Evolution and variability of the East Asian summer monsoon during the Pliocene: Evidence from clay mineral records of the South China Sea

The Late Pliocene is thought to be characterized by the simultaneous intensification of both the East Asian winter monsoon (EAWM) and East Asian summer monsoon (EASM). However, the evolution of the EASM during the Pliocene remains still controversial and only little is known about the dynamics of the EASM during the Pliocene on orbital time scales. Here we use clay mineral assemblages in sediments from Ocean Drilling Program (ODP) Site 1143 in the southern South China Sea (SCS) to obtain proxy records of past changes in the EASM climate during the Pliocene. Provenance analysis suggests that illite, chlorite and kaolinite originated mainly from the Mekong River drainage area. Smectite was derived mainly from the Indonesian islands. The kaolinite/illite ratio and the chemical index of alteration (CIA) of siliciclastic sediments allowed us to reconstruct the history of chemical weathering and physical erosion of the Mekong River drainage area and thus, the evolution of,the EASM during the Pliocene. Our clay minerals proxy data suggests a stronger EASM during the Early Pliocene than during the Late Pliocene. We propose that the long-term evolution of the EASM has been driven by global cooling rather than the uplift of the Tibetan Plateau. Spectral analysis of kaolinite/ illite ratio displays a set of strong periodicities at 100 ka, 30 ka, 28 ka, 25 ka, and 22 ka. with no clear obliquityrelated signal. Our study suggests that the Pliocene EASM intensity on orbital time scales is not only controlled by the Northern Hemisphere summer insolation, but also strongly influenced by equatorial Pacific ENSO-like ocean atmosphere dynamics. (C) 2010 Elsevier B.V. All rights reserved.

The variability of eddy kinetic energy in the South China Sea deduced from satellite altimeter data

We used fifteen years (1993-2007) of altimetric data, combined from different missions (ERS-1/2, TOPEX/Poseidon, Jason-1, and Envisat), to analyze the variability of the eddy kinetic energy (EKE) in the South China Sea (SCS). We found that the EKE ranged from 64 cm(2)/s(2) to 1 390 cm(2)/s(2) with a mean value of 314 cm(2)/s(2). The highest EKE center was observed to the east of Vietnam (with a mean value of 509 cm(2)/s(2)) and the second highest EKE region was located to the southwest of Taiwan Island (with a mean value of 319 cm(2)/s(2)). We also found that the EKE structure is the consequence of the superposition of different variability components. First, interannual variability is important in the SCS. Spectral analysis of the EKE interannual signal (IA-EKE) shows that the main periodicities of the IA-EKE to the east of Vietnam, to the southwest of Taiwan Island, and in the SCS are 3.75, 1.87, and 3.75 years, respectively. It is to the south of Taiwan Island that the IA-EKE signal has the most obvious impact on EKE variability. In addition, the IA-EKE exhibit different trends in different regions. An obvious positive trend is observed along the east coast of Vietnam, while a negative trend is found to the southwest of Taiwan Island and in the east basin of Vietnam. Correlation analysis shows that the IA-EKE has an obvious negative correlation with the SSTA in Nio3 (5A degrees S-5A degrees N, 90A degrees W-150A degrees W). El Nio-Southern Oscillation (ENSO) affects the IA-EKE variability in the SCS through an atmospheric bridge-wind stress curl over the SCS. Second, the seasonal cycle is the most obvious timescale affecting EKE variability. The locations of the most remarkable EKE seasonal variabilities in the SCS are to the east of Vietnam, to the southwest of Taiwan, and to the west of Philippines. To the east of Vietnam, the seasonal cycle is the dominant mechanism controlling EKE variability, which is attributed primarily to the annual cycle there of wind stress curl. In this area, the maximum EKE is observed in autumn. To the southwest of Taiwan Island, the EKE is enlarged by the stronger SCS circulation, which is caused by the intrusion branch from the Kuroshio in winter. Finally, intra-annual and mesoscale variability, although less important than the former, cannot be neglected. The most obvious intra-annual and mesoscale variability, which may be the result of baroclinic instability of the background flow, are observed to the southwest of Taiwan Island. Sporadic events can have an important effect on EKE variability.

