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This paper studied the spatial and temporal variability of the statistical structures of precipitation across Xinjiang, China, by analysing the time series of daily precipitation from 50 weather stations during the period from 1961 to 2008. Three indices precipitation concentration index (CI), precipitation concentration degree (PCD) and precipitation concentration period (PCP) were used to detect precipitation concentrations and the associated spatial patterns. The results show that higher precipitation CI values were mainly observed in Southern Xinjiang, whereas lower precipitation CI values were mostly detected in Northern Xinjiang. The precipitation CI values are noticeably larger in places where both annual total precipitation and number of rainy days are lower. The Mann-Kendall trend test demonstrates that the most parts of Xinjiang are characterized by no significant trends of precipitation CI at the 0.05 significance level. The periodicity characteristic of precipitation CI time series in Xinjiang could be detected by wavelet power spectrum analysis, and significant periods of that in most of Xinjiang were concentrated on 2-5 years band. The results of PCP reveal that rainfall in Xinjiang mostly occurs in summer, and the rainy season arrives earlier in Eastern Xinjiang than Western Xinjiang, whereas the results of PCD indicate that the rainfall in Northern Xinjiang was more dispersed within a year than that in Southern Xinjiang. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Climatological patterns in wind speed fluctuations with periods of 1 min to 10 h are analysed using data from a meteorological mast in the Danish North Sea. Fluctuations on these time scales are of particular relevance to the effective management of the power supply from large wind farms. The Hilbert-Huang transform (HHT) is shown to be an effective tool for analysing long time series of wind speed observations, as it describes the time-evolving spectral information in the time series. By binning and averaging the time-evolving spectrum, the average spectral behaviour of the wind speed under a certain class of conditions can be found. Here, the HHT is applied to create conditional spectra which demonstrate patterns in the occurrence of severe wind variability. It is shown that wind fluctuations over the North Sea are more severe for westerly flow than for easterly flow, and that severe fluctuations are often observed in the vicinity of precipitation. The most severe wind fluctuations occur in the autumn and winter seasons, and are slightly more common when the pressure tendency is rising. Further, it is found that the wind is more variable for atmospherically unstable conditions than for stable conditions. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article discusses the numerical experiments conducted by the National Centers for Environmental Prediction (NCEP) using the regional spectral model (RCM) to learn the effects of the Tibetan Plateau (TP) upon the Asian summer monsoon (ASM), the Indian Summer Monsoons (ISM) and the East Asian summer monsoon (EASM). The study finds that the TP height is directly proportional to the simulated ISM precipitation over north India.

The article presents a study on the measurement of the erythemal clearness index for Valencia, Spain. Values of three clearness indices were measured including the clearness index for the whole spectrum, clearness index for the ultraviolet range, and the erythemal clearness index for the erythemal radiation. The measurements of the clearness index for ultraviolet range reached values that were approximately 54% of that corresponding to the clearness index for the whole solar spectrum, while those of the measurements for clearness index for erythemal radiation were much smaller. Statistics for the erythemal clearness index were also calculated both for monthly as well as hourly means.

