980 resultados para Climate variation
Resumo:
Holocene silts (salt marshes) and highest intertidal-supratidal peats are superbly exposed on a 15 kin coastal transect which reveals two laterally extensive units of annually banded silts (Beds 3, 7) associated with three transgressive-regressive silt-peat cycles (early sixth-early fourth millennium BC). Bed 3 in places is concordantly and gradationally related to peats above and below, but in others transgresses older strata. Bed 7 also grades up into peat, but everywhere overlies a discordance. The banding in Bed 3 at three main and two minor sites was resolved and characterized texturally at high-resolution (2.5/5 mm contiguous slices) using laser granulometry (LS230 with PIDS) and a comprehensive scheme of data-assessment. Most of Bed 3 formed very rapidly, at peak values of several tens of millimetres annually, in accordance with modelled effects of sea-level fluctuations on mature marshes (bed concordant and gradational) and on marshes growing up after coastal erosion and retreat (bed with discordant base). Using data from the modern Severn Estuary, the textural contrast within bands, and its variation between bands, points to a variable but overall milder mid-Holocene climate than today. The inter-annual variability affected marsh dynamics, as shown by the behaviour of the finely divided plant tissues present. Given local calibration, the methodology is applicable to other tidal systems with banded silts in Britain and mainland northwest Europe. (c) 2006 Elsevier Ltd. All rights reserved.
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The nature and magnitude of climatic variability during the period of middle Pliocene warmth (ca 3.29–2.97 Ma) is poorly understood. We present a suite of palaeoclimate modelling experiments incorporating an advanced atmospheric general circulation model (GCM), coupled to a Q-flux ocean model for 3.29, 3.12 and 2.97 Ma BP. Astronomical solutions for the periods in question were derived from the Berger and Loutre BL2 astronomical solution. Boundary conditions, excluding sea surface temperatures (SSTs) which were predicted by the slab-ocean model, were provided from the USGS PRISM2 2°×2° digital data set. The model results indicate that little annual variation (0.5°C) in SSTs, relative to a ‘control’ experiment, occurred during the middle Pliocene in response to the altered orbital configurations. Annual surface air temperatures also displayed little variation. Seasonally, surface air temperatures displayed a trend of cooler temperatures during December, January and February, and warmer temperatures during June, July and August. This pattern is consistent with altered seasonality resulting from the prescribed orbital configurations. Precipitation changes follow the seasonal trend observed for surface air temperature. Compared to present-day, surface wind strength and wind stress over the North Atlantic, North Pacific and Southern Ocean remained greater in each of the Pliocene experiments. This suggests that wind-driven gyral circulation may have been consistently greater during the middle Pliocene. The trend of climatic variability predicted by the GCM for the middle Pliocene accords with geological data. However, it is unclear if the model correctly simulates the magnitude of the variation. This uncertainty is derived from, (a) the relative insensitivity of the GCM to perturbation in the imposed boundary conditions, (b) a lack of detailed time series data concerning changes to terrestrial ice cover and greenhouse gas concentrations for the middle Pliocene and (c) difficulties in representing the effects of ‘climatic history’ in snap-shot GCM experiments.
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Evolutionary theory suggests that divergent natural selection in heterogeneous environments can result in locally adapted plant genotypes. To understand local adaptation it is important to study the ecological factors responsible for divergent selection. At a continental scale, variation in climate can be important while at a local scale soil properties could also play a role. We designed an experiment aimed to disentangle the role of climate and ( abiotic and biotic) soil properties in local adaptation of two common plant species. A grass (Holcus lanatus) and a legume ( Lotus corniculatus), as well as their local soils, were reciprocally transplanted between three sites across an Atlantic-Continental gradient in Europe and grown in common gardens in either their home soil or foreign soils. Growth and reproductive traits were measured over two growing seasons. In both species, we found significant environmental and genetic effects on most of the growth and reproductive traits and a significant interaction between the two environmental effects of soil and climate. The grass species showed significant home site advantage in most of the fitness components, which indicated adaptation to climate. We found no indication that the grass was adapted to local soil conditions. The legume showed a significant home soil advantage for number of fruits only and thus a weak indication of adaptation to soil and no adaptation to climate. Our results show that the importance of climate and soil factors as drivers of local adaptation is species-dependent. This could be related to differences in interactions between plant species and soil biota.
