Climate’s firm grip on glacier ablation in the Cordillera Darwin Icefield, Tierra del Fuego

Domain: earth_science
Published: 2025-03-18
Editorial outcome: minor_revision

Abstract
The Cordillera Darwin Icefield (CDI) in Tierra del Fuego is one of the largest temperate ice bodies in the Southern Hemisphere. We simulate the climatic energy and mass balance of its glaciers (2000–2023), which are sensitive indicators of climatic changes in the Southern Hemisphere’s higher mid-latitudes. Year-round westerly winds cause strong climatic gradients across the mountain range, reflected in the energy and mass fluxes. Our results reveal a significant increase in surface melt (+0.18 m w.e. yr-1 per decade) over the past two decades. We also present the first estimate of dynamically controlled mass loss into adjacent fjords and lakes by frontal ablation, amounting to 1.44 ± 0.94 Gt yr-1 (26% of the total CDI mass loss). Frontal losses are mainly channelized through few marine-terminating glaciers. While frontal ablation is important for predicting the fate of individual glaciers, for the CDI as a whole, atmospheric conditions exert the main control on the current glacier evolution.

Introduction
The Cordillera Darwin Icefield (CDI) is one of the largest temperate icefields in the Southern Hemisphere1, holding a substantial mass of ice that is at least twice as large as the mass of all glaciers in the European Alps2,3. The main continuous icefield covers the Cordillera Darwin mountain range and is extended by few smaller adjacent ice bodies separated by fjords (Fig. 1), such as the Mount Sarmiento Massif in the west, summing up to a total glaciated area of 2356 km2 in 20224. Glaciers in the CDI descend from up to 2500 m a.s.l. down to sea level. This large altitudinal range is possible due to the extreme climatic conditions inducing high mass input at the highest elevations. Tierra del Fuego, located at the southernmost end of South America (Fig. 1a), is the closest continental land mass to Antarctica. Being situated between the subtropical anticyclone and the subpolar low-pressure trough, the area is exposed to strong, year-round westerly winds. Within this so-called storm track, frontal systems continuously transport moist maritime air masses towards the continent5. Orographic uplift of air masses causes abundant precipitation along the western slopes of the Cordillera Darwin while lee-side effects result in more arid conditions in the east6. The strength and position of the Southern Hemisphere westerlies impacts not only the formation of clouds and precipitation but also the global ocean circulation7. In the past few decades, the storm track has shifted poleward due to an intensification of the subtropical high in the southeast Pacific which is partly ascribed to human-induced climate change8. The southward shifting together with an intensification of the westerlies is projected to continue, at least, until the end of the 21st century under high emission scenarios7. Southern Patagonia is the only continental land mass disrupting the Southern Hemisphere westerly wind belt. Since glaciers are susceptible indicators of climate change, the glacier evolution of the CDI provides valuable insights into climatic changes in this region.

In the last decades, the CDI experienced strong ice loss1,9,10, contributing about 5% of the total loss in South America between 2000 and 2011/20149. Estimates of mass loss rates for Tierra del Fuego range between 1.02 ± 0.11 Gt yr-1 (2000–2011/14)9 and 1.9 ± 1.1 Gt yr-1 (2000–2018)10. Despite the general retreat pattern, individual glaciers are stable or even advancing, mostly in the central region of the CDI11. Such advance continues to this day as confirmed in glacier inventories covering the last two decades (Fig. S1). The largest advance of around 2 km was observed for Garibaldi Glacier (Fig. S1). The advancing behavior is all the more remarkable when compared to the extreme retreat of Marinelli Glacier12,13, the largest glacier of the CDI, which is located in close vicinity at the northern slope of Mount Shipton (Fig. 1c). From 1945–2005, Marinelli Glacier experienced an extreme recession of 12.2 km14, explained by warming and fast retreat along over-deepened fjord bathymetry12.

Around half of the CDI area consists of marine- or lake-terminating (MALT) glaciers (35% and 13%, respectively). Those glaciers do not only lose mass on their surface in contact with the atmosphere, but also at the ocean/lake interface via iceberg calving, which is controlled by ice dynamics and fracturing, and subaqueous melting, collectively known as frontal ablation15. The ice losses and the contrasting behavior observed for individual CDI glaciers can possibly be explained by both climatic and ice-dynamic changes. However, the attribution of ice loss to climatic or ice-dynamic forcing is still unknown. Most mass balance estimates have been obtained applying a geodetic method1,9,10 which comprises both of these loss terms ultimately quantifying the total mass change. An attribution is possible for individual glaciers if one of the two ice-loss terms is known. In the mass budgeting approach, one of these two terms is determined as a residual by subtracting either the climatic or frontal ablation loss from the total mass change16. However, due to the harsh climatic conditions and the inaccessibility of this region, the CDI remains poorly studied13,14,17,18 and neither of these two loss terms can be quantified reliably. The climatic mass balance (CMB) has been studied in the Cordon Martial (east of the study region, located in Argentina)19 and in the Mount Sarmiento Massif20,21 (western CDI), but these local efforts are insufficient and a systematic CDI-wide estimate of the CMB is needed. With this dataset, attribution of the CDI would be possible and, additionally, vital information on current trends and shifts in atmospheric conditions of the Southern Hemisphere’s higher mid-latitudes can be produced. Geodetic techniques in satellite remote sensing allow for operational inference of total glacier mass changes worldwide9,10,22. Thus, with the climatic mass balance term being quantified, we assume that the residual with respect to the geodetic mass budget is primarily explained by frontal ablation – an ice-dynamically controlled loss term. An alternative approach is the direct quantification of frontal losses with a flux gate approach15,23. Here, the frontal ablation is estimated based on the ice flux through a gate upstream of the glacier front. Due to the lack of ice thickness observations in the CDI producing high uncertainties on reconstruction products (e.g., refs. 2,3), results are, however, inaccurate. First estimates of frontal ablation in the CDI are limited to two glaciers: At Schiaparelli Glacier frontal ablation calculated with a mass budgeting approach20 agrees well with inferred values from time-lapse camera observations24. At Marinelli Glacier, Koppes et al.18 find a calving flux of around 0.4 Gt yr-1 (2000–2005) applying an ice budget model.

The two primary objectives of this study are to (1) quantify the unknown CMB of the CDI and (2) attribute CDI ice loss to climatic or frontal ablation. We simulate the CMB over a 23 year period, which provides insights in climatic and glaciological trends, and increases our process understanding of glacier response to climate. The energy and mass balance is examined using the physically based COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY)25, which combines a surface energy and mass balance model with a subsurface multi-layer snow and ice model (Methods section). The fully distributed model allows an analysis of the spatial and temporal variability in the surface energy and mass fluxes across the CDI. Together with geodetic observations, we use the CMB to close the mass budget of all glaciers in the CDI and provide an estimate of their frontal losses. The unprecedented attribution of the observed mass loss to climatic and ice-dynamic forcing plus the fully distributed CMB model allow conclusions to be drawn on the contrasting glacier behavior in the last two decades.

Results
Climatological characteristics of the CDI
High-resolution (200 m spatial and 3 hourly temporal) atmospheric forcing was created by observation-informed downscaling of ERA5 reanalysis data (Methods section). Our multi-method downscaling relies on quantile mapping26 as well as modeling of solar radiation27 and orographic precipitation28–30 for the period of 04/1999-03/2023. Variables comprise near-surface air temperature, relative humidity, air pressure, wind velocities, cloud cover, incoming solar radiation and precipitation (Methods section). Evaluation of atmospheric variables shows overall good agreement with observations from automatic weather stations (Table S1, Table S2). A comparison between a firn core in the central Cordillera Darwin and modeled precipitation at the closest grid point shows an overestimation (mean bias of +0.63 m w.e. yr-1) while catchment-wide precipitation about 50 km downwind measured with a stream gauge indicates an underestimation (mean bias of -0.43 m w.e. yr-1) (Fig. 1, Fig. S2). The location of the former firn core is in an exposed saddle position where the local wind field and snowdrift are not resolved at the process level, while the latter catchment comparison suffers from neglecting water storage. As our aim is a first climatic mass balance estimate on regional scale, consistent with regional geodetic measurements, local deviations are acceptable. The CDI is divided into four subregions (Fig. 1b) to analyze spatial variability of climatic characteristics and energy and mass fluxes across the study region. Significance of trends over the study period are formulated following the IPCC guidance for communication of confidence (Table S3)31. These different significance levels are marked in italic font.

The study region is characterized by temperate maritime climate. Downscaled annual mean air temperatures close to sea level (2 m above ground) lie around 5.2 °C with moderate interannual variability (±3 to 4 °C). Air temperatures show a positive trend (virtually certain) over the study period of +0.41 °C per decade with an intensification from west to east. Conditions are overall humid. While air temperatures at sea level exhibit no clear west-east gradient, annual average relative humidity shows a drying towards the east (Fig. S3b). Relative humidity is on average higher in winter than summer, with the amplitude increasing from around 7% in the west to around 12% in the east. Within the westerly wind belt, frontal systems move from the southern Pacific Ocean towards southern Patagonia causing high precipitation amounts due to orographic uplift. Highest amounts are reached in the westernmost edge of the Cordillera Darwin, going up to 4000 mm yr-1 at Mount Sarmiento (Fig. 2a). As the air masses move eastwards over the cordillera, fall out of precipitation causes a drying effect towards the east of the CDI (Fig. 2a, Fig. S3e). Precipitation amounts peak in the summer months, related to the increased wind velocities. The seasonality is forced by a southward shift of the westerly wind belt during summer32. Precipitation and wind both show an increasing trend (likely) over the study period (+70.8 mm yr-1 per decade and +0.1 m s-1 per decade, respectively). Wind velocities are high throughout the year especially in the westernmost edge of the CDI where annual averages go up to 5.5 m s-1, and decrease towards the central and eastern part of the CDI (Fig. 2b, Fig. S3d). High amounts of annual precipitation are accompanied by an average cloud cover of over 84 %. Such extensive cloud cover strongly limits direct solar radiation (Fig. S3c, Fig. S8a). Regional radiation differences between north and south are mainly explained by the orientation to the sun and the aspect of the slopes.

Climatic energy and mass balance of the CDI
The climatic energy and mass balance is simulated with COSIPY25, a fully-distributed surface energy and mass balance model coupled to a multi-layer subsurface snow and ice model (Methods section). For model evaluation, simulation results are compared to geodetic mass balances obtained from elevation change observations (2000–2013) based on the results by Braun et al.9 for glaciers with no frontal losses (Methods section) (Fig. S4). Glacier-wide specific mass balance is used for the comparison, in the following denoted as glacier-specific mass balance. Based on this performance, we infer a glacier-specific CMB uncertainty of ±0.62 m w.e. yr-1. The simulated icefield-wide average CMB of all land-terminating glaciers (-0.23 m w.e. yr-1) agrees well with the geodetic reference dataset of Braun et al.9 (-0.27 m w.e. yr-1) (Fig. S5).

The CMB of the entire CDI (including marine-, lake- and land-terminating glaciers) is nearly balanced for the study period (2000–2023) with +0.02 m w.e. yr-1. Temporal variability is high with annual values ranging between -0.81 and +0.93 m w.e. yr-1 (Fig. 3c). Across the CDI, glacier-specific values show a high spatial variability (Fig. 1c), spanning -5.47 to +2.43 m w.e. yr-1. We relate this diversity to hypsometry and aspect of the respective glacier catchments. Positive CMBs dominate especially in the central high-elevated part of the CDI (e.g., Rugidor, Garibaldi, Guilcher Oeste and Este), whereas lower-elevated glaciers or glaciers with large outlet tongues show more pronounced mass loss (e.g., Schiaparelli, Romanche, Alemania and many of the small, unnamed glaciers at the icefield margin) (Fig. 1c). The altitudinal gradient of the CMB is steep with strong mass losses on the glacier tongues at low elevation and high mass gain toward the mountain peaks (Fig. 2c). The largest range is present in the western part of the CDI, where the annual CMB reaches nearly -10 m w.e. yr-1 at the lowest point of Schiaparelli Glacier and nearly +10 m w.e. yr-1 at the highest peak (Fig. 2c), resulting in a gradient of -0.92 m w.e. yr-1 per 100 m.

