FY-3D MERSI-Ⅱ反射太阳波段长期响应衰减估计及订正方法

遥感仪器的长期辐射响应衰减估计与订正是提高卫星遥感数据稳定性和准确性的关键。利用MERSI-Ⅱ在沙漠和DCC稳定目标上空的长时间观测数据,建立仪器辐射响应与时间的函数关系模型,并通过逆方差加权平均方法融合两种稳定目标的结果,获取仪器辐射响应退化量和辐射定标系数的序列估计。辐射响应衰减跟踪监测结果表明,MERSI-Ⅱ自在轨开始业务运行到2022年9月,波长小于500 nm的3个蓝光波段(通道1,通道8—9)和波长大于1000 nm的4个近红外-短波红外波段(通道5—7,通道19)存在明显衰减,年衰减率为1.47%~4.32%。L1级产品精度检验也发现,7个明显衰减通道的业务定标偏差均超过±5%,其中通道5和8偏差最大,约为-20%。应用本研究获取的辐射定标系数序列后,L1产品辐射定标精度随时间变化平稳,定标偏差维持在±3%以内,同时L2级产品精度也明显提升,表明了该研究建立的辐射衰减估计与订正方法的有效性。

基于FY-3D卫星的微波与光学陆表温度融合研究

目前还没有基于国产卫星的1 km分辨率的全天候陆表温度(LST)产品,FY-3D卫星提供了中分辨率成像仪(MERSI)Ⅱ型1 km分辨率晴空LST产品与微波成像仪(MWRI)25 km全天候LST产品,因此可结合两者优势开展全天候1 km分辨率LST的融合研究。基于地理加权回归(GWR)方法,选择海拔、FY-3D归一化植被指数和归一化建筑指数等建立GWR模型对FY-3D/MWRI 25 km LST降尺度到1 km,并与MERSI 1 km LST进行融合;同时针对MWRI轨道间隙,利用前后1天融合后的云覆盖像元1 km LST进行补值,可以得到接近全天候下的1 km LST。基于以上融合算法,选择了中国区域多个典型日期FY-3D/MERSI和MWRI LST官网产品进行了融合试验,并利用公开发布的全天候1 km LST产品(TPDC LST)对FY-3D 1 km LST融合结果进行了评估。研究结果表明,基于GWR法的LST降尺度方法,可以有效避免传统微波LST降尺度方法中存在的“斑块”效应和局地温度偏低等问题;LST融合结果有值率从融合前的22.4%~36.9%可提高到融合后69.3%~80.7%,融合结果与TPDC LST的空间决定系数为0.503~0.787,均方根误差为3.6~5.8 K,其中晴空为2.6~4.9 K,云下为4.1~6.1 K;分析还表明目前官网产品FY-3D/MERSI和MWRI LST均存在缺值较多与精度偏低等问题,显示其存在较大改进潜力,这有利于进一步改进FY-3D LST融合质量。

基于re3data的中英科学数据仓储平台对比研究

以re3data为数据获取源,选取中英两国406个科学数据仓储为研究对象,从分布特征、责任类型、仓储许可、技术标准及质量标准等5个方面、11个指标对两国科学数据仓储的建设情况进行对比分析,试图为我国数据仓储的可持续发展提出建议:广泛联结国内外异质机构,推进多学科领域的交流与合作,有效扩充仓储许可权限与类型,优化技术标准的应用现况,提高元数据使用的灵活性。

