold method, local adaptive threshold method or adaptive Canny operator method is applied for edge detection. And then, morphological and thinning processes are carried out to get the lightning channel represented by the continuous sequence of pixels. Considering different characteristics of the lightning channel digital image, selecting appropriate algorithm can ensure getting a clear edge information even including weak edges, guaranteeing a good recognition effect finally.Through experiments, it can be concluded that for the lightning channel with simple structure and relatively uniform brightness, all algorithms mentioned above can get a good recognition result, among which the global adaptive threshold method is simpler and more efficient. Local adaptive threshold method can calculate the threshold for different images universally. And for the low-contrast images with a smooth background, using adaptive Canny operator method can achieve a satisfactory recognition result.

Radiometric Characteristics of FY-3C Microwave Humidity and Temperature Sounder
Guo Yang, Lu Naimeng, Gu Songyan, He Jieying, Wang Zhenzhan
2014, 25(4): 436-444.

The microwave humidity sounder (MWHS) is a five channel microwave radiometer in the range of 150-191 GHz onboard FY-3A and FY-3B. FY-3A and FY-3B are successfully launched in 2008 and 2010, respectively. The next generation of MWHS is a microwave humidity and temperature sounder. This sensor is developed to fly on the third satellite of new generation polar orbit meteorological satellite of China (FY-3C) is launched in September 2013.The microwave humidity and temperature sounder has 15 channels in the range of 89-191 GHz. Eight temperature sounding channels with central frequency of 118.75 GHz oxygen gas line and five humidity sounding channels with central frequency of 183.31 GHz water vapor line. Two window channels center at 89 GHz and 150 GHz. 118 GHz channel is first used to detect atmosphere on current operational satellite. Channels in the oxygen band are at around 54 GHz used by AMSU-A (advanced microwave sounding unit-A) and ATMS (advanced technology microwave sounder). Channels in the next oxygen absorption band are at around 118.75 GHz, which can well detect atmosphere temperature in the lower troposphere. The temperature sounding channels around 118.75 GHz detect the atmosphere temperature from 900 hPa to 25 hPa. The microwave humidity and temperature sounder adds two humidity sounding channels compared with MWHS that can obtain fine vertical distribution structure of atmosphere humidity.In order to determine the radiometric performance and the on-orbit use of the microwave humidity and temperature sounder, an extensive test is performed before launch. The microwave humidity and temperature sounder is placed in a thermal-vacuum chamber where the cold and earth targets are installed at fixed position. The instrument temperature is controlled at 5℃, 15℃ and 25℃ which is expected in orbit. The temperature of earth target maintains from 95 K to 330 K and space target is controlled at 95 K. Temperatures of these whole targets are measured by PRT (platinum resistance thermometer) and the temperature measurement accuracy is better than 0.1 K. The test database include counts of internal blackbody, earth and cold targets are obtained by the new microwave radiometer and the temperature measured by PRT.The sounder is calibrated with the thermal-vacuum chamber test method, and test data are quantitatively analyzed. Results for noise equivalent differential temperatures of fifteen channels show that all fifteen channel measured sensitivities meet requirements of indicators. Noise equivalent differential temperatures of humidity channels are all below 0.5 K which are also at the same level of indicators from ATMS. The channels around 118.75 GHz except channel 2 are all below 1 K, and that means observations from these channels used for temperature retrieval are well. Because the narrow bandwidth of channel 2, the noise equivalent differential temperature of this channel is about 1.7 K that maybe affects retrieval precision. Correlations between all channels are independent. After correcting all biases, the calibration accuracy is well below 1.12 K. Calibration results of microwave humidity and temperature sounder are stability for each channel. The radiometric characteristic analysis of all channels provide useful reference for in-orbit application of the new microwave radiometer sounder on FY-3C.

The Annual Variation and Its Influencing Mechanism of Surface Roughness Length of Yuzhong in Semi-arid Areas
Yao Tong, Zhang Qiang, Yin Han
2014, 25(4): 454-462.

