912 resultados para curriculum-based measurement
Resumo:
The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of 2 years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC or rBC and sulfate concentrations quite well, compared to previous comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January–March underestimated by 59 and 37 % for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44 % for July–September), but with overestimates as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is 3 times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anti-correlation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution.
Resumo:
Collocations between two satellite sensors are occasions where both sensors observe the same place at roughly the same time. We study collocations between the Microwave Humidity Sounder (MHS) on-board NOAA-18 and the Cloud Profiling Radar (CPR) on-board CloudSat. First, a simple method is presented to obtain those collocations and this method is compared with a more complicated approach found in literature. We present the statistical properties of the collocations, with particular attention to the effects of the differences in footprint size. For 2007, we find approximately two and a half million MHS measurements with CPR pixels close to their centrepoints. Most of those collocations contain at least ten CloudSat pixels and image relatively homogeneous scenes. In the second part, we present three possible applications for the collocations. Firstly, we use the collocations to validate an operational Ice Water Path (IWP) product from MHS measurements, produced by the National Environment Satellite, Data and Information System (NESDIS) in the Microwave Surface and Precipitation Products System (MSPPS). IWP values from the CloudSat CPR are found to be significantly larger than those from the MSPPS. Secondly, we compare the relation between IWP and MHS channel 5 (190.311 GHz) brightness temperature for two datasets: the collocated dataset, and an artificial dataset. We find a larger variability in the collocated dataset. Finally, we use the collocations to train an Artificial Neural Network and describe how we can use it to develop a new MHS-based IWP product. We also study the effect of adding measurements from the High Resolution Infrared Radiation Sounder (HIRS), channels 8 (11.11 μm) and 11 (8.33 μm). This shows a small improvement in the retrieval quality. The collocations described in the article are available for public use.
Resumo:
We present cross-validation of remote sensing measurements of methane profiles in the Canadian high Arctic. Accurate and precise measurements of methane are essential to understand quantitatively its role in the climate system and in global change. Here, we show a cross-validation between three datasets: two from spaceborne instruments and one from a ground-based instrument. All are Fourier Transform Spectrometers (FTSs). We consider the Canadian SCISAT Atmospheric Chemistry Experiment (ACE)-FTS, a solar occultation infrared spectrometer operating since 2004, and the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for carbon Observation (TANSO)-FTS, a nadir/off-nadir scanning FTS instrument operating at solar and terrestrial infrared wavelengths, since 2009. The ground-based instrument is a Bruker 125HR Fourier Transform Infrared (FTIR) spectrometer, measuring mid-infrared solar absorption spectra at the Polar Environment Atmospheric Research Laboratory (PEARL) Ridge Lab at Eureka, Nunavut (80° N, 86° W) since 2006. For each pair of instruments, measurements are collocated within 500 km and 24 h. An additional criterion based on potential vorticity values was found not to significantly affect differences between measurements. Profiles are regridded to a common vertical grid for each comparison set. To account for differing vertical resolutions, ACE-FTS measurements are smoothed to the resolution of either PEARL-FTS or TANSO-FTS, and PEARL-FTS measurements are smoothed to the TANSO-FTS resolution. Differences for each pair are examined in terms of profile and partial columns. During the period considered, the number of collocations for each pair is large enough to obtain a good sample size (from several hundred to tens of thousands depending on pair and configuration). Considering full profiles, the degrees of freedom for signal (DOFS) are between 0.2 and 0.7 for TANSO-FTS and between 1.5 and 3 for PEARL-FTS, while ACE-FTS has considerably more information (roughly 1° of freedom per altitude level). We take partial columns between roughly 5 and 30 km for the ACE-FTS–PEARL-FTS comparison, and between 5 and 10 km for the other pairs. The DOFS for the partial columns are between 1.2 and 2 for PEARL-FTS collocated with ACE-FTS, between 0.1 and 0.5 for PEARL-FTS collocated with TANSO-FTS or for TANSO-FTS collocated with either other instrument, while ACE-FTS has much higher information content. For all pairs, the partial column differences are within ± 3 × 1022 molecules cm−2. Expressed as median ± median absolute deviation (expressed in absolute or relative terms), these differences are 0.11 ± 9.60 × 10^20 molecules cm−2 (0.012 ± 1.018 %) for TANSO-FTS–PEARL-FTS, −2.6 ± 2.6 × 10^21 molecules cm−2 (−1.6 ± 1.6 %) for ACE-FTS–PEARL-FTS, and 7.4 ± 6.0 × 10^20 molecules cm−2 (0.78 ± 0.64 %) for TANSO-FTS–ACE-FTS. The differences for ACE-FTS–PEARL-FTS and TANSO-FTS–PEARL-FTS partial columns decrease significantly as a function of PEARL partial columns, whereas the range of partial column values for TANSO-FTS–ACE-FTS collocations is too small to draw any conclusion on its dependence on ACE-FTS partial columns.
