遥感估算降水在西藏高原中的应用研究

采用遥感估算降水模型RFE 2.0(Rainfall Estimation Algorithm Version 2)模拟了2009年西藏高原的区域降水,并结合该地区气象站降水观测资料分别从日、月、年尺度上评价了该模型在西藏高原降水估算中的适用性,最后通过系数校正分析了2009年8月西藏高原降水量和年降水量的分布格局。结果表明,RFE2.0模型日降水量模拟值与观测值的相关系数在0.40以上的测站占46%,变化趋势较一致,但在日降水量较小时(接近零)模拟结果不稳定,在降水量较大时(>15mm)模拟结果一般会偏低;月平均降水量模拟结果与观测结果的相关系数在0.80以上的测站占62%,模拟结果较好地反映了观测结果的变化趋势,但个别月份的模拟结果会出现偏差。雨季降水量的模拟结果明显好于干季,为进一步提高模拟精度,确定雨季校正系数为1.133,干季校正系数为1.265;年尺度上降水量的模拟值与观测值的相关系数为0.368(P=0.026)。整体来看,遥感估算降水模型(RFE2.0)模拟的西藏高原降水结果较好,可为西藏高原降水模拟提供借鉴和参考。     

高寒山区面降水量获取方法及影响因素研究进展

主要总结了高寒山区面降水数据的获取方法、影响因素及时空分布的研究进展,并指出了面降水量数据获取可能的解决途径。通常地面观测及空间插值、大气数值模式估算、遥感反演是面降水数据的主要获取方法,但应用于高寒山区都有一定局限性:地面观测点稀缺限制了各种空间插值方法的精度;大气数值模式,不能有效地模拟高寒山区复杂地形下的局地降水空间分布;地基遥感(多普勒雷达)受地形遮挡和自身条件的限制,空基遥感数据的精度受限于卫星搭载降水雷达的性能、卫星过境频率及空间分辨率等因素;对降水分布的估算存在很大误差。水汽源、坡向、海拔与下垫面地形是影响高山区降水量及其时空分布的主要因素。为此,在黑河上游祁连高山区,已进行的小范围加密观测、基于遥感空间格网的矩阵观测及大范围撒网式观测,仍是了解高寒山区降水量时空分布规律的基础;有待提高精度和时空分辨率的卫星数据,以及有效的地面-卫星遥感数据同化方法的研究,也将成为获取高寒山区精确的面降水量的有效途径;大气数值模式的降尺度研究也是一种途径,有待进一步研究。     

基于贝叶斯融合方法的高分辨率地面-卫星-雷达三源降水融合试验

为了探讨一种适用于区域性的地面、雷达、卫星等多源降水资料融合的方法,一种曾用于高分辨雷达、卫星土壤湿度产品反演的贝叶斯融合(Bayesian Merging)方法被尝试应用于江淮地区1 h-0.05°×0.05°经纬度高分辨率的雷达估测降水、卫星反演降水与地面站点观测降水3种资料的融合。在应用该方法时,通过2009年8月样本统计分别估计卫星和雷达反演降水的误差关系,通过曲线拟合建立误差方程,并以卫星资料作为背景场,但在融合时将雷达估测降水作为新的观测信息与地面观测降水同时引入。融合试验检验结果表明:贝叶斯融合方法能够有效实现雷达、地面、卫星3种不同来源资料的融合,该方法生成的多源融合产品的精度均优于任何单一来源的降水产品。     

神经网络方法在静止卫星多通道资料估算降水中的应用

使用人工神经网络 (ANN)模型探讨了利用静止卫星多通道资料估算地面降水的一种新方法 ,对淮河和长江典型区域 (2 4～ 3 6°N ,1 0 8°E以东 )一次暴雨过程的卫星遥感数据和地面水文站逐时降水资料的应用分析表明 ,该方法提供的客观定量的降水量估算的平均相关系数为 0 57,较现行业务使用的方法效果更佳     

GPM/IMERG产品在鲁南地区的精度评估

为了评估GPM/IMERG产品在鲁南地区的精度,利用2016年1—12月鲁南地区35个国家气象站的降水观测数据,采用定量和分类评分指标的方法,从时间、空间和降雨强度等方面对GPM/IMERG产品在鲁南地区的适用性进行评估。结果表明:IMERG数据在鲁南地区具有较高的精度,IMERG与站点观测数据相关系数为0.8,均方根误差为5.47mm/d,相对偏差为2.27%;从时间上来看,IMERG与站点观测区域平均日降水和月降水总体变化趋势是一致的,夏季的估算精度高于其他季节;从空间上来看,年降水量偏多的台站,IMERG数据会低估,年降水量偏少的台站,IMERG数据会高估,IMERG对中纬度山地和丘陵的估测精度优于平原;IMERG产品的估计精度与降雨强度有关,当降水量级为微量降水(小于1mm/d)时,卫星估测能力较弱,当降水强度为小雨及以上量级时,卫星估测降水产品与实际观测概率密度差异较小;IMERG估算稳定性降水的能力较强,在降水较多月份,IMERG的探测准确率较高、空报率较低、临界成功指数较好。     

