大氣物理與人工影響天氣
Atmospheric Physics and Weather Modifcation

云降水物理與人工影響天氣研究進展

1 云霧物理觀測與數(shù)值模擬研究

1.1 環(huán)北京春季大氣氣溶膠分布、來源及其與CCN轉(zhuǎn)化關(guān)系的飛機探測

利用2009 年春季開展的“環(huán)北京云觀測試驗”觀測的氣溶膠和云凝結(jié)核(CCN)數(shù)據(jù)，研究了試驗期間大氣氣溶膠的分布、來源特征及其與CCN的轉(zhuǎn)化關(guān)系。結(jié)果表明，高濃度氣溶膠基本分布在4500 m以下的區(qū)域，量級可以達到103cm-3。4500 m以上氣溶膠呈顯著下降趨勢，量級僅為10 cm-3；氣溶膠平均直徑在0.16～0.19 μm之間。4500 m以下氣溶膠平均粒子譜呈雙(多)峰分布，而在4500 m以上基本為單峰分布。受氣溶膠來源特性差異的影響，在0.3%的過飽和度下，4500 m以下氣溶膠轉(zhuǎn)化為CCN比例不到20%，但在4500 m以上可高達近50%。氣團移動軌跡顯示，4500 m以上的大氣高層均受到來自沙塵等較大尺度粒子的影響，飛機觀測的高CCN 濃度說明這種較大尺度氣溶膠粒子可溶性較大。而4500 m以下的低層，由于受到局地或區(qū)域地面污染的影響，氣溶膠的尺度較小，核化為CCN的過飽和度要求較高，因此氣溶膠到CCN 的轉(zhuǎn)化率低。同時建立了氣溶膠濃度和CCN 濃度的擬合關(guān)系。(盧廣獻)

1.2 人為污染物對冬季霧形成和發(fā)展的影響研究

基于WRF/Chem模式和霧的觀測資料，開展了包含和不包含人為污染排放源兩種大氣背景條件下的數(shù)值模擬對比試驗，在此基礎上探討了人為污染物對2009年12月1日發(fā)生在我國華北和華東地區(qū)的一次濃霧天氣過程的影響機理。結(jié)果表明，在考慮污染排放源時，模式模擬的霧的空間分布和強度變化與衛(wèi)星、能見度儀和微波輻射計的觀測更為接近。污染條件下的邊界層結(jié)構(gòu)更有利于霧的形成，人為大氣污染物使霧的范圍最大增加50%，霧的強度最大增加5倍，霧持續(xù)時間平均延長1.5 h。由于人為污染物增加了霧凝結(jié)核（FCN）數(shù)濃度，進而使霧滴數(shù)濃度顯著增大，有利于霧的增強。同時，污染物通過影響霧滴的凝結(jié)過程和潛熱釋放過程，對長波輻射降溫和湍流過程有重要影響，使邊界層的熱力和動力結(jié)構(gòu)更有利于霧的增強和發(fā)展。污染氣體SO2、NOx和NH3排放產(chǎn)生的二次氣溶膠對霧的形成和發(fā)展具有重要影響。不考慮這些污染氣體排放時，平均霧水含量可降低32%。（郭學良）

