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1.
应用盘锦市疾控中心2008年1月1日至2009年12月31日逐日脑血管病发病人数及同期逐日气象资料,采用相关分析、逐步回归等方法,分析了脑血管病与气象要素的关系,建立了逐日脑血管病发病趋势的气象预报模型。结果表明:各类气象要素与未来3 d脑血管病发病人数滑动平均具有较好的相关性;气象因子对脑血管病发病人数的影响存在着一种滞后效应和持续效应;脑血管病发病人数与当日最低气温、平均气温、最低气压、平均风速、湿度、最大气温日较差等气象要素相关显著;不同的季节影响脑血管病发病人数的敏感气象因子不同,且相关关系差异较大。逐日脑血管病发病趋势的气象预报模型预报检验效果较好。  相似文献   

2.
气象条件与 SARS发生的关系分析   总被引:5,自引:1,他引:5       下载免费PDF全文
根据 2 0 0 3年北京、香港SARS高发期间逐日确诊发病人数序列 ,运用数理统计和幂律关系方法 ,分析了不同地区SARS与气象条件之间的关系。结果表明 :京港两地SARS高发期的波动量与确诊前 7~ 1 0天的最高气温、最低气温、气温日较差、日照时数呈显著负相关 ,与相对湿度、云量呈正相关 ;气象条件与SARS发病人数呈显著的幂律关系 ,为自组织临界态理论在大气科学中的应用提供了观测证据。  相似文献   

3.
北京夏季日最大电力负荷预报模型建立方法探讨   总被引:2,自引:1,他引:1       下载免费PDF全文
为了探索夏季(6~8月)日气象负荷的最佳分离方式和引起日最大电力负荷波动的主要因子,以及建立预报模型最佳个数,基于北京市2005~2010年逐日最大电力负荷和同期的气象资料,分析了北京地区日最大电力负荷的变化规律,采用不同方法将气象负荷从夏季日最大电力负荷中分离出来,分析北京夏季气象负荷与气温、相对湿度、降水及炎热指数、高温持续日数、炎热日数持续时间、前一日气象负荷等因子之间的关系,并基于2005~2009年夏季逐日气象负荷和其主要影响因子采用逐步回归方法建立日最大电力负荷的预报模型,将2010年夏季北京日最大电力负荷作为预报效果的独立样本检验。结果显示:2005~2010年,北京逐日最大电力负荷具有明显的线性增长趋势,夏季日最大电力负荷具有显著的星期效应;与去掉逐年夏季日最大电力负荷趋势和夏季平均日最大电力负荷趋势相比,去掉全年逐日最大电力负荷变化趋势的夏季日气象负荷预报模型的拟合能力更优;北京夏季日气象负荷与当日气温的相关系数最高,与前一日气象负荷也关系密切;利用前一日相对气象负荷和当日气象要素一周逐日分别建立预报模型的拟合和预测效果较好。  相似文献   

4.
基于北京市海淀区2004--2007年夏季(6—9月)疾病预防控制中心的逐日腹泻疾病发病资料和同期地面气象观测资料,首先采用经典方差贡献分析技术分析了逐日发病人数与气象要素的相关性,选取方差贡献较大的要素作为预报因子,然后根据概率积分方法将发病人数划分为5个级别,采用回归方法分别建立了不同预报时效的预测模型,并检验历史样本的拟合结果。研究结果表明:(1)腹泻疾病发病人数与湿度、风速、气温均呈显著的正相关,其中,水汽压对腹泻疾病的方差贡献最大。(2)1~4d的预报效果较好,其中1~2d预报结果的完全正确率在40%以上,预报误差≤±1级的准确率可达98%。  相似文献   

5.
对2003年3—6月我国SARS(Sever Acute Respiratory Syndrome,严重急性呼吸道综合症)发病人数最多的北京、香港逐日病例和有关气象因子进行了对比分析,结果表明:气温、气压的走向和SARS发病率有很好的关系;相对湿度高、云量多和日照少是两地高发期的共同特点;冷空气活动对SARS疫情的流行有诱发推动的作用。通过高发期逐日发病人数和气象要素随基准值变化的对应关系设计了综合指数,分别计算了两地气温因子的高危指标,结果显示,两地日平均气温和日最低气温指标相差了3℃和7℃,两地日最高气温指标均为24~27℃。  相似文献   

