Considering combined or separated roughness and vegetation effects in soil moisture retrievals

For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (τ_nad) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB), soil roughness is modelled with a semi-empirical equation using four main parameters (Q_r, H_r, N_rp, with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N_rp and H_r on the SM and τ_nad retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011–2015). In this study, Q_r was set equal to zero and we assumed that N_rH = N_rV. The retrievals were performed by varying N_rp from −1 to 2 by steps of 1 and H_r from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth retrievals. These new results may have key consequences in terms of calibration of roughness effects within the algorithms of the SMOS (ESA) and the SMAP (NASA) space missions.     

Forest classification and impact of BIOMASS resolution on forest area and aboveground biomass estimation

The European Space Agency (ESA) is currently implementing the BIOMASS mission as 7th Earth Explorer satellite. BIOMASS will provide for the first time global forest aboveground biomass estimates based on P-band synthetic aperture radar (SAR) imagery. This paper addresses an often overlooked element of the data processing chain required to ensure reliable and accurate forest biomass estimates: accurate identification of forest areas ahead of the inversion of radar data into forest biomass estimates.The use of the P-band data from BIOMASS itself for the classification into forest and non-forest land cover types is assessed in this paper. For airborne data in tropical, hemi-boreal and boreal forests we demonstrate that classification accuracies from 90 up to 97% can be achieved using radar backscatter and phase information. However, spaceborne data will have a lower resolution and higher noise level compared to airborne data and a higher probability of mixed pixels containing multiple land cover types. Therefore, airborne data was reduced to 50 m, 100 m and 200 m resolution. The analysis revealed that about 50–60% of the area within the resolution level must be covered by forest to classify a pixel with higher probability as forest compared to non-forest. This results in forest omission and commission leading to similar forest area estimation over all resolutions. However, the forest omission resulted in a biased underestimated biomass, which was not equaled by the forest commission. The results underline the necessity of a highly accurate pre-classification of SAR data for an accurate unbiased aboveground biomass estimation.     

基于Roberts梯度与HIS色彩空间的SAR图像伪彩色编码

针对SAR灰度影像信息不丰富,不利于解译识别的问题,提出了一种基于Roberts梯度与HIS色彩空间的SAR图像伪彩色编码算法。首先,计算SAR图像的梯度图像,并确定梯度阈值T;然后,比较像素梯度与阈值的大小,大于阈值的像素按照Roberts梯度方法编码,否则按照基于HIS色彩空间方法编码;最后,对两种编码结果进行合成,得到最终伪彩色SAR图像。利用TerraSAR-X影像数据进行了实验验证,结果表明:本文研究的方法均能达到很好的伪彩色编码效果。     

水平距离和海拔高度对雷达估测降水影响及订正

以石家庄2006—2008年77次降水过程为例,分析了海拔高度和距雷达站水平距离对定量估测降水的影响,给出了估测降水时反射率因子取值的最佳高度以及距离高度订正值。对比了经验公式法和最优化法分别在有无距离高度订正4种情况下的估测效果,依据估测效果,设计了雷达定量估测降水最佳方案:若反射率因子小于30 dBz,则不进行距离高度订正,仅采用最优化法估测降水;若反射率因子大于30 dBz,则首先对反射率因子进行距离高度订正,然后采用最优化法估测降水。实例检验表明,该方案对单站10 mm·h~(-1)以上的强降水、过程降水量和区域降水量估测效果较好。     

泰山CD与济南SA天气雷达探测强冰雹风暴参数对比分析

利用泰山CD雷达和济南SA雷达探测资料,对2016年6月13—14日和9月11日4个长寿命强冰雹风暴参数进行了对比分析。结果表明,4个强冰雹风暴成熟阶段济南SA雷达探测到的DBZM值都在60 dBZ以上,C-VIL值基本在50 kg·m-2以上,TOP值基本在9 km以上, 0613平阴风暴和0614章丘风暴不仅持续时间相差不多,而且DBZM、C-VIL、TOP值基本相近,DBZM基本在 64 dBZ以上,最大达到70 dBZ,C-VIL基本在60 kg·m-2以上,最大在80 kg·m-2左右,TOP值基本在10～5 km以上;SA雷达和CD雷达监测到的风暴参数有明显差异,SA雷达观测到的强风暴DBZM、C-VIL和TOP值明显大于CD雷达观测到的值,特别是DBZM和C-VIL在风暴强盛阶段差异更加明显,风暴强盛阶段, SA和CD雷达观测到的0613阳谷风暴、0613平阴风暴、0614章丘风暴和0911高青风暴的DBZM平均差值分别为10 dBZ、10 dBZ、9 dBZ和7 dBZ,C-VIL平均差值分别为30 kg·m-2、28 kg·m-2、29 kg·m-2和28 kg·m-2。造成强风暴参数差异性的主要因素是大的粒子或者强降雨对CD雷达电磁波强烈衰减,同时泰山CD雷达的地理环境和观测模式也是原因之一。     

