应用气象学报

Vegetation Activity Responses to Climate Change in the Huang-Huai-Hai Area Based on GIMMS NDVI Dataset

Chen Huailiang, Xu Xiangde, Du Zixuan, Zou Chunhui

2009, 20(5): 513-520.

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Abstract:
Based on 1982 -2003 GIMMSNDVI sounding and climate data by use o f techniques for the trend, correlation and singular value decomposition (SVD) analysis, the space and time patterns of vegetation activity response to climate change in the Huan-Huai-Hai Area (HH A) is investigated.Results suggestthat this area show s a more significant warming trend and less distinct aridization, on the w ho le, with annual mean NDVI displaying a marginally increasing trend.In the spatial distribution figure of the correlation coefficient between annual average and climate factors, the annual average temperature is positive correlated to the annual NDVI in most area, which indicates that the increasing temperature is beneficial tothe vegetation growing in most region of the study area.On the other hand, the annual precipitation isnegatively correlated to the annual NDVI in south region but positively correlated to the annual NDVI innorth region of the study area.On the yearly basis, temperature is the most sensitive climate factor.Annual temperature, rainfall and relative humidity exert positive effect on the dynamic variation in vegetationNDVI while evaporation exerts negative effect.On the seasonal scale, temperature and rainfall are themost strongly influencing factors, with autumn climate having heavier impact on yearly mean NDVI. Natural vegetation is predominantly sensitive to rainfall and, to a less degree, to temperature; agriculturalvegetation is sensitive dominantly to temperature and, to less ex tent, to rainfall.The grassland vegetationis more sensitive to the precipitation and other climate factors than other kinds of natural vegetation.Among the agricultural vegetation, the rain-fed vegetation of one cropper annual and paddy-upland rotationagricultural vegetation of two crops per annual are more sensitive to the temperature and precipitation, butthe vegetation of two crops per annual in irrigated farm land is less sensitive to the climate factors.The precipitation of autumn, spring and winter and the temperature of spring and summer are the main factors affecting natural vegetation.The temperature of spring and winter, the precipitation of spring and summerare the main climate factors affecting the agriculture vegetation.April -September vegetation response toclimate has the spatial patterns as follow s.The anomaly field of N DVI has the same structure as that oftemperature, an anti-correlation structure with anomalies of evaporation, and a see-saw distribution withpositive (negative) correlation in the north (south) with that of rainfall anomalies, and an opposite distribution with positive (negative) correlations in the south (north) to that of relative humidity.

Regression Estimate of Event Possibility and Precipitation Categorical Forecast

Zhao Shengrong, Zhao Cuiguang, Shao Mingxuan

2009, 20(5): 521-529.

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Abstract:
Objective precipitation forecast is a difficult problem in NWP products interpretation.Because of itscharacteristics, objective precipitation forecast is a categorical forecast rather than precipitation amountforecast.The differences between two kinds of categorical precipitation forecast are analyzed.One categorical forecast is based on probability regression.Its method is processing original precipitation to 0 and 1corresponding categories, and then developing forecast equations of different categories to calculate the criterions.In real forecasting, the categorical precipitation will be determined through the criterion and theprobability forecast of that category.The other forecast is based on regression, the method of which ispreprocessing original samples with value smaller than the threshold to category of 0, and then developingforecast equations and criterions.The experimental result from autumn of 2007 to summer of 2008 indicates that probability regressionprecipitation categorical forecast is better than regression precipitation categorical forecast.Especiallywhen forecasting light rain, the TS score averaged over China using probability regression method is higher than that of regression precipitation categorical forecast, the false alarm ratio is obviously smaller, andalso the forecast bias is closer to 1.Through the analysis of predictors and variance contribution of singlesample, the cause of these differences becomes obvious.In regression categorical forecast, the variancecontribution of a few heavy rain samples is too large.It results in the relation of predictors and precipitation mainly reflected those minority heavy rain samples.That is why the false alarm ratio of regression categorical forecast is too high.It can be shown in comparing analysis that the probability regression categorical precipitation forecast is better than direct model precipitation forecast and the situation that false alarmratio is too high is improved.

Determination on the North Boundary of Summer Monsoon in East Asian with Soaking Rainfall

Huang Fei, Li Dongliang, Tang Xu, Wang Shigong, Wang Hui

2009, 20(5): 530-538.

