910 resultados para Sea gods.


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We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

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The retrieval (estimation) of sea surface temperatures (SSTs) from space-based infrared observations is increasingly performed using retrieval coefficients derived from radiative transfer simulations of top-of-atmosphere brightness temperatures (BTs). Typically, an estimate of SST is formed from a weighted combination of BTs at a few wavelengths, plus an offset. This paper addresses two questions about the radiative transfer modeling approach to deriving these weighting and offset coefficients. How precisely specified do the coefficients need to be in order to obtain the required SST accuracy (e.g., scatter <0.3 K in week-average SST, bias <0.1 K)? And how precisely is it actually possible to specify them using current forward models? The conclusions are that weighting coefficients can be obtained with adequate precision, while the offset coefficient will often require an empirical adjustment of the order of a few tenths of a kelvin against validation data. Thus, a rational approach to defining retrieval coefficients is one of radiative transfer modeling followed by offset adjustment. The need for this approach is illustrated from experience in defining SST retrieval schemes for operational meteorological satellites. A strategy is described for obtaining the required offset adjustment, and the paper highlights some of the subtler aspects involved with reference to the example of SST retrievals from the imager on the geostationary satellite GOES-8.

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AOGCMs of the two latest phases (CMIP3 and CMIP5) of the Coupled Model Intercomparison Project, like earlier AOGCMs, predict large regional variations in future sea level change. The model-mean pattern of change in CMIP3 and CMIP5 is very similar, and its most prominent feature is a zonal dipole in the Southern Ocean: sea level rise is larger than the global mean north of 50°S and smaller than the global mean south of 50°S in most models. The individual models show widely varying patterns, although the inter-model spread in local sea level change is smaller in CMIP5 than in CMIP3. Here we investigate whether changes in windstress can explain the different patterns of projected sea level change, especially the Southern Ocean feature, using two AOGCMs forced by the changes in windstress from the CMIP3 and CMIP5 AOGCMs. We show that the strengthening and poleward shift of westerly windstress accounts for the most of the large spread among models in magnitude of this feature. In the Indian, North Pacific and Arctic Oceans, the windstress change is influential, but does not completely account for the projected sea level change.

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During the last century, global climate has been warming, and projections indicate that such a warming is likely to continue over coming decades. Most of the extra heat is stored in the ocean, resulting in thermal expansion of seawater and global mean sea level rise. Previous studies have shown that after CO2 emissions cease or CO2 concentration is stabilized, global mean surface air temperature stabilizes or decreases slowly, but sea level continues to rise. Using idealized CO2 scenario simulations with a hierarchy of models including an AOGCM and a step-response model, the authors show how the evolution of thermal expansion can be interpreted in terms of the climate energy balance and the vertical profile of ocean warming. Whereas surface temperature depends on cumulative CO2 emissions, sea level rise due to thermal expansion depends on the time profile of emissions. Sea level rise is smaller for later emissions, implying that targets to limit sea level rise would need to refer to the rate of emissions, not only to the time integral. Thermal expansion is in principle reversible, but to halt or reverse it quickly requires the radiative forcing to be reduced substantially, which is possible on centennial time scales only by geoengineering. If it could be done, the results indicate that heat would leave the ocean more readily than it entered, but even if thermal expansion were returned to zero, the geographical pattern of sea level would be altered. Therefore, despite any aggressive CO2 mitigation, regional sea level change is inevitable.

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Fieldwalking in the Ginosar valley recorded an extensive spread of Late Hellenistic, Roman-period and Byzantine ceramics, tesserae, glass shards, and stone vessel fragments. Architectural stonework in modern Migdal, on the hilltop immediately west of this, seems, in part, to derive from the same site, which extended into the area of the present town. This suggests an urban centre immediately adjacent to, but probably separate from, the Roman-period site usually identified asMagdala, providing a context for the first-century boat currently displayed in the Yigdal Allon museum. The settlement may be identified with one of the un-located toponyms of the coast.

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A steady decline in Arctic sea ice has been observed over recent decades. General circulation models predict further decreases under increasing greenhouse gas scenarios. Sea ice plays an important role in the climate system in that it influences ocean-to-atmosphere fluxes, surface albedo, and ocean buoyancy. The aim of this study is to isolate the climate impacts of a declining Arctic sea ice cover during the current century. The Hadley Centre Atmospheric Model (HadAM3) is forced with observed sea ice from 1980 to 2000 (obtained from satellite passive microwave radiometer data derived with the Bootstrap algorithm) and predicted sea ice reductions until 2100 under one moderate scenario and one severe scenario of ice decline, with a climatological SST field and increasing SSTs. Significant warming of the Arctic occurs during the twenty-first century (mean increase of between 1.6° and 3.9°C), with positive anomalies of up to 22°C locally. The majority of this is over ocean and limited to high latitudes, in contrast to recent observations of Northern Hemisphere warming. When a climatological SST field is used, statistically significant impacts on climate are only seen in winter, despite prescribing sea ice reductions in all months. When correspondingly increasing SSTs are incorporated, changes in climate are seen in both winter and summer, although the impacts in summer are much smaller. Alterations in atmospheric circulation and precipitation patterns are more widespread than temperature, extending down to midlatitude storm tracks. Results suggest that areas of Arctic land ice may even undergo net accumulation due to increased precipitation that results from loss of sea ice. Intensification of storm tracks implies that parts of Europe may experience higher precipitation rates.

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There are significant discrepancies between observational datasets of Arctic sea ice concentrations covering the last three decades, which result in differences of over 20% in Arctic summer sea ice extent/area and 5%–10% in winter. Previous modeling studies have shown that idealized sea ice anomalies have the potential for making a substantial impact on climate. In this paper, this theory is further developed by performing a set of simulations using the third Hadley Centre Coupled Atmospheric Model (HadAM3). The model was driven with monthly climatologies of sea ice fractions derived from three of these records to investigate potential implications of sea ice inaccuracies for climate simulations. The standard sea ice climatology from the Met Office provided a control. This study focuses on the effects of actual inaccuracies of concentration retrievals, which vary spatially and are larger in summer than winter. The smaller sea ice discrepancies in winter have a much larger influence on climate than the much greater summer sea ice differences. High sensitivity to sea ice prescription was observed, even though no SST feedbacks were included. Significant effects on surface fields were observed in the Arctic, North Atlantic, and North Pacific. Arctic average surface air temperature anomalies in winter vary by 2.5°C, and locally exceed 12°C. Arctic mean sea level pressure varies by up to 5 mb locally. Anomalies extend to 45°N over North America and Eurasia but not to lower latitudes, and with limited changes in circulation above the boundary layer. No statistically significant impact on climate variability was simulated, in terms of the North Atlantic Oscillation. Results suggest that the uncertainty in summer sea ice prescription is not critical but that winter values require greater accuracy, with the caveats that the influences of ocean–sea ice feedbacks were not included in this study.