1.3 颮線災害性大風產(chǎn)生的微物理機理研究

采用衛(wèi)星、雷達及地面加密觀測資料，結(jié)合中尺度WRF數(shù)值模式，研究了河南2009年6月3日颮線產(chǎn)生的天氣背景、宏微觀結(jié)構(gòu)特征及造成災害性大風的機理。結(jié)果表明，此次颮線過程的主要影響系統(tǒng)是東北冷渦，其后部橫槽引導的南下冷空氣與西南暖濕氣流在河南新鄉(xiāng)南部一帶交匯促發(fā)強對流過程，最后演變?yōu)轱R線。但由于低層西南風偏弱，水汽條件不足，颮線發(fā)生的環(huán)境較為干冷。颮線產(chǎn)生區(qū)大氣處于條件性不穩(wěn)定狀態(tài)，對流有效位能（CAPE）在1300 J/kg左右，并具有適當?shù)拇怪憋L切變。地面氣象場顯示颮線具有相對冷濕的雷暴高壓和強冷池，颮線過程產(chǎn)生的災害性天氣以大風而非強降水為主。數(shù)值模式結(jié)果顯示，颮線下沉氣流的最大值僅為13 m/s，而地面風速最大值達到35 m/s，是最大下沉氣流的2.7倍。進一步的數(shù)值敏感試驗表明，降水粒子的蒸發(fā)和融化冷卻過程對降低地面溫度和產(chǎn)生地面強風具有重要影響，其中雨水蒸發(fā)過程產(chǎn)生的最大等效冷卻率為3 K/min，遠大于霰融化冷卻率0.7 K/min，因此雨水蒸發(fā)過程是影響冷池強度的關(guān)鍵因素，而地面強冷池在此次颮線災害性大風的產(chǎn)生中具有重要作用。（郭學良）

1.4 北京周邊細粒子氣溶膠及云凝結(jié)核譜特征分析

利用TSI3936掃描電遷移率粒徑分布譜儀觀測的細粒子氣溶膠與云凝結(jié)核（CCN）計數(shù)器進行對比，結(jié)合周邊地區(qū)大氣顆粒物數(shù)譜分布的主要特征和類型，分析了2011年11月10—15日河北涿州細粒子氣溶膠對CCN形成的影響。結(jié)果表明，細粒子氣溶膠峰值集中在100 nm周圍，午后譜寬最窄且數(shù)濃度最低，主要的氣溶膠來源大部分為交通污染的一次排放；氣溶膠細粒子數(shù)濃度較高時，觀測的CCN數(shù)量在各飽和度條件下一般較高，過飽和度0.6%時，CCN值最高；隨著過飽和度的增加，CCN的譜寬明顯漸寬。11日為霧日及12日晴空無云，細粒子氣溶膠數(shù)濃度對應明顯變小，CCN值也對應減?。?10日雖然氣溶膠細粒子較少，但是不同過飽和度觀測到的CCN值并不很低，這可能是較大粒子活化產(chǎn)生的CCN；由于細粒子主要成分吸濕性不佳，不利于活化，12日凌晨細粒子較多，但活化CCN較小且峰值向較小半徑傾斜（圖1）。（段婧）

2 人工影響天氣研究

2.1 利用AgI催化劑進行華南暴雨人工減雨的數(shù)值試驗

在對流云模式中增加了AgI兩個預報量，耦合了考慮受水汽過飽和度和溫度影響的4種核化機制的AgI催化模塊，使其具備了AgI 類催化劑的模擬能力，能夠研究AgI 類催化劑對對流云系統(tǒng)的影響。利用此模式對一次華南暴雨過程進行了人工緩減暴雨的成冰劑催化數(shù)值模擬試驗。模式采用AgI催化方法，對人工緩減暴雨的可能性及原理進行了研究。模擬結(jié)果表明，在適當?shù)臅r機對適當?shù)牟课贿M行大劑量的催化，可以減少總降水量，也可以減小最大降水中心的雨強。當催化劑量達到2×108（個/kg）時，可以減少39.3%的降水量，具備有效減緩暴雨成災的可能性。大劑量催化后，大量的AgI粒子在冷區(qū)核化，消耗了大量的過冷水。霰粒子的落速和雨水的落速減小，導致了降水量的減少。AgI在對流云中主要以受過飽和度影響的凝結(jié)凍結(jié)和催化劑長時間作用的浸沒凍結(jié)這兩種方式成冰。本研究所用催化方法在實際作業(yè)中具有技術(shù)可行性，并有較大社會和經(jīng)濟效益，值得深入研究和試驗。（樓小鳳）

