灰色模型用于卫星钟差长期预报的性能研究

利用灰色模型对GPSRb钟和Cs钟进行了长期预报,并与常用的二阶多项式模型预报进行比较,结果表明:灰色模型对GPSCs钟进行长期210d(天)预报时精度高达ns量级,对GPSRb钟的预报精度在10ns量级,明显高于二阶多项式模型的预报精度,满足实际应用中的精度要求。     

GOCE卫星重力计划及其应用

基于CHAMP和GRACE卫星，GOCE(Gravity Field and Stead—state Ocean Circulation Explore)是欧空局(ESA)的一颗重力场和静态洋流探测卫星。利用它可得到空间分辨率为200—80km的全球重力场模型和1cm精度的大地水准面．简要介绍了目前重力卫星的发展现状与其局限性，详细叙述了GOCE卫星的组成、科学目标、测量原理、在地球物理等学科中的重要应用，并提出GOCE等重力卫星资料在我国的应用设想。     

Inter‐annual changes of alpine inland lake water storage on the Tibetan Plateau: Detection and analysis by integrating satellite altimetry and optical imagery

The effects of climate change have a substantial influence on the extremely vulnerable hydrologic environment of the Tibetan Plateau. The estimation of alpine inland lake water storage variations is essential to modeling the alpine hydrologic process and evaluating water resources. Due to a lack of historical hydrologic observations in this remote and inaccessible region, such estimations also fill a gap in studies on the continuous inter‐annual and seasonal changes in the inland lake water budget. Using Lake Siling Co as a case study, we derived a time‐series of lake surface extents from MODIS imagery, and scarce lake water level data from the satellite altimetry of two sensors (ICESat/GLAS and ENVISAT RA‐2) between 2001 and 2011. Then, based on the fact that the rise in lake water levels is tightly dependent on the expansion of the lake extent, we established an empirical model to simulate a continuous lake water level dataset corresponding to the lake area data during the lake's unfreezing period. Consequently, from three dimensions, the lake surface area, water level and water storage variations consistently revealed that Lake Siling Co exhibited a dramatic trend to expand, particularly from 2001 to 2006. Based on the statistical model and lake area measurements from Landsat images since 1972, the extrapolated lake water level and water storage indicate that the lake has maintained a continual expansion process and that the cumulative water storage variations during 1999–2011 account for 66.84% of the total lake water budget (26.87 km³) from 1972 to 2011. Copyright © 2013 John Wiley & Sons, Ltd.     

山东青岛灵山湾南部海滩的时空演变及其影响因素*

全面准确评估海滩的时空演变,是海滩侵蚀防护的前提;基于卫星图像资源全面准确评估海滩的时空演变,对于缺乏长期连续实测数据的海滩的侵蚀防护具有重要意义。本研究基于谷歌地球引擎合成并下载灵南海滩(灵山湾南部海滩)1984—2021年的880幅卫星图像,聚焦海滩剖面提取干湿线和水边线在剖面上的位置;结合模拟潮位分析海滩剖面形态,计算海滩坡度和平均高、低潮线等,采用多指标研究灵南海滩的时空演变;结合历史资料分析影响灵南海滩演变的主要因素,并利用海滩实测数据评估利用卫星图像提取的海滩岸线的误差。结果表明,大量卫星图像的应用提高了研究结果的时间分辨率、精度和可靠性。在1984—2021年间,灵南海滩部分岸段发生了阶段性快速侵蚀,侵蚀速率为5.2~60 m/a,总侵蚀量达30~78 m,持续时间为0.5~11年,该快速侵蚀主要是挖沙、养殖场改建和废弃等人为因素造成的,风暴潮起次要的辅助作用。除上述快速侵蚀时段外,灵南海滩普遍发生慢速侵蚀,侵蚀速率一般小于2 m/a,这是相对海平面上升和河流入海泥沙锐减等的结果。     

气团订正对静止卫星成像仪资料同化在台风预报中的改进效果研究

基于美国台风预报系统（Hurricane Weather Research and Forecasting,HWRF）,研究了气团订正方法对GOES-13/15静止卫星成像仪资料同化效果的改进作用,选取了2012年6月23日生成于大西洋地区的台风Debby作为研究对象,通过一组对照试验比较了气团订正前后台风路径和初始场相关物理量的差异,结果表明:气团订正能显著减小GOES-13/15静止卫星成像仪资料的系统偏差,明显提高台风路径的预报效果,气团订正使得预报的台风路径与观测路径的平均偏差和标准差降低了30%左右,提前6 h实现了台风路径的正确转向。物理机制分析表明,经过气团订正后的静止卫星资料增强了位于台风东南侧副热带高压的强度,同时增加了台风东部的温度和比湿,在引导气流和大气温、湿场的共同作用下,台风预报路径实现了正确转向。      

