Catalonian precipitation patterns: Principal component analysis and automated regionalization

Summary A principal component analysis (PCA) based on a network including 179 pluviometric gauges is attempted in order to describe the main patterns governing precipitation in Catalonia (NE Spain). This PCA procedure is applied to the interstation covariance matrix and component loadings are then deduced from it and extensively interpreted. PCA results are used immediately after in a Davis and Kalkstein clustering process, leading to a rainfall division. The homogeneity of the different groups obtained is tested by means of the analysis of their spatial and temporal within-group variances.With 8 Figures     

Principal Component Analysis of precipitation and rainfall regionalization in Spain

Summary A T-mode Principal Component Analysis (PCA) based on a network including 68 pluviometric gauges and their 12 mean monthly amounts of rainfall is attempted in order to describe the main patterns governing precipitation in Spain. The procedure is applied to a 12 × 12 intermonth covariance matrix; the unrotated components and two additional solutions deduced after varimax and oblimin rotations are presented and discussed. In all cases component scores are computed and their spatial distribution is discussed. Two regionalizations of Spanish rainfall are then obtained and compared in terms of group homogeneity. There follows a discussion concerning the main pluviometric characteristics of each region deduced from the best division.With 7 Figures     

福建春雨多时空尺度变化特征

利用主成分分析和相关分析表明,近40 a来福建春雨量场的主要信息集中在前2个主分量上,可解释方差的83.8%,同时第1、第2主成分与福州、厦门春雨的相关显著性水平都超过0.01,因此,可用近百年福州、厦门3—4月降水量构造新序列代表福建春雨的前2个主分量,使分析资料延长至百年。采用连续小波分析和正交小波分析方法以及功率谱方法,研究福建春雨空间分布型的多时间尺度特征,研究结果表明：第1主分量表示的全省一致性旱涝具有显著的准4 a和24～26a的周期振荡;第2主分量表示的春雨分布南北差异主要表现为准两年和准11 a的周期振荡;春旱年南部的降水少于北部;从年代际角度看,20世纪50—60年代显著偏少,80年代显著偏多。福建目前处于春雨正常—偏少期,且南部的春旱比北部严重。     

Spatial and temporal characteristics of intraseasonal oscillations of precipitation over the United States

Summary  This study shows that precipitation over the United States has two time scales of intraseasonal variation at about 37 days and 24 days. The results are derived from the application of a combination of statistical methods including principal component analysis (PCA), singular spectrum analysis (SSA), and multi-channel singular spectrum analysis (MSSA) to over 10 years of gridded daily precipitation records. Both oscillations have largest amplitude during the cold season. The 37-day oscillation has larger interannual variability. Intraseasonal oscillations are most significant in the Pacific Northwest. The 37-day oscillation has opposite phases between the western and eastern United States, while the 24-day oscillation has the same phases. These intraseasonal time scale precipitation variations may be associated with previously revealed mid-tropospheric circulation anomalies that oscillate at similar time scales. Received February 7, 2000 Revised October 20, 2000     

中国夏季降水异常分布的非线性特征

运用基于前馈型人工神经网络的非线性主成分分析方法(NLPCA),对中国近50 a夏季降水异常分布的非线性特征进行了分析。结果表明,中国夏季降水的异常分布具有一定的非线性特征,当夏季降水距平的一维NLPCA近似在非线性主成分取极端相反位相时,对应的空间分布型表现出明显的不对称性;一维NLPCA对夏季原始降水距平场的近似,比传统一维PCA的近似更为逼真。     

基于主分量神经网络的降水集成预报方法研究

运用人工神经网络与主分量分析(PCA)相结合的方法,对同一降水预报量的各种数值预报产品进行集成预报研究.结果表明:主分量人工神经网络方法所构造的集成预报模型,不仅对历史样本的拟合精度好于个各子预报产品,独立样本的实验预报结果也显示出更好的预报准确率及稳定性.业务应用前景良好.     

