590 resultados para Aqua-modis


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Lake water temperature (LWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Consequently, the Global Climate Observing System (GCOS) lists LWT as an essential climate variable. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years, offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT) data set for European water bodies in or near the Alps based on the extensive AVHRR 1 km data record (1989–2013) of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14) and AVHRR/3 (NOAA-16, -17, -18, -19 and MetOp-A) data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV) Version 10 together with ERA-interim reanalysis data from the European Centre for Medium-range Weather Forecasts. The resulting LSWTs were extensively compared with in situ measurements from lakes with various sizes between 14 and 580 km2 and the resulting biases and RMSEs were found to be within the range of −0.5 to 0.6 K and 1.0 to 1.6 K, respectively. The upper limits of the reported errors could be rather attributed to uncertainties in the data comparison between in situ and satellite observations than inaccuracies of the satellite retrieval. An inter-comparison with the standard Moderate-resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature product exhibits RMSEs and biases in the range of 0.6 to 0.9 and −0.5 to 0.2 K, respectively. The cross-platform consistency of the retrieval was found to be within ~ 0.3 K. For one lake, the satellite-derived trend was compared with the trend of in situ measurements and both were found to be similar. Thus, orbital drift is not causing artificial temperature trends in the data set. A comparison with LSWT derived through global sea surface temperature (SST) algorithms shows lower RMSEs and biases for the simulation-based approach. A running project will apply the developed method to retrieve LSWT for all of Europe to derive the climate signal of the last 30 years. The data are available at doi:10.1594/PANGAEA.831007.

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post ed. Germanicam 3. Latine elaboravit multisque modis retractavit et auxit Guil. Gesenius

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Tiefengrundwasser findet sich in allen grosstektonischen Einheiten der Schweiz. Die bekannten, teilweise genutzten Vorkommen von Tiefengrundwas-ser und insbesondere die chemische Zusammensetzung dieser Wässer wird für die verschiedenen Einheiten aufgezeigt. Im Hinblick auf mögliche Nutzungskon-flikte werden die gesetzlichen Grundlagen und Massnahmen zum Schutz dieser Ressource diskutiert.

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Erwähnt in Nagler: Monogrammisten

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The dataset contains a cropland percent coverage map for Africa created through the combination of five existing land cover products: GLC-2000, MODIS Land Cover, GlobCover, MODIS Crop Likelihood and AfriCover. A synergy map was created in which the products are ranked by experts, which reflects the likelihood or probability that a given pixel is cropland. The cropland map was calibrated with national and sub-national crop statistics using a novel approach. Preliminary validation of the map was undertaken. The resulting cropland map has an accuracy of 83%, which is higher than the accuracy of any of the individual maps. The cropland percent coverage map for Africa is available for overlay on Google Earth or for download at http://agriculture.geo-wiki.org.

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The euphotic depth (Zeu) is a key parameter in modelling primary production (PP) using satellite ocean colour. However, evaluations of satellite Zeu products are scarce. The objective of this paper is to investigate existing approaches and sensors to estimate Zeu from satellite and to evaluate how different Zeu products might affect the estimation of PP in the Southern Ocean (SO). Euphotic depth was derived from MODIS and SeaWiFS products of (i) surface chlorophyll-a (Zeu-Chla) and (ii) inherent optical properties (Zeu-IOP). They were compared with in situ measurements of Zeu from different regions of the SO. Both approaches and sensors are robust to retrieve Zeu, although the best results were obtained using the IOP approach and SeaWiFS data, with an average percentage of error (E) of 25.43% and mean absolute error (MAE) of 0.10 m (log scale). Nevertheless, differences in the spatial distribution of Zeu-Chla and Zeu-IOP for both sensors were found as large as 30% over specific regions. These differences were also observed in PP. On average, PP based on Zeu-Chla was 8% higher than PP based on Zeu-IOP, but it was up to 30% higher south of 60°S. Satellite phytoplankton absorption coefficients (aph) derived by the Quasi-Analytical Algorithm at different wavelengths were also validated and the results showed that MODIS aph are generally more robust than SeaWiFS. Thus, MODIS aph should be preferred in PP models based on aph in the SO. Further, we reinforce the importance of investigating the spatial differences between satellite products, which might not be detected by the validation with in situ measurements due to the insufficient amount and uneven distribution of the data.