Mass is mainly gained from snowfall (63%) at the surface and from refreezing within the snowpack (36%) (Fig. 3a). Deposition of water vapor at the glacier surface contributes around 1 % to the accumulation. Mass loss is dominated by melt at the surface (92%) and subsurface (7%), with sublimation contributing only around 1% to the total ablation. The average annual CMB is positive in the southern and western part of the CDI (+0.33 and +0.09 m w.e. yr-1, respectively), while it is just below zero in the north and east (-0.06 and -0.12 m w.e. yr-1, respectively) (Fig. 3a). These differences mainly stem from the contributions of snowfall and surface melt. Snowfall amounts strongly reduce from +1.50 m w.e. yr-1 in the west to +0.92 m w.e. yr-1 in the east of the CDI (Fig. 3a). In the western part, the high accumulation is partly balanced by enhanced surface melt (-2.00 m w.e. yr-1). Over the remaining CDI, we find very similar surface melt rates of around -1.54 m w.e. yr-1. The decreasing snowfall towards the east also results in CMB decreases (Fig. 3a). Regional differences are also reflected in the equilibrium line altitudes (ELAs) - the elevation at which surface mass gain equals surface mass loss over 1 year - in the CDI. Simulated average ELA values increase from the west (759 m a.s.l.) over the center (~810 m a.s.l.) to the east (893 m a.s.l.). The CMB shows a pronounced seasonality (Fig. S6). In austral summer (December, January, February), it is strongly negative with the highest losses in the western (-0.77 m w.e. yr-1) and the smallest losses in the southern (-0.51 m w.e. yr-1) part of the CDI (Fig. S6a). This spatial difference is primarily explained by spatial variability in the surface melt. In austral winter (June, July, August), the CMB is positive all over the CDI with reduced melting (Fig. S6c). Regional differences are mainly linked to the snowfall gradient.

To understand the variability in surface melt, the energy fluxes at the surface and subsurface are analyzed. On average, the largest energy input comes from the net shortwave radiation (51%) and the sensible heat flux (32%) (Fig. 3b). The glacier heat flux (energy generated from penetrating shortwave radiation and refreezing that is transported to the surface via heat conduction) brings on average 15% of energy, and is mostly constrained to the higher reaches of the glaciers (Fig. S9b). The heat flux from rain is limited to the glacier tongues (Fig. S9c), contributing around 2% in total. Energy loss at the surface is dominated by the net longwave radiation (88%), followed by the latent heat flux (12%) (Fig. 3b), which is an energy source on the glacier tongues but a sink on the spatial average (Fig. S9a). The largest amount of energy available for melting is found in the western part of the CDI (Fig. 3b, Fig. S9d). The energy surplus mainly stems from the sensible heat flux that is more than twice as high (14.97 W m-2) as compared to the northern and eastern part (around 6.43 W m-2) of the CDI (Fig. 2d). Subsequently, the sensible heat flux is the primary energy source (47%) in the west (Fig. 3b). The enhanced values there are related to the higher wind velocities prevailing over the south-western part of the CDI (Fig. 2b). The slightly reduced net shortwave radiation in the south-west is caused on the one hand by reduced incoming radiation due to orientation and topographic shading (Fig. S8a), on the other hand by higher average surface albedo (around 0.83 in the south-west, around 0.81 in the north-east) related to the enhanced snowfall. The latent heat flux is an energy sink for the south, north and east part of the CDI (Fig. 3b). Its importance is reduced in the west. Due to the moister conditions in the west (Fig. S3b), water vapor transport towards the glacier surface is more common generating deposition and condensation instead of sublimation and evaporation, which are favored in the other subregions (Fig. S7a-b, Fig. S9a). In summer, the latent heat flux temporarily turns into an energy source in the west, which is not seen over the rest of the icefield (Fig. S6b). The energy balance shows a strong seasonality with highest melt energy in summer (Fig. S6b) and strongly reduced energy in winter (Fig. S6d). In winter, energy availability is limited due to the minimized solar energy together with reduced wind velocities and lower air temperatures.

Our results show that the inter-annual variability of the CMB (Fig. 3c) is mainly influenced by air temperature (Fig. S3a) (Pearson’s correlation r=-0.71) and by precipitation (Fig. S3e) dictating accumulation (r=0.73). The air temperature strongly influences the energy available for melting (r=0.85). Melt energy and CMB are also linked to the annual average incoming solar radiation (r=0.54 and r=-0.46, respectively) as well as the albedo (r=-0.68 and r=0.69, respectively). The importance of wind speed over the CDI is highlighted by a significant correlation with the sensible heat flux (r=0.62) as well as glacier accumulation (r=0.52).

Over the 23 year study period, we see an increasing trend (extremely likely) in the surface melt (+0.18 m w.e. yr-1 per decade) that translates into a likely decreasing trend for mass balance (-0.18 m w.e. yr-1 per decade), which is caused by the more negative annual CMB towards the end of the study period (Fig. 3c, Fig. S10a). The increasing surface melt is mainly caused by an extremely likely increasing trend in the sensible heat flux (+0.79 W m-2 per decade) and net longwave radiation (+0.62 W m-2 per decade) (Fig. S10b), which we primarily relate to increasing air temperature (both variables) and wind velocity (sensible heat flux). Additionally, we observe an extremely likely increasing net shortwave radiation (+0.78 W m-2 per decade) (Fig. S10b), which we explain with an albedo feedback (albedo decrease of -0.01 per decade, extremely likely). Altogether, an extremely likely increasing trend in available melt energy (+1.93 W m-2 per decade) is obtained. The trend in the CMB is more pronounced for lower elevation bins. Below 600 m elevation, the CMB shows an extremely likely decreasing trend (up to -0.50 m w.e. yr-1 per decade). Snowfall or accumulation trends are not significant and currently unable to compensate for the increased surface melt.

Estimation of frontal ablation in the CDI
Mass budgeting of the geodetic and climatic mass balance gives information on frontal ablation of the 39 marine- and lake-terminating (MALT) glaciers of the CDI (Methods section). This way, we are able to assess the direct ice flux into the fjords. An independent estimate for frontal ablation relies on the flux gate approach requiring surface velocities and near-front ice thickness3 (Methods section). The latter approach implies elevated uncertainties due to the largely unconstrained thickness maps of the CDI in absence of ground-truth data.

With the mass budgeting approach, the total frontal ablation of the CDI is estimated to 1.44 ± 0.94 Gt yr-1 between 2000–2013. About half of the total flux is channelized through Marinelli Glacier with 0.40 ± 0.10 Gt yr-1 and Grande Glacier with 0.30 ± 0.10 Gt yr-1 (Fig. 4). Another 20% of the frontal ablation is explained by two other prominent marine-terminating glaciers: Darwin with 0.14 ± 0.04 Gt yr-1, and Rugidor with 0.11 ± 0.04 Gt yr-1. The flux-gate approach gives an almost identical total frontal ablation with 1.49 ± 0.53 Gt yr-1 for the year 2013 and shows the overall same pattern (Fig. 4). Largest contributors are confirmed, however, in this case they are responsible for only around half of the total flux. For both approaches, the majority of MALT glaciers shows only low frontal ablation (<0.03 Gt yr-1) (Fig. 4) accounting on average for <1% of the total flux. For a few glaciers, the flux-gate approach shows clearly elevated values - though with large uncertainties. In general, calving into fjords explain the main share of the frontal ablation (around 90%) while these glaciers drain 75% of the surface area of all MALT glaciers. Calving into lakes therefore plays a secondary role.

The availability of geodetic datasets covering multiple observation periods (e.g., ref. 22.) allows an analysis of changes in frontal ablation rates over the study period (from 2000–2010 to 2010–2020). Bias-corrected estimates based on mass budgeting using these datasets and the CMB, reveal a total frontal ablation of 1.55 ± 0.71 Gt yr-1 (equaling 1.34 ± 0.61 m w.e. yr-1) for the first period, and a slightly reduced value of 1.42 ± 0.75 Gt yr-1 (equaling 1.25 ± 0.66 m w.e. yr-1) for the second period. Associated uncertainties do not allow any reliable statement to be made about changes over the study period. The derived values suggest, however, that the frontal ablation has changed less over the last 20 years (-0.05 m w.e. yr-1 per decade) than the CMB.

Disentangling climatical and dynamical control on observed glacier changes
With the CMB and the frontal ablation available, we can disentangle the glacier mass changes observed from remote sensing into climatical (CMB) and dynamical (frontal ablation) forcing. For few glaciers, the mass budgeting suggests frontal ablation as the major contributor to mass loss. The frontal ablation exceeds twice the climatic ablation for glaciers Rugidor, Marinelli, Darwin, Italia and two unnamed glaciers (CL112833070 and CL112840210) (Fig. 1c, Table S4). For these glaciers, the mass loss is primarily dictated by ice dynamics instead of climate. For about 15% of CDI glaciers, the contribution of climatic and frontal ablation is rather even (e.g., Grande, Cuevas, Lovisato, Frances) (Table S4). However, for more than half of the MALT glaciers, the climatic losses at the surface and within the snowpack largely exceed the frontal ablation, meaning that the mass loss of these glaciers is dominated by atmospheric processes at the glacier surface rather than ice dynamics.

Glaciers that have been advancing over the study period (Garibaldi, Finlandia, Guilcher Oeste and Este) are in general characterized by a strongly positive CMB and by medium to low frontal ablation (Fig. 1c). These glaciers do not only advance, but also show thickening further upstream (thus, gaining mass), suggesting a primary climatic control.

Overall, ablation in the CDI is primarily controlled by atmospheric conditions. The climatic ablation of the entire CDI on average amounts to 4.17 ± 1.48 Gt yr-1 (74% of total ablation) while the frontal ablation on average amounts to 1.44 ± 0.94 Gt yr-1 (26 % of total ablation). For around one third of the MALT glaciers, the mass loss is mainly controlled by frontal ablation. For six individual glaciers covering around 15% of the CDI area, the frontal overtakes the climatical contribution to ablation by a factor of two. While trends in CMB impose an increasing mass loss associated with climatic changes, frontal ablation remains without significant change over the study period.

Methods
Data
Meteorological observations in the Cordillera Darwin are sparse (Fig. 1c) due to the harsh environmental conditions and the inaccessibility of the region. Details of all automatic weather stations (AWSs) used in this study are listed in Table S1. Operators are the Chilean Water Directorate (Dirección General de Aguas, short DGA) or individual researchers installing stations within the framework of different research projects in the Cordillera Darwin. Measured variables range from near-surface air temperature, relative humidity, wind and air pressure to global radiation and precipitation (Table S1). However, the station network is located close to sea level, lacking information at higher elevation. This deficit is especially problematic for precipitation, which is strongly influenced by orographic effects. At one AWS (Río Betbeder) a gauging station is installed, providing valuable information on precipitation amounts over the entire river catchment (Fig. 1c). All stations have been quality checked including a screening for outliers or drift in the data. In March 2020, the COrdillera Darwin Ice CorE Survey (CODICES) project drilled a 3.25 m firn core in a flat, northwest-southeast oriented 150×150 m saddle (54.6814°S, 69.6394°W, 2324 m a.s.l), one of the highest flat areas in the Cordillera Darwin. Seasonal variability in major ions and insoluble microparticles were used to estimate annual layers. The firn core record extends from March 2020 to austral spring 2016.

Measurements of surface ablation or mass balance are limited in the Cordillera Darwin. Ablation stakes have been installed between 2013 and 2020 at Schiaparelli Glacier located within the Mount Sarmiento Massif at the western edge of the CDI. Stakes are limited to the lowest part of the ablation area, delivering information about surface melt only20. A 21 year long record of annual, winter and summer mass balance exists at the Martial Este Glacier located east of the main body of the CDI55. The glacier is located outside of the direct study region but we extended the domain for model validation.

