989 resultados para Subtropical climate


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Although climate models have been improving in accuracy and efficiency over the past few decades, it now seems that these incremental improvements may be slowing. As tera/petascale computing becomes massively parallel, our legacy codes are less suitable, and even with the increased resolution that we are now beginning to use, these models cannot represent the multiscale nature of the climate system. This paper argues that it may be time to reconsider the use of adaptive mesh refinement for weather and climate forecasting in order to achieve good scaling and representation of the wide range of spatial scales in the atmosphere and ocean. Furthermore, the challenge of introducing living organisms and human responses into climate system models is only just beginning to be tackled. We do not yet have a clear framework in which to approach the problem, but it is likely to cover such a huge number of different scales and processes that radically different methods may have to be considered. The challenges of multiscale modelling and petascale computing provide an opportunity to consider a fresh approach to numerical modelling of the climate (or Earth) system, which takes advantage of the computational fluid dynamics developments in other fields and brings new perspectives on how to incorporate Earth system processes. This paper reviews some of the current issues in climate (and, by implication, Earth) system modelling, and asks the question whether a new generation of models is needed to tackle these problems.

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A new spectral-based approach is presented to find orthogonal patterns from gridded weather/climate data. The method is based on optimizing the interpolation error variance. The optimally interpolated patterns (OIP) are then given by the eigenvectors of the interpolation error covariance matrix, obtained using the cross-spectral matrix. The formulation of the approach is presented, and the application to low-dimension stochastic toy models and to various reanalyses datasets is performed. In particular, it is found that the lowest-frequency patterns correspond to largest eigenvalues, that is, variances, of the interpolation error matrix. The approach has been applied to the Northern Hemispheric (NH) and tropical sea level pressure (SLP) and to the Indian Ocean sea surface temperature (SST). Two main OIP patterns are found for the NH SLP representing respectively the North Atlantic Oscillation and the North Pacific pattern. The leading tropical SLP OIP represents the Southern Oscillation. For the Indian Ocean SST, the leading OIP pattern shows a tripole-like structure having one sign over the eastern and north- and southwestern parts and an opposite sign in the remaining parts of the basin. The pattern is also found to have a high lagged correlation with the Niño-3 index with 6-months lag.

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The complexity inherent in climate data makes it necessary to introduce more than one statistical tool to the researcher to gain insight into the climate system. Empirical orthogonal function (EOF) analysis is one of the most widely used methods to analyze weather/climate modes of variability and to reduce the dimensionality of the system. Simple structure rotation of EOFs can enhance interpretability of the obtained patterns but cannot provide anything more than temporal uncorrelatedness. In this paper, an alternative rotation method based on independent component analysis (ICA) is considered. The ICA is viewed here as a method of EOF rotation. Starting from an initial EOF solution rather than rotating the loadings toward simplicity, ICA seeks a rotation matrix that maximizes the independence between the components in the time domain. If the underlying climate signals have an independent forcing, one can expect to find loadings with interpretable patterns whose time coefficients have properties that go beyond simple noncorrelation observed in EOFs. The methodology is presented and an application to monthly means sea level pressure (SLP) field is discussed. Among the rotated (to independence) EOFs, the North Atlantic Oscillation (NAO) pattern, an Arctic Oscillation–like pattern, and a Scandinavian-like pattern have been identified. There is the suggestion that the NAO is an intrinsic mode of variability independent of the Pacific.

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The entropy budget is calculated of the coupled atmosphere–ocean general circulation model HadCM3. Estimates of the different entropy sources and sinks of the climate system are obtained directly from the diabatic heating terms, and an approximate estimate of the planetary entropy production is also provided. The rate of material entropy production of the climate system is found to be ∼50 mW m−2 K−1, a value intermediate in the range 30–70 mW m−2 K−1 previously reported from different models. The largest part of this is due to sensible and latent heat transport (∼38 mW m−2 K−1). Another 13 mW m−2 K−1 is due to dissipation of kinetic energy in the atmosphere by friction and Reynolds stresses. Numerical entropy production in the atmosphere dynamical core is found to be about 0.7 mW m−2 K−1. The material entropy production within the ocean due to turbulent mixing is ∼1 mW m−2 K−1, a very small contribution to the material entropy production of the climate system. The rate of change of entropy of the model climate system is about 1 mW m−2 K−1 or less, which is comparable with the typical size of the fluctuations of the entropy sources due to interannual variability, and a more accurate closure of the budget than achieved by previous analyses. Results are similar for FAMOUS, which has a lower spatial resolution but similar formulation to HadCM3, while more substantial differences are found with respect to other models, suggesting that the formulation of the model has an important influence on the climate entropy budget. Since this is the first diagnosis of the entropy budget in a climate model of the type and complexity used for projection of twenty-first century climate change, it would be valuable if similar analyses were carried out for other such models.

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Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (−22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.

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21st century climate change is projected to result in an intensification of the global hydrological cycle, but there is substantial uncertainty in how this will impact freshwater availability. A relatively overlooked aspect of this uncertainty pertains to how different methods of estimating potential evapotranspiration (PET) respond to changing climate. Here we investigate the global response of six different PET methods to a 2 °C rise in global mean temperature. All methods suggest an increase in PET associated with a warming climate. However, differences in PET climate change signal of over 100% are found between methods. Analysis of a precipitation/PET aridity index and regional water surplus indicates that for certain regions and GCMs, choice of PET method can actually determine the direction of projections of future water resources. As such, method dependence of the PET climate change signal is an important source of uncertainty in projections of future freshwater availability.