An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI
Resumo:
In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.
Resumo:
Ruminant husbandry is a major source of anthropogenic greenhouse gases (GHG). Filling knowledge gaps and providing expert recommendation are important for defining future research priorities, improving methodologies and establishing science-based GHG mitigation solutions to government and non-governmental organisations, advisory/extension networks, and the ruminant livestock sector. The objectives of this review is to summarize published literature to provide a detailed assessment of the methodologies currently in use for measuring enteric methane (CH4) emission from individual animals under specific conditions, and give recommendations regarding their application. The methods described include respiration chambers and enclosures, sulphur hexafluoride tracer (SF6) technique, and techniques based on short-term measurements of gas concentrations in samples of exhaled air. This includes automated head chambers (e.g. the GreenFeed system), the use of carbon dioxide (CO2) as a marker, and (handheld) laser CH4 detection. Each of the techniques are compared and assessed on their capability and limitations, followed by methodology recommendations. It is concluded that there is no ‘one size fits all’ method for measuring CH4 emission by individual animals. Ultimately, the decision as to which method to use should be based on the experimental objectives and resources available. However, the need for high throughput methodology e.g. for screening large numbers of animals for genomic studies, does not justify the use of methods that are inaccurate. All CH4 measurement techniques are subject to experimental variation and random errors. Many sources of variation must be considered when measuring CH4 concentration in exhaled air samples without a quantitative or at least regular collection rate, or use of a marker to indicate (or adjust) for the proportion of exhaled CH4 sampled. Consideration of the number and timing of measurements relative to diurnal patterns of CH4 emission and respiratory exchange are important, as well as consideration of feeding patterns and associated patterns of rumen fermentation rate and other aspects of animal behaviour. Regardless of the method chosen, appropriate calibrations and recovery tests are required for both method establishment and routine operation. Successful and correct use of methods requires careful attention to detail, rigour, and routine self-assessment of the quality of the data they provide.
Resumo:
Measurements of down-welling microwave radiation from raining clouds performed with the Advanced Microwave Radiometer for Rain Identification (ADMIRARI) radiometer at 10.7-21-36.5 GHz during the Global Precipitation Measurement Ground Validation ""Cloud processes of the main precipitation systems in Brazil: A contribution to cloud resolving modeling and to the Global Precipitation Measurement"" (CHUVA) campaign held in Brazil in March 2010 represent a unique test bed for understanding three-dimensional (3D) effects in microwave radiative transfer processes. While the necessity of accounting for geometric effects is trivial given the slant observation geometry (ADMIRARI was pointing at a fixed 30 elevation angle), the polarization signal (i.e., the difference between the vertical and horizontal brightness temperatures) shows ubiquitousness of positive values both at 21.0 and 36.5 GHz in coincidence with high brightness temperatures. This signature is a genuine and unique microwave signature of radiation side leakage which cannot be explained in a 1D radiative transfer frame but necessitates the inclusion of three-dimensional scattering effects. We demonstrate these effects and interdependencies by analyzing two campaign case studies and by exploiting a sophisticated 3D radiative transfer suited for dichroic media like precipitating clouds.
Resumo:
This paper presents the use of a multiprocessor architecture for the performance improvement of tomographic image reconstruction. Image reconstruction in computed tomography (CT) is an intensive task for single-processor systems. We investigate the filtered image reconstruction suitability based on DSPs organized for parallel processing and its comparison with the Message Passing Interface (MPI) library. The experimental results show that the speedups observed for both platforms were increased in the same direction of the image resolution. In addition, the execution time to communication time ratios (Rt/Rc) as a function of the sample size have shown a narrow variation for the DSP platform in comparison with the MPI platform, which indicates its better performance for parallel image reconstruction.