低纬高原地区多元信息综合变分分析试验

利用高分辨率雷达、卫星降水反演数据和地面降水观测资料,建立联合降水估算场并对其进行变分订正,得到0.1°×0.1°细网格降水同化场。同化资料包括2008年6～8月逐日4次FY-2卫星和CINRAD/CC雷达降水估算资料、地面自动站降水观测资料,试验结果表明,采用变分方法对卫星及雷达联合降水估算场进行同化后,所得结果既较真实地反映了地面观测网天气尺度信息,也对低纬高原地区降水离散性分布特征的描述有较大的改善。     

贵州地区CMORPH卫星降水产品的误差订正

CMORPH卫星反演降水产品具有全天候、全球覆盖的特点,其时空分布相对均匀、独立,但是CMORPH本质上是通过间接手段反演得到,其降水精度无法与地面观测降水精度相比,并且存在一定的系统误差。结合地面自动站降水资料采用概率密度匹配法对贵州地区CMORPH卫星反演降水产品进行系统误差订正,该方法将每个格点的卫星降水累积概率分布曲线和地面降水概率密度分布曲线匹配,获取降水误差订正值;其中误差订正效果受降水累积概率分布拟合曲线的影响,而考虑到降水累积概率分布是非正态分布,因此选用Gamma分布拟合降水累积概率分布曲线。通过对2018年5月三次降水过程的订正结果分析得到如下结论:(1) 逐时的CMORPH卫星反演降水产品存在明显的非独立系统误差,误差范围随降水量级的变化而变化,存在低值高估的特点;(2) 在小时尺度下地面降水的累积概率密度呈指数衰减分布,而CMORPH的降水累积概率密度分布更加复杂,其在中雨、大雨区间内的降水概率较高;(3) 通过概率密度匹配法订正后的CMORPH与订正前相比降水空间结构更加贴近地面降水,强降水中心的量级和范围明显减小,平均绝对误差和均方根误差均减小,其中偏差订正值在0.114~0.468 mm/h,均方根误差订正在0.24~1.49 mm/h之间。经概率密度匹配法订正后的CMORPH卫星反演降水产品精度明显提升,更加接近于实际降水。      

GPM卫星反演降水产品在江苏地区的适用性

以江苏省70个地面雨量站分钟观测数据为基准,对比分析了一个完整年周期GPM卫星搭载的双频降水雷达(DPR)反演降水产品精度。结果表明DPR常规模式(NS)、匹配模式(MS)和高灵敏度模式(HS)扫描产品反演降水与地面雨量计观测数据均在过境后几分钟内达到最佳匹配效果。以NS产品为例,全年反演降水均方根误差大致为2mm/h,相关系数在0.5以上,相对偏差为-20%左右。并且降水产品在夏季反演精度最高。对反演误差进行初步分析发现,卫星反演降水率算法精度对校正因子ε有非常强的敏感性,并且选择ε值的算法约束不足会导致最终计算求解模块SLV的路径积分衰减PIA值异常,引起极端降水反演的误差。     

卫星云图资料在降水量客观分析中的应用试验

利用葵花8号卫星资料和地面降水观测资料,采用Spark GBT(Gradient Boosted Trees Regression)学习算法对中国西部地区进行定量降水估计(QPE),采用三维Barnes插值方法得到逐时降水格点场。试验结果表明,引入卫星资料估计降水,可以有效地改进站点密度小的区域的降水格点场的客观分析精度。     

基于FY-2C卫星资料估算四川地面降水方法研究

应用2006年6月6日00时(北京时)至7日06时四川地区的自动站降水资料和FY-2C静止卫星红外亮温资料,共3854对样本,分析发现1小时内的最低红外亮温和红外亮温增量两因子能很好地表征地面1小时累计降水量,且能有效地进行四川地面1小时降水估算,并由此建立了估算降水方法.通过对2006年8月27日13-19时,2006年8月28日04-16时两个时段估算降水结果的初步检验来看,其均方根差都小于2.0mm,随着最低亮温的增加,其均方根差也越小.由此可见,基于FY-2C静止卫星1小时内最低红外亮温和亮温增量来估算四川地面1小时降水是可行的,且效果较好.     

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.     

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     

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.     

Information for Authors

正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.