6.
通过分析1997-2003年5~10月广西电网电力负荷月、周和节假日的变化特征,及与气温的相关关系,发现:电力负荷基本呈逐年增加的趋势,工作日和非工作日有着不同的变化特征,电力负荷与气温有明显的相关关系。采用逐步回归方法,建立了广西电网逐日电力负荷预测模型,对2002-2003年模型的拟合结果及2004-2005年模型的预测结果分析表明:模型对广西逐日电力负荷具有较好的拟合和预测效果,对逐日电力负荷的季节变化具有较好的拟合效果,尤其是夏季预测与实况趋势基本吻合。  相似文献   

7.
基于北京市海淀区2004-2007年夏季(6-9月)疾病预防控制中心的逐日腹泻疾病发病资料和同期地面气象观测资料,首先采用经典方差贡献分析技术分析了逐日发病人数与气象要素的相关性,选取方差贡献较大的要素作为预报因子,然后根据概率积分方法将发病人数划分为5个级别,采用回归方法分别建立了不同预报时效的预测模型,并检验历史样本的拟合结果。研究结果表明:(1)腹泻疾病发病人数与湿度、风速、气温均呈显著的正相关,其中,水汽压对腹泻疾病的方差贡献最大。(2)1-4天的预报效果较好,其中1-2天预报结果的完全正确率在40%以上,预报误差≤±1级的准确率可达98%。该预报结果可为疾病预防控制中心指导广大城乡居民卫生防疫提供科学依据。  相似文献   

8.
呼吸道和心脑血管疾病与气象条件的关系及其预报模型   总被引:4,自引:6,他引:4  
对武汉市4家大医院1994-1998年呼吸道、心脑血管疾病的逐日发病人数与同期气象因子进行了相关分析。结果表明:呼吸道及心脑血管疾病的发病与气温、气压、湿度有着密切的关系,但同一个因子对不同疾病甚至同一类不同种病的作用不尽相同,即使同一个因子对同一种病在不同季节其影响也不完全相同。在相关分析的基础上,运用逐步回归方法建立了春夏秋冬8种疾病的逐日预报模型,并进行了合理的等级划分,经回代和预报检验,预报模式具有较好的预报能力。  相似文献   

9.
通过对2001~2002年南宁市2个最大医院呼吸道疾病39305例门诊资料进行小波分析,得出各种疾病发病人数均存在5~7天的周期。将呼吸道疾病发病人数和同期气象要素、大气污染物浓度资料进行相关分析,结果表明,呼吸道疾病发病人数与气温、气压、湿度密切相关,同时与大气污染物SO2、NO2、PM10浓度也密切相关。利用最优子集方法,按不同季节建立呼吸道疾病下周逐日发病人数预测方程,2004年1月支气管炎发病人数预报值与实际值相对误差为16.43%,2004年4月未来1~2天呼吸道疾病发病人数预报值对天气变化的敏感性与实际值基本一致。  相似文献   

10.
石家庄夏季用电量对天气的响应及其预测模型   总被引:1,自引:0,他引:1  
阎访  陈静  车少静 《干旱气象》2009,27(3):282-287
从石家庄市2005~2007年每年6~8月的逐日用电量资料中分离出随气象因子变化的气象电量,分有、无降水日分别计算了气象电量与同期气象资料中关键气象要素的相关系数,着重分析了气象电量随气温、湿度、降水的变化规律.结果表明:石家庄夏季气象电量与气温呈显著性正相关,而与相对湿度仅在有降水日为显著负相关;计算了用电量逐日变化值与气象要素日变化值之间的相关系数,发现要素差值之间存在着很好的相关性.在统计分析的基础上,借助Origin7.5软件,分有、无降水日建立了综合气象因子影响下气象电量及用电量逐日变化的多元回归预测模型,回归统计及方差分析表明:预测方程均通过了α=0.0005的F检验,复相关高于单相关,拟合率较高,能为电力部门合理调度提供参考.  相似文献   

11.
Daily meteorological observations have been made at the Brera astronomical observatory in Milan since 1763. Even if the data have always been collected at this observatory, the Milan series are far from being homogeneous as several changes were made to instruments, station location and observation methods. Within this context, the purpose of the paper is to discuss data homogenisation. Homogenisation is based both on objective information extracted from the station history (direct methodology) and on some statistical estimates (indirect methodology). Homogenisation by indirect methodology is mainly performed by comparison with other series whereas, if no other homogeneous series are available, it is based on the hypothesis that some statistics, such as the daily temperature range or the day to day variability, have no significant trends within some selected periods. Besides homogenisation also the completion of the series is discussed. Theresulting series are complete and homogenised daily minimum, mean and maximum temperatures and complete and homogenised daily mean pressures. They all cover the period 1763–1998.  相似文献   