FY-3D MWRI在轨交叉辐射定标和海表温度反演

海表温度(sea surface temperature,SST)在气候监测、海洋学研究、渔业经济研究和污染监测等多个方面起着重要作用。本文利用风云三号D星(FY-3D)微波成像仪(Microwave Radiation Imager,MWRI)数据对海表温度进行了反演。首先,以全球降水测量(Global Precipitation Measurement,GPM)卫星微波成像仪(GPM Microwave Imager,GMI)作为参考传感器,采用基于海洋微波辐射传输模型(radiative transfer model,RTM)的双差异方法对FY-3D MWRI进行交叉辐射定标,消除了其在轨辐射定标偏差,为精确反演海表温度奠定了基础;然后,在波段选择的基础上提出耦合微波海表发射率的海表温度多波段反演新算法,与传统的多波段反演算法相比,新反演算法的均方根误差从0.74 K减少至0.69 K;最后,用新反演算法从2020年的FY-3D MWRI数据反演得到全球的海表温度,并用时空匹配的iQuam浮标数据和GMI海表温度产品对反演结果进行精度验证,误差分别为0.04±1.13 K和−0.07±1.18 K。另外,在相同的条件下,用传统多波段算法反演得到的海表温度的误差分别为0.30±1.17 K和0.10±1.17 K。新算法的理论精度和实际反演精度均优于传统的多波段算法,说明本文发展的耦合微波海表发射率的多通道反演新算法是有效和精确的。

The First Global Map of Atmospheric Ammonia(NH_(3)) as Observed by the HIRAS/FY-3D Satellite

Atmospheric ammonia(NH_(3)) is a chemically active trace gas that plays an important role in the atmospheric environment and climate change. Satellite remote sensing is a powerful technique to monitor NH_(3) concentration based on the absorption lines of NH_(3) in the thermal infrared region. In this study, we establish a retrieval algorithm to derive the NH_(3)column from the Hyperspectral Infrared Atmospheric Sounder(HIRAS) onboard the Chinese Feng Yun(FY)-3D satellite and present the first atmospheric NH_(3) column global map observed by the HIRAS instrument. The HIRAS observations can well capture NH_(3) hotspots around the world, e.g., India, West Africa, and East China, where large NH_(3) emissions exist. The HIRAS NH_(3) columns are also compared to the space-based Infrared Atmospheric Sounding Interferometer(IASI)measurements, and we find that the two instruments observe a consistent NH_(3) global distribution, with correlation coefficient(R) values of 0.28–0.73. Finally, some remaining issues about the HIRAS NH_(3) retrieval are discussed.

新疆区域FY-3 NDVI数据集质量比较评估及其适用性评价

利用2014−2020年空间分辨率为250m×250m的MODIS和FY-3的NDVI数据,采用最大值合成法(MVC)合成MODIS和FY-3数据集周、月尺度NDVI值,基于不同数据集月尺度NDVI最大值,分别计算其季节、年平均NDVI。采用数值对比、相关性和线性回归等方法,比较分析2014−2020年新疆区域FY-3和MODIS NDVI数据的一致性,讨论FY-3在新疆区域的适用性,并基于FY-3 NDVI数据,采用变异系数法研究2014−2020年新疆植被覆盖的变化。结果表明:2014−2020年新疆区域的MODIS NDVI的月均值普遍低于FY-3 NDVI,两种数据变化规律一致性较好,但月尺度NDVI在沙地、草地、林地、耕地、2017年春季、2016年和2018年夏季、2015年和2019年秋季及2019年冬季存在差异,差异区主要位于阿勒泰山区、伊犁河谷和天山东段。2020年新疆区域各土地利用类型及季节的FY-3 NDVI均值高于MODIS NDVI均值,且FY-3 NDVI更接近实测值。新疆各土地利用类型及季节FY-3 NDVI数据的R^(2)、RMSE、MAD、RE、残差(θ)均低于MODIS NDVI,表明FY-3数据趋于集中,在新疆区域稳定性高于MODIS。新疆区域植被NDVI季节和空间稳定性差异较大,季节尺度上夏季波动性较小,春、秋季波动性较大;空间上,草地、森林、绿洲农耕区植被覆盖状况越好,植被年际稳定性越强。

Fusion SST from Infrared and Microwave Measurement of FY-3D Meteorological Satellite

Sea surface temperature(SST)is one of the important parameters of global ocean and climate research,which can be retrieved by satellite infrared and passive microwave remote sensing instruments.While satellite infrared SST offers high spatial resolution,it is limited by cloud cover.On the other hand,passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall,coastal effects,and high wind speeds.To achieve high-precision,comprehensive,and high-resolution SST data,it is essential to fuse infrared and microwave SST measurements.In this study,data from the Fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)SST and microwave imager(MWRI)SST were fused.Firstly,the accuracy of both MERSIII SST and MWRI SST was verified,and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST.After pretreatment and quality control of MERSI SST and MWRI SST,a Piece-Wise Regression method was employed to correct biases in MWRI SST.Subsequently,SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date.Finally,an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST.The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST.Furthermore,the fusion SST retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA SST.This study has improved the accuracy of FY satellite fusion SST products in China.

