scholarly journals Absolute Calibration of Radar Altimeters: Consistency with Electromagnetic Modeling

2005 ◽  
Vol 22 (6) ◽  
pp. 771-781 ◽  
Author(s):  
Gérard Caudal ◽  
Emmanuel Dinnat ◽  
Jacqueline Boutin
Keyword(s):  
Wind Speed ◽  
Empirical Model ◽  
Wave Spectrum ◽  
Absolute Calibration ◽  
Electromagnetic Modeling ◽  
Model Function ◽  
Electromagnetic Model ◽  
Using Data ◽  
Sea Wave

Abstract Empirical Ku-band altimeter model functions of near-nadir normalized radar cross-sectional σ° are compared to electromagnetic two-scale quasi-specular theory in the context of a standard sea wave spectral model. Three empirical model functions are tested: (i) the modified Chelton and Wentz model (WCM) using data from Geosat, (ii) the Callahan et al. model using data from TOPEX, and (iii) the Freilich and Vanhoff model using data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR). These three models are basically very similar, except that they differ in terms of the level of absolute calibration. The difference between the absolute calibrations of the two extreme models (MCW and Freilich and Vanhoff) is as high as 1.9 dB. Assuming a sea wave spectrum similar to that used by Elfouhaily et al., the two-scale quasi-specular electromagnetic model is run, with a wave separation wavenumber kd adjusted so as to minimize the rms difference between the theoretical σ°(θ) function and the empirical near-nadir model function. The quality of the best-fit solution is not perfect, however, because the shape and absolute level of the function σ°(θ) cannot usually be adjusted simultaneously by the electromagnetic model. Taking the model function used by Freilich and Vanhoff as a reference, an offset is then introduced to the empirical model function, and the residual error is computed as a function of the offset. The overall quality of the fit is shown to be best when a −1.1 dB offset is introduced into the Freilich and Vanhoff model function. To within 0.1 dB, this corresponds to the offset that would be required to match Callahan et al.’s model function. This result is obtained in a context where the effect of the peakedness of the sea surface was assumed negligible. When this effect is introduced, with a peakedness parameter Δ assumed to be independent of wind speed and taken tentatively as Δ = 0.23, as suggested by Chapron et al., the optimal offset is then found to be −0.2 dB, thus indicating that for this example the best consistency with electromagnetic modeling is closer to Freilich and Vanhoff’s calibration. A more refined assessment would require accurate measurements of the parameter Δ involving both magnitude and variability with wind speed. Such accurate measurements are, unfortunately, not available at this time.

TROPOMI Aerosol Index: detailed aerosol plume tracking and plans for future development

2020 ◽  
Author(s):  
Deborah Stein Zweers ◽  
Maarten Sneep ◽  
Maurits Kooreman ◽  
Piet Stammes ◽  
Gijsbert Tilstra ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
High Spatial Resolution ◽  
Absolute Calibration ◽  
Pixel Size ◽  
Plume Tracking ◽  
Using Data ◽  
Aerosol Index ◽  
Aerosol Plume ◽  
Global Mean

<p>The aerosol index (AER_AI) as calculated using data from the Tropospheric Monitoring Instrument (TROPOMI) onboard the ESA Sentinel 5 Precursor (S5P) platform was publically released in July 2018. The operational AER_AI dataset is available from May 2018 through the present. It is a useful data product not only for tracking ultraviolet (UV) absorbing aerosol plumes of desert dust, volcanic ash, and smoke from biomass burning but also for monitoring the quality of the TROPOMI Level 1b (L1b) data since the AER_AI calculation is very sensitive to the absolute calibration of irradiance and radiance. The aim of this work is first to highlight the new level of detail seen in aerosol plume events based on the recent switch to a reduced pixel size of 3.5 x 5.5 km. Such high spatial resolution also presents specific challenges as non-Lambertian cloud features and 3-D effects of clouds are now visible in the TROPOMI AER_AI data. Plans for an approach to flag and correct these features in future AER_AI updates will be given. Secondly this work will include an overview of the impacts on AER_AI due to observed degradation in the TROPOMI measured irradiance and wavelength-dependent features in the radiance. As a result of these L1b effects, there is a steadily increasing negative bias in the global mean AER_AI value. Examples are given how the new version of the L1b data (2.0.0) will be used to correct for this degradation-driven bias. Recommendations are also given to guide data users looking to perform trend analysis or those using AER_AI as a filter for aerosol removal or detection in other L2 data products.  </p>

THE INFLUENCE OF THE WIND SPEED PREDICTION ERROR ON THE SIZE OF THE STORAGE CONTROLLED OPERATION ZONE IN THE SYSTEM WITH THE WIND GENERATOR

2020 ◽  
Vol 2020 (57) ◽  
pp. 35-41
Author(s):  
K.S. Klen ◽  
◽  
M.K. Yaremenko ◽  
V.Ya. Zhuykov ◽  
◽  
...  
Keyword(s):  
Wind Speed ◽  
Prediction Error ◽  
Average Energy ◽  
Interpolation Formula ◽  
Wind Speed Prediction ◽  
Wind Generator ◽  
Prediction Horizon ◽  
Speed Prediction ◽  
Using Data ◽  
Predictor Corrector

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.

