40 resultados para latent tracks


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The North Pacific and Bering Sea regions represent loci of cyclogenesis and storm track activity. In this paper climatological properties of extratropical storms in the North Pacific/Bering Sea are presented based upon aggregate statistics of individual storm tracks calculated by means of a feature-tracking algorithm run using NCEP–NCAR reanalysis data from 1948/49 to 2008, provided by the NOAA/Earth System Research Laboratory and the Cooperative Institute for Research in Environmental Sciences, Climate Diagnostics Center. Storm identification is based on the 850-hPa relative vorticity field (ζ) instead of the often-used mean sea level pressure; ζ is a prognostic field, a good indicator of synoptic-scale dynamics, and is directly related to the wind speed. Emphasis extends beyond winter to provide detailed consideration of all seasons. Results show that the interseasonal variability is not as large during the spring and autumn seasons. Most of the storm variables—genesis, intensity, track density—exhibited a maxima pattern that was oriented along a zonal axis. From season to season this axis underwent a north–south shift and, in some cases, a rotation to the northeast. This was determined to be a result of zonal heating variations and midtropospheric moisture patterns. Barotropic processes have an influence in shaping the downstream end of storm tracks and, together with the blocking influence of the coastal orography of northwest North America, result in high lysis concentrations, effectively making the Gulf of Alaska the “graveyard” of Pacific storms. Summer storms tended to be longest in duration. Temporal trends tended to be weak over the study area. SST did not emerge as a major cyclogenesis control in the Gulf of Alaska.

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Botrytis cinerea occurred commonly on cultivated Primula ×polyantha seed. The fungus was mostly on the outside of the seed but sometimes was present within the seed. The fungus frequently caused disease at maturity in plants grown from the seed, demonstrated by growing plants in a filtered airflow, isolated from other possible sources of infection. Young, commercially produced P. ×polyantha plants frequently had symptomless B. cinerea infections spread throughout the plants for up to 3 months, with symptoms appearing only at flowering. Single genetic individuals of B. cinerea, as determined by DNA fingerprinting, often were dispersed widely throughout an apparently healthy plant. Plants could, however, contain more than one isolate.

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This study tested the hypothesis that aggressive, localized infections and asymptomatic systemic infections were caused by distinct specialized groups of Botrytis cinerea, using microsatellite genotypes at nine loci of 243 isolates of B. cinerea obtained from four hosts (strawberry (Fragaria ´ananassa), blackberry (Rubus fruticosus agg.), dandelion, (Taraxacum of®- cinale agg.) and primrose (Primula vulgaris)) in three regions in southern England (in the vicinities of Brighton, Reading and Bath). The populations were extremely variable, with up to 20 alleles per locus and high genic diversity. Each host in each region had a population of B. cinerea with distinctive genetic features, and there were also consistent host and regional distinctions. The B. cinerea population from strawberry was distinguished from that on other hosts, including blackberry, most notably by a common 154-bp amplicon at locus 5 (present in 35 of 77 samples) that was rare in isolates from other hosts (9¤166), and by the rarity (3¤77) of a 112-bp allele at locus 7 that was common (58¤166) in isolates from other hosts. There was signi®cant linkage disequilibrium overall within the B. cinerea populations on blackberry and strawberry, but with quite different patterns of association among isolates from the two hosts. No evidence was found for differentiation between populations of B. cinerea from systemically infected hosts and those from locally infected fruits.

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Using a recent theoretical approach, we study how global warming impacts the thermodynamics of the climate system by performing experiments with a simplified yet Earth-like climate model. The intensity of the Lorenz energy cycle, the Carnot efficiency, the material entropy production, and the degree of irreversibility of the system change monotonically with the CO2 concentration. Moreover, these quantities feature an approximately linear behaviour with respect to the logarithm of the CO2 concentration in a relatively wide range. These generalized sensitivities suggest that the climate becomes less efficient, more irreversible, and features higher entropy production as it becomes warmer, with changes in the latent heat fluxes playing a predominant role. These results may be of help for explaining recent findings obtained with state of the art climate models regarding how increases in CO2 concentration impact the vertical stratification of the tropical and extratropical atmosphere and the position of the storm tracks.

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A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors.

