Adaptation and Validation of a Sentinel-Based Chlorophyll-a Retrieval Software for the Central European Freshwater Lake, Balaton

The importance of lakes and reservoirs leads to the high need for monitoring lake water quality both at local and global scales. Remote sensing is a rapidly evolving, versatile technology that can be successfully applied in several economic and scientific fields. Numerous studies demonstrate the applicability of satellites in algae detection and monitoring. Algae play an essential role in aquatic ecosystems, although their overgrowth poses a serious risk. Overgrowth of algae, also known as algal bloom, has serious ecological, social, economic and health effects. The research area of our study was Lake Balaton, the largest lake in Central Europe. The aim was to find the most appropriate algorithm(s) for the inland lake to define the chlorophyll-a amount. In addition, two new algorithms were developed based on the reflectance values of the satellite image. The results show that the two highest correlations were performed by the newly validated, blue/green ratio-based algorithm, Chl-aB/G (r = 0.93) and the chl_re_oc2 algorithm (r = 0.86) of the Acolite software. Although the Acolite software was not developed for lakes but for marine waters, it is also applicable to inland waters.

A tropopause-related climatological a priori profile for IASI-SOFRID ozone retrievals: improvements and validation

The MetOp/Infrared Atmospheric Sounding Interferometer (IASI) instruments have provided data for operational meteorology and document atmospheric composition since 2007. IASI ozone (O3) data have been used extensively to characterize the seasonal and interannual variabilities and the evolution of tropospheric O3 at the global scale. SOftware for a Fast Retrieval of IASI Data (SOFRID) is a fast retrieval algorithm that provides IASI O3 profiles for the whole IASI period. Until now, SOFRID O3 retrievals (v1.5 and v1.6) were performed with a single a priori profile, which resulted in important biases and probably a too-low variability. For the first time, we have implemented a comprehensive dynamical a priori profile for spaceborne O3 retrievals which takes the pixel location, time and tropopause height into account for SOFRID-O3 v3.5 retrievals. In the present study, we validate SOFRID-O3 v1.6 and v3.5 with electrochemical concentration cell (ECC) ozonesonde profiles from the global World Ozone and Ultraviolet Radiation Data Centre (WOUDC) database for the 2008–2017 period. Our validation is based on a thorough statistical analysis using Taylor diagrams. Furthermore, we compare our retrievals with ozonesonde profiles both smoothed by the IASI averaging kernels and raw. This methodology is essential to evaluate the inherent usefulness of the retrievals to assess O3 variability and trends. The use of a dynamical a priori profile largely improves the retrievals concerning two main aspects: (i) it corrects high biases for low-tropospheric O3 regions such as the Southern Hemisphere, and (ii) it increases the retrieved O3 variability, leading to a better agreement with ozonesonde data. Concerning upper troposphere–lower stratosphere (UTLS) and stratospheric O3, the improvements are less important and the biases are very similar for both versions. The SOFRID tropospheric ozone columns (TOCs) display no significant drifts (<2.5 %) for the Northern Hemisphere and significant negative ones (9.5 % for v1.6 and 4.3 % for v3.5) for the Southern Hemisphere. We have compared our validation results to those of the Fast Optimal Retrievals on Layers for IASI (FORLI) retrieval software from the literature for smoothed ozonesonde data only. This comparison highlights three main differences: (i) FORLI retrievals contain more theoretical information about tropospheric O3 than SOFRID; (ii) root mean square differences (RMSDs) are smaller and correlation coefficients are higher for SOFRID than for FORLI; (iii) in the Northern Hemisphere, the 2010 jump detected in FORLI TOCs is not present in SOFRID.

A Semiotic Perspective of Metaphor Translation

This paper reports on a translation project launched at Xi’an International Studies University (XISU) in 2017 that focuses on political news published by Hanban, which offers a platform for instructions and services for Chinese language and culture globally. Assisted by the metaphor identification method MIPVU (Metaphor Identification Procedure from Vrije Universiteit) and the data retrieval software HyConc, metaphors in the self-established corpus were efficiently and comprehensively identified. The metaphors were classified into 12 categories based on metaphorical images in the source domains. Next, an analysis of the cultural, communicative, and political characteristics or features of the metaphors was conducted under the framework of semiotics by using a diversity of images of the metaphors’ corresponding signifier and signified to trace the emergence, processing/understanding, and transformation of the metaphors through translation. Ultimately, three feasible translation techniques are proposed that are suitable for different types of metaphors: 1) preserving the metaphorical image, 2) preserving the metaphorical image with annotation, and 3) transforming the metaphorical image, in pursuit of providing reference for translators in related translation practice.