Spatial and temporal patterns in the daily rainfall regime of Catalonia (northeastern Spain) recorded for the 1950–2000 period are analysed from several points of view, including the irregularity of the time series in terms of entropy, the Mann–Kendall test for time trends, a principal component analysis (PCA), an average linkage (AL) clustering algorithm and, finally, a power spectrum analysis, which includes a comparison of white-noise and Markovian red-noise hypotheses. The analyses are based on three monthly variables derived from the amounts recorded on a daily basis: the average daily rainfall and the standard deviation of the daily rainfall for each month, together with the corresponding coefficient of variation. The joint spatial–temporal variability is manifested by the irregularity index, which is characterized by relevant values in all cases and gradients from the north (Pyrenees and Pre-Pyrenees mountain ranges) to the south (Ebro Valley) and to the Mediterranean coast. The interpretation of the factor scores derived from the PCA and of the clusters obtained from the AL algorithm also describes the complex spatial distribution of the daily rainfall regime, given that the effects of atmospheric circulation patterns on rainfall regimes are conditioned by the complex orography of Catalonia and its proximity to the Mediterranean Sea. The factor loadings associated with the PCA also suggest a distinction between hot, cold and mild seasons. Finally, it is worth noting that monthly series are usually accompanied by white background noise and, in a few cases, signs of Markovian behaviour and some significant periodicities, which are generally of less than 10 months and which change from one cluster to another. Copyright © 2004 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The main questions motivating this study are: Can climate simulations describe the observations? To what extent can we use climate models to predict climate change? For this purpose, an analysis was made of the correspondences and/or discrepancies between observed winter precipitation data and the data from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis project, and from two global climatic models: ECHAM4/OPYC3 and HadCM3. The data used correspond to the accumulated winter precipitation for the period 1949–2000, and comparisons of the mean and variability patterns were made. The methods used were principal components analysis, to break down variability and reduce the dimensions of the fields, and correlation and cross-spectrum analyses for comparison of the time series. For all these, we studied the suitability of their average distributions, as well as their modes of spatial and spectral variability. The results for the Iberian Peninsula show good agreement between the precipitation data of the NCEP–NCAR reanalysis and the observations, both in the average analysis and in the main modes of spatial and time variability. Therefore, the reanalysis data were proved to be a good resource for interpreting climate variations. As regards the climatic models considered, in general the results point to their suitability for describing the spatial distribution of winter precipitation, whereas the spectral association is less appropriate. The variability of the precipitation data was related to circulation patterns and teleconnection indices, such as the North Atlantic oscillation and the Arctic oscillation. The results allow us to conclude that the discrepancies between the two models and observations must be due to a weak representation of the interannual variability. Copyright © 2004 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Develops a parameterization for mean effective size Dge in terms of ice water content (IWC) and temperature using in situ measurements of ice crystal spectra, cloud particle shapes and particle cross-sectional area A from four research projects conducted in latitudes north of 45 degrees N. Generally, Dge and IWC increase with increasing temperature. Good agreement between the parameterized Dge and derived Dge from measurements were found when small particles were included.

Russian winter snow depth data over a 48-year period (1936–1983) are analysed to reveal variation characteristics and associations to Atlantic sea surface temperature (SST) anomalies using methods of rotated principal component analysis (RPCA), singular spectrum analysis (SSA), and singular value decomposition (SVD) analysis. The study demonstrates that four time scales (4 years interannual, 11.8 years quasidecadal, 20 years bi-decadal and trend) characterize Russian winter snow depth variations. The decadal and longer time scale variations are found to be significantly associated with Atlantic SST anomalies. The trend, which occurred over much of the study region, is associated with SST trends over the northern north and tropical south Atlantic. Bi-decadal snow depth variation over central Siberia is associated with western tropical north Atlantic SSTs. A quasi-decadal variation over western European Russia is connected to a major Atlantic SST variation pattern of opposite signs over alternative latitudinal belts. This study suggests that the connections between the Atlantic Ocean and regional climate may be better reflected at decadal time scales than interannual and seasonal ones, as the dominant variability over the ocean is at slow modes. Copyright © 2000 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

