Low-frequency oscillations in the Northern Hemisphere

Summary Multichannel singular spectrum analysis (MSSA) has been applied to 5-day mean grid point data of 500 hPa geopotential heights over the Northern Hemisphere, to explore low frequency oscillatory variabilities over the region. Two major low-frequency oscillations with periods of 60–70 and 30–40 days were found. These two quasi-periodicities are significantly (at the 99% confidence level) different from those found in the corresponding pure red noise process. Also, they were reproducible when using different window lengths for MSSA and when applying MSSA to two equal-length subsets of the basic data series. In addition, when one subset (first subset) is projected onto the patterns of the other subset, the resulting (projection) spatial-temporal principal components corresponding to the two oscillations are highly correlated with those ST-PCs directly derived from the first subset by MSSA, indicating that the oscillatory components obtained from one subset explain a significant amount of variance in the other subset. Some reliable information about the amplitudes of the oscillations has been also obtained by using composite analysis.With 5 Figures     

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     

Daily modes of South Asian summer monsoon variability in the NCEP climate forecast system

The leading modes of daily variability of the Indian summer monsoon in the climate forecast system (CFS), a coupled general circulation model, of the National Centers for Environmental Predictions (NCEP) are examined. The space?Ctime structures of the daily modes are obtained by applying multi-channel singular spectrum analysis (MSSA) on the daily anomalies of rainfall. Relations of the daily modes to intraseasonal and interannual variability of the monsoon are investigated. The CFS has three intraseasonal oscillations with periods around 106, 57 and 30?days with a combined variance of 7%. The 106-day mode has spatial structure and propagation features similar to the northeastward propagating 45-day mode in the observations except for its longer period. The 57-day mode, despite being in the same time scale as of the observations has poor eastward propagation. The 30-day mode is northwestward propagating and is similar to its observational counterpart. The 106-day mode is specific to the model and should not be mistaken for a new scale of variability in observations. The dominant interannual signal is related to El Ni?o-Southern Oscillation (ENSO), and, unlike in the observations, has maximum variance in the eastern equatorial Indian Ocean. Although the Indian Ocean Dipole (IOD) mode was not obtained as a separate mode in the rainfall, the ENSO signal has good correlations with the dipole variability, which, therefore, indicates the dominance of ENSO in the model. The interannual variability is largely determined by the ENSO signal over the regions where it has maximum variance. The interannual variability of the intraseasonal oscillations is smaller in comparison.     

The Variability of the Interannual Oscillations of the Indian Summer Monsoon Rainfall

A new method of analysis namely, Singular Spectrum Analysis (SSA) is applied to the Indian Summer Monsoon (June-September) Rainfall (ISMR) series. The method is efficient in extracting the statistically significant oscillations with periods 2.8 and 2.3 year from the white noise of the ISMR series. The study shows that 2.8 / 2.3 year cycle captures the variability of the ISMR related to Southern Oscillation / Quasi Biennial Oscillation. The temporal structure of these oscillations show that these are in phase in extreme (excess and drought) monsoon conditions as well as in El Nino Southern Oscillation (ENSO) years. Both these oscillations show minimum variability during the period 1920-1940 and there is an increasing trend in the variability of these oscillations in the recent decades. The study enables to obtain pure signal consisting of reconstructed time series using these two Oscillations, from the original white noise series.     

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.     

Contrasting Indian Ocean SST variability with and without ENSO influence: A coupled atmosphere-ocean GCM study

Summary In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO’s influence on the interannual sea-surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSO’s influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3–5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin-wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east–west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.     

A Data-Adaptive Filter of the Tahiti-Darwin Southern Oscillation Index and the Associate Scheme of Filling Data Gaps

The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. In order to reduce the level of noise in the SO index, this paper introduces a fully data-adaptive filter based on singular spectrum analysis. Another interesting aspect of the filter is that it can be used to fill data gaps of the SO index by an iterative process. Eventually, a noiseless long-period data series without any gaps is obtained.     

