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Abstract The addition and refreezing of liquid water to Greenland’s accumulation area are increasingly important processes for assessing the ice sheet’s present and future mass balance, but uncertain initial conditions, complex infiltration physics and limited field data pose challenges. Satellite-based L-band radiometry offers a promising new tool for observing liquid water in the firn layer, although further validation is needed. This paper compares time series of liquid water amount (LWA) from three percolation zone sites generated by a localized point-model, a regional climate model,in situmeasurement, and L-band radiometric retrievals. LWA integrates the interplay of liquid water generation and refreezing, which often occur simultaneously and repeatedly within firn layers on diurnal, episodic, and seasonal scales offering insights into methods for measuring and modeling meltwater processes. The four LWA records showed average discrepancies of up to 62% nRMSE, reflecting shortcomings inherent to each method. Better agreement between series occurred after excluding the regional climate model record, lowering nRMSE to 8–13%. The agreement between L-band radiometry and other LWA records inspires confidence in this observational tool for understanding firn meltwater processes and serving as a validation target for simulations of water processes in Greenland’s melting firn layer. 

Abstract Rainfall high on the Greenland Ice Sheet is an emerging phenomenon with consequences for the thermal and structural makeup of the surface layer. We document changes to Greenland's firn column due to a 4‐day cold‐season warm/rain event. Heavy precipitation occurred with a sudden 30°C increase in air temperature, reaching 0°C at 2,000 m elevation. Thermistor strings within the firn layer across a 35 km transect show rapid warming of 6°–23°C reaching depths of 2–10 m. Antecedent conditions governed the magnitude, duration, and depth‐distribution of sensible and latent heat added to the firn column. Heat fluxes from the firn layer required up to 8 weeks to recover to baseline, a significant fraction of the winter period. The amount of liquid water refrozen in the firn column was ∼20%–100% of the prior summer demonstrating the impact of extreme weather events on the ice sheet's evolution and runoff characteristics. 

Abstract. Quantifying the total liquid water amounts (LWAs) 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 subsurface 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 National Aeronautics and Space Administration (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 (RT) 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, and the second source was the Glacier Energy and Mass Balance (GEMB) model within NASA's Ice-sheet and Sea-level System Model (ISSM). Both models were forced by in situ measurements from six automatic weather stations (AWSs) of the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-Net) located in the percolation zone of the GrIS. 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. 

Terrestrial LiDAR scans (TLS) offer a rich data source for high-fidelity vegetation characterization, addressing the limitations of traditional fuel sampling methods by capturing spatially explicit distributions that have a significant impact on fire behavior. However, large volumes of complex, high resolution data are difficult to use directly in wildland fire models. In this study, we introduce a novel method that employs a voxelization technique to convert high-resolution TLS data into fine-grained reference voxels, which are subsequently aggregated into lower-fidelity fuel cells for integration into physics-based fire models. This methodology aims to transform the complexity of TLS data into a format amenable for integration into wildland fire models, while retaining essential information about the spatial distribution of vegetation. We evaluate our approach by comparing a range of aggregate geometries in simulated burns to laboratory measurements. The results show insensitivity to fuel cell geometry at fine resolutions (2–8 cm), but we observe deviations in model behavior at the coarsest resolutions considered (16 cm). Our findings highlight the importance of capturing the fine scale spatial continuity present in heterogeneous tree canopies in order to accurately simulate fire behavior in coupled fire-atmosphere models. To the best of our knowledge, this is the first study to examine the use of TLS data to inform fuel inputs to a physics based model at a laboratory scale.