Analysis and estimation of the effects of missing values on the calculation of monthly temperature indices

Long and complete climatic data series are a fundamental resource for scientific research on climate change. Data quality is important, and missing value or data gap management is a key process that must be dealt with carefully to produce reliable datasets. Although a large variety of techniques are available for gap-filling, a widespread strategy is to consider a dataset reliable if the rate of missing data is below a given threshold. However this strategy varies from study to study. The aim of this paper is to analyze the impact of missing daily values on the estimation of monthly average temperature indices. The relationship between the error of the estimate and the presence of random or consecutive missing values, as well as data series autocorrelation is also analyzed. A theoretical, a linear and a nonlinear model to estimate the maximum error at the 95 % confidence interval are tested on data series provided by national and worldwide networks of stations. Consecutive missing values have an important effect on error estimation due to autocorrelation of temperature data series. On our dataset, the mean and standard deviation of the error for five consecutive missing values (0.27?±?0.05 °C) on a normalized daily series (σ?=?1) was higher than for five random missing values (0.14?±?0.006 °C). A nonlinear model taking into account the number of consecutive missing values is able to estimate the error and its performance is less affected by the presence of consecutive missing values than the other proposed models.     

Evidence of climatic change in Nigeria based on annual series of rainfall of different daily amounts, 1919–1985

Annual series of light rainfall, moderate rainfall and heavy rainfall are computed for 4 zones arranged from south to north in Nigeria: Coastal, Guinea-Savanna, Midland and Sahelian zones. Daily rainfall data for the period 1919–85 are utilized. Each series is examined for evidence of change in structure in terms of pattern of decrease and increase in dry and wet years, the overall trend, and the occurrence of runs of dry and wet years. The northern Nigeria (Midland and Sahel) heavy rainfall series and the Sahel moderate rainfall series are found to depict evidence of climatic change as defined by Landsberg (1975) that climatic conditions must change to a new equilibrium position with the values of climatic elements changed significantly. On the other hand Landsberg's definition of climatic fluctuations as involving temporary deflection which can revert to earlier conditions is found to fit the 4 regional light rainfall series and the Midland area moderate rainfall series. The southern Nigeria moderate and heavy rainfall series are found to depict only evidence of high frequency oscillations about a stable long-term mean. The recent drought in Nigeria north of about 9° N is shown to be associated with a large decline in moderate and heavy rainfalls over this part of the country.     

Analysis of the climatic signal in the South Dome,Greenland ice core

The purpose of this research was to investigate the statistical relationship between an oxygen isotope chronology from southern Greenland and climatic variables recorded at a coastal village. The response of the oxygen isotope time series to monthly temperature and precipitation data was calculated using a combination of principal components factor analysis and multiple regression analysis. Orthogonal eigenvectors extracted from 35 yr of climatic data reliably explained 59% of the temporal variance in mean annual oxygen isotope values. The response functions demonstrate an apparent seasonal reversal in the relationship between oxygen isotope values and temperature, with the response varying between a positive (direct) relationship in winter, spring, and autumn, and a negative (indirect) relationship in summer. The results, and their implications, are shown to be useful in the historical climatic reconstruction of the South Greenland region.     

A new method to reconstruct low-frequency climatic variability from documentary sources: application to winter rainfall series in Andalusia (Southern Spain) from 1501 to 2000

In this work a simple approach to reconstruct climatic variables from documentary data is proposed. This approach may be especially useful when an overlapping period between documentary and instrumental data is not available. On the other hand, the method avoids use artificial statistical procedures to rescale the reconstructed series and overcome the problem of the loss of variance. The methodology allows reconstruct changes in the mean value and standard deviation of the climate variables. It is based on accounting the number of extreme events in past, and inferring mean value and standard deviation using the assumption of normal distribution for the climatic variables. The application of the method is only possible if a sufficient number of events is recorded in the data base. It is useful to reconstruct changes in the long-time scale, using at least decadal periods as time units. The method is applied to winter rainfall series corresponding to 30-year periods in Andalusia (southern Spain), obtaining results comparable with those of previous analysis.     

