Shashwat Shukla

The stability of Antarctic ice shelves is closely linked to the properties of the firn layer, which regulates meltwater retention and influences ice shelf vulnerability to hydrofracturing. Firn Densification Models (FDMs) provide valuable insights into the firn structure, but key properties such as grain size are often parameterized using simple approximations, leading to significant uncertainties, especially in regions lacking in-situ validation. Here, we infer an effective firn grain-size parameter across Antarctic ice shelves, constrained by 15 years (2007–2021) of active microwave observations from the C-band Advanced Scatterometer (ASCAT). Within this framework, we use the Institute for Marine and Atmospheric Research Utrecht Firn Densification Model (IMAU-FDM) to prescribe the state of the firn layer (layer thickness, density, temperature, and liquid water content) and couple it with the Snow Microwave Radiative Transfer (SMRT) model to simulate radar backscatter. Grain size is treated as an unknown microstructural parameter and is optimized by minimizing the misfit between FDM–SMRT simulations and ASCAT observations. The retrieved parameter provides an observationally constrained measure of effective firn microstructure within the adopted FDM–SMRT framework, although independent validation is required before interpreting it as an absolute physical grain-size measurement. The framework is further used to examine how the sensitivity of ASCAT backscatter varies across firn regimes, and how this influences the interpretation of backscatter in terms of firn air content (FAC; the vertically integrated pore-air content of the firn column). Our results show broad consistency between the optimized effective grain size and IMAU-FDM estimates in high-FAC regions, where ASCAT backscatter is most sensitive to interannual variability in grain size. In contrast, larger discrepancies emerge in intermediate- to low-FAC regions, particularly on the Amery Ice Shelf, where ice saturation in the firn (pore-space depletion) influences grain growth. The sensitivity experiments indicate that inversion constraints are regime-dependent, with the strongest sensitivity to grain size in intermediate firn regimes and weaker constraints in strongly depleted firn. Furthermore, by statistically reducing grain-size-driven scatter after inversion, we present a proof of concept for a more interpretable backscatter–FAC relationship, which may support future development and evaluation of FAC-oriented diagnostic retrieval frameworks. These findings provide a basis for improving firn model parameterization and supporting large-scale diagnostic monitoring of firn-state variability across Antarctic ice shelves in a warming climate.

IntroductionThe question if life exists outside of Earth has been an important driver of Solar system exploration and exoplanet research in the last few decades [1-3]. Although terrestrial analogue research provides insight into this question [4-5], no definitive evidence of life outside Earth has been found at this moment [6]. This raises the question whether the current methodology for analogue research is sufficient, or needs changes.To answer this, we use AI to systematically analyse 2500 papers that use terrestrial analogues or analogue research methods to study life outside Earth. For each, we determined the used methods, scales at which they are applied, and investigated research questions. This gives new insights in which methods are used and underused, and which methods should be used in combination to improve the methodology towards understanding and detection of life outside Earth MethodsA systematic literature search was performed for analogue research related to life outside Earth. The resulting initial set of articles were analysed manually to determine the used methods, scales, and research questions. Then, articles referred to in review papers were collected to complete the literature compilation.This literature compilation was then analysed by using the Ollama framework [7] in combination with Langchain [8] to run the qwen3:0.6b LLM [9]. Analysis uses the following pipeline: 1) conversion to text-containing pdfs, 2) extraction of text sections 3) extraction of method sections from other sections 4) asking a series of binary question on sections relevant for methods, scales, and research questions to check the usage within each single article. ResultsThe initial compilation included ~700 articles, ~100 of which could be classified as reviews. The manual analysis showed the following:Interdisciplinary research is done, but remains limited. This hinders finding connections between biosignatures and other observables.Research on how to span different spatial scales, ranging from molecular to planetary scales and exoplanetary scales, is lacking. Here, especially the field-scale is underutilised, which may provide importance in linking potentially habitats to actual biosignatures.There is no clear separation between inhabited, uninhabited, and previously inhabited but no longer habitable environments. This affects the reliability of biosignature interpretation. Both false negatives and false positives are overlooked, with almost no research focusing on false negatives.The reviews increased the dataset to a total of ~2500 articles. These were all analysed by AI, with the initial set functioning as a control. AI-analysis deviates significantly from manual analysis, overall indicating higher numbers for each used method, scale, and research question. However, AI confirms that there is a small number of papers that utilises the field scale, indicating at least an agreement with the manual analysis that this scale is underutilised.Figure 1 Correlation diagram showing usage of observational scales and methods. Colours represent that certain methods or scales are used in the same paper (blue) or that they tend to be used separately (red). Light colours to white indicate underused methods and scales. Note that the AI tends give overall higher usage of methods and scales throughout papers, but does not find the same relationships as in the manual analysis. Discussion and conclusionThe research gaps resulting from the manual analysis indicate the need for an integrated, multi-scale framework to advance life-detection strategies. This is partially supported by AI, although improvement of the AI-analysis is needed before final conclusions can be drawn. As examples of suggestions for future research, biologists or biochemists should collaborate with geomorphologists, geophysicists, and imaging spectroscopists, in order to determine the relations between biosignatures on laboratory to field and remote-sensing scales. Futhermore, geologists and biologists should work with exoplanet researchers, to give them insights into the atmospheric processes and exclude false positives and negatives in exoplanetary signs of life. Such collaborations will prove essential to improving the methodology for the search for extraterrestrial life. References[1] C. S. Cockell et al. Astrobiology, 9, 1. (2009). [2] J. Matthey, Platin. Met. Rev., 20, 3. (1976). [3] D. Schulze-Makuch, J. M. Dohm, A. G. Fairén, V. R. Baker, W. Fink, and R. G. Strom Astrobiology, 5, 6. (2005). [4] A. G. Fairén et al. Astrobiology, 10, 8. (2010). [5] F. Biagioli, S. Bay, A. Zerboni, and C. Coleine Int. J. Astrobiol., 24, e29. (2025). [6] J. E. Brandenburg “The Discovery of Microbial Life on Mars.” Int. J. Immunol. Microbiol., 2, 2. (2025). [7] Ollama, Ollama’s documentation. Retrieved from: https://docs.ollama.com (2025). [8] H. Chase LangChain. Retrieved from: https://github.com/langchain-ai/langchain (2022). [9] Qwen Team “Qwen3 Technical Report.” Retrieved from: https://arxiv.org/abs/2505.09388 (2025).

