Snow variability in the Swiss Alps 1864-2009

We present a climate analysis of nine unique Swiss Alpine new snow series that have been newly digitized. The stations cover different altitudes (450–1860 m asl) and all time series cover more than 100 years (one from 1864 to 2009). In addition, data from 71 stations for the last 50–80 years for new snow and snow depth are analysed to get a more complete picture of the Swiss Alpine snow variability. Important snow climate indicators such as new snow sums (NSS), maximum new snow (MAXNS) and days with snowfall (DWSF) are calculated and variability and trends analysed. Series of days with snow pack (DWSP) ≥ 1 cm are reconstructed with useful quality for six stations using the daily new snow, local temperature and precipitation data. Our results reveal large decadal variability with phases of low and high values for NSS, DWSF and DWSP. For most stations NSS, DWSF and DWSP show the lowest values recorded and unprecedented negative trends in the late 1980s and 1990s. For MAXNS, however, no clear trends and smaller decadal variability are found but very large MAXNS values (>60 cm) are missing since the year 2000. The fraction of NSS and DWSP in different seasons (autumn, winter and spring) has changed only slightly over the ∼150 year record. Some decreases most likely attributable to temperature changes in the last 50 years are found for spring, especially for NSS at low stations. Both the NSS and DWSP snow indicators show a trend reversal in most recent years (since 2000), especially at low and medium altitudes. This is consistent with the recent ‘plateauing’ (i.e. slight relative decrease) of mean winter temperature in Switzerland and illustrates how important decadal variability is in understanding the trends in key snow indicators.

Intelligence is related to specific processes in visual change detection: Fixed-links modeling of hit rate and reaction time

By means of fixed-links modeling, the present study identified different processes of visual short-term memory (VSTM) functioning and investigated how these processes are related to intelligence. We conducted an experiment where the participants were presented with a color change detection task. Task complexity was manipulated through varying the number of presented stimuli (set size). We collected hit rate and reaction time (RT) as indicators for the amount of information retained in VSTM and speed of VSTM scanning, respectively. Due to the impurity of these measures, however, the variability in hit rate and RT was assumed to consist not only of genuine variance due to individual differences in VSTM retention and VSTM scanning but also of other, non-experimental portions of variance. Therefore, we identified two qualitatively different types of components for both hit rate and RT: (1) non-experimental components representing processes that remained constant irrespective of set size and (2) experimental components reflecting processes that increased as a function of set size. For RT, intelligence was negatively associated with the non-experimental components, but was unrelated to the experimental components assumed to represent variability in VSTM scanning speed. This finding indicates that individual differences in basic processing speed, rather than in speed of VSTM scanning, differentiates between high- and low-intelligent individuals. For hit rate, the experimental component constituting individual differences in VSTM retention was positively related to intelligence. The non-experimental components of hit rate, representing variability in basal processes, however, were not associated with intelligence. By decomposing VSTM functioning into non-experimental and experimental components, significant associations with intelligence were revealed that otherwise might have been obscured.

Phenotypic variability in familial combined pituitary hormone deficiency caused by a PROP1 gene mutation resulting in the substitution of Arg-->Cys at codon 120 (R120C).

As pituitary function depends on the integrity of the hypothalamic-pituitary axis, any defect in the development and organogenesis of this gland may account for a form of combined pituitary hormone deficiency (CPHD). A mutation in a novel, tissue-specific, paired-like homeodomain transcription factor, termed Prophet of Pit-1 (PROP1), has been identified as causing the Ames dwarf (df) mouse phenotype, and thereafter, different PROP1 gene alterations have been found in humans with CPHD. We report on the follow-up of two consanguineous families (n = 12), with five subjects affected with CPHD (three males and two females) caused by the same nucleotide C to T transition, resulting in the substitution of Arg-->Cys in PROP1 at codon 120. Importantly, there is a variability of phenotype, even among patients with the same mutation. The age at diagnosis was dependent on the severity of symptoms, ranging from 9 months to 8 yr. Although in one patient TSH deficiency was the first symptom of the disorder, all patients became symptomatic by exhibiting severe growth retardation and failure to thrive, which was mainly caused by GH deficiency (n = 4). The secretion of the pituitary-derived hormones (GH, PRL, TSH, LH, and FSH) declined gradually with age, following a different pattern in each individual; therefore, the deficiencies developed over a variable period of time. All of the subjects entered puberty spontaneously, and the two females also experienced menarche and periods before a replacement therapy was necessary.

