971 resultados para Climate control


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This document outlines a practical strategy for achieving an observationally based quantification of direct climate forcing by anthropogenic aerosols. The strategy involves a four-step program for shifting the current assumption-laden estimates to an increasingly empirical basis using satellite observations coordinated with suborbital remote and in situ measurements and with chemical transport models. Conceptually, the problem is framed as a need for complete global mapping of four parameters: clear-sky aerosol optical depth δ, radiative efficiency per unit optical depth E, fine-mode fraction of optical depth ff, and the anthropogenic fraction of the fine mode faf. The first three parameters can be retrieved from satellites, but correlative, suborbital measurements are required for quantifying the aerosol properties that control E, for validating the retrieval of ff, and for partitioning fine-mode δ between natural and anthropogenic components. The satellite focus is on the “A-Train,” a constellation of six spacecraft that will fly in formation from about 2005 to 2008. Key satellite instruments for this report are the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) radiometers on Aqua, the Ozone Monitoring Instrument (OMI) radiometer on Aura, the Polarization and Directionality of Earth's Reflectances (POLDER) polarimeter on the Polarization and Anistropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL), and the Cloud and Aerosol Lider with Orthogonal Polarization (CALIOP) lidar on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This strategy is offered as an initial framework—subject to improvement over time—for scientists around the world to participate in the A-Train opportunity. It is a specific implementation of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) program, presented earlier in this journal, which identified the integration of diverse data as the central challenge to progress in quantifying global-scale aerosol effects. By designing a strategy around this need for integration, we develop recommendations for both satellite data interpretation and correlative suborbital activities that represent, in many respects, departures from current practice

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Ninety-four sites worldwide have sufficient resolution and dating to document the impact of millennial-scale climate variability on vegetation and fire regimes during the last glacial period. Although Dansgaard–Oeschger (D–O) cycles all show a basically similar gross structure, they vary in the magnitude and the length of the warm and cool intervals. We illustrate the geographic patterns in the climate-induced changes in vegetation by comparing D–O 6, D–O 8 and D–O 19. There is a strong response to both D–O warming events and subsequent cooling, most marked in the northern extratropics. Pollen records from marine cores from the northern extratropics confirm that there is no lag between the change in climate and the vegetation response, within the limits of the dating resolution (50–100 years). However, the magnitude of the change in vegetation is regionally specific and is not a simple function of either the magnitude or the duration of the change in climate as registered in Greenland ice cores. Fire regimes also show an initial immediate response to climate changes, but during cooling intervals there is a slow recovery of biomass burning after the initial reduction, suggesting a secondary control through the recovery of vegetation productivity. In the extratropics, vegetation changes are largely determined by winter temperatures while in the tropics they are largely determined by changes in plant-available water. Tropical vegetation records show changes corresponding to Heinrich Stadials but the response to D–O warming events is less marked than in the northern extratropics. There are very few high-resolution records from the Southern Hemisphere extratropics, but these records also show both a vegetation and fire response to millennial-scale climate variability. It is not yet possible to determine unequivocally whether terrestrial records reflect the asynchroneity apparent in the ice-core records.

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This chapter presents a broad overview of understanding of climate change over the past century or so, together with a discussion of some of the uncertainties. It provides a background to the developments in understanding of climate change, presents evidence that climate has changed and assesses the mechanisms that cause climate change, with a particular emphasis on those due to human activity. The concepts underlying climate modelling are introduced and results are then presented that strongly support the view that human activity has played a major role in the observed climate change over the past 50 years. Possible changes in climate over the coming century are then discussed.

