The local climate in Southern Patagonia is strongly influenced by the interaction between the topography and persistent westerlies, which can generate föhn events, dry and warm downslope winds. The upstream flow regime influences different föhn types which dictate the lee-side atmospheric response regarding the strength, spatial extent and phenomenology. We use a combination of observations from four automatic weather stations (AWSs) and high-resolution numerical modeling with the Weather Research and Forecasting (WRF) model for a region in Southern Patagonia (48° S–52° S, 72° W–76.5° W) including the Southern Patagonian Icefield (SPI). The application of a föhn identification algorithm to a 10-month study period (June 2018–March 2019) reveals 81 föhn events in total. A simulation of three events of differing flow regimes (supercritical, subcritical, transition) suggests that a supercritical flow regime leads to a linear föhn event with a large spatial extent but moderate intensity. In contrast, a spatially limited but locally strong föhn response is induced by a subcritical regime with upstream blocking and by a transition regime with a hydraulic jump present. Our results imply that the hydraulic jump-type föhn event (transition case) is the most critical for glacier mass balances since it shows the strongest warming, drying, wind velocities and solar radiation over the SPI. The consideration of flow regimes over the last 40 years shows that subcritical flow occurs most frequently (78%), however transitional flow occurs 14% of the time, implying the potential impact on Patagonian glaciers.

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<p>Similar to the Patagonian Icefields, the Cordillera Darwin Icefield in Tierra del Fuego experienced important ice loss during the last decades. The difficult accessibility and the harsh weather conditions in that area result in scarce in-situ observations of climatic conditions and glacier mass balances. Under these challenging conditions, this study investigates calibration strategies of surface mass balance models in the Monte Sarmiento Massif, western Cordillera Darwin, with the goal to achieve realistic simulations of the regional surface mass balance in the period 2000-2022.</p> <p>We apply three calibration strategies ranging from a local single-glacier calibration to a regional calibration with and without the inclusion of a snowdrift parametrization. Furthermore, we apply four models of different complexity ranging from an empirical degree-day model to a fully-fledged surface energy balance model. This way, we examine the model transferability in space, the benefit of including regional mass change observations as calibration constraint and the advantage of increasing the model complexity regarding included processes. In-situ measurements comprise ablation stakes, ice thickness surveys and weather station records at Schiaparelli Glacier as well as elevation changes and flow velocity from satellite data for the entire study site. Performance of simulated surface mass balance is validated against geodetic mass changes and stake observations of surface melting.</p> <p>Results show that transferring mass balance models in space is a challenge, and common practices can produce distinctly biased estimates. The use of remotely sensed regional observations can significantly improve model performance. Increasing the complexity level of the model does not result in a clear improvement in our case where all four models perform similarly. Including the process of snowdrift, however, significantly increases the agreement with geodetic mass balances. This highlights the important role of snowdrift for the surface mass balance in the Cordillera Darwin, where strong and consistent westerly winds prevail.</p>

<p>Together with the Northern and the Southern Patagonian Icefield, the Cordillera Darwin Icefield (CDI) in Tierra del Fuego experienced strong ice loss during the last decades. In some areas the observed glacier retreat contrasts with findings of recent surface mass balance studies, which implies that the observed losses are partly caused by dynamic adjustments. However, the difficult accessibility of Patagonian glaciers and the harsh conditions result in scarce observational data of glacier mass balances, especially for the CDI. In the westernmost region of the CDI, Monte Sarmiento is located. It hosts an 83 km<sup>2</sup> icefield, with Schiaparelli Glacier being the largest glacier, terminating in a proglacial lake.</p><p>We focus on reproducing the local meteorological conditions using statistical downscaling of atmospheric reanalysis data to the study site as well as a linear model of orographic precipitation. Subsequently, we concentrate on a best representation of the surface mass balance (SMB) conditions on the local glaciers. For this purpose, we apply four melt models of different complexity: i) a positive degree-day model, ii) a simplified energy balance model using potential insolation, iii) a simplified energy balance model using the actual insolation (accounting for cloud cover, shading effects and diffuse radiation) and iv) a fully-fledged surface energy balance model. For the latter, we rely on the “COupled Snowpack and Ice surface energy and mass balance model in PYthon” (COSIPY). These models are calibrated on Schiaparelli Glacier (24.3 km<sup>2</sup>), which is the largest and best-studied glacier of the Monte Sarmiento Massif. Observational records comprise in-situ stake, thickness and meteorological measurements as well as remotely sensed elevation changes and flow velocities. After the melt model calibration, we apply them to other adjacent glacier basins and assess their performances against geodetic mass changes. This way, we want to answer the question if it is feasible to apply SMB models, calibrated for one single glacier, to surrounding glaciated areas under these unique climatic conditions. If a single-site calibration showed poor transferability properties, further remotely sensed observables will be considered in the calibration. This way we also hope to answer the question, which melt model can best reproduce the spatial variability in remotely sensed specific mass balances over a larger region.</p>

Abstract. This study investigates strategies for melt model calibration in the Monte Sarmiento Massif (MSM), Tierra del Fuego, with the goal to achieve realistic simulations of the regional surface mass balance (SMB). Applied calibration strategies range from a local single-glacier calibration to a regional calibration with the inclusion of a snowdrift parametrization. We apply four SMB models of different complexity. This way, we examine the model transferability in space, the benefit of regional mass change observations and the advantage of increasing the complexity level regarding included processes. Measurements include ablation and ice thickness observations at Schiaparelli Glacier as well as elevation changes and flow velocity from satellite data for the entire study site. Performance of simulated SMB is validated against geodetic mass changes and stake observations of surface melting. Results show that transferring SMB models in space is a challenge, and common practices can produce distinctly biased estimates. Model performance can be significantly improved by the use of remotely sensed regional observations. Furthermore, we have shown that snowdrift does play an important role for the SMB in the Cordillera Darwin, where strong and consistent winds prevail. The massif-wide average annual SMB between 2000 and 2022 falls between -0.25 and -0.07 m w.e. yr-1, depending on the applied model. SMB is mainly controlled by surface melting and snowfall. The model intercomparison does not indicate one obviously best-suited model for SMB simulations in the MSM.

Abstract. This study investigates strategies for calibration of surface mass balance (SMB) models in the Monte Sarmiento Massif (MSM), Tierra del Fuego, with the goal of achieving realistic simulations of the regional SMB. Applied calibration strategies range from a local single-glacier calibration to a regional calibration with the inclusion of a snowdrift parameterization. We apply four SMB models of different complexity. In this way, we examine the model transferability in space, the benefit of regional mass change observations and the advantage of increasing the complexity level regarding included processes. Measurements include ablation and ice thickness observations at Schiaparelli Glacier as well as elevation changes and flow velocity from satellite data for the entire study site. Performance of simulated SMB is validated against geodetic mass changes and stake observations of surface melting. Results show that transferring SMB models in space is a challenge, and common practices can produce distinctly biased estimates. Model performance can be significantly improved by the use of remotely sensed regional observations. Furthermore, we have shown that snowdrift does play an important role in the SMB in the Cordillera Darwin, where strong and consistent winds prevail. The massif-wide average annual SMB between 2000 and 2022 falls between −0.28 and −0.07 m w.e. yr−1, depending on the applied model. The SMB is mainly controlled by surface melting and snowfall. The model intercomparison does not indicate one obviously best-suited model for SMB simulations in the MSM.

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