Recent Progress of Fengyun Meteorology Satellites

After nearly 50 years of development, Fengyun(FY) satellite ushered in its best moment. China has become one of the three countries or units in the world(China, USA, and EU) that maintain both polar orbit and geostationary orbit satellites operationally. Up to now, there are 17 Fengyun(FY) satellites that have been launched successfully since 1988. There are two FY polar orbital satellites and four FY geostationary orbit satellites operate in the space to provide a huge amount of the earth observation data to the user communities. The FY satellite data has been applied not only in the meteorological but also in agriculture,hydraulic engineering, environmental, education, scientific research and other fields. More recently, three meteorological satellites have been launched within the past two years. They are FY-4 A on 11 December2016, FY-3 D on 15 November 2017 and FY-2 H on 5 June 2018. This paper introduces the current status of FY meteorological satellites and data service. The updates of the latest three satellites have been addressed.The characteristics of their payloads on-boarding have been specified in details and the benefit fields have been anticipated separately.

FY-2气象卫星在轨管理工程测控关键技术(上)

介绍了风云二号(FY 2)地球静止轨道自旋气象卫星工程测控的关键技术。分析了位置保持、姿态确定、星蚀和日凌的原理,给出了位置保持、姿态控制策略和地影、月影、日凌预报算法。并提出了一种检验定姿结果正确性的方法,提供了相应的工程计算参数。这些策略都已成功地用于FY 2卫星的在轨管理工程测控。

FY2卫星展宽云图接收机设计与实现

静止气象卫星是监测地表、大气、海洋以及空间环境等相关数据的重要手段,为气象、农业、空间环境等领域提供着大量的科学数据。重点对FY2接收机的实现方法进行了研究,主要内容包括二次变频方法、基于HSP50110/HSP50210的数字解调、差分解码、关键参数设置以及信号指示等。最后以误码率为指标并结合图像接收效果对接收机性能进行直观评估,结果表明,所设计的接收机图像清晰、误码率低,具有一定的实际意义与参考价值。

Basic performance of BeiDou-2 navigation satellite system used in LEO satellites precise orbit determination

The visibility for low earth orbit（LEO） satellites provided by the BeiDou-2 system is analyzed and compared with the global positioning system（GPS）. In addition, the spaceborne receivers＇ observations are simulated by the BeiDou satellites broadcast ephemeris and LEO satellites orbits. The precise orbit determination（POD） results show that the along-track component accuracy is much better over the service area than the non-service area, while the accuracy of the other two directions keeps at the same level over different areas. However, the 3-dimensional（3D） accuracy over the two areas shows almost no difference. Only taking into consideration the observation noise and navigation satellite ephemeris errors, the 3D accuracy of the POD is about30 cm. As for the precise relative orbit determination（PROD）, the 3D accuracy is much better over the eastern hemisphere than that of the western hemisphere. The baseline length accuracy is 3.4 mm over the service area, and it is still better than 1 cm over the non-service area. This paper demonstrates that the BeiDou regional constellation could provide global service to LEO satellites for the POD and the PROD. Finally, the benefit of geostationary earth orbit（GEO） satellites is illustrated for POD.

An improvement of snow/cloud discrimination from machine learning using geostationary satellite data

Snow and cloud discrimination is a main factor contributing to errors in satellite-based snow cover.To address the error,satellite-based snow cover performs snow reclassification tests on the cloud pixels of the cloud mask,but the error still remains.Machine Learning(ML)has recently been applied to remote sensing to calculate satellite-based meteorological data,and its utility has been demonstrated.In this study,snow and cloud discrimination errors were analyzed for GK-2A/AMI snow cover,and ML models(Random Forest and Deep Neural Network)were applied to accurately distinguish snow and clouds.The ML-based snow reclassified was integrated with the GK-2A/AMI snow cover through post-processing.We used the S-NPP/VIIRS snow cover and ASOS in situ snow observation data,which are satellite-based snow cover and ground truth data,as validation data to evaluate whether the snow/cloud discrimination is improved.The ML-based integrated snow cover detected 33–53%more snow compared to the GK-2A/AMI snow cover.In terms of performance,the F1-score and overall accuracy of the GK-2A/AMI snow cover was 73.06%and 89.99%,respectively,and those of the integrated snow cover were 76.78–78.28%and 90.93–91.26%,respectively.