Variability between laboratories performing coagulation tests with identical platforms: a nationwide evaluation study.

BACKGROUND While the assessment of analytical precision within medical laboratories has received much attention in scientific enquiry, the degree of as well as the sources causing variation between them remains incompletely understood. In this study, we quantified the variance components when performing coagulation tests with identical analytical platforms in different laboratories and computed intraclass correlations coefficients (ICC) for each coagulation test. METHODS Data from eight laboratories measuring fibrinogen twice in twenty healthy subjects with one out of 3 different platforms and single measurements of prothrombin time (PT), and coagulation factors II, V, VII, VIII, IX, X, XI and XIII were analysed. By platform, the variance components of (i) the subjects, (ii) the laboratory and the technician and (iii) the total variance were obtained for fibrinogen as well as (i) and (iii) for the remaining factors using ANOVA. RESULTS The variability for fibrinogen measurements within a laboratory ranged from 0.02 to 0.04, the variability between laboratories ranged from 0.006 to 0.097. The ICC for fibrinogen ranged from 0.37 to 0.66 and from 0.19 to 0.80 for PT between the platforms. For the remaining factors the ICC's ranged from 0.04 (FII) to 0.93 (FVIII). CONCLUSIONS Variance components that could be attributed to technicians or laboratory procedures were substantial, led to disappointingly low intraclass correlation coefficients for several factors and were pronounced for some of the platforms. Our findings call for sustained efforts to raise the level of standardization of structures and procedures involved in the quantification of coagulation factors.

Atmospheric CO₂ response to volcanic eruptions: The role of ENSO, season, and variability

Tropical explosive volcanism is one of the most important natural factors that significantly impact the climate system and the carbon cycle on annual to multi-decadal time scales. The three largest explosive eruptions in the last 50�years�Agung, El Chichón, and Pinatubo�occurred in spring/summer in conjunction with El Niño events and left distinct negative signals in the observational temperature and CO2 records. However, confounding factors such as seasonal variability and El Niño-Southern Oscillation (ENSO) may obscure the forcing-response relationship. We determine for the first time the extent to which initial conditions, i.e., season and phase of the ENSO, and internal variability influence the coupled climate and carbon cycle response to volcanic forcing and how this affects estimates of the terrestrial and oceanic carbon sinks. Ensemble simulations with the Earth System Model (Climate System Model 1.4-carbon) predict that the atmospheric CO2 response is �60 larger when a volcanic eruption occurs during El Niño and in winter than during La Niña conditions. Our simulations suggest that the Pinatubo eruption contributed 11�±�6 to the 25�Pg terrestrial carbon sink inferred over the decade 1990�1999 and �2�±�1 to the 22�Pg oceanic carbon sink. In contrast to recent claims, trends in the airborne fraction of anthropogenic carbon cannot be detected when accounting for the decadal-scale influence of explosive volcanism and related uncertainties. Our results highlight the importance of considering the role of natural variability in the carbon cycle for interpretation of observations and for data-model intercomparison.

Decadal-scale variability in hazardous winds in northern Switzerland since end of the 19th century

The decadal-scale variability in winter hazardous winds in northern Switzerland from 1871 to present is investigated in the Twentieth Century Reanalysis (20CR). Independent wind speed measurements taken at Zurich climate station show that the interannual and decadal variability in hazardous winds in northern Switzerland is realistically represented in the 20CR. Both time series exhibit pronounced decadal-scale variability with periods between approximately 36 and 47 years. At these periodicities, the hazardous wind variability in northern Switzerland is positively correlated with the variability in the North Atlantic Oscillation, however the strength and statistical significance of their co-variability varies over time.