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Extreme winter warming events in the sub-Arctic have caused considerable vegetation damage due to rapid changes in temperature and loss of snow cover. The frequency of extreme weather is expected to increase due to climate change thereby increasing the potential for recurring vegetation damage in Arctic regions. Here we present data on vegetation recovery from one such natural event and multiple experimental simulations in the sub-Arctic using remote sensing, handheld passive proximal sensors and ground surveys. Normalized difference vegetation index (NDVI) recovered fast (2 years), from the 26% decline following one natural extreme winter warming event. Recovery was associated with declines in dead Empetrum nigrum (dominant dwarf shrub) from ground surveys. However, E. nigrum healthy leaf NDVI was also reduced (16%) following this winter warming event in experimental plots (both control and treatments), suggesting that non-obvious plant damage (i.e., physiological stress) had occurred in addition to the dead E. nigrum shoots that was considered responsible for the regional 26% NDVI decline. Plot and leaf level NDVI provided useful additional information that could not be obtained from vegetation surveys and regional remote sensing (MODIS) alone. The major damage of an extreme winter warming event appears to be relatively transitory. However, potential knock-on effects on higher trophic levels (e.g., rodents, reindeer, and bear) could be unpredictable and large. Repeated warming events year after year, which can be expected under winter climate warming, could result in damage that may take much longer to recover.

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The North Water (NOW) Polynya is a regularly-forming area of open-water and thin-ice, located between northwestern Greenland and Ellesmere Island (Canada) at the northern tip of Baffin Bay. Due to its large spatial extent, it is of high importance for a variety of physical and biological processes, especially in wintertime. Here, we present a long-term remote sensing study for the winter seasons 1978/1979 to 2014/2015. Polynya characteristics are inferred from (1) sea ice concentrations and brightness temperatures from passive microwave satellite sensors (Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS)) and (2) thin-ice thickness distributions, which are calculated using MODIS ice-surface temperatures and European Center for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis data in a 1D thermodynamic energy-balance model. Daily ice production rates are retrieved for each winter season from 2002/2003 to 2014/2015, assuming that all heat loss at the ice surface is balanced by ice growth. Two different cloud-cover correction schemes are applied on daily polynya area and ice production values to account for cloud gaps in the MODIS composites. Our results indicate that the NOW polynya experienced significant seasonal changes over the last three decades considering the overall frequency of polynya occurrences, as well as their spatial extent. In the 1980s, there were prolonged periods of a more or less closed ice cover in northern Baffin Bay in winter. This changed towards an average opening on more than 85% of the days between November and March during the last decade. Noticeably, the sea ice cover in the NOW polynya region shows signs of a later-appearing fall freeze-up, starting in the late 1990s. Different methods to obtain daily polynya area using passive microwave AMSR-E/AMSR2 data and SSM/I-SSMIS data were applied. A comparison with MODIS data (thin-ice thickness < 20 cm) shows that the wintertime polynya area estimates derived by MODIS are about 30 to 40% higher than those derived using the polynya signature simulation method (PSSM) with AMSR-E data. In turn, the difference in polynya area between PSSM and a sea ice concentration (SIC) threshold of 70% is fairly low (approximately 10%) when applied to AMSR-E data. For the coarse-resolution SSM/I-SSMIS data, this difference is much larger, particularly in November and December. Instead of a sea ice concentration threshold, the PSSM method should be used for SSM/I-SSMIS data. Depending on the type of cloud-cover correction, the calculated ice production based on MODIS data reaches an average value of 264.4 ± 65.1 km**3 to 275.7 ± 67.4 km**3 (2002/2003 to 2014/2015) and shows a high interannual variability. Our achieved long-term results underline the major importance of the NOW polynya considering its influence on Arctic ice production and associated atmosphere/ocean processes.

