非差误差改正信息的大范围单历元网络差分方法

针对网络差分方法多采用双差模型,但双差模型在实现时不够灵活的问题,提出一种基于非差误差改正信息的大范围单历元网络差分方法。此方法能够克服双差网络差分模型的缺点,用户不需要选择一个参考站作为主参考站,更不需要主参考站的观测数据进行双差组合,从而减少了数据传输量,作业方式更加自由、灵活,且算法简单、作业范围大。大范围区域内的流动站用户利用非差误差改正数进行误差改正,然后可实现单历元网络差分定位。实验表明,该方法可完成大范围单历元网络差分定位,并能够得到分米级精度的定位结果。     

西北太平洋TC移动速度异常及预报误差特征的分析

利用国家气象局和上海台风研究所(CMA-STI)整编的西北太平洋1970—2009年热带气旋(TC,Tropical Cyclone)及TC最佳路径数据集和2005—2010年的TC路径预报误差资料,应用百分位法,确定TC移动速度异常指标,分析了40 a来西北太平洋TC移动速度及其变化异常发生的时空分布特征,研究了TC速度预报误差对路径预报误差的影响及其与大尺度引导气流之间的关系。结果显示:1)西北太平洋TC移速及移速变化累积概率达95%(5%)分位数的阈值分别为10.8 m·s~(-1)(1.43 m·s~(-1))和2.42m·s~(-1)(-1.72 m·s~(-1))。2)快速移动及加速的TC大都出现在日本海地区,而缓慢的和减速移动TC主要出现在南海区域。3)TC移动速度异常的季节变化表现为,快速移动的TC在5月出现的频率达到最高,缓慢移动的TC在10月频率达到最高,加速移动的TC在6月频率达到最高。4)近6 a的TC移速预报误差对TC路径预报误差的贡献平均约为41.6%。5)对TC路径预报误差偏大,且移速预报误差贡献大的个例分析显示,该个例大尺度环境引导气流偏弱使TC移动速度偏慢。而如果预报的大尺度环境引导气流偏强,使预报的TC移速偏快,那么就容易导致大的路径预报误差。     

Delineating Hierarchical Hospital Service Areas in Florida

Hospital service area (HSA) and hospital referral region (HRR), known as a hierarchical HSA system, have been used as analysis units in a growing body of large‐scale studies of healthcare spending, utilization, and outcome in the United States. However, the popular Dartmouth HSAs and HRRs were produced more than two decades ago and are unable to represent contemporary healthcare markets. This research uses a revised Huff Model to delineate two levels of hospital service areas in Florida, resulting in sixty‐four HSAs nested in twenty‐one HRRs. Three elements distinguish our method from existing work. First, a best‐fitting distance‐decay function derived from the actual travel pattern of hospitalization is embedded in the Huff Model to strengthen the model's theoretical foundation in individual spatial behavior. Secondly, the hierarchal central place structure is supported by the differing travel‐friction coefficients for general versus specialized patients; general patients experience a steeper gradient and thus a shorter average travel range that supports delineating more HSAs of smaller area size, and specialized patients exhibit a flatter gradient and thus a longer average travel range that leads to fewer HRRs of large‐sized areas. Finally, the delineation method automated in geographic information systems (GIS) can be easily replicated in other regions to define large‐scale and consistent hierarchical HSA systems.     

An expanded surface-water palaeotemperature inference model for use with fossil midges from eastern Canada

Using an expanded surface sample data set, representing lakes distributed across a transect from southernmost Canada to the Canadian High Arctic, a revised midge-palaeotemperature inference model was developed for eastern Canada. Modelling trials with weighted averaging (with classical and inverse deshrinking; with and without tolerance downweighting) and weighted averaging partial least squares (WA-PLS) regression, with and without square-root transformation of the species data, were used to identify the best model. Comparison of measured and predicted temperatures revealed that a 2 component WA-PLS model for square-root transformed percentage species data provided the model with the highest explained variance (r =0.88) and the lowest error estimate (RMSEP _jack =2.26 °C). Comparison of temperature inferences based on the new and old models indicates that the original model may have seriously under-estimated the magnitude of late-glacial temperature oscillations in Atlantic Canada. The new inferences suggest that summer surface water temperatures in Splan Pond, New Brunswick were approximately 10 to 12 °C immediately following deglaciation and during the Younger Dryas. During the Allerod and early Holocene, surface water temperatures of 20 to 24 °C were attained. The new model thus provides the basis for more accurate palaeotemperature reconstructions throughout easternmost Canada.     

