Fant 9884 publikasjoner. Viser side 268 av 396:
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The Tibetan Plateau (TP) region, often referred to as the Third Pole, is the world's highest plateau and exerts a considerable influence on regional and global climate. The state of the snowpack over the TP is a major research focus due to its great impact on the headwaters of a dozen major Asian rivers. While many studies have attempted to validate atmospheric reanalyses over the TP area in terms of temperature or precipitation, there have been – remarkably – no studies aimed at systematically comparing the snow depth or snow cover in global reanalyses with satellite and in situ data. Yet, snow in reanalyses provides critical surface information for forecast systems from the medium to sub-seasonal timescales.
Here, snow depth and snow cover from four recent global reanalysis products, namely the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 and ERA-Interim reanalyses, the Japanese 55-year Reanalysis (JRA-55) and the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-2), are inter-compared over the TP region. The reanalyses are evaluated against a set of 33 in situ station observations, as well as against the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover and a satellite microwave snow depth dataset. The high temporal correlation coefficient (0.78) between the IMS snow cover and the in situ observations provides confidence in the station data despite the relative paucity of in situ measurement sites and the harsh operating conditions.
While several reanalyses show a systematic overestimation of the snow depth or snow cover, the reanalyses that assimilate local in situ observations or IMS snow cover are better capable of representing the shallow, transient snowpack over the TP region. The latter point is clearly demonstrated by examining the family of reanalyses from the ECMWF, of which only the older ERA-Interim assimilated IMS snow cover at high altitudes, while ERA5 did not consider IMS snow cover for high altitudes. We further tested the sensitivity of the ERA5-Land model in offline experiments, assessing the impact of blown snow sublimation, snow cover to snow depth conversion and, more importantly, excessive snowfall. These results suggest that excessive snowfall might be the primary factor for the large overestimation of snow depth and cover in ERA5 reanalysis. Pending a solution for this common model precipitation bias over the Himalayas and the TP, future snow reanalyses that optimally combine the use of satellite snow cover and in situ snow depth observations in the assimilation and analysis cycles have the potential to improve medium-range to sub-seasonal forecasts for water resources applications.
European Geosciences Union (EGU)
2019
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2014
Low-risk removal of embedded surface soiling on delicate heritage objects can require novel alternatives to traditional cleaning systems. Edvard Munch’s monumental Aula paintings (1911–16) have a long history of exposure to atmospheric pollution and cleaning campaigns that have compromised the appearance and the condition of these important artworks. Soiling removal from porous and water-sensitive, unvarnished oil paintings continues to be a major conservation challenge. This paper presents the approach and results of research into the effect and efficiency of three novel systems used for soiling removal: soft particle blasting, CO2-snow blasting, and Nanorestore Gel® Dry and Peggy series hydrogels. Cleaning tests were performed on accelerated-aged and artificially soiled mock-ups consisting of unvarnished oil paint and chalk-glue grounds. Visual and analytical assessment (magnification using a light microscope and scanning electron microscope, as well as colour- and gloss measurement) was carried out before and after mock-up cleaning tests and the results were compared to those obtained using the dry polyurethane sponges employed in the most recent Aula surface cleaning campaign (2009–11). Although the results varied, the Nanorestore Gel® series proved promising with respect to improved soiling removal efficiency, and reduced pigment loss for the water-sensitive surfaces evaluated, compared to dry sponges.
Springer
2021
Evaluation of new data sources for improving the estimation of background concentrations in Norway. NILU OR
A previous report (OR 68/2011) described a geostatistical methodology developed for creating a consistent dataset of background concentrations of NO2, O3, PM10, and PM2.5 in Norway, that are representative of a typical year. The resulting dataset has a resolution of 0.1 degrees by 0.1 degrees and is available at hourly temporal resolution. Based on this existing methodology, this study reports on the evaluation of new data sources as a means of improving such estimates of background concentrations. The potential of satellite-derived NO2 data is evaluated for guiding the geostatistics-based spatial interpolation procedure of NO2 station data in Norway. Furthermore, the output from a high-resolution atmospheric model was tested with respect to its capability of improving the spatial and temporal characterization of background concentrations. Finally, an online web mapping system was developed to make the project results easily accessible and to provide basic data analysis and visualization routines for the public.
2013
2022