Policy-relevant indicators for mapping the vulnerability of urban populations to extreme heat events: A case study of Philadelphia

The recent global increase in extreme heat events linked to climate change is projected to continue. The additive effect of urban heat islands from impervious surfaces and urban heat emissions (e.g., from transportation and building cooling) exacerbates extreme heat events in urban areas, exposing dense populations to extreme heat with implications for human health. Ground- and satellite-based data on urban and suburban temperatures and vegetation over a historical period can help identify temporal and geospatial trends in heat exposure. A set of indicators has been developed to map the exposure, social sensitivity, and vulnerability of urban populations to heat wave health impacts. Guided by an Advisory Group of local planners in the pilot city of Philadelphia, localized trends of increasing urban extreme heat events using MODIS Land Surface Temperature (LST) data, confirmed with urban and non-urban temperature monitor data were identified. For the Philadelphia study area, the number of heat-event days in the urban setting has increased from approximately 4 days in 1980 to almost 12 days in 2013, while the non-urban setting has consistently experienced 5 days of heat events per year across the time period. Warmer micro-climates with limited vegetative cooling and elevated LSTs were also identified. The exposure indicator was combined with areas of high social sensitivity (e.g., low-income and elderly) to create a vulnerability indicator, showing significant overlap between highly exposed and highly sensitive populations. As a measure of the adaptive capacity of local governments to reduce the urban heat island, evidence of targeted vegetation increases or reduced localized temperatures linked to urban greening and cooling programs were sought, though none were of a scale to be identified by the 1 km satellite data utilized. The indicators have helped local decision makers to understand patterns of vulnerability, and may be used in the future to target adaptation actions and measure results (LST reduction or vegetation increase) from existing adaptation actions.     

南极海冰遥感现场对比实验

南极海冰区是影响全球气候 -环境变化的关键区域之一 ,卫星遥感资料是获取大区域海冰地球物理特征参数的最有效的手段。但是 ,在南半球晚冬-初春期间 ,卫星遥感反演的海冰资料的误差较大 ,精度较低。 2 0 0 3年 9- 1 0月 ,由澳大利亚南极局组织 ,包括中国等 7个国家 ,1 4个研究单位的科学家参加 ,以澳大利亚破冰船“南极光号”为现场工作平台 ,在东南极季节海冰带 ,通过与美国宇航局 (NASA)、日本宇宙开发促进会合作开展的卫星、飞机、船、冰站立体联合观测 ;对AMSR E等卫星遥感产生的海冰地球物理参数 (海冰密集度、雪盖厚度、海冰物理温度等 )进行地面详细验证 ,建立遥感数据与地面实测数据的统计关系 ,以发现各种卫星资料反演算式的使用范围和局限性 ,为改进卫星资料反演算式提供依据。     

卫星导航定位系统时间同步技术

卫星导航定位系统测距的基础是测时,而定轨和定位的前提是各观测量的时间同步,因此,时间同步是卫星导航定位系统建设的关键。卫星导航定位系统中时间同步技术包括卫星与地面(星-地)和地面站间(地-地)的时间同步,主要时间同步方法有用于星-地时间同步的双向时间频率传递法(TWSTFT)、倒定位法等,以及用于地-地时间同步的TWSTFT、卫星共视法、搬运钟法等。本文重点介绍TWSTFT和卫星共视法进行时间同步的基本原理、精度分析和卫星导航定位系统的钟差预报。     

伪卫星技术发展和应用综述

全球导航卫星系统已经引起了测量、测地、导航和其他与定位相关的学科的革命,但是卫星导航定位系统有两个内在的弱点：信号衰减和定位结果依赖卫星的几何布局。因此在比较苛刻的观测环境下,系统的表现明显降低。伪卫星就是为了解决这个问题而引入的。本文讲述了伪卫星发展的相关历史和近来伪卫星定位方面的一些成就,并提出了现存的技术问题。     

GMS-5反演湿度场的一维变分质量控制试验

应用一维变分方法对GMS5资料反演的相对湿度场进行了变分同化质量控制试验。首先具体分析了1998年6月12～29日的MM5模式12h预报湿度场、卫星反演湿度场和同化分析湿度场的误差统计量(误差平均值、误差自协方差矩阵、均方根误差等)。在此基础上,又应用一维变分方法对1998年7月20～30日的资料进行了同化试验,并以1998年7月21日00时(世界时)的结果为例,详细分析比较了3种湿度场。分析结果表明:MM5模式背景湿度场总体上低层偏湿,中上层偏干,各层面上的干湿区域区分明显;但往往湿区过湿,干区又偏干,均方根误差(RMSE)相对较大,各层面多在10以上,最高达到15.6。GMS5卫星反演湿度场总体与探空实测结果更接近,但整体平均看,各个层面基本上略偏湿,特别在中低层,RMSE为6.3～8.9。经过一维变分质量控制的湿度场基本接近卫星反演湿度场,但同化后的湿度场的RMSE在中低层要比卫星反演场的要小,RMSE下降了0.4～0.7,下降比率达到6%～9%;高层与卫星反演结果基本接近。对模式向前12h预报场而言,同化了卫星反演湿度场后,均方根误差值下降了1.4～9.0,下降比率达到17%～59%,同化后的湿度场与实际大气大大接近。     