2.2 北京地區(qū)人工減雨的數(shù)值研究

利用耦合了中國氣象科學研究院復雜雙參數(shù)云物理方案的GRAPES中尺度數(shù)值模式，對2008年夏季北京地區(qū)的降水過程進行了人工減雨的冷云催化數(shù)值試驗，研究了減雨的作業(yè)條件、作業(yè)效果和機制。結(jié)果表明，采用過量播撒冷云催化方法可以引起地面減雨，催化區(qū)適宜設在目標區(qū)上風方過冷水含量豐富的地區(qū)；過量播撒時劑量越大減雨效果越好，并且連續(xù)播撒好于單次播撒；催化引起地面雨量再分布，減雨區(qū)周圍伴有增雨區(qū)，但區(qū)域雨量總體變化為減雨。過量播撒引起微物理量含量和轉(zhuǎn)化過程強度發(fā)生變化，霰的融化、雪的融化和雨滴碰并云滴增長過程受到削弱，使雨水含量減少。同時也發(fā)現(xiàn)，催化也引起動力和熱力場發(fā)生變化，并可能會通過平流擴散等過程產(chǎn)生上下游效應，使催化效應延長。（孫晶）

2.3 巨核對暖云降水的影響

利用耦合了新的暖云參數(shù)化方案的中尺度模式MM5，研究了暖云降水中巨核（GCCN）的作用。在該暖云方案里，先假定一個3模態(tài)的氣溶膠正態(tài)對數(shù)分布，然后考慮對流、擴散、云滴和雨滴的核化非核化過程，再由氣溶膠質(zhì)量的預報量顯式地計算出氣溶膠的數(shù)濃度。以華北地區(qū)2006年6月25—26日的一次弱冷鋒過程為例，研究了巨核對云和降水的影響。研究表明，巨核具有增強雨滴的凝結(jié)、碰并和云雨自動轉(zhuǎn)化過程的作用，使云滴數(shù)減少高達40%，云水減少20%，云滴有效半徑增加高達30%左右。在污染和清潔環(huán)境下巨核均可增加降水（圖2）。（房文，鄭國光）

圖1 2011年11月10—15日河北涿州細粒子氣溶膠和不同過飽和度條件下CCN的小時平均譜的時間變化Fig1 Spectra distribution of fne particle aerosol and CCN under different supersaturation conditions during 10—15 November 2011 over Zhuozhou, Hebei Province, China

圖2 清潔大陸(a～c)、平均大陸(d～f)和北京城市氣溶膠分布(g～i)下模擬的云滴性質(zhì)：云滴數(shù)濃度(a、d、g)，混合比（b、e、h），有效半徑（c、f、i）Fig2 Cloud-drop properties under clean continental (a-c), average continental (d-f), and urban (g-i) aerosol conditions. Averaged cloud-drop number concentrations (a, d, g), mass mixing ratio (b, e, h), and effective radius (c, f, i)

Progress in Studies on Clouds and Precipitation and Weather Modifcation

1 Observational and numerical modeling studies of cloud/fog physics

1.1 Distribution and origin of aerosol and its relationship with CCN based on springtime multi-aircraft measurements of the Beijing Cloud Experiment (BCE)

The atmospheric aerosol distribution, source, and its relationship with cloud condensation nuclei (CCN) observed during the Beijing Cloud Experiment (BCE) are analyzed. The results show that the high number concentration of aerosol was mainly distributed below 4500 m, with the magnitude reaching 103cm-3. Above 4500 m, the aerosol number concentration decreases to 10 cm-3with the increasing altitude, and the aerosol mean diameters were between 0.16 and 0.19 μm. Below 4500 m, the number size distributions of aerosol showed a bimodal (multimodal) mode, and a unimodal mode above it. Due to the different sources of aerosol, the conversion ratios of aerosol to CCN were less than 20% below 4500 m, and reached 50% above the level at 0.3% supersaturation. The back trajectories showed that aerosols at higher levels above 4500 m were strongly affected by large-size particles and those below 4500 m were strongly affected by local or regional pollution. Based on observations, a relationship between the CCN number concentration and aerosol number concentration is established. (Lu Guangxian)

