A Calibrated Time Domain Envelope Measurement System for the Behavioral Modeling of Power Amplifiers

This paper presents a set-up which enables the generation and the calibrated time domain measurements of complex envelopes of modulated signals at both ports of non linear microwave power amplifiers. The architecture of the characterization tool is given. Examples of error corrected time domain envelopes at the input / output RF ports of a 36 dBm output power – 30dB power gain L-band SSPA are shown. Futhermore, the use of this characterization tool and a suitable processing of measurement data are applied to a novel measurement based behavioral modeling approach of non linear devices accounting for memory effects

Measurements of hydrogen cyanide (HCN) and acetylene (C2H2) from the Infrared Atmospheric Sounding Interferometer (IASI)

Hydrogen cyanide (HCN) and acetylene (C2H2) are ubiquitous atmospheric trace gases with medium lifetime, which are frequently used as indicators of combustion sources and as tracers for atmospheric transport and chemistry. Because of their weak infrared absorption, overlapped by the CO2 Q branch near 720 cm−1, nadir sounders have up to now failed to measure these gases routinely. Taking into account CO2 line mixing, we provide for the first time extensive measurements of HCN and C2H2 total columns at Reunion Island (21° S, 55° E) and Jungfraujoch (46° N, 8° E) in 2009–2010 using observations from the Infrared Atmospheric Sounding Interferometer (IASI). A first order comparison with local ground-based Fourier transform InfraRed (FTIR) measurements has been carried out allowing tests of seasonal consistency which is reasonably captured, except for HCN at Jungfraujoch. The IASI data shows a greater tendency to high C2H2 values. We also examine a nonspecific biomass burning plume over austral Africa and show that the emission ratios with respect to CO agree with previously reported values

Construction, visualisation, and clustering of transcription networks from microarray expression data.

Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express(3D)

The evaluation of SCIAMACHY CO and CH_4 scientific data products, using ground-based FTIR measurements

In the framework of the European EVERGREEN project, three scientific algorithms, namely WFM-DOAS, IMAPDOAS and IMLM, have been developed to retrieve the total column amounts of key atmospheric trace gases including CO and CH_4 from SCIAMACHY nadir observations in its near-infrared channels. These channels offer the capability to detect trace gases in the planetary boundary layer, potentially making the associated retrieval products suited for regional source-sink studies. The retrieval products of these three algorithms, in their present status of development, have been compared to independent data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers, for the year 2003. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of coincidences that satisfy the temporal and spatial collocation criteria, the individual SCIAMACHY data points have been compared with a 3rd order polynomial interpolation of the ground-based data with time. Particular attention has been paid to the question whether the products reproduce correctly the seasonal and latitudinal variabilities of the target species. We present an overall assessment of the data quality of the currently available latest versions of the CO and CH4 total column products from the three scientific retrieval algorithms

The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO₂ and CH₄ retrieval algorithm products with measurements from the TCCON

Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS (Thermal And Near-infrared Sensor for carbon Observations-Fourier Transform Spectrometer) and SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) instruments on board GOSAT (Greenhouse gases Observing SATellite) and ENVISAT (ENVIronmental SATellite), respectively, using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier transform spectrometers (FTSs) from the Total Carbon Column Observing Network (TCCON). The participating algorithms are the weighting function modified differential optical absorption spectroscopy (DOAS) algorithm (WFMD, University of Bremen), the Bremen optimal estimation DOAS algorithm (BESD, University of Bremen), the iterative maximum a posteriori DOAS (IMAP, Jet Propulsion Laboratory (JPL) and Netherlands Institute for Space Research algorithm (SRON)), the proxy and full-physics versions of SRON's RemoTeC algorithm (SRPR and SRFP, respectively) and the proxy and full-physics versions of the University of Leicester's adaptation of the OCO (Orbiting Carbon Observatory) algorithm (OCPR and OCFP, respectively). The goal of this algorithm inter-comparison was to identify strengths and weaknesses of the various so-called round- robin data sets generated with the various algorithms so as to determine which of the competing algorithms would proceed to the next round of the European Space Agency's (ESA) Greenhouse Gas Climate Change Initiative (GHG-CCI) project, which is the generation of the so-called Climate Research Data Package (CRDP), which is the first version of the Essential Climate Variable (ECV) "greenhouse gases" (GHGs). For XCO₂, all algorithms reach the precision requirements for inverse modelling (< 8 ppm), with only WFMD having a lower precision (4.7 ppm) than the other algorithm products (2.4–2.5 ppm). When looking at the seasonal relative accuracy (SRA, variability of the bias in space and time), none of the algorithms have reached the demanding < 0.5 ppm threshold. For XCH₄, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fails to meet the < 34 ppb threshold for inverse modelling, but note that this work focusses on the period after the 2005 SCIAMACHY detector degradation. The GOSAT XCH₄ precision ranges between 18.1 and 14.0 ppb. Looking at the SRA, all GOSAT algorithm products reach the < 10 ppm threshold (values ranging between 5.4 and 6.2 ppb). For SCIAMACHY, IMAP and WFMD have a SRA of 17.2 and 10.5 ppb, respectively