117 resultados para Climate Change: Learning from the past climate


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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.

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Chrysophyte cysts are recognized as powerful proxies of cold-season temperatures. In this paper we use the relationship between chrysophyte assemblages and the number of days below 4 °C (DB4 °C) in the epilimnion of a lake in northern Poland to develop a transfer function and to reconstruct winter severity in Poland for the last millennium. DB4 °C is a climate variable related to the length of the winter. Multivariate ordination techniques were used to study the distribution of chrysophytes from sediment traps of 37 low-land lakes distributed along a variety of environmental and climatic gradients in northern Poland. Of all the environmental variables measured, stepwise variable selection and individual Redundancy analyses (RDA) identified DB4 °C as the most important variable for chrysophytes, explaining a portion of variance independent of variables related to water chemistry (conductivity, chlorides, K, sulfates), which were also important. A quantitative transfer function was created to estimate DB4 °C from sedimentary assemblages using partial least square regression (PLS). The two-component model (PLS-2) had a coefficient of determination of View the MathML sourceRcross2 = 0.58, with root mean squared error of prediction (RMSEP, based on leave-one-out) of 3.41 days. The resulting transfer function was applied to an annually-varved sediment core from Lake Żabińskie, providing a new sub-decadal quantitative reconstruction of DB4 °C with high chronological accuracy for the period AD 1000–2010. During Medieval Times (AD 1180–1440) winters were generally shorter (warmer) except for a decade with very long and severe winters around AD 1260–1270 (following the AD 1258 volcanic eruption). The 16th and 17th centuries and the beginning of the 19th century experienced very long severe winters. Comparison with other European cold-season reconstructions and atmospheric indices for this region indicates that large parts of the winter variability (reconstructed DB4 °C) is due to the interplay between the oscillations of the zonal flow controlled by the North Atlantic Oscillation (NAO) and the influence of continental anticyclonic systems (Siberian High, East Atlantic/Western Russia pattern). Differences with other European records are attributed to geographic climatological differences between Poland and Western Europe (Low Countries, Alps). Striking correspondence between the combined volcanic and solar forcing and the DB4 °C reconstruction prior to the 20th century suggests that winter climate in Poland responds mostly to natural forced variability (volcanic and solar) and the influence of unforced variability is low.

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A higher risk of future range losses as a result of climate change is expected to be one of the main drivers of extinction trends in vascular plants occurring in habitat types of high conservation value. Nevertheless, the impact of the climate changes of the last 60 years on the current distribution and extinction patterns of plants is still largely unclear. We applied species distribution models to study the impact of environmental variables (climate, soil conditions, land cover, topography), on the current distribution of 18 vascular plant species characteristic of three threatened habitat types in southern Germany: (i) xero-thermophilous vegetation, (ii) mesophilous mountain grasslands (mountain hay meadows and matgrass communities), and (iii) wetland habitats (bogs, fens, and wet meadows). Climate and soil variables were the most important variables affecting plant distributions at a spatial level of 10 × 10 km. Extinction trends in our study area revealed that plant species which occur in wetland habitats faced higher extinction risks than those in xero-thermophilous vegetation, with the risk for species in mesophilous mountain grasslands being intermediary. For three plant species characteristic either of mesophilous mountain grasslands or wetland habitats we showed exemplarily that extinctions from 1950 to the present day have occurred at the edge of the species’ current climatic niche, indicating that climate change has likely been the main driver of extinction. This is largely consistent with current extinction trends reported in other studies. Our study indicates that the analysis of past extinctions is an appropriate means to assess the impact of climate change on species and that vulnerability to climate change is both species- and habitat-specific.

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This article describes the indigenous knowledge (IK) that agro-pastoralists in larger Makueni District, Kenya hold and how they use it to monitor, mitigate and adapt to drought. It examines ways of integrating IK into formal monitoring, how to enhance its value and acceptability. Data was collected through target interviews, group discussions and questionnaires covering 127 households in eight villages. Daily rainfall data from 1961–2003 were analysed. Results show that agro-pastoralists hold IK on indicators of rainfall variability; they believe in IK efficacy and they rely on them. Because agro-pastoralists consult additional sources, the authors interpret that IK forms a basic knowledge frame within which agro-pastoralists position and interpret meteorological forecasts. Only a few agro-pastoralists adapt their practices in anticipation of IK-based forecasts partly due to the conditioning of the actors to the high rainfall variability characteristic of the area and partly due to lack of resources. Non-drought factors such as poverty, inadequate resources and lack of preparedness expose agro-pastoralists to drought impacts and limit their adaptive capacity. These factors need to be understood and effectively addressed to increase agro-pastoralists’ decision options and the influence of IK-based forecasts on their decision-making patterns. The limited intergenerational transfer of IK currently threatens its existence in the longer term. One way to ensure its continued existence and use is to integrate IK into the education curriculum and to link IK with formal climate change research through the participation of the local people. However, further studies are necessary to address the reliability and validity of the identified IK indicators of climate variability and change.

