2018
DOI: 10.5194/acp-18-4187-2018
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Characterizing sampling and quality screening biases in infrared and microwave limb sounding

Abstract: Abstract. This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, scree… Show more

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Cited by 8 publications
(3 citation statements)
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“…A disadvantage is that there can be significant sampling biases. For example, limb viewing infrared instruments are heavily cloud contaminated in the tropics and will show a significant dry bias compared to maps made from nadir viewing or submillimeter instruments (Millán et al, 2018). This study will show that the sampling bias is more than a factor of two in the upper troposphere.…”
Section: Comparison Methodsmentioning
confidence: 80%
“…A disadvantage is that there can be significant sampling biases. For example, limb viewing infrared instruments are heavily cloud contaminated in the tropics and will show a significant dry bias compared to maps made from nadir viewing or submillimeter instruments (Millán et al, 2018). This study will show that the sampling bias is more than a factor of two in the upper troposphere.…”
Section: Comparison Methodsmentioning
confidence: 80%
“…These datasets differ greatly in geographical coverage, horizontal and vertical resolution, measurement frequency, and time period covered. To fully exploit these measurements, careful attention needs to be paid to understand how sampling differences between the instruments can affect their representation of the atmospheric state (e.g, Manney et al, 2007;Hegglin et al, 2008;Toohey et al, 2013;Lin et al, 2015;Millán et al, 2016;Miyazaki and Bowman, 2017;Millán et al, 2018;Chang et al, 2020).…”
Section: Datasetsmentioning
confidence: 99%
“…H 2 O, O 3 , HNO 3 , CH 4 , N 2 O, and NO 2 -as well as temperature (Fischer and Oelhaf, 1996;Fischer et al, 2008). Here, the Envisat/MIPAS HNO 3 and temperature data version V5H_HNO3_20 and V5H_T_20 and V5R_HNO3_224/225 and V5R_T_220/221 (nominal mode) derived with the IMK/IAA retrieval processor covering the periods July 2002-March 2003 and January 2005-April 2012, respectively, have been used (updated version of the retrieval as described in Milz et al, 2009, andvon Clarmann et al, 2009). Comparison of the MIPAS HNO 3 data product with satellite measurements from Odin/SMR (Odin/Sub-Millimetre Radiometer), ADEOS/ILAS-II (Advanced Earth Observing Satellite/Improved Limb Atmospheric Spectrometer), SCISAT/ACE-FTS (SCISAT/Atmospheric Chemistry Experiment-Fourier Transform Spectrometer), and the Envisat/MIPAS ESA (European Space Agency) product showed good agreement, and differences were generally within ±0.5 ppbv (Wang et al, 2007;Wolff et al, 2008).…”
Section: Envisat/mipasmentioning
confidence: 99%