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Abstract:
The summer monsoon brings plentiful water vapor, which is important for vegetation's growth andpeople's subsistence.T he relation between monsoon's northward advance and north boundary's locationis consanguineous.There are many monsoon indexes, and nor thward advancing of summer monsoon hasalso been investigated a lot.The research method considering vegetation growth angles proves to be accordant with the monsoon's influences on China. Station data and grid data including the daily rainfall dataof 715 stations of China from 1951 to 2006 are used to depict the summer monsoon's advancing process.Moisture transport is also investigated using NCEP/NCAR monthly mean and daily reanalysis data. First, the soaking rainfall index is defined to determine the East Asian summer monsoon area.It takes appearingsix times and more soaking rainfall (20 mm) processes during April to October as the standard, then theboundary belt positions for summer monsoon are defined according to the range of six times soaking rainfalllines waving variance annually, and wind vector changes in the boundary belt.Analyzing the continual soaking rainfall processes, the time when periods of drought ends is defined as the start time for summer monsoon in East Asian.This start time can represent the summer monsoon's northward advance.Besides, thecharacteristics of annual and decade variance of East Asian summer monsoon's north boundary and the variance of boundary belt's scopes are analyzed.Furthermore, the advanced process of East Asian summermonsoon's north boundary and its influence to the rainfall in China are investigated.To seek the cause about north boundary for summer monsoon waving unconventionally, it is important to analyze moisturetransport which maybe one important gene.The results show that : the soaking rainfall standard ascertainsboundary belt location for East Asian summer monsoon preferably, and it appears a tendency of southwardmoving and the scopes of boundary belt are enlarged.In brief, the location variance of East Asian summermonsoon's north boundary have a close correlation with south wind strength and moisture transport.It also has a certain influence to the rain band distribution of China as well as the precipitation in north of China, north boundary inclined north, also does the rain band, and the rainfall is relatively more in the northof China.

Temporal Change of Warm Winter Events over the Last 56 Years in China

Chen Yu, Ren Guoyu, Wang Ling, Zou Xukai, Zhang Qiang

2009, 20(5): 539-545.

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Abstract:
The climate of China is now clearly in the global warming up trend, in which the winter warming of thenorthern China is the most obvious.The influence of the warm winter upon the human society is omnibearing, including the direct or indirect impact on human health, daily life, economy activity, agriculture product and ecological environment.Generally, the warm winter means that the air temperature of winter is higher than the climatenormal values (the winter air temperature climatology value from 1971 to 2000).According to the China nationalstandard, the warm winter is classified into two groups by space and intensity grades.In the space group the warmwinter is divided into three spatial grads as sing le station warm winter, regional warm winter, and national warmwinter.In the intensity group, there are two grades as weak warm winter (warm winter) and strong warm winter.Average winter air temperature is divided into 3 probability categories to define the threshold of warm winter forsingle station and its warm winter intensity.Then the division criterions for regional and national winter warm intensity are calculated according to percentile rank of warm winter stations and areas respectively.On the basis of the new division method for warm winter, the characteristics of warm winter since 1952 in China are analyzed too.The analysis reveals that the southern China has a higher frequency of warm winter than northern China, while inmid-west China region strong warm winter occurs more frequently.The rising amplitude of warm winter index islarger in northern China than that in southern part, indicating that the warming trend in northern China is moreobvious.During 1952 to 1985, the occurrence of warm winter is rare in the nation-wide of China, when the frequency of warm winter in southern part of China is slightly higher than that happens in the northern part of China.The incidence of warm winter changes from the year of 1986.The number of warm winter year increases since1986 both in southern and northern China with that of northern part increasing significantly.The results also showthat there are 15 national warm winter years over 56 years with 5 strong warm winters.National warm winter index has an obvious rising trend at a warm winter area rate of 10%per 10 years.However, the air temperature hasgreat year -to-year variations, the possible abnormal cold winter should be properly considered even in the obviousglobal warming trend, and hence impacts of the cold winter shouldn't be neglected.

Assessment Analysis on Winter and Spring Temperature and Rainfall Forecasts over China with Regional Climate Model

Sun Linhai, Ai Wanxiu, Song Wenling, Liu Yiming

2009, 20(5): 546-554.