Estimation of insolation over the Pacific Ocean off the Sanriku coast

Surface solar radiation over the Pacific Ocean off the Sanriku coast has been estimated using Visible and Infrared Spin Scan Radiometer data supplied by the Geostationary Meteorological Satellite 5 for September, 1996 to June, 1997, when the Ocean Color and Temperature Scanner was functioning. The hourly and daily insolation is estimated with a spatial resolution of 0.01-degree grid. Thein situ surface short wave radiation obtained by the research vessel,Kofu-Maru belonging to the Japan Meteorological Agency is used for validation of the estimated insolation. It is shown that the estimated hourly and daily insolation has an rms (root mean square) error of 17.05% and 8.13%, respectively, which are the ratios between the rms error (W/m²) and the mean insolation (W/m²).     

卫星遥感在河南省国土资源管理工作中的应用及展望

本文通过对卫星遥感在河南省国土资源管理工作中应用情况的回顾和总结,提出了卫星遥感在土地利用遥感监测、卫片执法检查、建设用地监管平台和土地管理“一张图”建设、地质环境与地质灾害调查与监测、矿业活动调查与监测等国土资源管理方面的应用展望,较好地发挥了卫星遥感数据在国土资源管理工作中最直接、最便捷、最翔实的功效。     

哈尔滨CORS建设及其在测量中应用

介绍哈尔滨市GPS连续运行参考站系统的建设情况,详述系统原理和各组成部分的功能,以及在测量中的应用。     

Toward a global ocean data assimilation system based on ensemble optimum interpolation: altimetry data assimilation experiment

A global ocean data assimilation system based on the ensemble optimum interpolation (EnOI) has been under development as the Chinese contribution to the Global Ocean Data Assimilation Experiment. The system uses a global ocean general circulation model, which is eddy permitting, developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. In this paper, the implementation of the system is described in detail. We describe the sampling strategy to generate the stationary ensembles for EnOI. In addition, technical methods are introduced to deal with the requirement of massive memory space to hold the stationary ensembles of the global ocean. The system can assimilate observations such as satellite altimetry, sea surface temperature (SST), in situ temperature and salinity from Argo, XBT, Tropical Atmosphere Ocean (TAO), and other sources in a straightforward way. As a first step, an assimilation experiment from 1997 to 2001 is carried out by assimilating the sea level anomaly (SLA) data from TOPEX/Poseidon. We evaluate the performance of the system by comparing the results with various types of observations. We find that SLA assimilation shows very positive impact on the modeled fields. The SST and sea surface height fields are clearly improved in terms of both the standard deviation and the root mean square difference. In addition, the assimilation produces some improvements in regions where mesoscale processes cannot be resolved with the horizontal resolution of this model. Comparisons with TAO profiles in the Pacific show that the temperature and salinity fields have been improved to varying degrees in the upper ocean. The biases with respect to the independent TAO profiles are reduced with a maximum magnitude of about 0.25°C and 0.1 psu for the time-averaged temperature and salinity. The improvements on temperature and salinity also lead to positive impact on the subsurface currents. The equatorial under current is enhanced in the Pacific although it is still underestimated after the assimilation.     

Validation of AVHRR and TMI-derived sea surface temperature in the northern South China Sea

Satellite-derived SSTs are validated in the northern South China Sea (NSCS) using in situ SSTs from the drifting buoys and well-calibrated sensors installed on Research/Vessel(R/V) Shiyan 3. The satellite SSTs are Advanced Very High Resolution Radiometer (AVHRR) daytime SST, AVHRR nighttime SST, Tropical rainfall Measuring Mission Microwave Imager (TMI) daytime SST and TMI nighttime SST. Availability of satellite SST, which is the ratio that the number of available satellite SST to the total ocean pixels in NSCS is calculated; annual average SST availabilities of AVHRR daytime SST, AVHRR nighttime SST, TMI daytime SST and TMI nighttime SST are 68.42%, 69.99%, 56.57% and 52.80%, respectively. Though the TMI SST availability is nearly constant throughout the year, the variations of the AVHRR SST availability are much larger because of seasonal variations of cloud cover in NSCS. Validation of the satellite-derived SSTs shows that bias±standard deviation (STD) of AVHRR SST is −0.43±0.76 and −0.33±0.79 °C for daytime and nighttime, respectively, and bias±STD of TMI SSTs is 0.07±1.11 and 0.00±0.97 °C for daytime and nighttime, respectively. It is clear that AVHRR SSTs have significant regional biases of about −0.4 °C against the drifting buoy SSTs. Differences between satellite-derived−in situ SSTs are investigated in terms of the diurnal SST cycle. When satellite-derived wind speeds decrease down below 6 m/s, the satellite SSTs become higher than the corresponding in situ SSTs, which means that the SST difference (satellite SST−Buoy SST) is positive. This wind-speed dependence of the SST difference is consistent with the previous results, which have mentioned that low wind speed coupled with clear sky conditions (high surface solar radiation) enhance the diurnal SST amplitude and the bulk-skin temperature difference.