双叶模型在冬小麦田冠层CO2通量多层模拟中的应用

综合考虑农田生态系统中水、热、CO2输送所涉及的大气、水文、生物等生物物理过程,以Farquhar等提出的叶片尺度光合作用生物化学过程机理模型为理论基础,对其进行空间尺度扩展,并改进冠层分层方法,建立了均匀农田与大气之间物质输送和能量交换的多层模式,在模式中运用双叶模型,同时考虑叶片氮素水平垂直差异,对2008年4—5月华北平原冬小麦生长旺季农田生态系统中冠层CO2通量进行了模拟研究,并利用涡度相关观测的通量数据对模型的有效性加以验证,结果表明:在冠层多层空间,小麦拔节至孕穗期和开花至乳熟期叶片氮含量随冠层高度的衰减系数分别为0.793(R2=0.698)和1.374(R2=0.728),冠层内叶片氮含量的空间分布可以用以相对累积叶面积指数为自变量的函数来描述;模型分别计算各层阴、阳叶的光截取、气孔传导、光合作用等,最终计算冠层上方CO2通量,冬小麦农田净生态系统生产力模拟值与实测值相关显著(R2=0.78),模拟的CO2通量日变化特征晴天昼间比阴雨天和夜间的效果好;在考虑丛聚影响的叶片非随机分布的密集农田中,阴叶对总初始生产力的贡献率在35.7%左右,对生产力贡献很重要。分层统计显示,作物最终产量的形成主要...     

基于碳水通量耦合原理改进Penman-Monteith蒸散发模型

陆地蒸散(ET)涵括地表和潮湿叶片的蒸发和植物的蒸散发,是陆地水循环的重要组成部分。Penman-Monteith方程是估算陆地蒸散的重要方法,方程中的叶片或冠层气孔导度是提高估算精度的关键因子。根据碳水循环的耦合原理,植物光合作用模型可用于估算叶片或冠层气孔导度。植物光合作用模型可分为三类:1)使用总冠层导度的大叶模型(BL),2)区别阴、阳叶冠层导度的双大叶模型(TBL),3)区别阴、阳叶叶片导度的双叶模型(TL)。与这三类光合作用模型相对应,衍生出基于不同导度计算方法的三种蒸散估算模型。三种蒸散模型之间的主要区别在于是否进行从叶片尺度到冠层尺度的气孔导度集成。这三种模型中,双叶模型使用叶片尺度的气孔导度,集成度最低。反之,大叶模型使用冠层尺度的气孔导度,集成度最高。由于在Penman-Monteith中,蒸腾和气孔导度之间的关系是非线性的,气孔导度的集合会导致负偏差。因此,与通量测量相比,大叶蒸散模型的估算偏差最大,而双叶蒸散模型的估算偏差最小。     

棉花冠层阴阳叶空间分布的日变化及其对光合作用的影响

在2007年7—8月棉花生长旺季,将冠层按高度分多层,通过简单的试验方法确定了棉冠内叶片丛聚指数(clumping index,Ω),以此区分计算出田间各层逐时阳叶(受光叶)和阴叶(被遮荫叶)叶面积指数的动态值。在8月23日用LI-6400R便携式光合测量系统分多层分别测定阴、阳叶单张叶片净光合作用的日变化,结合阴、阳叶面积权重,探讨利用Ω区分阴阳叶之后对整个冠层日总光合作用的影响。试验结果表明:(1)花铃期棉花冠层内Ω约为0.68;(2)利用Ω计算得到8月23日冠层日间(09:00—18:00)总净光合作用日平均值大约为20.3μmol·m-2·s-1,其中阳叶贡献约占总量的72%,阴叶约占总量的28%;(3)上层叶片贡献约占总量的75%,中层叶片约占总量的22%,下层叶片约占总量的3%。     

基于Ｌｏｔｋａ Ｖｏｌｔｅｒｒａ方程的基因调控网络的稳定性分析

在2007年7—8月棉花生长旺季,将冠层按高度分多层,通过简单的试验方法确定了棉冠内叶片丛聚指数（clumping index,Ω）,以此区分计算出田间各层逐时阳叶（受光叶）和阴叶（被遮荫叶）叶面积指数的动态值。在8月23日用LI-6400R便携式光合测量系统分多层分别测定阴、阳叶单张叶片净光合作用的日变化,结合阴、阳叶面积权重,探讨利用Ω区分阴阳叶之后对整个冠层日总光合作用的影响。试验结果表明：（1）花铃期棉花冠层内Ω约为0.68;（2）利用Ω计算得到8月23日冠层日间（09：00—18：00）总净光合作用日平均值大约为20.3μmol·m-2·s-1,其中阳叶贡献约占总量的72%,阴叶约占总量的28%;（3）上层叶片贡献约占总量的75%,中层叶片约占总量的22%,下层叶片约占总量的3%。     

