基于亚马逊热带雨林的微波辐射计定标基准分析

亚马逊热带雨林作为稳定地物目标,适合进行星载微波辐射计的外定标。但近些年亚马逊热带雨林受人为破坏严重,植被覆盖面积减少,植被覆盖率降低,适合进行外定标的区域较往年发生了变化。文中依据亚马逊热带雨林近些年的归一化植被指数(NDVI)的变化情况,发现纬度位于3°S^2°N,经度位于74°W^69°W范围内的区域植被覆盖率高,适合进行星载微波辐射计外定标。文中以AMSR2 L1R亮温数据为基准,对比分析了该区域在2015-2017年3 a的亮温变化趋势,并以此作为该区域的定标基准。分析发现,该区域在非厄尔尼诺事件期间的亮温变化趋势呈现出特定的季节变化规律:在每年的6-7月,亮温值达到最低;在11-12月,亮温值达到最高,7-11月波动上升,12-6月波动下降。在厄尔尼诺事件发生期间会出现亮温值异常现象。     

多源星载辐射计SST数据对比分析

基于2018年4种红外辐射计(MODIS-Aqua,MODIS-Terra,VIIRS和AVHRR)的SST数据和3种微波辐射计(GMI,WindSat和AMSR2)的SST数据,分析了7种星载辐射计SST数据的全球覆盖情况,利用Argo数据对7种辐射计SST数据进行了真实性检验,并开展了微波产品、红外产品和Argo的交叉比对分析。结果表明:VIIRS SST数据的覆盖率、有效覆盖天数均高于MODIS-Aqua、MODIS-Terra和AVHRR;AMSR2微波辐射计SST数据的覆盖率和有效覆盖天数均高于GMI和WindSat;4种红外辐射计SST数据与Argo浮标数据的平均偏差在-0.27~0℃,均方根误差小于0.76℃,其中VIIRS数据质量最好;3种微波辐射计SST数据与Argo浮标数据的平均偏差在-0.04~0.22℃,均方根误差小于0.88℃,其中AMSR2绝对偏差、标准偏差和均方根误差均小于其他2个微波辐射计数据。AMSR2和VIIRS的SST数据交叉对比发现,AMSR2与APDRC Argo、VIIRS与APDRC Argo的平均偏差分别小于0.15和-0.20℃,标准偏差分别小于0.52和0.60℃;AMSR2与VIIRS平均偏差在-0.23~-0.10℃,标准偏差小于0.41℃,两者具有较高的一致性。     

一套基于FY-3B/MWRI观测的热带气旋微波亮温数据集

利用风云三号B星(FY-3B)微波成像仪(Microwave Radiation Imager,MWRI)一级亮温数据和每6 h一次的热带气旋(tropical cyclone,TC)最佳路径数据进行时空匹配,建立了TC微波亮温数据集.该数据集包含了2011—2016年全球六大海盆生成的热带风暴级别以上的TC共计538...     

基于AMSR2微波辐射计的近海面气温反演算法研究

基于多元线性回归方法,利用2013-01-06的AMSR2辐射计亮温数据和红外-微波融合SST数据产品,开展了近海面气温反演算法研究,并用TAO,RAMA和PIRATA等浮标实测数据对近海面气温的反演结果进行检验。近海面气温反演结果误差情况:均方根误差为0.66℃,偏差为0.02℃,相关系数R为0.91,该误差结果表明所建立近海面气温反演算法较好的反映在60°S~60°N纬度范围内的近海面气温分布情况;同时为进一步确定不同纬度近海面气温反演的误差分布,将近海面气温反演结果与ECMWF再分析数据进行了对比分析,结果表明,从赤道起算,纬度每升高或降低1°,反演均方根误差约增大0.1℃。     

利用专题微波辐射成像仪(SSM/I)检测东南极陆面亮温变化

介绍了微波辐射测量面目标表面亮度温度的原理,分析了冰雪的微波辐射特性与亮温特征。利用专题微波成像仪 (SSM/I) 数据研究了 1988 年 1－8 月份东南极内陆冰雪表面亮温变化。首先根据 37 GHz 水平极化辐射亮温 175 oK 等温线推算南极大陆冰外缘线,然后利用 37 GHz 数据计算分析了东南极内陆 1988 年年内 1－8 月的地面亮温均变化。结果表明在东南极内陆的地面亮温年内月均变化不大;在东南极的边缘,其受大洋季候风变化影响发生很大的变化。     