We use atmospheric variables from the ERA5 reanalysis product (the latest global product of the European Centre for Medium-Range Weather Forecasts, ECMWF) to generate the climatic forcing for the COSIPY model over the study site (54.25–55.00°S, 71.00–68.25°W). ERA5 provides high temporal (hourly) and spatial (31×31 km) resolution56. For Southern Patagonia, ERA5 and its previous versions have proven reliable in several modeling studies (e.g., refs. 20,21,30,46,57,58). Required variables for this study are near-surface air temperature, relative humidity, air pressure, wind speed, cloud cover fraction and total precipitation over the study region. For downscaling of precipitation, upstream (53.75–55.50°S, 74.50–73.25°W) information about air temperature, relative humidity, wind vectors and geopotential height between 850 and 500 hPa is needed.

Glacier outlines are taken from the DGA glacier inventory59,60 since the Randolph Glacier Inventory (V6) has revealed poor representation of outlines for the southern Andes, especially for smaller glaciers61. Glacier outlines available comprise two timestamps: 2000–2003 (in the following denoted as 2000) and 2019. Since glacier catchments in the more recent inventory had been partially upgraded, catchments in the 2000 inventory had to be homogenized with the 2019 inventory for consistency. Furthermore, it was shown that neglecting the temporal evolution of the glacial extent by relying on constant glacier outlines can bias the comparison between surface and geodetic mass balance62,63. Since elevation changes cover the period 2000 to 2013, we manually produced outlines for 2013. Therefore, we used late-summer images from Landsat 7 and 8 (2013) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) (2013 and 2014) and manually adjusted the outlines to the current glacier extent. Thus, inventories available in this study cover years 2000, 2013 and 2019.

Geodetic mass changes of glaciers of the Cordillera Darwin are derived from interferometric Synthetic Aperture Radar (SAR) digital elevation models (DEMs) of the Shuttle Radar Topography Mission (SRTM) of the National Aeronautics and Space Administration (NASA) and the TerraSAR-X add-on for Digital Elevation Measurement satellite mission (TanDEM-X) of the German Aerospace Center (DLR). The SRTM C-band DEM has been acquired in February 2000 at a spatial resolution of 1 arcsec64. We use the void-filled LP DAAC NASA SRTM DEM65. Bistatic SAR acquisitions of the TanDEM-X mission are available since 201166. Here, we use Co-registered Single look Slant range Complex (CoSSC) data of the Southern Hemisphere ablation periods of the years 2012–2014. To further minimize elevation offsets due to differences in ice accumulation or time-varying depths of SAR signal penetration into the glacier volume, we use TanDEM-X acquisition dates which are close to the mean SRTM acquisition date (2000-02-16) whenever possible.

Ice flow velocities and reconstructed ice thickness are taken from Millan et al.3. These datasets are used for calculation of frontal ablation based on a flux gate approach. To constrain the uncertainty in ice thickness, we further consider ice thickness fields from Carrivick et al.67 and from the consensus estimate2 to calculate the standard deviation per pixel. Furthermore, surface velocities close to the glacier fronts are used for a classification of non-calving glaciers. A reliable classification is essential for a comparison between climatic and geodetic mass balance. Glaciers exceeding a velocity threshold of 60 m yr-1 are classified as marine- or lake-terminating (MALT) glaciers, glaciers below the threshold velocity are classified as glaciers without significant frontal ablation and treated as land-terminating in this study.

Atmospheric forcing
Atmospheric input data required for the COSIPY simulation includes air temperature, relative humidity, incoming shortwave radiation, wind speed, air pressure, cloud cover and precipitation. To extend the climatic data beyond the respective measurement periods, we apply a downscaling scheme where we combine statistical downscaling with the application of a radiation model and a model of orographic precipitation.

Following previous studies in southern Patagonia (e.g., refs. 20,21,39), we apply quantile mapping for statistical downscaling of air temperature, relative humidity and air pressure. Quantile mapping is a method of statistical bias correction, where the cumulative distribution function of the model is adjusted to align with the cumulative distribution function of the observation26,68. Statistically downscaled air temperature and pressure are adjusted to sea level conditions, interpolated between the available station points via Ordinary Kriging69, and subsequently spatially extrapolated over the topography using a linear temperature lapse rate of -0.6 K/100 m20 and the barometric equation, respectively. Relative humidity is likewise interpolated between the recording AWSs with Ordinary Kriging. Wind speed and cloud cover fraction are taken directly from ERA5 and interpolated to the model resolution.

A radiation model70 is applied over the study site to calculate global radiation over the glacier surface, following the methodology of Temme et al.20 at the Mount Sarmiento Massif. The model calculates both the direct and diffuse component of the solar radiation based on cloud cover, temperature, humidity and pressure. Corrections are applied for the slope and aspect of the respective grid cell. Shaded grid cells, either from the terrain or self-shaded, exclusively receive the diffuse solar radiation component27,70.

Due to the small-scale and episodic character of precipitation events, statistical techniques often fail to infer reliable distributions over complex terrain from coarse global data sets. Furthermore, strong winds limit the reliability of observations in southern Patagonia43,71. An orographic precipitation model showed improved performance as compared to extrapolation of observational data using altitudinal lapse rates72. The model calculates the orographic portion of precipitation resulting from forced orographic uplift over a mountain39. It is grounded on the linear steady-state theory of orographic precipitation, considering airflow dynamics, cloud timescales and processes of advection and downslope evaporation28,29. Since the model assumes stable and saturated conditions with unblocked air flow crossing the CDI from west to east28,39, time intervals that do not fulfill these constraints are excluded. Thresholds and parameter settings are taken from Temme et al.20. The total precipitation is calculated by adding the orographic precipitation calculated in the model to the large-scale precipitation. The large-scale precipitation is obtained by removing the orographic component, calculated by running the orographic precipitation model on the ERA5 topography, from the ERA5 total precipitation. Recent elevation- and bias-corrected precipitation products (W5E5, WFDE5) with lower spatial resolution and shorter temporal coverage indicate an ERA5 overestimation over Tierra del Fuego73. Comparison of ERA5 daily precipitation with observations supports this finding74. To guarantee that the simulated total precipitation at the AWS locations agrees with the observed amounts, we constrain the large-scale precipitation from ERA5 to the annual measurements.

To derive snowfall from precipitation, a logistic transfer function is applied scaling around a threshold temperature of 1.0 °C. A snow drift parametrization is included in the modeling framework to account for snow redistribution caused by the strong westerly winds over the CDI. Locations sheltered from or exposed to wind are identified by a topographical analysis and solid precipitation is redistributed accordingly75. Parameters and adjustments to the model are transferred from the Mount Sarmiento Massif20.

Climatic forcing data are validated on a daily basis with meteorological observations from AWSs that have not been used in the downscaling (Table S1) based on a statistical analysis of mean model bias, root mean square error and correlation. Overall, the performance of downscaled and modeled climate variables is satisfying (Table S2). The agreement of downscaled variables with measurements is improved compared to the raw ERA5 input, confirming the success of the downscaling approach. For further information on precipitation amounts, we compare annual precipitation over the river catchment of Río Betbeder with observed stream flow at the gauging station there, and snowfall with results of a firn core in the central CDI. The former river catchment is located in the northeast of the CDI covering a total area of 146 km2 (Fig. 1c). The comparison indicates an underestimation (Fig. S2). However, considering the simplified approach (e.g., neglecting water storage and glaciers in the system), results are satisfying. The firn core site is located at an exposed saddle where we assume important wind erosion. The small-scale local wind field and snow drift are, however, not fully resolved in our modeling approach, which explains an overestimation in the modeled snowfall.

COSIPY model
The open-source COSIPY model (COupled Snowpack and Ice surface energy and mass balance model in PYthon)25 is a physically based model grounded on the concept of energy and mass conservation. It couples a surface energy and mass balance model with a multi-layer subsurface snow and ice model, with the calculated surface melt water serving as input to the subsurface model25. The energy balance model solves all energy fluxes F at the glacier surface:

F = SW in (1 - α) + LW in + LW out + Q sen + Q lat + Q g + Q RRR (1)

where SW in is the incoming shortwave radiation taken from the radiation model, α is the surface albedo, LW in and LW out are the incoming and outgoing longwave radiation, Q sen and Q lat are the turbulent sensible and latent heat flux, Q g is the glacier heat flux and Q RRR the rain heat flux. Melt can occur if the surface temperature is at the melting point (0.0 °C) and F is positive. Under this condition, the available energy for surface melt Q M equals F. Rain and melt water can percolate the snowpack and cause refreezing in the snow layers. Subsurface melting is possible by penetration of shortwave radiation in the upper snow layers. Solving the surface plus the internal mass balance in the snowpack, COSIPY gives the climatic mass balance (CMB)76. The total ablation includes surface melting, sublimation and subsurface melting. Accumulation is the sum of snowfall, deposition and refreezing.

Albedo values are differentiated between snow, firn and ice surfaces. The decay of surface albedo due to snow aging is parameterized following the scheme of Oerlemans and Knap77. The albedo depends on the time since the last snowfall and the snow depth. A bulk approach is applied to parameterize the turbulent heat fluxes. COSIPY offers the option to correct the flux-profile relationship by a stability correction using the Richardson-Number or the Monin-Obukhov similarity theory25. The latter is applied in this study (Table S5).

We apply COSIPY version 1.4 in the period 04/1999-03/2023 with a 200 m spatial and a 3 hourly temporal resolution. All parameter settings follow the COSIPY set-up in the Mount Sarmiento Massif20 and are summarized in Table S5. The model performance of COSIPY was positively evaluated in the Mount Sarmiento Massif, where four surface mass balance models of varying complexity were compared. COSIPY results agreed well with the other models as well as with observations of ablation stakes and geodetic mass balance20.

Geodetic mass balance processing
Elevation changes are calculated by DEM-differencing of SRTM and TanDEM-X. TanDEM-X DEMs are created based on differential interferometry following an established workflow9. First, interferograms are computed from concatenated overlapping acquisitions, phase-unwrapped based on a minimum cost flow algorithm and converted to elevation values using the SRTM DEM as reference surface. Thereafter, the raw TanDEM-X DEMs are iteratively co-registered to the SRTM DEM in the vertical and horizontal plane. Therefore, the 3D offset of each DEM is estimated based on all stable terrain with <25° surface slope excluding water and glacier areas. Finally, a regional elevation mosaic is created by merging all co-registered DEMs in the order of the relative deviation between the SRTM mean acquisition date (February 16th) and the tile-specific TanDEM-X date. The cell-specific TanDEM-X dates are stored with the DEM mosaic and subsequently used to calculate the respective elevation change rate during the SRTM and TanDEM-X DEM-differencing. The mean regional observation period of the elevation change rate measurement is 12.97 years (2000–2013).

To extract glacier-specific mass changes within the geodetic observation period, the elevation change map is masked to the glacier outlines of the 2000 inventory (see Data section). The mean elevation change rate is extracted for each glacier geometry and converted to volume and mass change based on the respective glacierized area and an approximate ice density of 900 ± 60 kg m-3. Since glacier area changes during the observation period can bias the derived mass budgets78,79, the specific mass change rate of each glacier is calculated using the mean glacier area of the 2000 and 2013 inventories following the UNESCO definitions76.

To estimate the glacier-specific uncertainty budget of our derived elevation change rates, we calculate the remaining vertical deviation after DEM co-registration of stable terrain9,79, i.e. raster cells which are not glaciers or water areas, in the vicinity of each glacier. First, all stable terrain cells within a 5 km buffer radius of each glacier outline are masked and filtered with a 2-98% quantile filter. The selected cells are then aggregated within 5° slope bins to account for the dependence between surface slope and vertical deviations between different DEMs, and the respective standard deviation is extracted. Finally, the total vertical accuracy of the elevation change measurement of each glacier is estimated by weighting the offsets (standard deviations) of each stable terrain slope bin by the corresponding glacier area of the same slope bin. In addition, we multiply the derived vertical elevation change uncertainty of each glacier by a constant factor of 2 based on the glacier area fraction without valid DEM-differencing measurements as the accuracy of the glacier-specific elevation change estimates is also related to the spatial coverage of the TanDEM-X DEMs. To convert the glacier-specific elevation change uncertainty into mass change uncertainty, we use ±60 kg m-3 as the error budget of the assumed mean glacier ice density54.