Moderate to heavy cold-weather precipitation occurrences in Tehran and the associated circulation types

Large-scale atmospheric circulations associated with 133 moderate to heavy cold-weather precipitation events recorded at Mehrabad station in Tehran, Iran, during the period 1951–2013 are analysed. To this end, the performance of un-rotated, orthogonally rotated and obliquely rotated solutions of T-mode principal component analysis (PCA) is examined in classifying the atmospheric circulations into a few representative circulation types (CTs). The T-mode PCAs were applied to the 500-hPa geopotential height for the events in a domain from 10^°E to 70^°E and from 20^°N to 50^°N. The first six leading principal components were retained and then orthogonally and obliquely rotated using varimax and promax solutions, respectively. Statistical inter-comparison of the CTs obtained using the three solutions suggests that the obliquely rotated solution is the better choice for circulation classification in the present study. The six CTs obtained using the oblique rotation were then linked to the daily total precipitation and daily mean temperature variability at Tehran station as well as to the standardized anomalies of the daily total precipitation and mean daily temperature of a dense network of stations distributed across Iran. It is found that the CTs identified, though generally comparable in producing significant precipitation in Tehran, vary in their potential to bring cold weather and generate snowfall in Tehran specifically and in the country in general. While the first three CTs give rise to regional patterns of standardized precipitation anomalies centred in Tehran, the next three CTs leave a pronounced precipitation signature almost across the whole country. As regards the standardized temperature anomalies, with the exception of one CT that causes deep and widespread negative standardized anomalies over most parts of the country, the other CTs are characterized with a dipolar structure of a deep intrusion of cold weather to the west and prevailing warm weather to the east of the country.     

Spatial and temporal variability of precipitation indices during 1961–2010 in Hunan Province,central south China

Based on daily precipitation records at 75 meteorological stations in Hunan Province, central south China, the spatial and temporal variability of precipitation indices is analyzed during 1961–2010. For precipitation extremes, most of precipitation indices suggest that both the amount and the intensity of extreme precipitation are increasing, especially the mean precipitation amount on a wet day, showing a significant positive trend. Meanwhile, both of the monthly rainfall heterogeneity and the contribution of the days with the greatest rainfall show an upward trend. When it comes to rainfall erosivity, most of this province is characterized by high values of annual rainfall erosivity. Although the directions of trends in annual rainfall erosivity at most stations are upward, only 6 of the 75 stations have significant trends. Furthermore, the spatial and temporal variation of dryness/wetness has been assessed by the standardized precipitation index (SPI). The principal component analysis (PCA) was applied to the SPI series computed on 24-month time scales. The results demonstrated a noticeable spatial variability with three subregions characterized by different trends: a remarkable wet tendency prevails in the central and southern areas, while the northern areas are dominated by a remarkable dry tendency.     

Spatiotemporal variability of drought on a short–medium time scale in the Calabria Region (Southern Italy)

The study analyses spatial and temporal patterns of drought in an area with a wide range of precipitation characteristics (the Calabria region in southern Italy) during the period 1921?C2007. The short-time (2, 3 and 6?months) Standardised Precipitation Index (SPI) was estimated to analyse drought especially from the agricultural point of view. Principal component analysis (PCA) was applied to the SPI to assess the spatial variability of drought. During the period of observation, moderate to severe drought occurred at a frequency of almost 13?% in wet seasons (autumn and winter). Almost half of the region was affected by drought in the years 1981?C1990 when the area experienced its most severe drought. Although the spatial patterns of drought estimated by PCA were logical and consistent with precipitation distribution, very complex patterns were observed for all the time scales looked at. The high fragmentation of the maps obtained makes them of limited value, and caution is recommended in classifying the region into homogeneous areas.     