Fractal analysis of climatic data: Annual precipitation records in Spain

Summary The rescaled range analysis was applied to the annual precipitation series from 10 weather stations in Spain for the period 1901–1989. The analysis reveals that the series of precipitations fits a fractal distribution, with a mean fractal dimension of 1.32 ± 0.01. This lies in the same order of magnitude as the fractal dimensions obtained from other macrometeorological and paleoclimatic registers. The favourable comparison between fractal dimensions of the variables on both small time scales and long-term time spans suggests that such values are characteristic of climatic change over the spectral range of 10 to 10⁶ years. The results contribute to the establishment of this assumption as a valid hypothesis for the interpolation of climatic change from one scale to the next, and also in applications such as hydrological design.With 2 Figures     

短时间序列气温要素空间插值方法精度的比较研究

利用中国气象局国家气象中心的全国1956年和1998年1月和7月平均气温数据,对综合法与ANUSPLIN软件插值精度进行了比较。结果表明:在具有30 a的月平均气温栅格数据库作为背景的前提下,采用综合法对短时间序列平均气温数据进行空间化处理,其方法简单、方便,误差相对较小,是一种较适合的方法。     

1921—1990年我国气温序列及变化趋势

本文使用全国716个站点的月平均气温资料,约2.2×10~5个数据,得到了近70年来我国年、月平均气温序列。在此基础上,讨论了我国气温变化特点。结果表明:40年代到60年代的降温,我国比北半球明显;80年代气温的上升趋势,北半球比我国强烈。     

海冰—海温反馈系统的季节性动力气候模式

本文在全海洋地球的假定下,建立了一个包括太阳辐射、海面温度等季节变化的理想动力气候模式。模拟结果指出:平衡态及其对外参数敏感性的季节变化很大,而且都是夏季比其它季节大得多;四个季节敏感性的平均值也比年平均模式的敏感性大,这可能主要是太阳辐射季节变化引起的。另外,当太阳常数或二氧化碳浓度减小至一定值时,会出现分岔,若继续减小到分岔点以下,则会发生气候灾变—"深冻"。分岔点上外参数的值在夏季要比其它三个季节大得多。以上结果表明物理过程的季节变化在长期气候变化的研究中是不可忽视的。      

云量变化对净辐射的影响

本文对全球平均、各纬带平均和几种特殊下垫面条件下大气顶和地表面的净辐射随云量变化的情况进行定量分析,并讨论了净辐射对云量变化的敏感性随各参数改变的情况。另外还定性地讨论了云在全球气候中的反馈作用以及这种反馈作用随各参数变化的特点。指出:一般条件下,净辐射对于云量变化是敏感的,只有当气候参数变化到临界值附近时,对气候的模拟可以不考虑云量的变化。从云量对气候的反馈来看,在气候参数发生变化时,气候系统的稳定性会发生本质的改变。     

Climate Warming, Wildfire Hazard, and Wildfire Occurrence in Coastal Eastern Spain

A climatic series (1941 to 1994) from a Mediterranean locality of NE Spain was used to calculate two wildfire hazard indices based on daily meteorological data. Both fire hazard indices increased over this period, as a consequence of increasing mean daily maximum temperature and decreasing minimum daily relative humidity. These trends were observed in both mean values of the indices and in the number of very high risk days. Annual data on the number of wildfires and burned area also show an increase from 1968 to 1994, and are significantly correlated with both fire hazard indices. Although other non-meteorological causes (e.g., human activities, fuel accumulation) have likely contributed to the observed increase of wildfires, an effect of climatic warming on wildfire occurrence is supported by this relationship.     

Decreasing teleconnections with inter-site distance in monthly climatic data and tree-ring width networks in a mountainous Alpine area