A LiDAR Point Clouds Dataset of Ships in a Maritime Environment

For the first time, this article introduces a LiDAR Point Clouds Dataset of Ships composed of both collected and simulated data to address the scarcity of LiDAR data in maritime applications. The collected data are acquired using specialized maritime LiDAR sensors in both inland waterways and wide-open ocean environments. The simulated data is generated by placing a ship in the LiDAR coordinate system and scanning it with a redeveloped Blensor that emulates the operation of a LiDAR sensor equipped with various laser beams. Furthermore,we also render point clouds for foggy and rainy weather conditions. To describe a realistic shipping environment, a dynamic tail wave is modeled by iterating the wave elevation of each point in a time series. Finally, networks serving small objects are migrated to ship applications by feeding our dataset. The positive effect of simulated data is described in object detection experiments, and the negative impact of tail waves as noise is verified in single-object tracking experiments. The Dataset is available at https://github.com/zqy411470859/ship_dataset.

Application of 9-component S-wave 3D seismic data to study sedimentary facies and reservoirs in a biogasbearing area:A case study on the Pleistocene Qigequan Formation in Taidong area,Sanhu Depression,Qaidam Basin,NW China

To solve the problems in restoring sedimentary facies and predicting reservoirs in loose gas-bearing sediment,based on seismic sedimentologic analysis of the first 9-component S-wave 3D seismic dataset of China,a fourth-order isochronous stratigraphic framework was set up and then sedimentary facies and reservoirs in the Pleistocene Qigequan Formation in Taidong area of Qaidam Basin were studied by seismic geomorphology and seismic lithology.The study method and thought are as following.Firstly,techniques of phase rotation,frequency decomposition and fusion,and stratal slicing were applied to the 9-component S-wave seismic data to restore sedimentary facies of major marker beds based on sedimentary models reflected by satellite images.Then,techniques of seismic attribute extraction,principal component analysis,and random fitting were applied to calculate the reservoir thickness and physical parameters of a key sandbody,and the results are satisfactory and confirmed by blind testing wells.Study results reveal that the dominant sedimentary facies in the Qigequan Formation within the study area are delta front and shallow lake.The RGB fused slices indicate that there are two cycles with three sets of underwater distributary channel systems in one period.Among them,sandstones in the distributary channels of middle-low Qigequan Formation are thick and broad with superior physical properties,which are favorable reservoirs.The reservoir permeability is also affected by diagenesis.Distributary channel sandstone reservoirs extend further to the west of Sebei-1 gas field,which provides a basis to expand exploration to the western peripheral area.

A Semantic-Sensitive Approach to Indoor and Outdoor 3D Data Organization

Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data models are studied,and the characteristics of building information modeling standards(IFC),city geographic modeling language(CityGML),indoor modeling language(IndoorGML),and other models are compared and analyzed.CityGML and IndoorGML models face challenges in satisfying diverse application scenarios and requirements due to limitations in their expression capabilities.It is proposed to combine the semantic information of the model objects to effectively partition and organize the indoor and outdoor spatial 3D model data and to construct the indoor and outdoor data organization mechanism of“chunk-layer-subobject-entrances-area-detail object.”This method is verified by proposing a 3D data organization method for indoor and outdoor space and constructing a 3D visualization system based on it.