Digital signal processing and artificial intelligence for the automated classification of food allergy

As a by-product of the ‘information revolution’ which is currently unfolding, lifetimes of man (and indeed computer) hours are being allocated for the automated and intelligent interpretation of data. This is particularly true in medical and clinical settings, where research into machine-assisted diagnosis of physiological conditions gains momentum daily. Of the conditions which have been addressed, however, automated classification of allergy has not been investigated, even though the numbers of allergic persons are rising, and undiagnosed allergies are most likely to elicit fatal consequences. On the basis of the observations of allergists who conduct oral food challenges (OFCs), activity-based analyses of allergy tests were performed. Algorithms were investigated and validated by a pilot study which verified that accelerometer-based inquiry of human movements is particularly well-suited for objective appraisal of activity. However, when these analyses were applied to OFCs, accelerometer-based investigations were found to provide very poor separation between allergic and non-allergic persons, and it was concluded that the avenues explored in this thesis are inadequate for the classification of allergy. Heart rate variability (HRV) analysis is known to provide very significant diagnostic information for many conditions. Owing to this, electrocardiograms (ECGs) were recorded during OFCs for the purpose of assessing the effect that allergy induces on HRV features. It was found that with appropriate analysis, excellent separation between allergic and nonallergic subjects can be obtained. These results were, however, obtained with manual QRS annotations, and these are not a viable methodology for real-time diagnostic applications. Even so, this was the first work which has categorically correlated changes in HRV features to the onset of allergic events, and manual annotations yield undeniable affirmation of this. Fostered by the successful results which were obtained with manual classifications, automatic QRS detection algorithms were investigated to facilitate the fully automated classification of allergy. The results which were obtained by this process are very promising. Most importantly, the work that is presented in this thesis did not obtain any false positive classifications. This is a most desirable result for OFC classification, as it allows complete confidence to be attributed to classifications of allergy. Furthermore, these results could be particularly advantageous in clinical settings, as machine-based classification can detect the onset of allergy which can allow for early termination of OFCs. Consequently, machine-based monitoring of OFCs has in this work been shown to possess the capacity to significantly and safely advance the current state of clinical art of allergy diagnosis

Temporal variations of IEEE 802.11b signal strengths in an in-building environment

Recent popularity of the IEEE 802.11b Wireless Local Area Networks (WLANs) in a host of current-day applications has instigated a suite of research challenges. The 802.11b WLANs are highly reliable and wide spread. In this work, we study the temporal characteristics of RSSI in the real-working environment by conducting a controlled set of experiments. Our results indicate that a significant variability in the RSSI can occur over time. Some of this variability in the RSSI may be due to systematic causes while the other component can be expressed as stochastic noise. We present an analysis of both these aspects of RSSI. We treat the moving average of the RSSI as the systematic causes and the noise as the stochastic causes. We give a reasonable estimate for the moving average to compute the noise accurately. We attribute the changes in the environment such as the movement of people and the noise associated with the NIC circuitry and the network access point as causes for this variability. We find that the results of our analysis are of primary importance to active research areas such as location determination of users in a WLAN. The techniques used in some of the RF-based WLAN location determination systems, exploit the characteristics of the RSSI presented in this work to infer the location of a wireless client in a WLAN. Thus our results form the building blocks for other users of the exact characteristics of the RSSI.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

