the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Dec 2024
Moisture Budget Estimates Derived from Airborne Observations in an Arctic Atmospheric River During its Dissipation
Abstract. This study quantifies the evolution of the moisture budget components of an Arctic atmospheric river (AR) derived from airborne observations from two research flights on consecutive days. We investigate how poleward transport of warm and moist air masses by AR generates precipitation near the sea ice edge, and how advection and evaporation additionally affect the local moisture amount during the dissipation phase of the AR.
Using the High Altitude and LOng Range Research Aircraft (HALO), we derive the atmospheric moisture budget components (local tendency of moisture, evaporation, moisture transport divergence and precipitation) within an intense Arctic AR event during the HALO-(𝒜𝒞)3 aircraft campaign. The components are quantified in sectors ahead of the AR-embedded cold front by airborne observations from dropsondes, radiometers and a radar. They are compared with model-based values from reanalyses and numerical weather prediction simulations.
The observational moisture budget components in the pre-cold frontal sectors contribute up to ± 1 mm h-1 to local moisture amount. The moisture transport divergence primarily controls the local moisture amount within the AR, while surface interactions are of minor importance. Precipitation is heterogenous but overall weak (<0.1 mm h-1) and evaporation is small. Although the AR decreases in strength, the budget components change from drying to significant moistening, mainly due to moisture advection. For this AR, we demonstrate the feasibility of the budget closure using single aircraft measurements, although we find significant residuals. Model-based comparisons suggest that these residuals stem from grid sub-scale variability within the AR corridor.
- Preprint
(18703 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2024-3632', Anonymous Referee #1, 20 Jan 2025
The authors quantify and discuss the contributions of evaporation, precipitation and transport to local changes in integrated water vapour in an Arctic atmospheric river using airborne observations. Understanding moisture budgets in such extreme advection events is an interesting topic, and the manuscript is technically sound.
What I am missing is to understand why the authors did what they did, and how the results presented in this paper advance our understanding of processes controlling Arctic Atmospheric rivers in general. The authors define their research goals in the introduction, but do not really motivate them based on identified knowledge gaps. Therefore, when those research questions are answered later in the manuscript, is was not obvious to me how the answers fit into and extend or improve the big-picture understanding.
While I would recommend a major revision to allow the authors to more clearly motivate their approach and explain the meaning of the results, the paper would also be publishable with some minor changes, as it is technically sound and, in most parts, clearly written.
Minor suggestions:
Abstract: The abstract would benefit from 1-2 sentences placing the research into a wider context (see above).
Line 82: I suggest deleting “pioneering” and “of this study”
Line 120 ff: choose consistent tense for describing data processing
Line 131: The sentence on the GTS could be misleading, as the GTS only collects and provides observations, whereas data assimilation happens at different modelling centers.
Line 137: Is there no difference between zonal and meridional spacing?
Line 159: “quite strong” - can you quantify that?
Line 176: a large extent of the atmospheric river? Or an area from the AR to Scandinavia?
Eq.1: The manuscript finds that transport divergence dominates the budget – is that a characterization of the AR or just stating the fact that the AR is moving (out of the observed box when we see drying through advection)?
Eq. 5: Why is this cd rather than ch? Are two values for two ranges of wind speeds the latest state of research on this? What about the COARE algorithm?
Line 398 – what is G2?
Figure 9: what processes drive the decay in IWP and IVT? What can we learn from the strong reduction in transport than water vapour? Do you expect this to generalize to other ARs?
line 555: Why not ICON data, which showed the better match?
Line 592: I did not see where these references show that ERA5 overestimates Arctic precip.
Line 608: “Our airborne analysis reveals the significance of small-scale precipitation within Arctic ARs as a key finding.” I would have summarized that precipitation is small and hard to quantify.
Line 640: see comment on equation 1.
