Height variability from the MIROC - IPCC model for the 20th century compared to that of the TOPEX/POSEIDON altimeter

Planetary waves are key to large-scale dynamical adjustment in the global ocean as they transfer energy from the east to the west side of oceanic basins; they connect the forcing in the ocean interior with the variability at its boundaries: and they change the local heat content, thus coupling oceanic, atmospheric, and biological processes. Planetary waves, mostly of the first baroclinic mode, are observed as distinctive patterns in global time series of sea surface height anomaly (SSHA) and heat storage. The goal of this study is to compare and validate large-scale SSHA signals from coupled ocean-atmosphere general circulation Model for Interdisciplinary Research on Climate (MIROC) with TOPEX/POSEIDON satellite altimeter observations. The last decade of the models` time series is selected for comparison with the altimeter data. The wave patterns are separated from the meso- and large-scale SSHA signals by digital filters calibrated to select the same spectral bands in both model and altimeter data. The band-wise comparison allows for an assessment of the model skill to simulate the dynamical components of the observed wave field. Comparisons regarding both the seasonal cycle and the Rossby wave Held differ significantly among basins. When carried within the same basin, differences can occur between equal latitudes in opposite hemispheres. Furthermore, at some latitudes the MIROC reproduces biannual, annual and semiannual planetary waves with phase speeds and average amplitudes similar to those observed by the altimeter, but with significant differences in phase. (C) 2008 Elsevier Ltd. All rights reserved.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

Loudness scattering due to vibro-acoustic model variability

The use of numerical simulation in the design and evaluation of products performance is ever increasing. To a greater extent, such estimates are needed in a early design stage, when physical prototypes are not available. When dealing with vibro-acoustic models, known to be computationally expensive, a question remains, which is related to the accuracy of such models in view of the well-know variability inherent to the mass manufacturing production techniques. In addition, both academia and industry have recently realized the importance of actually listening to a products sound, either by measurements or by virtual sound synthesis, in order to assess its performance. In this work, the scatter of significant parameter variations on a simplified vehicle vibro-acoustic model is calculated on loudness metrics using Monte Carlo analysis. The mapping from the system parameters to sound quality metric is performed by a fully-coupled vibro-acoustic finite element model. Different loudness metrics are used, including overall sound pressure level expressed in dB and Specific Loudness in Sones. Sound quality equivalent sources are used to excite this model and the sound pressure level at the driver's head position is acquired to be evaluated according to sound quality metrics. No significant variation has been perceived when evaluating the system using regular sound pressure level expressed in in dB and dB(A). This happens because of the third-octave filters that averages the results under some frequency bands. On the other hand, Zwicker Loudness presents important variations, arguably, due to the masking effects.

Representation of the Weddell Sea deep water masses in the ocean component of the NCAR-CCSM model

We examine Weddell Sea deep water mass distributions with respect to the results from three different model runs using the oceanic component of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM). One run is inter-annually forced by corrected NCAR/NCEP fluxes, while the other two are forced with the annual cycle obtained from the same climatology. One of the latter runs includes an interactive sea-ice model. Optimum Multiparameter analysis is applied to separate the deep water masses in the Greenwich Meridian section (into the Weddell Sea only) to measure the degree of realism obtained in the simulations. First, we describe the distribution of the simulated deep water masses using observed water type indices. Since the observed indices do not provide an acceptable representation of the Weddell Sea deep water masses as expected, they are specifically adjusted for each simulation. Differences among the water masses` representations in the three simulations are quantified through their root-mean-square differences. Results point out the need for better representation (and inclusion) of ice-related processes in order to improve the oceanic characteristics and variability of dense Southern Ocean water masses in the outputs of the NCAR-CCSM model, and probably in other ocean and climate models.

Influence of the meridional overturning circulation on tropical Atlantic climate and variability

The influence of the meridional overturning circulation on tropical Atlantic climate and variability has been investigated using the atmosphere-ocean coupled model Speedy-MICOM (Miami Isopycnic Coordinate Ocean Model). In the ocean model MICOM the strength of the meridional overturning cell can be regulated by specifying the lateral boundary conditions. In case of a collapse of the basinwide meridional overturning cell the SST response in the Atlantic is characterized by a dipole with a cooling in the North Atlantic and a warming in the tropical and South Atlantic. The cooling in the North Atlantic is due to the decrease in the strength of the western boundary currents, which reduces the northward advection of heat. The warming in the tropical Atlantic is caused by a reduced ventilation of water originating from the South Atlantic. This effect is most prominent in the eastern tropical Atlantic during boreal summer when the mixed layer attains its minimum depth. As a consequence the seasonal cycle as well as the interannual variability in SST is reduced. The characteristics of the cold tongue mode are changed: the variability in the eastern equatorial region is strongly reduced and the largest variability is now in the Benguela, Angola region. Because of the deepening of the equatorial thermocline, variations in the thermocline depth in the eastern tropical Atlantic no longer significantly affect the mixed layer temperature. The gradient mode remains unaltered. The warming of the tropical Atlantic enhances and shifts the Hadley circulation. Together with the cooling in the North Atlantic, this increases the strength of the subtropical jet and the baroclinicity over the North Atlantic.