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The evidence for anthropogenic climate change continues to strengthen, and concerns about severe weather events are increasing. As a result, scientific interest is rapidly shifting from detection and attribution of global climate change to prediction of its impacts at the regional scale. However, nearly everything we have any confidence in when it comes to climate change is related to global patterns of surface temperature, which are primarily controlled by thermodynamics. In contrast, we have much less confidence in atmospheric circulation aspects of climate change, which are primarily controlled by dynamics and exert a strong control on regional climate. Model projections of circulation-related fields, including precipitation, show a wide range of possible outcomes, even on centennial timescales. Sources of uncertainty include low-frequency chaotic variability and the sensitivity to model error of the circulation response to climate forcing. As the circulation response to external forcing appears to project strongly onto existing patterns of variability, knowledge of errors in the dynamics of variability may provide some constraints on model projections. Nevertheless, higher scientific confidence in circulation-related aspects of climate change will be difficult to obtain. For effective decision-making, it is necessary to move to a more explicitly probabilistic, risk-based approach.

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Purpose The sensitivity of soil organic carbon to global change drivers, according to the depth profile, is receiving increasing attention because of its importance in the global carbon cycle and its potential feedback to climate change. A better knowledge of the vertical distribution of SOC and its controlling factors—the aim of this study—will help scientists predict the consequences of global change. Materials and methods The study area was the Murcia Province (S.E. Spain) under semiarid Mediterranean conditions. The database used consists of 312 soil profiles collected in a systematic grid, each 12 km2 covering a total area of 11,004 km2. Statistical analysis to study the relationships between SOC concentration and control factors in different soil use scenarios was conducted at fixed depths of 0–20, 20–40, 40–60, and 60–100 cm. Results and discussion SOC concentration in the top 40 cm ranged between 6.1 and 31.5 g kg−1, with significant differences according to land use, soil type and lithology, while below this depth, no differences were observed (SOC concentration 2.1–6.8 g kg−1). The ANOVA showed that land use was the most important factor controlling SOC concentration in the 0–40 cm depth. Significant differences were found in the relative importance of environmental and textural factors according to land use and soil depth. In forestland, mean annual precipitation and texture were the main predictors of SOC, while in cropland and shrubland, the main predictors were mean annual temperature and lithology. Total SOC stored in the top 1 m in the region was about 79 Tg with a low mean density of 7.18 kg Cm−3. The vertical distribution of SOC was shallower in forestland and deeper in cropland. A reduction in rainfall would lead to SOC decrease in forestland and shrubland, and an increase of mean annual temperature would adversely affect SOC in croplands and shrubland. With increasing depth, the relative importance of climatic factors decreases and texture becomes more important in controlling SOC in all land uses. Conclusions Due to climate change, impacts will be much greater in surface SOC, the strategies for C sequestration should be focused on subsoil sequestration, which was hindered in forestland due to bedrock limitations to soil depth. In these conditions, sequestration in cropland through appropriate management practices is recommended.

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Episodic explosive volcanic eruptions are a natural part of the climate system but are often omitted from atmosphere-ocean general circulation model (AOGCM) preindustrial spin-up and control experiments. This omission imposes a negative bias on ocean heat uptake in simulations of the historical period. In models of a range of complexity, we find that global-mean sea level rise due to thermal expansion during the last ∼ 150 years is consequently underestimated by 5–30 mm, which is a substantial proportion of the model mean of 50 mm in Coupled Model Intercomparison Project Phase 3 AOGCMs with anthropogenic forcing only, and is therefore important in accounting for 20th century sea level rise. We test and recommend a procedure for removing the bias.

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Fundamental puzzles of climate science remain unsolved because of our limited understanding of how clouds, circulation and climate interact. One example is our inability to provide robust assessments of future global and regional climate changes. However, ongoing advances in our capacity to observe, simulate and conceptualize the climate system now make it possible to fill gaps in our knowledge. We argue that progress can be accelerated by focusing research on a handful of important scientific questions that have become tractable as a result of recent advances. We propose four such questions below; they involve understanding the role of cloud feedbacks and convective organization in climate, and the factors that control the position, the strength and the variability of the tropical rain belts and the extratropical storm tracks.