Model calibration and validation
Due to the limited in-situ observations in the Cordillera Darwin, calibration and validation of the CMB are a major challenge. With the large model domain and the high temporal and spatial resolution, resulting in a massive computational effort, intense model calibration is not feasible. Instead, the downscaling procedure and optimal parameter setting are grounded on the expertise gained at the Mount Sarmiento Massif, located at the western edge of the CDI20. Sensitivity runs are applied for further optimization, where the methods for the generation of the atmospheric input fields (relative humidity, wind velocity, air temperature) are varied, addressing the challenge to realistically reproduce the zonal climatic gradients. Temme et al.20 conclude that calibrating against regional satellite observations of mass change significantly improves the performance of CMB models. Following this approach, we rank the sensitivity runs based on the highest agreement with regional geodetic mass balance, as observed with satellite remote sensing, for all glaciers with no frontal ablation (region-wide average -0.27 m w.e. yr−1). The highest ranked run (region-wide average -0.23 m w.e. yr−1) agrees well with the geodetic observations and is presented in this study.

For model validation, we compare the climatic with the geodetic mass balance of each land-terminating glacier on a catchment level (catchment information not used during calibration). MALT glaciers are excluded because they also lose mass at the calving front due to ice dynamics. To reduce uncertainties, we limit the comparison to glaciers exceeding an area of 3 km2. This gives a validation dataset of glaciers covering ~37% of the total glaciated area of the CDI. Model performance is quantified by the root mean square error between the glacier-specific climatic and geodetic mass balance for these glaciers, resulting in a model error of ±0.62 m w.e. yr-1. Stake measurements at Schiaparelli Glacier20 and Martial Este Glacier80 serve as additional validation of melt on the western and eastern edges of the CDI (Table S6).

Frontal ablation
In this study, we apply two different methods to determine frontal ablation for the entire CDI and the individual marine- and lake-terminating glaciers in the Cordillera Darwin. Firstly, we apply a mass budgeting, where the residual of the total glacier mass balance (ΔM tot) from geodetic observations and the CMB (B _ ) simulated with COSIPY provides the frontal ablation (A f): A f = ΔM tot - B _ 16. Uncertainties in frontal ablation consist of the uncertainties in the glacier-specific CMB (see Model calibration and validation) and the uncertainties in the glacier-specific geodetic mass balance (see Geodetic mass balance processing) following classical Gaussian error propagation. Since the former uncertainty already includes random errors in the geodetic mass balance, the resulting uncertainties of frontal ablation values are likely an overestimation.

