基于CCI和MODIS数据的淮河流域地表土壤湿度降尺度方法研究

土壤湿度是控制陆地和大气间水热能量交换的一个关键参数,同时也是陆面生态系统水循环的重要组成部分。本文选用25 km分辨率的CCI(Climate Change Initiative)土壤湿度产品数据,并结合1 km分辨率的MODIS数据,构建微波土壤湿度产品数据降尺度回归算法,获取淮河流域1 km空间分辨率的土壤湿度数据。降尺度后所获取淮河流域1 km空间分辨率的土壤湿度数据总体上提高了25 km空间分辨率的CCI土壤湿度产品数据的精度.     

Comparison of soil moisture products from microwave remote sensing,land model,and reanalysis using global ground observations

High-quality soil moisture (SM) datasets are in great demand for climate, hydrology, and other fields, but detailed evaluation of SM products from various sources is scarce. Thus, using 670 SM stations worldwide, we evaluated and compared SM products from microwave remote sensing [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) (C- and X-bands) and European Space Agency's Climate Change Initiative (ESA CCI)], land surface model [Global Land Data Assimilation System (GLDAS)], and reanalysis data [ECMWF Re-Analysis-Interim (ERA-Interim) and National Centers for Environmental Prediction (NCEP)] under different time scales and various climates and land covers. We find that: (a) ESA CCI and GLDAS have the closest values to the in situ SM on the annual scale, whereas others overestimate the SM; ERA-Interim (averaged R = 0.58) and ESA CCI (averaged R = 0.54) correlate best with the in situ data, while GLDAS performs worst. (b) Overall, the deviations of each product vary in seasons. ESA CCI and ERA-Interim products are closer to the in situ SM at seasonal scales, and AMSR-E and NCEP perform worst in December–February and June–August, respectively. (c) Except for NCEP and ERA-Interim, others can well reflect the intermonthly variation of the in situ SM. (d) Under various climates and land covers, AMSR-E products are less effective in cold climates, whereas GLDAS and NCEP products perform poorly in arid or temperate and dry climates. Moreover, the Bias and R of each SM product differ obviously under different forest types, especially the AMSR-E products. In summary, SM from ESA CCI is the best, followed by ERA-Interim product, and precipitation is an important auxiliary data for selecting high-quality SM stations and improving the accuracy of SM from GLDAS. These results can provide a reference for improving the accuracy of the above SM products.     

二次电泳法分离管藻目绿藻PSI亚复合物研究

通过PAGE分离管藻目绿藻刺松藻和假根羽藻的PSI复合物CPIa，和CPI，二次电泳分析得到了多种亚复合物组分，其中包括PSI捕光复合物LHCI和不含LHCI的核心复合物CCI等。该方法研究为进一步研究管藻目PSI复合物的结构打下了基础。     

海洋管藻目绿藻——刺松藻和假根羽藻PSI荧光特异性的研究

采用分离、原位扫描和光谱分析方法,将管藻目录藻刺松藻和假根羽藻的叶绿体、类囊体膜、PSI复合物及其亚复合物的结构及光谱性质与软丝藻和菠菜做了比较。结果表明,管藻止录藻缺少作为高等植物PSI表征的730nm长波荧光,这一特异现象主要与LHCI结构的差异有关。采用PAGE法分离出的4种PSI复合物的荧光主发射峰分别在698、690、685和677nm,在710－715nm处有一个随分子量减小和逐渐明显的肩峰。不同去污剂处理只影响PSI复合荧光峰的高低,而不影响其峰位。PAGE再分离得到的假根羽藻LHCI由24－27．5kDa的4种多肽构成,Chl-a/Chl-b=1.2,77K荧光发射峰在682nm;CCI只含有67和56kDa多肽,是叶绿体715nm荧光的发射部位。当有HLCI存在时,该荧光不明显。     

管藻目绿藻刺松藻(Codium fragile)PSI色素蛋白复合物结构及多肽组成

采用温和的聚丙烯酰胺凝胶电泳（PAGE）法，从管藻目录藻刺松藻中分离到不同解离程度的光系统I（PSI）复合物，以及核心复合物CCI、捕光复合物LHCI和LHCI的亚组分，并就其多肽组成及相互关系做了研究。纯化的CCI复合物只含有66和56kDa多肽，荧光发射主峰在714－715nm；LHCI的77K荧光峰在683－684nm，没有高等植物730nm特征荧光，含有PSI复合物中的全部4种24.7-27.5kDa多肽。将中心复合物CPI再电泳，得到了只含24．5和27．2kDa多肽的LHCI亚组分。从而证实刺松藻LHCI也可分裂为含有光合色素的两个部分，它们与CCI结合的紧密程度不同。     