Toward CO2 and CH4 measurements by ground based observations of surface-scattered sunlight: Radiative transfer modeling

&lt;p&gt;Precise knowledge of sources and sinks in the carbon cycle is desired to understand&lt;br&gt;its sensitivity to climate change and to account and verify man-made emissions. An&lt;br&gt;important role herein play extended sources like urban areas. While in-situ measure-&lt;br&gt;ments of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) and methane (CH&lt;sub&gt;4&lt;/sub&gt;) are highly accurate but localized,&lt;br&gt;satellites measure column-integrated concentrations over an extended footprint. Our&lt;br&gt;innovative measurement technique aims at determining CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; concentrations&lt;br&gt;near to the ground on the scale of a few kilometers and therefore fills the sensitivity&lt;br&gt;gap between in-situ and satellite measurements.&lt;br&gt;Using a modified EM27/SUN Fourier transform spectrometer we are able to record&lt;br&gt;spectra of surface scattered sunlight in the range of 4000 &amp;#8722; 11000 cm&lt;sup&gt;&amp;#8722;1&lt;/sup&gt; . To accurately&lt;br&gt;retrieve CO&lt;sub&gt;2&lt;/sub&gt; and CH&lt;sub&gt;4&lt;/sub&gt; concentrations an advanced retrieval method is required that&lt;br&gt;includes the simultaneous estimation of atmospheric scattering properties.&lt;br&gt;Based on our radiative transfer and retrieval software RemoTeC, we built a simulation&lt;br&gt;environment that includes atmospheric scattering processes. With this tool we can&lt;br&gt;generate and retrieve synthetic scattered light observations. Here we present our&lt;br&gt;simulation environment, first results and ongoing developments.&lt;/p&gt;

Retrieval of atmospheric CH₄ vertical information from ground-based FTS near-infrared spectra

The Total Carbon Column Observing Network (TCCON) column-averaged dry air mole fraction of CH4 (XCH4) measurements have been widely used to validate satellite observations and to estimate model simulations. The GGG2014 code is the standard TCCON retrieval software used in performing a profile scaling retrieval. In order to obtain several vertical pieces of information in addition to the total column, in this study, the SFIT4 retrieval code is applied to retrieve the CH4 mole fraction vertical profile from the Fourier transform spectrometer (FTS) spectrum at six sites (Ny-Ålesund, Sodankylä, Bialystok, Bremen, Orléans and St Denis) during the time period of 2016–2017. The retrieval strategy of the CH4 profile retrieval from ground-based FTS near-infrared (NIR) spectra using the SFIT4 code (SFIT4NIR) is investigated. The degree of freedom for signal (DOFS) of the SFIT4NIR retrieval is about 2.4, with two distinct pieces of information in the troposphere and in the stratosphere. The averaging kernel and error budget of the SFIT4NIR retrieval are presented. The data accuracy and precision of the SFIT4NIR retrievals, including the total column and two partial columns (in the troposphere and stratosphere), are estimated by TCCON standard retrievals, ground-based in situ measurements, Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) satellite observations, TCCON proxy data and AirCore and aircraft measurements. By comparison against TCCON standard retrievals, it is found that the retrieval uncertainty of SFIT4NIR XCH4 is similar to that of TCCON standard retrievals with systematic uncertainty within 0.35 % and random uncertainty of about 0.5 %. The tropospheric and stratospheric XCH4 from SFIT4NIR retrievals are assessed by comparison with AirCore and aircraft measurements, and there is a 1.0 ± 0.3 % overestimation in the SFIT4NIR tropospheric XCH4 and a 4.0 ± 2.0 % underestimation in the SFIT4NIR stratospheric XCH4, which are within the systematic uncertainties of SFIT4NIR-retrieved partial columns in the troposphere and stratosphere respectively.

Study of Corpus’ Influences in EAP Research (2009-2018): A Bibliometric Analysis in CiteSpace

Using 328 papers published in SSCI (Social Science Citation Index) journals from the Web of Science between 2009 and 2018, this study analyzed corpus&rsquo; influences in EAP (English for Academic Purposes) research with mapping knowledge domains CiteSpace. This study found that the relationship between international EAP studies and corpus tends to increasingly tight in the past ten years. Corpus in EAP study mainly acts as the methodology that EAP is studied by means of self-building or existing corpora using retrieval software together with statistical analysis method. International scholars pay more attention to writing teaching, academic literacy and discourse/discourse analysis in EAP study, and the co-cited references mostly tend to the genres study of EAP.