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Abstract:
Regional climate model of National Climate Center (RegCM_NCC) is developed from the second generation regional climate model (RegCM2) of NCAR.Horizontal resolution of RegCM_NCC is 60 km, andthe center position is 35°N, 110°E, with 151 by 79 g rids, covering most areas of the East Asian.The vertical dimension is divided into 16 layers, and the top-level atmospheric pressure is 100 hPa.15 laps are adopted for buffer zone.The initial and lateral boundary conditions come from the corresponding nested National Climate Center global coupled model (CGCM_NCC).In order to study the prediction ability of RegCM_NCC, operational assessment (five parameters) ofNational Climate Center are used to assess the hindcast of average temperature and precipitation of RegCM_NCC from 1983 to 2002 in winter and 1984 to 2003 in spring, as well as the real-time forecasting from2003 to 2007.The hindcast of ave rage temperature in winter by RegCM_NCC for 20 years is similar to the observation.The forecast of the average temperature is low er than the observation in general.The hindcast ofprecipitation distribution in winter is obviously different from the observation.Forecasts of precipitationare in southwest China are especially inaccurate.The correlation coefficient distributions of the averagetemperature and precipitation between the forecast and the observation in most areas are positive.The P score of w inter average temperature in most years are greater than 60, and the average is 66.4.The ACC of winter average temperature is -0.7—0.4 and the average is -0.07.The P score of the winter precipitation in most years are 60—80 and the average is 69.9.The ACC of precipitation are -0.2—0.5, with the average of 0.05.The hindcast of average temperature in spring by RegCM_NCC for 20 years is similar to the observation.The forecast of average temperature in eastern China is higher, and that in western China is low erthan observation.There are great differences between hindcast of spring precipitation distribution and theobservation.In southwest China the precipitation forecasts accuracy is rather poor.The correlation coefficient distributions of the average temperature between the forecast and the observation in most area arepositive.Negative correlation distribution of precipitation is to the north of the Yangtze River.The P score of the spring average temperature in most years are greater than 60, and the average is67.8.The ACC of spring average temperature is -0.5—0.5 and the average is 0.05.The P score of thespring precipitation in most years are 60—75 and the average is 65.6.The ACC of precipitation are-0.4—0.3, with the average of -0.01.The assessment of the forecasts with regional climate model of National Climate Center approve s themodel' s ability in forecasting average temperature and precipitation in winter and spring.The forecastinglevel needs further improving for the low mean score and ACC.

Climatological Characteristics of Tropical Cyclones in the Northwestern Pacific

Zhao Shanshan, Gao Ge, Sun Xuguang, Yang Xiuqun

2009, 20(5): 555-563.

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Abstract:
Climatological characteristics of tropical cyclones in the Northwestern Pacific during 1951—2006 areinvestigated based on the tropical cyclone best track data from China Meteorological Administration.Tropical cyclones are classified into 6 different categories to study the long-term variation under the global warming background.From 1951 to 2006, nearly 33.9 tropical cyclones occur in the Northwestern Pacific every year.Tropical depressions contribute 18.8% and super typhoons contribute 17.8%.The total frequency of tropical cyclones in the Northwestern Pacific decreases since 1950s and the decreasing trend is1.8 times every 10 years.Frequency of tropical cyclones is highest in 1967 and lo west in 1998.The decrease trend of tropical cyclones frequency is mainly caused by tropical depression and super typhoon Ⅱ(maximum wind≥58 m · s ^-1, super typhoon Ⅱ for simple).The decrease trend of super typhoon Ⅱ ismost remarkable.Contributions of tropical depression and super typhoon Ⅱ frequencies decrease whilecontributions of other categories increase.Characteristics of frequency, intensity, the first and last date of super typhoon Ⅱ are different fromthose of other categories.About 56.3%of tropical cyclones in the Northwestern Pacific appear in summerseason, especially in August.The average monthly frequency is 7.9 in August and 0.3 in February.Withthe growing intensity of tropical cyclone, the maximum frequency postulate from August to October.Themaxim um frequency of super typhoon appears in autumn while those of other categories appear in August.Monthly frequencies of tropical depression and super typhoon Ⅱ take on decrease trends in autumn whilethose of other categories don' t show remarkable trends.The annual variations of super typhoon Ⅱ arenegative related with the annual variations of other categories except super typhoon Ⅰ.Yearly mean maxim um speed and minimum depression of tropical cyclones show a decrease trend.Yearly maximum speed oftropical cyclones decreases about 6.5 m · s ^-1 every 10 years, while yearly minimum depression has increased especially since 1987.Decrease trend of maximum speed is mainly caused by the decrease frequencyof super typhoon Ⅱ.The average first date of tropical cyclones is around 20 February and the average lastdate of tropical cyclones is around 15 December.The first date of tropical cyclones shows a slight delayingtrend.The first date of super typhoon Ⅱ have remarkable long-term delaying trend of 25 day s every 10y ears while the last date displays long-term advancing trend of 9 day s every 10 years.The last date of tropical storm has delaying trend while that of super typhoon Ⅰ has advancing trend.

Case Study of Big Particles Effect on Lightning Initiation in Clouds Using Model

Wang Fei, Dong Wansheng, Zhang Yijun, Ma Ming

2009, 20(5): 564-570.