Quasi-quadrennial and quasi-biennial variability in the equatorial Pacific

Evaluation of competing El Niño/Southern Oscillation (ENSO) theories requires one to identify separate spectral peaks in equatorial wind and sea-surface temperature (SST) time series. To sharpen this identification, we examine the seasonal-to-interannual variability of these fields by the data-adaptive method of multi-channel singular spectrum analysis (M-SSA). M-SSA is applied to the equatorial band (4°N-4°S), using 1950–1990 data from the Comprehensive Ocean and Atmosphere Data Set. Two major interannual oscillations are found in the equatorial SST and surface zonal wind fields, U. The main peak is centered at about 52-months; we refer to it as the quasi-quadrennial (QQ) mode. Quasi-biennial (QB) variability is split between two modes, with periods near 28 months and 24 months. A faster, 15-month oscillation has smaller amplitude. The QQ mode dominates the variance and has the most distinct spectral peak. In time-longitude reconstructions of this mode, the SST has the form of a standing oscillation in the eastern equatorial Pacific, while the U-field is dominated by a standing oscillation pattern in the western Pacific and exhibits also slight eastward propagation in the central and western Pacific. The locations of maximum anomalies in both QB modes are similar to those of the QQ mode. Slight westward migration in SST, across the eastern and central, and eastward propagation of U, across the western and central Pacific, are found. The significant wind anomaly covers a smaller region than for the QQ. The QQ and QB modes together represent the ENSO variability well and interfere constructively during major events. The sharper definition of the QQ spectral peak and its dominance are consistent with the devil's staircase interaction mechanism between the annual cycle and ENSO.     

近百年东亚冬季风的突变性和周期性

该文利用海平面气压场资料,计算了1873～1990年的东亚冬季风强度指数,并用滑动t检验和奇异谱分析方法（SSA）对近百年的东亚冬季风的突变性和周期性进行了研究。研究表明:东亚冬季风强度具有显著的年际及年代际变化。当冬季风强时,中国大部分地区温度降低,蒙古高压升高,阿留申低压加深。当冬季风弱时,天气及环流特点几乎与之相反。东亚冬季风存在QBO、LFO和IDO现象,各振荡分量都具有年代际的差别。     

近百年全球平均地面气温准周期信号及其长期演变特征的分析

应用奇异谱分析(SSA)方法,对全球及南北半球近100多年(1856～1997年)逐月地面气温距平序列的年际变化准周期性进行诊断分析,结果表明,全球平均气温序列中以准5～6年和准4年周期振荡最显著,其次是准两年周期振荡.各种准周期振荡年代际演变特征及其变率的阶段性,不但表现在振幅上,而且其波数亦很明显.上述特征在全球、南北半球都各有明显的差异.奇异交叉谱分析(SCSA)表明,全球平均地面气温的年际振荡与气候系统中其他各子系统所隐含的准周期信号具有各种耦合关系,尤其表现在与Nino区海温或南方涛动指数中的准周期信号的耦合关系上.     

On decadal-scale ocean-atmosphere interactions in the extended ECHAM1/LSG climate simulation

 The last 810 years of a control integration with the ECHAM1/LSG coupled model are used to clarify the nature of the ocean-atmosphere interactions at low frequencies in the North Atlantic and the North Pacific. To a first approximation, the atmosphere acts as a white noise forcing and the ocean responds as a passive integrator. The sea surface temperature (SST) variability primarily results from short time scale fluctuations in surface heat exchanges and Ekman currents, and the former also damp the SST anomalies after they are generated. The thermocline variability is primarily driven by Ekman pumping. Because the heat, momentum, and vorticity fluxes at the sea surface are correlated in space and time, the SST variability is directly linked to that in the ocean interior. The SST is also modulated by the wind-driven geostrophic fluctuations, resulting in persistent correlation with the thermocline changes and a slight low-frequency redness of the SST spectra. The main dynamics are similar in the two oceans, although in the North Pacific the SST variability is more strongly influenced by advection changes and the oceanic time scales are larger. A maximum covariance analysis based on singular value decomposition in lead and lag conditions indicates that some of the main modes of atmospheric variability in the two oceans are sustained by a very weak positive feedback between the atmosphere, SST, and the strength of the subtropical and subpolar gyres. In addition, in the North Atlantic the main surface pressure mode has a small quasi-oscillatory component at 6-year period, and advective resonance occurs for SST around 10-year period, both periods being also singled out by multichannel singular spectrum analysis. The ocean-atmosphere coupling is however much too weak to redden the tropospheric spectra or create anything more than tiny spectral peaks, so that the atmospheric and oceanic variability is dominated in both ocean sectors by the one-way interactions. Received: 2 April 1999 / Accepted: 14 October 1999     

Annual and seasonal variability of precipitation in Vojvodina,Serbia

Annual and seasonal variability of precipitation observed at 92 stations in Vojvodina (Serbia) were analyzed during the period 1946–2006. The rainfall series were examined by means of the empirical orthogonal functions (EOF). The first set of singular vectors explains from 68.8 % (in summer) to 81.8 % (in winter) of the total variance. The temporal variability of the time series associated with the main EOF configurations (the principal components, PCs) was examined using the Mann–Kendall test and the spectral analysis. The time series of PC1 revealed decreasing trend in the winter and spring precipitation and increasing trend in the autumn, summer, and annual precipitation. The relationships between the first PC and circulation patterns, such as the North Atlantic Oscillation (NAO), the East Atlantic (EA) pattern, and East Atlantic/West Russia pattern, were also investigated. The PC1, displaying temporal behavior of the first mode, demonstrated evident correspondence with the NAO index in analysis of the annual, winter, and autumn precipitation. Power spectra of the PC1 show statistically significant oscillations of about 3.3 years for the spring precipitation and about 8 and 15 years for the winter precipitation. Comparisons with spectral analysis of authors for some regions in Europe, most of them in the Mediterranean domain, show that similar periodicities are detected.     

