the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Oct 2024
Astroclimes – measuring the abundance of CO2 and CH4 in the Earth's atmosphere using astronomical observations
Abstract. Monitoring the abundance of greenhouse gases is necessary to quantify their impact on global warming and climate change. Carbon dioxide (CO2) and methane (CH4) are the two most important greenhouse gases when it comes to global warming, and there are many ground-based networks, such as TCCON, and satellites, such as OCO-2, OCO-3 and GOSAT-2, that are tasked with measuring the total column volume mixing ratio (VMR) of either one or both of these gases. However, these networks all rely on sunlight to carry out their measurements. For column measurements at night, a technique called integrated-path differential absorption (IPDA) has been employed recently using a lidar system. We present a new algorithm, Astroclimes, that hopes to complement and extend nighttime CO2 and CH4 column measurements. Astroclimes can measure the abundance of greenhouse gases on Earth by generating a model telluric transmission spectra and fitting it to the spectra of telluric standard stars in the near-infrared taken by ground-based telescopes. We carried out new observations for one night with the CARMENES spectrograph in the Calar Alto Observatory, Spain, as well as a weather balloon launch to measure a local atmospheric profile. After correcting for a small bias in CO2 estimates, we show that our CO2 and CH4 measurements exhibit good agreement with the refereed literature, and our average relative uncertainties for the column-averaged dry air mole fraction of CO2 and CH4 are 0.4 % and 0.5 %, respectively. These uncertainties are precision errors based on the 68 % confidence intervals of our MCMC analysis posterior distribution, they do not include any systematic errors or biases. A historical analysis of archival data from several different instruments will be carried out in future work to further test our algorithm and to identify and quantify potential systematic biases.
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RC1: 'Comment on egusphere-2024-2433', Anonymous Referee #1, 18 Oct 2024
In the previous short review reply required for starting up the discussion phase, I voted the paper as “good” in all relevant categories, because in my feeling it is important to make the atmospheric community aware of the existence of astronomical observations, which can be useful for the quantification of greenhouse gases (GHG) in the terrestrial atmosphere. As passive methods (specifically solar absorption spectroscopy) are restricted to daytime observations, this might be a useful complementation of existing approaches. I also appreciate the rigorous approach of the authors of even considering a balloon launch carrying instrumentation for in-situ measurement of CO2 mixing ratio and the comparison with TCCON and space borne data.
On the downside, the authors seem to lack connection with the community doing the operational atmospheric GHG remote sensing observations and therefore seem unaware of the requirements (measurements of column-averaged GHG abundances need to be very accurate to be useful) and the current state of art. This becomes apparent in the manuscript in several places, e.g., MIPAS, a limb sounder, which went out of order more than a decade ago, certainly is not a reasonable source for GHG profiles, as the retrieved column amount critically depends on the tropospheric mixing ratio. The TCCON community meanwhile has established a model-assisted approach for generating quite realistic a-priori GHG profiles.
The authors compare the quality of their measurements with the required precision requirements for detecting the large sources and sinks (line 613ff). I would doubt this is a reasonable measure for the required performance. Daytime measurements are much easier to perform and offer a significantly higher precision and accuracy. Dedicated observations using up observation time from huge astronomical telescopes would hardly be competitive with daytime solar spectroscopy, so only the use of calibration measurements performed in the context of astrophysical research purposes remains as a viable option. What can be learned from nighttime observations? Recently, TCCON has been complemented by COCCON, which uses portable field-deployable spectrometers. These spectrometers can be deployed near interesting sources (as cities, coal mines, landfills, …) for collecting dedicated observations, while astronomical observatories tend to be at remote locations. The variability and trend of background CO2 is easily monitored by the subset of remote TCCON stations.
The remaining interesting gap, which could be filled by astronomical observations, would be the explicit measurement of the complete diurnal XCO2 cycle. This task, however, would require observations of excellent quality and a very high level of consistency between daytime and nighttime observations and the data analysis chains. Most observatories probably reside in regions, which are not too interesting in regard of the diurnal CO2 cycle (remote desert areas), as the interesting signals are created either by biogenic fluxes or by the variable anthropogenic sources. There might be some observatories located in semi-arid high plains, where the study of the biogenic fluxes would be scientifically useful. Some older observatories today located near metropolitan areas might be interesting study places for anthropogenic signals, but probably these sites do not offer the required advanced instrumentation for collecting stellar spectra of sufficient quality.