An analysis of the variability of the North Atlantic Oscillation (NAO) since the beginning of the 19th century has been carried out using monthly pressure series from Gibraltar, Lisbon, The Azores and Iceland. In the first part, the combinations of stations that best monitor the NAO at different time intervals (monthly, seasonal and winter-annual) are analysed based on a signal/noise approach. The stability through time of the relationship between the pressures at the different stations is also studied. Based on this analysis, proxy indices of the NAO are obtained and compared with the NAO index resulting from a principal component analysis (PCA) of gridded sea level pressure (SLP) data. In the second part, the cross-spectral characteristics of the data of the northern and southern stations are studied in order to determine for which ranges of periods the pressure undergoes simultaneous coherent and out-of-phase variations. Based on the cross-spectral analysis, several filters are proposed to be applied to the pressure series prior to calculating the NAO index, in order to improve the reliability of the NAO index as an indicator of the NAO. Results show that for a monthly or seasonal index, The Azores must be selected as the southern station, but the strongest relationship is found for winter using Gibraltar as the southern station. The cross-spectral analysis shows, firstly, that the periods that are mainly responsible for coherent and out-of-phase variations are 6 months, 1 year, 2 years and 8 years (the most important). Secondly, several ranges of periods, mainly from 3 to 4 years and less than 6 months, are shown not to contribute to coherent and out-of-phase relationships between stations. Removing these ranges of periods from the pressure series prior to calculating the indices notably improves the reliability of the indices as indicators of the NAO state. The comparison of the filtered and unfiltered indices shows that extreme values of the NAO result from coherent out-of-phase pressure variations between stations. Copyright © 2000 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Based on a 5°×5° gridded monthly precipitation data set from 1911 to 1990, quasi-periodic oscillations are identified by performing a multichannel singular spectrum analysis (MSSA) on the first ten principal components (PCs; explaining 53.1% of total variance) of normalized monthly precipitation fields over Europe. Two robust quasi-periodic oscillations are isolated with periods of 23.8 months (2.0 years) and 43.5 months (3.6 years), respectively. Applying a reconstruction technique and composite analysis, spatial structures and temporal propagation of the quasi-periodic oscillations are revealed. The two oscillations behave differently: the 43.5-month oscillation clearly propagates northward; however, the 23.8-month oscillation seems quasi-stationary, although it propagates slowly southward. This may imply that the causes of these two oscillations are different. Oscillatory behaviour in the time series of a North Atlantic Oscillation (NAO) index has also been analysed by performing singular spectrum analysis (SSA) for the same period used for the analysis of precipitation. However, in the time series of the NAO index, the dominant oscillation is a 27.7-month (2.3-year) period, with no robust oscillation with a period of 3.6 years being detected. Furthermore, the two oscillations cannot be identified by MSSA from the precipitation fields regressed upon the NAO index. Therefore, it appears that the two quasi-periodic oscillations are not well related to the NAO, which may not be the most important atmospheric pattern associated with non-seasonal precipitation variability over Europe. Copyright © 2000 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The frequency spectrum of Northern Hemisphere atmospheric CO2 concentration shows strong periodicities at 6.2, 1.0 and 0.5 years. The 6.2 year cyclicity has been attributed to non-linear interactions between the annual cycle and the atmospheric pole tide. The yearly signal is linked to terrestrial photosynthesis; phase analysis shows that annual CO2 minima occur at a lag of approximately 85 days from insolation maxima. Variations in the nominal yearly period occur during times of anomalous anthropogenic CO2 production. Periodicity at 6 months represents a deviation of the yearly signal from an annual sinusoid. If the yearly signal is largely sinusoidal, a plausible source of the 6 month periodicity could be cyclic phytoplankton productivity driven by natural insolation modes. Together, the three largest spectral peaks account for over 99% of the variation in detrended CO2 data. Copyright © 1999 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The 12-monthly running means of stratospheric low latitude zonal winds at 10, 15, 20, 30, 40, 50, 70 mb, Southern Oscillation Index represented by Tahiti−Darwin atmospheric mean sea level pressure difference (T−D) and equatorial eastern Pacific sea surface temperature (SST) were subjected to maximum entropy spectral analysis for the whole period 1953–1995 as also for its portions. The SST and (T−D) had similar periodicities, as expected, the majormost at ca. 4.5 years and other smaller ones in the quasi-biennial and quasi-triennial regions. The stratospheric winds had the most prominent periodicity at ca. 2.17 years (26 months) in the early years, which changed to ca. 2.22 years (26.5 months) in the middle and ca. 2.50 years (30 months) in recent years, and had other minor periodicities. Some of the wind periodicities matched some of the SST, (T−D) periodicities during some intervals, indicating possible partially common origins and/or mutual influences. © 1998 Royal Meteorological Society [ABSTRACT FROM AUTHOR]