Vol.18, NO.4, 2007

Display Method:
Correction to the Localization of NOAA AVHRR with DEM
Zheng Zhaojun, Liu Ruixia, Liu Yujie
2007, 18(4): 417-426.
Errors can often be found in the 51 longitude and latitude location information of each scan line in the NOAA AVHRR data which are preprocessed without taking the Digital Elevation Model (DEM) into consideration, and are dramatically huge at the points with high altitude and far from the nadir.The simulation indicates that the horizontal location bias will be increased with the increasing of the zenith angle.This bias caused by the location error can reach the kilometer order level and is mainly displayed in the longitude direction, with small weight of the latitude direction.It is necessary to correct this deviation.Even to the users who project first and then re-correct with the surface control-point, orientation correction can reduce the difficulty in re-correction and improve the orientation precise.A quick and simple method is developed by which localization information of 2048 satellite observation points in a scan line can be corrected with DEM and that of 51 original localization points in AVHRR L1B data. Firstly, latitudes and longitudes of 2048 satellite observation points are figured out using 51 original localization points' information by equidistance interpolation of one variable in an entire siding-to-siding block.Simultaneously the altitude of each point is looked up from DEM data.Secondly, one points is located exactly and the other is not revised.The horizontal location bias (i.e., spherical surface radian deviation) of which the former is relative to the latter can be achieved with DEM and the uncorrected point latitude and longitude.Thirdly, new localization information of the inaccurate point is calculated by dint of original localization points information and spherical surface radian deviation, and then the correction is finished.Because DEM influence to the location of several points at nadir is minimal, they can be considered as original points located exactly and then those on both sides are set as ones to be revised.Thereupon corrections can be carried out from nadir to verge step by step.The method can effectively decrease orientation errors in AVHRR data without the altitude information, which will contribute to the better use.
The Spatial and Temporal Characteristics of Tropical Cyclone-induced Rainfall in China During 1960—2003
Cheng Zhengquan, Chen Lianshou, Liu Yan, Peng Taoyong
2007, 18(4): 427-434.
China is one of the countries which are greatly affected by tropical cyclones (TC), with an average of 7—8 landfalls every year.Because of lack of enough and effective observational data several decades ago, the overall statistical study of TC-induced rainfall is needed.With the gradually increase of observational stations in these years, more and more data are available. The TC-induced rainfall data used is distinguished from the daily rainfall by a subjective way in Shanghai Typhoon Institute.Based on the data of TC landing on China and the relevant induced rainfall from 1960—2003, study is carried out of the climate characteristics of the TC-induced rainfall.Results show that, TC rainfall occurs from May to November, with the most active period from July to September, associated with the TC landfall activities.TC rainfall increases in intensity and region from May to August, and then decreases to November, and the TC rainfall reach zenith in volume and coverage in August. Spatial distribution of the TC rainfall and the frequency of TC rainstorms illustrate that they decrease dramatically northwards and inlandwards with the maximum in Hainan Province and the coastal areas of South China and Southeast China. And the ratios of summer TC rainfall to summer total rainfall and TC yearly rainfall to total yearly rainfall in these regions are also highest.Commonly, the TC-induced rainfall is much more in coastal areas than in inland areas.While under advantageous circulation, also, extremely intensive rainstorms can occur somewhere inlands.Statistics shows that the relationship between TC rainfall and TC intensity is not strictly linear, probably because of the complexity of influencing factors on the TC rainfall.Averagely, the mean of TC-induced maximum process rainfall is largest in August and September, and the frequency of TC-induced rainstorms is most in July and August.And the induced rainfall varies with the location where TC land on.The TC which land on Fujian bring about more process rainfall and rainstorms than on the other provinces.TC rainfall in most TC-affected areas in China decreases wavily since 1960, and the intensity of trend is different in target regions. The rainfall volume of decrease is most in South China, and the trend of decrease is most prominent in southwestern part of Northeast China, the western part of Southwest China, the coastal areas of East China and parts of South China.
Monthly Temperature Forecasts by Using a Complex Autoregressive Model
Gu Xiangqian, Kang Hongwen, Jiang Jianmin
2007, 18(4): 435-441.
In order to find a new method to improve the skill of short-rang climate prediction, a complex autoregressive model is established based on mathematic derivation of the complex least-square, in which the conventional least-square formula is extended from the real number domain into the complex number domain.This complex least-square solution is an exact analytic formula, and the conventional way is corrected that the real number and the imaginary number are separately calculated to reserve the least-square in the complex number domain.With a spatial expansion of Fourier series on monthly temperature fields in mainland China, the applications of this complex autoregressive model (M1) to monthly temperature forecasts show a high skill comparing with other conventional statistical models in predicting monthly temperature anomalies for July and most other months at 160 meteorological stations in mainland China.The conventional statistical models include an autoregressive model in the complex number domain that the real number and the imaginary number are separately disposed (M2), an autoregressive model in the real number domain (M3), and a persistence-forecast model (M4). For example, the anomaly correlation coefficient and root mean square error prediction for July by the M1 reaches up to 0.185 and 1.079 ℃ comparing with 0.089 and 1.113 ℃ by the M2, 0.061 and 1.147 ℃ by the M3, and 0.064 and 1.449 ℃ by the M 4 respectively, although the M2 does somewhat higher skill than the M3 and M4. It is expected that a better method of spatial expansion should improve further the forecast skill.The complex least-square derived in this study is an exact solution comparing with the conventional method that the real part and the imaginary part are separately calculated.In fact, the conventional method does not reach the actual least square in a complex number domain.The forecast experiments suggest that the complex least-square is an effective technique to dispose a complex number series, and may be applied to the linear and non-linear regression and similar statistic methods that are based on the least-square method.Developments of complex statistical models could be a perspective way to improve sim ulation and forecast skill in complex number fields in meteorology and relative disciplines.