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The LMD AGCM was iteratively coupled to the global BIOME1 model in order to explore the role of vegetation-climate interactions in response to mid-Holocene (6000 y BP) orbital forcing. The sea-surface temperature and sea-ice distribution used were present-day and CO2 concentration was pre-industrial. The land surface was initially prescribed with present-day vegetation. Initial climate “anomalies” (differences between AGCM results for 6000 y BP and control) were used to drive BIOME1; the simulated vegetation was provided to a further AGCM run, and so on. Results after five iterations were compared to the initial results in order to identify vegetation feedbacks. These were centred on regions showing strong initial responses. The orbitally induced high-latitude summer warming, and the intensification and extension of Northern Hemisphere tropical monsoons, were both amplified by vegetation feedbacks. Vegetation feedbacks were smaller than the initial orbital effects for most regions and seasons, but in West Africa the summer precipitation increase more than doubled in response to changes in vegetation. In the last iteration, global tundra area was reduced by 25% and the southern limit of the Sahara desert was shifted 2.5 °N north (to 18 °N) relative to today. These results were compared with 6000 y BP observational data recording forest-tundra boundary changes in northern Eurasia and savana-desert boundary changes in northern Africa. Although the inclusion of vegetation feedbacks improved the qualitative agreement between the model results and the data, the simulated changes were still insufficient, perhaps due to the lack of ocean-surface feedbacks.

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Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness. CO2 concentration constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence on CO2 concentration, the quantitative relationship between atmospheric CO2 concentration and biomass burning is not well understood. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial–interglacial changes in biomass burning to an increase in CO2, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided last glacial maximum (LGM) climate anomalies – that is, differences from the pre-industrial (PI) control climate – from the Palaeoclimate Modelling Intercomparison Project Phase~2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes from biomass burning were corrected for the model's observed prediction biases in contemporary regional average values for biomes. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux at the LGM was in the range of 1.0–1.4 Pg C year-1, about a third less than that modelled for PI time. LGM climate with pre-industrial CO2 (280 ppm) yielded unrealistic results, with global biomass burning fluxes similar to or even greater than in the pre-industrial climate. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on primary production and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

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Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealised, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all three models showing an increase in surface temperature focussed in the northern hemisphere high latitudes, and a corresponding increase in global mean precipitation and run-off. Changes in precipitation and run-off patterns are driven mostly by a northward shift in the ITCZ, consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker forcing signal, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

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Based on the geological evidence that the northern Tibetan Plateau (NTP) had an uplift of a finite magnitude since the Miocene and the major Asian inland deserts formed in the early Pliocene, a regional climate model (RegCM4.1) with a horizontal resolution of 50 km was used to explore the effects of the NTP uplift and the related aridification of inland Asia on regional climate. We designed three numerical experiments including the control experiment representing the present-day condition, the high-mountain experiment representing the early Pliocene condition with uplifted NTP but absence of the Asian inland deserts, and the low-mountain experiment representing the mid-Miocene condition with reduced topography in the NTP (by as much as 2400 m) and also absence of the deserts. Our simulation results indicated that the NTP uplift caused significant reductions in annual precipitation in a broad region of inland Asia north of the Tibetan Plateau (TP) mainly due to the enhanced rain shadow effect of the mountains and changes in the regional circulations. However, four mountainous regions located in the uplift showed significant increases in precipitation, stretching from the Pamir Plateau in the west to the Qilian Mountains in the east. These mountainous areas also experienced different changes in the rainfall seasonality with the greatest increases occurring during the respective rainy seasons, predominantly resulted from the enhanced orographically forced upwind ascents. The appearance of the major deserts in the inland Asia further reduced precipitation in the region and led to increased dust emission and deposition fluxes, while the spatial patterns of dust deposition were also changed, not only in the regions of uplift-impacted topography, but also in the downwind regions. One major contribution from this study is the comparison of the simulation results with 11 existing geological records representing the moisture conditions from Miocene to Pliocene. The comparisons revealed good matches between the simulation results and the published geological records. Therefore, we conclude that the NTP uplift and the related formation of the major deserts played a controlling role in the evolution of regional climatic conditions in a broad region in inland Asia since the Miocene.

