the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Dec 2024
Quantifying biases in TROPESS AIRS, CrIS, and joint AIRS+OMI tropospheric ozone products using ozonesondes
Abstract. Quantifying changes in global and regional tropospheric ozone are critical for understanding global atmospheric chemistry and it's impact on air quality and climate. Satellites now provide multi-decadal records of daily global ozone profiles, but previous studies have found large disagreements in satellite-based ozone trends, including in trends from different products based on the same spectral radiances. In light of these disagreements, it is critical to quantify to what degree the observed trend is attributable to measurement error for each product by comparing satellite-retrieved ozone to long-term measurements from ozonesondes. NASA's TRopospheric Ozone and its Precursors from Earth System Sounding (TROPESS) project provides satellite retrievals of ozone from a suite of instruments, including CrIS, AIRS, and multispectral combinations such as AIRS and OMI (joint AIRS+OMI) using a common algorithm. We compare the long-term changes in these products to ozonesondes and find that the evolution of global tropospheric ozone satellite-sonde bias for TROPESS CrIS (0.21 ± 3.6 % decade-1, 2016–2021), AIRS (-0.41 ± 0.57 % decade-1, 2002–2022), and joint AIRS+OMI (1.1 ± 1.0 % decade-1, 2004–2022) is approximately one third the magnitude of trends in global tropospheric ozone reported by the Tropospheric Ozone Assessment Report Phase 1 (TOAR-I). We further quantify the bias in regional trends, which tend to be higher but with a smaller number of sondes, which can impact the satellite-sonde bias and trend. Our work represents an important basis for the utility of using satellite data to quantify changes in atmospheric composition in future studies.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-3701', Anonymous Referee #1, 07 Jan 2025
The study by Pennington et al. exploits ozonesondes to quantify the bias and drift in several satellite records of tropospheric ozone. Overall, this is a nice study providing valuable constraints on TROPRESS products but especially on the methods to QC the ozonesonde data before and after the satellite operators have been applied to the sondes (i.e. allowing for like-for-like comparison between the two). Therefore, this manuscript is suitable for publication in ACP subject to some minor comments.
Minor Comments:
Section 2: CrIS, AIRS and OMI have already been defined in Section 1, so do not need to be redefined in Section 2.
Line 121: Space needed between “15” and “km”.
Line 162: Should “altitude” be “altitudes”?
Line 182: Should “compared to climatology” be “compared to a climatology”?
Line 247: “AIRS’ and CrIS’ error”…should this be error or bias? On line 247 you have used “bias” and “error”. However, they are subtly different things. Please be consistent.
Figure S5: The multiple lines for each colour (red, black or blue) represent lat bins at 10 degree intervals. However, it is not possible to know which profile is for which lat bin. Or is the main point that they are typically close together? If the latter, please make that clear in the Figure caption or discussion.
Line 260: The authors cite Miles et al., 2015 for the RAL GOME-2 data. A more up to date study in TOAR-2 is that from Pope et al., (2023 - https://acp.copernicus.org/articles/23/14933/2023/acp-23-14933-2023.html) using multiple RAL Space products. Thus, could be useful to cite that ref on line 260 as well.
Line 282: The authors say “A previous study” but it is unclear what the study is. Can you provide the reference in the text?
Line 318: “Joint AIRS+OMI does not include high ozone values in the Northern high latitudes due to the low joint AIRS+OMI data volume near the poles”. Can the authors please expand on this statement as unclear to follow. Why would it not include high ozone values because of low sampling? Would you not expect to have normal levels (be this low or high values relative to other latitude bands) but just a noisier signal as the data volumes are lower?
Line 320: I know the authors cite Manney et al., 2017 for “multiple tropopauses”, however, it might be useful to add a sentence explaining who you get multiple tropopauses.
Table 2-4: It is clear that N is the sample size. However, I cannot see this defined in the Table caption. Thus, for clarity, please do so. Also, e.g. JJA is defined as June/July/August in lots (in not all) instances. You probably only need to define the season(s) once and then use the abbreviations.
Citation: https://doi.org/10.5194/egusphere-2024-3701-RC1 -
RC2: 'Comment on egusphere-2024-3701', Anonymous Referee #2, 13 Jan 2025
This paper evaluates the TRopospheric Ozone and its Precursors from Earth System Sounding (TROPESS) CrIS, AIRS, and AIRS+OMI ozone products. It quantifies the biases and bias trends in the products compared to quality controlled ozonesonde data to assess the suitability of the products for trend calculations. Multiple methods for quality controlling the ozonesonde data are also considered. The analysis is rigorous and thorough and provides important validation of the TROPESS products. I list general and specific comments below.
General Comments
- While the main focus of the paper is on quantifying biases and trends in bias in the TROPESS products, it would be helpful to provide more discussion of the ozone trends themselves seen in the TROPESS products in order to provide more context for the discussion of biases.
- Since MLS is used to quality control the sonde data, more discussion of how much uncertainty is present in MLS would be helpful to justify this choice.
Specific Comments
Line 92: Please explain why you focus specifically on SNPP-CrIS
Line 131: Is the Fu et al joint retrieval the same as what is implemented in MUSES?
Line 169: sonde operator or satellite operator?
Line 217: Please clarify if you are actually using the moving block bootstrapping in this study.
Line 239: Does “CrIS errors can be comparable…” mean some individual points in Fig. 5a are comparable, or something else?
Fig. S5: It’s a bit hard to interpret this figure where some of the red or blue lines cross the black lines. Perhaps light to dark shading or different linestyles could be used to indicate which lines correspond to different latitude bands?
Citation: https://doi.org/10.5194/egusphere-2024-3701-RC2 - CC1: 'Comment on egusphere-2024-3701', Owen Cooper, 30 Jan 2025
Data sets
TROPESS satellite data NASA TROPESS team https://disc.gsfc.nasa.gov/datasets?page=1&project=TROPESS
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