843 resultados para Remote sensor observations

em Publishing Network for Geoscientific


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The Sea Ice Mass Balance in the Antarctic (SIMBA) experiment was conducted from the RVIB N.B. Palmer in September and October 2007 in the Bellingshausen Sea in an area recently experiencing considerable changes in both climate and sea ice cover. Snow and ice properties were observed at 3 short-term stations and a 27-day drift station (Ice Station Belgica, ISB) during the winter-spring transition. Repeat measurements were performed on sea ice and snow cover at 5 ISB sites, each having different physical characteristics, with mean ice (snow) thicknesses varying from 0.6 m (0.1 m) to 2.3 m (0.7 m). Ice cores retrieved every five days from 2 sites and measured for physical, biological, and chemical properties. Three ice mass-balance buoys (IMBs) provided continuous records of snow and ice thickness and temperature. Meteorological conditions changed from warm fronts with high winds and precipitation followed by cold and calm periods through four cycles during ISB. The snow cover regulated temperature flux and controlled the physical regime in which sea ice morphology changed. Level thin ice areas had little snow accumulation and experienced greater thermal fluctuations resulting in brine salinity and volume changes, and winter maximum thermodynamic growth of ~0.6 m in this region. Flooding and snow-ice formation occurred during cold spells in ice and snow of intermediate thickness. In contrast, little snow-ice formed in flooded areas with thicker ice and snow cover, instead nearly isothermal, highly permeable ice persisted. In spring, short-lived cold air episodes did not effectively penetrate the sea ice nor overcome the effect of ocean heat flux, thus favoring net ice thinning from bottom melt over ice thickening from snow-ice growth, in all cases. These warm ice conditions were consistent with regional remote sensing observations of earlier ice breakup and a shorter sea ice season, more recently observed in the Bellingshausen Sea.

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We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.

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Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.

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In this paper, modernized shipborne procedures are presented to collect and process above-water radiometry for remote sensing applications. A setup of five radiometers and a bidirectional camera system, which provides panoramic sea surface and sky images, is proposed for the collection of high-resolution radiometric quantities. Images from the camera system can be used to determine sky state and potential glint, whitecaps, or foam contamination. A peak in the observed remote sensing reflectance RRS spectra between 750-780 nm was typically found in spectra with relatively high surface reflected glint (SRG), which suggests this waveband could be a useful SRG indicator. Simplified steps for computing uncertainties in SRG corrected RRS are proposed and discussed. The potential of utilizing "unweighted multimodel averaging," which is the average of four or more common SRG correction models, is examined to determine the best approximation RRS. This best approximation RRS provides an estimate of RRS based on various SRG correction models established using radiative transfer simulations and field investigations. Applying the average RRS provides a measure of the inherent uncertainties or biases that result from a user subjectively choosing any one SRG correction model. Comparisons between inherent and apparent optical property derived observations were used to assess the robustness of the SRG multimodel averaging ap- proach. Correlations among the standard SRG models were completed to determine the degree of association or similarities between the SRG models. Results suggest that the choice of glint models strongly affects derived RRS values and can also influence the blue to green band ratios used for modeling biogeochemical parameters such as for chlorophyll a. The objective here is to present a uniform and traceable methodology for determining ship- borne RRS measurements and its associated errors due to glint correction and to ensure the direct comparability of these measurements in future investigations. We encourage the ocean color community to publish radiometric field measurements with matching and complete metadata in open access repositories.