基于气象卫星的青藏高原低涡识别

利用长时间序列气象卫星及多源数据,研究青藏高原低涡综合识别方法,完成低涡数据集并与青藏高原低涡年鉴中低涡位置、路径和分布进行对比分析。研究表明:卫星识别多年平均低涡分布存在两个高值区,分别位于西藏的中北部和青海西南部及青藏高原西部,在有探空站的青藏高原东部（90°E以东）,卫星识别低涡高值区和年鉴数据吻合,冬半年,卫星识别低涡活动明显高于年鉴,主要为青藏高原西部低涡活动引起,逐年及2008年低涡路径对比也显示,有探空站区域卫星识别低涡和年鉴具有较好的一致性,表明卫星识别低涡在青藏高原东部地区的可信性;2015年青藏高原中西部新增3个探空站,年鉴中90°E以西低涡约占全年低涡总数量的22%,该区域卫星识别低涡和年鉴一致性较高,表明卫星识别低涡在高原中西部的可信性。因此,卫星识别低涡与年鉴低涡在有探空站区域有较好的一致性,可对年鉴中青藏高原东部低涡源地进行追踪,又可识别青藏高原中西部尤其是活跃于冬半年的低涡,是青藏高原年鉴低涡数据的有效补充。     

风云三号D星真彩色影像合成方法研究及应用

多光谱遥感数据真彩色合成影像具有处理速度快、不依赖其他遥感产品、易于理解判读等特点,其在气象、生态环境、减灾等领域具有不可替代的作用。本文以风云三号D卫星MERSI-Ⅱ传感器数据为例,经过大气校正和非线性拉伸等方法合成了真彩色影像。应用真彩色影像对沙尘、蓝藻、火灾和台风等事件进行监测分析,分析结果表明真彩色影像可以在上述事件中起到识别相关事件的影响范围、事件的发展变化情况等信息的作用。     

广西区域性冰雹天气的云图特征分型研究

基于2007-2017年风云系列卫星云图资料,结合高空、地面常规观测资料,针对广西23次区域性冰雹天气过程,从主要影响系统及卫星云图云型特征方面建立3种区域性冰雹卫星云图概念模型,即华北低槽型、高原东部低槽型以及南支槽东移型。结果表明：高空槽云系的位置和所属模型类型较为关键,冰雹云团多起源于高空槽前底部;华南沿海的副热带急流云系对冰雹云团的发生发展起到重要作用,冰雹云团通常发生在副热带急流云系的北侧晴空区中;广西区域性典型冰雹云团表现为长椭圆形,上风方向边界光滑呈"V"型并沿下风方向伸出很长的卷云砧。     

中国HY-2卫星雷达高度计有效波高真实性检验

Chinese Haiyang-2(HY-2) satellite is the first Chinese marine dynamic environment satellite. The dual-frequency(Ku and C band) radar altimeter onboard HY-2 has been working effective to provide operational significant wave height(SWH) for more than three years(October 1, 2011 to present).We validated along-track Ku-band SWH data of HY-2 satellite against National Data Buoy Center(NDBC) in-situ measurements over a time period of three years from October 1, 2011 to September 30, 2014, the root mean square error(RMSE) and mean bias of HY-2SWH is 0.38 m and(–0.13±0.35) m, respectively. We also did cross validation against Jason-2 altimeter SWH data,the RMSE and the mean bias is 0.36 m and(–0.22±0.28) m, respectively. In order to compare the statistical results between HY-2 and Jason-2 satellite SWH data, we validated the Jason-2 satellite radar altimeter along-track Ku-band SWH data against NDBC measurements using the same method. The results demonstrate the validation method in this study is scientific and the RMSE and mean bias of Jason-2 SWH data is 0.26 m and(0.00±0.26) m,respectively. We also validated both HY-2 and Jason-2 SWH data every month, the mean bias of Jason-2 SWH data almost equaled to zero all the time, while the mean bias of HY-2 SWH data was no less than –0.31 m before April2013 and dropped to zero after that time. These results indicate that the statistical results for HY-2 altimeter SWH are reliable and HY-2 altimeter along-track SWH data were steady and of high quality in the last three years. The results also indicate that HY-2 SWH data have greatly been improved and have the same accuracy with Jason-2SWH data after April, 2013. SWH data provided by HY-2 satellite radar altimeter are useful and acceptable for ocean operational applications.     

Generation of high resolution sea surface temperature using multi-satellite data for operational oceanography

In the present article, we introduce a high resolution sea surface temperature(SST) product generated daily by Korea Institute of Ocean Science and Technology(KIOST). The SST product is comprised of four sets of data including eight-hour and daily average SST data of 1 km resolution, and is based on the four infrared(IR) satellite SST data acquired by advanced very high resolution radiometer(AVHRR), Moderate Resolution Imaging Spectroradiometer(MODIS), Multifunctional Transport Satellites-2(MTSAT-2) Imager and Meteorological Imager(MI), two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2(AMSR2), and Wind SAT with in-situ temperature data. These input satellite and in-situ SST data are merged by using the optimal interpolation(OI) algorithm. The root-mean-square-errors(RMSEs) of satellite and in-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from January to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71°C and the bias value was –0.08°C. The largest RMSE and bias were 0.86 and –0.26°C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Japan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60°C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature(GHRSST) product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System(KOOS) as an input parameter for data assimilation.