Topographic Control of Regional Accumulation Rate Variability at South Pole and Implications for Ice-Core Interpretation

Snow-accumulation rates are known to be sensitive to local changes in ice-sheet surface slope because of the effect of katabatic winds. These topographic effects can be preserved in ice cores that are collected at non-ice-divide locations. The trajectory of an ice-core site at South Pole is reconstructed using measurements of ice-sheet motion to show that snow was probably deposited at places of different surface slope during the past 1000 years. Recent accumulation rates, derived from shallow firn cores, vary along this trajectory according to surface topography, so that on a relatively steep flank mean annual accumulation is similar to 18% smaller than on a nearby topographic depression. These modern accumulation rates are used to reinterpret the cause of accumulation rate variability with time in the long ice-core record as an ice-dynamics effect and not a climate-change signal. The results highlight the importance of conducting ancillary ice-dynamics measurements as part of ice-coring programs so that topographic effects can be deconvolved from potential climate signals.

A High-Resolution Record of Atmospheric Dust Composition and Variability Since Ad 1650 from a Mount Everest Ice Core

A Mount Everest ice core analyzed at high resolution for major and trace elements (Sr, Cs, Ba, La, Ce, Pr, Nd, Sm, Eu, Tb, Dy, Ho, Er, Tm, Yb, Lu, Bi, U, Tl, Al, S, Ca, Ti, V, Cr, Mn, Fe, Co) and spanning the period A. D. 1650- 2002 is used to investigate the sources of and variations in atmospheric dust through time. The chemical composition of dust varies seasonally, and peak dust concentrations occur during the winter-spring months. Significant correlations between the Everest dust record and dust observations at stations suggest that the Everest record is representative of regional variations in atmospheric dust loading. Back-trajectory analysis in addition to a significant correlation of Everest dust concentrations and the Total Ozone Mapping Spectrometer (TOMS) aerosol index indicates that the dominant winter sources of dust are the Arabian Peninsula, Thar Desert, and northern Sahara. Factors that contribute to dust generation at the surface include soil moisture and temperature, and the long-range transport of dust aerosols appears to be sensitive to the strength of 500-mb zonal winds. There are periods of high dust concentration throughout the 350-yr Mount Everest dust record; however, there is an increase in these periods since the early 1800s. The record was examined for recent increases in dust emissions associated with anthropogenic activities, but no recent dust variations can be conclusively attributed to anthropogenic inputs of dust.

Variability in Accumulation Rates from GPR Profiling on the West Antarctic Plateau

lsochronal layers in firn detected with ground-penetrating radar (GPR) and dated using results from ice-core analyses are used to calculate accumulation rates along a 100 km across-flow profile in West Antarctica. Accumulation rates are shown to be highly variable over short distances. Elevation measurements from global positioning system surveys show that accumulation rates derived from shallow horizons correlate well with surface undulations, which implies that wind redistribution of snow is the leading cause of this variability. Temporal changes in accumulation rate over 25-185 year intervals are smoothed to along-track length scales comparable to surface undulations in order to identify trends in accumulation that are likely related to changes in climate. Results show that accumulation rates along this profile have decreased in recent decades, which is consistent with core-derived time series of annual accumulation rates measured at the two ends of the radar profile. These results suggest that temporal variability observed in accumulation-rate records from ice cores and GPR profiles can be obscured by spatial influences, although it is possible to resolve temporal signals if the effects of local topography and ice flow are quantified and removed.

Seasonal Geophysical Monitoring of Biogenic Gases in a Northern Peatland: Implications for Temporal and Spatial Variability in Free Phase Gas Production Rates