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Impatiens noli-tangere is scarce in the UK and probably only native to the Lake District and Wales. It is the sole food plant for the endangered moth Eustroma reticulattum. Significant annual fluctuations in the size of I. noli-tangere populations endanger the continued presence of E. reticulatum in the UK. In this study, variation in population size was monitored across native populations of L noli-tangere in the English Lake District and Wales. In 1998, there was a crash in the population size of all metapopulations in the Lake District but not of those found in Wales. A molecular survey of the genetic affinities of samples in 1999 from both regions and a reference population from Switzerland was performed using AFLP and ISSR analyses. The consensus UPGMA dendrogram and a PCO scatter plot revealed clear differentiation between the populations of L noli-tangere in Wales and those in the Lake District. Most of the genetic variation in the UK (H-T= 0.064) was partitioned between (G(ST) = 0.455) rather than within (H-S = 0.034) regions, inferring little gene flow occurs between regions. There was similar bias towards differentiation between metapopulations in Wales, again consistent with low levels of interpopulation gene flow. This contrasts with far lower levels of differentiation in the Lake District which suggests modest rates of gene flow may occur between populations. It is concluded that in the event of local extinction of sites or populations, reintroductions should be restricted to samples collected from the same region. We then surveyed climatic variables to identify those most likely to cause local extinctions. Climatic correlates of population size were sought from two Lake District metapopulations situated close to a meteorological station. A combination of three climatic variables common to both sites explained 81-84% of the variation in plant number between 1990 and 2001. Projected trends for these climatic variables were used in a Monte Carlo simulation which suggested an increased risk of I. noli-tangere population crashes by 2050 at Coniston Water. but not at Derwentwater. Implications of these findings for practical conservation strategies are explored. (C) 2003 Elsevier Ltd. All rights reserved.
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A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.
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A simple and coherent framework for partitioning uncertainty in multi-model climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a measure of total variation additively into scenario uncertainty, model uncertainty and internal variability. This approach requires fewer assumptions than existing methods and can be easily used to quantify uncertainty related to model-scenario interaction - the contribution to model uncertainty arising from the variation across scenarios of model deviations from the ensemble mean. Uncertainty in global mean surface air temperature is quantified as a function of lead time for a subset of the Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with those published by other authors: scenario uncertainty dominates beyond 2050 and internal variability remains approximately constant over the 21st century. Both elements of model uncertainty, due to scenario-independent and scenario-dependent deviations from the ensemble mean, are found to increase with time. Estimates of model deviations that arise as by-products of the framework reveal significant differences between models that could lead to a deeper understanding of the sources of uncertainty in multi-model ensembles. For example, three models are shown diverging pattern over the 21st century, while another model exhibits an unusually large variation among its scenario-dependent deviations.
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Daily weather patterns over the North Atlantic are classified into relevant types: typical weather patterns that may characterize the range of climate impacts from aviation in this region, for both summer and winter. The motivation is to provide a set of weather types to facilitate an investigation of climate-optimal aircraft routing of trans-Atlantic flights (minimizing the climate impact on a flight-by-flight basis). Using the New York to London route as an example, the time-optimal route times are shown to vary by over 60 min, to take advantage of strong tailwinds or avoid headwinds, and for eastbound routes latitude correlates well with the latitude of the jet stream. The weather patterns are classified by their similarity to the North Atlantic Oscillation and East Atlantic teleconnection patterns. For winter, five types are defined; in summer, when there is less variation in jet latitude, only three types are defined. The types can be characterized by the jet strength and position, and therefore the location of the time-optimal routes varies by type. Simple proxies for the climate impact of carbon dioxide, ozone, water vapour and contrails are defined, which depend on parameters such as the route time, latitude and season, the time spent flying in the stratosphere, and the distance over which the air is supersaturated with respect to ice. These proxies are then shown to vary between weather types and between eastbound and westbound routes.