12.
司鹏  郭军  赵煜飞  王冀  曹丽娟  王敏  王琪  冯婧 《气象学报》2022,80(1):136-152
长期连续的日值观测资料是研究百年来极端气候事件及其变化特征的重要基础支撑。目前中外由于缺乏可靠的逐日百年尺度气候资料,使得20世纪50年代以前的极端气候变化规律仍然没有得到很好的认识。基于国家气象信息中心收集整理的日最高和最低气温观测资料,构建北京1841—2019年气温日值序列。首先,通过数据质量控制剔除原始基础资料中因人工观测、仪器故障及数字化过程造成的错误数据;其次,采用标准化序列法对北京气象观测站1951年以前的日最高和最低气温序列进行了插补;最后,利用惩罚最大t检验(PMT)和惩罚最大F检验(PMFT)对插补后的日值序列进行均一性检验,并采用分位数匹配法(QM)对检验得到的因迁站和仪器变更导致的统计显著断点进行订正,由此建立了北京百年均一化气温日值序列。分析表明,构建的北京百年逐日气温序列的年代变化特点与美国伯克利地球研发中心的月平均地表温度数据(Berkeley Earth-Monthly)、英国东英格利亚大学气候研究中心的全球月平均地表温度数据(CRUTS4.03)以及美国国家气候资料中心的全球历史气候数据(GHCNV3)具有一致性。从趋势变化来看,基于构建的逐日最高和最低气温序列统计得到1911—2019年北京地区年平均气温升高趋势为0.154±0.018℃/(10 a)(95%不确定性水平估计),与中国区域气温趋势变化速度基本一致。从而在一定程度上说明构建的北京百年尺度日最高和最低气温序列能够为极端气候变化领域提供新的基础数据。   相似文献   

13.
Time series of daily weather such as precipitation, minimum temperature and maximum temperature are commonly required for various fields. Stochastic weather generators constitute one of the techniques to produce synthetic daily weather. The recently introduced approach for stochastic weather generators is based on generalized linear modeling (GLM) with covariates to account for seasonality and teleconnections (e.g., with the El Niño). In general, stochastic weather generators tend to underestimate the observed interannual variance of seasonally aggregated variables. To reduce this overdispersion, we incorporated time series of seasonal dry/wet indicators in the GLM weather generator as covariates. These seasonal time series were local (or global) decodings obtained by a hidden Markov model of seasonal total precipitation and implemented in the weather generator. The proposed method is applied to time series of daily weather from Seoul, Korea and Pergamino, Argentina. This method provides a straightforward translation of the uncertainty of the seasonal forecast to the corresponding conditional daily weather statistics.  相似文献   

14.
Time-irreversible symmetry is a fundamental property of nonlinear time series. Time-irreversible behaviors of mean temperature measured on 182 stations over China from 1960 to 2012 are analyzed by directed horizontal visibility graph (DHVG for short), and significance of results has been estimated by Monte Carlo simulations. It is found that dominated time irreversibility emerges in nearly all daily temperature anomaly variations over China. Further studies indicate that these time-irreversible behaviors result from asymmetric distributions of persistent daily temperature increments and decrements, and this kind of symmetry can be quantified by distributions of consecutive daily mean temperature increasing or decreasing steps. At the same time, the findings above have been confirmed by artificially generated time series with given value of multiscale asymmetry.  相似文献   

15.
The seasonal-by-wind bias method for aligning time series of daily maximum and minimum temperatures from past conventional staffed and new automated sites using closely collocated, overlapping observations is presented for twenty-two modernized Reference Climate Stations in Canada. The method consists of adjusting for incompatible observing times and deriving biases from the daily “manual-minus-automated” temperature differences classified into seasons and wind-speed conditions. Most of the biases vary with the season, and many show limited wind dependency. Four sets of adjusted time series are prepared based on two-year and five-year overlapping data and on seasonal bias with or without wind conditions; the adjusted data are compared with the original observations. Based on the mean of the absolute differences and examination of box plots, the results show that, for this particular set of stations, the two-year versus five-year and seasonal versus seasonal-by-wind bias adjusted time series are overall similar. The largest contribution to the improvements in the adjusted observations came from matching the times of observation. Additionally, daily temperatures are adjusted using statistical methods applied with neighbouring station data but no overlapping observations at collocated stations; it is concluded that these do not necessarily resolve the bias between staffed and automated sites.  相似文献   