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Abstract:
A thunderstorm process in Beijing on 20 September 2008 is simulated using a 3-D charging-dischargingcloud model. The effects of big particles consisting of graupels, ices, hails and raindrops on lightning initiation are investigated.Temporal and spatial analysis on the model results, including the mass concentration and the charging velocity, shows that graupels and ices are the most important particles that affect theinitiation of most lightning.Because lightning always initiate in the region with mass distribution of graupels and ices.The charging velocities of graupels and ices also reach large values there.From the analysisof time series, those large charging velocities of graupels and ices appear when lightning initiate intensively.Hails may also be an important factor effecting the lightning initiation except for the early stage oflightning activity.The region of lightning initiation correlates partially with the mass contribution of hails.The period when the charging velocities of hails reach their large values chimes with the lightning activity.But hails meet their large values below the height of lightning initiation.At the early stage of lightning activity, the mass concentration of hails is very small.Raindrops locates beneath the region of lightning initiation from beginning to end.Their charging velocities become prominent after the end of lightning activity.So it is impossible for raindrops to affect the lightning initiation directly.In many cases, it can be the signal of lightning warning that some kind of strong echo reaches athreshold height.Through the effect of particles on lightning initiation above, it can be concluded that thestrong echo should be caused by graupels or hails.When graupels (hails) are brought to the upper level above the threshold height by updraft, graupels (hails) mixed with ices adequately and the strong chargingprocess occurs among them.The first lightning will initiate soon after that.

Analysis and Validation of Total Cloud Amount Data in China

Liu Ruixia, Chen Hongbin, Zheng Zhaojun, Liu Nianqing, Shi Chunxiang, Liu Yujie

2009, 20(5): 571-578.

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Abstract:
ISCCP, station observation and MODIS data are the major sources for cloud am unt so far.Cloud amount is crucial for climate analysis and climate model modulating.These three types of cloud amount data, especially the ISCCP and station observations are compared because they are of long term sequence, and the quantity results are given for future reference.Cloud amount data from ISCCP, station observations and MODIS in January and July 2004 are selected.Their spatial and temporal distribution characteristics are compared, and then the absolute error, relative error, bias, root-mean-square error and correlation coefficient between them are calculated in order toestimate the differences between them quantificationally.The analysis show that spatial distribution of cloud amount from ISCCP and station observation inJanuary and July are similar, but the high and low value regions don't match very well in Tianshan Mountain and Northeast China in January, especially at night.The disagreement may come from observation error in station data.The data at night in these two regions should be used carefully.In January the correlation coefficient between cloud amount from ISCCP and station observation is 0.59, the absolute error is2.56, the relative error is 1.49, the bias is 0.99 and the root-mean-square error is 3.55.In July, the correlation coefficient between them is 0.67, the absolute error is 2.06, the relative error is 0.85, the bias is1.13 and the root-mean-square error is 2.9.The comparison of cloud amount from ISCCP, station observations and MODIS shows that in Januarythe cloud amount derived from MODIS is the largest, but in July it is the smallest.And in January the correlation coefficient between cloud amount from MODIS and station observations is 0.5, absolute error is3.15, relative error is 1.5, bias is 2.0 and root-mean-square error is 4.1.In July the correlation coefficientbetween them is 0.69, absolute error is 1.96, relative error is 0.77, bias is 0.52 and root-mean-square error is 2.83.There is systematic error between cloud amount from satellite and ground station observations, so it'snecessary to correct it.Above all, the cloud amount data from ISCCP is of long time series and global.Its accuracy, spatialand temporal resolutions can meet climate research needs in main.

Characteristics of Meteorological Elements During Typhoon Kalmaegi Observed by Unmanned Aerial Vehicle

Li Yang, Ma Shuqing, Wang Guorong, Sun Zhaobin, Li Xiaoxia, Guan Fushun, Lin Juhong

2009, 20(5): 579-585.

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Abstract:
China is one of the countries where meteorological disasters happen frequently, and typhoon is one ofthe most serious disasters.Meteorological Observation Center of China Meteorological Administrationhave carried out typhoon observation experiment by unmanned aerial vehicle (UAV) in 2008.For the first time, UAV is used to observe typhoon Kalmaegion 18 July 2008, and it is a successfulfield campaign.The UAV sends back data and lands safely after the observation.The UAV flies directlytowards the typhon center and observes the temperature, relative humidity, pressure, wind direction andwind speed with onboard meteorological sensors.It takes almost 4 hours to observe the meteorological elements, the cruising altitude of UAV is 500 m and the nearest distance to typhoon center is about108.4 km.The meteorological elements such as air temperature, pressure, relative humidity, wind direction, wind speed and altitude are received successfully during the observation period.The UAV fliesthrough precipitation area, upwind area, strong convection and such serious flight environment.Thus aquasi-real-time observation system with the capability of flight observing, data collecting, processing anddistributing is established.The observation data reflects some basic characteristics of typhoon, showing that pressure and altitudehave good correlation (r=-0.98). Closer to the typhoon center, pressure is lower and wind speed ishigher.Gradients of temperature is about -1.02 ℃/100 m from ground to 300 m and about -0.46 ℃/100 m from 300 m to 500 m.The temperature varies largely with the height in the near surface layer, which shows that the ground surface has much influence on the temperature.During the observation period, the maximum wind velocity is about 22.3 m · s ^-1 with the average of about 15.1 m · s ^-1.Closer to the typhoon center, higher the relative humidity is.When the UAV arrives at the destination and returns, therelative humidity is 100%and after that it decreases.It can be concluded that when the relative humidity ishigh, UAV flies in the precipitation area.It also shows the waterproof performance of UAV is good, which ensures it fly normally in the precipitation weather.