Secondly, we apply a flux gate approach15,23. Here, frontal ablation is calculated based on the discharge (D) at a flux gate located upstream of the glacier front and the CMB downstream of the flux gate (B _ FG): A FG = -D - B _ FG. D is calculated by integrating the product of ice thickness and surface velocity perpendicular to the gate. For our study site, the lack of ice thickness measurements in the CDI makes modeled ice thickness uncertain. To quantify the uncertainty in the ice thickness, we calculate the standard deviation of the available ice thickness products from Carrivick et al.67, Millan et al.3 and the participants in the consensus estimate covering the CDI2. Time discrepancies are corrected for by satellite-derived elevation changes.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this work, Temme and collaborators present a climatic mass balance forced by reanalysis data validated with in situ\nobservations. Frontal ablation is also estimated. The methods are standard for this kind of research. The novelty is related to\nthe study area, as the modelling is applied to the glaciers of the Cordillera Darwin Icefield (CDI) in southernmost South\nAmerica, an area poorly studied. The main conclusion is atmospheric forcing is the main driver of the ablation in the region.\nThe work is well-written and easy to follow and the figures are mostly clear, but I think some clarifications need to be made\nbefore publication. I hope this review helps the authors improve the manuscript.\nI suggest a small change in the title, including “ablation” instead of “melt”. Results of the manuscript show that melt is the\nmain component in the total ablation processes, i.e. higher percentage (74%) compared to frontal ablation (26%). Melt by\ndefinition depends on the atmosphere conditions (could be also by oceanic or lake conditions but this is not directly\nquantified here). If I understand, I think the title looks to remark that the climate or atmosphere drives the “ablation” as stated\nin lines 260-261.\nThe sentence in L275 and repeated in L347 is a bit confusing. How the mass loss is controlled by atmospheric conditions if\nthe CMB is positive (0.02 m w.e. yr-1) or close to balance (L332)? Results show climatic ablation is quite larger than frontal\nablation (L275-277) and this is forced by the atmosphere, I understand this, but in terms of mass balance, the overall CMB is\nstill positive for the period meaning that CDI has been climatically balanced in the recent two decades (L380). In\nconsequence, overall no mass loss forced by atmosphere conditions between 2000-2022. Or do you refer to the last six\nyears of CMB modelling? or just to land-terminating glaciers that show negative specific CMB (L145-146)? Please clarify\nthis.\nNo justification for the period. For instance, why 22 years and not 30 years? In the title, the word “Climate” is used, and by\ndefinition, the climate is a 30-year period (WMO). If the 22-year period is well justified, maybe change “Climate´s” to\n“Atmosphere´s”.\nAs usual in glacier modelling-approach investigations some choices need to be better justified, for instance, the use of a\nconstant air temperature lapse rate over a spatial variable lapse rate. Also, other sources of uncertainties are not (at least)\nmentioned in the manuscript. For instance, no mention of debris cover areas. Is this area important to quantify melt rates at\nCDI?\nMinor comments\nL 38-39: “The large altitudinal range….” I don´t understand this sentence. How do the location and the climatic conditions\ncontrol the altitudinal range of the CDI? Or do you refer to the climate conditions extreme gradients? Please clarify.\nL59-60: Reference 17 includes a frontal reconstruction of Marinelli Glacier back to 1910.\nL63: I suggest including the area of the marine-terminating and the lake-terminating glaciers separately.\nL107: Why this period?\nL110: Any insight on why the correlation with Isla Hoste AWS is low?\nL114-115: Ok, but you also show individual glacier CMB results, for instance in Fig. 1. Are these values, especially the\naccumulation, reliable?\nL123-124: I understand what you mention here, and agree, but be aware that relative humidity is an indicator of how close to\nsaturation the atmosphere is and depends on the air temperature.\nL145-146: Similar to a previous comment, how reliable is the CMB estimation for individual glaciers? I agree that the\nregional CMB is a good approach for CDI considering the uncertainties, lack of measurements and differences in the\naccumulation rate reported in L114 but, along the manuscript, CMB of individual glaciers is used for comparisons.\nL152-153: I suggest adding a Figure (could be in Supplementary Material) to explore the differences in the CMB between\nland and marine-lacustrine glaciers.\nL176: Change Juli by July.\nL297-308: Why present ELA results in the Discussion section and not in the Results sections?\nL317-321: Any clue for this behaviour? Southern Annular Mode or another mode of interannual or interdecadal variability?\nL315-328: Missing references about glacier energy balance in Patagonian glaciers that could be useful to add to the\ndiscussion.\nL329: Also missing references about surface melt trends and projections in Patagonian glaciers. I suggest comparing your\nfindings with previous works at regional scale. Considering the uncertainties that are mentioned in the paper I suggest\nkeeping a regional point of view for comparisons. Some comparison by glacier is fine, but the approach here is regional.\nL380-381: This sentence seems more appropriate for the climate or atmosphere forcing on mass balance.\nL446: Is there any reference for this velocity threshold?", "reviewer_2": "The study models the surface mass balance of all glaciers in the Cordillera Darwin (CDI) in Tierra del Fuego from\n2000 to 2019, utilizing the open-source surface energy balance model COSIPY (Sauter et al., 2020), which is forced by\ndownscaled ERA5 data. The model parameters are primarily calibrated with in-situ mass balance observations from one or\na few glaciers in the region. Notably, this calibration process is based on the authors’ previously published work (Temme et\nal., 2023). The difference between the geodetic mass balance and the simulated surface mass balance for lake- and ocean-\nterminating glaciers is used to estimate mass loss due to frontal ablation.\nOverall, the paper is well-written, but there are areas where additional methodological detail would enhance clarity\n(elaborated further in my specific comments). The authors highlight the novelty of the study as \"the first simulation of the\nclimatic energy and mass balance of glaciers in this region.\" However, given that the same first author has previously\napplied the COSIPY model (developed by Sauter et al., 2020) to a subset of glaciers in the region (Temme et al., 2023), this\nwork may be better framed as an extension of that earlier study, expanding the model's application to a broader set of\nglaciers.\nThe method used to estimate frontal ablation raises some concerns, particularly regarding the quantification of uncertainties\n(detailed in my specific comments). A more comprehensive uncertainty analysis would strengthen the credibility of the\nresults, particularly in relation to frontal ablation estimates.\nIn summary, while the study provides valuable insights into the region, the novelty of the contribution could be more clearly\narticulated. Additionally, addressing some critical methodological elements, such as a more rigorous uncertainty analysis,\nwould significantly enhance the robustness of the results.\nSpecific comments:\nAbstract: The authors should include the period of the simulations in the abstract. It took me some time to determine that the\nsimulations cover 2000–2019, and having this information up front would clarify the scope of the study.\nLine 77-78: “...melt, which is strongly linked to air temperature”\nOne of the references cited here used a positive-degree-day (PDD) model to simulate melt, so linking melt to temperature is\nan inherent assumption of the model.\nLine 78-79: “Despite these local efforts to determine the mass balance of individual glaciers, a systematic approach for a\nCDI-wide estimate of the CMB is to this day missing.”\nHowever, Temme et al. (2023) (reference #20) addresses not just individual glacier modeling but also regional-scale\nmodeling. The authors may want to reconsider this statement, as it somewhat underrepresents the existing work in this area.\nLine 80: “This lack of knowledge can be addressed with a well-informed modelling product of CMB.”\nThe term “well-informed modeling product of CMB” is unclear. It would improve clarity to specify what is meant by this term\nand what type of model product the authors are referring to.\nLine 82-83: “Thus, with the climatic loss term available, the mass budget of the CDI glaciers can successfully be closed and\ngive the dynamic loss as residual.”\nThere seems to be a disconnect between this statement and the preceding one. The total mass loss is derived from geodetic\nestimates, not the climatic loss term. I suggest rephrasing this to clarify that the dynamic loss is inferred from the residual of\nthe modeled climatic mass balance (CMB) and geodetic mass balance. Additionally, errors in both the CMB and geodetic\nestimates could be significant, making it challenging to assume that the residual solely represents dynamic loss.\nLine 94: “In this way, an unprecedented attribution of the observed mass loss to climatic and ice-dynamic forcing becomes\npossible.”\nWhile this is an important step forward, the authors should also account for the uncertainty in the modeled CMB and\ngeodetic estimates. Without addressing these uncertainties, the attribution may not be as straightforward as suggested here.\nFor instance, Hugonnet et al. (2021) point out that the accuracy of geodetic mass balance estimates can decline when\nmoving from multi-annual to annual timescales.\nLine 96-97: “The energy and mass balance will be examined using the physically-based COupled Snowpack and Ice\nsurface energy and mass balance model in PYthon (COSIPY).”\nIt would be helpful to explain why COSIPY was chosen for this study. Temme et al. (2023) compared COSIPY with simpler\nmodels, such as PDD approaches, and noted that some of the model parameters, like those in the albedo parameterization,\nstill require calibration with mass balance observations. If the model is calibrated with geodetic mass balance, how can it\nprovide an independent estimate of the ice-dynamic component? If the in-situ mass balance data from one or a few glaciers\nis used for calibration, how do the authors address the potential issue of limited parameter transferability across the CDI?\nLine 422: “...since comparison with the Randolph Glacier Inventory (V6) has revealed strong weaknesses of the latter for the\nsouthern Andes.”\nThe term “weaknesses” seems too vague and possibly unsuitable here. It would be more informative to specify what\nshortcomings of the Randolph Glacier Inventory were identified in the region. Does it poorly represent glacier outlines in this\narea?\nLine 428-430: “Since elevation changes cover the period 2000 to 2013, we manually produced outlines for 2013, which\nhave been missing so far. Thus, inventories available in this study cover years 2000, 2013 and 2019 oriented on inventory\navailability and geodetic data.”\nThe phrase “oriented on inventory availability” is unclear. I suggest rewording for clarity. Also, more detail is needed on how\nthe 2013 outlines were manually produced, as this is a crucial methodological step.\nLine 431-441: What is the final output of this method? Is it glacier-wide geodetic mass changes over the entire period?\nPlease clarify the time period and spatial scale covered by these mass change estimates.\nLine 464: Why was a radiation model used instead of directly employing incoming solar radiation from ERA5? Have you\nevaluated ERA5’s radiation data for this region, and if so, why was it deemed unsuitable for glacier-scale modeling?\nAdditionally, if you use cloudiness data from ERA5 for the radiation model, how reliable is this parameter, given that ERA5\ncloud data may be less accurate than its radiation estimates?\nLine 481: “...which is obtained by removing the orographic component from the ERA5 precipitation.”\nDoes ERA5 provide an orographic component of precipitation? Based on Hersbach et al. (2020), ERA5 supplies large-scale\nand convective precipitation, but not explicitly an orographic component. Please clarify this point, as convective precipitation\nis not synonymous with orographic precipitation.\nLine 523: “Albedo values are differentiated between snow, firn and ice surfaces. The decay of surface albedo due to snow\naging is parameterized following the scheme of Oerlemans and Knap.”\nGiven the critical role of albedo in surface energy balance (SEB) modeling, have you evaluated the modeled albedo against\nobservations from your study area? If in-situ albedo data is unavailable, MODIS-derived albedo could be a useful\ncomparison. Without any evaluation, it’s unclear how reliable the albedo model is for this region, and its validation\nelsewhere (e.g., in the European Alps) may not be sufficient due to spatial variability in albedo characteristics.\nLine 526: “correction using the Richardson-Number or the Monin-Obukhov similarity theory.”\nWhich approach was ultimately used? Further, how were roughness lengths determined? Have you compared your\nmodeled turbulent heat fluxes with measurements from glacier sites in your region to evaluate performance?\nLine 529: “was positively evaluated”\nThis phrase is unclear. Could you elaborate on what is meant by “positively evaluated” in this context?\nLine 532: “COSIPY results agreed well with the other models as well as with observations of ablation stakes and geodetic\nmass balance.”\nWhile this is a useful finding, it would be important to specify which parameters in COSIPY were calibrated and how this\ncalibration was performed. As noted earlier, calibration with geodetic mass balance or in-situ data has implications for the\ninterpretation of the results and the separation of the climatic and dynamic components of mass balance.\nLine 559: “Sensitivity runs are applied for further optimization.”\nPlease clarify what parameters or inputs were varied in the sensitivity runs. Were different datasets or methods used for\ncalibration, or were the model parameters adjusted? Additionally, it is crucial to provide a breakdown of the uncertainties that\narise from your modeling approach.\n“Model performance is quantified by the root mean square error between the glacier-specific climatic and geodetic mass\nbalance for the individual catchments.”\nHow do you address the fact that geodetic mass balance includes both the climatic and ice-flow components? Are you\ncomparing glacier-wide mass balance only? Please provide more details.\nLine 577-578: “Uncertainties of the glacier-specific CMB, constrained by model validation, directly translate into the\nuncertainties of frontal ablation estimations.”\nMore details are needed on how the uncertainties in glacier-specific CMB are quantified. Furthermore, uncertainties in\ngeodetic mass balance estimates should also be considered. Ideally, validation of frontal ablation estimates should be\nconducted on a study glacier where in-situ measurements of frontal ablation, ice-flow, and surface mass balance are\navailable.\nLine 582-583: “For our study site, the lack of ice thickness measurements in the CDI makes ice thickness highly speculative.\nThis directly translates into elevated uncertainties for frontal ablation.”\nCould you provide more details on how these uncertainties due to speculative ice thickness were quantified? It would\nstrengthen the paper to explain the methodology or assumptions used to assess these elevated uncertainties.\nResults section:\nSince you are using a surface energy balance (SEB) model for ablation, it would be informative to estimate the individual\ncontributions of key SEB components (incoming shortwave and longwave radiation, albedo, sensible and latent heat fluxes)\nto the total annual melt. While some information is provided, it would be beneficial to present a more systematic breakdown\nof how each term changes over the study period, both temporally and spatially. In particular, further discussion on albedo\nand incoming longwave radiation beyond the estimates of trends would provide valuable insights.