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Large progress has been made in the past few years towards quantifying and understanding climate variability during past centuries. At the same time, present-day climate has been studied using state-of-the-art data sets and tools with respect to the physical and chemical mechanisms governing climate variability. Both the understanding of the past and the knowledge of the processes are important for assessing and attributing the anthropogenic effect on present and future climate. The most important time period in this context is the past approximately 100 years, which comprises large natural variations and extremes (such as long droughts) as well as anthropogenic influences, most pronounced in the past few decades. Recent and ongoing research efforts steadily improve the observational record of the 20th century, while atmospheric circulation models are used to underpin the mechanisms behind large climatic variations. Atmospheric chemistry and composition are important for understanding climate variability and change, and considerable progress has been made in the past few years in this field. The evolving integration of these research areas in a more comprehensive analysis of recent climate variability was reflected in the organisation of a workshop “Climate variability and extremes in the past 100 years” in Gwatt near Thun (Switzerland), 24–26 July 2006. The aim of this workshop was to bring together scientists working on data issues together with statistical climatologists, modellers, and atmospheric chemists to discuss gaps in our understanding of climate variability during the past approximately 100 years.

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Alpine snowbeds are characterised by a very short growing season. However, the length of the snow-free period is increasingly prolonged due to climate change, so that snowbeds become susceptible to invasions from neighbouring alpine meadow communities. We hypothesised that spatial distribution of species generated by plant interactions may indicate whether snowbed species will coexist with or will be out-competed by invading alpine species – spatial aggregation or segregation will point to coexistence or competitive exclusion, respectively. We tested this hypothesis in snowbeds of the Swiss Alps using the variance ratio statistics. We focused on the relationships between dominant snowbed species, subordinate snowbed species, and potentially invading alpine grassland species. Subordinate snowbed species were generally spatially aggregated with each other, but were segregated from alpine grassland species. Competition between alpine grassland and subordinate snowbed species may have caused this segregation. Segregation between these species groups increased with earlier snowmelt, suggesting an increasing importance of competition with climate change. Further, a dominant snowbed species (Alchemilla pentaphyllea) was spatially aggregated with subordinate snowbed species, while two other dominants (Gnaphalium supinum and Salix herbacea) showed aggregated patterns with alpine grassland species. These dominant species are known to show distinct microhabitat preferences suggesting the existence of hidden microhabitats with different susceptibility to invaders. These results allow us to suggest that alpine snowbed areas are likely to be reduced as a consequence of climate change and that invading species from nearby alpine grasslands could outcompete subordinate snowbed species. On the other hand, microhabitats dominated by Gnaphalium or Salix seem to be particularly prone to invasions by non-snowbed species.

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Watershed services are the benefits people obtain from the flow of water through a watershed. While demand for such services is increasing in most parts of the world, supply is getting more insecure due to human impacts on ecosystems such as climate or land use change. Population and water management authorities therefore require information on the potential availability of watershed services in the future and the trade-offs involved. In this study, the Soil and Water Assessment Tool (SWAT) is used to model watershed service availability for future management and climate change scenarios in the East African Pangani Basin. In order to quantify actual “benefits”, SWAT2005 was slightly modified, calibrated and configured at the required spatial and temporal resolution so that simulated water resources and processes could be characterized based on their valuation by stakeholders and their accessibility. The calibrated model was then used to evaluate three management and three climate scenarios. The results show that by the year 2025, not primarily the physical availability of water, but access to water resources and efficiency of use represent the greatest challenges. Water to cover basic human needs is available at least 95% of time but must be made accessible to the population through investments in distribution infrastructure. Concerning the trade-off between agricultural use and hydropower production, there is virtually no potential for an increase in hydropower even if it is given priority. Agriculture will necessarily expand spatially as a result of population growth, and can even benefit from higher irrigation water availability per area unit, given improved irrigation efficiency and enforced regulation to ensure equitable distribution of available water. The decline in services from natural terrestrial ecosystems (e.g. charcoal, food), due to the expansion of agriculture, increases the vulnerability of residents who depend on such services mostly in times of drought. The expected impacts of climate change may contribute to an increase or decrease in watershed service availability, but are only marginal and much lower than management impacts up to the year 2025.