16.
Summary This study concerns a comparison of the ECHAM3/T42 simulated series of daily extreme temperatures and series observed in southern Moravia (a part of the Czech Republic). ECHAM climate model was developed from the ECMWF model (the former part of its name EC) and parametrizations were created at the Max Planck Institute in Hamburg (the latter part of the abbreviation HAM). Simulated (1×CO2) times series of daily variables have rarely been validated against the real datasets. In this paper, attention is focused on autocorrelation coefficients whose estimates are computed by the jackknife method and differences in the estimates between the simulations and observations are examined. It is shown that for the average simulated series (4 gridpoints) the jackknife autocorrelation coefficients are substantially larger in all seasons than those computed for the average series in Moravia (5 stations). The daily extreme temperature variability is underestimated in the simulations, the persistence of the simulated series being much higher. In order to gain an additional insight into this finding trimmed means and trimmed sample variances are computed. An examination of frequencies of day-to-day changes (absolute values) calculated from the observations and simulations shows that small day-to-day temperature changes are clearly preferred in the model at the expense of larger changes which are recorded in Moravia. It is obvious that the largest changes observed are not captured in the simulations. Received June 12, 1997 Revised October 29, 1997  相似文献   

17.
The longest continuous record of measurements of atmospheric CO2 concentration available to date, that was made between 1877 and 1910 at the Montsouris Observatory in the outskirts of Paris, is presented and the methods used and the site are described. Annual, seasonal and daily variations in the record were considerable, especially between 1877 and 1880 and possible reasons for this high variability are discussed. Although no direct proof of the reliability of the series is available an attempt has been made to estimate this by comparisons with contemporary series whose precision is better known and also through an analysis of the results from the point of view of the major sources of error. The results suggest a precision of measurement better than 2%; analysis of the daily and the mean seasonal variation shows no evidence of any significant urban contamination of the Montsouris record. Mean decadal values of the Montsouris series show a marked rise in concentration from 283 ppm in the first decade to 313 ppm in the second, with a small and nonsignificant drop to 309 ppm in the third decade of the series. The results of the measurements are thus compatible with the hypothesis that a major and variable non-fossil fuel source of atmospheric CO2 was active during the last quarter of the nineteenth century. Contribution from the Agricultural Research Organization, The Volcani Center, Bet Dagan, Israel. No. 254-E, 1981 series.  相似文献   

18.
Two new Boolean parameters are defined: the sunshine number (related to the state of the sky) and the sunshine stability number (which is as a measure of the fluctuation of the radiative regime). Elementary statistical and sequential properties of both parameters are presented in this paper. Actinometric and meteorological data measured at 15?s lag during 2009 in Timisoara (Romania, southeastern Europe) are used. The yearly series of daily averaged sunshine number has negative skewness and kurtosis. The series of daily averaged sunshine stability number has positive skewness and kurtosis. The series of daily averaged values of sunshine number are best described by an ARIMA(0,1,2) model. ARIMA(0,1,0) and ARIMA(0,2,0) models (associated with an appropriately defined white noise) may be used for synthesis of the sunshine number time series. The first model is to be preferred for practical reasons. The series of daily averaged values of sunshine stability number are best described by an ARIMA(2,2,1) model. The ARIMA(0,0,0) model is recommended to be used for generating time series of sunshine stability number. This model may be used for any particular day during the year and the only parameter depending on the day is the white noise standard deviation. A relationship between the white noise standard deviation and the daily averaged sunshine stability number is proposed.  相似文献   

19.
Daily meteorological observations have been made at the old astronomical observatory in Stockholm since 1754. Complete daily mean series of air temperature and sea level pressure are reconstructed from the observational data for 1756–1998. The temperature and pressure series arereconstructed and homogenized with the aid of metadata, statistical tests and comparisons with data from other stations. Comparisons with independently reconstructed daily series for nearby Uppsala (1722–1998) show that the quality of thedaily Stockholm data is good, although the reliability is lower before the mid-19th century. The daily temperature data show that the colder winter mean temperatures of the late 18th to early 19th centuries were connected with a particularly high frequency of very cold winter days. The warmer summers of the same period are more connected with a general shift of the temperature distribution towards higher temperatures than in the late 20th century.  相似文献   

20.
气象观测环境的变化对气温序列的影响分析   总被引:15,自引:2,他引:15  
本文利用安徽省1971~2000年共30 a逐日平均气温、最高气温、最低气温的气候整编资料,选取气象观测环境完全符合相关规定(A类)和不完全符合相关规定(B类)两类代表站,分别建立了气温序列和两者的气温差值序列,并对气温序列的气候平均值和气温差值序列的气候趋势进行了分析。结果表明:气象观测环境的变化将影响气温序列。与A类台站相比,B类台站平均气温、最高气温和最低气温的气候平均值表现出一致偏高的特征,最低气温偏高最多;B类台站与A类台站平均气温、最高气温和最低气温的差值均有显著增大的趋势,平均气温差值的增大最为显著。  相似文献   

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