An Efficient Hybrid Forecasting Approach for Wind Speed Time Series

2017 ◽  
Vol 7 (9) ◽  
pp. 13
Author(s):  
Bhargavi Munnaluri ◽  
K. Ganesh Reddy
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wind Speed ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Support Vector ◽  
Hybrid Forecasting ◽  
Artificial Neural ◽  
Future Utilization

Wind forecasting is one of the best efficient ways to deal with the challenges of wind power generation. Due to the depletion of fossil fuels renewable energy sources plays a major role for the generation of power. For future management and for future utilization of power, we need to predict the wind speed.  In this paper, an efficient hybrid forecasting approach with the combination of Support Vector Machine (SVM) and Artificial Neural Networks(ANN) are proposed to improve the quality of prediction of wind speed. Due to the different parameters of wind, it is difficult to find the accurate prediction value of the wind speed. The proposed hybrid model of forecasting is examined by taking the hourly wind speed of past years data by reducing the prediction error with the help of Mean Square Error by 0.019. The result obtained from the Artificial Neural Networks improves the forecasting quality.

Effect of networks on product innovation: empirical evidence from Indonesian SMEs

2013 ◽  
Vol 1 (2) ◽  
pp. 140-158 ◽  
Author(s):  
Nurul Indarti ◽  
Theo Postma
Keyword(s):  
Empirical Evidence ◽  
Product Innovation ◽  
Dynamic Effects ◽  
Depth Of Knowledge ◽  
External Knowledge ◽  
Software Firms ◽  
Using Data

Innovative companies generally establish linkages with other actors and access external knowledge in order to benefit from the dynamic effects of interactive processes. Using data from 198 furniture and software firms in Indonesia, this study shows that the quality of interaction (i.e. multiplexity) as indicated by the depth of knowledge absorbed from various external parties and intensity of interaction (i.e., tie intensity) are better predictors of product innovation than the diversity of interaction.

Founding Family Ownership and the Selection of Industry Specialist Auditors

2014 ◽  
Vol 28 (2) ◽  
pp. 261-276 ◽  
Author(s):  
Fei Kang
Keyword(s):  
Financial Reporting ◽  
Family Firms ◽  
Structure And Agency ◽  
Founding Family ◽  
Using Data ◽  
Dual Class Shares ◽  
Dual Class ◽  
Selection Of ◽  
Industry Specialist

SYNOPSIS This study examines how family firms' unique ownership structure and agency problems affect their selection of industry-specialist auditors. Using data from Standard & Poor's (S&P) 1500 firms, the results show that family firms are more likely to appoint industry-specialist auditors than non-family firms, which suggests that family firms have strong incentives to signal the quality of financial reporting. Additional analysis indicates that due to the potential entrenchment problems, family firms with family member CEOs or with dual-class shares have even a higher tendency to hire industry-specialist auditors to signal their disclosure quality.

Institutions and Political Support

2017 ◽  
Author(s):  
Shaun Bowler
Keyword(s):  
Political Institutions ◽  
Political Process ◽  
Institutional Reform ◽  
Institutional Arrangements ◽  
Individual Characteristics ◽  
Political Support ◽  
The Political ◽  
General Expectation ◽  
Using Data

This chapter analyzes to what extent variation in political institutions affects political support. The chapter observes that the existing research is not always clear on which institutions should produce what kind of effect, although a general expectation is that institutional arrangements improve political support when they give citizens an increased sense of connection to the political process. In general then, we should expect institutions that strengthen the quality of representation to strengthen political support. This general expectation is specified in six hypotheses that are tested using data from the ESS 2012. The chapter demonstrates that electoral systems that provide voters with more choice about candidates, multiparty governments, and “responsive” legislatures, correlate positively with political support. However, compared to other macro-level factors and individual characteristics, the effects of political institutions on political support are modest. The chapter concludes that the prospects for institutional reform to strengthen political support are limited.

scholarly journals Quantitative Trait Loci: A Meta-analysis

Genetics ◽  
2000 ◽  
Vol 155 (1) ◽  
pp. 463-473
Author(s):  
Bruno Goffinet ◽  
Sophie Gerber
Keyword(s):  
Quantitative Trait Loci ◽  
Confidence Interval ◽  
Quantitative Trait ◽  
Meta Analysis ◽  
Trait Loci ◽  
Akaike Criterion ◽  
Using Data

Abstract This article presents a method to combine QTL results from different independent analyses. This method provides a modified Akaike criterion that can be used to decide how many QTL are actually represented by the QTL detected in different experiments. This criterion is computed to choose between models with one, two, three, etc., QTL. Simulations are carried out to investigate the quality of the model obtained with this method in various situations. It appears that the method allows the length of the confidence interval of QTL location to be consistently reduced when there are only very few “actual” QTL locations. An application of the method is given using data from the maize database available online at http://www.agron.missouri.edu/.