\nLine 204: “Our results show that the annual CMB (Fig. 3c) is mainly controlled by air temperature (Fig. S3a).”\nThe word “controlled” may not be the best choice here. Temperature influences the CMB model primarily through the bulk\nmethod for sensible heat fluxes, which you indicate contribute around 30% to melt. Perhaps what you mean to say is that the\ninter-annual variability in CMB is most strongly correlated with temperature. Additionally, have you considered correlating\nCMB with albedo? Several studies (e.g., Davaze et al., 2018; Williamson et al., 2020; Xiao et al., 2022) demonstrate that\nmass balance is often strongly correlated with summer albedo.\nLine 230-236:\nIt was noted earlier that the flux-gate approach carries large uncertainties due to the lack of ice-thickness estimates, yet the\nreported errors for CDI frontal ablation using this approach are smaller than those from the method based on the difference\nbetween geodetic and CMB estimates. How is the total error from the flux-gate approach assessed? It would be helpful to\ninclude more detail on this in the Methods section. Additionally, how are the error estimates for frontal ablation of individual\nglaciers calculated?\nTable S5:\nWhile you’ve listed the roughness length for momentum, it would also be useful to include the roughness lengths for\ntemperature and humidity, as these are also important in the bulk method used in your SEB model. Additionally, how were\nthe roughness lengths determined? The roughness length of momentum for ice seems quite small (on the order of 10^-4 m).\nTypically, roughness lengths for ice are closer to 10^-3 m (see Hock, 2005 for reference). Could you clarify how this value\nwas chosen and whether it might be underestimated?", "reviewer_3": "This study produces the first climatic mass balance (CMB) simulation over the Cordillera Darwin Icelfield (CDI), one of the\nlargest ice bodies in the Southern Hemisphere. These outputs are differenced from satellite-derived elevation change\nmeasurement to calculate the mass loss due to iceberg calving and subaqueous melting (collectively termed frontal\nablation) for the first time. Results show that there is a strong climatic gradient associated with westerly winds across the CDI\nwhich definitively influences glacier mass balance. Frontal ablation accounts for 26% of the total mass loss in the CDI. Over\nthe 22-year study period, surface melt has increased (+0.18 m w.e. yr-1 per decade). While frontal ablation is important for\npredicting the evolution of specific glaciers, atmospheric conditions are the main control on glacier evolution.\nThe study results and conclusions are valid, robust, and represent an important contribution to the field of glaciology. The\nmanuscript is well written, and the figures and tables are formatted properly and of excellent quality. The suggested changes\nare minor and include drawing conclusions regarding the contrasting glacier behavior in the CDI within the discussion,\napplying a density conversion of 850 +/- 60 kgm-3 to convert the geodetic change to mass change, and modifying the\nintroduction to improve readability and clarity.\nKind regards,\nNicole Schaffer, PhD.\nGeneral comments\nValidity: The results and conclusions of this study are valid and robust.\nSignificance: Given that the CDI is one of the largest ice bodies in the Southern Hemisphere and contributes ~5% of the total\nloss in South America (Braun et al., 2019), the results are quite important for the field of glaciology and climate change\nscience. The CMB data set produced provides a second method to estimate mass loss that complements the satellite-\nderived elevation change measurements calculated here and previously published. Together these provide a more robust\nestimate of mass loss for the CDI, especially considering they are in close agreement. Confirming that climatic variables\nexert the greatest influence on glacier evolution, insight into how these variables are distributed over the CDI, and\nknowledge of how much loss is attributed to frontal ablation and how this varies through time helps tremendously for\nmodeling the evolution of these glaciers in the future.\nData and methodology: The approach is valid, reproducible, and meets the standards presented in published work within\nhighly respected journals. The data quality is good and the figures and tables provided both in the main text and SI support\nthe research and illustrate the results very effectively. In general, the manuscript is well written.\nAnalytical approach: The analysis is robust and the statistical results presented are appropriate.\nClarity and context: The manuscript text is clear and accessible. Sufficient context has been provided with the appropriate\nreferences and the results have been placed in the context of previous literature. The only section that needs some work in\nterms of the readability and clarity is the introduction (see comments in the “suggested improvements” section).\nReferences: Yes, the manuscript references previous literature appropriately.\nYour expertise: With respect to the CMB I have published using more simplistic models (e.g. enhanced temperature-index\nmodel) and have a strong background in glaciology and mass balance modelling theory (MSc and PhD in glaciology), but\nhave not published first-author articles using a full energy balance model. With respect to elevation change measurements, I\nhave a strong background in this area with publications on the subject but have not processed interferometry data sets\nmyself. I have published articles including calculations for frontal ablation.\nSuggested improvements:\nA sub-objective of this manuscript is to gain insight and draw conclusions on the contrasting glacier behavior in the last two\ndecades. This is addressed directly and possibly indirectly in several locations within the results and discussion sections.\nFor example, L262-274 where the four advancing glaciers are discussed in detail. L151-160 where the diversity is related to\nthe hypsometry, aspects and MALT versus land-termination of the respective glaciers. In the results/discussion the authors\ndiscuss how more precipitation in the south-western part of the CDI result in more positive mass balance here and more\nlosses in the north-east (e.g. L293-296). The impact of the ELA on mass balance is also discussed (e.g. L297-308). It would\nbe good to bring together all the above points and any other highly relevant results/information within the discussion section\nto draw some conclusions on why we observe contrasts in mass balance over the CDI. Particularly for those glaciers with a\npositive mass balance. Some or all of the text on L151-161 and L262-274 could be deleted from the results and moved to the\ndiscussion. If relevant, incorporate the four glaciers dominated by frontal ablation into this discussion. It would also be good\nto incorporate a very brief discussion on why MALT glaciers show on average a more positive CMB than land-terminating\nones (1-2 sentences).\nA density of 900 +/- 60 kgm-3 has been used to convert geodetic change to mass change in this manuscript. This is the\nstandard approach. However, it is well known that the “density” for geodetic volume-to-mass conversion is not constant and\nis systematically lower than ice density in most cases (Huss et al. 2013). This is due to the accretion/removal of low-density\nfirn layers and changes in the firn density profile with positive/negative mass balance. A value of 850 +/- 60 kgm-3 is\nappropriate for most situations. Therefore, I would suggest applying a density of 850 +/- 60 kgm-3 in addition to 900 +/- 60\nkgm-3. This could be included within the discussion section. New calculations for the dynamic component should be\nincluded and any changes to your main observations/conclusions should be discussed.\nIn general, the manuscript reads very well. The only section that needs some work in terms of the readability and clarity is\nthe introduction. This section could benefit from some restructuring and minor sentence modifications. To that end, I have\nmade some suggested changes and included this as a pdf with tracked changes. Here, the sentence starting on L67 has\nbeen moved after the mass budgeting is explained as this seems to flow better. I have modified the aims of the study to\nimprove clarity and have also made many suggestions to improve the readability (see tracked changes pdf). Details of the\nstudies quoted have been removed as this breaks the flow of the introduction. These sentences could be incorporated nicely\ninto the discussion (e.g. sentence on L76 could be incorporated in the sentence on L309, the sentence starting on L86 could\nbe incorporated in the paragraph on L339 and the sentence starting on L89 is redundant as this information is already in the\ndiscussion). Finally, I have added a sentence on L70 to first to explicitly make the reader aware that most of the\nmeasurements available (e.g. those described on L53-55) are geodetic and include both loss terms before discussing the\nmass budgeting approach.\nDetailed comments:\nIntroduction\nPlease see the tracked changes .pdf\nResults\nL110 What is “local”? Please define explicitly.\nL110-112 This sentence states that “A comparison of local precipitation with a firn core in the central Cordillera Darwin\nshows an overestimation”, but there is no data to back this statement up. Please provide a quantitative comparison (e.g.\namount of overestimation in SWE). Likewise, the statement “catchment-wide precipitation about 50 km downwind indicates an\nunderestimation” is qualitative (Figure S2). Please provide a quantitative comparison as well (e.g. mean and standard\ndeviation for the difference in streamflow between the stream gauges and downscaled data).\nL114 Consider changing “ As we aim at a…” to “As our aim is a…”\nL121 I assume the results presented here (e.g. 5.2ᵒC) are from the downscaled climate data, but it would be good to\nexplicitly state this so it is clear.\nL132 Consider changing to “…wind also show an increasing …”\nL172 consider rephrasing as “…decreasing snowfall towards the east results in CMB decreases….”\nL237-238 Here the author indicates that “..the majority of MALT glaciers show only low frontal ablation.” Can you quantify\nand specify what you mean by “low frontal ablation”? Are you referring to low frontal ablation rates for the majority of MALT\nglaciers compared to the average frontal ablation rate? It would be helpful to provide a simple reference value (e.g. the\naverage frontal ablation of all glaciers compared to the average for 50% of the glaciers with the lowest values)\nL290 I assume you mean global warming rates. If so modify this sentence to “…exceeds global warming rates…”\nL360 did you mean “temperate” instead of “temperature” here?\nL353 This paragraph could be modified to improve the readability and make it more concise in some places. I have simply\nhighlighted the text that should be reviewed in the tracked changes pdf.\nL238 change “For few..” to “For a few…”. Same comment for L253.\nL251-253 The first two sentences are a bit redundant and could be reduced to: “With the CMB and the frontal ablation\navailable, we can disentangle the total glacier mass changes observed from remote sensing into climatical and dynamical\nforcing.”\nFigure 1 For clarity it would be good to add the years associated with the CMB data here. For example, the first sentence\ncould be modified to “…(CDI) over the period 2000-2022.”\nFigure S2 consider modifying the figure caption from “..to precipitation over the river catchment…” to “..to downscaled\nprecipitation over the river catchment…” so it is clear that the yellow data set is the downscaled data set.\nDiscussion\nL293 modify “…moisture, more rich in snow conditions…” to “moister, snow-rich conditions…”\nL343 change “Alike” to “Like”\nL378 change “of glacier…” to “and glacier…”\nL378 It would be good to highlight why this location is unique and very relevant for climate science. Consider modifying to:\n“…at this unique location which is part of the only continental landmass crossed by the Southern Hemisphere westerly wind\nbelt.” …or something similar that highlights why the location is unique.\nL353-354 consider modifying to “…we satisfactorily constrain the CMB.”\nL355 consider modifying to “However, energy fluxes…”\nL359 consider modifying to “Furthermore, the considerable…”\nL386-387 The current statement about climatic warming is vague and not very convincing. Consider modifying to “…climatic\nwarming has definitively impacted CDI glaciers and their evolution is mainly controlled by atmospheric conditions.”\nFigure S4 In the caption it says that “The color scheme gives the model error” while in the legend the colour scheme is\nlabeled as the “difference climatic to geodetic mass balance.” I am assuming the legend is correct, so the caption should be\nmodified.\nFigure S6 change “Snowfall SNOW” to “snowfall (SNOW)”\nTable S1 – Consider modifying the label for column one from “Name” to “Station name”. Also change the header\n“responsibility” to “responsible”\nTable S2 – label the first column (e.g. Station name).\nData and Methods\nL395 replace “…temperature via relative…” with “…temperature, relative…”\nL429 consider removing “, which have been missing so far” as this is redundant because it is clear from the previous\nsentences that there are no outlines for this year.\nL430 consider removing “oriented on inventory availability and geodetic data” since this is redundant. It is already mentioned\nin the preceding sentences.\nL442 replace “had been” with “are”\nTable S2 From the text it sounds like this comparison is between the downscaled climate data and AWS data only (e.g. river\ncatchment data and firn core are not used). It would be good to state this explicitly by modifying the caption to: “…compared\nto the AWS observations.”\nReferences\nHuss M (2013) Density assumptions for converting geodetic glacier volume change to mass change. The Cryosphere 7(3),\n877–887. doi: 10.5194/tc-7-877-2013", "reviewer_1_attached": "Dear editor and referees,\nWe would like to thank you very much for the detailed and constructive comments to our\nmanuscript. We are convinced that the revisions have improved the overall quality of our\nmanuscript. Before we reply in detail to the individual comments, we would like to\nmention the most important changes implemented in the manuscript:\n1) The introduction was revised following the suggestions of the reviewers (mainly\nreviewer 3).\n2) We revised and streamlined the methods section and provide now more details\nespecially on the model calibration and validation and the uncertainty analysis. In this\nway, we hope to clarify the distinction between the actual calibration targets on regional\nscale and the glacier-specific observations used for uncertainty metrics.\n3) The uncertainty analysis of the frontal ablation estimation has been extended and\ncomprises now the measurement error of the (specific) geodetic mass balance. We\nfollow a statistical uncertainty propagation. Uncertainties have been updated\nthroughout the manuscript.\n4) We extended the modelling period by one year, now covering 2000-2023. Changes in\nnumbers and trends are minor, corroborating the robustness of our CMB results.\nKind regards,\nFranziska Temme, in the name of all co-authors\nPoint-by-point response to reviewer comments\nReviewer #1 (Remarks to the Author):\nIn this work, Temme and collaborators present a climatic mass balance forced by\nreanalysis data validated with in situ observations. Frontal ablation is also estimated.\nThe methods are standard for this kind of research. The novelty is related to the study\narea, as the modelling is applied to the glaciers of the Cordillera Darwin Icefield (CDI) in\nsouthernmost South America, an area poorly studied. The main conclusion is\natmospheric forcing is the main driver of the ablation in the region. The work is well-\nwritten and easy to follow and the figures are mostly clear, but I think some clarifications\nneed to be made before publication. I hope this review helps the authors improve the\nmanuscript.\nWe would like to thank you very much for the detailed and constructive review of our\nmanuscript. In the following, you find our point-by-point list of answers to the raised\ncomments. We are convinced that our actions have significantly improved the quality of\nthe manuscript. We sincerely hope you find our response satisfactory, and we have been\nable to clarify the raised points. Referee comments are reproduced in black font color.