Liquid water path retrieval using the lowest frequency channels of <Emphasis Type="Italic">Fengyun-3C</Emphasis> Microwave Radiation Imager (MWRI)

The Microwave Radiation Imager (MWRI) on board Chinese Fengyun-3 (FY-3) satellites provides measurements at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with both horizontal and vertical polarization channels. Brightness temperature measurements of those channels with their central frequencies higher than 19 GHz from satellite-based microwave imager radiometers had traditionally been used to retrieve cloud liquid water path (LWP) over ocean. The results show that the lowest frequency channels are the most appropriate for retrieving LWP when its values are large. Therefore, a modified LWP retrieval algorithm is developed for retrieving LWP of different magnitudes involving not only the high frequency channels but also the lowest frequency channels of FY-3 MWRI. The theoretical estimates of the LWP retrieval errors are between 0.11 and 0.06 mm for 10.65- and 18.7-GHz channels and between 0.02 and 0.04 mm for 36.5- and 89.0-GHz channels. It is also shown that the brightness temperature observations at 10.65 GHz can be utilized to better retrieve the LWP greater than 3 mm in the eyewall region of Super Typhoon Neoguri (2014). The spiral structure of clouds within and around Typhoon Neoguri can be well captured by combining the LWP retrievals from different frequency channels.     

Liquid Water Path Retrieval Using the Lowest Frequency Channels of Fengyun-3C Microwave Radiation Imager(MWRI)

The Microwave Radiation Imager(MWRI) on board Chinese Fengyun-3(FY-3) satellites provides measurements at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with both horizontal and vertical polarization channels. Brightness temperature measurements of those channels with their central frequencies higher than 19 GHz from satellite-based microwave imager radiometers had traditionally been used to retrieve cloud liquid water path(LWP) over ocean. The results show that the lowest frequency channels are the most appropriate for retrieving LWP when its values are large. Therefore, a modified LWP retrieval algorithm is developed for retrieving LWP of different magnitudes involving not only the high frequency channels but also the lowest frequency channels of FY-3 MWRI. The theoretical estimates of the LWP retrieval errors are between 0.11 and 0.06 mm for 10.65-and 18.7-GHz channels and between0.02 and 0.04 mm for 36.5-and 89.0-GHz channels. It is also shown that the brightness temperature observations at10.65 GHz can be utilized to better retrieve the LWP greater than 3 mm in the eyewall region of Super Typhoon Neoguri(2014). The spiral structure of clouds within and around Typhoon Neoguri can be well captured by combining the LWP retrievals from different frequency channels.     

Spatiotemporal Variations of Microwave Land Surface Emissivity (MLSE) over China Derived from Four-Year Recalibrated Fengyun 3B MWRI Data

Microwave Land Surface Emissivity (MLSE) over China under both clear and cloudy sky conditions was retrieved using measurements of recalibrated microwave brightness temperatures (Tbs) from Fengyun-3B Microwave Radiation Imager (FY-3B MWRI), combined with cloud properties derived from Himawari-8 Advanced Himawari Imager (AHI) observations. The contributions from cloud particles and atmospheric gases to the upwelling Tbs at the top of atmosphere were calculated and removed in radiative transfer. The MLSEs at horizontal polarizations at 10.65, 18.7, and 36.5 GHz during 7 July 2015 to 30 June 2019 over China showed high values in the southeast vegetated area and low values in the northwest barren, or sparsely vegetated, area. The maximum values were found in the belt area of the Qinling-Taihang Mountains and the eastern edge of the Qinghai-Tibet Plateau, which is highly consistent with MLSEs derived from AMSR-E. It demonstrates that the measurements of FY-3B MWRI Tbs, including its calibration and validation, are reliable, and the retrieval algorithm developed in this study works well. Seasonal variations of MLSE in China are mainly driven by the combined effects of vegetation, rainfall, and snow cover. In tropical and southern forest regions, the seasonal variation of MLSE is small due to the enhancement from vegetation and the suppression from rainfall. In the boreal area, snow causes a significant decrease of MLSE at 36.5 GHz in winter. Meanwhile, the MLSE at lower frequencies experiences less suppression. In the desert region in Xinjiang, increases of MLSEs at all frequencies are observed with increasing snow cover.     

