950 resultados para temperature dependance
Resumo:
The optically stimulated luminescence (OSL) signal within quartz may be enhanced by thermal transfer during pre-heating. This may occur via a thermally induced charge transfer from low temperature traps to the OSL traps. Thermal transfer may affect both natural and artificially irradiated samples. The effect, as empirically measured via recuperation tests, is typically observed to be negligible for old samples (<1% of natural signal). However, thermal transfer remains a major concern in the dating of young samples as thermal decay and transfers of geologically unstable traps (typically in the TL range 160–280°C) may be incomplete. Upon pre-heating such a sample might undergo thermal transfer to the dating trap and result in a De overestimate. As a result, there has been a tendency for workers to adopt less rigorous pre-heats for young samples. We have investigated the pre-heat dependence of 23 young quartz samples from various depositional environments using pre-heats between 170°C and 300°C, employing the single aliquot regeneration (SAR) protocol. SAR De's were also calculated for 25 additional young quartz samples of different depositional environments and compared with previous multiple aliquot additive dose (MAAD) data. Results demonstrate no significant De dependence upon pre-heat temperatures. A close correspondence between MAAD data and the current SAR data for the samples tested is also illustrated.
Resumo:
Centennial-scale records of sea-surface temperature and opal composition spanning the Last Glacial Maximum and Termination 1 (circa 25–6 ka) are presented here from Guaymas Basin in the Gulf of California. Through the application of two organic geochemistry proxies, the U37K′ index and the TEX86H index, we present evidence for rapid, stepped changes in temperatures during deglaciation. These occur in both temperature proxies at 13 ka (∼3°C increase in 270 years), 10.0 ka (∼2°C decrease over ∼250 years) and at 8.2 ka (3°C increase in <200 years). An additional rapid warming step is also observed in TEX86H at 11.5 ka. In comparing the two temperature proxies and opal content, we consider the potential for upwelling intensity to be recorded and link this millennial-scale variability to shifting Intertropical Convergence Zone position and variations in the strength of the Subtropical High. The onset of the deglacial warming from 17 to 18 ka is comparable to a “southern hemisphere” signal, although the opal record mimics the ice-rafting events of the north Atlantic (Heinrich events). Neither the modern seasonal cycle nor El Niño/Southern Oscillation patterns provide valid analogues for the trends we observe in comparison with other regional records. Fully coupled climate model simulations confirm this result, and in combination we question whether the seasonal or interannual climate variations of the modern climate are valid analogues for the glacial and deglacial tropical Pacific.
Resumo:
Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.
Resumo:
Observations at the Mauna Loa Observatory, Hawaii, established the systematic increase of anthropogenic CO2 in the atmosphere. For the same reasons that this site provides excellent globally averaged CO2 data, it may provide temperature data with global significance. Here, we examine hourly temperature records, averaged annually for 1977–2006, to determine linear trends as a function of time of day. For night-time data (22:00 to 06:00 LST (local standard time)) there is a near-uniform warming of 0.040 °C yr−1. During the day, the linear trend shows a slight cooling of −0.014 °C yr−1 at 12:00 LST (noon). Overall, at Mauna Loa Observatory, there is a mean warming trend of 0.021 °C yr−1. The dominance of night-time warming results in a relatively large annual decrease in the diurnal temperature range (DTR) of −0.050 °C yr−1 over the period 1977–2006. These trends are consistent with the observed increases in the concentrations of CO2 and its role as a greenhouse gas (demonstrated here by first-order radiative forcing calculations), and indicate the possible relevance of the Mauna Loa temperature measurements to global warming.
Resumo:
Peculiar reduction pathways of the complexes fac-[Re(imH)(CO)3(phen)]+ and fac-[Re(imCH3)(CO)3(phen)]+ (imH = imidazole, imCH3 = N-methylimidazole and phen = 1,10-phenanthroline) have been unravelled by performing combined cyclic voltammetric and in situ IR spectroelectrochemical experiments. In the temperature range of 293–233 K, the initial reduction of the phen ligand in [Re(imH)(CO)3(phen)]+ results in irreversible conversion of the imidazole ligand to 3-imidazolate by a rapid phen•−→ imH intramolecular electron transfer coupled with N H bond cleavage. This process is followed by second phen-localized 1e− reduction producing [ReI(3-im−)(CO)3(phen•−)]−, similar to the analogous 2,2'-bipyridine complex. In contrast to the bpy analogue, the stability of the phen•−-containing complexes is significantly affected by lowering the temperature. At 233 K, a secondary reaction occurs in both [Re(3-im−)(CO)3(phen•−)]− and [Re(imCH3)(CO)3(phen•−)]. The resulting products exhibit v(CO) wavenumbers indistinguishable from those of the parent phen•− complexes; however, their oxidation occurs at a considerably more positive electrode potential. It is proposed that these species are produced by a new C C bond formation between the C(2) site of 3-im− or imCH3 and the C(2) site of the phen•−ligand.
