Arctic sea ice concentration retrieval using the DT-ASI algorithm based on FY-3B/MWRI data

Sea ice concentration (SIC) is one of the most important indicators when monitoring climate changes in the polar region. With the development of the Chinese satellite technology, the FengYun (FY) series has been applied to retrieve the sea ice parameters in the polar region. In this paper, to improve the SIC retrieval accuracy from the passive microwave (PM) data of the Microwave Radiation Imager (MWRI) aboard on the FengYun-3B (FY-3B) Satellite, the dynamic tie-point (DT) Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) (DT-ASI) SIC retrieval algorithm is applied and obtained Arctic SIC data for nearly 10 a (from November 18, 2010 to August 19, 2019). Also, by applying a land spillover correction scheme, the erroneous sea ice along coastlines in melt season is removed. The results of FY-3B/DT-ASI are obviously improved compared to that of FY-3B/NT2 (NASA-Team2) in both SIC and sea ice extent (SIE), and are highly consistent with the results of similar products of AMSR2 (Advanced Microwave Scanning Radiometer 2)/ASI and AMSR2/DT-ASI. Compared with the annual average SIC of FY-3B/NT2, our result is reduced by 2.31％. The annual average SIE difference between the two FY- 3Bs is 1.65×106 km2, of which the DT-ASI algorithm contributes 87.9％ and the land spillover method contributes 12.1％. We further select 58 MODIS (Moderate-resolution Imaging Spectroradiometer) cloud-free samples in the Arctic region and use the tie-point method to retrieve SIC to verify the accuracy of these SIC products. The root mean square difference (RMSD) and mean absolute difference (MAD) of the FY-3B/DT-ASI and MODIS results are 17.2％ and 12.7％, which is close to those of two AMSR2 products with 6.25 km resolution and decreased 8％ and 7.2％ compared with FY-3B/NT2. Further, FY-3B/DT-ASI has the most significant improvement where the SIC is lower than 60％. A high-quality SIC product can be obtained by using the DT-ASI algorithm and our work will be beneficial to promote the application of FengYun Satellite.     

积雪密度演变对北极积雪深度模拟的影响

积雪具有复杂的时空分布,在高纬度地区的气−冰−海耦合系统中扮演了重要的角色。准确的积雪质量平衡计算可以帮助我们更好地理解海冰演变过程以及极区冰雪与大气之间的相互作用。雪密度是影响积雪质量平衡众多因素中的重要因子。现有的一维高分辨率冰雪热力学模型（如HIGHTSI）中,使用常数块体雪密度均值将降雪雪水当量转化为积雪深度。本文参考拉格朗日冰上积雪模型（SnowModel-LG）模式对积雪分层压实的处理,简化为新、旧两个雪层,并在质量守恒条件下同时考虑新、旧雪层深度对压实增密的响应,将该物理过程加入HIGHTSI模式中。利用ERA-Interim再分析数据作为大气强迫,针对北极15个冰质量平衡浮标沿其漂移轨迹模拟了降雪积累期海冰表面雪密度变化对积雪深度变化的影响,在原HIGHTSI设置下分别采用定常块体雪密度均值330 kg/m³（T1试验）、接近实际的常数新雪密度200 kg/m³（T2试验）以及改进后框架下新、旧雪层随时间压实增密的雪密度（T3试验）计算积雪深度,并将模拟结果与浮标观测进行对比。结果表明,本文改进的算法对雪密度变化的处理更为合理,且能较好地再现积雪深度的变化;考虑新、旧雪层深度对压实增密的响应能较好地避免以较低的降雪密度持续过度积累,以浮标观测为标准,分层积雪密度压实计算得到的平均绝对误差相对T2减小了5 cm。     

基于FY-3B/VIRR数据的济南市城市热岛效应与影响因素分析

热岛效应是城市发展过程中的热点社会问题之一。研究以济南为例,基于 FY－3B/VIRR数 据,应用改进型 Becker和 Li “分裂窗” 算法获得遥感地表温度数据;采用热岛强度指数与热岛比例指数,定量分析济南市2013—2020年城市热岛效应的时空变化特征;从自然与社会经济角度,采用灰色关联度分析法,定量评价城市热环境的影响因素对城市热岛效应变化的贡献度。结果表明：1）改进型 Becker和 Li “分裂窗” 算法在济南市有较好应用,与国家级地面气象观测站 “0 cm地表温度” 实测数据线性拟合决定系数 R2 为 0.89。2）热岛区域面积年际变化呈现先增加后减小逐渐平稳的变化趋势,冷岛区域变化特征与热岛区域明显相反。3）夏季热岛区域面积（35.3%）最大,秋季（22.5%）次之,春（11.5%）、冬（10.6%）两季基本持平。4）热岛空间格局以城镇聚合轴为主导驱动,呈现 “点－线” 式空间结构特点。5）热岛比例指数总体呈现下降趋势,2013 年（0.22）与 2014 年（0.24）属较轻热岛年份。6）总人口数与归一化植被指数是影响济南城市热岛效应的主要因素。研究对于加强济南市地表热环境的监测与评价,指导城市规划与生态城市建设具有一定意义。     

长牡蛎细胞周期调控关键基因cyclin B3 的克隆及其在性腺发育中的作用

首次在长牡蛎（Crassostrea gigas）中克隆得到细胞周期蛋白B3（cyclin B3）的cDNA 全长序列和基因组结构序列。cyclin B3 基因cDNA 全长2383 bp, 其中编码区长度为1293 bp, 编码一条含430 个氨基酸的多肽链, 氨基酸序列比对和结构域分析均表明其为其他物种cyclin...