Retrieval of snow depth on Antarctic sea ice from the FY-3D MWRI data

The snow depth on sea ice is an extremely critical part of the cryosphere.Monitoring and understanding changes of snow depth on Antarctic sea ice is beneficial for research on sea ice and global climate change.The Microwave Radiation Imager(MWRI)sensor aboard the Chinese FengYun-3D(FY-3D)satellite has great potential for obtaining information of the spatial and temporal distribution of snow depth on the sea ice.By comparing in-situ snow depth measurements during the 35th Chinese Antarctic Research Expedition(CHINARE-35),we took advantage of the combination of multiple gradient ratio(GR(36V,10V)and GR(36V,18V))derived from the measured brightness temperature of FY-3D MWRI to estimate the snow depth.This method could simultaneously introduce the advantages of high and low GR in the snow depth retrieval model and perform well in both deep and shallow snow layers.Based on this,we constructed a novel model to retrieve the FY-3D MWRI snow depth on Antarctic sea ice.The new model validated by the ship-based observational snow depth data from CHINARE-35 and the snow depth measured by snow buoys from the Alfred Wegener Institute(AWI)suggest that the model proposed in this study performs better than traditional models,with root mean square deviations(RMSDs)of 8.59 cm and 7.71 cm,respectively.A comparison with the snow depth measured from Operation IceBridge(OIB)project indicates that FY-3D MWRI snow depth was more accurate than the released snow depth product from the U.S.National Snow and Ice Data Center(NSIDC)and the National Tibetan Plateau Data Center(NTPDC).The spatial distribution of the snow depth from FY-3D MWRI agrees basically with that from ICESat-2;this demonstrates its reliability for estimating Antarctic snow depth,and thus has great potential for understanding snow depth variations on Antarctic sea ice in the context of global climate change.

基于FY-3D MERSIⅡ数据的辽宁省作物生长季日平均气温估算方法比较

作为反映气候特征的重要指标之一,日平均气温在农业气象灾害监测和气候变化研究等领域承担着至关重要的作用。与传统日平均气温的监测和估算方式相比,遥感技术具有全方位、宏观、动态等不可比拟的绝对优势,能够准确地描述日平均气温的空间异质性。为提高农业服务质量,保证农业健康、可持续发展,探索作物生长季日平均气温遥感反演方法,提高农业气象灾害监测精确度,以FY-3D MERSIⅡ遥感数据为基础,提取研究区日间地表温度(LST_(day))、夜间地表温度(LST_(night))、归一化植被指数(NDVI),同时还考虑了高程(DEM)、坡度(Slope)两个变量,结合气象站日平均气温数据,分别构建多元线性回归和随机森林日平均气温遥感反演模型,开展辽宁省2021年作物生长季(5—9月)日平均气温遥感监测的应用研究。结果表明:(1)基于多元线性回归模型反演的日平均气温均方根误差(RMSE)为1.71℃,平均绝对误差(MAE)为1.45℃;基于随机森林反演误差RMSE为1.17℃,MAE为0.96℃;整体上,随机森林的日平均气温反演结果更好,适用性更强。(2)实验当天和前1 d的降水总量对日平均气温的估算结果具有很大影响,降水量随时间的变化曲线与日平均气温的反演误差散点分布情况基本一致,呈现降水总量越大,日平均气温的反演误差越大的趋势,日平均气温反演结果受大气水汽含量的影响很大。(3)对输入的气温影响因子的重要性进行动态的统计分析,发现LST_(day)和DEM是日平均气温反演时两个最重要的变量,且LST_(day)对日平均气温反演的影响最为重要,但是随着作物的生长,DEM的重要性也越来越凸显。