\nOur response and the undertaken actions are formulated in green font color, text that\nwas adjusted/added in the manuscript is highlighted in italic font.\nI suggest a small change in the title, including “ablation” instead of “melt”. Results of the\nmanuscript show that melt is the main component in the total ablation processes, i.e.\nhigher percentage (74%) compared to frontal ablation (26%). Melt by definition depends\non the atmosphere conditions (could be also by oceanic or lake conditions but this is\nnot directly quantified here). If I understand, I think the title looks to remark that the\nclimate or atmosphere drives the “ablation” as stated in lines 260-261.\nThank you for this comment. We agree and changed the word ‘melt’ to ‘ablation’.\nThe sentence in L275 and repeated in L347 is a bit confusing. How the mass loss is\ncontrolled by atmospheric conditions if the CMB is positive (0.02 m w.e. yr-1) or close to\nbalance (L332)? Results show climatic ablation is quite larger than frontal ablation\n(L275-277) and this is forced by the atmosphere, I understand this, but in terms of mass\nbalance, the overall CMB is still positive for the period meaning that CDI has been\nclimatically balanced in the recent two decades (L380). In consequence, overall no\nmass loss forced by atmosphere conditions between 2000-2022. Or do you refer to the\nlast six years of CMB modelling? or just to land-terminating glaciers that show negative\nspecific CMB (L145-146)? Please clarify this.\nThank you for pointing this out. We are referring to the ablation being mainly controlled\nby atmospheric conditions (instead of dynamic). We exchanged ‘mass loss’ with\n‘ablation’ in both mentioned sentences.\nNo justification for the period. For instance, why 22 years and not 30 years? In the title,\nthe word “Climate” is used, and by definition, the climate is a 30-year period (WMO). If\nthe 22-year period is well justified, maybe change “Climate´s” to “Atmosphere´s”.\nSee response to your comment on L107 regarding the justification of the period.\nWe would like to stick to this terminology in the title. Although the WMO defines 30 years\nas the standard climate period, it is not uncommon to also use shorter periods (from 20\nyears) in this context. The IPCC Glossary explicitly names periods of 20 years as\napplicable (IPCC 2012):\n”Climate in a narrow sense is usually defined as the average weather, or more rigorously,\nas the statistical description in terms of the mean and variability of relevant quantities\nover a period of time ranging from months to thousands or millions of years. The\nclassical period for averaging these variables is 30 years, as defined by the World\nMeteorological Organization. (…) In various chapters in this report diherent averaging\nperiods, such as a period of 20 years, are also used.”\nAs usual in glacier modelling-approach investigations some choices need to be better\njustified, for instance, the use of a constant air temperature lapse rate over a spatial\nvariable lapse rate. Also, other sources of uncertainties are not (at least) mentioned in\nthe manuscript. For instance, no mention of debris cover areas. Is this area important to\nquantify melt rates at CDI?\nThank you for this comment. In the sensitivity runs, we tested the application of a zonal\ngradient in the temperature lapse rate (added in the ‘Model calibration and validation’\nsection). Such gradient diherences were reported by Bravo et al. (2019), who found\nsteeper lapse rates east of the Andes as compared to west. Comparison with the\ngeodetic mass balances (for land-terminating glaciers) showed, however, no superior\nbehavior in the calibration.\nDebris-covered glacier areas are not common in the region. The Chilean Glacier\nInventory (Barcaza et al., 2017) defines only around 1 % of the glacier area as debris\ncovered. Therefore, we are convinced that debris-cover is negligible in this study.\nMinor comments\nL 38-39: “The large altitudinal range….” I don´t understand this sentence. How do the\nlocation and the climatic conditions control the altitudinal range of the CDI? Or do you\nrefer to the climate conditions extreme gradients? Please clarify.\nThank you for this question. We are referring to the altitudinal range of the glaciers,\ndescending down to sea level. This is possible due to the extreme climatic conditions\nproducing high accumulation amounts at the top. We reformulated the sentence to\nmake the statement clearer.\n“This large altitudinal range, with glaciers descending down to sea level, is possible due\nto the extreme climatic conditions inducing high mass input at the top.”\nL59-60: Reference 17 includes a frontal reconstruction of Marinelli Glacier back to 1910.\nWe added the reference, thank you.\nL63: I suggest including the area of the marine-terminating and the lake-terminating\nglaciers separately.\nWe included the information as suggested:\n“Around half of the CDI area consists of marine- or lake-terminating (MALT) glaciers\n(35% and 13%, respectively).”\nL107: Why this period?\nWe rely on 2000 (-1 year as spin-up) as start year because of data availability. Several\ndatasets that we use are dated at ~2000. Those are the glacier inventory (Barcaza et al.\n2017), the surface topography from SRTM and the geodetic mass balance (with elevation\nchanges calculated 2000-2013). The end date is chosen as close to present day as\npossible (when we started working on the study). To model full mass balance years, we\noriented the simulation times on the hydrological year. We have, however, extended the\nclimate data and the COSIPY simulation to 2023 now.\nL110: Any insight on why the correlation with Isla Hoste AWS is low?\nWe assume that you are referring to the precipitation at AWS Hoste, since the\ncorrelation for the other variables is high. Looking at the measurements again, we\nidentify issues with the precipitation sensor starting after ~1 year of measurements. We\nshortened the timeseries accordingly and updated the statistics in table S2. The\nupdated correlation is 0.72.\nL114-115: Ok, but you also show individual glacier CMB results, for instance in Fig. 1. Are\nthese values, especially the accumulation, reliable?\nSee response to your comment on L145-146.\nL123-124: I understand what you mention here, and agree, but be aware that relative\nhumidity is an indicator of how close to saturation the atmosphere is and depends on\nthe air temperature.\nThank you for that comment. We reformulated the sentence to make the statement\nclearer:\n“While air temperature at sea level exhibits no clear west-east gradient, annual average\nrelative humidity shows a drying towards the east (Fig. S3b).”\nL145-146: Similar to a previous comment, how reliable is the CMB estimation for\nindividual glaciers? I agree that the regional CMB is a good approach for CDI considering\nthe uncertainties, lack of measurements and diherences in the accumulation rate\nreported in L114 but, along the manuscript, CMB of individual glaciers is used for\ncomparisons.\nThank you for this question. Admittedly, we do report CMB values of individual glacier\ncatchments but we do so including the specific CMB uncertainty, which is quantified in\nan objective and systematic way. With this uncertainty assessment, we think it is\nwarranted to forward values for individual glacier catchments. Let me explain the\nuncertainty assessment:\nWe are comparing the glacier-wide integrated mass balance (specific mass balance) for\neach land-terminating glacier (> 3 km2). As land-terminating glaciers have no\ndynamically controlled losses, the two datasets are directly comparable. The glacier-\nspecific geodetic information has not been used for model calibration (only the regional\naverage has been used), and is, thus, an independent validation dataset. We compare\nthe (specific) geodetic and climatic mass balance per glacier catchment and calculate\nthe root mean square error (RMSE ±0.62 m w.e. yr-1). This error presents the\naccuracy/uncertainty of the climatic mass balance on a glacier-specific basis. We\nreformulated the ‘Model calibration and validation’ section to increase clarity (former\nL553-571), especially the following sentence:\n“Model performance is quantified by the root mean square error between the glacier-\nspecific climatic and geodetic mass balance for these glaciers, resulting in a model error\nof ±0.62 m w.e. yr-1.”\nL152-153: I suggest adding a Figure (could be in Supplementary Material) to explore the\ndiherences in the CMB between land and marine-lacustrine glaciers.\nThank you for this comment. The diherence can be seen in Fig. 1, where both the CMB\nand the termination type of the glaciers are included. We, however, agree that the\ninformation is hard to extract from this figure. Therefore, we added a figure with the\naverage annual CMB for each glacier, color-coding the termination type, to the\nsupplement (Fig. S11).\nL176: Change Juli by July.\nChanged.\nL297-308: Why present ELA results in the Discussion section and not in the Results\nsections?\nThank you for this comment. At this point, we compare the simulated ELA results with\nresults from previous studies, which we want to keep in the Discussion section.\nHowever, we moved the first two sentences (L296-298), where we only present results,\nto the results section.\nL317-321: Any clue for this behaviour? Southern Annular Mode or another mode of\ninterannual or interdecadal variability?\nThank you for this comment. The Southern Annular Mode is claimed to be the main\nmode of climate variability over southern Patagonia. We tested correlations between the\nSAM index and the climatic mass balance, snowfall and melt energy. None of these\nvariables indicates a relation between SAM and the mass/energy balance of the CDI.\nWe clearly see that the more positive phase around 2009 - 2015 is accompanied by higher\nsnowfall amounts and less surface melt compared to the years before and after (Fig.\nS10a). Climate data shows slightly lower air temperatures and years with increased\nprecipitation amounts. However, we do not have an explanation for this variability at the\nmoment. It would certainly be an interesting future study!\nWe added the following sentences:\n“Those more positive or negative periods are strongly linked to snowfall amounts and\nsurface melt (Fig. S10a). A distinct relation to the Southern Annular Mode, which is\nproposed as the main mode of climate variability in Tierra del Fuego33, cannot reliably be\nconfirmed from our results. This finding is in agreement with a recent study focused on\nthe Patagonian Icefields44.”\nL315-328: Missing references about glacier energy balance in Patagonian glaciers that\ncould be useful to add to the discussion.\nThank you for this comment. We already give several references about glacier energy\nbalance of Patagonian glaciers in this section (Temme et al. 2023, Weidemann et al.\n2020, Weidemann et al. 2018, Schaefer et al. 2020, Minowa et al. 2023, Schneider et al.\n2007). We now added the publication of Bravo et al. (2022). These are all publications\naddressing the energy balance of Patagonian glaciers that we are aware of. If you know\nother essential studies that we overlooked for this region, we would ask you to specify\nthose so that we can include them. Thank you!\nL329: Also missing references about surface melt trends and projections in Patagonian\nglaciers. I suggest comparing your findings with previous works at regional scale.\nConsidering the uncertainties that are mentioned in the paper I suggest keeping a\nregional point of view for comparisons. Some comparison by glacier is fine, but the\napproach here is regional.\nThank you for this comment. We extended the discussion on surface mass balance and\nmelt trends and projections for Patagonia:\n“A trend analysis over the study period clearly demonstrates an extremely likely increase\nin surface melt, which is in agreement with simulations of surface melt for the Northern\nand Southern Patagonian Icefield estimating a positive trend of +0.30 m w.e. yr-1 per\ndecade (1975-2005)37. This rise in surface melt is the main driver of a likely trend towards\nmore negative mass balance in the CDI. Congruently, Bravo et al.37 present negative\ntrends in the surface mass balance of the Northern and Southern Patagonian Icefield\n(1975-2005). However, contrary results are presented in ref. 45,43,46. Despite the likely\npositive trend in precipitation amounts in the CDI, we do not find an increase in snowfall\namounts. In general, glaciers in the CDI that are covering a lower elevation range (<\n600 m) already experience more pronounced mass losses with an average CMB trend of\n-0.43 m w.e. yr-1 per decade (extremely likely). At Perito Moreno Glacier some 400 km\nnorth of the CDI, Minowa et al.41 found a virtually certain decreasing trend in the surface\nmass balance over the ablation zone of -0.90 ±0.3 m w.e. yr-1 per decade (1996-2020).\nThis decreasing trend is in general agreement with our findings for areas at similar\naltitudes in the CDI (-0.50 m w.e. yr-1 per decade). If the recent trends continue, the CDI\nwill get further out of balance and glaciers will trace a path of accelerating mass loss as\nalready indicated by the current trend in the CMB (Fig. 3c). Projections for the Northern\nand Southern Patagonian Icefield predict just such a pathway of enhanced surface melt\ncausing decreasing surface mass balance until 205037.”\nL380-381: This sentence seems more appropriate for the climate or atmosphere forcing\non mass balance.\nThank you.\nL446: Is there any reference for this velocity threshold?\nThank you for this question. In order to enable a direct comparison between the specific\ngeodetic and climatic mass balance, we need to identify all glaciers with no (or\nnegligible) frontal ablation. The Chilean Glacier Inventory (Barcaza et al. 2017), which is\nused in this study, includes a classification of the termination type, but has a large share\nof lake- and marine-terminating glaciers. Especially for the lake-terminating glaciers, we\n(visually) identified many cases where frontal ablation is negligible due to a small calving\nfront and low ice velocity.\nTherefore, we had to revise the classification for our purposes. The goal was to find an\nobjective classification to distinguish those glaciers with significant frontal losses from\nthose with no or negligible frontal losses. Ice velocity is suitable because glaciers with\nnegligible ice flow at the front also have negligible calving. The classification is a\ncompromise between on the one hand excluding glaciers from the calibration/validation\ndataset with significant calving losses to avoid biased results, and on the other hand\nguaranteeing a calibration/validation dataset that is large enough. With our approach,\nwe achieve a calibration/validation dataset that covers ~37% of the entire CDI.\nTo guarantee that glaciers that had been defined as land terminating in the Chilean\nInventory will keep this classification, the threshold velocity of 60 m yr-1 (there was a\ntypo in the text) was suitable.\nA rough assessment of the calving fluxes of newly defined land-terminating glaciers\n(=glaciers terminating in lakes or fjords but defined as land-terminating in our study)\nshows that the specific calving losses are mostly < 0.1 m w.e. yr-1.", "reviewer_2_attached": "Dear editor and referees,\nWe would like to thank you very much for the detailed and constructive comments to our\nmanuscript. We are convinced that the revisions have improved the overall quality of our\nmanuscript. Before we reply in detail to the individual comments, we would like to\nmention the most important changes implemented in the manuscript:\n1) The introduction was revised following the suggestions of the reviewers (mainly\nreviewer 3).\n2) We revised and streamlined the methods section and provide now more details\nespecially on the model calibration and validation and the uncertainty analysis. In this\nway, we hope to clarify the distinction between the actual calibration targets on regional\nscale and the glacier-specific observations used for uncertainty metrics.\n3) The uncertainty analysis of the frontal ablation estimation has been extended and\ncomprises now the measurement error of the (specific) geodetic mass balance. We\nfollow a statistical uncertainty propagation. Uncertainties have been updated\nthroughout the manuscript.