Contrast Analysis on Atmospheric Circulation and Heat Source Anomalies in Strong and Weak Years of East Asian Summer Monsoon
Lü Junmei, Zhang Qingyun, Tao Shiyan, Ju Jianhua
2007, 18(4): 442-451.
Based on East Asian summer monsoon (EASM) index defined by Huang Gang et al., the differences of atmospheric circulation, atmospheric heat source and external forcing (i. e., SST) between strong and weak monsoon years are discussed.It is found that SSTA in Pacific appears La Niña pattern in winter preceding a strong EASM until the summer. That is to say, the SST in the equatorial central and eastern Pacific is low, while that in the Western Pacific Warm Pool is high.The convective activities over the equatorial eastern Indian Ocean, Sumatra and Warm Pool become obviously stronger than weak monsoon years.Meanwhile the atmosphere over South Asia, extending from the Indian subcontinent, through the southern part of the Tibetan Plateau, the Indochina Peninsula to South China, is abnormally heated.Furthermore, the analysis of mean tropospheric temperature anomalies shows that the heat contrasts between sea and land intensify.It is advantageous for the occurrences of strong EASM.In addition, the ascendant flow near Warm Pool is strong because of the active convection.So the Walker circulation becomes intense. The Asian subtropical westerly jet and subtropical high are located northward while the strong EASM advances northward.North China is located at the south side of the Asian subtropical westerly jet during July and August.So the precipitation over North China is abundant.Another rain belt is located at South China.But the precipitation over the Yangtze and Huaihe River Basins is short.On the other hand, winter SSTA in Pacific shows El Niño pattern preceding a weak EASM.The SST in the equatorial central and eastern Pacific and tropical Indian Ocean is high whereas that in the Warm Pool stretching through northwestern Pacific is low.This SSTA pattern lasts until the summer.As a result, the convective activity near Warm Pool becomes weak.Moreover, from April to July the atmosphere over the equatorial central and eastern Pacific is abnormally heated.But the atmosphere over South Asia, extending from the Indian subcontinent to South China, is cold.At the same time, the land-sea thermal difference between Asian land and the ocean weakens.It means a weak EASM.The center of convection activity shifts eastward into the central Pacific.Accordingly the Walker circulation becomes subdued.The ascendant flow over Indochina Peninsula and Philippine is weak.The Asian subtropical westerly jet and subtropical high are located southward while the weak EASM advances northward.The Yangtze and Huaihe River Basins are located at the south side of the Asian subtropical westerly jet during July and August, the precipitation over this region is abundant.Also, the physical scenario of atmosphere and SST anomalies associated with the interannual variability of the EASM are given.
Relationships Between Perturbation Kinetic Energy Anomaly Along East Asian Westerly Jet and Subtropical High in Summer
Yang Lianmei, Zhang Qingyun
2007, 18(4): 452-459.
In summer, upper level subtropical westerly jet stream along 40°N over East Asia is one of the most important large-scale circulation systems which influence weather and climate change over east China. At the same time, it is also a wave-guide along Rossby wave activity.Thus, it is necessary to define an objective and quantitive perturbation kinetic energy (Ek) index along East Asian westerly jet (EAWJ), and Ek annual variation and anomalies are investigated.Moreover, the relationships between Ek and EAWJ intensity and EAWJ position are examined, lastly the configuration and connection processes between Ek variability along EAWJ and South Asia high (SAH) and western pacific subtropical high (WPSH) in summer are confirmed by NCEP/NCAR reanalysis dataset from 1979 to 2003.u basic and v basic are defined by wave number k < 3 based on wind u and v in 200 hPa calculated by Fourier expressions, the perturbation kinetic energy of Rossby wave along EAWJ is defined by k≥3 wave activity, and Rossby wave perturbation (u′, v′)=(u, v)-(ub vb), Ek=(u′·u′+v′·v′)/2 which is averaged in the area of latitude with maxima zonal wind shifted±5°and in 100°—140°E, so normal Ek is defined as Rossby wave activity index along EAWJ which also includes meridional displacement variability of EAWJ.EAWJPI (East Asian westerly jet position index) is defined by the difference of zonal wind in 200 hPa between 35°—40°N, 100°—140°E and 40°—45°N, 100°—140°E, and EAWJII (East Asian westerly jet intensity index) is defined by the summation of zonal wind in 200 hPa averaged by 35°—45°N, 100°—140°E.The results show that EAWJ is southward (northward) than the normal and its intensity becomes stronger (weaker) while Ek strengthened (weakened). Not only Ek variations are associated with EAWJ intensity and steady Rossby wave perturbation along westerly jet in summer, but also south—north wave train anomaly in East Asia. Height anomaly in Asia mid-latitude area is most remarkable.When Ek appears stronger (weaker) than normal, center position of circumglobal wave train wave in mid-latitude zone moves to southern (northern). The correlation coefficient is 0.56 between Ek and SAH intensity, 0.66 between Ek and SAH eastward ridge point position, and-0.52 between Ek and WPSH ridge line position during 1979—2003 summer respectively, all are over 99% level.While Ek appears stronger (weaker) than normal, SAH moves to eastward (westward) and stronger (weaker) than the normal.At the same time, WPSH is southward (northward) than the normal.It is found that the response of WPSH to Ek anomaly is going with the change of divergence-convergence over East Asia in 200 hPa and vertical motion in tropic and subtropical zone from surface to upper air.
