Validating the reported random errors of ACE‐FTS measurements

Toohey, Matthew; Strong, Kimberly; Bernath, P. F.; Boone, C. D.; Walker, Kaley A.; Jönsson, Andreas; Shepherd, Theodore G.

doi:10.1029/2010jd014185

Cited by 14 publications

(9 citation statements)

References 45 publications

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“…This method has been applied in several previous studies to satellite measurements to validate the reported precision. For example, Toohey et al [2010] use the short-term scatter in tropical Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) measurements to validate the reported random error for several retrieved molecular concentration profiles. Piccolo and Dudhia [2007] compare the standard deviation of Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) retrievals at the intersections of ascending and descending legs of the orbit track to validate the reported precision of MIPAS Level 2 products, and uncertainties in Microwave Limb Sounder (MLS) ozone retrievals are characterized similarly by Froidevaux et al [2008].…”

Section: Osiris "Matched Pair" Measurementsmentioning

confidence: 87%

Precision estimate for Odin‐OSIRIS limb scatter retrievals

Bourassa¹,

McLinden²,

Bathgate³

et al. 2012

J. Geophys. Res.

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[1] The limb scatter measurements made by the Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument on the Odin spacecraft are used to routinely produce vertically resolved trace gas and aerosol extinction profiles. Version 5 of the ozone and stratospheric aerosol extinction retrievals, which are available for download, are performed using a multiplicative algebraic reconstruction technique (MART). The MART inversion is a type of relaxation method, and as such the covariance of the retrieved state is estimated numerically, which, if done directly, is a computationally heavy task. Here we provide a methodology for the derivation of a numerical estimate of the covariance matrix for the retrieved state using the MART inversion that is sufficiently efficient to perform for each OSIRIS measurement. The resulting precision is compared with the variability in a large set of pairs of OSIRIS measurements that are close in time and space in the tropical stratosphere where the natural atmospheric variability is weak. These results are found to be highly consistent and thus provide confidence in the numerical estimate of the precision in the retrieved profiles.

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Section: Osiris "Matched Pair" Measurementsmentioning

confidence: 87%

Precision estimate for Odin‐OSIRIS limb scatter retrievals

Bourassa¹,

McLinden²,

Bathgate³

et al. 2012

J. Geophys. Res.

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“…It should also be noted that in atmospheric science, the use of PDFs is not uncommon in tracer and validation studies. Lary and Lait (2006), in their introduction, give excellent examples of different types of tracer studies; and studies such as Migliorini et al (2004), Lary and Lait (2006), and Wu et al (2008) have demonstrated that PDFs can be used as a validation tool, where PDFs as measured by different atmospheric sounders are inter-compared rather than inter-comparing co-located measurements.…”

Section: Introductionmentioning

confidence: 99%

Detecting physically unrealistic outliers in ACE-FTS atmospheric measurements

2015

Self Cite

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The ACE-FTS (Atmospheric Chemistry Experiment -Fourier Transform Spectrometer) instrument on board the Canadian satellite SCISAT has been observing the Earth's limb in solar occultation since its launch in 2003. Since February 2004, high resolution (0.02 cm −1) observations in the spectral region of 750-4400 cm −1 have been used to derive volume mixing ratio profiles of over 30 atmospheric trace species and over 20 atmospheric isotopologues. Although the full ACE-FTS level 2 data set is available to users in the general atmospheric community, until now no quality flags have been assigned to the data. This study describes the two-stage procedure for detecting physically unrealistic out-liers within the data set for each retrieved species, which is a fixed procedure across all species. Since the distributions of ACE-FTS data across regions (altitude/latitude/season/local time) tend to be asymmetric and multimodal, the screening process does not make use of the median absolute deviation. It makes use of volume mixing ratio probability density functions , assuming that the data, when sufficiently binned, are at most tri-modal and that these modes can be represented by the superposition of three normal, or log-normal, distributions. Quality flags have been assigned to the data based on retrieval statistical fitting error, the physically unrealis-tic outliers described in this study, and known instrumen-tal/processing errors. The quality flags defined and discussed in this study are now available for all level 2 versions 2.5 and 3.5 data and will be made available as a standard product for future versions.

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“…For the majority of points, from 60°N to 60°S (c.f. Figure 1), the modifications made using Equation (2) has only a minimal effect and is within the measurement uncertainty calculated using the ACE-FTS error estimates (see Toohey et al, 2010, for details on ACE-FTS error estimation).…”

Section: Significancementioning

confidence: 99%

On sampling bias adjustment for sparsely observing satellite instruments for the example of carbonyl sulfide (OCS)

Kloss

Hobe

Höpfner

et al. 2018

Preprint

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Abstract. When computing climatological averages of atmospheric trace gas mixing ratios obtained from satellite-based measurements, sampling biases arise if data coverage is not uniform in space and time. Complete homogeneous spatio-temporal coverage is essentially impossible to achieve. Solar occultation measurements, by virtue of satellite orbits and the requirement of direct observation of the sun through the atmosphere, result in particularly sparse spatial coverage. In this study, a method is presented to adjust for such sampling biases when calculating climatological means. The method is demonstrated using carbonyl sulfide (OCS) measurements at 16 km altitude from the ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform 15 Spectrometer). At this altitude, OCS mixing ratios show a steep gradient between the poles and equator. ACE-FTS measurements, which are provided as vertically resolved profiles, and integrated stratospheric OCS columns are used in this study. The bias adjustment procedure requires no additional observations other than the satellite data product itself and is expected to be generally applicable when constructing climatologies of long-lived tracers from sparsely and heterogeneously sampled satellite data. In a first step of the adjustment procedure, a regression model is used to fit a 2-D surface to all available ACE-FTS OCS measurements as a function of day-of-year and latitude. The regression model fit is used to calculate an adjustment factor, 20 which is then used to adjust each measurement individually. The mean of the adjusted measurement points of a chosen spatio-temporal frame is then used as the bias-free climatological value. When applying the adjustment factor to seasonal averages in 30° zones, the maximum spatio-temporal sampling bias adjustment was 11 % for OCS mixing ratios at 16 km and 5 % for the stratospheric OCS column. The adjustments were validated against the much denser and more homogeneous OCS data product from the limb-sounding MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument, and both the direction and sign of the adjustments were in agreement with the adjustment of the ACE-FTS data.

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Validating the reported random errors of ACE‐FTS measurements

Cited by 14 publications

References 45 publications

Precision estimate for Odin‐OSIRIS limb scatter retrievals

Precision estimate for Odin‐OSIRIS limb scatter retrievals

Detecting physically unrealistic outliers in ACE-FTS atmospheric measurements

On sampling bias adjustment for sparsely observing satellite instruments for the example of carbonyl sulfide (OCS)

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