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1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0-7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50-250 µm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45-50 µm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250-4000 µm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and Applications: Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1-100,000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

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Cerrãdo savannas have the greatest fire activity of all major global land-cover types and play a significant role in the global carbon cycle. During the 21st century, temperatures are projected to increase by ∼ 3 ◦C coupled with a precipitation decrease of ∼ 20 %. Although these conditions could potentially intensify drought stress, it is unknown how that might alter vegetation composition and fire regimes. To assess how Neotropical savannas responded to past climate changes, a 14 500-year, high-resolution, sedimentary record from Huanchaca Mesetta, a palm swamp located in the cerrãdo savanna in northeastern Bolivia, was analyzed with phytoliths, stable isotopes, and charcoal. A nonanalogue, cold-adapted vegetation community dominated the Lateglacial–early Holocene period (14 500–9000 cal yr BP, which included trees and C3 Pooideae and C4 Panicoideae grasses. The Lateglacial vegetation was fire-sensitive and fire activity during this period was low, likely responding to fuel availability and limitation. Although similar vegetation characterized the early Holocene, the warming conditions associated with the onset of the Holocene led to an initial increase in fire activity. Huanchaca Mesetta became increasingly firedependent during the middle Holocene with the expansion of C4 fire-adapted grasses. However, as warm, dry conditions, characterized by increased length and severity of the dry season, continued, fuel availability decreased. The establishment of the modern palm swamp vegetation occurred at 5000 cal yr BP. Edaphic factors are the first-order control on vegetation on the rocky quartzite mesetta. Where soils are sufficiently thick, climate is the second-order control of vegetation on the mesetta. The presence of the modern palm swamp is attributed to two factors: (1) increased precipitation that increased water table levels and (2) decreased frequency and duration of surazos (cold wind incursions from Patagonia) leading to increased temperature minima. Natural (soil, climate, fire) drivers rather than anthropogenic drivers control the vegetation and fire activity at Huanchaca Mesetta. Thus the cerrãdo savanna ecosystem of the Huanchaca Plateau has exhibited ecosystem resilience to major climatic changes in both temperature and precipitation since the Lateglacial period.

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A present day control integration performed with the Hadley Centre's coupled climate model HadGEM1.2 experiences a large salinity bias in the Arctic Ocean when compared to in situ observations. Such a large salinity bias may have implications for both Arctic and Atlantic Ocean circulation. Large differences are seen between the runoff in HadGEM and the observations from the Global Runoff Data Centre, in particular in the Lena catchment, which could account for this salinity bias. We suggest that this discrepancy in runoff is, at least in part, due to a lack of snow accumulation in the model. The model climatology is very different to those obtained by remote sensing, such as the Global Snow Water Equivalent Climatology (NSIDC) and GlobSnow (ESA).

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We apply the Coexistence Approach (CoA) to reconstruct mean annual precipitation (MAP), mean annual temperature (MAT), mean temperature of thewarmestmonth (MTWA) and mean temperature of the coldest month (MTCO) at 44 pollen sites on the Qinghai–Tibetan Plateau. The modern climate ranges of the taxa are obtained (1) from county-level presence/absence data and (2) from data on the optimum and range of each taxon from Lu et al. (2011). The CoA based on the optimumand range data yields better predictions of observed climate parameters at the pollen sites than that based on the county-level data. The presence of arboreal pollen, most of which is derived fromoutside the region, distorts the reconstructions. More reliable reconstructions are obtained using only the non-arboreal component of the pollen assemblages. The root mean-squared error (RMSE) of the MAP reconstructions are smaller than the RMSE of MAT, MTWA and MTCO, suggesting that precipitation gradients are the most important control of vegetation distribution on the Qinghai–Tibetan Plateau. Our results show that CoA could be used to reconstruct past climates in this region, although in areas characterized by open vegetation the most reliable estimates will be obtained by excluding possible arboreal contaminants.