Circulation patterns, daily precipitation in Portugal and implications for climate change simulated by the second Hadley Centre GCM

Based on principal component analysis (PCA) and a k-means clustering algorithm, daily mean sea level pressure (MSLP) fields over the northeastern Atlantic and Western Europe, simulated by the Hadley Centre's second generation coupled ocean-atmosphere GCM (HADCM2) control run (HADCM2CON), are validated by comparison with the observed daily MSLP fields. It is clear that HADCM2 reproduces daily MSLP fields and its seasonal variability over the region very well, despite suffering from some deficiencies, such as the systematic displacement of the atmospheric centres of action. Four daily circulation patterns, previously identified from the observed daily MSLP fields over the area and well related to daily precipitation in Portugal, were also well classified from the daily MSLP fields simulated by HADCM2. The model can also simulate rather successfully the relationships between the four daily circulation patterns and daily precipitation in southern Portugal. However, compared with observations, daily precipitation intensities simulated by the model are too weak in southern Portugal. Nevertheless, HADCM2 represents a considerable improvement relative to the UKTR experiment. The results described here imply that it is doubtful whether regional precipitation scenarios provided by HADCM2 can be directly applied in impact studies and that a downscaling technique, based on daily circulation patterns, might be successful in reproducing local and regional precipitation characteristics. Moreover, the four circulation patterns can also be clearly identified in the two perturbed experiments, one under greenhouse gases forcing only (HADCM2GHG) and the other under additional forcing of sulphate aerosol (HADCM2SUL), although changes in the frequencies of occurrence of certain circulation patterns are found. Nevertheless, the observed links between regional precipitation in southern Portugal and large-scale atmospheric circulation seem likely to hold in the model's perturbed climate. It is therefore credible to use those links to downscale large-scale atmospheric circulation from GCM simulations to obtain future precipitation scenarios in southern Portugal. Received: 21 August 1998 / Accepted: 28 May 1999     

Iran's precipitation analysis using synoptic modeling of major teleconnection forces (MTF)

In this relatively unprecedented study, the effects of thirty-four leading teleconnection Patterns (indices) of atmospheric circulation- on regional-scale for the Middle East- along with precipitation over Iran have been investigated. Different types of data including teleconnection Indices from NOAA (NCEP/NCAR, BOM) and monthly precipitation data from thirty-six synoptic stations of Iran were applied. The data have been investigated with various types of statistical and synoptical methods. The results indicate that El Niño–Southern Oscillation (ENSO) is the most effective factor and it could possibly influence the spatiotemporal variation of precipitation on all types of climate regimes in Iran. ENSO (nino3.4), The Atlantic Multidecadal Oscillation (AMO) and The Arctic oscillation (AO) are known as the first three important indices, determined by Principal component analysis (PCA) method. The research has clarified that a combination of warm phase of ENSO and a predominant Southeastern (SE) wind over the Indian Ocean can result in a significant moisture transport from the Indian Ocean to the Middle East and to Iran; a combination of cold phase of ENSO and a predominant Northwestern (NW) wind over the Indian Ocean can be followed by a widespread drought over the Middle East and Iran. The results also indicate that a combination of the first three important above-mentioned indices and the Indian Ocean Dipole (IOD) can provide a much better explanation for spatial and temporal variation of precipitation of Iran. Finally, the results of this study will enable us to present a new approach and new graphical-conceptual modeling, called "Teleconnection-Synoptic Method (TSM)"to clarify the underlying mechanism that can explain the spatial and temporal variations of global atmospheric circulation and precipitation of Iran. According to the correlation of different patterns with precipitation, the strongest relationships are related to the Scandinavia Index (SCN), Pressure Change in East Pacific (dPEPac) and Trade Wind Index at the 850 hPa (TrdWnd850), respectively.     