Unprecedented low twentieth century winter sea ice extent in the Western Nordic Seas since A.D. 1200

We reconstructed decadal to centennial variability of maximum sea ice extent in the Western Nordic Seas for A.D. 1200–1997 using a combination of a regional tree-ring chronology from the timberline area in Fennoscandia and δ¹⁸O from the Lomonosovfonna ice core in Svalbard. The reconstruction successfully explained 59% of the variance in sea ice extent based on the calibration period 1864–1997. The significance of the reconstruction statistics (reduction of error, coefficient of efficiency) is computed for the first time against a realistic noise background. The twentieth century sustained the lowest sea ice extent values since A.D. 1200: low sea ice extent also occurred before (mid-seventeenth and mid-eighteenth centuries, early fifteenth and late thirteenth centuries), but these periods were in no case as persistent as in the twentieth century. Largest sea ice extent values occurred from the seventeenth to the nineteenth centuries, during the Little Ice Age (LIA), with relatively smaller sea ice-covered area during the sixteenth century. Moderate sea ice extent occurred during thirteenth–fifteenth centuries. Reconstructed sea ice extent variability is dominated by decadal oscillations, frequently associated with decadal components of the North Atlantic Oscillation/Arctic Oscillation (NAO/AO), and multi-decadal lower frequency oscillations operating at ~50–120 year. Sea ice extent and NAO showed a non-stationary relationship during the observational period. The present low sea ice extent is unique over the last 800 years, and results from a decline started in late-nineteenth century after the LIA.     

近百年全球平均气温年际变率中的QBO长期变化特征

应用奇异谱分析(SSA)方法和奇异交叉谱分析(SCSA)方法，对全球及南北半球近100多年(1856～1997年)逐月地面气温距平序列中的准两年周期振荡(QBO)的长期演变特征进行诊断分析。结果表明:全球平均气温序列蕴含显著的QBO分量，它们与全球气候系统中其他各个子系统所隐含的QBO信号具有各种耦合对应关系，尤其突出地表现在Nino区海温和以SLP序列为代表的全球大气环流系统中QBO信号的耦合对应关系上。而平均气温的QBO的年代际特征及其变率的阶段性，不但表现在振幅上，而且其位相亦很明显。上述特征在全球、两半球具有明显的差异。     

Long-term precipitation variability in the Ionian Islands, Greece (Central Mediterranean): climatic signal analysis and future projections

The present study examines the variability of the precipitation regime across the Ionian Islands complex, Greece (Central Mediterranean), for a period spanning more than one century. Significant negative long-term linear trends in the annual precipitation totals are observed, more pronounced in the southern parts of the studied area, while a climatic discontinuity possibly occurred during the 1970s, manifested first in the southern Ionian. Statistically significant nonlinear trends and subdecadal intermittent oscillations were detected using Monte Carlo singular spectral analysis. The correlation of the winter precipitation variability at Ionian complex with the North Atlantic Oscillation anomalies was also investigated and extended in the frequency domain. Finally, future projections were performed using an ensemble of Regional Climatic Models. Model simulations suggested a decrease of the order of ～20% or more in the mean annual precipitation of the area by the end of the century.     

An objective analysis of the observed spatial structure of the tropical Indian Ocean SST variability

The observed interannual Indian Ocean sea surface temperature (SST) variability from 1950 to 2008 is analyzed in respect to the spatial structure of the variability. The analysis is based on an objective comparison of the leading empirical orthogonal function modes against the stochastic null hypothesis of spatial red noise (isotropic diffusion). Starting from this red noise assumption, the analysis searches for those structures that are most distinct from the red noise hypothesis. This objective approach will put previously well and less known modes of variability into the context of the multivariate SST variability. The Indian Ocean SST variability is marked by relatively weak SST variability, which is strongly dominated by a basin wide monopole pattern that is caused by different processes. The leading modes of variability are the El Nino Southern Oscillation (ENSO) variability and the warming trend, which both project onto the basin wide monopole structure. Other more characteristic spatial patterns of internal variability are much less dominant in the tropical Indian Ocean, which is quite different from all other ocean basin, where characteristic teleconnection patterns exist. The remaining, ENSO independent, detrended variability is dominated by multi-pole patterns from the southern Indian Ocean reaching into the tropical Indian Ocean, which are probably primarily caused by extra-tropical atmospheric forcings. The large scale tropical Indian Ocean internal variability itself has no dominant structure. The currently often used dipole mode index (DMI) does not appear to present a dominant teleconnection pattern of the Indian Ocean internal SST variability. In the context of the objective analysis presented here, the DMI partly reflects the ENSO variability and is also a representation of the multi-dimensional, chaotic spatial red noise (isotropic diffusion) process. As such the DMI cannot be interpreted as a coherent teleconnection between the two poles.     