Based on data observed at the Semi-arid Climate and Environment Observatory of Lanzhou University (SACOL) from June 2006 to December 2010, temporal characteristics of aerodynamic roughness length over the natural vegetation surface of Yuzhong are analyzed. Annual change characteristics of roughness length and influencing mechanisms in the southeast and northwest are analyzed, taking the impact of terrain, vegetation, precipitation and thermal conditions into account, and the fitting relationships between normalized roughness and time are given. It shows that for heterogeneous underlying surface, the difference of aerodynamic roughness length in different wind directions caused by undulating terrain and vegetation difference is very significant. According to the prevailing wind direction, two wind directions which are southeast and northwest are selected. Both magnitude and changing trends of roughness length of two selected wind directions are remarkable different. The averaged roughness length in southeast is 0.015 m, whose magnitude is equal to the roughness length over sparsely vegetated underlying surface like deteriorated grassland, while the averaged roughness length in northwest is 0.123 m, whose magnitude is equal to the roughness length over farmland underlying surface. To eliminate effects of the inter-annual variation of roughness length, the normalized roughness length is injected into the discussion. The time-distributing characteristics in two wind directions vary considerably, which can be considered showing opposite trends. The annual changing trend of roughness length in southeast decreases first and then increases, while it increases first and then decreases in northwest. And due to differences in terrain and vegetation, influencing mechanisms of the time variation of roughness length in the two wind directions are different. The annual variation trend of normalized roughness is consistent with the annual variation of atmospheric stability and the roughness length has a certain relationship with atmospheric stability in southeast due to the stunted sparse vegetation. While the annual variation trend of roughness length is consistent with the annual variation of precipitation and the roughness length has a good relationship with precipitation in northwest due to the impact of vegetation, and the vegetation is mainly effected by the precipitation. The time parametric relationship between normalized roughness and time in two directions can be described by a set of sinusoidal functions, and the related coefficient can reach 0.49 and 0.82, respectively.

Observation of a Tornado in the Circulation Background of Northeast Cold Vortex
Wang Ning, Wang Tingting, Zhang Shuo, Mu Xiuxiang, Yang Xiufeng
2014, 25(4): 463-469.

The synoptic situation and Doppler radar data of the tornado process of Taobei District of Baicheng city in Jilin Province on 12 June 2012 (referred as "612" tornado) are analyzed, results are as follows.The tornado process occurrs in the southeast quadrant of the upper cold vortex, and in the convective unstable region of the north of the upper-level jet and the left of the low-level jet, also, in a relatively warm and humid environment of the surface systems. The caculation of atmospheric convective parameters shows that strong vertical wind shear (no less than 6.0×10-3 s-1) occurs at low layer (0-1 km) and relatively low lifting condensation level (no more than 1 km) exists in the tornado process, and the convective available potential energy is large before the tornado occurs. As for the radar echo characteristics, the height of the strong core (no less than 50 dBZ) is below 4 km in the tornado event, making it a low centroid convective system. The tornado occurs in the strong echo zones where a banded echo with an approximate nodular echo join together, and it gradually evolves into an "S" type with "V" type gap, and the echo of the strongest center value reaches 61 dBZ. Using the Doppler radar derived products and the radial velocity map, tornado vortex signature (TVS) could be detected, indicating that "612" tornado occurs in strong convective storm with smaller-scale TVS and larger vertical vorticity (about 3.65×10-2 s-1-3.83×10-2 s-1), having short duration. TVS could be identified in advance before the tornado, so it is very useful for estimation and prediction of tornados.

Determining Weight Coefficients of Meteorological Service Evaluation Criteria with AHP
Yan Minhui, Yao Xiuping, Wang Lei, Zhang Jinfeng
2014, 25(4): 470-475.