一维综合孔径微波辐射计遥感海面温度的敏感性分析

一维综合孔径微波辐射计能够有效提高观测的空间分辨率，其观测入射角通常在0°~55°范围内变化。为了开发适用于一维综合孔径微波辐射计的海面温度反演算法，需要评估其观测亮温对海洋大气环境要素的敏感性。利用海面发射率模型和大气辐射传输模型，构建了适用于一维综合孔径微波辐射计的微波海洋大气辐射传输模式，研究了C波段垂直和水平极化微波辐射亮温在不同入射角下对海洋大气环境要素的敏感性变化情况，并定量计算了相应的敏感系数。结果表明:垂直和水平极化亮温对海洋大气环境要素的敏感性表现出不同的特性。随着入射角的增大，垂直极化亮温对海面温度的敏感性增强，对海面风场的敏感性相对减弱；水平极化亮温则相反。由大气水汽含量和云液态水含量误差引入的垂直和水平极化亮温误差随入射角增大而增大，但是，即使在55°的大入射角下垂直和水平极化亮温误差仍小于0.12 K。对于海面温度反演精度优于1 K的要求，一维综合孔径微波辐射计的测温精度需优于0.6 K。研究结果对于一维综合孔径微波辐射计海面温度反演算法的研究和载荷设计具有一定的理论指导意义。     

HY-2卫星扫描微波辐射计数据反演北极海冰漂移速度

本文基于最大互相关法,利用海洋二号（HY-2）卫星扫描微波辐射计37 GHz通道多时相垂直极化亮温数据,获取了北极海冰漂移速度。采用2012年和2013年国际北极浮标计划海冰现场观测数据,对利用微波辐射计亮温资料反演的冬季北极海冰漂移速度进行了定量验证,结果表明:流速和流向均方根误差分别为1.12 cm/s和16.37°,从一定程度上说明了HY-2卫星扫描微波辐射计亮温数据反演海冰漂移速度的可行性。此外,使用美国国防气象卫星F-17搭载的专用微波成像仪91 GHz通道垂直极化亮温,采用高斯拉普拉斯滤波方法进行处理,结合最大互相关法反演的海冰漂移速度,优于法国海洋开发研究院海冰漂移速度产品。     

基于梯度信息的微波辐射亮温资料质量控制方法

卫星微波垂直探测器的辐射观测资料在数值预报中的同化应用使得数值预报水平有了巨大的飞跃。微波资料的质量控制是保证观测资料成功同化的关键所在。文章提出一种基于AMSU-A(Advanced Microwave Sounding Unit-A)辐射亮温资料梯度信息的新质量控制方法,将亮温梯度距平值明显较大的资料作为被降水污染或因为其他原因出现的"坏"的资料。利用中尺度非静力WRF(Weather Research and Forecasting)模式和区域三维变分同化,针对"海鸥"(2008)和"圆规"(2010)2个个例,对比旧质量控制中的降水检测和阈值检测方法,评估该方法用于AMSU-A资料同化时对台风数值模拟的情况。研究表明,旧质量控制方法将会使一些"坏"的微波观测资料同化进入模式,降低模式分析场的质量,进而导致同化结果有较大误差。相对于旧方法获得的分析场,利用基于亮温梯度信息的质量控制方法可使更多"坏"的观测剔除,同化后模式初始时刻的位势高度场和风场更接近于真实情况。与传统AMSU-A辐射资料的同化相比,新质量控制方案使2个台风路径数值模拟的偏差有明显的减小:"海鸥"个例中,模拟台风路径误差的最大改善比为12,路径误差改善约540km;"圆规"个例的最大改善比为13,模拟路径误差减小118km。     

应用微波辐射亮温确定北极海冰边缘的算法

海冰边缘区(MIZ)的边缘位置是微波遥感图像的1个基本特征,本文利用AMSR-E微波辐射亮温的强度比,提出1个确定MIZ边缘位置的方法。强度比最初用来确定数字影像中海冰和海水的阈值。研究发现,强度比也可以反应海冰与海水的微波辐射的差异。在无冰水域,垂直极化的18.7(V18.7)和36.5(V36.5)GHz的高级微波扫描辐射计(AM-SR-E)的亮温之比主要在0.86～0.89之间变化,此时它们在散点图中聚集成1条经过原点的直线;而在MIZ,它们的比值发生了显著改变。强度比比较好的体现了V18.7和V36.5的亮温比值在MIZ边缘处的变化特征:强度比快速增大,并且它的梯度出现极大值。全年中MIZ边缘处的亮温比值在0.89～0.90之间变化,此时对应的海冰密集度为0.08。     