A set of high resolution surface ground penetrating radar (GPR) surveys, combined with elevation rod ( to monitor surface deformation) and gas flux measurements, were used to investigate in situ biogenic gas dynamics within a northern peatland (Caribou Bog, Maine). Gas production rates were directly estimated from the time series of GPR measurements. Spatial variability in gas production was also investigated by comparing two sites with different geological and ecological attributes, showing differences and/or similarities depending on season. One site characterized by thick highly humified peat deposits (5-6 m), wooded heath vegetation and open pools showed large ebullition events during the summer season, with estimated emissions (based on an assumed range of CH(4) concentration) between 100 and 172 g CH(4) m(-2) during a single event. The other site characterized by thinner less humified peat deposits (2-3 m) and shrub vegetation showed much smaller ebullition events during the same season (between 13 and 23 g CH(4) m(-2)). A consistent period of free-phase gas (FPG) accumulation during the fall and winter, enhanced by the frozen surficial peat acting as a confining layer, was followed by a decrease in FPG after the snow/ice melt that released estimated fluxes between 100 and 200 g CH(4) m(-2) from both sites. Estimated FPG production rates during periods of biogenic gas accumulation ranged between 0.22 and 2.00 g CH(4) m(3) d(-1) and reflected strong seasonal and spatial variability associated with differences in temperature, peat soil properties, and/or depositional attributes (e. g., stratigraphy). Periods of decreased atmospheric pressure coincided with short-period increases in biogenic gas flux, including a very rapid decrease in FPG content associated with an ebullition event that released an estimated 39 and 67 g CH(4) m(-2) in less than 3.5 hours. These results provide insights into the spatial and seasonal variability in production and emission of biogenic gases from northern peatlands.

Spatial and Temporal Melt Variability at Helheim Glacier, East Greenland, and Its Effect on Ice Dynamics

Understanding the behavior of large outlet glaciers draining the Greenland Ice Sheet is critical for assessing the impact of climate change on sea level rise. The flow of marine-terminating outlet glaciers is partly governed by calving-related processes taking place at the terminus but is also influenced by the drainage of surface runoff to the bed through moulins, cracks, and other pathways. To investigate the extent of the latter effect, we develop a distributed surface-energy-balance model for Helheim Glacier, East Greenland, to calculate surface melt and thereby estimate runoff. The model is driven by data from an automatic weather station operated on the glacier during the summers of 2007 and 2008, and calibrated with independent measurements of ablation. Modeled melt varies over the deployment period by as much as 68% relative to the mean, with melt rates approximately 77% higher on the lower reaches of the glacier trunk than on the upper glacier. We compare melt variations during the summer season to estimates of surface velocity derived from global positioning system surveys. Near the front of the glacier, there is a significant correlation (on >95% levels) between variations in runoff (estimated from surface melt) and variations in velocity, with a 1 day delay in velocity relative to melt. Although the velocity changes are small compared to accelerations previously observed following some calving events, our findings suggest that the flow speed of Helheim Glacier is sensitive to changes in runoff. The response is most significant in the heavily crevassed, fast-moving region near the calving front. The delay in the peak of the cross-correlation function implies a transit time of 12-36 h for surface runoff to reach the bed.

Satellite-Derived Variability in Chlorophyll, Wind Stress, Sea Surface Height, and Temperature in the Northern California Current System

Satellite-derived data provide the temporal means and seasonal and nonseasonal variability of four physical and biological parameters off Oregon and Washington ( 41 degrees - 48.5 degrees N). Eight years of data ( 1998 - 2005) are available for surface chlorophyll concentrations, sea surface temperature ( SST), and sea surface height, while six years of data ( 2000 - 2005) are available for surface wind stress. Strong cross-shelf and alongshore variability is apparent in the temporal mean and seasonal climatology of all four variables. Two latitudinal regions are identified and separated at 44 degrees - 46 degrees N, where the coastal ocean experiences a change in the direction of the mean alongshore wind stress, is influenced by topographic features, and has differing exposure to the Columbia River Plume. All these factors may play a part in defining the distinct regimes in the northern and southern regions. Nonseasonal signals account for similar to 60 - 75% of the dynamical variables. An empirical orthogonal function analysis shows stronger intra-annual variability for alongshore wind, coastal SST, and surface chlorophyll, with stronger interannual variability for surface height. Interannual variability can be caused by distant forcing from equatorial and basin-scale changes in circulation, or by more localized changes in regional winds, all of which can be found in the time series. Correlations are mostly as expected for upwelling systems on intra-annual timescales. Correlations of the interannual timescales are complicated by residual quasi-annual signals created by changes in the timing and strength of the seasonal cycles. Examination of the interannual time series, however, provides a convincing picture of the covariability of chlorophyll, surface temperature, and surface height, with some evidence of regional wind forcing.