Resumo:
Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.Useful probabilistic climate forecasts on decadal timescales should be reliable (i.e. forecast probabilities match the observed relative frequencies) but this is seldom examined. This paper assesses a necessary condition for reliability, that the ratio of ensemble spread to forecast error being close to one, for seasonal to decadal sea surface temperature retrospective forecasts from the Met Office Decadal Prediction System (DePreSys). Factors which may affect reliability are diagnosed by comparing this spread-error ratio for an initial condition ensemble and two perturbed physics ensembles for initialized and uninitialized predictions. At lead times less than 2 years, the initialized ensembles tend to be under-dispersed, and hence produce overconfident and hence unreliable forecasts. For longer lead times, all three ensembles are predominantly over-dispersed. Such over-dispersion is primarily related to excessive inter-annual variability in the climate model. These findings highlight the need to carefully evaluate simulated variability in seasonal and decadal prediction systems.
Resumo:
Considerable effort is presently being devoted to producing high-resolution sea surface temperature (SST) analyses with a goal of spatial grid resolutions as low as 1 km. Because grid resolution is not the same as feature resolution, a method is needed to objectively determine the resolution capability and accuracy of SST analysis products. Ocean model SST fields are used in this study as simulated “true” SST data and subsampled based on actual infrared and microwave satellite data coverage. The subsampled data are used to simulate sampling errors due to missing data. Two different SST analyses are considered and run using both the full and the subsampled model SST fields, with and without additional noise. The results are compared as a function of spatial scales of variability using wavenumber auto- and cross-spectral analysis. The spectral variance at high wavenumbers (smallest wavelengths) is shown to be attenuated relative to the true SST because of smoothing that is inherent to both analysis procedures. Comparisons of the two analyses (both having grid sizes of roughly ) show important differences. One analysis tends to reproduce small-scale features more accurately when the high-resolution data coverage is good but produces more spurious small-scale noise when the high-resolution data coverage is poor. Analysis procedures can thus generate small-scale features with and without data, but the small-scale features in an SST analysis may be just noise when high-resolution data are sparse. Users must therefore be skeptical of high-resolution SST products, especially in regions where high-resolution (~5 km) infrared satellite data are limited because of cloud cover.
Resumo:
With a wide range of applications benefiting from dense network air temperature observations but with limitations of costs, existing siting guidelines and risk of damage to sensors, new methods are required to gain a high resolution understanding of the spatio-temporal patterns of urban meteorological phenomena such as the urban heat island or precision farming needs. With the launch of a new generation of low cost sensors it is possible to deploy a network to monitor air temperature at finer spatial resolutions. Here we investigate the Aginova Sentinel Micro (ASM) sensor with a bespoke radiation shield (together < US$150) which can provide secure near-real-time air temperature data to a server utilising existing (or user deployed) Wireless Fidelity (Wi-Fi) networks. This makes it ideally suited for deployment where wireless communications readily exist, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors < ± 0.22 °C between -25 and 30 °C, with a time constant in ambient air of 110 ± 15 s. Subsequent field tests of it within the bespoke shield also had excellent performance (root-mean-square error = 0.13 °C) over a range of meteorological conditions relative to a traceable operational UK Met Office platinum resistance thermometer. These results indicate that the ASM and bespoke shield are more than fit-for-purpose for dense network deployment in urban areas at relatively low cost compared to existing observation techniques.
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We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.
Resumo:
We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8-9 % over SADIST (maximum score of 77.93 % compared to 69.27 %). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3x3 pixel domain. We find an increase of 5-7 % in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02 % compared to 85.69 %). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).
Resumo:
Artificial diagenesis of the intra-crystalline proteins isolated from Patella vulgata was induced by isothermal heating at 140 °C, 110 °C and 80 °C. Protein breakdown was quantified for multiple amino acids, measuring the extent of peptide bond hydrolysis, amino acid racemisation and decomposition. The patterns of diagenesis are complex; therefore the kinetic parameters of the main reactions were estimated by two different methods: 1) a well-established approach based on fitting mathematical expressions to the experimental data, e.g. first-order rate equations for hydrolysis and power-transformed first-order rate equations for racemisation; and 2) an alternative model-free approach, which was developed by estimating a “scaling” factor for the independent variable (time) which produces the best alignment of the experimental data. This method allows the calculation of the relative reaction rates for the different temperatures of isothermal heating. High-temperature data were compared with the extent of degradation detected in sub-fossil Patella specimens of known age, and we evaluated the ability of kinetic experiments to mimic diagenesis at burial temperature. The results highlighted a difference between patterns of degradation at low and high temperature and therefore we recommend caution for the extrapolation of protein breakdown rates to low burial temperatures for geochronological purposes when relying solely on kinetic data.