淮北棉区花铃期冠层不同高度叶片光合特性的差异

基于多层二叶模型,在自然群体条件下,将棉花冠层分为上、中、下三层,研究淮北棉花花铃期冠层上、中、下层,阴叶（无直射光照射）与阳叶（有直射光照射）的光合特性的差异。结果表明,同一高度阳叶的光量子通量密度与光合速率显著大于阴叶;不同高度叶片光量子通量密度与光合速率均表现为上层阳叶〉中层阳叶〉下层阳叶,上层阴叶〉中层阴叶〉下层阴叶;上层阳叶气孔导度大于阴叶,中、下层阴、阳叶的气孔导度无显著差异;上部叶片气孔导度〉中部叶片〉下部叶片;同一高度阳叶胞间二氧化碳浓度显著小于阴叶,随着冠层深度（形态学自上而下）的增加,两者差异增大;不同高度叶片胞间二氧化碳浓度随着冠层深度的增加,呈增加趋势,阳叶差异不显著,阴叶差异显著。     

陆面模式的植物叶光合生理的数值模拟试验及分析

根据C3、C4植物生态生理过程中植物叶水平的光合同化机制过程和植物叶片尺度的光合作用限制函数方程。采用单叶光合作用模式进行C3、C4植物光合模拟试验,模拟不同环境影响因子对C3、C4植物光合作用的影响。结果表明,植物叶尺度光合作用模型能较好地模拟不同环境影响因子下的C3、C4植物光合作用状况。本文依据C3、C4植物光合生理特性进一步分析植物光合作用的三个限制函数方程在C3、C4植物光合的不同作用,揭示吸收光合有效辐射(PAR)、叶内温度(Tc)和CO2浓度(Ci)的敏感性。结果可用于植被—大气相互作用的能量和碳同化过程的物质交换研究。     

一个简单的陆面过程模式

本模式为针对大气环流模式所发展的一个简单的陆面过程模式，它包含:（1）地表温度计算，（2）冠层叶面贮水量和土壤湿度计算，（3）陆面与大气之间的水分和能量交换。对于表面温度和含水量的计算，采用的是联立求解计算方案，即耦合计算。植被冠层叶面的辐射特性和冠层形态对冠层中的辐射交换的影响得到有效和尽可能简单的模拟。另外，植被的气孔阻抗、表面与大气之间的水热交换通量和土壤中的水热输导作了较为细致的描写。利用此模式开展了对两个不同覆盖类型的陆面过程的模拟，模拟和观测的表面通量、温度和湿度较为相近。     

C3植物光合作用日变化的模拟

对前人光合作用-气孔导度耦合模型进行了修正,建立了光合作用-蒸腾作用-气孔导度的耦合模型,它概括了叶片上各主要物理过程和生理过程之间的相互联系和制约关系。 用数值方法研究了不同环境因子（太阳辐射、温度、湿度和风速等）对光合作用、蒸腾作用和气孔导度的日变化及中午降低（midday depression）的影响。 主要结果是:（1）当边界层导度减小时,光合“午睡”加剧,蒸腾作用减弱,但作为反馈调节,气孔导度增加。 （2）气孔导度的最适温度最低,光合作用次之,蒸腾作用最适温度最高。当光合作用中午受到高温的胁迫时,气孔导度下降的幅度最大,光合作用次之,蒸腾作用的降幅最小。一天中,气孔导度降低的持续时间最长,蒸腾作用降低的持续时间最短。（3）空气绝对湿度越低,气孔导度越低,光合午睡越明显。蒸腾作用则决定于饱和水汽压差(Vpd)和气孔导度两个因素的相反的作用。蒸腾作用随Vpd增加而增大,但Vpd超过一定值后,反而使蒸腾作用下降。 （4）当温度在光合最适温度以上时,太阳辐射的增加使叶温增加,引起光合“午睡”的加剧和气孔导度的降低。（5）ci/cs在中午的降低表明气孔的关闭是光合作用“午睡”现象的原因。     

半干旱区春小麦受条锈菌侵染后光合作用和蒸腾作用的变化规律

采用美国CI-301PS型便携式光合作用测定仪,对半干旱区大田春小麦的健康叶片和受条锈菌侵染后病叶的光合作用和蒸腾作用进行活体监测。结果表明：在干旱环境下。受条锈菌侵染后小麦叶片的光合作用和蒸腾作用发生了明显变化,其光合速率比健叶明显降低,而病叶细胞间隙CO2浓度、气孔导度、蒸腾速率等有所升高,且日变化随病叶严重度的不同而明显不同。受干旱和病原物侵染的双重胁迫,小麦叶片的光合效率显著降低,水分利用率也随之下降。不仅与叶绿素含量的明显下降有关,而且与干旱造成的水分亏缺对小麦体内生理生化代谢造成损伤,碳同化过程受到抑制等有着密切的关系。     

棉田土壤热通量的计算

本文在两年棉花田间试验观测的基础上,利用土壤中热传导方程模拟5cm层土壤温度的时间变化,进而推算出其它层次的土壤温度,与实测值相比,模拟均方误最大为0．14,最大温度绝对误差为0．7℃．通过对温度方程求深度上的偏导数获得土壤热通量的计算公式,计算值与实测值比较,均方误最大为0．006,效果较好。本文还通过2cm层土壤热通量与棉花冠层净辐射之间的关系,结果表明土壤热通量与冠层净辐射有着很好的相关性。     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on