近50年火山喷发和太阳活动对我国气候影响的研究

利用特征向量分析与时序叠加分析和谱分析相结合的方法，分析了近50a来我国地面气温和降水场中火山喷发和太阳活动的气候信号，强烈的火山喷发导致全国大部分地区降温，喷发1a多以后降温最明显，并能持续约半年。除这个主信号以外，青藏高原、东南沿海和东北地区都可能出现较为复杂的温度变化，温度变化与太阳活动之间的联系更多地反映在二者的振荡关系上。在降水场中的火山信号较弱，表现为火山喷发后的秋冬季节南方地区降水偏多。在青藏高原积雪和深层地温的变化中，没有发现火山和太阳活动信号。     

基于EC025配料的短时强降水概率预报产品及应用

利用ECMWF预报资料,从动力、热力、水汽、能量和降水预报5个方面选取影响短时强降水发生的因子,构建多因变量数组,并利用主成分分析确定配料系数及其阈值,在此基础上进行配料,研发了四川省短时强降水概率预报产品投入应用。结果表明:产品对盆地20mm/h以上和高原地区10mm/h以上的短时强降水落区预报效果显著。      

Reconstruction of long-term precipitation records for Edinburgh: an examination of the mechanisms responsible for temporal variability in precipitation

Summary Recent dry years (combined dry winter and summer months) within the UK (2005 and 2006) have enhanced concerns relating to long term water resources and future water provision in large conurbations. This paper examines the mechanisms responsible for precipitation variability for five different areas in Edinburgh (precipitation regions) using composite historic precipitation records for the period 1861–2005. Trend analysis and principal component analysis (PCA) were undertaken to examine precipitation variability over time and space. Annual correlation co-efficients were derived for relationships between precipitation areas, atmospheric–oceanographic variations and geographic parameters. Stepwise regression models were constructed to specify annual precipitation, through atmospheric variations, for each of the precipitation areas. Significant downward trends in precipitation (p < 0.05) were noted in two out of the five precipitation areas, with one principal component representing precipitation variability over Edinburgh and the Pentland Hills. Precipitation variability is best explained by fluctuations in pressure, altitude and proximity to coast. Precipitation trends cannot be explained by changes in atmospheric circulation patterns. Authors’ addresses: N. Macdonald, Department of Geography, University of Liverpool, Liverpool L69 7ZT, United Kingdom; I. D. Phillips, J. Thorpe, School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston B15 2TT, United Kingdom.     

A spectral analysis of Iberian Peninsula monthly rainfall

Summary A spectral analysis of Iberian Peninsula monthly rainfall series was carried out. The data set consists of monthly precipitation records from 40 meteorological observatories over 74 years (1919–1992). The stations are representative of most of the Iberian Peninsula. The rainfall series were analyzed spatially by means of Principal Component Analysis (PCA) and temporally by means of the Multi-Taper Method (MTM) of spectral analysis of by Monte-Carlo Singular Spectrum Analysis (MCSSA). The PCA gave six dominant modes of variation which explain 75% of the variance with each component affecting a different region of the Peninsula. The spectral analysis showed 7 year oscillations for the dominant pattern and 2.7 and 16 years for the third pattern. The 7-year oscillation seems to be related to other climatic oscillations recorded in the northern hemisphere while the 2.7-year oscillation could be related to the ENSO phenomenon. Received July 18, 2000 Revised April 19, 2001     

Low Frequency Variability of Rainfall in Southeastern South America

Summary The climatic variations of precipitation, within the period range of 10 and 100 years, in the Southeastern South America (SSA) region are investigated. A gaussian low-pass filter with a cut-off period at 30 years, was applied to annual precipitation records, in order to smooth high frequencies and to make evident the variability within the searched low frequency ranges (longer-than-30 years period). The principal components analysis (PCA) applied to filtered series allowed the determination of two climatic signals, defined by the first and second principal components (PC ₁ and PC ₂). Both signals reflect remarkable changes in the annual precipitation values (a sustained increase in precipitation), over a large region of SSA (great part of Argentine pampas and Uruguay). The PCA applied to the filtered precipitation records for each quarter, which we have associated to seasonal rainfall, allowed the determination of the incidence of PC ₁ and PC ₂ on the variability of the series. In particular, it is in the summer rainfall where the two first seasonal components, (PC1₁ and PC1₂), show a high degree of similarity (correlations >0.8) with the respective annual components PC ₁ and PC ₂. During the spring season only the first component, (PC4₁), shows high correlation with PC ₁; the rest of the seasonal components do not show correlations exceeding the established values of 0.8. Received May 5, 1997 Revised April 26, 1998     