A Severe Convection Weather of Jiangxi in April 2003
Qian Chuanhai, Zhang Jinyan, Ying Dongmei, Lin Jian
2007, 18(4): 460-467.
Convection weather is one of the most severely disastrous weather phenomena in China, with features of small spacial scale, short life span, sudden emergence and great damaging force.It is always very difficult to make an accurate analysis and forecast for severe convection weather in the daily operational work.With the application of Doppler radar and the development of numerical weather prediction technology, the know ledge about the severe convection weather and the related mechanisms is also improved in recent years.Effective ways have been developed in some countries to be applied in the analysis and forecast for severe weather.Examples can be found in U S A, where parameter estimation, graphics identification and statistical characteristics based on climate have been put into operational use for forecast of hailstones and tornadoes, and proved to be useful in improving the accuracy.Much improvement is also made in China Meteorological Administration in recent years in severe weather observation, many new instruments, such as radars, automatic weather stations, lightening detection and GPS/MET vapor detection instruments etc have been gradually put into operational use.These new data definitely provide forecasters and researchers good opportunities to study the severe convection weather and improve the forecast accuracy.Using NCEP/NCAR daily meteorological reanalysis data, sounding data, TBB and Doppler radar images, a typical convection induced severe weather process occurred on April 12—13, 2003 in Jiangxi and northern Fujian is diagnosed and analyzed, the result shows that this severe convection weather takes place under favorable conditions of upper trough coupling with a low-level vortex and shear environments. Lower level southwesterly jet contributes as a vapor transportation passage.Dry and cold airs of upper level overlapping upon wet and warm airs in low er level create a convectively unstable layer.Under this condition, convective weather could be easily initiated and high instability energy releases with suitable triggering mechanism. Several mesoscale convective clouds involve in the development of the severe weather, and deep convection mostly concentrates on the frontal parts of the clouds where TBB isolines converging with high gradient.Also the Doppler radar images show that the maximum reflection up to 79 dBz is reported during hail-fall, and bow echo could be observed.Convective available potential energy (CAPE) is a meaningful sign in the process of convection event.Before the severe weather, CAPE grow s gradually and accumulates.The severe weather initiates soon after the CAPE reaches its peak values, then with CAPE's releasing and becoming weak rapidly, severe weather downgrades.Dry air intrusion to mid-level from upper level plays an important role in the development of convection.Energy-front zone and strong vertical vorticity-pole provides thermodynamic and dynamic conditions for this severe convection weather.
Mechanism Triggering the "03.7" Heavy Rainfall in the Northwest of Hunan Province
Ye Chengzhi, Pan Zhixiang, Liu Zhixiong, Huang Xiaoyu
2007, 18(4): 468-478.
The analysis on torrential rain event in Hunan Province on July 7 to 9, 2003 is accomplished.It is the result of the combined use of conventional intensive observational data, GMS satellite cloud picture, Doppler radar data and the numerical simulation result with mesoscale numerical model of the Penn State/NCAR Mesoscale Model 5(MM5). In particular, it emphasizes the output based on the observational facts and the MM5 high resolution data.The mesoscale convective system is discovered which is prone to the existence and maintenance of the heavy rainfall center in Zhangjiajie.In order to reveal the development mechanism and spatial structures of Meiyu front rainstorm mesoscale convective systems, some innovative work about this rainstorm triggering mechanism is done.These important scientific conclusions can be used to seek new forcasting ideas, and ultimately improve the heavy rain forecast.The heavy rain is related to the movement and evolvement of multiple mesoscale convergence disturbances. With the rapid development of the mesoscale rain clusters, the β-mesoscale vortex takes shape, by which this torrential rain is directly affected.The reason of this rainstorm is not the severe multi-cell and super-cell.Due to the atmosphere constantly generation of new convective cells and afterwards vanish in the north, the organized multi-cell storm is the main reason of this heavy rain in Zhangjiajie.The appearance of head wind zone about several kilometers above the district of Zhangjiajie which is reflected in the Doppler radar radial velocity field is the result of small-scale cyclone formation and maintenance. It is closely related to the emergence of continuous heavy rain.In the low troposphere layer, as the Southwest jet velocity fluctuates, jet stream flow and the largest northeast nuclear center are split by it and the development of the β-mesoscale vortex in the northwest of Hunan is triggered.The suction effect caused by the low-level jet disturbance and the divergence on the top-level of troposphere is the triggering mechanism of the heavy rain, and the dynamical and vapor field disturbance induced by the mesoscale topography is the main element of the heavy rain.The β-mesoscale vortex presents intricacy thermal and dynamical structure, the θse equiscalar surface tilt is forced by the latent heat release caused by the strong convective movement and the sudden increase of PV on the low-mid level is made.Simultaneous, the strong convective movement takes place in the region of isentropic surface marked by a sunken feature.The PV sliding along the entropy isentropic and the slope vortex development may be the main cause of maintain and development of the β-mesoscale vortex.
Applied Research on Forest Fire Danger Weather Index
Niu Ruoyun, Zhai Panmao, She Wanming
2007, 18(4): 479-489.