CFL-03型风廓线雷达故障分析诊断技巧

现在风廓线雷达已被广泛应用在局地天气预报、空中管制、大气污染预防等方面,对国民经济的发展具有重要的意义。随着雷达使用年限的增加,雷达设备故障率也在增加。由于CFL-03型风廓线雷达已经实现了全固态、模块化设计,许多气象局都订购了相关的备件,因此只要对设备进行故障诊断,判断出故障的位置,进行备件更换,设备就可以恢复正常工作。按照CFL-03型风廓线雷达的组成,对故障部位进行分析,结果表明,常见故障发生的地方一是监控组合的监控板,二是故障发生点为接收机的标频组件、基准组件等,三是故障发生点为发射机的功合部分、波控的波束转换板,四是故障点为天线的一分六公分器。在故障判断过程中,最简单的方法就是利用分机组合上的故障指示灯和软件界面上的故障信息指示表来判断。此外,利用三用表、示波器、频谱仪和矢量网络分析仪等可以进一步判断故障。     

神农架林区西南坡局地暴雨过程诊断分析

神农架林区西南坡为局地暴雨灾害多发区。利用常规资料、多普勒雷达资料和区域自动站资料,分析了导致神农架林区西南坡2014年8月6日至7日夜间连续两场短时暴雨过程中MCS发生发展的天气背景及结构特征,并探讨了神农架山区复杂地形构造对西南坡暴雨的增幅作用。结果表明:1)中高层天气系统强迫弱时,副高边缘地面暖低压倒槽及850 h Pa气旋性弯曲区与辐合的发生发展可能是造成这类局地强降水天气的触发系统,地面弱冷空气的入侵有利于降水的维持和加强。2)两次局地暴雨过程均是由中β尺度对流系统影响产生的,降水历时短、强度大,雨区移动呈现局地性,具有明显的中尺度强对流系统特征,分别属前导层状云与尾随层状云中尺度对流系统型。3)第一场暴雨过程以对流降水为主,回波较强;第二场暴雨过程回波质心低且层状云特征比较突出,但维持时间相对较长,降水效率更高。4)神农架西南坡坡度大,海拔高度高,地形的动力抬升和辐合作用促使上升运动加强,地形强迫抬升作用显著不仅对局地对流触发、降水增幅有重要作用,而且会影响中尺度对流系统结构,这可能是神农架林区西南坡暴雨高发的重要原因。     

Application of a nondestructive method to evaluate the active layer in a cold region

To provide a safe transportation system in an extremely cold region,evaluation needs to be conducted of the thickness and the volumetric water content of the active layer,as they significantly affect frost heave.The objective of this study was to evaluate the dielectric constant(κ)of the active layer using ground-penetrating radar(GPR)and a dynamic cone penetrometer(DCP);this evaluation was then used to estimate the thickness and the volumetric water content of the active layer.A field located in midwest Alaska was selected as the study site.A GPR survey and two DCP tests were conducted on the surface of the ground,and the ground temperature was measured.From the GPR survey,travel times of the electromagnetic wave in the active layer were obtained.In addition,the thickness of the active layer was determined by using the dynamic cone penetration index(DCPI)and ground temperature.By using the travel time and travel distance of the electromagnetic wave in the active layer,dielectric constants were calculated as 26.3 and 26.4 for two DCP points.From the mean dielectric constant,the volumetric water content was estimated to be 40%~43%,and the thickness of the active layer was evaluated along the GPR survey line.The spatial-scaled GPR image showed that the thickness of the active layer varied from 520 mm to 700 mm due to the presence of a puddle,which accelerated the heat exchange.The results show that evaluation of the dielectric constant using the GPR survey and the DCP test can be effectively used to estimate the thickness and the volumetric water content of the active layer.     

华南暴雨试验IOP-6期间6月9日长乐地区强降水风场结构的初步分析

华南暴雨第六次加强观测期间 (IOP-6), 1998年6月9日在福建长乐地区出现了一次局地性的强降水过程.该文应用单多普勒天气雷达资料及其风场反演结果对此次过程进行了初步分析, 从多普勒雷达反演的风场结构看, 这次过程与出现在3~5 km高度上的风切变有关, 在低层雷达回波图像上出现中尺度气旋波的结构, 强降水是气旋波活动的结果.     

青藏高原地面Doppler雷达与TRMM星载雷达测云比较

利用 1998年青藏高原地面Doppler雷达资料和TRMMPR资料进行对比分析 ,分别从不同角度出发 ,分析了Doppler雷达和TRMMPR所测云区在回波结构和回波强度等方面的相同和差异之处 ,以及产生误差的必然和可能的原因