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The sensitivity of sea breeze structure to sea surface temperature (SST) and coastal orography is investigated in convection-permitting Met Office Unified Model simulations of a case study along the south coast of England. Changes in SST of 1 K are shown to significantly modify the structure of the sea breeze immediately offshore. On the day of the case study, the sea breeze was partially blocked by coastal orography, particularly within Lyme Bay. The extent to which the flow is blocked depends strongly on the static stability of the marine boundary layer. In experiments with colder SST, the marine boundary layer is more stable, and the degree of blocking is more pronounced. Although a colder SST would also imply a larger land–sea temperature contrast and hence a stronger onshore wind – an effect which alone would discourage blocking – the increased static stability exerts a dominant control over whether blocking takes place. The implications of prescribing fixed SST from climatology in numerical weather prediction model forecasts of the sea breeze are discussed.
Resumo:
Positive-stranded viruses synthesize their RNA in membrane-bound organelles, but it is not clear how this benefits the virus or the host. For coronaviruses, these organelles take the form of double-membrane vesicles (DMVs) interconnected by a convoluted membrane network. We used electron microscopy to identify murine coronaviruses with mutations in nsp3 and nsp14 that replicated normally while producing only half the normal amount of DMVs. Viruses with mutations in nsp5 and nsp16 produced small DMVs but also replicated normally. Quantitative RT-PCR confirmed that the most strongly affected of these, the nsp3 mutant, produced more viral RNA than wild-type virus. Competitive growth assays were carried out in both continuous and primary cells to better understand the contribution of DMVs to viral fitness. Surprisingly, several viruses that produced fewer or smaller DMVs showed a higher relative fitness compared to wild-type virus, suggesting that larger and more numerous DMVs do not necessarily confer a competitive advantage in primary or continuous cell culture. For the first time, this directly demonstrates that replication and organelle formation may be, at least in part, studied separately during positive-stranded RNA virus infection.
Resumo:
We study the orientational ordering on the surface of a sphere using Monte Carlo and Brownian dynamics simulations of rods interacting with an anisotropic potential. We restrict the orientations to the local tangent plane of the spherical surface and fix the position of each rod to be at a discrete point on the spherical surface. On the surface of a sphere, orientational ordering cannot be perfectly nematic due to the inevitable presence of defects. We find that the ground state of four +1/2 point defects is stable across a broad range of temperatures. We investigate the transition from disordered to ordered phase by decreasing the temperature and find a very smooth transition. We use fluctuations of the local directors to estimate the Frank elastic constant on the surface of a sphere and compare it to the planar case. We observe subdiffusive behavior in the mean square displacement of the defect cores and estimate their diffusion constants.
Resumo:
Extreme temperature during reproductive development affects rice (Oryza sativa L.) yield and seed quality. A controlled-environment reciprocal-transfer experiment was designed where plants from two japonica cultivars were grown at 28/24 ⁰C and moved to 18/14 ⁰C and vice versa, or from 28/24 to 38/34 ⁰C and vice versa, for 7-d periods to determine the respective temporal pattern of sensitivity of spikelet fertility, yield, and seed viability to each temperature extreme. Spikelet fertility and seed yield per panicle were severely reduced by extreme temperature in the 14 d period prior to anthesis; and both cultivars were affected at 38/34 ⁰C while only cv. Gleva was affected at 18/14 ºC. The damage was greater the earlier the panicles were stressed within this period. Later-exserted panicles compensated only partly for yield loss. Seed viability was significantly reduced by 7-d exposure to 38/34 ⁰C or 18/14 ⁰C at 1 to 7 and 1 to 14 d after anthesis, respectively, in cv. Gleva. Cultivar Taipei 309 was not affected by 7 d exposure at 18/14 ⁰C; and no consistent temporal pattern of sensitivity was evident at 38/34 ⁰C. Hence, brief exposure to low or high temperature was most damaging to spikelet fertility and yield 14 to 7 d before anthesis, coinciding with microsporogenesis; and it was almost as damaging around anthesis. Seed viability was most vulnerable to low or high temperature in the 7 or 14 d after anthesis, when histodifferentiation occurs.