With the rapid development of social economy in China, the demand for meteorological service keeps growing, and the evaluation for meteorological service satisfaction becomes more important. The Analytic Hierarchy Process (AHP) method is used to evaluate the meteorological service satisfaction objectively, and constructing judgment matrix of good consistency is the key to use AHP.Two scales of AHP are used to construct judgment matrix of good consistency, and then weight coefficients can be calculated and the meteorological service can be evaluated. In the assessment system of meteorological service, using overall evaluation of meteorological services as the target layer, the first-grade and the second-grade evaluation indicators are composed. With the survey data of public satisfaction to meteorological services of 2010, 1-9 methods of scale and 0.618 methods of scale in AHP are applied to establish the judgment matrices. It is found that for the judgment matrix with less than 5 evaluation indicators, 1-9 methods of scale can be used; but for the judgment matrix with 5 evaluation indicators or more, 0.618 methods of scale should be used to calculate coefficients. The method is used in processing survey data of 2011, and coefficients for the first-grade and the second-grade evaluation indicators are calculated rapidly. The main value changes between two years are compared. Among weight coefficients for the first-grade, the value of meteorological information service contents increases while the value of meteorological knowledge propaganda and popularization decreases, which illustrates that the public pays more attention to the meteorological service contents and the meteorological department has achieved certain results in the meteorological knowledge propaganda and popularization. There is no obvious tendency change among values of the second-grade evaluation indicators. All judgment matrices pass the comparison matrix consistency tests, proving that the principle of judgment matrix construction is reasonable, effective and useful.

Effects of Different Soil Moistures on Photosynthetic Characteristics of Sunflower
Yun Wenli, Hou Qiong, Wang Haimei, Li Jianjun, Zhang Chao
2014, 25(4): 476-482.

The soil drought is one of key factors limiting photosynthesis in northwest areas of China. In order to understand the influence of drought stress on crop, the light response curves and several parameters of photosynthesis of sunflower are measured with Li-6400 Portable Photosynthesis System under three soil moisture grades: Arid soil, suitable soil moisture and wetter soil moisture (corresponding soil water contents are 40%-54.9%, 55%-69.9% and 70%-90%, respectively) in different development stages (two pairs of leaves-bud stage, bud stage-flowering stage, flowering stage-maturity stage). Results show that all coefficients of light response curve equations fitted using rectangular hyperbola model are above 0.99, meaning good compatibility between the model and the response process of photosynthesis of sunflower to light. The light response curves of sunflower growing under different soil moisture in different development stages show similar trends, the net photosynthetic rate (Pn) increases with photosynthetic active radiation rapidly at first and then slowly. For different development stages, changes of light response curves show a similar regulation with reduced soil moisture, but Pn of sunflower under wetter soil moisture is greater than that under suitable soil moisture and drought stress at the same photosynthetic active radiation, and differences are statistically significant with the photosynthetic active radiation increasing. Influences of soil moisture on the maximum net photosynthetic rate (Pmax) and apparent quantum efficiency are not synchronous. Pmax increases with soil moisture and apparent quantum efficiency under the condition of water stress in maximum. In the entire growth period of sunflower in the Hetao Irrigation District, light compensation point and light saturation point are 30.51-107.98 μmol·m-2·s-1 and 2260.8-3658.9 μmol·m-2·s-1, respectively. It shows that sunflower with high solar energy utilization efficiency is the typical sun plants, and is particularly fond of light. The effect of soil moisture content in light compensation point and light saturation point is different. The light saturation point increases with soil moisture, while light compensation point is the opposite. According to the variation of light compensation point and light saturation point, sunflower under suitable soil moisture not only expands the scope of the use of light but also is conducive to the accumulation of dry matter, sunflower under drought stress narrows the range of available light. The dark respiration rate (Rd) decreases gradually with plant growth, and decreases under drought stress in different development stages, which is conducive to reduce the influence of drought stress on dry matter accumulation of crops.

Applicability Analysis of Phenological Models in the Flowering Time Prediction of Ornamental Plants in Beijing Area
Zhang Aiying, Wang Huanjiong, Dai Junhu, Ding Deping
2014, 25(4): 483-492.