国外地球同步轨道气象卫星成像观测模式发展分析

经过多年的发展,国外气象卫星从定时开展全圆盘观测逐步发展到定时全圆盘观测与灵活的区域观测相结合的灵活机动观测模式。定时全圆盘观测主要用于支持大尺度天气系统追踪,数值预报应用以及气候数据集建设;区域观测主要是充分发挥新一代卫星成像仪器时间空间分辨率的优势,开展1000～2000km尺度天气系统,尤其是中小尺度快速变化的对流系统和台风的监测,为天气分析和预警服务。选取有代表性的新一代静止气象卫星两类成像仪器,以采用长线列二维扫描成像机制的美国GOES-R成像仪/欧洲MTG成像仪和采用焦平面成像机制的韩国气象海洋卫星海洋水色仪作为典型光学成像类仪器,讨论其灵活成像模式,以期为我国第二代静止气象卫星风云四号的观测模式优化提供参考。

地球静止轨道CW方程建模误差分析

针对地球静止轨道的小倾角、小偏心率的特点,本文在瞬时密切轨道坐标系推导分析了CW方程的各类误差要素,包括地球非球形摄动、三体引力等环境误差,以及线性化误差、非圆轨道相关误差等。采用误差线性化方法结合CW方程解析解得到了J_(2)、偏心率相关误差项的解析表达式。数值计算表明:地球静止轨道下CW方程的误差项要素较多,与相对运动构型的尺寸、漂移特性等均相关。二次项误差、偏心率相关误差、J_(2)项相关误差量级相当,是地球静止轨道CW方程的主要误差源,同时呈现出常数和低频波动相结合的误差形式,分析结果可作为地球静止轨道高精度相对导航和制导设计的理论依据。

China land soil moisture EnKF data assimilation based on satellite remote sensing data

Soil moisture plays an important role in land-atmosphere interactions. It is an important geophysical parameter in research on climate, hydrology, agriculture, and forestry. Soil moisture has important climatic effects by influencing ground evapotranspi ration, runoff, surface reflectivity, surface emissivity, surface sensible heat and latent heat flux. At the global scale, the extent of its influence on the atmosphere is second only to that of sea surface temperature. At the terrestrial scale, its influence is even greater than that of sea surface temperatures. This paper presents a China Land Soil Moisture Data Assimilation System (CLSMDAS) based on EnKF and land process models, and results of the application of this system in the China Land Soil Moisture Data Assimilation tests. CLSMDAS is comprised of the following components: 1) A land process mo del—Community Land Model Version 3.0 (CLM3.0)—developed by the US National Center for Atmospheric Research (NCAR); 2) Precipitation of atmospheric forcing data and surface-incident solar radiation data come from hourly outputs of the FY2 geostationary meteorological satellite; 3) EnKF (Ensemble Kalman Filter) land data assimilation method; and 4) Observa tion data including satellite-inverted soil moisture outputs of the AMSR-E satellite and soil moisture observation data. Results of soil moisture assimilation tests from June to September 2006 were analyzed with CLSMDAS. Both simulation and assimila tion results of the land model reflected reasonably the temporal-spatial distribution of soil moisture. The assimilated soil mois ture distribution matches very well with severe summer droughts in Chongqing and Sichuan Province in August 2006, the worst since the foundation of the People’s Republic of China in 1949. It also matches drought regions that occurred in eastern Hubei and southern Guangxi in September.

MTSAT-2静止气象卫星中国区域雪盖监测

利用MTSAT-2静止气象卫星数据开展了中国区域的雪盖监测研究,结合MODIS雪盖产品及站点雪深观测数据对判识结果进行对比分析和验证。首先,根据MTSAT-2静止气象卫星数据特点,进行角度效应校正及多时相数据合成,以减少云对图像的影响;其次,根据多个雪盖判识因子建立中国区域雪盖判识算法;最后,对比分析2011年1月份MTSAT-2和MODIS雪盖判识结果,并使用站点观测数据进行精度验证。研究表明:(1)MTSAT-2雪盖判识受云影响比例约30%,MODIS雪盖产品受云影响比例约60%,MTSAT-2去云效果明显。(2)无云情况下,MTSAT-2雪盖判识和MODIS雪盖产品判识精度均高于92%;有云覆盖时,MTSAT-2判识精度约65%,优于MODIS雪盖产品35%的判识精度。(3)MTSAT-2静止气象卫星在保持高积雪判识精度的前提下,可以更有效减少云对雪盖判识影响,实时获取更多地表真实信息。该研究对中国区域雪盖信息准确监测、气候变化研究以及防灾减灾等具有重要意义。