THE WORLD IN PIECES: AARON EINBOND

Aaron Einbond was born in New York in 1978. He received his compositional education in the US (Harvard, University of California, Berkeley), the UK (Cambridge, Royal College of Music) and France (IRCAM), and his teachers have included Mario Davidovsky, Julian Anderson, Edmund Campion and Philippe Leroux. He currently teaches music composition, sound and technology at City University, London. He is interested in applications of technology within instrumental music, and almost all of his works combine electronics and acoustic instruments. Since 2007 – beginning with his piece Beside Oneself for viola and electronics (first performed by Ellen Ruth Rose), composed while studying at the University of California, Berkeley – he has also used audio analysis and retrieval software to transcribe recorded sounds into instrumental notation.Einbond's interest in phonographic transcription connects his work to that of other composers of his generation, including Patricia Alessandrini, Joanna Bailie, Richard Beaudoin and Cassandra Miller. (It also finds precedents in a wider musical interest in forms of transcription that one can find in the music of composers as diverse as Peter Ablinger, Luciano Berio and Michael Finnissy.) What makes Einbond's work distinctive is his focus on timbre as a musical parameter, rather than more abstract or easily quantifiable values such as pitch.

Sistem Temu Kembali Informasi Pada Gejala Autisme Dengan Metode Vector Space Model

Information is now very easy to get anywhere. Information technology, especially the internet, strongly supports the exchange of information very quickly. The internet has become an information and communication media that has been used by many people with many interests, especially in taking large-scale information data, Unfortunately the information presented is sometimes less relevant. Quality information is influenced by relevance, accuracy and on time. However, there are not many effective search systems available. This study discusses the implementation of an information retrieval system to find and find symptoms of autism disorders using the Vector Space Model (VSM) method. Vector Space Model (VSM) is a model used to measure the similarity between a document and a query. In this model, queries and documents are considered vectors in n dimensional space. Where n is the number of all terms listed. The purpose of this study was to design an information retrieval software to find and match the symptoms of autism disorders. By using Vector Space Model, it is hoped that it can provide a solution to the search engine to provide text matching information in the database using certain keywords, the results of the matching are presented in the form of ranks.

Retrieval of atmospheric CH₄ vertical information from TCCON FTIR spectra

TCCON (Total Carbon Column Observing Network) column-averaged dry air mole fraction of CH4 (XCH4) measurements have been widely used to validate satellite observations and to estimate model simulations. The GGG2014 code is the standard TCCON retrieval software performing a profile scaling retrieval. In order to obtain several vertical information in addition to total column, in this study, the SFIT4 retrieval code is applied to retrieve CH4 mole fraction vertical profile using TCCON spectra (SFIT4TCCON) at six sites (Ny-Ålesund, Sodankylä, Bialystok, Bremen, Orléans and St Denis) during the time period of 2016−2017. The retrieval strategy of SFIT4TCCON is investigated. The degree of freedom for signal of the SFIT4TCCON retrieval is about 2.4, with two distinct species of information in the troposphere and in the stratosphere. The averaging kernel and error budget of the SFIT4TCCON retrieval are presented. The data accuracy and precision of the SFIT4TCCON retrievals, including the total column and two partial columns (in the troposphere and stratosphere), are estimated by TCCON standard retrievals, ground-based in situ measurements, ACE-FTS satellite observations, TCCON proxy data and AirCore measurements. By comparison against TCCON standard retrievals, it is found that the retrieval uncertainty of SFIT4TCCON XCH4 is similar to that of TCCON standard retrievals with the systematic uncertainty within 0.35 % and the random uncertainty about 0.5 %. The tropospheric and stratospheric XCH4 from SFIT4TCCON retrievals are assessed by comparing with AirCore measurements at Sodankylä, and there is a 1.2 % overestimation in the SFIT4TCCON tropospheric XCH4 and a 4.0 % underestimation in the SFIT4TCCON stratospheric XCH4, which are within the systematic uncertainties of SFIT4TCCON retrieved partial columns in the troposphere and stratosphere, respectively.