In recent years, with the tourism booming and the increasing demands for flower-appreciation, the prediction of flowering date of ornamentals plants becomes more and more important. For a long time, phenological models are widely used in agriculture field, but rarely applied in predicting flowering time of ornamental plants.Based on phenological data of three ornamentals plants (Prunus discoidea, Magnolia denudata and Amygdalus davidiana) in Beijing Area, corresponding meteorological data during the period of 1981-2012 at Haidian and Miyun meteorological stations, three phenological models (SW Model, UniChill Model and Statistical Model) for simulating the first flowering date and the full flowering date of the above three plants are developed. In the experimental process, the least square fitting is introduced in computing parameters, including linear least square fitting in Statistical Model and nonlinear least square fitting in SW Model and UniChill Model. Moreover, the simulating annealing approach is used to obtain the analytic solutions for SW Model and UniChill Model. Results show that SW Model performs well in simulating the first flowering date and the full flowering date of Prunus discoidea, the full flowering date of Magnolia denudata, and the first flowering date and the full flowering date of Amygdalus davidiana. Besides, SW Model is the most applicable model with the root mean square error (RMSE) of external verification between 1.93-3.58 days. UniChill Model ranks the second with the RMSE of 2.49-3.89 days, and Statistical Model has the largest uncertainty with the RMSE of 2.37-4.24 days. As far as prediction accuracy is concerned, SW Model also ranks the first, and for more than 85% of years, the prediction error is within 3 days.Above all, SW Model is recommended for predicting the flowering dates of the ornamental plants in Beijing Area. But Statistical Model based on daily average temperature, considering the comprehensive effect of light and moisture and plant physiological processes, may perform better. With the increasing urban heat island effect in Beijing Area, the deviation caused by urban heat island effect should be removed during the application of SW Model.

Climatology Calculation of Solar Energy Resource in Sichuan Province
Shen Yanbo, Zhang Shunqian, Guo Peng, Wang Xiangyun
2014, 25(4): 493-498.

Using SMARTS to calculate clear-sky global radiation, fully thinking of the weaken effects of the altitude and the atmosphere, in terms of water vapor in atmosphere, meteorological visibility and O3 content, a climatology universal calculation equation on solar energy resource is established, which is based on the percentage of sunshine. This method is different from the calculation of solar energy resources using extraterrestrial radiation. Taken Sichuan Province as an example, results show that this method not only has unambiguous physical meaning, but also decreases the error of the calculating result obviously. 7-station annual value relative error is less than 7%, with the highest of 6.26% for Panzhihua and the lowest of-0.67% for Luzhou, the error is significantly lower than that in previous studies of Sichuan. Contrast with results from extraterrestrial radiation, not only the quantity but also discreteness of relative error decreases by more than a half. For the distribution of solar energy resources in Sichuan, it is large in the east part and low in the west part. From the change of each month, solar energy resources in the western plateau is relatively stable, the minimum monthly solar radiation for a maximum of 62% at Litang Station; solar energy resource in the east basin is fluctuant, the minimum monthly radiant exposure is only accounted for 22% of the maximum value at Zigong Station. The climatology universal calculation equation on solar energy resource can better resolve the problem of using the same calculation equation in the region which has complex topography and climate, avoiding the boundary discontinuity, effectively which is brought by using partition method in the past, and it is useful for special regional situations of huge relative altitude between the east part and the west part of China with obvious changes of dry and wet. This statistical equation is suitable for the calculation of solar energy resources, first of all, each input parameter on average is needed. If the equation is used to calculate the total radiation exposure radiation in a special month or a special year, it will result in great error.

Risk Assessment and Temporal-spatial Distribution of Power Grid Lighting Disasters in Beijing
Gan Lu, Li Jin, Deng Changju, Zhang Deshan, Hu Haibo, Ye Kuan
2014, 25(4): 499-504.