Detection and Correction of AMSR-E Radio-Frequency Interference

Radio-frequency interference (RFI) affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E) Aqua satellite observations reveals very strong and widespread RFI contam- inations on the C- and X-band data. Fortunately, the strong and moderate RFI signals can be easily identified using an index on observed brightness temperature spectrum. It is the weak RFI that is diffi- cult to be separated from the nature surface emission. In this study, a new algorithm is proposed for RFI detection and correction. The simulated brightness temperature is used as a background signal (B) and a departure of the observation from the background (O-B) is utilized for detection of RFI. It is found that the O-B departure can result from either a natural event (e.g., precipitation or flooding) or an RFI signal. A separation between the nature event and RFI is further realized based on the scattering index (SI). A positive SI index and low brightness temperatures at high frequencies indicate precipitation. In the RFI correction, a relationship between AMSR-E measurements at 10.65 GHz and those at 18.7 or 6.925 GHz is first developed using the AMSR-E training data sets under RFI-free conditions. Contamination of AMSR-E measurements at 10.65 GHz is then predicted from the RFI-free measurements at 18.7 or 6.925 GHz using this relationship. It is shown that AMSR-E measurements with the RFI-correction algorithm have better agreement with simulations in a variety of surface conditions.     

CLM4.5模式对青藏高原土壤湿度的数值模拟及评估

本文利用1981～2016年的CRUNCEP资料（0.5°×0.5°）作为大气驱动数据,驱动CLM4.5（Community Land Model version 4.5）模式模拟了青藏高原地区1981～2016 年的土壤湿度时空变化。将模拟数据与台站观测资料、再分析资料（ERA-Interim和GLDAS-CLM）和微波遥感FY-3B/MWRI土壤湿度资料对比验证,表明了CLM4.5模拟资料可以合理再现青藏高原地区土壤湿度的空间分布和长期变化趋势。而且基于多种卫星遥感资料建立的较高分辨率（0.1°×0.1°）的青藏高原地表数据更加细致地刻画了土壤湿度的空间变化。对比结果表明:CLM4.5模拟土壤湿度与各个台站观测的时空变化一致,各层土壤湿度的模拟和观测均显著相关,且对浅层的模拟优于深层,但模拟结果比台站观测系统性偏大。模拟与再分析资料和微波遥感资料土壤湿度的空间分布具有一致性,均表现为从青藏高原的西北部向东南部逐渐增加的分布特点,三江源湿地和高原东南部为土壤湿度的高值区,柴达木盆地和新疆塔里木盆地的沙漠地区为低值区,土壤湿度由浅层向深层增加。土壤湿度的长期变化趋势基本表现为“变干—变湿”相间的带状分布,不同层次的土壤湿度变化趋势基本一致。模拟资料也合理地再现了夏季土壤湿度逐月的变化:高原西南地区的土壤湿度明显大范围增加,北部的柴达木盆地的干旱范围也明显的向北收缩,高原南部外围土壤湿度也明显增加,CLM4.5模拟土壤湿度比再分析资料和微波遥感资料更加细致地描述了夏季逐月土壤湿度空间分布及其变化特征。     

基于仿真的6.9 GHz通道亮温改进FY-3D MWRI海面温度产品

海洋表面温度SST（Sea Surface Temperature）是全球海洋和气候研究的重要参数之一，卫星被动微波遥感由于能够实现全天候观测而被越来越多的应用到SST研究中。中国的风云三号（FY 3）卫星搭载的微波成像仪（MWRI）缺少对SST更加敏感的7 GHz附近垂直极化通道，本研究将FY 3 MWRI与具有6.9 GHz通道的Aqua AMSR 2进行时空匹配，采用神经网络方法，利用匹配的FY 3 MWRI的通道亮温模拟仿真AMSR 2的69 GHz垂直极化通道亮温（6.9V），通过引入仿真的6.9V来提高FY 3 MWRI SST的反演精度。结果表明：引入仿真的6.9V可以改进FY 3 MWRI SST反演精度，对35°～90°S之间海域的SST改进更加显著，主要由于6.9V对低SST的探测灵敏度更高且在低SST反演时受风速的影响较小导致的。如果FY3后续卫星可以搭载6.9 GHz通道，将可进一步提升低SST特别是两极SST的反演精度。     

青藏高原CMIP6土壤湿度适用性评估

为了解第六次国际耦合模式比较计划(CMIP6)土壤湿度数据在青藏高原的适用性,利用全球陆面数据同化系统(GL-DAS)Noah模型输出的土壤湿度产品,对CMIP6 Historical试验的土壤湿度数据进行评估.结果表明:在青藏高原地区,CMIP6集合平均土壤湿度总体高于Noah产品,季节变化幅度明显小于Noah产品;...     