YSOVAR: Mid-infrared Variability in the Star-forming Region Lynds 1688

The emission from young stellar objects (YSOs) in the mid-infrared (mid-IR) is dominated by the inner rim of their circumstellar disks. We present IR data from the Young Stellar Object VARiability (YSOVAR) survey of ~800 objects in the direction of the Lynds 1688 (L1688) star-forming region over four visibility windows spanning 1.6 yr using the Spitzer Space Telescope in its warm mission phase. Among all light curves, 57 sources are cluster members identified based on their spectral energy distribution and X-ray emission. Almost all cluster members show significant variability. The amplitude of the variability is larger in more embedded YSOs. Ten out of 57 cluster members have periodic variations in the light curves with periods typically between three and seven days, but even for those sources, significant variability in addition to the periodic signal can be seen. No period is stable over 1.6 yr. Nonperiodic light curves often still show a preferred timescale of variability that is longer for more embedded sources. About half of all sources exhibit redder colors in a fainter state. This is compatible with time-variable absorption toward the YSO. The other half becomes bluer when fainter. These colors can only be explained with significant changes in the structure of the inner disk. No relation between mid-IR variability and stellar effective temperature or X-ray spectrum is found.

YSOVAR: Mid-infrared Variability in NGC 1333

As part of the Young Stellar Object VARiability (YSOVAR) program, wemonitored NGC 1333 for ∼35 days at 3.6 and 4.5 μm using theSpitzer Space Telescope. We report here on the mid-infrared variabilityof the point sources in the ∼10‧ × ∼20‧ areacentered on 03:29:06, +31:19:30 (J2000). Out of 701 light curves ineither channel, we find 78 variables over the YSOVAR campaign. Abouthalf of the members are variable. The variable fraction for the mostembedded spectral energy distributions (SEDs) (Class I, flat) is higherthan that for less embedded SEDs (Class II), which is in turn higherthan the star-like SEDs (Class III). A few objects have amplitudes(10–90th percentile brightness) in [3.6] or [4.5] > 0.2 mag; amore typical amplitude is 0.1–0.15 mag. The largest color changeis >0.2 mag. There are 24 periodic objects, with 40% of them beingflat SED class. This may mean that the periodic signal is primarily fromthe disk, not the photosphere, in those cases. We find 9 variableslikely to be “dippers,” where texture in the disk occultsthe central star, and 11 likely to be “bursters,” whereaccretion instabilities create brightness bursts. There are 39 objectsthat have significant trends in [3.6]–[4.5] color over thecampaign, about evenly divided between redder-when-fainter (consistentwith extinction variations) and bluer-when-fainter. About a third of the17 Class 0 and/or jet-driving sources from the literature are variableover the YSOVAR campaign, and a larger fraction (∼half) are variablebetween the YSOVAR campaign and the cryogenic-era Spitzer observations(6–7 years), perhaps because it takes time for the envelope torespond to changes in the central source. The NGC 1333 brown dwarfs donot stand out from the stellar light curves in any way except there is amuch larger fraction of periodic objects (∼60% of variable browndwarfs are periodic, compared to ∼30% of the variables overall).

Isolating the signal of ocean global warming

Identifying the signature of global warming in the world's oceans is challenging because low frequency circulation changes can dominate local temperature changes. The IPCC fourth assessment reported an average ocean heating rate of 0.21 ± 0.04 Wm−2 over the period 1961–2003, with considerable spatial, interannual and inter-decadal variability. We present a new analysis of millions of ocean temperature profiles designed to filter out local dynamical changes to give a more consistent view of the underlying warming. Time series of temperature anomaly for all waters warmer than 14°C show large reductions in interannual to inter-decadal variability and a more spatially uniform upper ocean warming trend (0.12 Wm−2 on average) than previous results. This new measure of ocean warming is also more robust to some sources of error in the ocean observing system. Our new analysis provides a useful addition for evaluation of coupled climate models, to the traditional fixed depth analyses.