ERA-40-aided assessment of the atmospheric influence on satellite retrieval of Adriatic Sea surface temperature

The aim of this work is assessment of regional atmospheric influence on satellite derivation of Adriatic Sea surface temperature (SST). To this end the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-40 reanalysis dataset has been employed to provide the temperature and humidity profiles and surface data, while the RTTOV 8.7 radiative transfer model was used to calculate the top-of-atmosphere brightness temperatures for the advanced very high-resolution radiometer (AVHRR) channels. Ten ERA-40 grid points over the Adriatic Sea were used in the analysis, providing 29,590, 00 UTC and 12 UTC, clear-sky profiles. Climatological analysis of the ERA-40 profiles demonstrated distinct seasonal variability over the Adriatic Sea. Seasonality noted in the temperature and specific humidity profiles also evinced in the atmospheric transmittance, thermal channels temperature deficit, and derived γ and ρ parameters. A multivariate analysis was applied to relate the simulated top-of-atmosphere brightness temperatures to the Adriatic SSTs in order to generate exploratory sets of SST retrieval coefficients. All derived coefficient sets exhibited smaller noise amplification factor than the global counterpart. A test comparison of satellite-derived SST with an 11-month in situ SST series showed than locally derived coefficients provide smaller scatter (improved precision), and skin-centred bias that requires additional adjustment. Almost identical SST residual and error metric was obtained with seasonally adjusted classical split-window coefficients and with coefficients explicitly accommodating water-vapor dependence. Comparison with data reinforces the notion that the atmosphere over the Adriatic may exhibit variability that cannot be fully accommodated by globally adjusted correction.     

Interannual and interdecadal oscillation patterns in sea level

Relative sea-level height (RSLH) data at 213 tide-gauge stations have been analyzed on a monthly and an annual basis to study interannual and interdecadal oscillations, respectively. The main tools of the study are singular spectrum analysis (SSA) and multi-channel SSA (M-SSA). Very-low-frequency variability of RSLH was filtered by SSA to estimate the linear trend at each station. Global sea-level rise, after postglacial rebound corrections, has been found to equal 1.62±0.38 mm/y, by averaging over 175 stations which have a trend consistent with the neighboring ones. We have identified two dominant time scales of El Niño-Southern Oscillation (ENSO) variability, quasi-biennial and low-frequency, in the RSLH data at almost all stations. However, the amplitudes of both ENSO signals are higher in the equatorial Pacific and along the west coast of North America. RSLH data were interpolated along ocean coasts by latitudinal intervals of 5 or 10 degrees, depending on station density. Interannual variability was then examined by M-SSA in five regions: eastern Pacific (25°S–55°N at 10° resolution), western Pacific (35°S–45°N at 10°), equatorial Pacific (123°E–169°W, 6 stations), eastern Atlantic (30°S, 0°, and 30°N–70°N at 5°) and western Atlantic (50°S–50°N at 10°). Throughout the Pacific, we have found three dominant spatio-temporal oscillatory patterns, associated with time scales of ENSO variability; their periods are 2, 2.5–3 and 4–6 y. In the eastern Pacific, the biennial mode and the 6-y low-frequency mode propagate poleward. There is a southward propagation of low-frequency modes in the western Pacific RSLH, between 35°N and 5°S, but no clear propagation in the latitudes further south. However, equatorward propagation of the biennial signal is very clear in the Southern Hemisphere. In the equatorial Pacific, both the quasi-quadrennial and quasi-biennial modes at 10°N propagate westward. Strong and weak El Niño years are evident in the sea-level time series reconstructed from the quasi-biennial and low-frequency modes. Interannual variability with periods of 3 and 4–8 y is detected in the Atlantic RSLH data. In the eastern Atlantic region, we have found slow propagation of both modes northward and southward, away from 40–45°N. Interdecadal oscillations were studied using 81 stations with sufficiently long and continuous records. Most of these have variability at 9–13 and some at 18 y. Two significant eigenmode pairs, corresponding to periods of 11.6 and 12.8 y, are found in the eastern and western Atlantic ocean at latitudes 40°N–70°N and 10°N–50°N, respectively.