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The widely-adopted protocol for the cryopreservation of winter buds of fruit trees, such as Malus and Pyrus, was developed in a region with a continental climate, that provides relatively hard winters with a consequent effect on adaptive plant hardiness. In this study the protocol was evaluated in a typical maritime climate (eastern Denmark) where milder winters can be expected. The survival over two winters was evaluated, looking at variation between seasons and cultivars together with the progressive reduction in survival due to individual steps in the protocol. The study confirms that under such conditions significant variation in survival can be expected and that an extended period of imposed dehydration at -4oC is critical for bud survival. The occurrence of freezing events during this treatment suggests that cryodehydration may be involved, as well as evaporative water loss. To optimize the protocol for maritime environments, further investigation into the water status of the explants during cryopreservation is proposed. Keywords: Malus x domestica, cryopreservation, dormant bud, survival, grafting
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The Asian monsoon system, including the western North Pacific (WNP), East Asian, and Indian monsoons, dominates the climate of the Asia-Indian Ocean-Pacific region, and plays a significant role in the global hydrological and energy cycles. The prediction of monsoons and associated climate features is a major challenge in seasonal time scale climate forecast. In this study, a comprehensive assessment of the interannual predictability of the WNP summer climate has been performed using the 1-month lead retrospective forecasts (hindcasts) of five state-of-the-art coupled models from ENSEMBLES for the period of 1960–2005. Spatial distribution of the temporal correlation coefficients shows that the interannual variation of precipitation is well predicted around the Maritime Continent and east of the Philippines. The high skills for the lower-tropospheric circulation and sea surface temperature (SST) spread over almost the whole WNP. These results indicate that the models in general successfully predict the interannual variation of the WNP summer climate. Two typical indices, the WNP summer precipitation index and the WNP lower-tropospheric circulation index (WNPMI), have been used to quantify the forecast skill. The correlation coefficient between five models’ multi-model ensemble (MME) mean prediction and observations for the WNP summer precipitation index reaches 0.66 during 1979–2005 while it is 0.68 for the WNPMI during 1960–2005. The WNPMI-regressed anomalies of lower-tropospheric winds, SSTs and precipitation are similar between observations and MME. Further analysis suggests that prediction reliability of the WNP summer climate mainly arises from the atmosphere–ocean interaction over the tropical Indian and the tropical Pacific Ocean, implying that continuing improvement in the representation of the air–sea interaction over these regions in CGCMs is a key for long-lead seasonal forecast over the WNP and East Asia. On the other hand, the prediction of the WNP summer climate anomalies exhibits a remarkable spread resulted from uncertainty in initial conditions. The summer anomalies related to the prediction spread, including the lower-tropospheric circulation, SST and precipitation anomalies, show a Pacific-Japan or East Asia-Pacific pattern in the meridional direction over the WNP. Our further investigations suggest that the WNPMI prediction spread arises mainly from the internal dynamics in air–sea interaction over the WNP and Indian Ocean, since the local relationships among the anomalous SST, circulation, and precipitation associated with the spread are similar to those associated with the interannual variation of the WNPMI in both observations and MME. However, the magnitudes of these anomalies related to the spread are weaker, ranging from one third to a half of those anomalies associated with the interannual variation of the WNPMI in MME over the tropical Indian Ocean and subtropical WNP. These results further support that the improvement in the representation of the air–sea interaction over the tropical Indian Ocean and subtropical WNP in CGCMs is a key for reducing the prediction spread and for improving the long-lead seasonal forecast over the WNP and East Asia.
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Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled(CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates. There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5 simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 %/K for simulations and 3-4 %/K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Niño Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (75% precipitation percentile), the precipitation response is ~13-15%/K for GPCP and ~5%/K for models while trends in P are 2.4%/decade for GPCP, 0.6% /decade for CMIP5 and 0.9%/decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.
Resumo:
An analysis of the climate of precipitation extremes as simulated by six European regional climate models (RCMs) is undertaken in order to describe/quantify future changes and to examine/interpret differences between models. Each model has adopted boundary conditions from the same ensemble of global climate model integrations for present (1961–1990) and future (2071–2100) climate under the Intergovernmental Panel on Climate Change A2 emission scenario. The main diagnostics are multiyear return values of daily precipitation totals estimated from extreme value analysis. An evaluation of the RCMs against observations in the Alpine region shows that model biases for extremes are comparable to or even smaller than those for wet day intensity and mean precipitation. In winter, precipitation extremes tend to increase north of about 45°N, while there is an insignificant change or a decrease to the south. In northern Europe the 20-year return value of future climate corresponds to the 40- to 100-year return value of present climate. There is a good agreement between the RCMs, and the simulated change is similar to a scaling of present-day extremes by the change in average events. In contrast, there are large model differences in summer when RCM formulation contributes significantly to scenario uncertainty. The model differences are well explained by differences in the precipitation frequency and intensity process, but in all models, extremes increase more or decrease less than would be expected from the scaling of present-day extremes. There is evidence for a component of the change that affects extremes specifically and is consistent between models despite the large variation in the total response.