Evaluation for Retrieving Precision and Some Merits of COSMIC Data

Du Ming bin, Yang Yinming, Ding Jincai

2009, 20(5): 586-593.

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Abstract:
The COSMIC (Constellation Observing System for Meteorology Ionosphere and Climate) consists of six Low Earth Orbit (LEO) satellites. Based on the GPS signals observed by LEO in the occultation condition of the GPS satellites, the profiles of atmospheric temperature, pressure, humidity and ionosphere are retrieved. COSMIC provides these to about 2000 to 3000 GPS soundings globally every day since September 2006, and it can be the effective supplementary of regular radiosonde. COSMIC data is collected in the area of China and Northwest Pacific during the period of January to October in 2007.And the precision, applicability and characteristics of fitting all weather condition are evaluated by the error statistics based on radiosonde data. The results show that the accuracy of temperature profiles retrieved from COSMIC is excellent. The root-mean-square error (RMS) is less than 2 K and the relative error is less than 1%. The retrieved refractivity above 500 hPa level is very accurate, with the RM S less than 1, while under 500 hPa level the RMS increases from 1 to 10 near the ground. The precision of water vapor is high above 500 hPa level, but the RMS increases linearly from 0.2 hPa or less to 2 hPa near the ground under 500 hPa level. Meanwhile the error comparison between COSMIC data and NCEP (National Center of Environment Precipitation) reanalysis data shows that COSMIC data have higher accuracy than NC EP in vapor pressure and refractivity, for instance, the relative error of vapor pressure of COSMIC is 2%-5% less than NCEP data. Additionally two COSMIC occultation events in the clouds are studied to compare COSMIC data with the nearby radiosonde and airborne dropsonde observations. It' s validated that the profiles of the temperature, vapor pressure and refractivity of COSMIC data coincide well with the corresponding radiosonde profiles, so the COSMIC data are appropriate under all weather condition.

A Process of Hydrometeor Phase Change with Dual-polarimetric Radar

Cheng Zhoujie, Liu Xianxun, Zhu Yaping

2009, 20(5): 594-601.

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Abstract:
The phase of hydrometeor is one of the most important microphysics characteristics of cloud. The development of dual-polarimetric weather radar makes the retrieval of the hydrometeor phases possible theoretically, which has been one of the hottest applications of the dual-polarimetric radar. The fuzzy logic has been extensively used in the classification of hydrometeor now, and become the dominant technique in this field. Th rough continuously studying in statistics with more and more in situ measurements, the parameters in fuzzy logic algorithm have become relatively steady for individual dual-polarimetric radar in operational use. The evolution of hydrometeor phase in the cloud process is an important aspect to the research of water microphysical circular in the cloud-precipitation system, and plays great role in many meteorological fields, such as weather modification, aviation security, weather model, and so on. How ever the studies on the changing of the hydrometeor phase with time series of radar data are relatively immature, publications in which are seldom seen. A fuzzy logic system for classifying hydrometeors based on the combination of polarimetric radar measurements and conventional observation data is described, and a Beta membership function is utilized for the fuzzification, the parameters of which are also given based on the former statistics achievements for the S-band radar.The input variables include radar reflectivity, L_DR, Z_DR and the height of 0℃ and -40℃ layer, and the output types are drizzle, rain, low-density dry ice crystal, highdensity dry ice crystal, wet ice crystal, dry graupel, wet graupel, small hail, large hail, sleet, and cloud droplet. Then a case study on an evolution of the hydrometeor phase in a stratiform cloud precipitation process is analyzed based on the CAM Ra radar and RAOBs data, which takes place at Chilbolton the UK summer morning, and lasts approximate 39 minutes. The whole process is divided into three phases including the initial phase, mature phase and the dissipating phase, for each phase a analysis on the changing of the hydrometeor type is given based on the classified results of all the radar observations in it, and the results show that in the initial phase stratiform cloud has a layered structure of hydrometeor types including high-density dry ice, wet ice crystal and liquid droplet from top to bottom; the core of the large-echo region is filled by large ice crystals, and the other area in the large-echo region is filled by liquid hydrometeors in initial phase; from initial phase to mature phase liquid hydrometeors on the top of the large-echo region have a trend of freezing; in the dissipating phase the 0℃ layer bright band disappears gradually, on the top of which a wet ice crystals are wrapped by high-density dry crystal.