Summary The similarities in time series recorded at sites which are distant from each other are called teleconnections. In this paper, the loss of such correlations with inter-site distance was investigated for both climatic and dendrochronological data sets, with 70 tree-ring chronologies. A dense network of weather stations was studied in the southeastern French Alps, covering complex climatic gradients over three departments. 78 sites with precipitation data (with a total of 48 756 monthly values), and 48 stations that recorded temperature (with 20 722 monthly mean values) were analysed. In the same area, four coniferous species (mountain pine and stone pine, European larch and Norway spruce) provided 37 ring-width chronologies for high elevation sites near the timberline. Both silver fir and Norway spruce provided a second tree-ring chronology network for 33 different sites at lower elevations. The teleconnections between precipitation series were found to be higher than those observed for temperature over short distances, but the maximum threshold distance was lower (193 km) compared to a positive correlation distance that exceeds 500 km for temperature. The maximum temperatures had stronger teleconnections than minimum values (522 km versus 476 km), since the latter are linked more with other site factors, such as slope, exposure and local topography. As expected, the tree-ring chronologies showed weaker teleconnections than the climatic series, with a threshold distance of 374 km obtained for all high elevation forests. The coniferous species with high intra-specific teleconnections over large distances were, in decreasing importance, Pinus uncinata (> 500 km), Picea abies (477 km), Pinus cembra (over 254 km) and Larix decidua (over 189 km only). The two former species showed the highest intra-specific correlations (with mean correlation R=0.625 and 0.666). The dendrochronological teleconnections were found to have a extent lesser for trees species that depend on rainfall (such as larch, and stone pine). They are enhanced, however, for temperature sensitive species such as spruce and mountain pine (a drought resistant tree). Therefore, these two latter conifers appear to be especially suitable for climatic reconstruction over large distances in mountainous areas. However, teleconnections within silver fir (Abies alba) and spruce chronologies were sharply reduced (over 131 km and 135 km) in lower elevation forests, underlining the interest of timberline forests for dendroclimatology. A better knowledge of the spatial correlations in climatic series and ring-width data may enable the optimisation of weather station networks. It may also permit a better choice of weather stations used for dendroclimatology, either for tree-ring and climate relationship calibration or for climate reconstructions. In dendrochronology, wood dating also requires the knowledge of to what extent remote ring-width chronologies can be used. Received September 11, 2000 Revised March 26, 2001     

气象要素时间序列的演化建模分析与短期气候预测

以武汉站(5~9月)汛期降水量观测数据序列为例,将这类具有明显的不规则性(混沌特征)时间序列分解为宏观气候尺度周期的波动部分和迭加其上的微观气候尺度周期的波动部分,分别采用演化建模方法和自然基小波方法模拟逼近。特别强调由演化建模方法得到的非线性常微分方程较之传统的线性建模具有更好的分析预测能力。     

On climatic fluctuations and climate trends of modern Moscow

Considered are the results of the investigation of climatic fluctuations, supercentury climate trend, and 30-year trends in modern Moscow based on the time series of monthly mean values of air temperature for 1879?C2010. The data of air temperature anomalies in the Northern Hemisphere for the same period were used for the comparison. The computation of characteristics was carried out using the method of singular spectral analysis.     

Estimation of the monthly and annual mean maximum and mean minimum air temperature values in Greece

In this study, regression equations to estimate the monthly and annual values of the mean maximum and mean minimum air temperatures in Greece are derived. For this purpose, data from 87 meteorological stations distributed all over Greece are used. Geographical parameters, i.e., altitude, latitude, longitude, minimum distance from the sea and an index of terrain morphology, are used as independent variables. These equations explain 79?C97% of the variance of the temperature values and have standard error of estimate between 0.59 and 1.20°C. Data from 37 other meteorological stations are used to validate the accuracy of the equations. Topographic or climatic factors, which could not be introduced into the equations, are responsible for most temperature residuals >0.5°C or <?0.5°C. Moreover, some particular emphasis has been given to the values of the regression coefficient for the altitude, since it is the estimator for the mean lapse rate of air temperature.     

On the sea level variability and storm surge frequency from the data of tide-gage stations in the Northwestern Pacific

The sea level variability in the Northwestern Pacific based on the observations at tide-gage stations of JASL system is considered. The long-term seasonal variations of the sea level at these stations are presented and the climatic trends, variability range, and standard deviations of monthly mean values of the sea level from the long-term seasonal values are computed. The frequency of the sea level exceeding relative to the moving average with the shift of 30 days is computed. It is shown that, contrary to general opinion, the frequency of the sea level exceeding relative to the moving average in the Northwestern Pacific does not increase on the whole under conditions of the climate warming and sea level rise.     