Citation: https://doi.org/10.5194/egusphere-2024-3632-RC1 -
RC2: 'Comment on egusphere-2024-3632', Anonymous Referee #2, 12 Feb 2025
Using airborne observations from the HALO-(AC)³ aircraft campaign, the authors investigate the moisture budget of an Arctic atmospheric river (AR) during its dissipation stage. Their results show that within the AR's pre-cold frontal sectors, local moisture tendency is primarily governed by moisture transport divergence, while surface interactions, including evaporation and precipitation, play a minor role. The evolution of the moisture budget reveals an initial drying phase driven by moisture transport divergence, which later transitions to moistening due to moisture advection. This study demonstrates that it is possible to close the moisture budget within an AR using single-aircraft measurements.
Most previous studies on ARs have relied on reanalyses and climate model data to investigate and characterize these features. In contrast, studies utilizing in-situ observations remain relatively rare. In this regard, the present study is particularly valuable to the AR research community. Observational studies like this one are crucial, as they provide empirical data that can help constrain the representation of ARs in both reanalyses and climate models. Overall, this manuscript is well-written and well-structured, with a clear logical flow. I appreciate the considerable effort the authors have invested in this work. I find the manuscript well-suited for publication in ACP and have only minor comments, which I outline below. These comments primarily aim to improve the manuscript’s clarity. I recommend publication after the authors address these minor revisions.
Specific Comments:
- Only S1 is investigated with data from ICON-2km and ERA5. It would be good to do some analyses on S2, S3, and S4 using model data to check if the temporal evolution of the moisture budget based on model data is consistent with that based on airborne observations shown in the manuscript.
- Line 25: Arctic ARs are also projected to increase (see Ma et al., 2024a). Please consider citing this paper.
- Line 33: Ma et al. (2024b) also shows that ARs play a critical role in inducing Arctic heat extreme at the synoptic timescale. Please consider citing this paper.
- Lines 187-188: “became drier within the AR”, do you mean “became drier within the AR from RF05 to RF06”?
- Line 222: Please define “lateral width”
- Lines 221-223: I am not quite sure how to interpret this sentence. Could you explain in more details?
- Figure 3 caption: What is Arctic AR flight corridor? Is it the area enclosed by the red rectangle?
- Line 252: Please indicate the region of S1 in Figure 3 using dashed orange lines (similar to what you have shown in Figure 8).
- Lines 265-266: Please briefly explain what PAMTRA does.
- Line 274: What is the length of the “segments”?
- Line 280: How does the mean local IWV change vary with the length of the segments (i.e., the sensitivity of local IWV change to segment length)?
- Figure 8: What are those big white triangles?
- Lines 400-401: It is true for S3 and S4. It seems to me that it is not true for S1 and S2.
- Line 417: “box widths”, do you mean “box heights”?
- Lines 443-444: Is the mass convergence weak or strong for this AR?
- Line 561: What do you mean by “the expansion of the IVT”?
- Line 564: What is “IVT spreading”?
- Figure 17: Please define “AR region” shown in the legend.
- Line 599: Why does radar show higher rate? Based on the legend on Figure 17, the mean precipitation rate in ICON HALO Track is 0.06, while that in radar HALO is 0.04.
- Figure 17: Where are the highlighted radar-based values along the flight? Could you explicitly point them out?
- Line 601: what is the difference between “AR corridor” and “AR flight corridor”?
- Line 642: Again, what is the “spreading of the IVT field”?
References:
Ma et al. (2024a): https://www.nature.com/articles/s41467-024-45159-5
Ma et al. (2024b): https://acp.copernicus.org/articles/24/4451/2024/
Citation: https://doi.org/10.5194/egusphere-2024-3632-RC2
Data sets
Unified Airborne Active and Passive Microwave Measurements over Arctic Sea Ice and Ocean during the HALO-(AC)³ Campaign in Spring 2022 Henning Dorff et al. https://doi.org/10.1594/PANGAEA.963250
ERA5 hourly data on pressure levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.bd0915c6
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 176 | 34 | 13 | 223 | 14 | 15 |
- HTML: 176
- PDF: 34
- XML: 13
- Total: 223
- BibTeX: 14
- EndNote: 15
Viewed (geographical distribution)
| Country | # | Views | % |
|---|---|---|---|
| United States of America | 1 | 97 | 43 |
| Germany | 2 | 47 | 21 |
| China | 3 | 11 | 4 |
| France | 4 | 11 | 4 |
| India | 5 | 7 | 3 |
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
- 97