Forest fire is one of the main disasters which damage the ecosystem on the earth.Not only vegetation coverage and charcoal storage can be reduced and atmosphere composition can be changed, but also variation of vegetation structure and biological species can be induced and social economy, human health, and even life can be impacted.And the occurrence of forest-fire is very closely related with the meteorological conditions. Until now domestic and foreign meteorologists and forestry experts have developed a lot of forest fire danger weather indices to estimate and predict possibility of ignition, fire intensity and its spread, as well as difficulty of wildfire control. In this study, 5 calculation methods of forest fire danger weather index are chosen, which have been approved universally or used in state-level early warning service in China, using meteorological observation data of 575 national basic meteorological stations from Jan 1, 1971 to May 31, 2005, to conduct contrast analysis and applied research on the practical effects of these indices in China.The purpose of this study is to examine and discover a best method to find forest fire danger weather index which suits Chinese weather and climatic characteristics, and to improve the operational level of Chinese state-level forest fire danger monitoing and early warning.The results indicate that IFFD, INMC, IN and IMN index may be promoted and used in China on a large scale (except in middle and lower reaches and nearby regions of Yangtze River), in which the overall application effect of IFFD index is the best, and IMN index takes the second place.IFFD index is the best in these five kinds of indices not only because of its practical application effect, and because it has the highest corresponding relations with number of the forest-fire in Northeast China and Southwest China, which are two large key Chinese meteorological service regions of forest fire protection, but also of its construction method.IKBD is not suitable for the most areas of China, but when it is brought into IFFD as a part of drought factor, the practical application effect of IFFD is improved significantly.The practical application effect of IMN is proved to be also good.Its value is closer to the fact than IN, after weighting coefficient is introduced to control the reduction rate of different precipitation to the index.INMC also has good instruction function to forest fire risk, but it is not a patch on IFFD and IMN as a whole.One of the causes is that INMC is insufficient in considering the previous climatic background.In fact, high or extremely high forest fire danger weather rating is related closely to previous precipitation deficit.
Genetic Conditions of Sandstorms in the Hinterland of Taklimakan Desert
Li Shengyu, Lei Jiaqiang, Xu Xinwen
2007, 18(4): 490-496.
Sandstorm is a kind of catastrophic weather with great impacts on ecology and social economy.As a result of special natural conditions, the Tarim Basin is one important area in China where sandstorm occurs very frequently. Research working on sandstorm in the Tarim Basin before is primarily focusing on the verge of the Tarim Basin, but few of the works are about the sandstorm in the hinterland of the Taklimakan Desert.In order to understand comprehensively the law of sandstorm occurrence in the Tarim Basin, the genetic conditions of sandstorm in the hinterland of Taklimakan desert is to be disclosed by analyzing the data of sandstorms collected from 1997 to 2002 at Tazhong weather station.Results show that the abundance of dust substance is a prerequisite to the occurrence of sandstorm in most areas.But dust origin isn't the limiting factor of sandstorm occurrence in the inner part of the Taklimakan Desert.At the same time the precipitation in this area is too little to change the moisture of sand surface, so precipitation can't influence the abundance of dust substance.The occurrence of sandstorm primarily depends on wind force which can be represented by average wind speed and days of strong wind, but statistic results show that wind forces only weakly correlate with days of sandstorm, therefore there are still other factors influencing the occurrence of sandstorm.Air stability which can be figured by temperature and weather process is another important factor influencing sandstorm occurrence.It is found that the occurrence of sandstorm has a positive correlation with temperature because of unstable air mass near ground surface.Sandstorms mainly occur in spring and summer, rarely in autumn and w inter; furthermore, sandstorms occur more frequently in summer more than in spring.Sandstorms mainly occur in daytime especially in the afternoon, but only a few occur in nighttime.Precipitation is a key indicator of weather process in the hinterland of the Taklimakan Desert.Statistic results show that sandstorms occurrence has a positive correlation with monthly days and monthly amount of precipitations.Data indicate that the month with annual largest precipitation doesn't correspond with the biggest hours of sandstorm persistence, but with the lower than the maximum in a year.As a result, a large amount of precipitation has a restrained effect on the occurrence of sandstorm to some extends.From 1997 to 2002, annual precipitation and air temperature tend to increase, but sandstorm occurrence tends to decline.This phenomenon may be response to the decrease of weather process especially dry and cold air activity caused by global climatic change.In brief, because the environment in the hinterland of the Taklimakan Desert is very extreme featured by mobile sand surface, scarce precipitation, strong evaporation, the genetic conditions of sandstorms in this area are also very special and different from other areas.
The Trend Variation Feature of Fog Days in Fujian Province for Recent 44 Years
Wu Bin, Shi Neng, Li Ling
2007, 18(4): 497-505.
The monthly data of fog (visibility less than 1000 m) and dense fog (visibility less than 500 m) from 50 meteorological stations in Fujian Province in the period of 1961—2004 are used to analyze the annual and seasonal distribution feature, the long term trend variation, the annual and decadal variation and possible influence factors etc.The results show that the regions where annual and seasonal fog occurs frequently are in the central and western Sanming, while few occurrences are in the coast and the south of Fujian, the same is dense fog.Among the more fog regions, the number of annual fog days is more than 80, some exceed 100 days.In less fog regions it is less than 20 days.More than 30%of fog days in more fog areas are dense fog, some areas such as the southern Nanping it can even pass 50%. Dense fog seldom occurs in the coast.Fog occurs frequently during autumn and winter (October to next February) in inland and in spring in the coast areas.In summer, fog events are not prone happening.The time which dense fog appears often is in October to next February.The tendency of annual and seasonal fog days significantly decreases in large parts of Fujian with the tendency coefficients above 99.9%confidence level for 30 stations, and only in western Longyan and parts of the coast the tendency increases.For dense fog, the decreasing tendency is less than that of fog, there is nearly no change in the tendency in the south and the middle coast in Fujian, only in the middle inland the tendency has significant decrease. Analysis is focused on decadal average numbers of dense fog and its deviation coefficient.It is pointed out that though the dense fog days have a small decrease in 1990s but its deviation coefficient is the biggest, therefore the dangerous of dense fog increases while the predictability is difficult.The annual and seasonal fog days represent significant decadal variability.The annual fog days are below the normal after the mid 1980s, before which it is above the normal.Special analysis is given to 6 representative stations for the tendency and monthly variable rule of fog and dense fog.Furthermore studies of the reasons for the decrease of fog point out that the fog days have good negative relation with annual average temperature, and good positive one with relative humidity.The remarkable jump points for the three are in the mid 1980s.After that time the temperature increases faster, while relative humidity reduces remarkably and the numbers of fog decrease too.It still has a certain relationship with the dimension of forest.But due to the limited data, it now has some uncertainties.