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This study describes and discusses initiatives taken by public (water) agencies in the state of Brandenburg in Germany, the state of California in the USA and the Ebro River Basin in Spain in response to the challenges which climate change poses for the agricultural water sector. The drivers and actors and the process of changing agricultural water governance are its particular focus. The assumptions discussed are: (i) the degree of planned and anticipatory top-down implementation processes decreases if actions are more decentralized and are introduced at the regional and local level; (ii) the degree of autonomous and responsive adaptation approaches seems to grow with actions at a lower administrative level. Looking at processes of institutional change, a variety of drivers and actors are at work such as changing perceptions of predicted climate impacts; international obligations which force politicians to take action; socio-economic concerns such as the cost of not taking action; the economic interests of the private sector. Drivers are manifold and often interact and, in many cases, reforms in the sector are driven by and associated with larger reform agendas. The results of the study may serve as a starting point in assisting water agencies in developing countries with the elaboration of coping strategies for tackling climate change-induced risks related to agricultural water management.

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The stability of terrestrial carbon reservoirs is thought to be closely linked to variations in climate 1, but the magnitude of carbon–climate feedbacks has proved dificult to constrain for both modern 2–4 and millennial 5–13 timescales. Reconstructions of atmospheric CO2 concentrations for the past thousand years have shown fluctuations on multidecadal to centennial timescales 5–7, but the causes of these fluctuations are unclear. Here we report high-resolution carbon isotope measurements of CO2 trapped within the ice of the West Antarctic Ice Sheet Divide ice core for the past 1,000 years. We use a deconvolution approach 14 to show that changes in terrestrial organic carbon stores best explain the observed multidecadal variations in the 13 C of CO2 and in CO2 concentrations from 755 to 1850 CE. If significant long-term carbon emissions came from pre-industrial anthropogenic land-use changes over this interval, the emissions must have been offset by a natural terrestrial sink for 13 C-depleted carbon, such as peatlands. We find that on multidecadal timescales, carbon cycle changes seem to vary with reconstructed regional climate changes. We conclude that climate variability could be an important control of fluctuations in land carbon storage on these timescales.

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This paper analyses the adaptiveness of the Public Agricultural Extension Services (PAES) to climate change. Existing literature, interviews and group discussions among PAES actors in larger Makueni district, Kenya, provided the data for the analyses. The findings show that the PAES already have various elements of adaptiveness in its policies, approaches and methods of extension provision. However, the hierarchical structure of the PAES does not augur well for self-organisation at local levels of extension provision, especially under conditions of abrupt change which climate change might trigger. Most importantly, adpativeness presupposes adaptive capacity but the lack of resources in terms of funding for extension, limited mobility of extension officers, the low extension staff/farmer ratio, the aging of extension staff and significant dependence on donor funding limits the adaptiveness of the PAES. Accordingly criteria and indicators were identified in literature with which an initial assessement of the adaptiiveneess of PAES was conducted. However this assessment framework needs to be improved and future steps will integrate more specific inputs from actors in PAES in order to make the framework operational.

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Volcanic eruptions contribute to climate variability, but quantifying these contributions has been limited by inconsistencies in the timing of atmospheric volcanic aerosol loading determined from ice cores and subsequent cooling from climate proxies such as tree rings. Here we resolve these inconsistencies and show that large eruptions in the tropics and high latitudes were primary drivers of interannual-to-decadal temperature variability in the Northern Hemisphere during the past 2,500 years. Our results are based on new records of atmospheric aerosol loading developed from high-resolution, multi-parameter measurements from an array of Greenland and Antarctic ice cores as well as distinctive age markers to constrain chronologies. Overall, cooling was proportional to the magnitude of volcanic forcing and persisted for up to ten years after some of the largest eruptive episodes. Our revised timescale more firmly implicates volcanic eruptions as catalysts in the major sixth-century pandemics, famines, and socioeconomic disruptions in Eurasia and Mesoamerica while allowing multi-millennium quantification of climate response to volcanic forcing.

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We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and in reanalysis products covering approximately the last 60 years. The focus of the study lies on identifying the link of the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation. Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. In addition, considering multi-centennial timescales, we find in two global simulations a long-term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations. We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understand- ing of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.