1,721,008 research outputs found
A high-resolution gridded dataset of daily temperature and precipitation records (1980-2018) for Trentino-South Tyrol (north-eastern Italian Alps)
No full textA high-resolution gridded dataset of daily mean temperature and precipitation series spanning the period 1980-2018 was built for Trentino-South Tyrol, a mountainous region in north-eastern Italy, starting from an archive of observation series from more than 200 meteorological stations and covering the regional domain and surrounding countries. The original station data underwent a processing chain including quality and consistency checks, homogeneity tests, with the homogenization of the most relevant breaks in the series, and a filling procedure of daily gaps aiming at maximizing the data availability. Using the processed database, an anomaly-based interpolation scheme was applied to project the daily station observations of mean temperature and precipitation onto a regular grid of 250g mg ×g 250g m resolution. The accuracy of the resulting dataset was evaluated by leave-one-out station cross-validation. Averaged over all sites, interpolated daily temperature and precipitation show no bias, with a mean absolute error (MAE) of about 1.5g g C and 1.1g mm and a mean correlation of 0.97 and 0.91, respectively. The obtained daily fields were used to discuss the spatial representation of selected past events and the distribution of the main climatological features over the region, which shows the role of the mountainous terrain in defining the temperature and precipitation gradients. In addition, the suitability of the dataset to be combined with other high-resolution products was evaluated through a comparison of the gridded observations with snow-cover maps from remote sensing observations. The presented dataset provides an accurate insight into the spatio-temporal distribution of temperature and precipitation over the mountainous terrain of Trentino-South Tyrol and a valuable support for local and regional applications of climate variability and change. The dataset is publicly available at 10.1594/PANGAEA.924502 (Crespi et al., 2020)
Mapping particulate matter in alpine regions with satellite and ground-based measurements: An exploratory study for data assimilation
No full textThe objective of this study is the integration of satellite and in-situ measurements of particulate matter (PM10) to provide PM10 maps in Switzerland and South Tyrol (Italy) on an operational daily basis. Satellite retrieval of PM has been widely investigated in the past years, showing moderate potential (uncertainty of ∼30%) but also a number of severe limitations (e.g., due to cloud and snow cover or unknown aerosol extinction profiles). Its actual effectiveness can only be tested by a comparison with the mapping capability of ground-based measurements from existing air-quality networks. Moreover, the integration of both observational systems (assimilation) can improve PM mapping. Herein, we apply a linear model including aerosol optical depth (AOD) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and meteorological boundary layer height (BLH) to estimate spatially homogeneous maps of PM10 over the study region in 2008-2009. AOD from MODIS is used to compare the results with those of similar studies. The validation of the satellite maps reveals higher accuracy in flat areas (r ∼ 0.6, RMSE ∼ 10 μg m-3) than in alpine valleys and elevated sites. In contrast, the inverse distance interpolation of in-situ measurements is able to produce more accurate (r > 0.8, RMSE < 6 μg m-3) PM10 maps. An assimilation schema was developed considering the interpolation of ground measurements as a background field, updating it with satellite observations wherever they are available. The accuracy of the assimilated maps is assessed and compared to the background fields. It is found that satellite data is of limited benefit in the considered region due to the good spatial coverage of the ground networks and the difficulties inherent to the satellite PM retrieval over rugged topography. The results of the assimilation are positive (∼1 μg m-3 improvement in RMSE) when a number of ground sites (80%) are excluded. It is concluded that satellite data are of higher interest for regions with a sparser distribution of measurement sites (e.g., distance > 100 km between sites). © 2011 Elsevier Ltd
Evaluating snow in EURO-CORDEX regional climate models with observations for the european alps: Biases and their relationship to orography, temperature, and precipitation mismatches
Full text linkClimate models are important tools to assess current and future climate. While they have been extensively used for studying temperature and precipitation, only recently regional climate models (RCMs) arrived at horizontal resolutions that allow studies of snow in complex mountain terrain. Here, we present an evaluation of the snow variables in theWorld Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) RCMs with gridded observations of snow cover (from MODIS remote sensing) and temperature and precipitation (E-OBS), as well as with point (station) observations of snow depth and temperature for the European Alps. Large scale snow cover dynamics were reproduced well with some over-and under-estimations depending on month and RCM. The orography, temperature, and precipitation mismatches could on average explain 31% of the variability in snow cover bias across grid-cells, and even more than 50% in the winter period November-April. Biases in average monthly snow depth were remarkably low for reanalysis driven RCMs
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Forest biodiversity estimated from optical and LiDAR data: testing the spectral variation hypothesis and the height variation hypothesis through the Rao’s Q index
Full text linkVariations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
High spatial resolution aerosol retrieval with MAIAC: Application to mountain regions
No full textAerosol spatial distribution in populated mountain areas is very heterogeneous and often characterized by scales of variability of several kilometers. Satellites provide an effective tool to map aerosols on an operational basis, but most of the aerosol products intended for continental/global applications have a coarse spatial resolution (10-18 km). The Multiangle Implementation of Atmospheric Correction (MAIAC) is a recently developed algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS), which provides Aerosol Optical Depth (AOD) at a high resolution of 1 km. We analyze the quality and potential of MAIAC AOD in the Alpine region and we derive high resolution AOD maps for the years 2008 and 2009. Cloudiness and snow in mountain regions occasionally lead to an overestimation of AOD due to unresolved cloud and snow pixel contamination. Therefore, we developed a filter that almost preserves the spatial resolution of the product to ensure the good accuracy of MAIAC AOD for air-quality and climatological applications. The AOD is validated with AERONET measurements in the region and compared to the standard MODIS AOD product (MOD04). Similar accuracies are found for both products (RMSE = 0.05) but with MAIAC providing about 50% more observations at the examined locations, because of its higher spatial resolution and less restrictive filtering. Comparison with ground measurements of aerosol mass (PM10) shows that MAIAC AOD can be used to detect the fine scales of aerosol variability (2-3 km) in the mountains. Finally, AOD maps for the Alpine region demonstrate that topography is correlated with the average aerosol spatial distribution. Copyright 2011 by the American Geophysical Union
PM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region
No full textThe subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10km and 2 measurements per day for MODIS, ~25km and observation intervals of 15min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV~0.7, rMOD~0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r~0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas. © 2010 Elsevier Inc
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