The stability of Antarctic ice shelves is closely linked to the properties of the firn layer, which regulates meltwater retention and influences ice shelf vulnerability to hydrofracturing. Firn Densification Models (FDMs) provide valuable insights into the firn structure, but key properties such as grain size are often parameterized using simple approximations, leading to significant uncertainties, especially in regions lacking in-situ validation. Here, we leverage 15 years (2007–2021) of active microwave observations from the C-band Advanced Scatterometer (ASCAT) to infer an effective firn grain-size parameter across Antarctic ice shelves. Within this framework, we use the Institute for Marine and Atmospheric Research Utrecht Firn Densification Model (IMAU-FDM) to prescribe the state of the firn layer (layer thickness, density, temperature, and liquid water content) and couple it with the Snow Microwave Radiative Transfer (SMRT) model to simulate radar backscatter. Grain size is treated as an unknown microstructural parameter and is optimized by minimizing the misfit between FDM–SMRT simulations and ASCAT observations. The framework is further used to examine how the sensitivity of ASCAT backscatter varies across firn regimes, and how this influences the interpretation of backscatter in terms of FAC. Our results show broad consistency between optimized effective grain size and IMAU-FDM estimates in high-Firn Air Content (FAC) regions, where ASCAT backscatter is most sensitive to interannual variability in grain size. In contrast, larger discrepancies emerge in intermediate- to low-FAC regions, particularly on the Amery Ice Shelf, where ice saturation in the firn (pore-space depletion) influences grain growth. The sensitivity experiments indicate that inversion constraints are regime-dependent, with the strongest sensitivity to grain size in intermediate firn regimes and weaker constraints in strongly depleted firn. Furthermore, by statistically reducing grain-size-driven scatter after inversion, we present a proof of concept for a more interpretable backscatter–FAC relationship. These findings provide a basis for improving firn model parameterization and advancing large-scale monitoring of firn evolution across Antarctic ice shelves in a warming climate.