The Variation of Ozone Concentrations in Urban Districts of Hangzhou and Their Relationship with Meteorological Factors

Hong Shengmao, Jiao Li, He Xi, Zhou Chunyu

2009, 20(5): 602-611.

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Abstract:
Based on the observation data of near surface O₃ and meteorological factors in 7 monitoring sites of Hangzhou urban area from 2005 to 2007, the O₃ concentration and their temporal variation characteristics are researched. The peak hourly concentration and its nonattainment rate of Hangzhou are compared with those of other major cities at home and abroad. The variation of O₃ concentration and its nonattainment rate under different weather conditions are studied, and the variation of O₃ concentration with different levels of UV intense is discussed. The results show that the ozone concentration increases significantly year by year, the annual mean ozone concentration and the peak hourly concentration in 2007 are 44 μg.m^-3 and 348 μg.m^-3, respectively, showing a growth of about 20%from 2006. The ozone nonattainment rate in 2007 is 13.2%, about twice as high as that in 2006. The percentages of ozone nonattainment days from June to September are 75% in total nonattainment days. The appearing time of ozone nonattainment is from 10:00 to 18:00, and the most frequent appearing time of highest nonattainment concentration is around 14:00. The higher ozone nonattainment rate occurs in summer, primarily under the wind direction of SSE, lower in spring, still lower in fall, and the low est value occurs in winter, taking on a very obvious seasonal variation trend. The variation of ozone concentration in sites differs during four seasons, showing highest concentration in summer and lowest in winter where concentration are higher, but on the others sites highest value occurs in spring and lowest in winter. The diurnal mean concentration during the rainy season is low er with effects of air mass and meteorological conditions brought by summer monsoon. The diurnal variation ranges of ozone concentration are different in four seasons, showing higher peak value and low er valley in summer and fall. The concentrations of peak and valley are all low er in winter. The diurnal variation range of higher concentration sites is bigger than that of lower concentration sites. The peak hourly concentration in Hangzhou is close to the levels of Texas, US and Hong Kong, China, but the nonattainment range is higher. During the daytime, the highest ozone concentration occurs under the wind direction of SE, and during nighttime under the wind direction of E. The variation of ozone concentration changes with synoptic systems. The ozone concentrations in areas controlled by high pressure passage and high pressure systems are higher, and percentages of nonattainment days are 37.8% and 24.4% respectively. The ozone concentration is higher on the UV intense days. The ozone concentration and intensity of UV radiation are significantly correlated. The results of multiple regression analysis between ozone concentrations and various weather factors show that the temperature, relative humidity, duration of sunshine are major factors that affect ozone concentration. The ozone concentration is remarkable negatively correlated with relative humidity and visibility (P < 0.05), and is significantly positively correlated with the temperature and sunshine (P < 0.05). The cause is that higher temperature, lower relative humidity and longer time of sunshine may accelerate the rate of photochemical reaction, which has a positive impact on O₃ generation, and leads to higher concentration of ozone, otherwise ozone concentration is lower.

The Analysis and Simulation of an Advection FogEvent in Beijing

Liang Aimin, Zhang Qinghong, Qing hong, Liu Kaiyu, Li Xiulian, Feng Jianbi

2009, 20(5): 612-621.

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Abstract:
A dense advection fog event occurs in Beijing on 21 February 2007. Since the fog occurs during the Chinese Spring Festival, this unexpected event makes a mess of the traffic. The surface observation data of the Beijing Capital International Airport, the auto-observations across Beijing area and NCEP 1°×1°analysis are used to analyze this process. And a numerical simulation is made using the meso-scale model MM5. The analyses and simulation show that weak convergent low is the primary weather pattern of the dense fog event. There is no obvious cold air intruding and the atmospheric stratification is relatively stable prior to the event. Meanwhile there is a meso-scale surface convergent line, at the south of which moisture is transported to Beijing area by the southeast airflow. These weather conditions offer good basic conditions for the night-fog formation. The simulation of this advection fog event indicates that the simulated fog area and the motion are basically coincided with the actual situation, which show the potential ability of MM5 to forecast advection fog event. And further analyses shows that 6-7 h before the occurrence of the fog, inversion layer first occurs in the ground layer, and then the inversion layer top continuously rises and becomes thicker. Moreover, the coincidence or the separation of temperature curve and dew-point curve correlate with the occurrence or dissipation of fog. Besides, there is obvious horizontal temperature gradient at the front edge of the fog area, and at the surface layer southeast airflow is blocked by the fog and turns to west, then converges at the front edge of the fog. In addition, below 930 hPa, at the front edge of the vertical temperature inversion area, there is a vertical thermodynamic circulation with downdraft at the fog area and updraft at the front edge of the fog area. During the event, there is a complete warm center above the fog area, thick inversion layer and weak updraft. Such stable situation causes the long duration of the fog. And during the dissipation of fog, the large area of fog is separated into patches. In some areas where temperature rises faster, the stronger ascending motion destroys the inversion, so the fog area reduces as a result.

