the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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.
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Status: open (until 16 Feb 2025)
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RC1: 'Comment on egusphere-2024-3632', Anonymous Referee #1, 20 Jan 2025
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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
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
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