FY-3微波成像仪10.6 GHz通道超分辨率图像重建

为改善风云三号 (FY-3) 微波成像仪10.6 GHz通道空间分辨率,提出利用超分辨率图像重建算法进行图像重建。分析并指出FY-3微波成像仪10.6 GHz通道具有过采样特征,具备重建得到高于瞬时视场图像的潜力;基于超分辨率图像重建理论,根据FY-3气象卫星轨道、姿态,微波成像仪性能参数以及工作模式等物理约束,建立微波成像仪的超分辨率成像模型,并推导计算出超分辨率成像模型参数;采用POCS算法重建得到10.6 GHz通道的超分辨率图像,采用目视比较分析、图像统计分析对重建图像进行质量评价:重建图像像元平均梯度提高26.5%,功率谱分量和提高5.7%,重建图像具有更高的空间分辨率;台风亮温分析应用显示了从重建图像可发现更微小的景物细节目标。采用超分辨率图像重建算法对FY-3微波成像仪10.6 GHz通道进行重建处理,结果有效且正确,可为数据用户提供更多可用的遥感数据,对微波遥感数据应用具有提升作用。     

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个,以及对应每个TC的微波十通道亮温和36.50 GHz、89.00 GHz的极化校正亮温度,并简要阐明了该数据集在热带气旋研究方面的潜在应用,尤其对TC生命周期内的微波亮温特征及TC强度变化研究提供了有力的数据支撑。     

Retrieval of Sea Surface Wind Speed by One-Dimensional Synthetic Aperture Microwave Radiometer

One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles. In this paper, we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0° ~65°. We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9, 10.65, 18.7, 23.8 and 36.5 GHz. Then, the microwave radiative transfer forward model is used to simulate the measured brightness temperatures. The sensitivity of the brightness temperatures at 0°~65° to the sea surface wind speed is calculated. Then, vertical polarization channels(VR), horizontal polarization channels(HR) and all channels(AR) are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0° ~65°, and the relationship between the retrieval error and incidence angle is obtained. The results are as follows:(1) The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization.(2) The retrieval error increases with Gaussian noise. The retrieval error of VR first increases and then decreases with increasing incidence angle, the retrieval error of HR gradually decreases with increasing incidence angle, and the retrieval error of AR first decreases and then increases with increasing incidence angle.(3) The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.     

Retrieval of Oceanic Total Precipitable Water Vapor and Cloud Liquid Water from Fengyun-3D Microwave Sounding Instruments

Fengyun-3 D(FY-3 D) satellite is the latest polar-orbiting meteorological satellite launched by China and carries 10 instruments onboard. Its microwave temperature sounder(MWTS) and microwave humidity sounder(MWHS) can acquire a total of 28 channels of brightness temperatures, providing rich information for profiling atmospheric temperature and moisture. However, due to a lack of two important frequencies at 23.8 and 31.4 GHz, it is difficult to retrieve the total precipitable water vapor(TPW) and cloud liquid water path(CLW) from FY-3 D microwave sounder data as commonly done for other microwave sounding instruments. Using the channel similarity between Suomi National Polar-orbiting Partnership(NPP) advanced technology microwave sounder(ATMS) and FY-3 D microwave sounding instruments, a machine learning(ML) technique is used to generate the two missing low-frequency channels of MWTS and MWHS. Then, a new dataset named as combined microwave sounder(CMWS) is obtained,which has the same channel setting as ATMS but the spatial resolution is consistent with MWTS. A statistical inversion method is adopted to retrieve TPW and CLW over oceans from the FY-3 D CMWS. The intercomparison between different satellites shows that the inversion products of FY-3 D CMWS and Suomi NPP ATMS have good consistency in magnitude and distribution. The correlation coefficients of retrieved TPW and CLW between CMWS and ATMS can reach 0.95 and 0.85, respectively.     