Improving the Quality of Survey Data on College Campus Woman Abuse: The Contribution of a Supplementary Open-Ended Question

2020 ◽  
pp. 107780122097549
Author(s):  
Walter S. DeKeseredy ◽  
Danielle M. Stoneberg ◽  
James Nolan ◽  
Gabrielle L. Lory
Keyword(s):  
Quality Of Life ◽  
Higher Education ◽  
Survey Data ◽  
College Campus ◽  
Woman Abuse ◽  
Institutions Of Higher Education ◽  
Prevalence Rates ◽  
Methodological Challenge ◽  
Using Data

Obtaining accurate survey data on the prevalence of woman abuse in institutions of higher education continues to be a major methodological challenge. Underreporting is difficult to overcome; yet, there may be effective ways of minimizing this problem. One is adding a supplementary open-ended question to a primarily quantitative questionnaire. Using data derived from the Campus Quality of Life Survey (CQLS), this article examines whether asking respondents to complete such a question increases the prevalence rates of four types of woman abuse and provides information on behaviors that are not included in widely used and validated measures of these harms.

scholarly journals What does my neighbourhood have to do with my weight? A protocol for systematic review and meta-analysis of the association between neighbourhood socioeconomic status and body weight

BMJ Open ◽  
2017 ◽  
Vol 7 (9) ◽  
pp. e017567
Author(s):  
Shimels Hussien Mohammed ◽  
Mulugeta Molla Birhanu ◽  
Tesfamichael Awoke Sissay ◽  
Tesfa Dejenie Habtewold ◽  
Balewgizie Sileshi Tegegn ◽  
...  
Keyword(s):  
Systematic Review ◽  
Socioeconomic Status ◽  
Data Extraction ◽  
Meta Analysis ◽  
Cross Sectional ◽  
Registration Number ◽  
Newcastle Ottawa Scale ◽  
Neighbourhood Socioeconomic Status ◽  
Using Data

IntroductionIndividuals living in poor neighbourhoods are at a higher risk of overweight/obesity. There is no systematic review and meta-analysis study on the association of neighbourhood socioeconomic status (NSES) with overweight/obesity. We aimed to systematically review and meta-analyse the existing evidence on the association of NSES with overweight/obesity.Methods and analysisCross-sectional, case–control and cohort studies published in English from inception to 15 May 2017 will be systematically searched using the following databases: PubMed, EMBASE, Web of Sciences and Google Scholar. Selection, screening, reviewing and data extraction will be done by two reviewers, independently and in duplicate. The Newcastle–Ottawa Scale (NOS) will be used to assess the quality of evidence. Publication bias will be checked by visual inspection of funnel plots and Egger’s regression test. Heterogeneity will be checked by Higgins’s method (I2statistics). Meta-analysis will be done to estimate the pooled OR. Narrative synthesis will be performed if meta-analysis is not feasible due to high heterogeneity of studies.Ethics and disseminationEthical clearance is not required as we will be using data from published articles. Findings will be communicated through a publication in a peer-reviewed journal and presentations at professional conferences.PROSPERO registration numberCRD42017063889.

Explaining Political Knowledge: The Role of Procedural Quality in an Informed Citizenry

2016 ◽  
Vol 65 (1) ◽  
pp. 61-80 ◽  
Author(s):  
Nicholas Clark
Keyword(s):  
Political Process ◽  
Political Knowledge ◽  
The Political ◽  
Factual Knowledge ◽  
Governance Indicators ◽  
Informed Citizenry ◽  
Using Data ◽  
The Comparative Study ◽  
Knowledge Seeking

While much is known about the micro-level predictors of political knowledge, there have been relatively few efforts to study the potential macro-level causes of knowledge. Seeking to improve our understanding of country-based variation in knowledge, this article demonstrates that individuals have an easier time finding and interpreting information in political environments that provide the public with greater opportunities to engage, observe, and learn about the political process. To investigate that possibility, the article analyzes how the procedural quality of the political process affects political knowledge. Using data from the Comparative Study of Electoral Systems and the Worldwide Governance Indicators Project, survey analyses show that the transparency and responsiveness of a political system indeed influence the public’s information about political parties and, to a lesser extent, the amount of factual knowledge retained by survey respondents. In other words, the quality of democratic governance affects how much individuals know about the political process.

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