6 resultados para Radiometers

em Publishing Network for Geoscientific


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Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I-SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I-SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000-2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis.

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The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the RV Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which we compared to ecological provinces proposed elsewhere in the literature. As could be expected, picophytoplankton was responsible for most of the variability of PFTs in the eastern Atlantic Ocean. Our bio-optical clusters agreed well with established provinces and thus can be used to classify areas of similar biogeography. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.

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We map the weekly position of the Antarctic Polar Front (PF) in the Southern Ocean over a 12-year period (2002-2014) using satellite sea surface temperature (SST) estimated from cloud-penetrating microwave radiometers. Our study advances previous efforts to map the PF using hydrographic and satellite data and provides a unique realization of the PF at weekly resolution across all longitudes. The mean path of the PF is asymmetric; its latitudinal position spans from 44 to 64° S along its circumpolar path. SST at the PF ranges from 0.6 to 6.9 °C, reflecting the large spread in latitudinal position. The average intensity of the front is 1.7 °C per 100 km, with intensity ranging from 1.4 to 2.3 °C per 100 km. Front intensity is significantly correlated with the depth of bottom topography, suggesting that the front intensifies over shallow bathymetry. Realizations of the PF are consistent with the corresponding surface expressions of the PF estimated using expendable bathythermograph data in the Drake Passage and Australian and African sectors. The climatological mean position of the PF is similar, though not identical, to previously published estimates. As the PF is a key indicator of physical circulation, surface nutrient concentration, and biogeography in the Southern Ocean, future studies of physical and biogeochemical oceanography in this region will benefit from the provided data set.

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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.

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Measurements of solar radiation over and under sea ice have been performed on various stations in the Arctic Ocean during the Polarstern cruise PS92 (TRANSSIZ) between 19 May and 30 June 2015. All radiation measurements have been performed with Ramses spectral radiometers (Trios, Rastede, Germany). All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors were mounted on a Remotely Operated Vehicle (ROV) and one radiometer was installed on the sea ice for surface reference measurements (solar irradiance). On the ROV, one irradiance sensor (cos-collector) for energy budget calculations and one radiance sensor (9° opening angle) to obtain high resolution spatial variability were installed. Along with the radiation measurements, ROV positions were obtained from acoustic USBL-positioning and all parameters of vehicle depth, distance to the ice and attitude recorded. All times are given in UTC.

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Arctic sea ice has declined and become thinner and younger (more seasonal) during the last decade. One consequence of this is that the surface energy budget of the Arctic Ocean is changing. While the role of surface albedo has been studied intensively, it is still widely unknown how much light penetrates through sea ice into the upper ocean, affecting sea-ice mass balance, ecosystems, and geochemical processes. Here we present the first large-scale under-ice light measurements, operating spectral radiometers on a remotely operated vehicle (ROV) under Arctic sea ice in summer. This data set is used to produce an Arctic-wide map of light distribution under summer sea ice. Our results show that transmittance through first-year ice (FYI, 0.11) was almost three times larger than through multi-year ice (MYI, 0.04), and that this is mostly caused by the larger melt-pond coverage of FYI (42 vs. 23%). Also energy absorption was 50% larger in FYI than in MYI. Thus, a continuation of the observed sea-ice changes will increase the amount of light penetrating into the Arctic Ocean, enhancing sea-ice melt and affecting sea-ice and upper-ocean ecosystems.