scholarly journals An Analytical Error Model for Spaceborne SAR Multichannel Azimuth Reconstruction

2017 ◽  
Author(s):  
F.Q. de Almeida ◽  
M. Younis ◽  
G. Krieger ◽  
A. Moreira
Keyword(s):  
Error Model ◽  
Analytical Error ◽  
Analytical Error Model

scholarly journals An Analytical Error Model for Spaceborne SAR Multichannel Azimuth Reconstruction

2018 ◽  
Vol 15 (6) ◽  
pp. 853-857 ◽  
Author(s):  
Felipe Queiroz de Almeida ◽  
Marwan Younis ◽  
Gerhard Krieger ◽  
Alberto Moreira
Keyword(s):  
Error Model ◽  
Analytical Error ◽  
Analytical Error Model

scholarly journals Quantifying uncertainty in climatological fields from GPS radio occultation: an empirical-analytical error model

2011 ◽  
Vol 4 (3) ◽  
pp. 2749-2788 ◽  
Author(s):  
B. Scherllin-Pirscher ◽  
G. Kirchengast ◽  
A. K. Steiner ◽  
Y.-H. Kuo ◽  
U. Foelsche
Keyword(s):  
Radio Occultation ◽  
Sampling Error ◽  
Statistical Error ◽  
Error Component ◽  
Error Model ◽  
Atmospheric Parameters ◽  
Bending Angle ◽  
Analytical Error ◽  
Low Latitudes ◽  
Analytical Error Model

Abstract. Due to the measurement principle of the radio occultation (RO) technique, RO data are highly suitable for climate studies. Single RO profiles can be used to build climatological fields of different atmospheric parameters like bending angle, refractivity, density, pressure, geopotential height, and temperature. RO climatologies are affected by random (statistical) errors, sampling errors, and systematic errors, yielding a total climatological error. Based on empirical error estimates, we provide a simple analytical error model for these error components, which accounts for vertical, latitudinal, and seasonal variations. The vertical structure of each error component is modeled constant around the tropopause region. Above this region the error increases exponentially, below the increase follows an inverse height power-law. The statistical error strongly depends on the number of measurements. It is found to be the smallest error component for monthly mean 10° zonal mean climatologies with more than 600 measurements per bin. Due to smallest atmospheric variability, the sampling error is found to be smallest at low latitudes equatorwards of 40°. Beyond 40°, this error increases roughly linearly, with a stronger increase in hemispheric winter than in hemispheric summer. The sampling error model accounts for this hemispheric asymmetry. However, we recommend to subtract the sampling error when using RO climatologies for climate research since the residual sampling error remaining after such subtraction is estimated to be 50 % of the sampling error for bending angle and 30 % or less for the other atmospheric parameters. The systematic error accounts for potential residual biases in the measurements as well as in the retrieval process and generally dominates the total climatological error. Overall the total error in monthly means is estimated to be smaller than 0.07 % in refractivity and 0.15 K in temperature at low to mid latitudes, increasing towards higher latitudes. This study focuses on dry atmospheric parameters as retrieved from RO measurements so for context we also quantitatively explain the difference between dry and physical atmospheric parameters, which can be significant at low latitudes below about 10 km.

scholarly journals Quantifying uncertainty in climatological fields from GPS radio occultation: an empirical-analytical error model

2011 ◽  
Vol 4 (9) ◽  
pp. 2019-2034 ◽  
Author(s):  
B. Scherllin-Pirscher ◽  
G. Kirchengast ◽  
A. K. Steiner ◽  
Y.-H. Kuo ◽  
U. Foelsche
Keyword(s):  
Radio Occultation ◽  
Sampling Error ◽  
Total Error ◽  
Statistical Error ◽  
Error Component ◽  
Error Model ◽  
Atmospheric Parameters ◽  
Analytical Error ◽  
Low Latitudes ◽  
Analytical Error Model

Abstract. Due to the measurement principle of the radio occultation (RO) technique, RO data are highly suitable for climate studies. RO profiles can be used to build climatological fields of different atmospheric parameters like bending angle, refractivity, density, pressure, geopotential height, and temperature. RO climatologies are affected by random (statistical) errors, sampling errors, and systematic errors, yielding a total climatological error. Based on empirical error estimates, we provide a simple analytical error model for these error components, which accounts for vertical, latitudinal, and seasonal variations. The vertical structure of each error component is modeled constant around the tropopause region. Above this region the error increases exponentially, below the increase follows an inverse height power-law. The statistical error strongly depends on the number of measurements. It is found to be the smallest error component for monthly mean 10° zonal mean climatologies with more than 600 measurements per bin. Due to smallest atmospheric variability, the sampling error is found to be smallest at low latitudes equatorwards of 40°. Beyond 40°, this error increases roughly linearly, with a stronger increase in hemispheric winter than in hemispheric summer. The sampling error model accounts for this hemispheric asymmetry. However, we recommend to subtract the sampling error when using RO climatologies for climate research since the residual sampling error remaining after such subtraction is estimated to be only about 30% of the original one or less. The systematic error accounts for potential residual biases in the measurements as well as in the retrieval process and generally dominates the total climatological error. Overall the total error in monthly means is estimated to be smaller than 0.07% in refractivity and 0.15 K in temperature at low to mid latitudes, increasing towards higher latitudes. This study focuses on dry atmospheric parameters as retrieved from RO measurements so for context we also quantitatively explain the difference between dry and physical atmospheric parameters, which can be significant at altitudes below about 6 km (high latitudes) to 10 km (low latitudes).

RETRACTION NOTE: Les structures des phrases dans les tracts du mai 1968

2019 ◽  
Vol 3 ◽  
pp. 00047
Author(s):  
Nokiamy Sesena Tamba ◽  
Myrna Laksman-Huntley
Keyword(s):  
Social Sciences ◽  
Public Domain ◽  
Background Color ◽  
Font Size ◽  
Analytical Error ◽  
Social Sciences And Humanities ◽  
Retracted Article ◽  
Du Mai ◽  
Web Archive ◽  
Digital Press

<p class="MsoNormal" style="line-height: 24px;">As of October 15, 2019, the following article is being retracted from the UGM Digital Press Social Sciences and Humanities series.</p><p class="MsoNormal" style="line-height: 24px;"><span style="font-size: 1rem;">“Les structures des phrases dans les tracts du mai 1968” by Nokiamy Sesena Tamba and Myrna Laksman-Huntley, Social Sciences and Humanities Series Vol 3: 00033, Proceeding of Conférence internationale sur le français 2018, Joesana Tjahjani, Merry Andriani, Sajarwa, Wening Udasmoro (eds) DOI:&nbsp;</span><a href="https://doi.org/10.29037/digitalpress.43306" target="_blank" style="background-color: rgb(255, 255, 255); font-size: 1rem;">https://doi.org/10.29037/digitalpress.43306</a></p><p class="MsoNormal" style="line-height: 24px;">The original article is registered through this URL&nbsp;<a href="https://digitalpress.ugm.ac.id/article/306" target="_blank">https://digitalpress.ugm.ac.id/article/306</a></p><p class="MsoNormal" style="line-height: 24px;">as decided by authors and conference organizers on the basis of analytical error. It may encourage potential misleading circulation of information in the future.</p><p class="MsoNormal" style="line-height: 24px;">On the following exchange of information with the publisher, it has been decided that the article will be retracted.</p><p class="MsoNormal" style="line-height: 24px;">The retracted article will remain in public domain, that is maintaining its appearance on UGM Digital Press web archive and the Conférence internationale sur le français 2018 printed version. However, it will receive a watermark to accentuate its retracted status.</p>

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