兼顾共性基础与个性特色的智慧园区评价方法

作为智慧城市的重要组成和微观缩影,智慧园区建设十分重要,而评价方法是评估园区建设水平、促进园区健康发展的关键要素。当前,随着新一代信息通信技术(Information and Communications Technology,ICT）的高速发展,及全生命周期管理等先进理念的贯彻实践,智慧园区建设与发展欣欣向荣。然而,与之一体的评价方法却关注鲜少,存在迭代缓慢和类型单一等问题,可能会影响对智慧园区发展水平的客观评价。鉴于此,论文在充分继承原有方法的先进基础上,提出兼顾共性基础与个性特色的CCI（Commonality Combined with Individuality,CCI）智慧园区评价方法,其中,CCI评价指标体系共包括8个一级指标、30个二级指标和63个三级指标。共性评价指标是所有园区共有的基础指标,是必选项,充分融合全生命周期管理的理念,围绕智慧园区顶层设计基础层-平台层-应用层的基本架构展开梳理;个性评价指标是个别园区特有的特色指标,是可选项,需要依据园区的实际产业生产流程或业务内容展开分析。同时,以深圳市智慧妈湾作为实证案例,构建CCI评价指标体系并应用层次分析法（Analytic Hierarchy Process, AHP）展开综合评价,结合评价结果给出了发展建议：智慧妈湾整体水平较高,符合其打造先行示范区智慧城市标杆的目标定位;但在智慧平台、智慧物流、智慧金融、智慧文创方面还有一定的提升空间。最后,评价结果与智慧妈湾实际情况的一致性,论证了CCI智慧园区评价方法的科学性和可行性。     

Spatial variations of small phytoplankton contributions in the Northern Bering Sea and the Southern Chukchi Sea

Phytoplankton size classes (hereafter, PSCs) were derived from satellite ocean color data using a present phytoplankton abundance-based optical algorithm in the northern Bering and southern Chukchi Seas to characterize the spatial and seasonal variations of the different PSC and investigate the contributions of small phytoplankton to the total phytoplankton biomass. The comparison results showed that the phytoplankton abundance-based method approach could reasonably classify the three PSCs (pico-, nano-, and micro phytoplankton). The satellite maps of the dominant PSCs were derived using long-term satellite ocean color data. The general spatial distribution showed that the large (micro-) phytoplankton were dominant in the coastal waters and the west side of the Bering strait, while the small size (nano- or pico-) phytoplankton were dominant in the open ocean waters. Nano- and microphytoplankton were dominant in May and October in most of the study area, while pico-phytoplankton were dominant in the summer months in the open ocean waters. The annual variation in small phytoplankton dominance had a strong positive relationship with the annual mean sea surface temperature (SST), which is consistent with the increasing dominance of small phytoplankton biomass as water temperature increases. Microphytoplankton have an apparent increasing trend in the southeastern Chukchi Sea but slightly decreasing trends in Chirikov and St. Lawrence Island Polynya (SLIP). In contrast, there were increasing trends in picophytoplankton in Chirikov and SLIP, which seems to be related to increasing annual SST. It is crucial to monitor changes in dominant groups of phytoplankton community in the Bering and Chukchi Seas as important biological hotspots responding to the recent changes in environmental conditions.     

青藏高原多年冻土和季节性冻土区土壤水分变化及其与降水的关系

使用地面观测数据对欧洲空间局(ESA)发布的气候变化倡议(CCI)土壤水分产品进行精度校准,结合青藏高原及其周边降水气象站数据,分析土壤水分动态变化及其与降水的关系。结果表明:(1)校正后的CCI主被动组合产品所反演的青藏高原土壤水分获得了更高的精度,且显示1986~2016年暖季土壤水分在多年冻土区的逐年变化更为稳定。(2)高原土壤水分空间分布与降水分布高度一致,降水是该地区土壤水分的重要调节因子。多年冻土区暖季土壤水分与降水的相关性较低,而季节性冻土区较高,原因是多年冻土的存在可能有利于维持土壤水分的稳定性。多年冻土对于土壤水分有着重要的调节作用,气候变暖所导致的多年冻土退化,会降低土壤水分的调节能力,进而影响到青藏高原生态系统和水文循环。     

川西高原马尔康旅游气候舒适度分析与评价

为了更好地发展旅游事业,在对马尔康旅游资源做出具体规划的同时,对当地的气候资源特征进行分析与评价。利用马尔康县气象站1966~2005年逐日气温、相对湿度、风速、降水量等观测资料,计算当地温湿指数、风寒指数、着衣指数、综合舒适指数等,进而对旅游气候舒适度进行定量分析与评价。研究结果表明:(1)马尔康地区温湿指数和风寒指数分别在7、8月份达最大值,着衣指数在7月份达最小值,人体在7月份感觉最舒适;(2)40a间,马尔康地区温湿指数,风寒指数和着衣指数总体变化较稳定,个别年份波动较大;(3)1966~1990年,舒适天数基本在125d左右波动;受全球变暖影响,1990~2005年马尔康舒适天数呈明显波动上升趋势。这说明马尔康夏季为最适宜旅游季节,全年大概有120d非常适宜旅游,旅游资源丰富,且气候变化对当地旅游资源开发有明显促进作用。