Distribution Characteristics of Yunnan Province Atmospheric Water Resource
Tao Yun, Zhao Di, He Hua, Gao Xishuai, Zheng Jianmeng, Huang Wei
2007, 18(4): 506-515.
Using the monthly precipitation and temperature of Yunnan 124 stations from 1961 to 2004, the water resource components, such as the evaporation (E) and utilizable rainfall (P-E), are calculated by means of Takahashi's evaporation equation. The temporal and spatial features of water resource components and their periods are also analyzed. Results indicate that components (P, E, P-E) of water resource in southern area are higher than that of northern area. The grads in southern area are big and that in northern area are small. 44-year average P-E and have very similar spatial and temporal distribution. The biggest and smallest center of P-E are unanimously corresponding with P, but the value of P-E is smaller than P. The components (P, E, P-E) of water resource in Yunnan have obvious seasonal changes. The biggest value of the components (P, E, P-E) appears in summer. Their annual average values are 548 mm, 236 mm, 313 mm respectively and their ratios to the whole year are respectively 55%, 45% and 67%. The smallest value of the components (P, E, P-E) appears in winter and their ratios to the whole year are respectively 5%, 7%and 2%. The components (P, E, P-E) of water resource in Yunnan also have obvious inter-monthly, interannual and interdecadal changes. The biggest value appears in July and the smallest appears in January or December. The difference between the maximum and the minimum of components (P, E, P-E) of water resource is very large. At the same time, the interdecadal difference of components (P, E, P-E) of water resource is also very obvious. P and P-E are relatively abundant from 1960s to the middle of 1970s, they are less from mid 1970s to mid 1990s and more after mid 1990s. By the power spectrum period analysis method, it is revealed that there is a significant period of 2.6 years in total annual rainfall and total annual utilizable rainfall and there is a significant period of 2.9 years in total annual evaporation. The water resource of Yunnan Province is divided into three regions:abundant region, poor region and general region. There are very obvious differences among regional and annual mean utilizable rainfall, evaporation and rainfall of the three regions.
The Quality Control of Surface Monthly Climate Data in China
Ren Zhihua, Xiong Anyuan, Zou Fengling
2007, 18(4): 516-523.
It is generally agreed that outliers detection as well as outliers identification is of primary importance to quality control (QC) of observational data. Using some traditional quality techniques such as high-low extreme check, confidence limit control, internal consistency check etc, China historical surface meteorological data has been examined over and over, but there is a wide variety of erroneous values that are not been detected yet. If the continuity and distribution state of a data series and the outliers existence are not been understood well beforehand, some special erroneous values cannot be detected. The surface climate data series become more complex and inhomogeneous as a result of station moves, changes in the environment surrounding a station, and frequent changes in observational criterion in China. Therefore, the distribution of the data series from a great number of stations in China is not a normal distribution. Though discontinuities and inhomogeneities in time series are not of the field of QC, they have an effect upon traditional QC result. On the other hand, there would be problems in the sequential monthly climate data even the data among years as a result of measurement instrument errors, that of instrument calibration, a gradual shift in the physical characteristics of the instrument apparatus, or misoperation by observers etc if the above problems could not be solved in time. Perhaps the kind of data are not of great difference to the normal data, but they have certain impact on climate analysis. After analyzing the inhomogeneities, distribution state of the series and erroneous data in existence in China historical surface climate data, the QC method of surface monthly climate data in China has been developed, which is a breakthrough to traditional QC techniques of monthly climate data. It turns out that the quality control of China surface monthly climate data should include the following three steps: The check of continuous erroneous data after integrating the 12 monthly time series into a new individual series; the temporal check and spatial check of outliers after time series converted from likely inhomogeneous distribution to homogeneous one; manual advanced identification of continuous suspicious data and outliers. With the above QC method, about 250000 surface monthly climate data of base stations in China from 1971 to 2000 is examined. The climate data contains more than 10 monthly variables: Surface air temperature, surface air relative humidity, wind speed, skin surface temperature, eight layers of soil temperature, sunshine duration, pan evaporation, frozen earth depth and snow depth etc. 136 erroneous monthly climate data referring to various variables are detected in total. The causes of erroneous monthly data according with original data such as hourly data is the following: Use other station data or monthly data to substitute true data; miss-recording such as enlarging or reducing 10 times in original data; the original data should not be equal to 0, but the record data is 0; the measurement instrument is mal functioning.
Characteristics of Organic Carbon and Elemental Carbon in PM2.5 During Winter in Taiyuan
Meng Zhaoyang, Zhang Huaide, Jiang Xiaoming, Yan Peng, Wang Yan, Lin Weili, Zhang Yangmei, Wang Shufeng
2007, 18(4): 524-531.