Previous Exercise Training Has a Beneficial Effect on Renal and Cardiovascular Function in a Model of Diabetes

Exercise training (ET) is an important intervention for chronic diseases such as diabetes mellitus (DM). However, it is not known whether previous exercise training intervention alters the physiological and medical complications of these diseases. We investigated the effects of previous ET on the progression of renal disease and cardiovascular autonomic control in rats with streptozotocin (STZ)-induced DM. Male Wistar rats were divided into five groups. All groups were followed for 15 weeks. Trained control and trained diabetic rats underwent 10 weeks of exercise training, whereas previously trained diabetic rats underwent 14 weeks of exercise training. Renal function, proteinuria, renal sympathetic nerve activity (RSNA) and the echocardiographic parameters autonomic modulation and baroreflex sensitivity (BRS) were evaluated. In the previously trained group, the urinary albumin/creatinine ratio was reduced compared with the sedentary diabetic and trained diabetic groups (p < 0.05). Additionally, RSNA was normalized in the trained diabetic and previously trained diabetic animals (p < 0.05). The ejection fraction was increased in the previously trained diabetic animals compared with the diabetic and trained diabetic groups (p < 0.05), and the myocardial performance index was improved in the previously trained diabetic group compared with the diabetic and trained diabetic groups (p < 0.05). In addition, the previously trained rats had improved heart rate variability and BRS in the tachycardic response and bradycardic response in relation to the diabetic group (p < 0.05). This study demonstrates that previous ET improves the functional damage that affects DM. Additionally, our findings suggest that the development of renal and cardiac dysfunction can be minimized by 4 weeks of ET before the induction of DM by STZ.

Spatio-temporal variability of sugarcane yield efficiency in the state of Sao Paulo, Brazil

The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of Sao Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of Sao Paulo.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

Sympathetic overactivity precedes metabolic dysfunction in a fructose model of glucose intolerance in mice

De Angelis K, Senador DD, Mostarda C, Irigoyen MC, Morris M. Sympathetic overactivity precedes metabolic dysfunction in a fructose model of glucose intolerance in mice. Am J Physiol Regul Integr Comp Physiol 302: R950-R957, 2012. First published February 8, 2012; doi: 10.1152/ajpregu.00450.2011.-Consumption of high levels of fructose in humans and animals leads to metabolic and cardiovascular dysfunction. There are questions as to the role of the autonomic changes in the time course of fructose-induced dysfunction. C57/BL male mice were given tap water or fructose water (100 g/l) to drink for up to 2 mo. Groups were control (C), 15-day fructose (F15), and 60-day fructose (F60). Light-dark patterns of arterial pressure (AP) and heart rate (HR), and their respective variabilities were measured. Plasma glucose, lipids, insulin, leptin, resistin, adiponectin, and glucose tolerance were quantified. Fructose increased systolic AP (SAP) at 15 and 60 days during both light (F15: 123 +/- 2 and F60: 118 +/- 2 mmHg) and dark periods (F15: 136 +/- 4 and F60: 136 +/- 5 mmHg) compared with controls (light: 111 +/- 2 and dark: 117 +/- 2 mmHg). SAP variance (VAR) and the low-frequency component (LF) were increased in F15 (>60% and >80%) and F60 (>170% and >140%) compared with C. Cardiac sympatho-vagal balance was enhanced, while baroreflex function was attenuated in fructose groups. Metabolic parameters were unchanged in F15. However, F60 showed significant increases in plasma glucose (26%), cholesterol (44%), triglycerides (22%), insulin (95%), and leptin (63%), as well as glucose intolerance. LF of SAP was positively correlated with SAP. Plasma leptin was correlated with triglycerides, insulin, and glucose tolerance. Results show that increased sympathetic modulation of vessels and heart preceded metabolic dysfunction in fructose-consuming mice. Data suggest that changes in autonomic modulation may be an initiating mechanism underlying the cluster of symptoms associated with cardiometabolic disease.

