64 resultados para oceanography : general : climate and interannual variability


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Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

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210Pb, 137Cs and 14C dated sediments of two late Holocene landslide lakes in the Provincial Park Lagunas de Yala (Laguna Rodeo, Laguna Comedero, 24°06′S, 65°30′W, 2100 m asl, northwestern Argentina) reveal a high-resolution multi-proxy data set of climate change and human impact for the past ca. 2000 years. Comparison of the lake sediment data set for the 20th century (sediment mass accumulation rates MARs, pollen spectra, nutrient and charcoal fluxes) with independent dendroecological data from the catchment (fire scars, tree growth) and long regional precipitation series (from 1934 onwards) show that (1) the lake sediment data set is internally highly consistent and compares well with independent data sets, (2) the chronology of the sediment is reliable, (3) large fires (1940s, 1983/1984–1989) as documented in the local fire scar frequency are recorded in the charcoal flux to the lake sediments and coincide with low wet-season precipitation rates (e.g., 1940s, 1983/1984) and/or high interannual precipitation variability (late 1940s), and (4) the regional increase in precipitation after 1970 is recorded in an increase in the MARs (L. Rodeo from 100 to 390 mg cm−2 yr−1) and in an increase in fern spores reflecting wet vegetation. The most significant change in MARs and nutrient fluxes (Corg and P) of the past 2000 years is observed with the transition from the Inca Empire to the Spanish Conquest around 1600 AD. Compared with the pre-17th century conditions, MARs increased by a factor of ca. 5 to >8 (to 800 +130, −280 mg cm−2 yr−1), PO4 fluxes increased by a factor of 7, and Corg fluxes by a factor of 10.5 for the time between 1640 and 1930 AD. 17th to 19th century MARs and nutrient fluxes also exceed 20th century values. Excess Pb deposition as indicated by a significant increase in Pb/Zr and Pb/Rb ratios in the sediments after the 1950s coincides with a rapid expansion of the regional mining industry. Excess Pb is interpreted as atmospheric deposition and direct human impact due to Pb smelting.

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Aim Geographical, climatic and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. The aim of this study was to: (1) characterize patterns of beta diversity in global drylands; (2) detect common environmental drivers of beta diversity; and (3) test for thresholds in environmental conditions driving potential shifts in plant species composition. Location Global. Methods Beta diversity was quantified in 224 dryland plant communities from 22 geographical regions on all continents except Antarctica using four complementary measures: the percentage of singletons (species occurring at only one site); Whittaker's beta diversity, β(W); a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites, β(R2); and a multivariate abundance-based metric, β(MV). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographical, climatic and soil variables. Results Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity percentage of singletons and β(W) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance (β(R2) and β(MV) were more associated with climate variability. Interactions among soil variables, climatic factors and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Main conclusions Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving c. 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

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The Mediterranean region has been identified as a global warming hotspot, where future climate impacts are expected to have significant consequences on societal and ecosystem well-being. To put ongoing trends of summer climate into the context of past natural variability, we reconstructed climate from maximum latewood density (MXD) measurements of Pinus heldreichii (1521–2010) and latewood width (LWW) of Pinus nigra (1617–2010) on Mt. Olympus, Greece. Previous research in the northeastern Mediterranean has primarily focused on inter-annual variability, omitting any low-frequency trends. The present study utilizes methods capable of retaining climatically driven long-term behavior of tree growth. The LWW chronology corresponds closely to early summer moisture variability (May–July, r = 0.65, p < 0.001, 1950–2010), whereas the MXD-chronology relates mainly to late summer warmth (July–September, r = 0.64, p < 0.001; 1899–2010). The chronologies show opposing patterns of decadal variability over the twentieth century (r = −0.68, p < 0.001) and confirm the importance of the summer North Atlantic Oscillation (sNAO) for summer climate in the northeastern Mediterranean, with positive sNAO phases inducing cold anomalies and enhanced cloudiness and precipitation. The combined reconstructions document the late twentieth—early twenty-first century warming and drying trend, but indicate generally drier early summer and cooler late summer conditions in the period ~1700–1900 CE. Our findings suggest a potential decoupling between twentieth century atmospheric circulation patterns and pre-industrial climate variability. Furthermore, the range of natural climate variability stretches beyond summer moisture availabilityobserved in recent decades and thus lends credibility to the significant drying trends projected for this region in current Earth System Model simulations.