Taiyuan is a city characterized by coal-combustion pollution. Aerosol is one of the main pollutants in Taiyuan. The primary objectives of the study are to examine the temporal variations of PM2.5, OC, EC concentrations with OC/EC ratio during winter in Taiyuan, and to find and understand the correlations among PM2.5, OC, EC, OC/EC ratio and meteorological factors. Continuous observation of PM2.5 is conducted in Taiyuan during high pollution seasons from December 18, 2005 to February 3, 2006. PM2.5 samples are obtained from the rooftop of Shanxi Meteorological Sciences Institute. PM2.5 samples are collected every day using TEOM series 1400a ambient particulate monitor-ACCU. The samples are collected on 47 mm Whatman quartz microfiber filters. Continuous meteorological data are obtained from Shanxi Meteorological Observatory. EC and OC in PM2.5 are determined by Sunset carbon analyzer.The study shows that the concentrations of PM2.5, OC and EC are high during winter in Taiyuan. The daily concentration of PM2.5 varies from 25.4 to 419.0 μg/m3 with the average of 193.4±102.3 μg/m3. According to the standard of daily average value of PM2.5 (65 μg/m3) published by US EPA in 1997, 89% of daily average PM2.5 values exceeds the US air quality standard during winter, which shows fine particles pollution is serious during winter in Taiyuan. The average OC concentration is 28.9±14.8 μg/m3, while EC is 4.8±2.2 μg/m3. The highest values/lowest values of OC and EC are 3.3, 1.1, respectively. High variability of OC concentrations may be due to the contributions of different emission sources. The OC and EC levels at Taiyuan, especially OC, are higher than other urban cities, reflecting more severe carbonaceous pollution in Taiyuan. OC and EC account for 18.6% and 2.9% of PM2.5, respectively, which indicates that carbonaceous aerosols are key components for controlling fine particles pollution in Taiyuan. Coal combustion from residential heating during winter is the major emission source of OC and EC, and the emission of OC increases largely relative to EC during winter. The most OC/EC ratios exceed 2.0 and average OC/EC ratio is 7.0±3.9 in winter. Higher OC/EC ratios are found during heating seasons with increased primary emission sources like coal combustion. The OC-EC correlation is low during winter in Taiyuan city, pointing to the complex of emission sources. The meteorological conditions have significant effects on the ambient concentrations of PM2.5, OC, EC and OC/EC ratio. Fog, the relative humidity, wind speed and snows are major factors that influence the concentration variation of carbonaceous aerosols. Positive correlation exists between PM2.5, OC and OC/EC ratio with relative humidity, meanwhile negative correlation exists between PM2.5, OC, EC and OC/EC ratio with the visibility and wind speed.
Simulation Study of Climate Change Impact on Crop Yield in Heilongjiang Province from 1961 to 2003
Gao Yonggang, Gu Hong, Ji Juzhi, Wang Yuguang
2007, 18(4): 532-538.
Climate warming is very remarkable in Northeast China, especially in Heilongjiang Province form 1961 to 2003, the climate change trend exerts significant impact on the yield change trend of crops. Based on the climate change trend in various areas of Heilongjiang Province from 1961 to 2003, with daily meteorological data of meteorological stations and their interpolated grid (50 km×50 km) data in Heilongjiang Province from 1961 to 2003, the main food crops (maize and soybean) yields are simulated by WOFOST model in every grid of Heilongjiang Province from 1961 to 2003, the effectiveness test of WOFOST model is made between the official statistical yield data and the simulation yield data from 1988 to 2003, the simulation effect is good for WOFOST model. The mathematical analyses are used for the change trends of climate factor and simulation yield, the spacial distributional characteristics are calculated and analyzed for the change trends of climate factors and the main food crops simulation yields in Heilongjiang Province from 1961 to 2003, the impacts of climate change trend are discussed on the chief food crops simulation yield change trends in Heilongjiang Province from 1961 to 2003. The results show that the impacts of the different spacial distribution of the climate change trend are important to the different spacial distribution of chicf food crops simulation yield change trends, but the impacts are different for different crops. The change trend of simulation yield for maize is increasing in Heilongjiang Province from 1961 to 2003, the average increasing extent is about 4.81%/10a, the rising air temperature change trend is a primary climate factor on the increasing simulation yield change trend for maize in Heilongjiang Province. As a whole, the change trend of simulation yield for soybean is falling in Heilongjiang Province from 1961 to 2003, the average falling extent is about-1.52%/10a. The climate change trend impacts are different on the simulation yield change trends of northern and southern areas for soybean, the northern area of Heilongjiang Province is superior planted area for soybean, the rising air temperature change trend is a primary climate factor on the increasing simulation yield change trend for soybean, the change trends of relevant air temperature and rainfall are primary climate factors on the falling simulation yield change trend in southern area for soybean.
Operational Prediction Method of Nationwide Cotton Development Stages
Qian Shuan, Chen Hui, Wang Liangyu
2007, 18(4): 539-547.