Method for Dynamic Forecast of Corn Yield Based on Climatic Suitability

Wei Ruijiang, Song Yingbo, Wang Xin

2009, 20(5): 622-627.

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Abstract:
Summer corn is one of the major grain crops in Hebei Province.Its growing development and yield formation are influenced by weather conditions during the growing and maturity seasons. So it is of great significance to forecast the yield dynamically for agricultural production and food security of Hebei Province. Operational weather forecast for crop yield has a history over 20 years in China, laying the foundation for the application of yield forecast. How ever, many of the crop yield forecasting methods are carried out at fixed time. Dynamical forecast that tracks the whole growth period of crops and considers the three typical climatic factors (sunshine, temperature and precipitation), is rarely carried out.There are some attempts that establish comprehensive climate models based on related analysis between crops and weather conditions considering the whole growth period of crops affected by the three factors. But it hasn't been done much to use the climate suitability for yield forecast.Meteorological data from the Hebei Meteorological Bureau are adopted, including temperature, precipitation and sunlight hours per ten-day period from 1972 to 2005 in the eight representative summer corn producing cities (Tangshan, Langfang, Baoding, Shijiazhuang, Cangzhou, Hengshui, Xingtai and Handan). The annual corn yield per unit data from the Hebei Province Statistics Bureau are used for research. Based on the physiological characteristics of summer corn, temperature suitability model, precipitation suitability model, sunshine suitability model and general climatic suitability model are established. Then the climatic suitability of every ten days during the corn growing period over the eight cities is calculated for the years of 1972 -2005. Correlation analysis results betw een climatic suitability and the corresponding yield fluctuation quantity indicate that the relationship betw een them is remarkable, and the climatic suitability model of summer corn can reflect the climate and its dynamic changes in Hebei Province objectively. Taking the climatic suitability of every ten days during the growing period as the basis, the dynamical forecasting models of eight regions from 1972 to 2005 in Hebei Province have been established at different stages using the statistical analysis software SPSS.The average accuracy of the forecasting model by yield fitting validation is 88.8% for historical forecasting during 1972-2005 and 96.8% for a rolling yield forecasting during 2006-2007 respectively, proving the model applicable to operational service. The model should be further optimized in future work owing to imperfection in the precipitation suitability model, and the lagged effect of pre-precipitation should be brought into consideration.

Oceanic Evaporation Duct Diagnosis Model Based on Air-sea Flux Algorithm

Li Yunbo, Zhang Yonggang, Tang Haichuan, Wang Hua, Jiao Lin

2009, 20(5): 628-633.

[FullText HTML] (776) [PDF 955KB](2004)

Abstract:
Evaporation duct is a prevailing weather phenomenon that occurs on the sea, which is also the most important factor of anomalous propagation of electromagnetic wave. It influences the application of radar, correspondence and electronic equipment seriously. But there are some problems in the evaporation duct diagnosis model. For example, the diagnostic precision of many empirical functions summarized in land trials, is not validated in oceanic environment; the practicability of Monin-Obukhov Similarity Theory (MOST) in very low wind speed is limited; the seawater salinity has influences on water vapor press. TOGA COA RE flux algorithm supplies so me conditions for the precise diagnosis of Oceanic evaporation duct. Utilizing COARE 3.0 flux algorithm by Fairall and "gustiness" by Godfrey et al, the traditional MOST is appropriate to low wind speed condition, and evaporation duct model is established based on the flux algorithm (called Flux Evaporation Duct Model) combined with the precise atmospheric refractive index formula. Using the tower actual observation data in Ping tan Island during May, the Flux Evaporation Duct Model is compared with US Navy's Paulus-Jeske Model on evaporation duct height (EDH) and the profile of modified refractivity M. Gene rally speaking, the EDH calculated by the Flux Evaporation Duct Model is close to the actual data, superior to Paulus-Jeske Model obviously.But the two models' precision in the unstable cases is better than the stable cases. M-profiles computed by the Flux Model tally with the iron tower fitting results, the profile curvature computed by PJ Model is better, but there is obvious deviation for M value in the low altitude. In the comparison, it's found the EDH diagnosis accuracy does not mean the M profiles tally with the actual situation. Finally, using the marine radar sounding trial data in 2002, it's further verified the result that the Flux Model is able to provide good duct environment parameters for marine electro magnetic propagation computation and increase the precision of the radar sounding performance.

