An evaluation of two automated quality control methods designed for use with hourly wind profiler data

1994 ◽  
Vol 12 (8) ◽  
pp. 711-724 ◽  
Author(s):  
P. A. Miller ◽  
M. F. Barth ◽  
D. W. van de Kamp ◽  
T. W. Schlatter ◽  
B. L. Weber ◽  
...  

Abstract. The National Oceanic and Atmospheric Administration (NOAA) has completed the installation of a 30-site demonstration network of wind-profiling radars in the central United States. The network is being used to demonstrate and assess the utility of wind profiler technology in a quasi-operational environment, and to help define operational requirements for possible future national networks. This paper describes two automated quality control methods designed to remove erroneous winds from the hourly network data. Case study examples and statistical evaluation of the performance of each method are also presented.

2020 ◽  
Vol 9 (3) ◽  
pp. 171-176
Author(s):  
Nurul Retno Nurwulan ◽  
Wilcha Anatasya Veronica

A good quality control system is important to be implemented to increase productivity and minimize defects in products. One of the quality control methods is failure mode and effect analysis (FMEA). This study uses the FMEA to identify the causes of the defects and recommend the prevention methods to overcome the causes of the defects in an Indonesian paper mill. The risk priority number (RPN) is calculated by multiplying the severity, occurrence, and detection of the failures that have been determined. Unsymmetrical and tainted products are the most dominant defects in the paper mill. An inappropriate machine setting is the cause of unsymmetrical products with the highest RPN of 343. The second highest RPN is problems with bleaching machines that caused tainted products with an RPN value of 216. This study offers suggestions to Indonesian paper mill to prevent and minimize defective products. 


2004 ◽  
Vol 85 (12) ◽  
pp. 1871-1886 ◽  
Author(s):  
Stanley G. Benjamin ◽  
Barry E. Schwartz ◽  
Edward J. Szoke ◽  
Steven E. Koch

An assessment of the value of data from the NOAA Profiler Network (NPN) on weather forecasting is presented. A series of experiments was conducted using the Rapid Update Cycle (RUC) model/assimilation system in which various data sources were denied in order to assess the relative importance of the profiler data for short-range wind forecasts. Average verification statistics from a 13-day cold-season test period indicate that the profiler data have a positive impact on short-range (3–12 h) forecasts over the RUC domain containing the lower 48 United States, which are strongest at the 3-h projection over a central U.S. subdomain that includes most of the profiler sites, as well as downwind of the profiler observations over the eastern United States. Overall, profiler data reduce wind forecast errors at all levels from 850 to 150 hPa, especially below 300 hPa where there are relatively few automated aircraft observations. At night when fewer commercial aircraft are flying, profiler data also contribute strongly to more accurate 3-h forecasts, including near-tropopause maximum wind levels. For the test period, the profiler data contributed up to 20%–30% (at 700 hPa) of the overall reduction of 3-h wind forecast error by all data sources combined. Inclusion of wind profiler data also reduced 3-h errors for height, relative humidity, and temperature by 5%-15%, averaged over different vertical levels. Time series and statistics from large-error events demonstrate that the impact of profiler data may be much larger in peak error situations. Three data assimilation case studies from cold and warm seasons are presented that illustrate the value of the profiler observations for improving weather forecasts. The first case study indicates that inclusion of profiler data in the RUC model runs for the 3 May 1999 Oklahoma tornado outbreak improved model guidance of convective available potential energy (CAPE), 300-hPa wind, and precipitation in southwestern Oklahoma at the onset of the event. In the second case study, inclusion of profiler data led to better RUC precipitation forecasts associated with a severe snow and ice storm that occurred over the central plains of the United States in February 2001. A third case study describes the effect of profiler data for a tornado event in Oklahoma on 8 May 2003. Summaries of National Weather Service (NWS) forecaster use of profiler data in daily operations, although subjective, support the results from these case studies and the statistical forecast model impact study in the broad sense that profiler data contribute significantly to improved short-range forecasts over the central United States where these observations currently exist.