The cotton development stages are the important features for the description of cotton individual and population characters. Accurate prediction of cotton development stage is very important for realizing various services on early warning and recovery of meteorological disasters and management strategies for cotton production, but there isn't the prediction function for cotton development stage in nationwide agrometeorological operation. In order to satisfy the service demand, the prediction method of the cotton development stage on the base of the operational data is studied. Cotton is main planted in Xinjiang Uygur Autonomous Region, Yellow River and Yangtze River drainage areas in China, where climate features are different. 50 cotton-produced counties of nationwide agrometeorological observation network are located in above main cotton-produced regions, the observation of their cotton development stages reflect the course and status of Chinese cotton development well. The time for same cotton development stage is different each other in different cotton areas, the difference between years is high by analyzing the variability of cotton development stages. The various factors affecting cotton development for 50 cotton observation stations are very different. So the prediction model of the cotton development stage is built in simple station, simple development period. Among affecting factors of cotton development stages, active temperature accumulation is the most main factor for the whole cotton area, precipitation is also relative in some cotton-produced counties located in Yellow River drainage area. According to above results, operational prediction model based on active accumulated temperature and growth days index for cotton development stages has been built, considering received data available and service characteristics of nationwide agrometeorological operation, combining with the results of weather forecast. Among models, active accumulated temperature and growth days index are refreshed year by year, cotton development stages are refreshed decade by decade, historical or forecast temperature is refreshed day by day, the timely operational dynamic prediction of cotton development stages has been realized in this way. The model results of the historical fitting from 1992 to 2001, extrapolating prediction from 2002 to 2003 and testing prediction in 2004 are as follow comparing with observed cotton development stages. The frequencies within 5 days error are above 80% for the fifth leaves and blooming stages, above 70% for emergence, the third leaves and squaring stages, their average absolute errors are within 4 days for above stages. The frequency within 6 days error is near to 70% and average absolute error is within 6 days for boll opening. The frequency within 10 days error is near to 70% and average absolute error is near to 10 days for stopping growth by integrating two methods of active temperature accumulation and first frost in autumn. These results are satisfied, which could meet the demands of nationwide agrometeorological operation service.
The Climatic Zoning of Spring Maize in Hunan Based on Meteorological Disaster Indexes
Lu Kuidong, Huang Wanhua, Fang Li, Zhou Yu, Xie Baicheng
2007, 18(4): 548-554.
The maize is the biggest drought grain crop in Hunan, the single yield is lower than the average of the country about 450 kg/hm2, moreover, the total yield is very difficult to reach the practical demand. So considering the reduction of the meteorological disaster's risk, and carrying out the maize plant zoning, it is expected to arrange well the distribution and provide scientific foundation to prevent and avoid disasters. The climate factor are defined in zoning index in crop climate zoning research in the past, the grade division is the main method. Plant zoning will be carried out according to the meteorological disaster index which will restrict the spring maize high and stable yield.Based on the historical meteorological data of 97 weather stations in Hunan from 1961 to 2004, combined with the ecological habit of maize and field experiment data results, the disaster index is calculated in maize growth. This index includes the drought from maize spin to maize autumn, high temperature damage and protracted rain spell at the stage of seeding, and it affects significantly in maize growth. At the same time, these indexes are used to maize plant zoning. The three disasters of the zoning distribution character are systematic analyzed in City-star software. The protracted rain spell annual probability is from 23.3% to 86.7% at the stage of seeding, the terrain distribution tendency is more in the south than north. The drought annual probability is from 4.6% to 45.5% at the procreate growth, the tendency is that the west of Hunan and the south of center Hunan has much high probability, there is small probability in the Zi River valley and the Dongting Lake region. The high temperature damage annual probability is from 0 to 81.8% from spin to autumn, there is high occurrence probability in Hengyang, the south of center Zhuzhou; but there is low occurrence probability in the Dongting Lake region, the west of Hunan and the hilly southwest Hunan, the mountainous southeast Hunan. The annual probability of disaster index is used. At the same time, the "variable speed" theory is introduced. The climate factor is not only the integral grade, but also fine variable. The zoning grade according to disaster factor for maize growth influence is used. The drought occurrence annual probability grade index is Kd=Pd/0.25. The high temperature damage occurrence annual probability grade index is Kh=Ph/0.30; protracted rain spell occurrence annual probability grade index is Kc=Pc/0.50. At last, the total grade index is reached, it is K=Kd+Kh+Kc. The spring plants are divided into four regions according to the synthesis grade index.The results show that most regions are adaptable to plant maize in Hunan, whereas the adaptability is different in different areas. The high yield region distributes in the optimum region and suitable region; the low yield region distributes in the relatively suitable region and sub-suitable region. But the low yield region in the southeast of Hunan is in the suitable region, the causes for that may be the lack of sunshine and temperature in the mountainous region and the soil fertility is bad.
Interpretation of Monthly Dynamical Extended Range Forecast Products in Northwest China
Lin Shu, Chen Lijuan, Chen Yanshan, Li Xingmin, Li Yanchun
2007, 18(4): 555-560.
Using monthly precipitation data of 163 observatory stations in Northwest China, reanalysis data of 500 hPa monthly average geopotential height from NCEP/NCAR, and monthly 500 hPa geopotential height of monthly dynamical extended range forecast, comparisons among the climatic forecast, persistence forecast, explanation test of reanalysis data, forecast experiment with the interpretation method of monthly dynamical extended range forecast products are made. The results show that the skill of the reanalysis data explanation test has the highest score, while the climatic forecast score is the lowest. The score of the interpretation method of monthly dynamical extended range forecast is a little lower than that of the interpretation test of reanalysis data, but higher than that of climatic forecast and persistence forecast. It indicates that by the spatial distribution of the PS score over Northwest China, the distribution of monthly dynamical extended range forecast is very similar with that of the analysis data of interpretation test. The regions with the highest PS score located in the south of Qinghai Province, south of Gansu Province and south of Shaanxi Province where the monthly precipitation climate value is relatively high. The regions with the lowest PS score locate in part of Xinjiang, west of Hexi of Gansu Province where the monthly precipitation climate value is relatively lower. And the downscaling tests show high skill when more data of observation stations are used.
Observation and Analysis of the Aggregation Growth Among Ice-snow Crystals
Huang Geng, Su Zhengjun, Guan Liyou, Zhang Jihuai
2007, 18(4): 561-567.