Mean and Variability of the Tropical Atlantic Ocean in the CCSM4

This study analyzes important aspects of the tropical Atlantic Ocean from simulations of the fourth version of the Community Climate System Model (CCSM4): the mean sea surface temperature (SST) and wind stress, the Atlantic warm pools, the principal modes of SST variability, and the heat budget in the Benguela region. The main goal was to assess the similarities and differences between the CCSM4 simulations and observations. The results indicate that the tropical Atlantic overall is realistic in CCSM4. However, there are still significant biases in the CCSM4 Atlantic SSTs, with a colder tropical North Atlantic and a hotter tropical South Atlantic, that are related to biases in the wind stress. These are also reflected in the Atlantic warm pools in April and September, with its volume greater than in observations in April and smaller than in observations in September. The variability of SSTs in the tropical Atlantic is well represented in CCSM4. However, in the equatorial and tropical South Atlantic regions, CCSM4 has two distinct modes of variability, in contrast to observed behavior. A model heat budget analysis of the Benguela region indicates that the variability of the upper-ocean temperature is dominated by vertical advection, followed by meridional advection.

Soil carbon balance in a tropical grassland: Estimation of soil respiration and its partitioning using a semi-empirical model

In savannah and tropical grasslands, which account for 60% of grasslands worldwide, a large share of ecosystem carbon is located below ground due to high root:shoot ratios. Temporal variations in soil CO2 efflux (R-S) were investigated in a grassland of coastal Congo over two years. The objectives were (1) to identify the main factors controlling seasonal variations in R-S and (2) to develop a semi-empirical model describing R-S and including a heterotrophic component (R-H) and an autotrophic component (R-A). Plant above-ground activity was found to exert strong control over soil respiration since 71% of seasonal R-S variability was explained by the quantity of photosynthetically active radiation absorbed (APAR) by the grass canopy. We tested an additive model including a parameter enabling R-S partitioning into R-A and R-H. Assumptions underlying this model were that R-A mainly depended on the amount of photosynthates allocated below ground and that microbial and root activity was mostly controlled by soil temperature and soil moisture. The model provided a reasonably good prediction of seasonal variations in R-S (R-2 = 0.85) which varied between 5.4 mu mol m(-2) s(-1) in the wet season and 0.9 mu mol m(-2) s(-1) at the end of the dry season. The model was subsequently used to obtain annual estimates of R-S, R-A and R-H. In accordance with results reported for other tropical grasslands, we estimated that R-H accounted for 44% of R-S, which represented a flux similar to the amount of carbon brought annually to the soil from below-ground litter production. Overall, this study opens up prospects for simulating the carbon budget of tropical grasslands on a large scale using remotely sensed data. (C) 2012 Elsevier B.V. All rights reserved.

Spatio-temporal variability of sugarcane yield efficiency in the state of São Paulo, Brazil

The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.

Spatial variability of soil fertility and its relationship with seed physiological potential in a soybean production area

The correlation of soil fertility x seed physiological potential is very important in the area of seed technology but results published with that theme are contradictory. For this reason, this study to evaluate the correlations between soil chemical properties and physiological potential of soybean seeds. On georeferenced points, both soil and seeds were sampled for analysis of soil fertility and seed physiological potential. Data were assessed by the following analyses: descriptive statistics; Pearson's linear correlation; and geostatistics. The adjusted parameters of the semivariograms were used to produce maps of spatial distribution for each variable. Organic matter content, Mn and Cu showed significant effects on seed germination. Most variables studied presented moderate to high spatial dependence. Germination and accelerated aging of seeds, and P, Ca, Mg, Mn, Cu and Zn showed a better fit to spherical semivariogram: organic matter, pH and K had a better fit to Gaussian model; and V% and Fe showed a better fit to the linear model. The values for range of spatial dependence varied from 89.9 m for P until 651.4 m for Fe. These values should be considered when new samples are collected for assessing soil fertility in this production area.

3C 273 variability at 7 mm: evidence of shocks and precession in the jet

We report on four years of observations of 3C 273 at 7mm obtained with the Itapetinga radio telescope, in Brazil, between 2009 and 2013. We detected a flare in 2010 March, when the flux density increased by 50 per cent and reached 35 Jy. After the flare, the flux density started to decrease and reached values lower than 10 Jy. We suggest that the 7-mm flare is the radio counterpart of the γ -ray flare observed by the Fermi Large Area Telescope in 2009 September, in which the flux density at high energies reached a factor of 50 of its average value. A delay of 170 d between the radio and γ -ray flares was revealed using the discrete correlation function (DCF) that can be interpreted in the context of a shock model, in which each flare corresponds to the formation of a compact superluminal component that expands and becomes optically thin at radio frequencies at latter epochs. The differences in flare intensity between frequencies and at different times are explained as a consequence of an increase in the Doppler factor δ, as predicted by the 16-yr precession model proposed by Abraham & Romero. This increase has a large effect on boosting at high frequencies while it does not affect the observed optically thick radio emission too much. We discuss other observable effects of the variation in δ, such as the increase in the formation rate of superluminal components, the variations in the time delay between flares and the periodic behaviour of the radio light curve that we have found to be compatible with changes in the Doppler factor.