基于Argo浮标数据的星载微波辐射计Aquarius数据产品质量评估

Aquarius是专门用于海洋盐度监测的L波段辐射计,于2011年6月发射入轨,目前已进入业务化运行阶段。本文以太平洋为研究区域,利用Argo盐度现场数据对星载微波辐射计Aquarius的2012年2级数据产品质量进行了分析与讨论,结果表明:与Argo数据比较,Aquarius数据盐度存在0.1的负偏差,标准差约为0.7,升轨和降轨数据差异不明显;受亮温陆地污染和无线电射频干扰的影响,近岸海域反演误差较大;海面温度较高的低纬海域反演结果优于中纬度海域;受亮温敏感性及粗糙海面发射率模型的影响,Aquarius在低温水域以及高风速条件下盐度反演误差较大,标准差可达1以上。     

Effect of air-sea temperature difference on ocean microwave brightness temperature estimated from AMSR,SeaWinds, and buoys

The effect of air-sea temperature differences on the ocean microwave brightness temperature (Tb) was investigated using the Advanced Microwave Scanning Radiometer (AMSR) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) during a period of seven months. AMSR Tb in the global ocean was combined with wind data supplied by the scatterometer SeaWinds aboard ADEOS-II and air temperature given by a weather forecast model. Tb was negatively correlated with air-sea temperature difference, its ratio lying around −0.4K/°C at the SeaWinds wind speed of 14 m/s for the 6 GHz vertical polarization. Tb of AMSR-E aboard AQUA during 3.5 years was combined with ocean buoy data, and similar results were obtained.     

SMAP卫星辐射计在中国近海及沿岸的RFI特征分析

射频干扰RFI(Radio-Frequency Interference)的校正和抑制一直是微波遥感研究领域的重要问题之一。本文基于SMAP卫星2015年5月1日至5日L波段辐射计亮温数据对中国近海及沿岸的射频干扰进行了特征分析。研究发现RFI分布不均匀,主要集中在城市群及其周边地区;通过对比辐射计天线接收的亮温数据与射频干扰校正和抑制后的数据,发现研究区域主要的射频干扰(95%)的平均值为1.4 K,整体射频干扰平均值为2.5 K,标准差为6.5;研究区域中不同波段和极化的数据受到射频干扰影响较为相似,受射频干扰影响最大的是升轨的垂直极化数据,受影响最小的是升轨的水平极化数据。     

Cross-calibration of brightness temperature obtained by FY-3B/MWRI using Aqua/AMSR-E data for snow depth retrieval in the Arctic

This study cross-calibrated the brightness temperatures observed in the Arctic by using the FY-3B/MWRI L1 and the Aqua/AMSR-E L2A. The monthly parameters of the cross-calibration were determined and evaluated using robust linear regression. The snow depth in case of seasonal ice was calculated by using parameters of the crosscalibration of data from the MWRI T_b. The correlation coefficients of the H/V polarization among all channels T_b of the two sensors were higher than 0.97. The parameters of the monthly cross-calibration were useful for the snow depth retrieval using the MWRI. Data from the MWRI T_b were cross-calibrated to the AMSR-E baseline.Biases in the data of the two sensors were optimized to approximately 0 K through the cross-calibration, the standard deviations decreased significantly in the range of 1.32 K to 2.57 K, and the correlation coefficients were as high as 99%. An analysis of the statistical distributions of the histograms before and after cross-calibration indicated that the FY-3B/MWRI T_b data had been well calibrated. Furthermore, the results of the cross-calibration were evaluated by data on the daily average T_b at 18.7 GHz, 23.8 GHz, and 36.5 GHz(V polarization), and at 89 GHz(H/V polarization), and were applied to the snow depths retrieval in the Arctic. The parameters of monthly cross-calibration were found to be effective in terms of correcting the daily average T_b. The results of the snow depths were compared with those of the calibrated MWRI and AMSR-E products. Biases of 0.18 cm to 0.38 cm were observed in the monthly snow depths, with the standard deviations ranging from 4.19 cm to 4.80 cm.     