FY-3C MWHS-Ⅱ辐射率在RMAPS-CA中的同化

中亚地区常规气象观测站点稀疏,同化极轨卫星FY-3C上的Ⅱ型微波湿度探测器(MWHS-Ⅱ)辐射率资料可有效减小该地区数值预报初始场的不确定性。本研究首次在中亚快速更新多尺度资料分析和预报系统RMAPS-CA中同化了FY-3C/MWHS-Ⅱ辐射率,评估了其同化效果。结果表明:(1)单个时次冷启动的同化时间窗口内,仅有56%的辐射率资料通过了质量控制并被RMAPS-CA同化。(2)偏差订正整体减小了各水汽通道的背景场辐射亮温偏差,最大减幅出现在通道14,达0.5 K。通道14偏差订正前的观测辐射亮温和背景场辐射亮温间存在较大偏差,是其同化应用中需要特别注意的。(3)FY-3C/MWHS-Ⅱ辐射率同化整体提高了RMAPS-CA系统对高空温度、位势高度、高空风速等的中短期预报准确率。同时,使得2 m温度和10 m风速的预报准确率预报均方根误差分别平均减小了0.2 K和2 m/s。其同化有效降低了小雨预报的漏报率和空报率,小雨预报的TS评分提升了16%。降低了中雨和大雨预报的漏报率,3个量级降水预报的BIAS评分分别提升了18%、38%和36%。

FY-3B/D星NDVI与MODIS NDVI对作物长势监测对比

风云三号卫星(FY-3)NDVI数据是中国对全球用户开放可进行全球尺度作物长势监测的主要卫星遥感数据源,客观评估其进行作物长势监测的真实状况和能力,对业务产品应用推广、产品算法和流程改进以及长时序标准数据生产等具有重要意义。采用国际通用的年际差值比较模型、植被状况指数模型(VCI)以及基于NDVI的作物生长过程评估了中国风云三号B星(FY-3B)和D星(FY-3D)NDVI旬、月合成业务产品与同期MODIS MOD13A1和MOD13A3 NDVI数据对作物长势的监测情况。年际比较模型结果表明,FY-3 NDVI的监测动态范围比MODIS NDVI的窄约0.1—0.15,两者差值在-0.02—0.02,均方根误差在0.08—0.09,在长势分级评估时可忽略,但动态范围偏窄提示有必要在分级评估时使用窄一些的阈值范围。植被状况指数模型结果表明,FY-3B NDVI和MODIS NDVI的监测结果高度一致,因此FY-3B NDVI和MODIS NDVI一样可准确反映作物生长的年际差异。作物生长过程动态监测结果表明,FY-3和MODIS月合成NDVI的年际比较结果总体一致,但在作物快速生长阶段,MODIS用3个16 d数据采用权重法合成月值的方法有一定偏差,导致两者出现差异;FY-3旬合成数据和MODIS 16 d合成数据的监测结果总体一致,前者在作物生长旺季的年际区分度更优,后者的监测曲线更平滑。但是,FY-3 NDVI与MODIS NDVI存在总体偏差,需进一步的数据处理、质量控制和客观标定,以生成与MODIS、AVHRR等一致且连续的长时序FY-3 NDVI标准数据集产品,方可用于作物生长参数定量评估。

2 cm以上的C-TI-RADS 3类甲状腺结节的临床特点分析

目的统计2 cm以上的中国版甲状腺影像报告及数据系统(C-TI-RADS)3类甲状腺结节的临床特点,并探究其与性别、结节成分、对侧是否有癌、是否弥漫性回声改变、甲状腺过氧化物酶抗体(thyroid peroxidase antibody,TPOAB)、甲状腺球蛋白抗体(anti-thyroglobulin antibodies,TGAB)等的相关性。方法回顾性分析2022年9月-2023年3月我科收治的甲状腺超声C-TI-RADS 3类且最大直径≥2 cm的94例甲状腺结节患者(均接受细胞病理和/或组织病理检查)的临床病理学信息。统计TBSⅠ类、良性、低风险肿瘤、恶性的比例,并比较性别、结节成分、对侧是否有癌、是否弥漫性回声改变、TPOAB、TGAB等临床特点在良性、低风险肿瘤、恶性三组中的比例有无统计学差异。结果排除7例TBSⅠ类患者,87例结节病理明确患者中,良性72例(细胞学38例、组织学34例)、低风险肿瘤5例(细胞学2例、组织学3例)、恶性10例(PTC 8例、FTC 1例、MTC 1例)。不同病理类型之间,结节成分(囊实性/实性)组间差异具有显著性,差异有统计学意义(χ^(2)=10.369,P=0.006);性别、是否弥漫性回声改变、对侧是否有癌、TPOAB、TGAB组间差异无统计学意义(P均>0.05)。进一步分析结节成分与病理类型的关系,结果表明,低风险肿瘤相对于良性结节实性比例更高,差异有统计学意义(χ^(2)=9.571,P=0.002);而恶性结节相对于低风险肿瘤(χ^(2)=2.143,P=0.143),恶性结节相对于良性结节(χ^(2)=2.165,P=0.141)囊实性比例差异均无统计学意义。结论虽然各种版本的甲状腺影像报告与数据系统均将TI-RADS 3级结节认定为良性可能,但恶性结节在C-TI-RADS 3类甲状腺结节中仍占一定比例,需要重视诸如囊实性结节、甲状腺滤泡性肿瘤、甲状腺髓样癌等超声征象不典型的甲状腺结节。在评估结节良恶性时,超声引导下细针穿刺细胞病理学检查是必要的,需要重视标本不满意或无法诊断的情况,提高诊断的准确性。

