scholarly journals Validation Test Report for the NRL Ocean Surface Flux (NFLUX) Quality Control and 2D Variational Analysis System

2014 ◽  
Author(s):  
Jackie May ◽  
Neil Van de Voorde ◽  
Clark Rowley
Keyword(s):  
Quality Control ◽  
Variational Analysis ◽  
Surface Flux ◽  
Ocean Surface ◽  
Test Report ◽  
Validation Test ◽  
Analysis System

Validation Test Report for OCEANS 1.0: The 1/40 Global, Reduced Gravity NRL Layered Ocean Model

1998 ◽  
Author(s):  
E. J. Metzger ◽  
Robert C. Rhodes ◽  
Dong S. Ko ◽  
Harley E. Hurlburt
Keyword(s):  
Ocean Model ◽  
Reduced Gravity ◽  
Test Report ◽  
Validation Test

The Use of Bred Vectors in the NCEP Global 3D Variational Analysis System

1997 ◽  
Vol 12 (3) ◽  
pp. 689-695 ◽  
Author(s):  
Zhao-Xia Pu ◽  
Eugenia Kalnay ◽  
David Parrish ◽  
Wanshu Wu ◽  
Zoltan Toth
Keyword(s):  
Variational Analysis ◽  
Bred Vectors ◽  
Analysis System

scholarly journals An Assessment of the Uncertainties in Ocean Surface Turbulent Fluxes in 11 Reanalysis, Satellite-Derived, and Combined Global Datasets

2011 ◽  
Vol 24 (21) ◽  
pp. 5469-5493 ◽  
Author(s):  
Michael A. Brunke ◽  
Zhuo Wang ◽  
Xubin Zeng ◽  
Michael Bosilovich ◽  
Chung-Lin Shie
Keyword(s):  
Wind Stress ◽  
Coupled System ◽  
Surface Flux ◽  
Ocean Surface ◽  
Turbulent Fluxes ◽  
Department Of Energy ◽  
Strong Wind ◽  
Wind Speeds ◽  
Direct Covariance ◽  
Environmental Prediction

Abstract Ocean surface turbulent fluxes play an important role in the energy and water cycles of the atmosphere–ocean coupled system, and several flux products have become available in recent years. Here, turbulent fluxes from 6 widely used reanalyses, 4 satellite-derived flux products, and 2 combined product are evaluated by comparison with direct covariance latent heat (LH) and sensible heat (SH) fluxes and inertial-dissipation wind stresses measured from 12 cruises over the tropics and mid- and high latitudes. The biases range from −3.0 to 20.2 W m−2 for LH flux, from −1.4 to 6.0 W m−2 for SH flux, and from −7.6 to 7.9 × 10−3 N m−2 for wind stress. These biases are small for moderate wind speeds but diverge for strong wind speeds (>10 m s−1). The total flux biases are then further evaluated by dividing them into uncertainties due to errors in the bulk variables and the residual uncertainty. The bulk-variable-caused uncertainty dominates many products’ SH flux and wind stress biases. The biases in the bulk variables that contribute to this uncertainty can be quite high depending on the cruise and the variable. On the basis of a ranking of each product’s flux, it is found that the Modern-Era Retrospective Analysis for Research and Applications (MERRA) is among the “best performing” for all three fluxes. Also, the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and the National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) reanalysis are among the best performing for two of the three fluxes. Of the satellite-derived products, version 2b of the Goddard Satellite-Based Surface Turbulent Fluxes (GSSTF2b) is among the best performing for two of the three fluxes. Also among the best performing for only one of the fluxes are the 40-yr ERA (ERA-40) and the combined product objectively analyzed air–sea fluxes (OAFlux). Direction for the future development of ocean surface flux datasets is also suggested.

Using videotaped specimens to test quality control in a computer-assisted semen analysis system

2000 ◽  
Vol 73 (3) ◽  
pp. 636-640 ◽  
Author(s):  
William R. Boone ◽  
Jeffrey M. Jones ◽  
Sander S. Shapiro
Keyword(s):  
Quality Control ◽  
Semen Analysis ◽  
Computer Assisted ◽  
Test Quality ◽  
Analysis System

Quality Assurance of Energy Dispersive Spectrometry Systems

1998 ◽  
Vol 4 (S2) ◽  
pp. 214-215
Author(s):  
E. B. Steel ◽  
R. B. Marinenko
Keyword(s):  
Quality Control ◽  
Energy Dispersive Spectrometry ◽  
Standard Procedure ◽  
Energy Dispersive ◽  
X Ray ◽  
Standard Procedures ◽  
Reliability Sensitivity ◽  
Control Procedures ◽  
Analysis System ◽  
Quality Instruments

Monitoring the performance and capabilities of energy dispersive X-ray spectrometers (EDS) and related x-ray analysis electronics and software is important for maintaining and improving the reliability, sensitivity, and accuracy of the x-ray analysis system. There is growing demand for quality systems through laboratory accreditation, ISO 9000, ISO Guide 25 and related programs that require set quality control procedures for analytical instrumentation. In such cases it is frequently more useful to have one national/international standard. This approach is not only more efficient than having each analyst devise their own system, but the use of the same standard procedures among labs would allow direct intercomparison of results. This intercomparison can help labs and manufacturers determine what are normal versus abnormal results and lead to higher quality instruments and analyses.We are designing a standard procedure to maximize the efficiency of each quality control (QC) measurement so that we spend as little time monitoring the analysis system as is possible.

scholarly journals All-Sky Microwave Radiance Assimilation in NCEP’s GSI Analysis System

2016 ◽  
Vol 144 (12) ◽  
pp. 4709-4735 ◽  
Author(s):  
Yanqiu Zhu ◽  
Emily Liu ◽  
Rahul Mahajan ◽  
Catherine Thomas ◽  
David Groff ◽  
...  
Keyword(s):  
Quality Control ◽  
Bias Correction ◽  
Microwave Radiometer ◽  
Cloud Water ◽  
Development Effort ◽  
Observation Error ◽  
Background Error ◽  
Radiance Assimilation ◽  
Analysis System ◽  
Sky Conditions

Abstract The capability of all-sky microwave radiance assimilation in the Gridpoint Statistical Interpolation (GSI) analysis system has been developed at the National Centers for Environmental Prediction (NCEP). This development effort required the adaptation of quality control, observation error assignment, bias correction, and background error covariance to all-sky conditions within the ensemble–variational (EnVar) framework. The assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) microwave radiometer for ocean fields of view (FOVs) is the primary emphasis of this study. In the original operational hybrid 3D EnVar Global Forecast System (GFS), the clear-sky approach for radiance data assimilation is applied. Changes to data thinning and quality control have allowed all-sky satellite radiances to be assimilated in the GSI. Along with the symmetric observation error assignment, additional situation-dependent observation error inflation is employed for all-sky conditions. Moreover, in addition to the current radiance bias correction, a new bias correction strategy has been applied to all-sky radiances. In this work, the static background error variance and the ensemble spread of cloud water are examined, and the levels of cloud variability from the ensemble forecast in single- and dual-resolution configurations are discussed. Overall, the all-sky approach provides more realistic simulated brightness temperatures and cloud water analysis increments, and improves analysis off the west coasts of the continents by reducing a known bias in stratus. An approximate 10% increase in the use of AMSU-A channels 1–5 and a 12% increase for channel 15 are also observed. The all-sky AMSU-A radiance assimilation became operational in the 4D EnVar GFS system upgrade of 12 May 2016.

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