Solar-Terrestrial Signal Record in Tree Ring Width Time Series from Brazil

This work investigates the behavior of the sunspot number and Southern Oscillation Index (SOI) signal recorded in the tree ring time series for three different locations in Brazil: Humaita in Amaznia State, Porto Ferreira in So Paulo State, and Passo Fundo in Rio Grande do Sul State, using wavelet and cross-wavelet analysis techniques. The wavelet spectra of tree ring time series showed signs of 11 and 22 years, possibly related to the solar activity, and periods of 2-8 years, possibly related to El Nio events. The cross-wavelet spectra for all tree ring time series from Brazil present a significant response to the 11-year solar cycle in the time interval between 1921 to after 1981. These tree ring time series still have a response to the second harmonic of the solar cycle (5.5 years), but in different time intervals. The cross-wavelet maps also showed that the relationship between the SOI x tree ring time series is more intense, for oscillation in the range of 4-8 years.

Pollen Season and Climate: Is the Timing of Birch Pollen Release in the UK Approaching its Limit?

In light of heightened interest in the response of pollen phenology to temperature, we investigated recent changes to the onset of Betula (birch) pollen seasons in central and southern England, including a test of predicted advancement of the Betula pollen season for London. We calculated onset of birch pollen seasons using daily airborne pollen data obtained at London, Plymouth and Worcester, determined trends in the start of the pollen season and compared timing of the birch pollen season with observed temperature patterns for the period 1995–2010. We found no overall change in the onset of birch pollen in the study period although there was evidence that the response to temperature was nonlinear and that a lower asymptotic start of the pollen season may exist. The start of the birch pollen season was strongly correlated with March mean temperature. These results reinforce previous findings showing that the timing of the birch pollen season in the UK is particularly sensitive to spring temperatures. The climate relationship shown here persists over both longer decadal-scale trends and shorter, seasonal trends as well as during periods of ‘sign-switching’ when cooler spring temperatures result in later start dates. These attributes, combined with the wide geographical coverage of airborne pollen monitoring sites, some with records extending back several decades, provide a powerful tool for the detection of climate change impacts, although local site factors and the requirement for winter chilling may be confounding factors.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Paleoclimate data-model comparison and the role of climate forcings over the past 1500 years

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.

Relations entre le programme de promotion des habiletés d’adaptation pour les enfants de 6-7 ans "Les amis de Zippy" et le climat de classe

Le programme d’enseignement des habiletés d’adaptation Les amis de Zippy vise la promotion de la santé mentale des élèves du premier cycle du primaire. La présente étude est une analyse secondaire réalisée à partir des données d’évaluation des effets du programme. L’objectif général vérifie si l’appartenance au groupe d’intervention est associée à une meilleure qualité du climat relationnel de classe à la fin de l’année scolaire, tel que perçu par les enseignants, tout en contrôlant pour la qualité du climat avant la réalisation du programme. La qualité du climat correspond aux relations entre les élèves et aux relations entre les élèves et l’enseignant. L’effet modérateur de la gestion de comportements et les pratiques pédagogiques est aussi analysé. L’échantillon est constitué de 35 enseignants auto-sélectionnés, répartis entre deux groupes non aléatoires. Les échelles suivantes du QES pour le primaire, version enseignant, sont utilisées : relations entre les élèves, relations entre les élèves et les enseignants, gestion des comportements et pratiques pédagogiques. Les résultats, obtenus grâce à des régressions linéaires multiples, montrent que généralement, l’appartenance au groupe n’explique pas significativement la qualité du climat de classe. Cependant, un effet d’interaction entre le climat de classe et la gestion de comportements est identifié. Lorsque les enseignants gèrent plus difficilement leur classe, le programme Les amis de Zippy est associé à un climat relationnel entre les élèves et l’enseignant moins favorable que dans le groupe témoin. Puisque ces résultats préliminaires peuvent être attribuables à des variables externes non contrôlées, ils devront être approfondis par des études subséquentes.

Manejo de stress, coping e resiliência em motoristas de ônibus urbano

Pós-graduação em Psicologia do Desenvolvimento e Aprendizagem - FC

EPICA Dome C carbon dioxide concentrations from 650 to 391 kyr BP

A record of atmospheric carbon dioxide (CO2) concentrations measured on the EPICA (European Project for Ice Coring in Antarctica) Dome Concordia ice core extends the Vostok CO2 record back to 650,000 years before the present (yr B.P.). Before 430,000 yr B.P., partial pressure of atmospheric CO2 lies within the range of 260 and 180 parts per million by volume. This range is almost 30% smaller than that of the last four glacial cycles; however, the apparent sensitivity between deuterium and CO2 remains stable throughout the six glacial cycles, suggesting that the relationship between CO2 and Antarctic climate remained rather constant over this interval.

Climate variability and hemorrhagic fever with renal syndrome transmission in northeastern China

Background: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by climatic variables. However, few studies have examined the quantitative relationship between climate variation and HFRS transmission. ---------- Objective: We examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China. ---------- Methods: We obtained data on monthly counts of reported HFRS cases in Elunchun and Molidawahaner counties for 1997–2007 from the Inner Mongolia Center for Disease Control and Prevention and climate data from the Chinese Bureau of Meteorology. Cross-correlations assessed crude associations between climate variables, including rainfall, land surface temperature (LST), relative humidity (RH), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI) and monthly HFRS cases over a range of lags. We used time-series Poisson regression models to examine the independent contribution of climatic variables to HFRS transmission. ----------- Results: Cross-correlation analyses showed that rainfall, LST, RH, and MEI were significantly associated with monthly HFRS cases with lags of 3–5 months in both study areas. The results of Poisson regression indicated that after controlling for the autocorrelation, seasonality, and long-term trend, rainfall, LST, RH, and MEI with lags of 3–5 months were associated with HFRS in both study areas. The final model had good accuracy in forecasting the occurrence of HFRS. ---------- Conclusions: Climate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention.

Relationship between emotional climate and the fluency of classroom interactions

This study examined emotional climate in relation to the teaching and learning of grade 7 science. A multi-method and multi-theoretic approach used sociocultural frameworks as a foundation for interpretive research, conversation analysis, prosody analysis, and studies of nonverbal conduct. Emotional climate varied continuously throughout a lesson. Dialogues occurred and afforded learning when interactions between the teacher and students were fluent and included humour and collective effervescence. Emotional climate was negatively valenced when the teacher and/or students endeavoured to establish and maintain power by restricting others’ participation to spectator roles. The teacher’s endeavours to maintain and establish control over students were potentially detrimental to teaching and learning, teachers and learners. This type of teaching gradually evolved into a form we referred to as cranky teaching, whereby the teacher and her students showed signs of frustration and the enacted teaching and learning roles lacked fluency. The methods we pioneered in the present study might be helpful for other teachers who wish to participate in research on their classes to ascertain what works and should be strengthened, and identify practices and rituals that are deleterious and in need of change.