22 resultados para Mediterranean-scale correlations

em CentAUR: Central Archive University of Reading - UK


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A methodology is presented for the development of a combined seasonal weather and crop productivity forecasting system. The first stage of the methodology is the determination of the spatial scale(s) on which the system could operate; this determination has been made for the case of groundnut production in India. Rainfall is a dominant climatic determinant of groundnut yield in India. The relationship between yield and rainfall has been explored using data from 1966 to 1995. On the all-India scale, seasonal rainfall explains 52% of the variance in yield. On the subdivisional scale, correlations vary between variance r(2) = 0.62 (significance level p < 10(-4)) and a negative correlation with r(2) = 0.1 (p = 0.13). The spatial structure of the relationship between rainfall and groundnut yield has been explored using empirical orthogonal function (EOF) analysis. A coherent, large-scale pattern emerges for both rainfall and yield. On the subdivisional scale (similar to 300 km), the first principal component (PC) of rainfall is correlated well with the first PC of yield (r(2) = 0.53, p < 10(-4)), demonstrating that the large-scale patterns picked out by the EOFs are related. The physical significance of this result is demonstrated. Use of larger averaging areas for the EOF analysis resulted in lower and (over time) less robust correlations. Because of this loss of detail when using larger spatial scales, the subdivisional scale is suggested as an upper limit on the spatial scale for the proposed forecasting system. Further, district-level EOFs of the yield data demonstrate the validity of upscaling these data to the subdivisional scale. Similar patterns have been produced using data on both of these scales, and the first PCs are very highly correlated (r(2) = 0.96). Hence, a working spatial scale has been identified, typical of that used in seasonal weather forecasting, that can form the basis of crop modeling work for the case of groundnut production in India. Last, the change in correlation between yield and seasonal rainfall during the study period has been examined using seasonal totals and monthly EOFs. A further link between yield and subseasonal variability is demonstrated via analysis of dynamical data.

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We use proper orthogonal decomposition (POD) to study a transient teleconnection event at the onset of the 2001 planet-encircling dust storm on Mars, in terms of empirical orthogonal functions (EOFs). There are several differences between this and previous studies of atmospheric events using EOFs. First, instead of using a single variable such as surface pressure or geopotential height on a given pressure surface, we use a dataset describing the evolution in time of global and fully three-dimensional atmospheric fields such as horizontal velocity and temperature. These fields are produced by assimilating Thermal Emission Spectrometer observations from NASA's Mars Global Surveyor spacecraft into a Mars general circulation model. We use total atmospheric energy (TE) as a physically meaningful quantity which weights the state variables. Second, instead of adopting the EOFs to define teleconnection patterns as planetary-scale correlations that explain a large portion of long time-scale variability, we use EOFs to understand transient processes due to localised heating perturbations that have implications for the atmospheric circulation over distant regions. The localised perturbation is given by anomalous heating due to the enhanced presence of dust around the northern edge of the Hellas Planitia basin on Mars. We show that the localised disturbance is seemingly restricted to a small number (a few tens) of EOFs. These can be classified as low-order, transitional, or high-order EOFs according to the TE amount they explain throughout the event. Despite the global character of the EOFs, they show the capability of accounting for the localised effects of the perturbation via the presence of specific centres of action. We finally discuss possible applications for the study of terrestrial phenomena with similar characteristics.

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By making use of TOVS Path-B satellite retrievals and ECMWF reanalyses, correlations between bulk microphysical properties of large-scale semi-transparent cirrus (visible optical thickness between 0.7 and 3.8) and thermodynamic and dynamic properties of the surrounding atmosphere have been studied on a global scale. These clouds constitute about half of all high clouds. The global averages (from 60°N to 60°S) of mean ice crystal diameter, De, and ice water path (IWP) of these clouds are 55 μm and 30 g m−2, respectively. IWP of these cirrus is slightly increasing with cloud-top temperature, whereas De of cold cirrus does not depend on this parameter. Correlations between De and IWp of large-scale cirrus seem to be different in the midlatitudes and in the tropics. However, we observe in general stronger correlations between De and IWP and atmospheric humidity and winds deduced from the ECMWF reanalyses: De and IWP increase both with increasing atmospheric water vapour. There is also a good distinction between different dynamical situations: In humid situations, IWP is on average about 10 gm−2 larger in regions with strong large-scale vertical updraft only that in regions with strong large-scale horizontal winds only, whereas the mean De of cold large-scale cirrus decreases by about 10 μm if both strong large-scale updraft and horizontal winds are present.