国家中心城市竞争力及其职能演变——基于上市企业总部的研究

国家中心城市是核心和枢纽城市,也是大企业最为集聚的地方。企业总部是企业的决策和命令中心,拥有大企业总部的数量及企业总部规模是衡量国家中心城市竞争力的重要指标。利用国内上市企业的数据,计算中国城市的控制和命令指数（简称CCI指数）,从全国尺度考察北京、上海和广州等8个国家中心城市的竞争力及其职能演化,并剖析国家中心城市总部职能的专业化格局。结果发现：北京和上海两个城市控制和支配功能要远远强于其他国家中心城市,一直位居前两位。从2005年到2014年,北京的CCI指数显著增强,且优势逐渐扩大。北京地位的显著提升很大程度上得益于金融业央企的上市和增长,这是北京作为政治中心的独特优势进一步释放的结果。而其余国家中心城市的CCI指数大多呈现下降趋势。在行业上,金融业、制造业和采矿业一直占据中国经济的主要控制与支配地位。过去10年,金融业在经济中的地位显著增强,尤其是东部大城市的金融业CCI指数普遍有大幅提升;相反,制造业和采矿业的控制与支配功能则明显减弱。对国家中心城市的分析来看,北京、上海和广州在大部分行业中都具有明显优势,属于全国性的综合型大城市。而其余5个国家中心城市的功能专业化程度较低。此外,8个国家中心城市与周边区域发展的相互联系存在明显差异,究其原因在于区域经济发展程度和城市产业发展特点。     

气候变化对中国集中供暖气候指标的影响

应用高空间分辨率的网格逐日气象数据,根据国家集中供暖有关设计规范定义了集中供暖气候指标,分析了气候变暖对中国集中供暖气候指标的影响。结果表明：近55 a来中国集中供暖初日均呈后延趋势,初日特征线年代际南北移动较小。供暖终日均呈提前趋势,终日特征线在110°E以东地区南北移动较大,2000年以来终日特征线较20世纪60年代北抬了200~300 km。供暖期长度均呈减少趋势,东北、华北地区近55 a减少了10~15 d,西北地区减少了15~20 d;东北、华北、西北地区供暖强度分别减少了12%、20%、15%。从1991~2015年冬季气温变化来看,东北地区最冷冬季与最暖冬季的温度相差可达6.2℃,对供暖强度的影响可达28.9%,华北和西北地区冬季气温最大变幅分别为3.7℃、3.3℃,对供暖强度的影响分别为26.8%和17.6%。气候变暖对中国集中供热气候指标产生了显著的影响。供热部门应该根据天气变化来安排供暖,同时还要注意气候变暖背景下极端冷事件的发生,保证集中供暖安全运行。     

Record Low Sea-Ice Concentration in the Central Arctic during Summer 2010

The Arctic sea-ice extent has shown a declining trend over the past 30 years. Ice coverage reached historic minima in 2007 and again in 2012. This trend has recently been assessed to be unique over at least the last 1450 years. In the summer of 2010, a very low sea-ice concentration(SIC) appeared at high Arctic latitudes—even lower than that of surrounding pack ice at lower latitudes. This striking low ice concentration—referred to here as a record low ice concentration in the central Arctic(CARLIC)—is unique in our analysis period of 2003–15, and has not been previously reported in the literature. The CARLIC was not the result of ice melt, because sea ice was still quite thick based on in-situ ice thickness measurements.Instead, divergent ice drift appears to have been responsible for the CARLIC. A high correlation between SIC and wind stress curl suggests that the sea ice drift during the summer of 2010 responded strongly to the regional wind forcing. The drift trajectories of ice buoys exhibited a transpolar drift in the Atlantic sector and an eastward drift in the Pacific sector,which appeared to benefit the CARLIC in 2010. Under these conditions, more solar energy can penetrate into the open water,increasing melt through increased heat flux to the ocean. We speculate that this divergence of sea ice could occur more often in the coming decades, and impact on hemispheric SIC and feed back to the climate.     

Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part Ⅱ: Model Uncertainty

This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II. Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60°S and 60°N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved.     

基于卫星资料梯度信息的新型变分同化方法对于台风数值模拟的研究

卫星资料凭着卫星遥感的全球性、连续性和高频次观测等优势,成为一种重要的非常规资料源,但卫星观测仍然存在各种各样的观测误差,其中包含由于观测偶然性所造成的统计学上的随机误差及仪器本身和辐射传输模式等造成的系统性偏差,这些误差在很大程度上影响了卫星资料的质量。文中提出了一种能有效订正卫星观测资料系统性偏差的梯度信息同化算法,该方法用一个梯度算子进行模式变量与观测变量的梯度变换,从而达到订正系统性偏差的目的。本文利用WRF（Weather Research Forecast）模式及其同化模式WRFDA（WRF Data Assimilation system）,以及AIRS（Atmospheric Infrared Sounder）资料,对台风“圆规”进行了实际的数值模拟和同化试验,数值结果表明,梯度信息同化方法能明显改善台风路径的模拟,在处理可信度较低的资料时仍然适用。另外,通过同化诊断分析,发现卫星资料的系统性偏差对于台风数值模拟有较大影响,而文中提出的梯度信息同化方法能较好的解决此类问题。