基于遥感与地理信息系统支持下的地表植被特征参数反演

利用Sellers等对于不同植被类型在观测的基础上已经建立起来的光合作用有效辐射吸收系数(FPAR)或叶面积指数(LAI)与归一化标准植被指数(NDVI)的函数关系,以国家卫星气象中心接收稿日期的美国卫星NOAA-16的范围为(5～65°N,60～150°E、分辨率为1 km的NDVI资料为原始资料,根据2000年10月15日至2001年10月15日期间MODIS卫星遥感数据反演得到的IGBP分类系统1 km分辨率的土地覆被类型资料为辅助资料,对反演这一研究范围内的地表植被特征参数FPAR和LAI进行了有益的尝试,得到了比较好的结果,并成功地运用于集成沙尘天气数值预报系统中.     

黑河流域土壤质地分类数据建立及其模拟效果检验

原全球土壤质地类型分布在黑河地区的数据(下称原全球数据)不能体现该流域不同海拔高度土壤分布的非均匀性特征,为了定量表征研究区土壤的非均匀分布,在流域范围收集了53个土壤亚类剖面数据,对照土壤三角,与国际通用的STASGO 30 s土壤质地类型分类标准对应,基于黑河流域1∶100000土壤亚类分布图,建立了黑河流域30 s分辨率的土壤质地类型分布图(黑河数据)。这套数据可以描述出原全球STASGO 30 s数据不能表现出的山区和绿洲区的土壤非均匀分布实际。分别使用黑河数据和原全球数据作为下垫面土壤分布,运用耦合了陆面过程的中尺度大气模式,对黑河流域中上游区域进行了模拟,检验了两套数据对气温模拟的准确性,讨论了土壤分布变化对环境要素模拟的影响。结果表明,使用黑河土壤分布数据对上游山区的气温模拟性能好于原全球数据,中游绿洲区使用两套土壤分布数据的模拟值都偏高,大部分站点使用黑河土壤分布数据的模拟值略高于使用原全球数据的模拟值。这可能与模式中使用的全球土壤水、热参数在研究区的代表性以及中游区的人类活动加剧了土壤温、湿度的时空异质性有关。因此,黑河流域土壤水、热参数以及高分辨率的土壤温、湿度分布是提高该区域土壤—大气相互作用数值模拟性能的重要途径。环境要素变化与土壤类型分布变化呈非线性关系。气温模拟值对土壤分布变化最为敏感。     

2002年8月湖南致洪强降水过程与成因分析

利用2002年8月的常规观测资料,1°×1°的NCEP逐日再分析资料,1°×1°的云顶黑体亮度温度(TBB)逐时资料,水利部发布的2002年5～8月水情资料,以及1960～1997年中国315站的逐日降水资料,对2002年8月中下旬湖南百年难遇的大洪水发生原因以及致洪强降水进行分析.发现:(1)2002年8月受12、14号台风影响的湖南南部大暴雨和8月中旬持续高空槽前的大面积强降水,是引起8月中下旬湖南严重洪涝灾害的直接原因之一;(2)2002年4～5月以及梅雨期湘南地区的强降水使得土壤水份饱和,江河湖库维持较高的水位,导致8月上中旬先后3次强降水过程产生的雨水只能作为径流流入洞庭湖水系,使洞庭湖水系的来水与长江上游的洪峰来水遭遇,造成8月中下旬洞庭湖水系的严重洪涝灾害;(3)8月上中旬的强降水过程中,中尺度对流系统(MCS)十分活跃,而MCS的发生、发展又与有利于出现对流活动的大尺度环境场有关.     

1995～1997年T106历史资料应用整理

1　引言1 995～ 1 997年Ｔ10 6 历史资料有 34个要素 ,5 2张光盘。资料以每日为单位建立文件 ,加上时效和层次 ,每日文件就包含 1 6 1 2个要素场 ,为 70～ 1 46°Ｅ ,1 5～ 6 5°Ｎ 1× 1格点资料。文件采用ａｒｊ软件压缩 ,解压后有96兆左右字节。如此庞大的资料在实际开发应用中使用相当困难 ,为此本文按年月分单个要素场从历史资料中提取我省所需的范围资料 ,每月重新建立 1 6 1 2个要素场文件 ,就可以直接从光盘读取要素场资料。2　资料整理思路及步骤资料区域范围缩小为 85～ 1 1 5°Ｅ ,2 0～45°Ｎ ,按年月分单个要素场从 1 995～ 1 …     