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A climatology of cyclones with a focus on their relation to wind storm tracks in the Mediterranean region (MR) is presented. Trends in the frequency of cyclones and wind storms, as well as variations associated with the North Atlantic Oscillation (NAO), the East Atlantic/West Russian (EAWR) and the Scandinavian variability pattern (SCAND) are discussed. The study is based on the ERA40 reanalysis dataset. Wind storm tracks are identified by tracking clusters of adjacent grid boxes characterised by extremely high local wind speeds. The wind track is assigned to a cyclone track independently identified with an objective scheme. Areas with high wind activity – quantified by extreme wind tracks – are typically located south of the Golf of Genoa, south of Cyprus, southeast of Sicily and west of the Iberian Peninsula. About 69% of the wind storms are caused by cyclones located in the Mediterranean region, while the remaining 31% can be attributed to North Atlantic or Northern European cyclones. The North Atlantic Oscillation, the East Atlantic/West Russian pattern and the Scandinavian pattern all influence the amount and spatial distribution of wind inducing cyclones and wind events in the MR. The strongest signals exist for the NAO and the EAWR pattern, which are both associated with an increase in the number of organised strong wind events in the eastern MR during their positive phase. On the other hand, the storm numbers decrease over the western MR for the positive phase of the NAO and over the central MR during the positive phase of the EAWR pattern. The positive phase of the Scandinavian pattern is associated with a decrease in the number of winter wind storms over most of the MR. A third of the trends in the number of wind storms and wind producing cyclones during the winter season of the ERA40 period may be attributed to the variability of the North Atlantic Oscillation.

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Combined micropaleontological and geochemical analyses of the high-sedimentation gravity core M-4G provided new centennial-scale paleoceanographic data for sapropel S1 deposition in the NE Aegean Sea during the Holocene Climatic Optimum. Sapropel layer S1a (10.2–8.0 ka) was deposited in dysoxic to oxic bottom waters characterized by a high abundance of benthic foraminiferal species tolerating surface sediment and/or pore water oxygen depletion (e.g., Chilostomella mediterranensis, Globobulimina affinis), and the presence of Uvigerina mediterranea, which thrives in oxic mesotrophic-eutrophic environments. Preservation of organic matter (OM) is inferred based on high organic carbon as well as loliolide and isololiolide contents, while the biomarker record and the abundances of eutrophic planktonic foraminifera document enhanced productivity. High inputs of terrigenous OM are attributed to north Aegean borderland riverine inputs. Both alkenone-based sea surface temperatures (SSTs) and δO18G. bulloides records indicate cooling at 8.2 ka (S1a) and ~7.8 ka (S1 interruption). Sapropelic layer S1b (7.7–6.4 ka) is characterized by rather oxic conditions; abundances of foraminiferal species tolerant to oxygen depletion are very low compared with the U. mediterranea rise. Strongly fluctuating SSTs demonstrate repeated cooling and associated dense water formation, with a major event at 7.4 ka followed by cold spells at 7.0, 6.8, and 6.5 ka. The prominent rise of the carbon preference index within the S1b layer indicates the delivery of less degraded terrestrial OM. The increase of algal biomarkers, labile OM-feeding foraminifera and eutrophic planktonic species pinpoints an enhanced in situ marine productivity, promoted by more efficient vertical convection due to repeated cold events. The associated contributions of labile marine OM along with fresher terrestrial OM inputs after ~7.7 ka imply sources alternative/additional to the north Aegean riverine borderland sources for the influx of organic matter in the south Limnos Basin, plausibly related to the inflow of highly productive Marmara/Black Sea waters.

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Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only

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Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data

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The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals

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Palaeoproxy records alone are seldom sufficient to provide a full assessment of regional palaeoclimates. To better understand the possible changes in the Mediterranean climate during the Holocene, a series of palaeoclimate integrations for periods spanning the last 12 000 years have been performed and their results diagnosed. These simulations use the HadSM3 global climate model, which is then dynamically downscaled to approximately 50 km using a consistent regional climate model (HadRM3). Changes in the model’s seasonal-mean surface air temperatures and precipitation are discussed at both global and regional scales, along with the physical mechanisms underlying the changes. It is shown that the global model reproduces many of the large-scale features of the mid-Holocene climate (consistent with previous studies) and that the results suggest that many areas within the Mediterranean region were wetter during winter with a stronger seasonal cycle of surface air temperatures during the early Holocene. This precipitation signal in the regional model is strongest in the in the northeast Mediterranean (near Turkey), consistent with low-level wind patterns and earlier palaeosyntheses. It is, however, suggested that further work is required to fully understand the changes in the winter circulation patterns over the Mediterranean region.

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An account is given of a number of recent studies with idealised models whose aim is to further understanding of the large-scale tropical atmospheric circulation. Initial-value integrations with a model with imposed heating are used to discuss aspects of the Asian summer monsoon, including constraints on cross-equatorial flow into the monsoon. The summer descent in the Mediterranean region and on the eastern sides of the summer subtropical anticyclones are seen to be associated with the monsoons to their east. An aqua-planet GCM is used to investigate the relationship between simple SST distributions and tropical convection and circulation. The existence of strong equatorial convection and Hadley cells is found to depend sensitively on the curvature of the meridional profile in SST. Zonally confined SST maxima produce convective maxima centred to the west and suppression of convection elsewhere. Strong equatorial zonal flow changes are found in some experiments and three mechanisms for producing these are investigated in a model with imposed heating. 1.

