2000~2016年青藏高原地表反照率时空分布及动态变化

应用MODIS地表反照率产品MCD43C3,结合青藏高原自然带数据、积雪覆盖率和植被指数数据,采用一元线性回归方法分析了2000~2016年青藏高原地表反照率的分布及变化特征,结果表明:1）高原地表反照率空间分布差异大,整体上东南部低、西北部高,受地形和地表覆盖影响较大。2）高原地表反照率四季的空间分布变化明显,高海拔山脉和高寒灌丛草甸是高原地表反照率年内和年际变化的敏感地区。3）高原地表反照率年变化介于0.19~0.26,一定程度上表现为“双峰单谷”型,与地表覆盖类型的季节变化密切相关。4）高原地表反照率年际变化整体呈缓慢波动减小的趋势,平均变率约为－0.4×10-3 a-1,减小的区域约占高原总面积的66%,川西 —藏东针叶林带的西南部地区减小得最快,减小速率超过1.0×10-2 a-1。5）高原地表反照率减小与冰川消融和积雪减少密切相关,高原植被覆盖改善也是一个重要因素。     

基于SCIATRAN模型的二氧化氮DOAS 反演敏感性试验

气溶胶和地表反照率是影响星载SCIAMACHY仪器观测数据定量遥感NO2大气柱总量的2个主要因子.文中利用高光谱分辨率大气辐射传输模型SCIATRAN,在考虑分子吸收和气溶胶多次散射影响基础上,精确模拟了气溶胶、地表反照率和NO2气体浓度变化对差分处理前后卫星反射光谱的影响,并定义影响因子f,对3个模拟参数进行综合评价.结果表明:(1)通过剔除卫星反射光谱中慢变光谱变化成分,DOAS方法明显降低了气溶胶和地表反照率对卫星反射光谱的影响;(2)差分处理前,3个模拟参数的影响强弱依次为地表反照率、气溶胶和NO2浓度;而差分处理后,3个模拟参数的影响强弱依次为NO2浓度、地表反照率和气溶胶.在影响趋势上,气溶胶和地表反照率很相似,均体现为宽带效应,在440-450 nm内有水汽强吸收和多次散射复杂相互作用导致的较大峰值;NO2浓度变化对差分处理前后的光谱都呈现气体吸收结构的影响特性;(3)由于吸收和散射相互作用等因素的影响,在基于卫星观测的差分光谱中仍然残留有气溶胶和地表反照率的误差,地表反照率约占18.6%,气溶胶约占6.2%.因此,当前SCIAMACHY遥感的NO2产品在中国区域浓度偏高,需要对气溶胶和地表反照率进行二次精细化的订正.     

寿县地区小麦和水稻田地表反照率观测分析

利用寿县气候观象台2007年10月～2008年9月地表反射率观测资料,分析了农田地表反照率的季节变化,对比了小麦和水稻在不同生长期的平均反照率,讨论了天气状况和天气过程对反照率的影响.结果表明,在小麦和水稻的生长期内,地表反照率变化相似,均先增大后减小.在作物生长初期,水稻田平均反照率低于小麦田反照率约0.02;中期时,两者相近;成熟后,水稻反照率高于小麦反照率约0.04.降水过后,晴空地表反照率减小.     

青藏高原MODIS地表反照率和GLASS地表反照率的对比分析

对比分析了青藏高原MODIS地表反照率产品和GLASS地表反照率产品的空间分布连续性、高质量反演结果的比例,应用青藏高原CAMP/Tibet试验期间的高精度观测数据评估了两种产品的精度,通过人工目视解译MODIS地表反射率图像并结合MODIS积雪产品分析了影响两种产品精度的原因,结果表明：1）GLASS地表反照率产品具有比MODIS地表反照率产品更好的空间分布连续性和更高的反演质量;2）绝大多数时段内两种产品都能与地面观测结果保持较好的一致性,能准确地反映地表反照率的异常变化过程;3）局地积雪是影响两种产品精度的重要因素之一;4）积雪条件下,GLASS地表反照率反演算法比MODIS地表反照率反演算法更具优势。研究结果有助于促进人们对地表反照率卫星遥感反演产品的认识,改进青藏高原地表反照率卫星遥感反演算法,提高青藏高原地表反照率卫星遥感反演结果的精度、反演质量和空间分布连续性。     

1982—2000年中国区域地表反照率时空分布特征

利用1982—2000年NOAA-AVHRR数据资料,研究了中国区域地表反照率的空间分布及其随时间的变化规律。结果表明,中国区域年均地表反照率在空间分布上有很大的差异,胡焕庸线以西地区地表反照率明显大于以东地区;年平均地表反照率呈现缓慢下降趋势,但是不同地区的变化趋势有所不同,年均地表反照率显著降低的区域主要集中在华北平原,显著增加的区域主要集中在长白山和大兴安岭北部;不同季节地表反照率存在很大的差异,冬季最大,春、夏季次之,秋季最小,且冬季平均地表反照率波动幅度比较大;不同地表覆盖的地表反照率的年际变化也存在比较显著的差异。     