FY-3B/3C和AMSR2土壤含水量产品在锡林郭勒草原地区的适用性评价

土壤表层含水量存在于陆-气界面,是模拟全球水文、能源和碳循环及其相互作用的一个重要变量,对于气候和地球系统研究至关重要。为了评价风云三号B星(FY-3B)、风云三号C星(FY-3C)、先进微波扫描辐射计(AMSR2)土壤含水量产品在锡林郭勒草原以及不同土地覆盖类型的精度和适用性,本文基于2014-2019年生长季的地面观测数据,应用时间序列相关性(R)、均方根误差(RMSE)、平均偏差(Bias)和无偏均方根误差(ubRMSE)分析了这三种网格产品的可靠性。结果表明:(1)在日尺度上,FY-3B和FY-3C土壤含水量产品高估了陆地表层含水量,AMSR2低估了土壤含水量;各项评价指标表明三种土壤含水量产品均能够捕捉锡林郭勒草原表层土壤含水量的时间变化趋势。(2)在月尺度上,与AMSR2相比,FY-3B和FY-3C土壤含水量产品的月度分布与实测土壤含水量分布较为一致。(3)在生长季尺度,3种卫星土壤含水量产品能够反映各草原亚型的土壤含水量状况;FY-3B和FY-3C土壤含水量产品在植被覆盖较高的地区适用性较好,AMSR2在植被覆盖较低的地区可靠性较好,3种产品在监测土壤含水量方面具有互补功能;FY-3B与原位土壤含水量的变化趋势一致性最好;FY-3B和FY-3C能较好反映研究区西部和东部土壤含水量变异情况,AMSR2能很好捕捉研究区中部土壤含水量变异状况。

Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the“21·7”Henan Extremely Persistent Heavy Rainfall

Assimilation of the Advanced Geostationary Radiance Imager(AGRI)clear-sky radiance in a regional model is performed.The forecasting effectiveness of the assimilation of two water vapor(WV)channels with conventional observations for the“21·7”Henan extremely heavy rainfall is analyzed and compared with a baseline test that assimilates only conventional observations in this study.The results show that the 24-h cumulative precipitation forecast by the assimilation experiment with the addition of the AGRI exceeds 500 mm,compared to a maximum value of 532.6 mm measured by the national meteorological stations,and that the location of the maximum precipitation is consistent with the observations.The results for the short periods of intense precipitation processes are that the simulation of the location and intensity of the 3-h cumulative precipitation is also relatively accurate.The analysis increment shows that the main difference between the two sets of assimilation experiments is over the ocean due to the additional ocean observations provided by FY-4A,which compensates for the lack of ocean observations.The assimilation of satellite data adjusts the vertical and horizontal wind fields over the ocean by adjusting the atmospheric temperature and humidity,which ultimately results in a narrower and stronger WV transport path to the center of heavy precipitation in Zhengzhou in the lower troposphere.Conversely,the WV convergence and upward motion in the control experiment are more dispersed;therefore,the precipitation centers are also correspondingly more dispersed.