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The growth rate of atmospheric carbondioxide(CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO 2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.

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Past agricultural responses to climate variability can helps us to better understand the current and future impacts of climate change on agricultural production. We studied rye (Secale cereale) and barley (Hordeum vulgare) yield responses to temperature fluctuations in Finland during the period 1861–1913. Our analyses demonstrate the high sensitivity of non-industrialised northern agriculture to temperature anomalies. We found evidence of a strong relationship between monthly and seasonal mean temperatures and crop yields. In particular, high spring temperatures were associated with higher yields. Additionally, we tested temperature-sensitive tree-ring series for their value in indicating previous agricultural outputs. The results imply that tree-ring proxies (in particular, maximum latewood density) can provide novel material for studies of historical periods and locations where instrumentally measured climate and harvest data are not available.

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Throughout the last millennium, mankind was affected by prolonged deviations from the climate mean state. While periods like the Maunder Minimum in the 17th century have been assessed in greater detail, earlier cold periods such as the 15th century received much less attention due to the sparse information available. Based on new evidence from different sources ranging from proxy archives to model simulations, it is now possible to provide an end-to-end assessment about the climate state during an exceptionally cold period in the 15th century, the role of internal, unforced climate variability and external forcing in shaping these extreme climatic conditions, and the impacts on and responses of the medieval society in Central Europe. Climate reconstructions from a multitude of natural and human archives indicate that, during winter, the period of the early Spörer Minimum (1431–1440 CE) was the coldest decade in Central Europe in the 15th century. The particularly cold winters and normal but wet summers resulted in a strong seasonal cycle that challenged food production and led to increasing food prices, a subsistence crisis, and a famine in parts of Europe. As a consequence, authorities implemented adaptation measures, such as the installation of grain storage capacities, in order to be prepared for future events. The 15th century is characterised by a grand solar minimum and enhanced volcanic activity, which both imply a reduction of seasonality. Climate model simulations show that periods with cold winters and strong seasonality are associated with internal climate variability rather than external forcing. Accordingly, it is hypothesised that the reconstructed extreme climatic conditions during this decade occurred by chance and in relation to the partly chaotic, internal variability within the climate system.

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The paralysis-by-analysis phenomenon, i.e., attending to the execution of one's movement impairs performance, has gathered a lot of attention over recent years (see Wulf, 2007, for a review). Explanations of this phenomenon, e.g., the hypotheses of constrained action (Wulf et al., 2001) or of step-by-step execution (Masters, 1992; Beilock et al., 2002), however, do not refer to the level of underlying mechanisms on the level of sensorimotor control. For this purpose, a “nodal-point hypothesis” is presented here with the core assumption that skilled motor behavior is internally based on sensorimotor chains of nodal points, that attending to intermediate nodal points leads to a muscular re-freezing of the motor system at exactly and exclusively these points in time, and that this re-freezing is accompanied by the disruption of compensatory processes, resulting in an overall decrease of motor performance. Two experiments, on lever sequencing and basketball free throws, respectively, are reported that successfully tested these time-referenced predictions, i.e., showing that muscular activity is selectively increased and compensatory variability selectively decreased at movement-related nodal points if these points are in the focus of attention.

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Changes in marine net primary productivity (PP) and export of particulate organic carbon (EP) are projected over the 21st century with four global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All four models show a decrease in global mean PP and EP between 2 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in PP and EP. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in PP and EP as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where three models project an increase in PP while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observation-based estimates compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer net primary production from satellite observations.

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Congenital isolated ACTH deficiency (IAD) is a rare disease characterized by low plasma ACTH and cortisol levels and preservation of all other pituitary hormones. This condition was poorly defined before we identified TPIT, a T-box transcription factor with a specific role in differentiation of the corticotroph lineage in mice and humans, as its principal molecular cause.