The stability of Antarctic ice shelves is closely linked to the properties of the firn layer, which regulates meltwater retention and influences ice shelf vulnerability to hydrofracturing. Firn Densification Models (FDMs) provide valuable insights into the firn structure, but key properties such as grain size are often parameterized using simple approximations, leading to significant uncertainties, especially in regions lacking in-situ validation. Here, we leverage 15 years (2007–2021) of active microwave observations from the C-band Advanced Scatterometer (ASCAT) to infer an effective firn grain-size parameter across Antarctic ice shelves. Within this framework, we use the Institute for Marine and Atmospheric Research Utrecht Firn Densification Model (IMAU-FDM) to prescribe the state of the firn layer (layer thickness, density, temperature, and liquid water content) and couple it with the Snow Microwave Radiative Transfer (SMRT) model to simulate radar backscatter. Grain size is treated as an unknown microstructural parameter and is optimized by minimizing the misfit between FDM–SMRT simulations and ASCAT observations. The framework is further used to examine how the sensitivity of ASCAT backscatter varies across firn regimes, and how this influences the interpretation of backscatter in terms of FAC. Our results show broad consistency between optimized effective grain size and IMAU-FDM estimates in high-Firn Air Content (FAC) regions, where ASCAT backscatter is most sensitive to interannual variability in grain size. In contrast, larger discrepancies emerge in intermediate- to low-FAC regions, particularly on the Amery Ice Shelf, where ice saturation in the firn (pore-space depletion) influences grain growth. The sensitivity experiments indicate that inversion constraints are regime-dependent, with the strongest sensitivity to grain size in intermediate firn regimes and weaker constraints in strongly depleted firn. Furthermore, by statistically reducing grain-size-driven scatter after inversion, we present a proof of concept for a more interpretable backscatter–FAC relationship. These findings provide a basis for improving firn model parameterization and advancing large-scale monitoring of firn evolution across Antarctic ice shelves in a warming climate.

The stability of Antarctic ice shelves is closely linked to the properties of the firn layer, which regulates meltwater retention and influences ice shelf vulnerability to hydrofracturing. Firn Densification Models (FDMs) provide valuable insights into the firn structure, but key properties such as grain size are often parameterized using simple approximations, leading to significant uncertainties, especially in regions lacking in-situ validation. Here, we leverage 15 years (2007–2021) of active microwave observations from the C-band Advanced Scatterometer (ASCAT) to infer an effective firn grain-size parameter across Antarctic ice shelves. Within this framework, we use the Institute for Marine and Atmospheric Research Utrecht Firn Densification Model (IMAU-FDM) to prescribe the state of the firn layer (layer thickness, density, temperature, and liquid water content) and couple it with the Snow Microwave Radiative Transfer (SMRT) model to simulate radar backscatter. Grain size is treated as an unknown microstructural parameter and is optimized by minimizing the misfit between FDM–SMRT simulations and ASCAT observations. The framework is further used to examine how the sensitivity of ASCAT backscatter varies across firn regimes, and how this influences the interpretation of backscatter in terms of FAC. Our results show broad consistency between optimized effective grain size and IMAU-FDM estimates in high-Firn Air Content (FAC) regions, where ASCAT backscatter is most sensitive to interannual variability in grain size. In contrast, larger discrepancies emerge in intermediate- to low-FAC regions, particularly on the Amery Ice Shelf, where ice saturation in the firn (pore-space depletion) influences grain growth. The sensitivity experiments indicate that inversion constraints are regime-dependent, with the strongest sensitivity to grain size in intermediate firn regimes and weaker constraints in strongly depleted firn. Furthermore, by statistically reducing grain-size-driven scatter after inversion, we present a proof of concept for a more interpretable backscatter–FAC relationship. These findings provide a basis for improving firn model parameterization and advancing large-scale monitoring of firn evolution across Antarctic ice shelves in a warming climate.

The stability of Antarctic ice shelves is closely linked to the properties of the firn layer, which regulates meltwater retention and influences ice shelf vulnerability to hydrofracturing. Firn Densification Models (FDMs) provide valuable insights into the firn structure, but key properties such as grain size are often parameterized using simple approximations, leading to significant uncertainties, especially in regions lacking in-situ validation. Here, we leverage 15 years (2007–2021) of active microwave observations from the C-band Advanced Scatterometer (ASCAT) to infer an effective firn grain-size parameter across Antarctic ice shelves. Within this framework, we use the Institute for Marine and Atmospheric Research Utrecht Firn Densification Model (IMAU-FDM) to prescribe the state of the firn layer (layer thickness, density, temperature, and liquid water content) and couple it with the Snow Microwave Radiative Transfer (SMRT) model to simulate radar backscatter. Grain size is treated as an unknown microstructural parameter and is optimized by minimizing the misfit between FDM–SMRT simulations and ASCAT observations. The framework is further used to examine how the sensitivity of ASCAT backscatter varies across firn regimes, and how this influences the interpretation of backscatter in terms of FAC. Our results show broad consistency between optimized effective grain size and IMAU-FDM estimates in high-Firn Air Content (FAC) regions, where ASCAT backscatter is most sensitive to interannual variability in grain size. In contrast, larger discrepancies emerge in intermediate- to low-FAC regions, particularly on the Amery Ice Shelf, where ice saturation in the firn (pore-space depletion) influences grain growth. The sensitivity experiments indicate that inversion constraints are regime-dependent, with the strongest sensitivity to grain size in intermediate firn regimes and weaker constraints in strongly depleted firn. Furthermore, by statistically reducing grain-size-driven scatter after inversion, we present a proof of concept for a more interpretable backscatter–FAC relationship. These findings provide a basis for improving firn model parameterization and advancing large-scale monitoring of firn evolution across Antarctic ice shelves in a warming climate.