巴丹吉林沙漠与小尺度湖泊夏季地表特征对比分析

利用2009年7 9月"巴丹吉林沙漠陆气相互作用及其对区域气候的影响研究"试验所得观测资料,系统分析了夏季典型晴天下巴丹吉林沙漠和沙湖不同下垫面的辐射和能量收支特征。结果表明:(1)沙漠点和沙湖点土壤温湿度都有明显的日变化,表现为准正弦曲线。地表向下日较差逐步变小,日峰值和谷值都有明显的滞后性。5~10 cm土壤温、湿度受地表温度影响较大,20 cm以下不再有明显的日变化。沙湖点土壤湿度较大,且出现逆湿现象。(2)沙漠点和沙湖点太阳总辐射的日变化趋于一致;沙漠点大气长波辐射、地表长波辐射、有效辐射均比沙湖点略低,地表反射辐射大于沙湖点。沙漠的地表长波有效辐射均小于沙湖点,两观测点净辐射差异较小。(3)两观测点的地表反照率呈"U"形分布;沙漠点的日平均反照率为0.32,沙湖点为0.23。(4)沙漠点以感热输送为主,波文比为3.4;沙湖点则以潜热输送为主,波文比为0.2。     

基于MODIS数据地表反照率时空变化特征及影响因子研究

地表反照率表征地球表面对太阳辐射的反射能力,是影响地表辐射能量收支平衡的关键参数。本文以淮河流域为例,利用MODIS（MODerate resolution Imaging Spectroradiometer）数据,采用网格趋势分析、异常变化分析、相关分析和灰色关联度分析等方法,分析了淮河流域2005～2015年地表反照率的时空变化规律,以及土地利用类型、地形因子、地表参数和气候等影响因子。结果表明:淮河流域年平均地表反照率整体呈“北高南低、东高西低”的空间分布规律,变化在0.043～0.223,平均值为 0.145。低值区主要集中于水体密集和山区丘陵地带,且标准差相对较小;高值区主要集中于流域中部及东部平原地带,且标准差较大。61.5%的区域地表反照率呈增加趋势,且存在季节性差异,夏季平均地表反照率最大,春季次之,秋季最小,冬季则由于降雪覆盖和农田利用的影响波动幅度较大。淮河流域地表反照率与归一化植被指数（Normalized Difference Vegetation Index,NDVI）、地表温度、气温和降水在大部分区域呈正相关,面积占比分别达到90.23%、82.32%、85.41%和93.70%。灰色关联度分析表明,不同土地利用类型（水体除外）下年均地表反照率受各因子影响排序为:NDVI>气温>地表温度>降水,空间变化受各因子影响排序为:NDVI>降水>地表温度>气温>高程。     

青藏高原三江源区退化草地生态系统的地表反照率特征

为了揭示青藏高原三江源区草地退化对生态系统地表反照率的影响,利用2006年12月至2007年11月一整年的观测数据,分析了地表反照率的季和日变化特征及其影响因子。退化草地生态系统的年均地表反照率为0.22,生长季(5～9月)的平均地表反照率为0.18,非生长季为0.25。在植物生长初期的5月,地表反照率主要受土壤水分影响,5月末至6月初出现全年最低值;植物生长旺季的7～8月,受植被的影响地表反照率相对较稳定,并略高于生长季中其它各月。地表反照率的日变化呈"U"型,阴天的地表反照率高于晴天。全年地表反照率出现的最大频率集中在0.20附近,非生长季在0.22附近,生长季在0.18附近。退化草地生态系统生长季地表反照率的变化受土壤水分和植被的的影响,而非生长季受积雪的影响较大。     

地表反照率研究进展

地表反照率是陆面过程模式及气候模拟研究中的一个重要参数,地表反照率的变化会改变整个地气系统的能量收支平衡,并引起局地以至全球的气候变化。不同下垫面地表反照率存在明显的差异,中国区域地表反照率的空间分布也存在明显的区域差异。遥感反演地表反照率在空间上具有较高的精度,但反演结果很难直接应用于陆面过程模式。各种陆面模式对地表反照率计算主要基于陆面土地覆盖分类,包含了许多先验的预定参数,由于某些过程处理中的简化假设,从而对地表反照率的计算带来一定的误差。      

多年冻土区与季节冻土区地表反照率对比观测研究

利用多年冻土区唐古拉气象站与季节冻土区那曲毕节气象站2008年辐射、土壤未冻水含量及积雪等数据,对两种冻土类型下垫面上的地表反照率进行分析研究,得出两站地表反照率均呈现冬春季较大,夏秋季较小的规律,并且,积雪使地表反照率形成极大值,最大极值接近0.9。唐古拉站的地表反照率整体上比毕节站大,年平均地表反照率分别为0.38和0.31。地表反照率月较差(每月日平均地表反照率最大值与最小值的差值)冬季毕节站高于唐古拉站,而夏秋季节则相反。晴天,两站地表反照率均呈现"U"形,表现出早晚大、中午小,春、夏、秋、冬各季节典型晴天的地表反照率日平均值唐古拉站分别为0.23、0.20、0.20和0.25,毕节站为0.26、0.21、0.22和0.29。此外,讨论了两站太阳高度角和土壤湿度对地表反照率的影响,得出两站地表反照率随太阳高度角的增大均呈现e指数衰减趋势,土壤湿度与地表反照率呈负相关关系,且降雨对地表反照率的变化影响较大。     

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