近46年中国冬季日均气温及极端温度的变化

应用1961—2006年我国599个站的冬季逐日平均温度资料,分析了冬季各月最低（高）日均温度、低温日数及三种极端温度指数的变化趋势。结果表明冬季各月最低、最高温度的变化均呈明显上升趋势,2月份升温最显著,日均气温低于5℃的冷日数和日均气温低于-10℃的严寒日数在冬季各月都是减少的。全国近46年冬季极端低温日数呈明显减少的趋势,1986年出现一次跃变,2006年最少;极端高温日数普遍增加,1995年出现跃变,1998年达到峰值;霜冻日数在27°N-46°N间区域显著减少,跃变点在1987年,最低值出现在1998年。     

CT断层重建中滤波函数设计的新方法

滤波函数在CT图像重建过程中起着非常重要的作用,直接关系到重建图像质量。为了提高CT重建图像质量,本文从加权平均的思想出发,根据FBP重建算法的理论基础,提出一种设计滤波函数的新思路,并分析了五点加权平均滤波函数性能比较。最后针对Shepp-Logan模型数据和实际的海螺投影数据,设计出一种新的滤波函数并与S-L和R-L滤波函数的重建效果进行了比较。从比较结果可以看出,新设计的滤波函数重建的图像效果在整体性能上最好,在局部地方,其密度分辨率有所提高。本文为滤波函数的设计提出了一种新的想法和思路。     

基于H-P滤波法、ARIMA和VAR模型的库区滑坡位移综合预测

受库水位涨落及降雨等影响,库区滑坡位移表现出明显的周期性。基于位移时间序列分析,将滑坡监测位移分解为趋势项与周期项之和。趋势项反映滑坡变形的长期趋势,其主要受滑坡本身地质结构等因素影响。周期项反映滑坡变形的波动性,其主要受外部因素影响。以三峡库区巫山塔坪滑坡为例,考虑长江水位与降雨量影响,采用H-P滤波法从滑坡位移中分解出趋势项及周期项,利用差分自回归滑动平均模型（ARIMA）对趋势项进行平稳处理并计算趋势项预测值,利用向量自回归模型（VAR）计算周期项预测值。趋势项预测值与周期项预测值之和为滑坡位移预测值。与实际监测值及多种方法分析比较,表明综合预测所得结果能较好反映滑坡变形的趋势性和波动性,位移预测效果较好。     

Causes and effects of spatial and temporal variations of cold period in Chinese oases between 1960 and 2014

Based on daily average temperatures and observation data from 74 meteorological stations in Chinese oases, we calculate five-day (pentad) average temperature ≤0°C for the start and end pentad as well as pentads of cold period using linear regression analysis, nonparametric Mann-Kendall tests, the Morlet wavelet power spectrum, and correlation analysis. We also analyze spatial and temporal variations and their effects on the start and end pentad as well as pentads of cold period in Chinese oases. Results show that over the last 55 years, the start pentad of cold period has been postponed while the end pentad has been advanced. Overall, the pentads have gradually shortened over time at trend rates that are 0.3 p/10a,–0.27 p/10a, and–0.58 p/10a, respectively. Spatial differences are significant, especially for the Qaidam Basin oasis where the start pentad is the earliest, the end pentad is the latest, and the trend of change is most obvious. Mutation points for the start and end pentad as well as pentads of cold period were observed in 1990, 1998, and 1994, respectively. Of these, the start pentad and pentads of cold period show a periodic cycle, related to atmospheric circulation and El Nino events, while the end pentad exhibits a periodic cycle, related to solar activity. The Tibetan Plateau index (TPI), the Asian polar vortex area index (APVAI), and carbon dioxide emissions (CDE) are the main factors affecting cold period in the study area, whereas the South Asian summer monsoon (SASM) index exerts the greatest effect on the Qaidam Basin oasis. The start and end pentad as well as pentads of cold period increase in concert with latitude, longitude, and altitude; in response to these changes, the start pentad is advanced, the end pentad is postponed, and pentads of cold period are gradually extended. Results show that change in latitude is most significant. Overall, the start and end pentad as well as pentads of cold period show clear responses to regional warming, but there are different effects on each.     

A Hierarchy of Spatial Marginality Through Spatial Filtering

Abstract

Taking a clue from classic time-series decomposition, this article demonstrates a spatial filtering and search technique that permits the partitioning of a measure of marginality, here measured as the percent of the population living at less than 50 percent of the poverty level, into macro, meso, and micro components. This approach supports theory that has argued for scale-specific explanations of spatial marginality. The technique also offers promise for many other types of investigations such as disease incidence, microclimate dynamics, and consumer preferences.     