Long-term change, interannual and intra-seasonal variability in climate and glacier mass balance in the Central Greater Caucasus, Russia

Long-term trends, interannual and intra-seasonal variability in the mass-balance record from Djankuat glacier, central Greater Caucasus, Russia, are related to local climate change, synoptic and large-scale anomalies in atmospheric circulation. A clear warming signal emerged in the central Greater Caucasus in the early 1990s, leading to a strong increase in ablation. In the absence of a compensating change in winter accumulation, the net mass balance of Djankuat has declined. The highest value of seasonal ablation on record was registered in the summer of 2000. At the beginning of the 21st century these trends reversed. Ablation was below average even in the summer of 2003, which was unusually warm in western Europe. Precipitation and winter accumulation were high, allowing for a partial recovery of net mass balance. The interannual variability in the components of mass balance is weakly related to the North Atlantic Oscillation (NAO) and the Scandinavian teleconnection patterns, but there is a clear link with the large-scale circulation anomalies represented by the Rossby pattern. Five synoptic categories have been identified for the ablation season of 2005, revealing a strong separation between components of radiation budget, air temperature and daily melt. Air temperature is the main control over melt. The highest values of daily ablation are related to the strongly positive NAO which forces high net radiation, and to the warm and moist advection from the Black Sea.

Stratospheric temperature trends: impact of ozone variability and the QBO

In most climate simulations used by the Intergovernmental Panel on Climate Change 2007 fourth assessment report, stratospheric processes are only poorly represented. For example, climatological or simple specifications of time-varying ozone concentrations are imposed and the quasi-biennial oscillation (QBO) of equatorial stratospheric zonal wind is absent. Here we investigate the impact of an improved stratospheric representation using two sets of perturbed simulations with the Hadley Centre coupled ocean atmosphere model HadGEM1 with natural and anthropogenic forcings for the 1979–2003 period. In the first set of simulations, the usual zonal mean ozone climatology with superimposed trends is replaced with a time series of observed zonal mean ozone distributions that includes interannual variability associated with the solar cycle, QBO and volcanic eruptions. In addition to this, the second set of perturbed simulations includes a scheme in which the stratospheric zonal wind in the tropics is relaxed to appropriate zonal mean values obtained from the ERA-40 re-analysis, thus forcing a QBO. Both of these changes are applied strictly to the stratosphere only. The improved ozone field results in an improved simulation of the stepwise temperature transitions observed in the lower stratosphere in the aftermath of the two major recent volcanic eruptions. The contribution of the solar cycle signal in the ozone field to this improved representation of the stepwise cooling is discussed. The improved ozone field and also the QBO result in an improved simulation of observed trends, both globally and at tropical latitudes. The Eulerian upwelling in the lower stratosphere in the equatorial region is enhanced by the improved ozone field and is affected by the QBO relaxation, yet neither induces a significant change in the upwelling trend.

Decadal to multidecadal variability and the climate change background

Three prominent quasi-global patterns of variability and change are observed using the Met Office's sea surface temperature (SST) analysis and almost independent night marine air temperature analysis. The first is a global warming signal that is very highly correlated with global mean SST. The second is a decadal to multidecadal fluctuation with some geographical similarity to the El Niño–Southern Oscillation (ENSO). It is associated with the Pacific Decadal Oscillation (PDO), and its Pacific-wide manifestation has been termed the Interdecadal Pacific Oscillation (IPO). We present model investigations of the relationship between the IPO and ENSO. The third mode is an interhemispheric variation on multidecadal timescales which, in view of climate model experiments, is likely to be at least partly due to natural variations in the thermohaline circulation. Observed climatic impacts of this mode also appear in model simulations. Smaller-scale, regional atmospheric phenomena also affect climate on decadal to interdecadal timescales. We concentrate on one such mode, the winter North Atlantic Oscillation (NAO). This shows strong decadal to interdecadal variability and a correspondingly strong influence on surface climate variability which is largely additional to the effects of recent regional anthropogenic climate change. The winter NAO is likely influenced by both SST forcing and stratospheric variability. A full understanding of decadal changes in the NAO and European winter climate may require a detailed representation of the stratosphere that is hitherto missing in the major climate models used to study climate change.