Assimilation of FY-3D MWTS-Ⅱ Radiance with 3D Precipitation Detection and the Impacts on Typhoon Forecasts

Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally,without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach.In this study,the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2(MWTS-Ⅱ)onboard the Fengyun-3D,which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters.Cycling data assimilation and forecasting experiments for Typhoons Lekima(2019)and Mitag(2019)are carried out.Compared with the control experiment,the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%.The quality of the additional MWTS-Ⅱradiance data is close to the clear-sky data.The case studies show that the average root-mean-square errors(RMSE)of prognostic variables are reduced by 1.7%in the upper troposphere,leading to an average reduction of4.53%in typhoon track forecasts.The detailed diagnoses of Typhoon Lekima(2019)further show that the additional MWTS-Ⅱradiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation,thus providing more precise structures.This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts.

新息增量法评估FY-3E/HIRAS-Ⅱ观测质量

FY-3E/HIRAS-Ⅱ作为世界上第一个晨昏轨道的星载红外高光谱仪器,评估其观测资料质量对提高资料同化分析场和全球数值天气预报精度具有十分重要的作用。本文基于2021年12月-2022年1月及2022年3月共35天的HIRAS-Ⅱ观测,采用新息增量法检验了其在轨辐射观测资料质量,按陆地和洋面分别统计了O-B偏差和标准差的分布特征;进一步匹配相同时间段、相同区域的MetOp-B/IASI观测资料,使用双重差异的O-B法分析了HIRAS-Ⅱ观测资料质量,可消除偏差中辐射传输模式模拟的影响。结果表明,不论海洋还是陆地,HIRAS-Ⅱ长波与中波大部分通道的O-B平均偏差均小于0.5 K、标准差在1 K以内,陆地上标准差比洋面偏大(尤其是窗区通道)。664~665 cm^(-1)CO_(2)吸收带和1300~1680 cm^(-1)水汽吸收带,由于再分析资料的偏差引起RTTOV模拟的辐射值存在系统性误差,使得偏差较大;980~1080 cm^(-1)O_(3)吸收带和1300 cm^(-1)CH_(4)吸收带附近较大的偏差是由于辐射传输模式RTTOV中吸收气体浓度采用固定的气候廓线值造成的,这些波段与MetOp-B/IASI相比的double O-B偏差均趋近于0 K,说明O-B偏差主要是由于辐射传输模式模拟误差造成的,而不是仪器观测的质量低。短波大部分通道的O-B平均偏差在-2 K~2 K之间,标准差在2 K以内。1920 cm^(-1)附近通道由于是仪器中波与短波的交界处,采用的探测器不同造成较大的O-B偏差。2267~2380 cm^(-1)较大的偏差是由于RTTOV模拟亮温时没有考虑非局地热力平衡NLTE效应的影响。波数大于2400 cm^(-1)的短波波段由于太阳污染使得偏差和标准差都逐渐增大。HIRAS-ⅡO-B偏差随扫描角存在不对称现象,使用时需要进行扫描角偏差订正。

融合GNSS和随机森林算法的FY-3D PWV高精度校正模型

FY-3D可降水量(precipitable water vapor,PWV)是我国新一代极轨气象卫星提供的新型遥感水汽产品。针对降水、云、地表反射等因素影响导致的FY-3D PWV产品精度不高的问题,提出了一种融合GNSS和随机森林算法的FY-3D PWV高精度校正模型。该模型使用随机森林算法作为核心结构,充分考虑FY-3D PWV产品的多类型影响因素,以FY-3D像元的PWV值、时间、位置、高程、地表类型以及观测姿态等特征参数为输入变量,以高精度GNSS PWV为目标变量,利用美国西部地区2020年的实测数据进行了模型训练和测试。实验结果表明,相比于初始产品和线性校正模型,该模型分别使FY-3D PWV产品的精度提高了40.68%和36.07%,说明了其在FY-3D水汽产品校正中的优越性和稳定性。