四川省多种土壤水分资料对比分析

从降水响应、指标评估两个方面对比分析了四川省西昌、宜宾和乐至3站2017~2018年CLDAS土壤湿度产品、人工观测和自动土壤水分站3种土壤水分资料。结果表明,3种资料的土壤相对湿度对降水都有较好的响应,其中自动站对土壤水分变化的响应最为明显,而CLDAS的响应则较为平缓,CLDAS体积含水量对降水的响应不如CLDAS相对湿度好,特别是在深层,基本没有响应降水影响。对比评估指标显示,各站土壤相对湿度人工观测与自动站的相关性最好,西昌站3种资料两两间相关性最好,乐至站各资料间的相关性较差,偏差和均方根误差也较大,体积含水量各站各资料间相关性没有相对湿度高。总体看,CLDAS土壤湿度产品,特别是相对湿度在浅层对降水的响应要好于深层,与人工观测和自动站的相关性也好于深层,CLDAS土壤湿度产品在浅层可以弥补四川部分地区自动站稀疏的缺陷。      

利用微波辐射计AMSR-E反演陆地上空大气水汽的研究

目前的大气水汽算法只适用于晴空条件,但是全球大部分时间云层覆盖都处于40%～60%之间。因此,只适用于晴空条件下的大气水汽反演算法,是不能满足应用需求的。而微波具有一定的穿透能力这一特点,使得其在全天候大气水汽探测方面具有很大的发展潜力。本文发展了基于微波辐射计AMSR-E的数据反演大气水汽的算法,利用不同波段间地表发射率之间的线性关系,消去辐射计信号中的地表信息,而AMSR-E的23.8GHz对大气水汽比较敏感,因此用其反演大气水汽,反演的结果和MODIS以及实测的数据进行对比,算法优势明显。     

自动土壤水分观测站业务化检验分析

土壤水分监测对农业生产和科学研究都具有重要意义,自动土壤水分观测数据得到了广泛应用,实现了土壤水分的自动监测。通过对天津新建DZN3型自动土壤水分观测站业务化检验过程进行介绍,分析了自动观测数据的到报率和土壤常数的测定,并对人工与自动观测数据做了详细的对比分析,通过两个实例分析了对比检验的方法,确定了能够业务化运行的自动土壤水分观测站,分析了站点未通过检验的原因,并对重新进行业务化检验的站点和日常维护提出了建议,介绍的方法为今后开展相关业务化检验奠定了基础。     

自动土壤水分观测资料应用误差分析

根据从国家气象信息中心实时资料数据库读取的自动土壤水分监测资料,对比同日人工测定的土壤相对湿度数据,发现白天各时次自动监测数据与人工监测数据之间均存在15%左右的差异。具体针对监测仪器自身的结构特点以及中国气象局的业务要求,从两种监测方法自身的监测地段代表性、数据测量和换算、监测土层深度、监测时间、土壤水分常数测算、土壤结构变化等多种角度分析数据间存在差异的原因;认为多种可以估算的差异"叠加"在一起时,对比差异最大可能达到20%左右,加上其他误差因素的影响,实际应用中出现15%左右的差异是可以解释的;选择较长序列的站点实测资料进行了数据差异的实况分析。结合业务中常用的墒情等级判断指标,分析数据差异对客观判断构成的数据干扰和数据损失。建议直接利用体积含水量进行业务应用分析,探究全新的自动土壤水分监测数据应用方法,在具体应用中建立相应的指标体系或指标模型,充分发挥自动土壤水分监测的优势。     

Evaluation of AMSR-E——Derived Soil Moisture over Northern China

In this study,the authors evaluated two re-motely sensed surface soil moisture datasets derived from the Advanced Microwave Scanning Radiometer of the Earth Observing System (AMSR-E) over northern China.The soil moisture datasets were derived from algorithms developed by the National Snow and Ice Data Center (NSIDC) and jointly developed by the Vrije Universiteit Amsterdam and NASA Goddard Space Flight Center (VUA-NASA).The NSIDC and VUA-NASA products were compared to in situ soil moisture data from nine enhanced coordinated observation stations.The VUA-NASA dataset presented a strong correlation with top layer in situ soil moisture observations,and the correla-tion coefficients ranged from 0.34 to 0.73 (p0.01).The correlation coefficients decreased as the observed soil layer depth increased.The correlation coefficients be-tween the NSIDC retrievals and the top layer in situ ob-servations were between 0.10 and 0.62 (p0.01).Fur-thermore,VUA-NASA soil moisture variations agreed well with in situ soil moisture dynamics and responded sensitively to precipitation events.In contrast,the NSIDC dataset failed to capture signals of soil moisture dynamics.The analyses demonstrated that the VUA-NASA product was capable of representing soil moisture conditions over northern China.     