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This paper describes the development and first results of the “Community Integrated Assessment System” (CIAS), a unique multi-institutional modular and flexible integrated assessment system for modelling climate change. Key to this development is the supporting software infrastructure, SoftIAM. Through it, CIAS is distributed between the community of institutions which has each contributed modules to the CIAS system. At the heart of SoftIAM is the Bespoke Framework Generator (BFG) which enables flexibility in the assembly and composition of individual modules from a pool to form coupled models within CIAS, and flexibility in their deployment onto the available software and hardware resources. Such flexibility greatly enhances modellers’ ability to re-configure the CIAS coupled models to answer different questions, thus tracking evolving policy needs. It also allows rigorous testing of the robustness of IA modelling results to the use of different component modules representing the same processes (for example, the economy). Such processes are often modelled in very different ways, using different paradigms, at the participating institutions. An illustrative application to the study of the relationship between the economy and the earth’s climate system is provided.

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A review of the implications of climate change for freshwater resources, based on Chapter 4 of Working Group 2, IPCC.

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Current changes in the tropical hydrological cycle, including water vapour and precipitation, are presented over the period 1979-2008 based on a diverse suite of observational datasets and atmosphere-only climate models. Models capture the observed variability in tropical moisture while reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite instruments employed and only cursory agreement with model simulations, primarily relating to the interannual variability associated with the El Niño Southern Oscillation. All datasets display a positive relationship between precipitation and surface temperature but with a large spread. The tendency for wet, ascending regions to become wetter at the expense of dry, descending regimes is in general reproduced. Finally, the frequency of extreme precipitation is shown to rise with warming in the observations and for the model ensemble mean but with large spread in the model simulations. The influence of the Earth’s radiative energy balance in relation to changes in the tropical water cycle are discussed

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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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Quaternary-aged calcrete horizons are common weathering products in arid and semi-arid regions. It is, however, unclear how calcrete forming processes respond to the major oscillations in climate that occur over the Quaternary period. This paper presents a U-series-based calcrete age database from the Sorbas basin, southeast Spain. The study constructs an age frequency distribution of these ages which is consequently compared to a range of palaeoenvironmental records from the Mediterranean. The age distribution presented here suggests that the formation of pedogenic calcrete horizons in the Sorbas basin primarily occurs during 'warm' isotope stages (MIS 1 and 5), with very few calcrete ages occurring during cold glacial/stadial stages (MIS 2, 3 and 4). It is suggested that this is a function of the environments that existed during 'warm' isotope stages being more conducive to calcrete development than those that existed during cold climate episodes. In a semi-arid region such as the Sorbas basin it is likely that increased aridity during glacial stages, coupled with reduced vegetation and accelerated landscape instability, was crucial in reducing rates of calcrete formation. In a semi-arid region such as southeast Spain, calcrete formation during the Quaternary, therefore, oscillates with climate change but is primarily a "warm" episode phenomenon. It is suggested that further studies are required to see how calcrete genesis responds to environmental change in more humid parts of the Mediterranean. (C) 2009 Elsevier B.V. All rights reserved.

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A U-series calcrete chronology has been constructed for three Late Quaternary terrace units, termed the D1, D2 and D3 terraces in age descending order, from the Rio Aguas river system of the Sorbas basin, southeast Spain. The D1 terrace formed between 30,300 +/- 4400 year BP and 12,140 +/- 360 year BP, correlating well with the Last Glacial Maximum when rates of sediment supply would have increased greatly, because of higher rates of weathering, reduced vegetation cover and weak soil development. The D2 terrace formed between 12,800 +/- 1100 year BP and 9,600 +/- 530 year BP, correlating well with the Younger Dryas event. The D3 terrace could only be poorly constrained to the early Holocene and no unequivocal cause could be assigned to this period of aggradation. The sedimentology and geomorphology of the D2 terrace suggests, however, that the aggradation of this unit was a response to diapirism/karstic processes occurring within the underlying Messinian gypsum strata and the subsequent damming of the Aguas system. Therefore, despite its coincident occurrence with the Younger Dryas, aggradation of the D2 terrace is unrelated to climate change. The style of this response, controlled predominantly by the characteristics of the underlying bedrock, makes correlating the terrace record of the Aguas with other systems in the Mediterranean unreliable. This study, therefore, highlights the problems of correlating fluvial sequences in regions of variable tectonics, climatic history and bedrock geology and emphasises the need to properly understand the main controls on individual fluvial systems before any attempt is made to correlate their depositional histories. (C) 2004 Elsevier Ltd. All rights reserved.

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Large temperature variations on land, in the air, and at the ocean surface, and highly variable flux of ice-rafted debris (IRD) delivered to the North Atlantic Ocean show that rapid climate fluctuations took place during the last glacial period. These quasi-periodic, high-amplitude climate variations followed a sequence of events recognized as a rapid warming, followed by a phase of gradual cooling, and terminating with more rapid cooling and increased flux of IRD to the north Atlantic Ocean. Each cycle lasted ˜1500 years, and was followed by an almost identical sequence. These cycles are referred to as Dansgaard/Oechger cycles (D/O cycles), and approximately every fourth cycle culminated in a more pronounced cooling with a massive discharge of IRD into the north Atlantic Ocean over an interval of ˜500 years. These massive discharges of IRD are known as Heinrich layers. “Heinrich events” are thus characterized as a rapid transfer of IRD from a “source,” the bed of the Laurentide Ice Sheet (LIS), to a “sink,” the North Atlantic.