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The decline of bees has raised concerns regarding their conservation and the maintenance of ecosystem services they provide to bee-pollinated wild flowers and crops. Although the Mediterranean region is a hotspot for bee species richness, their status remains poorly studied. There is an urgent need for cost-effective, reliable, and unbiased sampling methods that give good bee species richness estimates. This study aims: (a) to assess bee species richness in two common Mediterranean habitat types: semi-natural scrub (phrygana) and managed olive groves; (b) to compare species richness in those systems to that of other biogeographic regions, and (c) to assess whether six different sampling methods (pan traps, variable and standardized transect walks, observation plots and trap nests), previously tested in other European biogeographic regions, are suitable in Mediterranean communities. Eight study sites, four per habitat type, were selected on the island of Lesvos, Greece. The species richness observed was high compared to other habitat types worldwide for which comparable data exist. Pan traps collected the highest proportion of the total bee species richness across all methods at the scale of a study site. Variable and standardized transect walks detected the highest total richness over all eight study sites. Trap nests and observation plots detected only a limited fraction of the bee species richness. To assess the total bee species richness in bee diversity hotspots, such as the studied habitats, we suggest a combination of transect walks conducted by trained bee collectors and pan trap sampling

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We consider two weakly coupled systems and adopt a perturbative approach based on the Ruelle response theory to study their interaction. We propose a systematic way of parameterizing the effect of the coupling as a function of only the variables of a system of interest. Our focus is on describing the impacts of the coupling on the long term statistics rather than on the finite-time behavior. By direct calculation, we find that, at first order, the coupling can be surrogated by adding a deterministic perturbation to the autonomous dynamics of the system of interest. At second order, there are additionally two separate and very different contributions. One is a term taking into account the second-order contributions of the fluctuations in the coupling, which can be parameterized as a stochastic forcing with given spectral properties. The other one is a memory term, coupling the system of interest to its previous history, through the correlations of the second system. If these correlations are known, this effect can be implemented as a perturbation with memory on the single system. In order to treat this case, we present an extension to Ruelle's response theory able to deal with integral operators. We discuss our results in the context of other methods previously proposed for disentangling the dynamics of two coupled systems. We emphasize that our results do not rely on assuming a time scale separation, and, if such a separation exists, can be used equally well to study the statistics of the slow variables and that of the fast variables. By recursively applying the technique proposed here, we can treat the general case of multi-level systems.

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Harvesting the Sea provides the first systematic treatment of the exploitation of various marine resources, such as large-scale fishing, fish salting, salt and purple-dye production, and oyster and fish-farming, in the Roman world and its role within the ancient economy. Bringing together literary, epigraphic, and legal sources, with a wealth of archaeological data collected in recent years, the book shows that these marine resources were an important feature of the Roman economy and, in scope and market-oriented production, paralleled phenomena taking place in the Roman agricultural economy on land. The book also examines the importance of technological innovations, the organization of labour, and the use of the existing legal framework in defence of economic interests against competitors for the same natural resource.

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High-resolution simulations over a large tropical domain (∼20◦S–20◦N and 42◦E–180◦E) using both explicit and parameterized convection are analyzed and compared to observations during a 10-day case study of an active Madden-Julian Oscillation (MJO) event. The parameterized convection model simulations at both 40 km and 12 km grid spacing have a very weak MJO signal and little eastward propagation. A 4 km explicit convection simulation using Smagorinsky subgrid mixing in the vertical and horizontal dimensions exhibits the best MJO strength and propagation speed. 12 km explicit convection simulations also perform much better than the 12 km parameterized convection run, suggesting that the convection scheme, rather than horizontal resolution, is key for these MJO simulations. Interestingly, a 4 km explicit convection simulation using the conventional boundary layer scheme for vertical subgrid mixing (but still using Smagorinsky horizontal mixing) completely loses the large-scale MJO organization, showing that relatively high resolution with explicit convection does not guarantee a good MJO simulation. Models with a good MJO representation have a more realistic relationship between lower-free-tropospheric moisture and precipitation, supporting the idea that moisture-convection feedback is a key process for MJO propagation. There is also increased generation of available potential energy and conversion of that energy into kinetic energy in models with a more realistic MJO, which is related to larger zonal variance in convective heating and vertical velocity, larger zonal temperature variance around 200 hPa, and larger correlations between temperature and ascent (and between temperature and diabatic heating) between 500–400 hPa.