the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Jun 2023
An inverse model to correct for the effects of post-depositional processing on ice-core nitrate and its isotopes: model framework and applications at Summit, Greenland and Dome C, Antarctica
Zhuang Jiang
Becky Alexander
Joel Savarino
Abstract. Comprehensive evaluation of the effects of post-depositional processing is a prerequisite for appropriately interpreting ice-core records of nitrate concentration and isotopes. In this study, we developed an inverse model that uses archived snow/ice-core nitrate signals to reconstruct primary nitrate flux and its isotopes (δ15N and Δ17O). The model was then applied to two polar sites, Summit, Greenland and Dome C, Antarctica using measured snowpack nitrate concentration and isotope profiles in the top few meters. At Summit, the model successfully reproduced the observed atmospheric 15δN(NO3–) and Δ17O(NO3–) and their seasonality. The model was also able to reasonably reproduce the observed snowpack nitrate profiles at Dome C as well as the skin layer and atmospheric δ15N(NO3–) and Δ17O(NO3–) at the annual scale. The calculated Fpri at Summit was 6.9 × 10-6 kgN m2 a-1 and the calculated Δ17O(NO3–) of Fpri is consistent with atmospheric observations in the northern hemisphere. However, the calculated 15δN(NO3–) of Fpri displays an opposite seasonal pattern to atmospheric observations in the northern mid-latitudes, but is consistent with observations in two Arctic coastal sites. The calculated Fpri at Dome C varies from 1.5 to 2.2 × 10-6 kgN m-2 a-1, with δ15N(NO3–) of Fpri varying from 6.2 to 29.3 ‰ and Δ17O(NO3–) of Fpri varying from 48.8 to 52.6 ‰. The calculated Fpri at Dome C is close to previous estimated stratospheric denitrification flux in Antarctica, and the high δ15N(NO3–) and Δ17O(NO3–) of Fpri at Dome C also point towards the dominate role of stratospheric origin of primary nitrate to Dome C.
- Preprint
(1707 KB) - Metadata XML
- BibTeX
- EndNote
Zhuang Jiang et al.
Status: open (extended)
-
RC1: 'Comment on egusphere-2023-1054', Anonymous Referee #1, 27 Aug 2023
reply
Ice core nitrate isotope compositions may be useful to reconstruct atmospheric nitrate isotope compositions in the past with paleoclimate implications. Previous studies have investigated impacts of post-depositional processing on isotope compositions of nitrate preserved in snow and ice. In this work, Jiang et al. revised the TRANSITS model (a one-dimension snow photochemistry model) to calculate atmospheric nitrate deposition flux and isotope compositions based on snow records. Exemplary applications were applied to Summit and Dome C data and the calculated results were compared with measurement data. Although future efforts are needed to further evaluate and improve this model, this work is an important step towards a more precise interpretation of ice core nitrate isotope data. The equation derivation appears correct, and the model logic looks scientifically reasonable to me. However, the writing of this manuscript is too technical to readers outside the small community of post-depositional possessing of nitrate isotopes, and one may need to read all papers written by the authors previously to understand this work. This writing style is not easy for casual readers (especially for atmospheric scientists who do not work in cryospheric sciences and isotopes) to follow. I spent considerable time to digest the manuscript, even though I am kind of familiar with topics discussed in this manuscript. I therefore have some suggestions that aim to improve the clarity of this manuscript.
- Line 29: Please define Fpri at the very beginning. For readers who did not read the authors’ previous papers, they would not understand what it is.
- Lines 263-265: Please rewrite this sentence. It is not clear.
- The definition listed in Table 1 is unclear. For example, I do not understand what “d15N of archived nitrate flux” means. Does a flux have a d15N value? Does it mean d15N of archived nitrate? In my opinion, these definitions make the manuscript difficult to follow.
- There are 13 input parameters listed in Table 1, but only 6 are described in Table 2. It is difficult for readers to check everything throughout different parts of the manuscript and from different papers.
- Section 3: It is recommended to explicitly describe what parameters were used to do the calculation and what parameters were used to compare with the model results at each site. For example, it is stated that weekly data from Jiang et al. (2022) were used (Section 3.1). I need to re-read Jiang et al. (2022) to understand what these data are. In addition, I do not fully understand how the authors tested their model results. Did they use the atmospheric nitrate data reported in Jiang et al. (2022) or the surface snow as described in page 12? Where are the data from?
- Lines 387-389 and 397-398: I would not say that the seasonality of modeled d15N agrees well with observation based on Figure 3. As noted by the authors, the model cannot capture the seasonal variation from September to April.
- Lines 428-430: Could the authors tune the epsilon value in the model, give a quick estimation what epsilon value may reproduce the observational data, and briefly discuss if this epsilon value is reasonable? This test should be straightforward.
- Figure 5: I am confused what the results of “inverse model” mean. The inverse model used measured isotope values as input parameters. So I guess the model “results” plotted in this graph are the isotope values of “deposition nitrate” calculated from the model or the model input (calculated averages of measured values?). Please clarify.
- Figure 6: Is it possible to show a similar figure for Summit so that readers can better understand how the model behaves if we just look at the annual average?
- The authors may notice the new work by Shi et al. (2023), which is highly relevant to this manuscript and was just published after the submission of this manuscript. Please cite this work during the revision: Shi, G., Buffen, A. M., Hu, Y., Chai, J., Li, Y., Wang, D., & Hastings, M. G. (2023). Modeling the complete nitrogen and oxygen isotopic imprint of nitrate photolysis in snow. Geophysical Research Letters, 50, e2023GL103778
Citation: https://doi.org/10.5194/egusphere-2023-1054-RC1
Zhuang Jiang et al.
Zhuang Jiang et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 231 | 68 | 17 | 316 | 12 | 13 |
- HTML: 231
- PDF: 68
- XML: 17
- Total: 316
- BibTeX: 12
- EndNote: 13
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1