Despite the increased awareness and action towards Equality, Diversity and Inclusion (EDI), the glaciological community still experiences and perpetuates examples of exclusionary and discriminatory behavior. We here discuss the challenges and visions from a group predominantly composed of early-career researchers from the 2023 edition of the Karthaus Summer School on Ice Sheets and Glaciers in the Climate System. This paper presents the results of an EDI-focused workshop that the 36 students and 12 lecturers who attended the summer school actively participated in. We identify common threads from participant responses and distill them into collective visions for the future of the glaciological research community, built on actionable steps toward change. In this paper, we address the following questions that guided the workshop: What do we see as current EDI challenges in the glaciology research community and which improvements would we like to see in the next fifty years? Contributions have been sorted into three main challenges we want and need to face: making glaciology (1) more accessible, (2) more equitable and (3) more responsible.

The determination of the Surface Mass Balance (SMB) for the Antarctic ice sheet remains subject to significant uncertainty. Sentinel-1 Synthetic Aperture Radar (SAR) satellite sensors with their large-scale ability to penetrate the snowpack, represent a promising tool to more effectively assess the SMB. However, it is challenging to directly relate SMB to the SAR backscatter signal. The multitude of interactions between the snow microstructure and the backscatter signal complicate a direct translation5 from the backscatter signal to SMB using physical models. Additionally, the lack of reliable ground truth data limits the establishment of an empirical relationship with SMB across all of Antarctica. In this study we focus on establishing an empirical relationship between the SMB and dual polarisation SAR backscatter locally across three ice rises in Dronning Maud Land. The SMB of the ice rises was reconstructed using ground penetrating radar data and compared to the incidence angle corrected, four year average of the Sentinel-1 cross-polarization ratio σ_hh / σ _HV. We found a correlation between the SMB and the cross-10 polarization ratio with an R-value of 0.65 when using all available orbits. To understand this relationship we ran a radiative transfer model (SMRT) together with a physical snowmodel (SNOWPACK), which was forced by field measurements across the central ice rise. The results show generally lower density and grain size in accumulation zones but also higher specific surface area of the grains. Overall the results show the existence of a relationship between the SMB and the cross-polarization ratio for the study area. This promising proxy could be extended to larger parts of Antarctica in future research.

The determination of the Surface Mass Balance (SMB) for the Antarctic ice sheet remains subject to significant uncertainty. Sentinel-1 Synthetic Aperture Radar (SAR) satellite sensors with their large-scale ability to penetrate the snowpack, represent a promising tool to more effectively assess the SMB. However, it is challenging to directly relate SMB to the SAR backscatter signal. The multitude of interactions between the snow microstructure and the backscatter signal complicate a direct translation5 from the backscatter signal to SMB using physical models. Additionally, the lack of reliable ground truth data limits the establishment of an empirical relationship with SMB across all of Antarctica. In this study we focus on establishing an empirical relationship between the SMB and dual polarisation SAR backscatter locally across three ice rises in Dronning Maud Land. The SMB of the ice rises was reconstructed using ground penetrating radar data and compared to the incidence angle corrected, four year average of the Sentinel-1 cross-polarization ratio σ_hh / σ _HV. We found a correlation between the SMB and the cross-10 polarization ratio with an R-value of 0.65 when using all available orbits. To understand this relationship we ran a radiative transfer model (SMRT) together with a physical snowmodel (SNOWPACK), which was forced by field measurements across the central ice rise. The results show generally lower density and grain size in accumulation zones but also higher specific surface area of the grains. Overall the results show the existence of a relationship between the SMB and the cross-polarization ratio for the study area. This promising proxy could be extended to larger parts of Antarctica in future research.