1.2 Impacts of anthropogenic atmospheric pollutant on formation and development of a winter heavy fog event

The WRF/Chem model coupled with local anthropogenic atmospheric pollution emissions and fog observational data were used to assess the effects of human-induced pollutants on a heavy fog event on 1 December 2009 in North China and East China. The experiments with and without anthropogenic emissions were designed and conducted. The results suggest that the simulated fog distribution and intensity with anthropogenic emission are closer to observed ones. The polluted atmospheric boundary layer condition is found to create a favorable condition for fog formation, increasing the fog area by 150%, the intensity of 5 times in maximum, and the duration of additional 1.5 h on average. Compared with that under the clean air condition, the number concentration of fog condensation nuclei (FCN) is much higher in polluted air, which causes a higher fog droplet number concentration, and infuences the processes of droplet condensation, long wave radiation, turbulent motion, and provides the favorable dynamic and thermal boundary conditions for fog development. The secondary aerosols produced by trace gases SO2, NOx, and NH3exert great infuences on the formation and development of fog, and the averaged liquid water content decreases by 32%, without these trace gas emission. (Guo Xueliang)

1.3 Numerical simulation studies on severe surface wind formation mechanism and structural characteristics of a squall line

An unusually severe squall line resulted in significant losses of lives and property on 3 June 2009 in Henan Province, China. To better understand the genesis and development mechanisms of the squall line, the data of satellite, radar, intensive surface observation, and the mesoscale Weather Research and Forecasting (WRF) model were used to investigate the atmospheric background, macrostructure, and microstructure of the squall line and the formation mechanism of the damaging surface wind. The results show that a northeast cold vortex was the main infuencing system of the squall line. The transversal trough located at the back of the northeast cold vortex induced a strong cold airfow, which met a relatively weak southwesterly warm and moist airfow to produce convection. The system further developed in the study region as a severe squall line.The atmosphere contained weak southwesterly winds and water vapor in low layers; thus, the atmospheric environment of the squall line formation was dry. The atmosphere was conditionally unstable with a convective available potential energy (CAPE) index of approximately 1300 J/kg and adequate wind shear. A relatively cold and moist high with thunderstorms and a strong cold pool on the surface field occurred concurrently with the squall line to produce severe surface wind in addition to heavy rain. The results of the WRF model showed that although the maximum downdraft of the squall line was only 13 m/s, the surface outfow wind speed was 35 m/s, which exceeded the maximum downdraft by a factor of 2.7. Further investigation revealed that the cooling processes of rain evaporation and graupel melting were the major contributors to the decrease in surface temperature and strong wind production. Among them, the cooling rate due to rain evaporation was approximately 3 K/min while that due to graupel melting was approximately 0.7 K/min. Therefore, the key factor to infuence the cold pool intensity was rain evaporation; this cold pool played a critical role in the formation of the severe surface winds during the squall line event. (Guo Xueliang)

1.4 Characteristic of spectra of fne particle aerosol and CCN around Beijing, China

The aerosol (from TSI3936) and CCN (from CCN contour) data observed in winter of 2011 over a satellite city of Beijing are used to analyze the distribution of fine particle aerosol and CCN in different weather conditions and their diurnal variation characteristics. In consideration of the characteristics of fine aerosol spectra in the nearby region, the aerosol infuences on CCN formation are investigated preliminarily. The results show that∶ (1) The peak value of fne particle aerosol is concentrated around 100 nm. The aerosol spectra are the narrowest and the aerosol number concentration is the lowest in the afternoon. The pollution emission from automobiles is the main aerosol source. (2) Around 04∶00, there is a lower concentration of aerosol but higher CCN at different supersaturation (SS) conditions. (3) The highest value of CCN appears at 0.6% SS. The spectra are obviously wider with increasing SS. Although the fne particle aerosol concentration is low on 10 November 2011, the CCN concentration is not accordingly low. This may arise from activation of big particles. When more fne particles exist on 12 November, the CCN concentration is low, and the peak value of CCN concentration is low as well (Fig1). (Duan Jing)