As mentioned before, observations of the diurnal XCO2 cycle would require a very high level of consistency between the nighttime observations and daytime observations. The daytime observations could be realized by collocating a COCCON spectrometer, which offers spectral resolution comparable to the astronomical observations. Furthermore, the same data processing software needs to be used for daytime and nighttime measurements. This could be achieved by extending the data analysis chain as realized by TCCON for handling nighttime observations. For this purpose, spectral models of telluric standard stars would be implemented in the GGG2020 software to replace the solar source by a telluric standard star source when analyzing nighttime observations. (Concerning the airglow emission lines, the most rigorous strategy would be to perform on/off measurements, then the background spectrum recorded at the same airmass as the stellar observation could be subtracted from the stellar spectrum.) If the authors prefer use of their own software development, the code needs to extended to handle the analysis of daytime observations.
I suggest a significant revision of the paper, with stronger focus on the description of the astronomical observations, their performance characteristics and availability (this would provide better insight of what can be expected from astronomical observations in general for measuring atmospheric GHG abundances). The use of different codes for nighttime and daytime measurements appears problematic to me, as even a very minor bias would impair the usefulness of adding nighttime measurements. A demonstration of compatibility using collocated daytime-nighttime measurements is required. Finally, particular attention shall be given to ensure consistent data analysis schemes between daytime and nighttime measurement. Implementation of the required extensions for handling nighttime observations into a recognized operational code used for GHG data analysis as GGG2020 would appear more useful to me than the development of own code.
Citation: https://doi.org/10.5194/egusphere-2024-2433-RC1 -
RC2: 'Comment on egusphere-2024-2433', Matthias Buschmann, 19 Oct 2024
The paper "Astroclimes - measuring the abundance of CO2 and CH4 in the Earth’s atmosphere using astronomical observations" by Fetzner-Keniger et al. presents the retrieval of atmospheric CO2 and CH4 from nighttime spectra of telluric standard stars. This is important work and could enhance the current observation capabilities of the atmospheric carbon cycle.
However, the paper tries to do two things at once:
a) introduce a newly developed retrieval algorithm and
b) compare the results against known measurementsto a) There are mature retrieval algorithms like GFIT, SFIT or PROFFIT used in the TCCON, NDACC and COCCON networks. From an algorithm perspective the authors should first validate their algorithm against any one of these. I'm sure the respective communities will be happy to collaborate and share a set of their spectra to test against. This comparison would evaluate the Astroclimes algorithm performance and using the same or similar prior information and atmospheric parameters has the benefit of reduced overhead in trying to re-invent the wheel (e.g. the used merge algorithm).
In turn, the standard retrievals could be adjusted to work with the presented stellar spectra yielding a robust result derived from recognized standard methods.to b) The comparison/validation presented here has several issues. The required precision to capture the atmospheric variability in CH4 or CO2 requires closer spatial and/or temporal collocation. Thus a comparison to TCCON Orléans is not advisable and great care has to be taken in collocating satellite overpasses. The comparison against available atmospheric reanalysis models of CO2 and CH4 would mitigate some of the issues.
The restriction to measurements from one night is understandable, but if the data exists should be extended to at least a year to test if the relatively well known seasonal cycle of the trace gases can be reproduced or even if any long-term trend is visible.
An additional issue are the reported uncertainties. The variability in the one night of measurements in Fig 13 and 14 respectively suggests a large standard deviation of about maybe 10 ppm (XCO2) and maybe 50 ppb (XCH4) which would mean a relative error of about 2.5% instead of the reported 0.5%.
An additional remark: There have been attempts to perform nighttime measurements from ground-based spectrometers from the TCCON and NDACC communities before. See e.g. https://doi.org/10.1016/S0022-4073(02)00069-9 or https://doi.org/10.5194/amt-10-2397-2017
I would encourage the authors to connect with any of the TCCON-, COCCON- or NDACC-PIs. The prospect of potentially longer (night) time series of atmospheric spectra of sufficient quality to retrieve trace gases is very much worth pursuing and I encourage re-submission after addressing the mentioned issues.
Citation: https://doi.org/10.5194/egusphere-2024-2433-RC2
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