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Climate change is a serious threat to crop productivity in regions that are already food insecure. We assessed the projected impacts of climate change on the yield of eight major crops in Africa and South Asia using a systematic review and meta-analysis of data in 52 original publications from an initial screen of 1144 studies. Here we show that the projected mean change in yield of all crops is − 8% by the 2050s in both regions. Across Africa, mean yield changes of − 17% (wheat), − 5% (maize), − 15% (sorghum) and − 10% (millet) and across South Asia of − 16% (maize) and − 11% (sorghum) were estimated. No mean change in yield was detected for rice. The limited number of studies identified for cassava, sugarcane and yams precluded any opportunity to conduct a meta-analysis for these crops. Variation about the projected mean yield change for all crops was smaller in studies that used an ensemble of > 3 climate (GCM) models. Conversely, complex simulation studies that used biophysical crop models showed the greatest variation in mean yield changes. Evidence of crop yield impact in Africa and South Asia is robust for wheat, maize, sorghum and millet, and either inconclusive, absent or contradictory for rice, cassava and sugarcane.
Resumo:
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.
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Ozone (O3) precursor emissions influence regional and global climate and air quality through changes in tropospheric O3 and oxidants, which also influence methane (CH4) and sulfate aerosols (SO42−). We examine changes in the tropospheric composition of O3, CH4, SO42− and global net radiative forcing (RF) for 20% reductions in global CH4 burden and in anthropogenic O3 precursor emissions (NOx, NMVOC, and CO) from four regions (East Asia, Europe and Northern Africa, North America, and South Asia) using the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model (CTM) simulations, assessing uncertainty (mean ± 1 standard deviation) across multiple CTMs. We evaluate steady state O3 responses, including long-term feedbacks via CH4. With a radiative transfer model that includes greenhouse gases and the aerosol direct effect, we find that regional NOx reductions produce global, annually averaged positive net RFs (0.2 ± 0.6 to 1.7 ± 2 mWm−2/Tg N yr−1), with some variation among models. Negative net RFs result from reductions in global CH4 (−162.6 ± 2 mWm−2 for a change from 1760 to 1408 ppbv CH4) and regional NMVOC (−0.4 ± 0.2 to −0.7 ± 0.2 mWm−2/Tg C yr−1) and CO emissions (−0.13 ± 0.02 to −0.15 ± 0.02 mWm−2/Tg CO yr−1). Including the effect of O3 on CO2 uptake by vegetation likely makes these net RFs more negative by −1.9 to −5.2 mWm−2/Tg N yr−1, −0.2 to −0.7 mWm−2/Tg C yr−1, and −0.02 to −0.05 mWm−2/Tg CO yr−1. Net RF impacts reflect the distribution of concentration changes, where RF is affected locally by changes in SO42−, regionally to hemispherically by O3, and globally by CH4. Global annual average SO42− responses to oxidant changes range from 0.4 ± 2.6 to −1.9 ± 1.3 Gg for NOx reductions, 0.1 ± 1.2 to −0.9 ± 0.8 Gg for NMVOC reductions, and −0.09 ± 0.5 to −0.9 ± 0.8 Gg for CO reductions, suggesting additional research is needed. The 100-year global warming potentials (GWP100) are calculated for the global CH4 reduction (20.9 ± 3.7 without stratospheric O3 or water vapor, 24.2 ± 4.2 including those components), and for the regional NOx, NMVOC, and CO reductions (−18.7 ± 25.9 to −1.9 ± 8.7 for NOx, 4.8 ± 1.7 to 8.3 ± 1.9 for NMVOC, and 1.5 ± 0.4 to 1.7 ± 0.5 for CO). Variation in GWP100 for NOx, NMVOC, and CO suggests that regionally specific GWPs may be necessary and could support the inclusion of O3 precursors in future policies that address air quality and climate change simultaneously. Both global net RF and GWP100 are more sensitive to NOx and NMVOC reductions from South Asia than the other three regions.