The process of the ice-snow crystal running together plays an important part in origination of precipitation. It is a focus in cloud physics research. It discusses the cloud and fog that happens in lab and field observations. Result shows that as the droplets coalesce and grow, there is a speed up process also in ice crystals growth, such as snowflake, snow-circular, graupel and hail that coalesce super-cooled droplets and aggregate among ice-snow crystals. Experiments show, in the lab the shapes are fixed basically in temperature of -3.5- -20 ℃. The aggregate among ice-snow crystals only happens in saturated or super-saturated water level vapor pressure in the lab. While in insaturation (no liquid droplets) it does not happen. In 1 m3 chamber their shapes are dendritic and stellar, and their aggregated mechanism is caught by branches appearing in -13- -17.℃ While in 96 m3 chamber the shapes are needle, columnar, dendritic and stellar, the mechanism is adhesion and adhering appearing in -5- -18 ℃. In field observations of natural cloud and fog, the mechanism of the ice-snow crystal running together is adhesion and adhering appearing in -3- -17 ℃, and their shapes are dendritic, stellar, sector, plate, tabular, needle, columnar and columnar bean.The 1 m3 chamber is 1.76 m high and 0.88 m wide, the experiment is made in-3.5- -20 17. The 96 m3 chamber is 14.8 m high, 3.0 m wide, the experiment is made in-5- -18 ℃. The temperature is measure by three Pt resistance thermometers with the difference of 0.1 ℃ to compare with standards one. The sample that burnt for Silver Iodide pyrotechnic is made by deposit method. A great deal ice crystal aggregates into each other appearing in -13- -17 ℃ in 1 m3 chamber when the sample is exposured for 1 minute. But for other temperatures of -3.5- -20 ℃ it does not. While in 96 m3 chamber the aggregation process happens among ice crystals. Their sizes are lager than 1 m3, because the ice crystals could be maintained for a few hours, and there exists torrent and the ice crystal could move with air in 96 m3 chamber. In field observation, the measurement is made by PMS, 2D-C, 2D-P on aircraft in cloud, and by electronic microscope and the samples making for deposit on ground. The shapes of snowflake aggregation vary in cloud in nature because they could exist long in cloud and exhibit convective and torrent features. The ice crystal could interact with them. Another field observation is made by artificial dispersing fog by liquid nitrogen, and samples are measured by electronic microscope for deposit on ground. The ice-snow crystals running into snowflakes by the mechanism of adhering in -3— -8 ℃, and their shapes are hollow columnar, columnar and needle.
Antarctic Sea-ice Extent Oscillation Index with the Relationship Between ASEOI and Synoptic Climate in Summer of China
Ma Lijuan, Lu Longhua, Bian Lingen
2007, 18(4): 568-572.
Sea ice is an important part of climate system and its change will influence local and regional circulation, even global climate change. Recently, Arctic Oscillation (AO) and Antarctic Oscillation (AAO) and their impacts on East Asia and global climate draw more attention of meteorologists. Cheng et al. find a teetertotter characteristic of sea ice concentration between the peripheries of Ross Sea and Bellingshausen Sea, and define the differences between them as the Antarctic Sea-ice Oscillation Index (ASOI). However, it's hard to define the scopes of these two regions exactly. In this study, a new index, ASEOI is built, as the difference of sea ice extent between Ross Sea Region and Antarctic Peninsula Region. Higher ASEOI represents less sea ice in Ross Sea Region and more sea ice in Antarctic Peninsula Region. Results indicate that this new index can well account for the impacts of prophasic sea-ice variations on atmospheric circulation and synoptic climate.The correlation analysis between ASEOI and SOI indicates that lower ASEOI in the previous spring of Southern Hemisphere (SH) will cause stronger Southern Oscillation (SO); lower ASEOI in the previous autumn of SH will lead to weaker SO from June to September. ASEOI can be used as an indicator of precipitation in the lower and middle reaches of Yangtze River and temperature in North China and South China. Taking ASEOI in October as examples, if ASEOI in the preceding October is below normal, the precipitation in the middle and lower reaches of Yangtze River in July would be more and the flood would be easy to build there, while the temperature would be higher in most part of North China and lower in South China. As it is known, less precipitation usually comes with the hot weather, and this would undoubtedly intensify drought in North China.This research helps the better understanding of interaction between Antarctica sea ice and atmospheric circulation and cognize the physical processes of sea-ice-air interaction in Antarctica, and offers helpful reference for further discussing the relationship between the variations of Antarctic sea ice and atmospheric circulation or synoptic climate. At the same time, it helps develop the correlative numerical simulation and seek the strong prognosis signals of Antarctica to the short-term climate influence on China.
Z-R Relation with Its Application to Typhoon Precipitation in Zhoushan
He Kuanke, Fan Qiping, Li Kaiqi, Chen Shuqin, Gong Yan
2007, 18(4): 573-576.
Using the typhoon base data of Dopplar weather radar and Zhejiang automatic precipitation station data in 2004 and 2005, the Z-R relation of typhoon precipitation suiting the local area is set up, which is confirmed to be available. It is applied to estimate the precipitation of typhoon "Nanmadol" and "Khanun", with comparing with the real precipitation and the estimated precipitation based on Z-R relation of American WSR-88D. It shows that in an area with small rainfall, the estimated precipitation by use of Z-R relation of American WSR-88D is more close to the fact than the precipitation with using the target relation. However, in an area with heavy rainfall, the latter is more close to the fact than the former, which the rainfall is seriously underestimated. Also, causes of the main error are further studied.