基于一维综合孔径微波辐射计的大气海洋环境参数敏感性分析

相比于实孔径微波辐射计,一维综合孔径微波辐射计具有高空间分辨率和多入射角观测特点。本文提出采用观测频率为6.9,10.65,18.7,23.8和36.5 GHz,且入射角范围为0°~65°的一维综合孔径微波辐射计遥感大气海洋环境要素。基于构建的微波大气海洋辐射传输正演模型,分析了辐射计亮温对大气海洋环境要素的敏感性,为辐射计关键指标确定和大气海洋环境要素反演算法设计提供技术支撑。结果表明：一维综合孔径微波辐射计的垂直和水平极化亮温对大气海洋环境要素的敏感性表现出不同特性,且敏感性随入射角的改变而变化显著;6.9和10.65 GHz对海面温度的敏感性较大,且随着入射角的增大,垂直极化亮温的敏感性增大,水平极化亮温的敏感性减小;10.65和18.7 GHz对海面风速的敏感性相对较大,且敏感性最大的风速区间位于10~20 m/s;23.8 GHz对大气水汽含量最敏感,且水汽含量较低、入射角较大时,敏感性越大;36.5 GHz对云液态水含量最敏感,随着入射角的增大,垂直极化亮温的敏感性减小,水平极化的敏感性增大,但两者均在液态水含量较小时表现出较大的敏感性。     

Difference characteristics of sea surface temperature observed by GLI and AMSR aboard ADEOS-II

This study compares infrared and microwave measurements of sea surface temperature (SST) obtained by a single satellite. The simultaneous observation from the Global Imager (GLI: infrared) and the Advanced Microwave Scanning Radiometer (AMSR: microwave) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) provided an opportunity for the intercomparison. The GLI-and AMSR-derived SSTs from April to October 2003 are analyzed with other ancillary data including surface wind speed and water vapor retrieved by AMSR and SeaWinds on ADEOS-II. We found no measurable bias (defined as GLI minus AMSR), while the standard deviation of difference is less than 1°C. In low water vapor conditions, the GLI SST has a positive bias less than 0.2°C, and in high water vapor conditions, it has a negative (positive) bias during the daytime (nighttime). The low spatial resolution of AMSR is another factor underlying the geographical distribution of the differences. The cloud detection problem in the GLI algorithm also affects the difference. The large differences in high-latitude region during the nighttime might be due to the GLI cloud-detection algorithm. AMSR SST has a negative bias during the daytime with low wind speed (less than 7 ms⁻¹), which might be related to the correction for surface wind effects in the AMSR SST algorithm.     

A wind speed retrieval algorithm by combining 6 and 10 GHz data from Advanced Microwave Scanning Radiometer: Wind speed inside hurricanes

A wind speed retrieval algorithm was developed using 6 and 10 GHz h-pol (6H and 10H) data of the Advanced Microwave Scanning Radiometer (AMSR) aboard the Advanced Earth Observation Satellite-II (ADEOS-II) and AMSR-E aboard AQUA, for the purpose of retrieving wind speed inside rainstorms, primarily hurricanes and typhoons. The h-pol was used rather than the v-pol, because the brightness temperature sensitivity to the ocean wind at h-pol is larger than v-pol. The microwave emission change of 6H and 10H corresponding to ocean wind was evaluated in no-rain areas by combining AMSR and SeaWinds data aboard the ADEOS-II (SeaWinds was NASA’s scatterometer), and it was found that the ratio of the two 6H to 10H increments due to ocean wind is 0.9. Assuming that this result also holds with higher wind speeds and under rainy conditions, the brightness temperatures at 6H and 10H were simulated using a microwave radiative transfer model. A parameter W6 (unit; Kelvin) was then defined, representing an increment at 6H due to ocean wind. W6 is applicable to rainy areas, and to all ranges of sea surface temperature. W6 was compared with wind speed reported by the National Hurricanes Center for several hurricanes in the Western Atlantic Ocean during three years (2002 to 2004). W6 averaged around centers of hurricanes was found to exhibit a sensitivity to wind speed, such as increasing from 22 K to 65 K as the wind speed rose from 65 to 140 knots (33 to 72 m/s), and an empirical relationship relating the averaged W6 to wind speed in hurricanes was derived.