东北地区汛期降水与全球大洋海温异常关系的SVD分析

利用中国160站月平均降水量资料和英国气象局整编的1950.1～1998.12全球逐月海温格点资料(格点分辨率2°×2°),采用相关分析和SVD方法研究了东北地区汛期(7～8月)降水异常与印度洋和大西洋海温异常的关系。结果表明:不同的海区对东北汛期降水异常有不同的影响。东北汛期降水与前一年6～7月西南印度洋海温有较好的负相关关系,东北西南部、东北部和西南印度洋KeyⅠ海区(23～13°S,57～77°E)为SVD耦合相关的显著区域。东北汛期降水与当年3～5月北大西洋KeyⅡ海区(21～27°N,61～75°W)有较好的正相关关系,对应了海温分布型是南北“翘翘板”型。两海区的海温异常共同对东北地区汛期降水异常有较好的预示作用。两海区海温异常对应的全国降水异常的空间分布在东北和华北地区是一致的。     

利用卫星资料试作青藏高原地表净辐射场的气候反演

利用 ERBE和 ISCCP卫星辐射及总云量资料 ,结合已提出的地表短波吸收辐射 ,大气逆辐射以及地表长波辐射的气候反演方法 ,计算出 2 5°～ 4 0°N,75°～ 95°E间 2 .5°× 2 .5°经纬度网络点及高原 63个站点的各月平均地表净辐射 ,绘制出其在高原的分布图 ,揭示其时空分布特征。     

影响北部湾地区热带气旋特征统计和分类

基于北海市气象局承担的项目<制作影响北部湾地区热带气旋历史资料库>,对库中收录1954～2002年的所有进入18°～23°N,105°～112°E范围,且中心附近最大风力达8级或以上的共计128个热带气旋的天气气候特征进行初步的统计和分析,同时对该资料库系统的各种分类功能进行简单介绍.为今后的热带气旋预报和研究工作提供一个资料平台.     

华北汛期降水异常与100hPa高度场异常的关系

利用华北17站1951～2000年的逐月降水资料,与前期的100 hPa高度场(1958～1997年)求相关,找到了100 hPa高度场影响华北地区汛期降水的关键影响区为25°～35°N,85°～105°E,对应的关键影响时段为前一年3～5月.然后用SVD方法证实了前一年春季正是与华北汛期降水相关最显著的时段;而所选关键区正是处于一种范围更大的100 hPa高度场空间分布型的关键部位,而华北地区是关键区影响中国东部降水的最显著的区域之一.     

南海地区降水的时空特征

文中利用美国 NCEP重分析资料中的 1 979～ 1 995年 1 7a逐旬的全球降水资料 ,采用小波分析方法分析了南海地区降水的多时间层次和多空间层次结构 ,研究了南海季风的爆发及时间演变 ,探讨了南海季风爆发的机制。结果表明 :( 1 )南海季风爆发于 5月中旬 ,季风爆发过程实际上是小范围 ( 32个经度 )降水向大范围 ( 64个经度 )降水调整的过程 ,一旦出现较强的大范围降水 ,并到达南海地区 ,就爆发了南海季风 ,调整完毕则是印度季风和东亚季风的相继爆发。( 2 )在 1 0°N以北的地区 ,季风最早发生在南海 ,然后逐渐西移到印度 ,达到印度季风最盛期后 ,迅速东撤。( 3)南海地区可分为 3个区域 :北部 ( 2 0～ 2 2°N)、中部 ( 1 0～ 2 0°N)和南部 ( 1 0°N以南 )。南海雨季主要发生在 1 0°N以北的北部和中部 ,北部雨季是平稳增强的单峰型 ,而中部雨季是突发性的 ,雨季内降水起伏较大。( 4 )南海季风区有很强的年变化 ,30～ 60 d和 2 0～30 d的变化也比较显著 ,还有 3个月左右的周期变化。除年振荡以外 ,各种周期振荡随时间变化较大 ,在雨季表现得最强烈。( 5)南海季风的爆发与 2 0～ 30 d和 30～ 60 d两种低频振荡有关。     

美国地温分布与后一季降水的相关分析

利用1967—1981年美国100多个站的月平均地温资料,给出了各季(3个月)40吋深度的平均地温距平分布图。将它们分别与后一季的降水量距平百分率分布图相比较,发现两者分布形势基本一致,特别是两种图上的高值轴线或低值轴线都基本相合,轴线之间的平均距离小于2°纬距者占总数的83.7％。 土壤对不同尺度的气候扰动是一个滤波器,只有低频扰动才能穿透到深层土壤之中,它们之间的关系可表示为:。τ为扰动周期,K_s为土壤热传导率,z_m称为“最大信息深度”。     

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.     

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.     

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.     

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