Measurement of the energy spectrum of cosmic rays above 10(18) eV using the Pierre Auger Observatory
Resumo:
We report a measurement of the flux of cosmic rays with unprecedented precision and Statistics using the Pierre Auger Observatory Based on fluorescence observations in coincidence with at least one Surface detector we derive a spectrum for energies above 10(18) eV We also update the previously published energy spectrum obtained with the surface detector array The two spectra are combined addressing the systematic uncertainties and, in particular. the influence of the energy resolution on the spectral shape The spectrum can be described by a broken power law E(-gamma) with index gamma = 3 3 below the ankle which is measured at log(10)(E(ankle)/eV) = 18 6 Above the ankle the spectrum is described by a power law with index 2 6 followed by a flux suppression, above about log(10)(E/eV) = 19 5, detected with high statistical significance (C) 2010 Elsevier B V All rights reserved
Resumo:
This thesis evaluates different sites for a weather measurement system and a suitable PV- simulation for University of Surabaya (UBAYA) in Indonesia/Java. The weather station is able to monitor all common weather phenomena including solar insolation. It is planned to use the data for scientific and educational purposes in the renewable energy studies. During evaluation and installation it falls into place that official specifications from global meteorological organizations could not be meet for some sensors caused by the conditions of UBAYA campus. After arranging the hardware the weather at the site was monitored for period of time. A comparison with different official sources from ground based and satellite bases measurements showed differences in wind and solar radiation. In some cases the monthly average solar insolation was deviating 42 % for satellite-based measurements. For the ground based it was less than 10 %. The average wind speed has a difference of 33 % compared to a source, which evaluated the wind power in Surabaya. The wind direction shows instabilities towards east compared with data from local weather station at the airport. PSET has the chance to get some investments to investigate photovoltaic on there own roof. With several simulations a suitable roof direction and the yearly and monthly outputs are shown. With a 7.7 kWpeak PV installation with the latest crystalline technology on the market 8.82 MWh/year could be achieved with weather data from 2012. Thin film technology could increase the value up to 9.13 MWh/year. However, the roofs have enough area to install PV. Finally the low price of electricity in Indonesia makes it not worth to feed in the energy into the public grid.
Resumo:
The focus of this article is on relations between classroom interaction, curricular knowledge and student engagement in diverse classrooms. It is based on a study with ethnographic perspective in which two primary school classes in Sweden were followed for three years. The analysis draws on Halliday's Systemic Functional Linguistics. The results indicate that language use in the classrooms is on a basic everyday level and that high teacher control results in low-demanding tasks and low engagement among students. Interaction in the classrooms mainly consists of short talk-turns with fragmented language, frequent repairs and interruptions, while writing and reading consists of single words and short sentences. Although the classroom atmosphere is friendly and inclusive, second language students are denied necessary opportunities to develop curricular knowledge and Swedish at the advanced level, which they will need higher up in the school system. The restricted curriculum that these students are offered in school thus restricts their opportunities to school success. Thus, I argue for a more reflective and critical approach regarding language use in classrooms.
Resumo:
GPS tracking of mobile objects provides spatial and temporal data for a broad range of applications including traffic management and control, transportation routing and planning. Previous transport research has focused on GPS tracking data as an appealing alternative to travel diaries. Moreover, the GPS based data are gradually becoming a cornerstone for real-time traffic management. Tracking data of vehicles from GPS devices are however susceptible to measurement errors – a neglected issue in transport research. By conducting a randomized experiment, we assess the reliability of GPS based traffic data on geographical position, velocity, and altitude for three types of vehicles; bike, car, and bus. We find the geographical positioning reliable, but with an error greater than postulated by the manufacturer and a non-negligible risk for aberrant positioning. Velocity is slightly underestimated, whereas altitude measurements are unreliable.
Resumo:
The accurate measurement of a vehicle’s velocity is an essential feature in adaptive vehicle activated sign systems. Since the velocities of the vehicles are acquired from a continuous wave Doppler radar, the data collection becomes challenging. Data accuracy is sensitive to the calibration of the radar on the road. However, clear methodologies for in-field calibration have not been carefully established. The signs are often installed by subjective judgment which results in measurement errors. This paper develops a calibration method based on mining the data collected and matching individual vehicles travelling between two radars. The data was cleaned and prepared in two ways: cleaning and reconstructing. The results showed that the proposed correction factor derived from the cleaned data corresponded well with the experimental factor done on site. In addition, this proposed factor showed superior performance to the one derived from the reconstructed data.