Hydro-climatic variability and forest fires in Mexico’s northern temperate forests

Global warming is likely modifying the hydrological cycle of forested watersheds. This report set as objectives to: a) assess the hydrological variables interception loss, I, potential and actual evapo-transpiration, E, Et, runoff, Q, and soil moisture content, θ; b) evaluate whether these variables are presenting consistent trends or oscillations that can be associated to global warming or climate variability; and c) relate θ to the number of wildfires and the burned area in Durango, Mexico. A mass balance approach estimated daily variables of the water cycle using sub-models for I and Et to calculate Q and θ for a time series from 1945 to 2007. Regression and auto-regressive and moving averaging (ARIMA) techniques evaluated the statistical significance of trends. The cumulative standardized z value magnified and ARIMA models projected statistically similar monthly and annual time series data of all variables of the water cycle. Regression analysis and ARIMA models showed monthly and annual P, I, E, and Et, Q, and θ do not follow consistent up or downward linear tendencies over time with statistical significance; they rather follow oscillations that could be adequately predicted by ARIMA models (r² ≥ 0.70). There was a consistent statistical association (p ≤ 0.05) of θ with the number of wildfires and the area burned regardless of the different spatial scales used in evaluating these variables. The analysis shows seasonal variability is increasing over time as magnifying pulses of dryness and wetness, which may be the response of the hydrological cycle to climate change. Further research must center on using longer time series data, testing seasonal variability with additional statistical analysis, and incorporating new variables in the analysis.     

大连地区阵风系数特征分析

利用2015年5月至2020年4月辽宁省大连地区9个国家气象站、2017年165个区域气象站逐10 min测风资料, 从风向、风级、月际变化、日变化、空间分布和天气影响系统等对大连地区最大、平均、最小阵风系数进行统计分析。结果表明: 1—12月平均阵风系数的变化范围为1.66~1.77, 秋末冬初平均阵风系数偏大, 春夏季节偏小; 与冷空气相对应风向的平均阵风系数大于与暖空气相对应的风向; 随着风级的增大, 最大、最小阵风系数向平均阵风系数收敛; 不同风级下阵风系数的频率分布均呈单峰型分布, 风级越大, 分布范围越窄。除西南风外, 其他风向的阵风系数均表现出白天大、夜间小的特点。大连地区阵风系数具有明显的地域特点, 东南和西北部沿海区域的阵风系数比内陆和西南沿海偏小, 风向基本不影响阵风系数的空间分布。大连的大风过程多受海上气旋和高压前部双系统共同影响, 气旋、台风以及雷暴大风的平均阵风系数大于同风级的平均值。     

基于多模式集成冬半年气温预报偏差修正

卡尔曼滤波递减平均方法对模式直接输出的气温预报进行订正,能有效提高预报准确率,但有时会造成显著负订正的现象,使订正预报效果反而不及模式直接输出。利用消除偏差集合平均方法(BREM)选择最优滑动训练期对2019年10月至2020年4月ECMWF预报(EC)、经过卡尔曼滤波递减平均法订正的预报(EC_COR)及中央台网格指导预报(SCMOC)等3种气温预报在黑龙江省的结果进行集成,并将BREM方法对EC_COR的修正效果进行评估,结果表明:不同预报结果都表现为冬季和夜间预报的准确率更低,气温偏低的11月至翌年1月更倾向于表现出预报较实况系统性偏高的特点。BREM方法能有效地修正EC_COR对EC负订正的现象,且可显著高于任何一种参与集成的单一预报效果。可在对单一模式进行卡尔曼滤波递减平均订正的基础上,进一步提升预报质量。另外,利用集成方法对高质量预报产品的融合(不局限于模式直接输出预报或是订正预报)可获取较单一预报更优的预报结果。     

改进的修正预测法预报电离层

利用自回归移动平均ARMA模型的线性最小方差预测法预报电离层存在的主要问题是极值点处预测误差较大。通过对模型阶数上限及定阶准则的选取进行实验分析,确定了合适的模型阶数并建立了相应模型。修正预测法可利用新信息对线性最小方差预测法的预测结果进行修正。这是一种短期预报方法,每次向前预测一步即2 h,但结果并不理想。考虑到电离层变化的周期性,为了进一步减小极值点处预测误差,提出了改进的修正预测法。实验表明,改进的修正预测法预测结果与原始值符合较好。     

玉林夏季高温天气气候特征与环流形势分析

利用近50年（1961～2010年）广西玉林站的气温、风、相对湿度、日照等地面观测资料及历史天气图、NCEP／NCAR再分析资料,统计分析了玉林夏季高温天气的气候特征并探讨出现高温天气的大气环流形势。结果表明：（1）玉林高温天气主要出现在6-9月,3d以上的持续高温主要出现在7～8月,且高温日数的年际差异很大。玉林高温...