Assessment and Assimilation of FY-3 Humidity Sounders and Imager in the UK Met Office Global Model

China's Feng Yun 3(FY-3) polar orbiting satellites are set to become an important source of observational data for numerical weather prediction(NWP),atmospheric reanalyses,and climate monitoring studies over the next two decades.As part of the Climate Science for Service Partnership China(CSSP China) program,FY-3 B Microwave Humidity Sounder 1(MWHS-1) and FY-3 C MWHS-2 observations have been thoroughly assessed and prepared for operational assimilation.This represents the first time observations from China's polar orbiting satellites have been used in the UK's global NWP model.Since 2016,continuous data quality monitoring has shown occasional bias changes found to be correlated to changes in the energy supply scheme regulating the platform heating system and other transient anomalies.Nonetheless,MWHS-1 and MWHS-2 significantly contribute to the 24-h forecast error reduction by 0.3% and 0.6%,respectively,and the combination of both instruments is shown to improve the fit to the model background of independent sounders by up to 1%.The observations from the Microwave Radiation Imager(MWRI) also are a potentially significant source of benefits for NWP models,but a solar-dependent bias observed in the instrument half-orbits has prevented their assimilation.This paper presents the bases of a correction scheme developed at the Met Office for the purpose of a future assimilation of MWRI data.     

再分析资料和陆面数据同化资料土壤湿度产品在中国北方地区的适用性评估

土壤湿度是地球系统模拟的重要参数之一,准确获得其时空分布和变化特征是研究陆-气相互作用的基础。再分析资料和陆面数据同化资料均可提供全球或区域高分辨率土壤湿度产品,但在使用前需要对其进行评估分析。利用土壤湿度观测数据,计算ERA5、ERA5-Land、NCEP-DOE R2、CRA40再分析资料和GLDAS-Noah、GLDAS-CLSM、CLDAS陆面数据同化资料土壤湿度产品与观测数据的中位数、模拟偏差、相关系数等统计指标,并分季节和气候区讨论不同土壤湿度产品在中国北方地区的模拟效果。结果表明:整体来看,CRA40与观测值的相关性最好,ERA5和ERA5-Land分别对干中心、湿中心模拟效果更好,GLDAS-Noah对于较干土壤地区模拟略偏湿,CLDAS对较湿土壤地区模拟结果以系统性偏干为主,NCEP-DOE R2和GLDAS-CLSM模拟效果较差;ERA5、ERA5-Land、NCEP-DOE R2、GLDAS-Noah和CLDAS在所有季节均为模拟正偏差,春季模拟效果较好的是CRA40、ERA5-Land,夏季和秋季ERA5-Land、ERA5和CRA40与观测值相关性较好,不同产品模拟的冬季土壤湿度和观测值相关性是全年中最小的;不同土壤湿度产品在干旱区以模拟偏湿为主,GLDAS-Noah模拟效果最佳,但模拟土壤湿度峰值和谷值的出现时间较观测较早,GLDAS-Noah、CRA40、ERA5能较好模拟季风区干、湿土壤的持续时段和土壤湿度变化振幅,大部分产品能模拟出夏季风影响过渡区较干土壤和较湿土壤的出现时间。     

中国区域多种微波遥感土壤湿度产品质量评估

以自动土壤水分观测站土壤湿度作为验证数据, 对2012年中国区域ASCAT、WINDSAT、FY3B、SMOS 4种微波遥感土壤湿度产品按省份进行了评估研究。结果表明:ASCAT质量最优, 在中国大多数地区与观测数据的相关系数较高, 归一化标准偏差较小。WINDSAT其次, 质量优于FY3B, 而SMOS在中国大部分地区质量差, 受无线电频率干扰严重。4种产品在中国西北地区表现均略好, 如山西、陕西、宁夏等省区。研究还发现, 同一卫星土壤湿度产品在同一季节, 不同地区评估质量不同, 这可能与不同地区的地表植被覆盖类型有关。     

AMSR-E土壤湿度产品在锡林浩特草地样区的精度验证

AMSR-E土壤湿度产品已逐渐应用于气象,农业等各个领域,对土壤湿度的研究,特别是干旱半干旱地区,有着重要的科研和现实意义.为了验证AMSR-E土壤湿度产品在锡林浩特草地的适用性,利用锡林浩特草地野外实验,在3 km×3km范围内,与同经纬度地面9个点的2 cm土壤体积含水量数据作产品精度验证.通过与降水量的比较,验证了AMSR-E土壤湿度产品的可靠性,通过与地面实测值的比较,验证结果表明,AMSR-E反演的平均土壤体积含水量与地面实测平均土壤体积含水量分别为13.3%和11.8%,两者土壤体积含水量的RMSE为3.7%.