2 Weather modifcation studies

2.1 Simulation study on the effect of AgI seeding on heavy rainfall reduction in South China

An AgI seeding scheme is coupled with a three-dimensional cloud model, considering four nucleation modes. A case of heavy rainfall during the South China heavy storm in 1998 is simulated using this model. Numerical seeding experiments of releasing AgI in clouds are conducted to study the possibility of heavy rainfall attenuation through the AgI seeding. Several tests for different locations and with different concentrations of seeding particles are designed. The results show that overseeding in the updraft area with supercooled water can not only reduce the amount of rainfall, but also reduce the maximum rainfall strength. With 2 × 108kg-1seeding concentration, rainfall amount can be decreased by up to 39%, which greatly lowers the possibility of fooding. After seeding with large amounts of AgI, numerous AgI particles are nucleated, and these ice particles consume most supercooled water. The falling speeds of graupel become so smaller (some even weaker than the updraft) that many graupel particles can not fall down to the warm region to melt into raindrops. The bigger number of graupel particles contributes the bigger number of rain droplets with weaker falling speed. The time of peak rainfall is delayed and the duration of peak rainfall is shortened, thus the surface rainfall is decreased. The results also show that condensation freezing and immersion freezing are the dominant nucleation modes in convective clouds. The over-seeding methods used in this investigation are feasible and applicable in practical feld experiments. (Lou Xiaofeng)

2.2 Numerical study on artifcial seeding for rainfall reduction in Beijing

A heavy rainfall episode happened on 14 July 2008 in Beijing. This event is simulated by using the mesoscale model GRAPES coupled with the CAMS (Chinese Academy of Meteorological Sciences) cloud microphysical scheme. Numerical experiments on the effects of adding ice crystals are conducted to study if there is any possibility to decrease the heavy rainfall. Several tests for different seeding times and different concentrations of seeding particles are designed. The results show that overseeding ice particles in cold clouds results in the reduction of rainfall. The seeding area should be selected in the upwind side with lots of supercooled water. The seeding effect is better when the amount of seeding ice particles is higher. Seeding results in the redistribution of rainfall. Several areas with increased rainfall also appeared. After overseeding ice particles, the processes of the graupel and snow melting and the cloud water collection by rain water are weakened. These result in the decreasing of rainfall. The dynamical and thermodynamical processes are altered by the overseeding. The advection and diffusion processes may expand the affecting area. (Sun Jing)

2.3 The effect of GCCN on warm-cloud precipitation

A warm cloud microphysical parameterization was incorporated into a regional model to study the sensitivity of cloud-radiative properties and precipitation to giant cloud condensation nuclei (GCCN) concentration changes. By assuming a tri-modal lognormal aerosol size distribution, the aerosol numbers are explicitly calculated from prognostic aerosol masses, with considerations of advection, diffusion, and cloud and rain drop activation/deactivation processes. Sensitivity experiments of a cold front passing through northern China during 25—27 June 2005 with different initial conditions for clean, continental, and urban types of aerosols were then conducted to study the GCCN effects. It is found that the presence of giant nuclei enhances the condensation, collection, and cloud-rain auto-conversion process, leading to the decreases of cloud drop numbers and cloud water by up to 40% and 20%, respectively, and the increase of cloud drop radius by 30%. The GCCN increases accumulated precipitation in both polluted and clean environments (Fig2). (Fang Wen, Zheng Guoguang)