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Abstract has to submitted by author

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By incorporating recently available remote sensing data, we investigated the mass balance for all individual tributary glacial basins of the Lambert Glacier-Amery Ice Shelf system, East Antarctica. On the basis of the ice flow information derived from SAR interferometry and ICESat laser altimetry, we have determined the spatial configuration of eight tributary drainage basins of the Lambert-Amery glacial system. By combining the coherence information from SAR interferometry and the texture information from SAR and MODIS images, we have interpreted and refined the grounding line position. We calculated ice volume flux of each tributary glacial basin based on the ice velocity field derived from Radarsat three-pass interferometry together with ice thickness data interpolated from Australian and Russian airborne radio echo sounding (RES) surveys and inferred from ICESat laser altimetry data. Our analysis reveals that three tributary basins have a significant net positive imbalance, while five other subbasins are slightly positive or close to zero balance. Overall, in contrast to previous studies, we find that the grounded ice in Lambert Glacier-Amery Ice Shelf system has a positive mass imbalance of 22.9 ± 4.4 Gt/a. The net basal melting for the entire Amery Ice Shelf is estimated to be 27.0 ± 7.0 Gt/a. The melting rate decreases rapidly from the grounding zone to the ice shelf front. Significant basal refreezing is detected in the downstream section of the ice shelf. The mass balance estimates for both the grounded ice sheet and the ice shelf mass differ substantially from other recent estimates.

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Lake ice change is one of the sensitive indicators of regional and global climate change. Different sources of data are used in monitoring lake ice phenology nowadays. Visible and Near Infrared bands of imagery (VNIR) are well suited for the observation of freshwater ice change, for example data from AVHRR and MODIS. Active and passive microwave data are also used for the observation of lake ice, e.g., from satellite altimetry and radiometry, backscattering coefficient from QuickSCAT, brightness temperature (Tb) from SSM/I, SMMR, and AMSR-E. Most of the studies are about lake ice cover phenology, while few studies focus on lake ice thickness. For example, Hall et al. using 5 GHz (6 cm) radiometer data showed a good relationship between Tb and ice thickness. Kang et al. found the seasonal evolution of Tb at 10.65 GHz and 18.7 GHz from AMSR-E to be strongly influenced by ice thickness. Many studies on lake ice phenology have been carried out since the 1970s in cold regions, especially in Canada, the USA, Europe, the Arctic, and Antarctica. However, on the Tibetan Plateau, very little research has focused on lake ice-cover change; only a small number of published papers on Qinghai Lake ice observations. The main goal of this study is to investigate the change in lake ice phenology at Nam Co on the Tibetan Plateau using MODIS and AMSR-E data (monitoring the date of freeze onset, the formation of stable ice cover, first appearance of water, and the complete disappearance of ice) during the period 2000-2009.

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High-latitude ecosystems play an important role in the global carbon cycle and in regulating the climate system and are presently undergoing rapid environmental change. Accurate land cover data sets are required to both document these changes as well as to provide land-surface information for benchmarking and initializing Earth system models. Earth system models also require specific land cover classification systems based on plant functional types (PFTs), rather than species or ecosystems, and so post-processing of existing land cover data is often required. This study compares over Siberia, multiple land cover data sets against one another and with auxiliary data to identify key uncertainties that contribute to variability in PFT classifications that would introduce errors in Earth system modeling. Land cover classification systems from GLC 2000, GlobCover 2005 and 2009, and MODIS collections 5 and 5.1 are first aggregated to a common legend, and then compared to high-resolution land cover classification systems, vegetation continuous fields (MODIS VCFs) and satellite-derived tree heights (to discriminate against sparse, shrub, and forest vegetation). The GlobCover data set, with a lower threshold for tree cover and taller tree heights and a better spatial resolution, tends to have better distributions of tree cover compared to high-resolution data. It has therefore been chosen to build new PFT maps for the ORCHIDEE land surface model at 1 km scale. Compared to the original PFT data set, the new PFT maps based on GlobCover 2005 and an updated cross-walking approach mainly differ in the characterization of forests and degree of tree cover. The partition of grasslands and bare soils now appears more realistic compared with ground truth data. This new vegetation map provides a framework for further development of new PFTs in the ORCHIDEE model like shrubs, lichens and mosses, to represent the water and carbon cycles in northern latitudes better. Updated land cover data sets are critical for improving and maintaining the relevance of Earth system models for assessing climate and human impacts on biogeochemistry and biophysics.