Influence of observed and RCM-simulated precipitation on the water discharge over the Sirba basin, Burkina Faso/Niger

The forcing of a hydrologic model (ABC) by both observed and simulated precipitation from a regional climate model (MAR) has been performed over the Sirba watershed (39,000 km²) located in the Sahelian region. Two aspects have been more specifically examined: the spatial and temporal representations of precipitation. The comparison between simulated and observed discharges—using observed rainfall datasets as forcing of the hydrologic model—has shown that the representation of daily precipitation (which is mainly convective in the Sahelian region) was not sufficiently accurate to correctly simulate the hydrologic response of the watershed. Since this response drives the soil water budget and consequently the amount of evaporation in forthcoming coupling experiments, it is thus necessary to develop more realistic infra-daily precipitation associated with convective events. A new temporal disaggregation scheme has been then developed. Considering observed as well as simulated precipitation fields, this method has significantly improved the simulated discharge at the catchment outlet. The major role played by the temporal component compared to spatial component of the precipitation has been then underlined. In addition, the present study shows the unsuitability of the simulated precipitation from the RCM to directly force a hydrologic model at infra daily timescale even if the cumulative amount and the main features of the precipitation seasonal cycle are well simulated.     

Analysis of drought determinants for the Colorado River Basin

Ongoing drought in the Colorado River Basin, unprecedented urban growth in the watershed, and numerical model simulations showing higher temperatures and lower precipitation totals in the future have all combined to heighten interest in drought in this region. In this investigation, we use principal components analysis (PCA) to independently assess the influence of various teleconnections on Basin-wide and sub-regional winter season Palmer Hydrological Drought Index (PHDI) and precipitation variations in the Basin. We find that the Pacific Decadal Oscillation (PDO) explains more variance in PHDI than El Niño-Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), and the planetary temperature combined for the Basin as a whole. When rotated PCA is used to separate the Basin into two regions, the lower portion of the Basin is similar to the Basin as a whole while the upper portion, which contains the high-elevation locations important to hydrologic yield for the watershed, demonstrates poorly defined relationships with the teleconnections. The PHDI for the two portions of the Basin are shown to have been out of synch for much of the twentieth century. In general, teleconnection indices account for 19% of the variance in PHDI leaving large uncertainties in drought forecasting.     

长江中下游夏季降水与热带对流的关系

本文利用1979～2001年中国160站月平均降水资料、NCEP／NCAR月平均再分析资料，包括OLR资料、500hPa高度场、海平面气压场及850hPa风场，借助相关分析、合成分析研究了长江中下游夏季降水与热带对流活动的关系。结果表明，热带对流活动与长江中下游夏季降水之间呈显著的正相关，即夏季热带对流活动强(弱)，长江中下游降水偏少(多)，易出现干旱(洪涝)。热带对流活动异常引起中、低纬度大气环流系统异常，中、低纬度大气环流系统异常向中、高纬度传播，引起中、高纬度大气环流系统异常，构成东亚地区大气环流异常，导致长江中下游地区夏季降水异常。     

交叉熵神经网络及其在闽北大雨以上降水预报中的应用

基于误差平方和最小化准则的BP神经网络(ANN-MSE)并不适合解决小概率天气事件的预报问题,引进一种改进的以交叉熵函数为目标函数的神经网络方法(ANN-CE),该法是一个三层反向传播神经网络,其输出层只用一个节点.利用2003-2008年的ECMWF预报场资料,把该法用于福建省南平市4-6月部分大雨或以上降水96h预报中,分别用原始因子和PCA降维后的主因子建立了ANN-CE预报模型和ANN-MSE预报模型,用这些模型对2009-2010年独立样本进行了试报.测试结果显示主因子预报模型TS评分比原始因子预报模型高且漏报次数少,其中,主因子ANN-CE预报模型的TS评分和漏报率分别是0.51和0.17,其性能是所有模型中最好且最为稳定的,是一种适合于小概率事件预报的方法.