Reconstruction of Nineteenth Century Summer Temperatures in Norway by Proxy Data from Farmers'Diaries

Proxy data from five farmers; diaries in the Møre, Dovre and Trøndelag regions in central Norway were used for climatic reconstruction purposes. The method chosen was "simple linear regression analysis" with the start of the grain harvest (barley or oats) as predictor and summer temperature (May – August) as predictand. Overlapping periods with modern instrumental observations (starting 1858 or later) were used for calibration of the model. The model was tested on independent data by establishing the regression on one half of the overlapping period and applying the regression on the other half. The standard deviation in the residuals varied from 0.3°C to 0.7°C and the biases of the mean values from –0.3°C to +0.3°C. Climatic reconstructions were established for the early- and mid-nineteenth century summer temperature, i.e. during the last part of what has come to be regarded as the "Little Ice Age", in this article considered to end around 1880.By use of the proxy data model, huge inhomogeneities of the "classical" Trondheim series were detected, the early nineteenth century part of the series evidently being too warm. The inhomogeneity was removed by use of adjustment terms. The adjusted series indicates that in the Trondheim region the summer temperature during the last part of the "Little Ice Age" phase was about 1°C lower than the latest 60 years. This is in serious contradiction to the classical Trondheim series.     

洞庭湖区近百年气温序列构建及其变化特征

采用统计方法并结合气象台站历史沿革信息,对1910-2010年洞庭湖区气温观测资料进行均一性检验和订正,并利用洞庭湖区周边气象台站资料对洞庭湖区1951年以前缺测的气温资料进行插补,构成完整的气温序列。基于洞庭湖区完整气温序列,构建洞庭湖区近百年气温序列并分析其变化特征。结果表明：1910-2010年洞庭湖区年平均气温呈显著上升趋势,其中冬季和春季平均气温上升幅度最大,秋季次之,夏季变化趋势不显著;气温变化存在明显的冷暖交替,冷暖期交替比中国地区更频繁;近百年洞庭湖区年和冬季、春季、秋季平均气温均存在一个显著增暖的突变点;小波分析表明,近百年洞庭湖区年和四季平均气温均经历了冷-暖-冷-暖4个阶段的交替。     

Functional clustering for Italian climate zones identification

This work presents a functional clustering procedure applied to meteorological time series. Our proposal combines time series interpolation with smoothing penalized B-spline and the partitioning around medoids clustering algorithm. Our final goal is to obtain homogeneous climate zones of Italy. We compare this approach to standard methods based on a combination of principal component analysis and Cluster Analysis (CA) and we discuss it in relation to other functional clustering approaches based on Fourier analysis and CA. We show that a functional approach is simpler than the standard methods from a methodological and interpretability point of view. Indeed, it becomes natural to find a clear connection between mathematical results and physical variability mechanisms. We discuss how the choice of the basis expansion (splines, Fourier) affects the analysis and propose some comments on their use. The basis for classification is formed by monthly values of temperature and precipitation recorded during the period 1971–2000 over 95 and 94 Italian monitoring stations, respectively. An assessment based on climatic patterns is presented to prove the consistency of the clustering and a comparison of results obtained with different methods is used to judge the functional data approach.     

9414号热带气旋(DOUG)非对称结构和对降水影响的分析

ＤＯＵＧ热带气旋在靠近华东沿海大陆北上过程中，气旋西侧的降水强度显著减弱，主要是ＤＯＵＧ气旋的完全非对称结构造成的。本文从大尺度天气系统配置、卫星云图和中尺度数值模式计算结果分析了ＤＯＵＧ气旋内区和外区非对称结构的成因和演变。外区的非对称结构主要由环境场的大尺度天气系统的东高西低气压场配置造成的。气旋近中心中－β尺度的辐散下沉系统的发展是造成内区非对称结构的主要原因。二者的形成是相互独立的。但内区非对称结构的发展会促使外区非对称结构的加强。前者向后者逼近并结合造成了ＤＯＵＧ的完全非对称结构     

A MODIFIED WEATHER GENERATOR(WGEN)FOR THE GENERATION OF DAILY WEATHER VARIABLES

Long series of daily weather data are frequently needed to evaluate diachronic climatic impacton water resources,the effects of watershed changes on hydrology and to use in a variety ofweather and general circulation models.A computer generation model called WGEN that wasdeveloped in the United States of America,was modified in this study and applied to Nigerianweather data spanning the period between 1969 to 1988 and covering 17 sites located in thedifferent climatic zones in Nigeria.The model generated the monthly mean maximum and minimumtemperatures,solar radiation,total rainfall,and number of wet and dry days with high accuracy,95% of the times.The Mann-Whitney U-test revealed that the number of months per year forwhich observed and generated weather variables were significant,was less than 4 in majority of thesites.