Exploring the interplay between natural decadal variability and anthropogenic climate change in summer rainfall over China. Part I: Observational evidence

Summer rainfall over China has experienced substantial variability on longer time scales during the last century, and the question remains whether this is due to natural, internal variability or is part of the emerging signal of anthropogenic climate change. Using the best available observations over China, the decadal variability and recent trends in summer rainfall are investigated with the emphasis on changes in the seasonal evolution and on the temporal characteristics of daily rainfall. The possible relationships with global warming are reassessed. Substantial decadal variability in summer rainfall has been confirmed during the period 1958–2008; this is not unique to this period but is also seen in the earlier decades of the twentieth century. Two dominant patterns of decadal variability have been identified that contribute substantially to the recent trend of southern flooding and northern drought. Natural decadal variability appears to dominate in general but in the cases of rainfall intensity and the frequency of rainfall days, particularly light rain days, then the dominant EOFs have a rather different character, being of one sign over most of China, and having principal components (PCs) that appear more trendlike. The increasing intensity of rainfall throughout China and the decrease in light rainfall days, particularly in the north, could at least partially be of anthropogenic origin, both global and regional, linked to increased greenhouse gases and increased aerosols.

Understanding advances in the simulation of intraseasonal variability in the ECMWF model. Part I: the representation of the MJO

As a major mode of intraseasonal variability, which interacts with weather and climate systems on a near-global scale, the Madden – Julian Oscillation (MJO) is a crucial source of predictability for numerical weather prediction (NWP) models. Despite its global significance and comprehensive investigation, improvements in the representation of the MJO in an NWP context remain elusive. However, recent modifications to the model physics in the ECMWF model led to advances in the representation of atmospheric variability and the unprecedented propagation of the MJO signal through the entire integration period. In light of these recent advances, a set of hindcast experiments have been designed to assess the sensitivity of MJO simulation to the formulation of convection. Through the application of established MJO diagnostics, it is shown that the improvements in the representation of the MJO can be directly attributed to the modified convective parametrization. Furthermore, the improvements are attributed to the move from a moisture-convergent- to a relative-humidity-dependent formulation for organized deep entrainment. It is concluded that, in order to understand the physical mechanisms through which a relative-humidity-dependent formulation for entrainment led to an improved simulation of the MJO, a more process-based approach should be taken. T he application of process-based diagnostics t o t he hindcast experiments presented here will be the focus of Part II of this study.

Analysis of the variability of auditory brainstem response components through linear regression

(ABR) is of fundamental importance to the investiga- tion of the auditory system behavior, though its in- terpretation has a subjective nature because of the manual process employed in its study and the clinical experience required for its analysis. When analyzing the ABR, clinicians are often interested in the identi- fication of ABR signal components referred to as Jewett waves. In particular, the detection and study of the time when these waves occur (i.e., the wave la- tency) is a practical tool for the diagnosis of disorders affecting the auditory system. In this context, the aim of this research is to compare ABR manual/visual analysis provided by different examiners. Methods: The ABR data were collected from 10 normal-hearing subjects (5 men and 5 women, from 20 to 52 years). A total of 160 data samples were analyzed and a pair- wise comparison between four distinct examiners was executed. We carried out a statistical study aiming to identify significant differences between assessments provided by the examiners. For this, we used Linear Regression in conjunction with Bootstrap, as a me- thod for evaluating the relation between the responses given by the examiners. Results: The analysis sug- gests agreement among examiners however reveals differences between assessments of the variability of the waves. We quantified the magnitude of the ob- tained wave latency differences and 18% of the inves- tigated waves presented substantial differences (large and moderate) and of these 3.79% were considered not acceptable for the clinical practice. Conclusions: Our results characterize the variability of the manual analysis of ABR data and the necessity of establishing unified standards and protocols for the analysis of these data. These results may also contribute to the validation and development of automatic systems that are employed in the early diagnosis of hearing loss.