Asymmetric Trends of Daily Maximum and Minimum Temperature in Global Warming and Its Effects on Agriculture Ecosystems

Tan Kaiyan, Fang Shibo, Ren Sanxue, Zhang Xinshi

2009, 20(5): 634-641.

[FullText HTML] (798) [PDF 422KB](2216)

Abstract:
Some recent major research findings on trends of daily maximum and minim um temperature in global warming and warming experiments in agro-ecosystems are summarized briefly.Investigating the daily mean maximum and minimum temperatures of the Northern Hemisphere landmass, it's found that the rising rate of the minim um temperature is 2—3 times as big as that of the maximum temperature during the period of 1950—1993. It indicates that the daily mean maximum and minim um temperatures rising are asymmetry. The largest increase in temperature occurs in wintertime and springtime, implying that temperature increase is asymmetry in seasons too. Similar trends are observed for the past 52 years (1951—2002) in China.The agro-ecosystems response to temperature increasing in asymmetric trends is introduced in detail. As for the rise of the minimum temperature, almost all researches confirm that the growing season has been extended and the spring crops phenological phases have become earlier than before. The minimum temperature and the maximum temperature have different effects on different crops' phenological calendar and on one crop's different phenological phases. Most of the existing reports about agro-ecosystems response to temperature increase concentrate on crops model simulation and statistic description. And most of the results show that increasing temperature has made the growth period shorter and the ripe date earlier. As for these causes, some studies imply that it could cut down the crops yields.But others consider that increasing minimum temperature will lessen the danger of crop chill injury, and will improve the crops yields. Some studies also suggest that the temperature rising, especially the daily maximum temperature rising has nonlinear effects on corn yields. Thus the roles of minimum temperature and maximum temperature to crops grow and yields are still uncertain. The temperature also plays an important role in controlling the soil CO₂ releases. Most of experiments about temperature rising are conducted in OTC (open-top chamber) or greenhouse, where the maximum temperature is increased much more than the minimum temperature (the minimum temperature are almost unchanged comparing with blank). Therefore, all the OTC and greenhouse experiments are mainly set to simulate the effects of the maximum temperature rising on crops. A recently reported method designed to simulate minimum temperature rising is also reviewed. Minimum temperature rising experiments have been carried out on grassland and forest ecosystems, but the experiments in agro-ecosystems are seldom reported.

Design and Implementation of Resource Monitor Module in Meteorological Computational Grid Platform

Wang Bin, Chang Biao, Zhu Jiang, Liu Chunhua

2009, 20(5): 642-648.

[FullText HTML] (777) [PDF 1106KB](1938)

Abstract:
Computing resources, aggregated by meteorological computational Grid, are composed of high performance computers and storage resources.These resources are installed in different areas with different system structures, running conditions and workloads. In order to monitor the status of resources in meteorological computational Grid and to provide users and administrators with reference information, resource monitor module is designed and implemented as part of meteorological computational Grid platform software system.The resource monitor module involves 3 layers : remote meteorological Grid nodes, resource state information acquisition, and web representation.Resource state describes the system information of high performance computers in a meteorological Grid node, comprising 3 major parts, overall information, nodes information and jobs information. The layer of resource state information acquisition is made up of poller, collector, feeder and related configuration files.Correspondingly, the acquisition process of resource state information in the resource monitor module can be divided into 3 parts, polling, collecting and feeding. Web representation layer is on the top and provides users with resource state information through commonly used internet browsers.The resource monitor module is developed based on Grid management software UNICORE and client software ARCON Client, and implemented with Java and XML technology. ARCON Client Toolkit is used to implement node accessing function in the resource monitor module. The poller submits querying jobs for status information to computers in Grid nodes automatically and termly, and pushes it into the log queue when a job is submitted.The collector reads the queue and retrieves results of query. The feeder parses the results and writes a specially formatted XML file. The code of querying and retrieving is asynchronous so as to avoid waiting in querying. As a result, the monitor program runs stably and robustly. Major packages of resource state information acquisition layer are base driver, job scheduling, log queue query, resource state parsing, and configuration setting etc. The web representation reads the XML file containing the resource state query results, and implements resource state displaying via Flex and J2EE technologies.At present, 10 high performance computers have been brought into centralized monitoring in National Meteorological Information Center, Beijing, Chengdu, Guangzhou, Shenyang Regional Centers as well as Anhui Province. Resource monitor module is one of the key parts of meteorological Grid platform software system and providing real time services.In the future, with the further construction of meteorological computational Grid, the resource monitor module will see further application and put major computing resources in meteorological department into supervision.

Vol.20, NO.5, 2009