2016 ◽  
Vol 60 (5) ◽  
pp. 429-435 ◽  
Author(s):  
Elly Crighton ◽  
Ian Mullaney ◽  
Robert Trengove ◽  
Michael Bunce ◽  
Garth Maker

Herbal medicines are growing in popularity, use and commercial value; however, there remain problems with the quality and consequently safety of these products. Adulterated, contaminated and fraudulent products are often found on the market, a risk compounded by the fact that these products are available to consumers with little or no medical advice. Current regulations and quality control methods are lacking in their ability to combat these serious problems. Metabolomics is a biochemical profiling tool that may help address these issues if applied to quality control of both raw ingredients and final products. Using the example of the popular herbal medicine, ginseng, this essay offers an overview of the potential use of metabolomics for quality control in herbal medicines and also highlights where more research is needed.


2015 ◽  
Vol 32 (9) ◽  
pp. 1545-1561 ◽  
Author(s):  
A. Molod ◽  
H. Salmun ◽  
M. Dempsey

AbstractAn algorithm was developed to estimate planetary boundary layer (PBL) heights from hourly archived wind profiler data from the NOAA Profiler Network (NPN) sites located throughout the central United States. Unlike previous studies, the present algorithm has been applied to a long record of publicly available wind profiler signal backscatter data. Under clear-sky conditions, summertime averaged hourly time series of PBL heights compare well with Richardson number–based estimates at the few NPN stations with hourly temperature measurements. Comparisons with estimates based on clear-sky reanalysis show that the wind profiler (WP) PBL heights are lower by approximately 250–500 m. The geographical distribution of daily maximum PBL heights corresponds well with the expected distribution based on patterns of surface temperature and soil moisture. Wind profiler PBL heights were also estimated under mostly cloudy-sky conditions, and are generally comparable to the Richardson number–based PBL heights and higher than the reanalysis PBL heights. WP PBL heights have a smaller clear–cloudy condition difference than either of the other two. The algorithm presented here is shown to provide a reliable summertime climatology of daytime hourly PBL heights throughout the central United States.


2017 ◽  
Vol 34 (7) ◽  
pp. 1591-1606 ◽  
Author(s):  
Yu Zhang ◽  
Min Chen ◽  
Jiqin Zhong

AbstractA wind profiler network with a total of 65 profiling radar systems was operated by the China Meteorological Observation Center (MOC) of the China Meteorological Administration (CMA) until July 2015. In this study, a quality control procedure is constructed to incorporate the profiler data from the wind-profiling network into the local data assimilation and forecasting systems. The procedure applies a blacklisting check that removes stations with gross errors and an outlier check that rejects data with large deviations from the background. As opposed to the biweight method, which has been commonly implemented in outlier elimination for univariate observations, the outlier elimination method is developed based on the iterated reweighted minimum covariance determinant (IRMCD) for multivariate observations, such as wind profiler data. A quality control experiment is performed separately for subsets containing profiler data tagged with/without rain flags in parallel every 0000 and 1200 UTC from 20 June to 30 September 2015. The results show that with quality control, the frequency distributions of the differences between the observations and the model background meet the requirements of a Gaussian distribution for data assimilation. A further intensive assessment of each quality control step reveals that the stations rejected by the blacklisting contained poor data quality and that the IRMCD rejects outliers in a robust and physically reasonable manner. Detailed comparisons between the IRMCD and the biweight method are performed, and the IRMCD is demonstrated to be more efficient and more comprehensive regarding the dataset used in this study.


2019 ◽  
pp. 40-46 ◽  
Author(s):  
V.V. Savchenko ◽  
A.V. Savchenko

We consider the task of automated quality control of sound recordings containing voice samples of individuals. It is shown that in this task the most acute is the small sample size. In order to overcome this problem, we propose the novel method of acoustic measurements based on relative stability of the pitch frequency within a voice sample of short duration. An example of its practical implementation using aninter-periodic accumulation of a speech signal is considered. An experimental study with specially developed software provides statistical estimates of the effectiveness of the proposed method in noisy environments. It is shown that this method rejects the audio recording as unsuitable for a voice biometric identification with a probability of 0,95 or more for a signal to noise ratio below 15 dB. The obtained results are intended for use in the development of new and modifying existing systems of collecting and automated quality control of biometric personal data. The article is intended for a wide range of specialists in the field of acoustic measurements and digital processing of speech signals, as well as for practitioners who organize the work of authorized organizations in preparing for registration samples of biometric personal data.


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