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The winter climate of Europe and the Mediterranean is dominated by the weather systems of the mid-latitude storm tracks. The behaviour of the storm tracks is highly variable, particularly in the eastern North Atlantic, and has a profound impact on the hydroclimate of the Mediterranean region. A deeper understanding of the storm tracks and the factors that drive them is therefore crucial for interpreting past changes in Mediterranean climate and the civilizations it has supported over the last 12 000 years (broadly the Holocene period). This paper presents a discussion of how changes in climate forcing (e.g. orbital variations, greenhouse gases, ice sheet cover) may have impacted on the ‘basic ingredients’ controlling the mid-latitude storm tracks over the North Atlantic and the Mediterranean on intermillennial time scales. Idealized simulations using the HadAM3 atmospheric general circulation model (GCM) are used to explore the basic processes, while a series of timeslice simulations from a similar atmospheric GCM coupled to a thermodynamic slab ocean (HadSM3) are examined to identify the impact these drivers have on the storm track during the Holocene. The results suggest that the North Atlantic storm track has moved northward and strengthened with time since the Early to Mid-Holocene. In contrast, the Mediterranean storm track may have weakened over the same period. It is, however, emphasized that much remains still to be understood about the evolution of the North Atlantic and Mediterranean storm tracks during the Holocene period.

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Previous studies have shown that sea-ice in the Sea of Okhotsk can be affected by local storms; in turn, the resultant sea-ice changes can affect the downstream development of storm tracks in the Pacific and possibly dampen a pre-existing North Atlantic Oscillation (NAO) signal in late winter. In this paper, a storm tracking algorithm was applied to the six hourly horizontal winds from the National Centers for Environmental Prediction (NCEP) reanalysis data from 1978(9) to 2007 and output from the atmospheric general circulation model (AGCM) ECHAM5 forced by sea-ice anomalies in the Sea of Okhotsk. The life cycle response of storms to sea-ice anomalies is investigated using various aspects of storm activity—cyclone genesis, lysis, intensity and track density. Results show that, for enhanced positive sea-ice concentrations in the Sea of Okhotsk, there is a decrease in secondary cyclogenesis, a westward shift in cyclolysis and changes in the subtropical jet are seen in the North Pacific. In the Atlantic, a pattern resembling the negative phase of the NAO is observed. This pattern is confirmed by the AGCM ECHAM5 experiments driven with above normal sea-ice anomalies in the Sea of Okhotsk

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Building on studies by Brayshaw et al. (2009, 2011) of the basic ingredients of the North Atlantic storm track (land-sea contrast, orography and SST), this article investigates the impact of Eurasian topography and Pacific SST anomalies on the North Pacific and Atlantic storm tracks through a hierarchy of atmospheric GCM simulations using idealised boundary conditions in the HadGAM1 model. The Himalaya-Tibet mountain complex is found to play a crucial role in shaping the North Pacific storm track. The northward deflection of the westerly flow around northern Tibet generates an extensive pool of very cold air in the north-eastern tip of the Asian continent, which strengthens the meridional temperature gradient and favours baroclinic growth in the western Pacific. The Kuroshio SST front is also instrumental in strengthening the Pacific storm track through its impact on near-surface baroclinicity, while the warm waters around Indonesia tend to weaken it through the impact on baroclinicity of stationary Rossby waves propagating poleward from the convective heating regions. Three mechanisms by which the Atlantic storm track may be affected by changes in the boundary conditions upstream of the Rockies are discussed. In the model configuration used here, stationary Rossby waves emanating from Tibet appear to weaken the North Atlantic storm track substantially, whereas those generated over the cold waters off Peru appear to strengthen it. Changes in eddy-driven surface winds over the Pacific generally appear to modify the flow over the Rocky Mountains, leading to consistent modifications in the Atlantic storm track. The evidence for each of these mechanisms is, however, ultimately equivocal in these simulations.

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Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.