Spatial Patterns of Intraseasonal Variability of Chlorophyll and Sea Surface Temperature in the California Current

Six years of daily satellite data are used to quantify and map intraseasonal variability of chlorophyll and sea surface temperature (SST) in the California Current. We define intraseasonal variability as temporal variation remaining after removal of interannual variability and stationary seasonal cycles. Semivariograms are used to quantify the temporal structure of residual time series. Empirical orthogonal function (EOF) analyses of semivariograms calculated across the region isolate dominant scales and corresponding spatial patterns of intraseasonal variability. The mode 1 EOFs for both chlorophyll and SST semivariograms indicate a dominant timescale of similar to 60 days. Spatial amplitudes and patterns of intraseasonal variance derived from mode 1 suggest dominant forcing of intraseasonal variability through distortion of large scale chlorophyll and SST gradients by mesoscale circulation. Intraseasonal SST variance is greatest off southern Baja and along southern Oregon and northern California. Chlorophyll variance is greatest over the shelf and slope, with elevated values closely confined to the Baja shelf and extending farthest from shore off California and the Pacific Northwest. Intraseasonal contributions to total SST variability are strongest near upwelling centers off southern Oregon and northern California, where seasonal contributions are weak. Intraseasonal variability accounts for the majority of total chlorophyll variance in most inshore areas save for southern Baja, where seasonal cycles dominate. Contributions of higher EOF modes to semivariogram structure indicate the degree to which intraseasonal variability is shifted to shorter timescales in certain areas. Comparisons of satellite-derived SST semivariograms to those calculated from co-located and concurrent buoy SST time series show similar features.

Phytoplankton Scales of Variability in the California Current System: 1. Interannual and Cross-Shelf Variability

In the California Current System, strong mesoscale variability associated with eddies and meanders of the coastal jet play an important role in the biological productivity of the area. To assess the dominant timescales of variability, a wavelet analysis is applied to almost nine years (October 1997 to July 2006) of 1-km-resolution, 5-day-averaged, Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll a (chl a) concentration data. The dominant periods of chlorophyll variance, and how these change in time, are quantified as a function of distance offshore. The maximum variance in chlorophyll occurs with a period of similar to 100-200 days. A seasonal cycle in the timing of peak variance is revealed, with maxima in spring/summer close to shore (20 km) and in autumn/winter 200 km offshore. Interannual variability in the magnitude of chlorophyll variance shows maxima in 1999, 2001, 2002, and 2005. There is a very strong out-of-phase correspondence between the time series of chlorophyll variance and the Pacific Decadal Oscillation (PDO) index. We hypothesize that positive PDO conditions, which reflect weak winds and poor upwelling conditions, result in reduced mesoscale variability in the coastal region, and a subsequent decrease in chlorophyll variance. Although the chlorophyll variance responds to basin-scale forcing, chlorophyll biomass does not necessarily correspond to the phase of the PDO, suggesting that it is influenced more by local-scale processes. The mesoscale variability in the system may be as important as the chl a biomass in determining the potential productivity of higher trophic levels.

Time of emergence of trends in ocean biogeochemistry

For the detection of climate change, not only the magnitude of a trend signal is of significance. An essential issue is the time period required by the trend to be detectable in the first place. An illustrative measure for this is time of emergence (ToE), that is, the point in time when a signal finally emerges from the background noise of natural variability. We investigate the ToE of trend signals in different biogeochemical and physical surface variables utilizing a multi-model ensemble comprising simulations of 17 Earth system models (ESMs). We find that signals in ocean biogeochemical variables emerge on much shorter timescales than the physical variable sea surface temperature (SST). The ToE patterns of pCO2 and pH are spatially very similar to DIC (dissolved inorganic carbon), yet the trends emerge much faster – after roughly 12 yr for the majority of the global ocean area, compared to between 10 and 30 yr for DIC. ToE of 45–90 yr are even larger for SST. In general, the background noise is of higher importance in determining ToE than the strength of the trend signal. In areas with high natural variability, even strong trends both in the physical climate and carbon cycle system are masked by variability over decadal timescales. In contrast to the trend, natural variability is affected by the seasonal cycle. This has important implications for observations, since it implies that intra-annual variability could question the representativeness of irregularly sampled seasonal measurements for the entire year and, thus, the interpretation of observed trends.