the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Retrieval and Validation of Total Seasonal Liquid Water Amounts in the Percolation Zone of Greenland Ice Sheet Using L-band Radiometry
Abstract. Quantifying the total liquid water amounts (LWA) in the Greenland ice sheet (GrIS) is critical for understanding GrIS firn processes, mass balance, and global sea-level rise. Although satellite microwave observations are very sensitive to ice sheet melt and thus can provide a way of monitoring the ice sheet melt globally, estimating total LWA, especially the sub-surface LWA, remains a challenge. Here, we present a microwave retrieval of LWA over Greenland using enhanced resolution L-band brightness temperature (TB) data products from the NASA Soil Moisture Active Passive (SMAP) satellite for the 2015–2023 period. L-band signals receive emission contributions deep in the ice sheet and are sensitive to the liquid water content (LWC) in the firn column. Therefore, they can estimate the surface-to-subsurface LWA, unlike higher frequency signals (e.g., 18 and 37 GHz bands), which are limited to the top few centimeters of the surface snow during the melt. We used vertically polarized TB (V-pol TB) with empirically derived thresholds to detect liquid water and identify distinct ice sheet zones. A forward model based on radiative transfer in the ice sheet was used to simulate TB. The simulated TB was then used in an inversion algorithm to estimate LWA. Finally, the retrievals were compared with the LWA obtained from two sources. The first source was a locally calibrated ice sheet energy and mass balance (EMB) model, which was forced by in situ measurements from six automatic weather stations (AWS) of the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and Greenland Climate Network (GC-Net) located in the percolation zone of the GrIS. The second source was the corresponding LWA obtained from the Glacier Energy and Mass Balance (GEMB) model within the National Aeronautics and Space Administration’s (NASA) Ice-sheet and Sea-Level System Model (ISSM). The retrievals show generally good agreement with both the references, demonstrating the potential for advancing our understanding of ice sheet physical processes to better project Greenland’s contribution to the global sea level rise in response to the warming climate.
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Status: open (until 17 Dec 2024)
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RC1: 'Comment on egusphere-2024-2563', Anonymous Referee #1, 25 Oct 2024
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This manuscript introduces a highly relevant and impactful application of L-band radiometry in a relatively unexplored research field. The manuscript is generally of very high quality, well written, and with excellent figures. I recommend a few clarifications and comments below. I look forward to seeing the progress on this manuscript and the further development of this method (data product?) in the future.
1. At the end of the introduction, you mention and cite a few previous attempts using passive microwave to quantify liquid water on the ice sheet. Can you briefly summarize the work to date and mention how the content of the manuscript adds to or differs from the current status of the subject?In my opinion one of the primary novelties of the manuscript is the demonstration of liquid water retrieval with single-angle L-band satellite observations. You might also want to consider citing the below paper which also demonstrated single-incidence angle retrievals of snow liquid water, but using a ground-based radiometer.Naderpour, R., Houtz, D., & Schwank, M. (2021). Snow wetness retrieved from close-range L-band radiometry in the western Greenland ablation zone. Journal of Glaciology, 67(261), 27-38.
2. In equation (1) isn’t this neglecting reflection?
3. Can you clarify in the RT model if multiple scattering or coherence are being considered or not? I see now in line 216 “incoherent approach”, can you quickly qualitatively explain this assumption?
4. Line 207, is there any justification to choosing the frozen and melt season reference dates? These would also vary with latitude and elevation?
5. I don’t quite understand in line 215 how the top layer is considered infinite thickness and then discrete thickness layers are used beneath this? Maybe this just means that no attenuation is considered in these layers, only refraction, so it is independent of layer thickness?
6. In line 248, How is 5% determined to be the maximum volume fraction of water? What about large supraglacial lakes?
7. Line 260. Can you explain “the inversion only considered increasing TBs for LWA quantification”. How is “increasing” versus “decreasing” determined? From one daily average to the next? Does this assume that melt always increases brightness temperatures? What about the reflective effect after water volume fraction becomes high and TB decreases again?
8. Line 363, “The AWS measurements that run the model” maybe “The AWS measurements for which the model was run” or “The AWS measurements that are the driving inputs of the model”.
9. Line 416 “2025 – 2023” I think you mean 2021-2023?
10. Line 498 mentions firn aquifers. What is the current status of identifying these? Will they be unidentifiable in the product because the frozen versus melt season TBs do not vary much? Are they apparent in the magnitude of the frozen season TBs? I believe this has been addressed to some degree in the literature, it might be helpful to add some references.11. In addition to the technical limitations mentioned in the conclusion, I believe it could show great impact to also discuss longer-term plans and potential of this dataset. E.g. Is there any plan to provide integrated melt-water estimates across the ice sheet or use these retrievals in a bigger picture Surface Mass Balance study? Is there a path or plan towards generating a SMAP data product based on this algorithm?
Citation: https://doi.org/10.5194/egusphere-2024-2563-RC1
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