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Three years of meteorological data collected at the WLEF-TV tower were used to drive a revised version of the Simple Biosphere (SiB 2.5) Model. Physiological properties and vegetation phenology were specified from satellite imagery. Simulated fluxes of heat, moisture, and carbon were compared to eddy covariance measurements taken onsite as a means of evaluating model performance on diurnal, synoptic, seasonal, and interannual time scales. The model was very successful in simulating variations of latent heat flux when compared to observations, slightly less so in the simulation of sensible heat flux. The model overestimated peak values of sensible heat flux on both monthly and diurnal scales. There was evidence that the differences between observed and simulated fluxes might be linked to wetlands near the WLEF tower, which were not present in the SiB simulation. The model overestimated the magnitude of the net ecosystem exchange of CO2 in both summer and winter. Mid-day maximum assimilation was well represented by the model, but late afternoon simulations showed excessive carbon uptake due to misrepresentation of within-canopy shading in the model. Interannual variability was not well simulated because only a single year of satellite imagery was used to parameterize the model.

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A mesoscale meteorological model (FOOT3DK) is coupled with a gas exchange model to simulate surface fluxes of CO2 and H2O under field conditions. The gas exchange model consists of a C3 single leaf photosynthesis sub-model and an extended big leaf (sun/shade) sub-model that divides the canopy into sunlit and shaded fractions. Simulated CO2 fluxes of the stand-alone version of the gas exchange model correspond well to eddy-covariance measurements at a test site in a rural area in the west of Germany. The coupled FOOT3DK/gas exchange model is validated for the diurnal cycle at singular grid points, and delivers realistic fluxes with respect to their order of magnitude and to the general daily course. Compared to the Jarvis-based big leaf scheme, simulations of latent heat fluxes with a photosynthesis-based scheme for stomatal conductance are more realistic. As expected, flux averages are strongly influenced by the underlying land cover. While the simulated net ecosystem exchange is highly correlated with leaf area index, this correlation is much weaker for the latent heat flux. Photosynthetic CO2 uptake is associated with transpirational water loss via the stomata, and the resulting opposing surface fluxes of CO2 and H2O are reproduced with the model approach. Over vegetated surfaces it is shown that the coupling of a photosynthesis-based gas exchange model with the land-surface scheme of a mesoscale model results in more realistic simulated latent heat fluxes.

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The occurrence of extreme cyclones is analysed in terms of their relationship to the NAO phase and the dominating environmental variables controlling their intensification. These are latent energy (equivalent potential temperature 850 hPa is used as an indicator), upper-air baroclinicity, horizontal divergence and jet stream strength. Cyclones over the North Atlantic are identified and tracked using a numerical algorithm, permitting a detailed analysis of their life cycles. Extreme cyclones are selected as the 10% most severe in terms of intensity. Investigations focus on the main strengthening phase of each cyclone. The environmental factors are related to the NAO, which affects the location and orientation of the cyclone tracks, thus explaining why extreme cyclones occur more (less) frequently during strong positive (negative) NAO phases. The enhanced number of extreme cyclones in positive NAO phases can be explained by the larger area with suitable growth conditions, which is better aligned with the cyclone tracks and is associated with increased cyclone life time and intensity. Moreover, strong intensification of cyclones is frequently linked to the occurrence of extreme values of growth factors in the immediate vicinity of the cyclone centre. Similar results are found for ECHAM5/OM1 for present day conditions, demonstrating that relationships between the environment factors and cyclones are also valid in the GCM. For future climate conditions (following the SRES A1B scenario), the results are similar, but a small increase of the frequency of extreme values is detected near the cyclone cores. On the other hand, total cyclone numbers decrease by 10% over the North Atlantic. An exception is the region near the British Isles, which features increased track density and intensity of extreme cyclones irrespective of the NAO phase. These changes are associated with an intensified jet stream close to Europe. Moreover, an enhanced frequency of explosive developments over the British Isles is found, leading to more frequent windstorms affecting Europe.

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Winter storm-track activity over the Northern Hemisphere and its changes in a greenhouse gas scenario (the Special Report on Emission Scenarios A1B forcing) are computed from an ensemble of 23 single runs from 16 coupled global climate models (CGCMs). All models reproduce the general structures of the observed climatological storm-track pattern under present-day forcing conditions. Ensemble mean changes resulting from anthropogenic forcing include an increase of baroclinic wave activity over the eastern North Atlantic, amounting to 5%–8% by the end of the twenty-first century. Enhanced activity is also found over the Asian continent and over the North Pacific near the Aleutian Islands. At high latitudes and over parts of the subtropics, activity is reduced. Variations of the individual models around the ensemble average signal are not small, with a median of the pattern correlation near r = 0.5. There is, however, no evidence for a link between deviations in present-day climatology and deviations with respect to climate change.