Based on the daily power grid disaster data during 1996-2009 in Beijing, power grid disasters caused by the thunder and lighting (hereafter referred as power grid lighting disasters) are investigated. Results show that power grid lighting disasters present seasonal and daily variations in Beijing. Seasonal variation characteristic of power grid lighting disasters is mainly centralized from June to September, account for 88.4%. The highest appear in August, it can account for 32.9%. And daily variation characteristics analysis shows that from 1500 BT to 2100 BT is the high-incidence period. The analysis on spatial distribution of power grid lighting disasters indicates that there are more disasters in the north than those in the south. In terms of the same period of the daily thunderstorm data, economic and population characteristics, five indices are selected to evaluate the risk of power grid lighting disasters in Beijing, such as power grid lighting disaster probability, power grid lighting disaster frequency, power grid lighting disaster density, economic vulnerability module and life vulnerability module, respectively. And the different power grid lighting disaster evaluation indices are investigated. Four-grade classification methods are used to classify the evaluation indices in order to assess the risk of the power grid lighting disasters in Beijing. Firstly, the five indices are classified into four degrees with a given value as follow: The highest and the lowest degrees are 1.0 and 0.2, while the intermediate degrees are 0.8 and 0.5. Secondly, the comprehensive vulnerability evaluation index of power grid lighting disasters is obtained by adding the degree values of five indices. Then the comprehensive vulnerability evaluation index is also graded as four degrees, which are defined as the maximal damageable area, the high-damageable area, the medium damageable area and the lower damageable area. Finally, regional vulnerability zoning of the power grid lighting disasters are obtained by the average value of the power grid lighting disaster vulnerability evaluation indices. From the result of risk zoning, it can be concluded that the relatively higher power grid lighting disaster risk zones mainly locate in urban area of Beijing, while risks of mountain areas and their piedmont areas are relatively lower. Results of power grid lighting disaster vulnerability evaluation might be provided for the power grid lighting protection and disaster reduction proposal in Beijing.

ARQCS Starting Strategy and Its Relationship with Computing Resource Cost
Liu Yiming, Zhou Zijiang, Yuan Fang, Ruan Yuzhi, He Wenchun, Sun Chao, Liu Yuanyuan
2014, 25(4): 505-512.
AWS Observation Data Real-time Quality Control System (ARQCS) is an operational real-time meteorological data application system under IBM P570 high performance computing (HPC) Oracle 11g database platform. Functions including data decoding, database inserting, quality control (QC), storage management and share service are provided for more than 30000 AWS all over China. In 2009, when ARQCS is firstly built, QC methods including boundary value check, internal consistency check, time consistency check and spatial consistency check is applied to only 1 element of hourly precipitation. And the starting strategy is a static one, which start ARQCS at the 15th, 25th, 35th, 45th and 55th minute every hour. Later in 2010, QC methods of other important meteorological elements including air temperature, air pressure, humidity, wind direction and speed get to be applied in ARQCS. Meanwhile, the system computing logic is made more complex after 2 times of updating in 2011 and 2012. Now, it is planned to extend ARQCS to 158 elements in 11 classes totally, which need more calculating resources accordingly. To guarantee QC capability and service timeliness of ARQCS in a high level under limited computing resources, a series of schemes are designed and investigated. System log under IBM P570 HPC Oracle database environment from 1st April to 30th Sep in 2012 is used to analyze ARQCS performance. It is found that the database entry rate (ER) of AWS data exhibits a trapezoid shaped distribution, and variance of ER is large from the 5th to the 20th minute in one hour, which means accumulated ER at the 15th minute is unstable and a low accumulated ER may be got if ARQCS starts at this time. It also indicates that an accumulated ER of 95% is very possible (84.89%) to get before the 20th minute, and accumulated ER is increased by only 1.36% after the 20th minute in average. So a new dynamic starting strategy is employed, that ARQCS starts for the first time when accumulated ER gets more than 95% or until the 20th minute, and starts for the second time at the 55th minute. With this approach, the possibility for accumulated ER over 95% at the 1st QC starting is increased by 29% (from 66.38% to 95.83%). And the average 1st QC starting time is 20.6 seconds before the 15th minute in original static starting strategy. Also, less number of starts from 5 to 2 decrease the CPU time cost from 26.5 minutes to 10.2 minutes per hour, which means saving 391 minutes CPU time per day. It is concluded that the dynamic starting strategy is effective for ARQCS starting adaptively and ensures system robustness.