\n4) We extended the modelling period by one year, now covering 2000-2023. Changes in\nnumbers and trends are minor, corroborating the robustness of our CMB results.\nKind regards,\nFranziska Temme, in the name of all co-authors\nPoint-by-point response to reviewer comments\nReviewer #2 (Remarks to the Author):\nThe study models the surface mass balance of all glaciers in the Cordillera Darwin\nIcefield (CDI) in Tierra del Fuego from 2000 to 2019, utilizing the open-source surface\nenergy balance model COSIPY (Sauter et al., 2020), which is forced by downscaled ERA5\ndata. The model parameters are primarily calibrated with in-situ mass balance\nobservations from one or a few glaciers in the region. Notably, this calibration process is\nbased on the authors’ previously published work (Temme et al., 2023). The diherence\nbetween the geodetic mass balance and the simulated surface mass balance for lake-\nand ocean-terminating glaciers is used to estimate mass loss due to frontal ablation.\nOverall, the paper is well-written, but there are areas where additional methodological\ndetail would enhance clarity (elaborated further in my specific comments). The authors\nhighlight the novelty of the study as \"the first simulation of the climatic energy and mass\nbalance of glaciers in this region.\" However, given that the same first author has\npreviously applied the COSIPY model (developed by Sauter et al., 2020) to a subset of\nglaciers in the region (Temme et al., 2023), this work may be better framed as an\nextension of that earlier study, expanding the model's application to a broader set of\nglaciers.\nThe method used to estimate frontal ablation raises some concerns, particularly\nregarding the quantification of uncertainties (detailed in my specific comments). A more\ncomprehensive uncertainty analysis would strengthen the credibility of the results,\nparticularly in relation to frontal ablation estimates.\nIn summary, while the study provides valuable insights into the region, the novelty of the\ncontribution could be more clearly articulated. Additionally, addressing some critical\nmethodological elements, such as a more rigorous uncertainty analysis, would\nsignificantly enhance the robustness of the results.\nWe would like to thank you very much for the detailed and constructive review of our\nmanuscript. In the following, you find our point-by-point list of answers to the raised\ncomments. We are convinced that our actions have significantly improved the quality of\nthe manuscript. We sincerely hope you find our response satisfactory, and we have been\nable to overcome your methodological concerns. Referee comments are reproduced in\nblack font color. Our response and the undertaken actions are formulated in green font\ncolor, text that was adjusted/added in the manuscript is highlighted in italic font.\nSpecific comments:\nAbstract: The authors should include the period of the simulations in the abstract. It\ntook me some time to determine that the simulations cover 2000–2019, and having this\ninformation up front would clarify the scope of the study.\nThank you for this comment. We added the simulation period (2000-2023).\nLine 77-78: “...melt, which is strongly linked to air temperature”\nOne of the references cited here used a positive-degree-day (PDD) model to simulate\nmelt, so linking melt to temperature is an inherent assumption of the model.\nThank you for this comment. Based on another reviewer’s comment, we removed this\nsentence. It is giving too much detail for the Introduction and those points are better\nbeing discussed in the Discussion section. For the exact reformulation, see next\ncomment.\nLine 78-79: “Despite these local ehorts to determine the mass balance of individual\nglaciers, a systematic approach for a CDI-wide estimate of the CMB is to this day\nmissing.”\nHowever, Temme et al. (2023) (reference #20) addresses not just individual glacier\nmodeling but also regional-scale modeling. The authors may want to reconsider this\nstatement, as it somewhat underrepresents the existing work in this area.\nThank you for this comment. We agree that the formulation was misleading. We revised\nthe entire introduction based on another reviewer’s comments. The sentence was\nreformulated to:\n“The climatic mass balance (CMB) has been studied in the Cordon Martial (east of the\nstudy region, located in Argentina)19 and in the Mount Sarmiento Massif20,21(western CDI),\nbut these local e`orts are insu`icient and a systematic CDI-wide estimate of the CMB is\nneeded.”\nLine 80: “This lack of knowledge can be addressed with a well-informed modelling\nproduct of CMB.”\nThe term “well-informed modeling product of CMB” is unclear. It would improve clarity\nto specify what is meant by this term and what type of model product the authors are\nreferring to.\nThank you for this comment. The statement was removed in the course of the revision of\nthe introduction section based on another reviewer’s comments.\nLine 82-83: “Thus, with the climatic loss term available, the mass budget of the CDI\nglaciers can successfully be closed and give the dynamic loss as residual.”\nThere seems to be a disconnect between this statement and the preceding one. The\ntotal mass loss is derived from geodetic estimates, not the climatic loss term. I suggest\nrephrasing this to clarify that the dynamic loss is inferred from the residual of the\nmodeled climatic mass balance (CMB) and geodetic mass balance. Additionally, errors\nin both the CMB and geodetic estimates could be significant, making it challenging to\nassume that the residual solely represents dynamic loss.\nWe added a more detailed explanation in the text, saying:\n“Thus, with the climatic mass balance term being quantified, we assume that the\nresidual with respect to the geodetic mass budget is primarily explained by frontal\nablation – an ice-dynamically controlled loss term.”\nLine 94: “In this way, an unprecedented attribution of the observed mass loss to climatic\nand ice-dynamic forcing becomes possible.”\nWhile this is an important step forward, the authors should also account for the\nuncertainty in the modeled CMB and geodetic estimates. Without addressing these\nuncertainties, the attribution may not be as straightforward as suggested here. For\ninstance, Hugonnet et al. (2021) point out that the accuracy of geodetic mass balance\nestimates can decline when moving from multi-annual to annual timescales.\nWe refined and added more details on the uncertainty analysis of the frontal ablation in\nthe Data & Methods section on ‘Frontal ablation’. See also response to your comment on\nL577-578.\nLine 96-97: “The energy and mass balance will be examined using the physically-based\nCOupled Snowpack and Ice surface energy and mass balance model in PYthon\n(COSIPY).”\nIt would be helpful to explain why COSIPY was chosen for this study. Temme et al. (2023)\ncompared COSIPY with simpler models, such as PDD approaches, and noted that some\nof the model parameters, like those in the albedo parameterization, still require\ncalibration with mass balance observations. If the model is calibrated with geodetic\nmass balance, how can it provide an independent estimate of the ice-dynamic\ncomponent? If the in-situ mass balance data from one or a few glaciers is used for\ncalibration, how do the authors address the potential issue of limited parameter\ntransferability across the CDI?\nThank you for these questions.\nFor model calibration we use the region-wide average geodetic mass balance of all land-\nterminating glaciers (> 3km2) (= -0.27 m w.e./yr). By taking the land-terminating glaciers\nonly, the dynamic component is zero and the climatic and geodetic mass balance are\ndirectly comparable. Temme et al. (2023) conclude that calibrating against regional\ngeodetic observations is the best strategy to achieve realistic regional simulations of\nclimatic/surface mass balance, and to address the limited parameter transferability. We\nfollow this strategy, and we achieve a good agreement between the geodetic (-\n0.27 m w.e./yr) and climatic mass balance (-0.23 m w.e./yr), confirming the applicability\non the CDI.\nFor validation of the climatic mass balance, we again stick to the land-terminating\nglaciers, preventing a contribution of dynamic losses. However, now we compare the\n(specific) geodetic and climatic mass balance per glacier catchment (instead of the\nregional average taken for calibration), and calculate the root mean square error (RMSE\n±0.62 m w.e. yr-1). This error presents the accuracy/uncertainty of the climatic mass\nbalance on a glacier-specific basis. In-situ ablation observations from Schiaparelli and\nMartial Este Glacier are used for additional validation information.\nWe chose the COSIPY model since its application has been proven to be successful in\nthe area before (Temme et al. 2023) and we focus not only on the climatic mass balance\nbut also on the energy balance. Less complex models (positive-degree-day or\nsimplified-energy-balance model) would not have enabled a detailed analysis of the CDI\nglaciers’ energy balance.\nLine 422: “...since comparison with the Randolph Glacier Inventory (V6) has revealed\nstrong weaknesses of the latter for the southern Andes.”\nThe term “weaknesses” seems too vague and possibly unsuitable here. It would be more\ninformative to specify what shortcomings of the Randolph Glacier Inventory were\nidentified in the region. Does it poorly represent glacier outlines in this area?\nThank you. We reformulated the sentence for more clarity:\n“Glacier outlines are taken from the DGA glacier inventory 55,56 since the Randolph\nGlacier Inventory (V6) has revealed poor representation of outlines for the southern\nAndes, especially for smaller glaciers58.”\nLine 428-430: “Since elevation changes cover the period 2000 to 2013, we manually\nproduced outlines for 2013, which have been missing so far. Thus, inventories available\nin this study cover years 2000, 2013 and 2019 oriented on inventory availability and\ngeodetic data.”\nThe phrase “oriented on inventory availability” is unclear. I suggest rewording for clarity.\nAlso, more detail is needed on how the 2013 outlines were manually produced, as this is\na crucial methodological step.\nThank you for this comment. The outlines for 2013 were produced using satellite images\nfrom late summer 2013 and 2014, and manually adjusting the outlines to the 2013\nglacier extent. Satellite images used are Landsat 7 and 8 (March 2013) as well as ASTER\n(Advanced Spaceborne Thermal Emission and Reflection Radiometer) (January to March\n2013 and 2014).\nWe reformulated the section to: “Since elevation changes cover the period 2000 to 2013,\nwe manually produced outlines for 2013. Therefore, we used late-summer images from\nLandsat 7 and 8 (2013) and ASTER (Advanced Spaceborne Thermal Emission and\nReflection Radiometer) (2013 and 2014) and manually adjusted the outlines to the\ncurrent glacier extent. Thus, inventories available in this study cover years 2000, 2013\nand 2019.”\nLine 431-441: What is the final output of this method? Is it glacier-wide geodetic mass\nchanges over the entire period? Please clarify the time period and spatial scale covered\nby these mass change estimates.\nThe details on the processing and output of the method are given in (former) L533-552,\nwhile in this section only the data itself is described. To highlight the time period more\nclearly, we added it in (former) L 552: “The mean regional observation period of the\nelevation change rate measurement is 12.97 years (2000-2013).”\nLine 464: Why was a radiation model used instead of directly employing incoming solar\nradiation from ERA5? Have you evaluated ERA5’s radiation data for this region, and if so,\nwhy was it deemed unsuitable for glacier-scale modeling? Additionally, if you use\ncloudiness data from ERA5 for the radiation model, how reliable is this parameter, given\nthat ERA5 cloud data may be less accurate than its radiation estimates?\nThank you for this question. The coarse resolution of ERA5 data does not resolve the\nlocal topography, and is thus not directly applicable for our high-resolution (200x200m)\nstudy. A topographic correction would have been required. The applied radiation model\nruns on the target resolution and, thus, the topography is well resolved, incorporating\ncorrections for slope and aspect of the topography as well as topographic shading.\nIn our study, we follow in general the approach and setup of Temme et al. (2023) in the\nMount Sarmiento Massif, where COSIPY was carefully calibrated. In this study, the same\nradiation model was employed. To ensure transferability, the methodology must remain\nconsistent.\nThe performance of the modelled radiation is validated with available AWS\nmeasurements (Table S2).\nLine 481: “...which is obtained by removing the orographic component from the ERA5\nprecipitation.”\nDoes ERA5 provide an orographic component of precipitation? Based on Hersbach et al.\n(2020), ERA5 supplies large-scale and convective precipitation, but not explicitly an\norographic component. Please clarify this point, as convective precipitation is not\nsynonymous with orographic precipitation.\nThank you for this question. The orographic component of ERA5 is calculated by running\nthe orographic precipitation model on the ERA5 elevation model. This ERA5 orographic\nprecipitation is subtracted from the ERA5 total precipitation, giving the large-scale\nprecipitation without an orographic component. We reformulated the section\naccordingly:\n“The total precipitation is calculated by adding the orographic precipitation calculated in\nthe model to the large-scale precipitation. The large-scale precipitation is obtained by\nremoving the orographic component, calculated by running the orographic precipitation\nmodel on the ERA5 topography, from the ERA5 total precipitation.”\nLine 523: “Albedo values are differentiated between snow, firn and ice surfaces. The\ndecay of surface albedo due to snow aging is parameterized following the scheme of\nOerlemans and Knap.”\nGiven the critical role of albedo in surface energy balance (SEB) modeling, have you\nevaluated the modeled albedo against observations from your study area? If in-situ\nalbedo data is unavailable, MODIS-derived albedo could be a useful comparison.\nWithout any evaluation, it’s unclear how reliable the albedo model is for this region, and\nits validation elsewhere (e.g., in the European Alps) may not be suhicient due to spatial\nvariability in albedo characteristics.\nThank you for this comment. Unfortunately, there are no in-situ observations of albedo\navailable in the Cordillera Darwin to our knowledge. The albedo scheme of Oerlemans\nand Knap was applied and validated, however, at the Southern Patagonian Icefield\nbased on satellite observations (Bravo et al. 2022).\nFollowing your suggestion, we extracted daily values of surface albedo of the\nMODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 61 dataset (Hall and\nRiggs 2021) for the period 2000-2022. We use the \"Snow_Albedo_Daily_Tile\" band\n(https://nsidc.org/data/mod10a1/versions/61#anchor-documentation) provided by the\nNational Snow and Ice Data Center (NSIDC). As anticipated, the spatial and temporal\ncoverage over the CDI is very low due to persistent cloud coverage of the majority of\nglacierized areas. Using MODIS data directly as an input to the model would thus not be\nfeasible. Instead, we decided to derive seasonal-average-tiles for winter (JJA) and\nsummer (DFJ) (see figures below). Also in those fields, we observe incomplete coverage\nand many pixels with few observations. Furthermore, we do not see a clear elevation\ndependent albedo as we would have expected it. At several points, neighboring pixels\nshow extreme diherences.\nEven in winter (JJA), when snowfall is extremely frequent, many pixels show albedo\nvalues around 40-50% in the central plateau (>1500 m a.s.l.), as can be seen for the\nexample year 2020 below (the year with the best coverage). A possible explanation for\nthese inconsistencies could be a misclassification of pixels, indicating clear sky\nconditions while clouds are still present over the ice surface. We strongly doubt these\nvalues.\nIn summer (DJF), the largest part of the CDI has no albedo observations which we relate\nto cloud coverage and/or misclassifications of the albedo product over the snow-\ncovered areas (see example from year 2011/12 below).\nDue to these complications, we unfortunately don’t see a way to make use of the\nMODIS-derived albedo for our study site.\nThe albedo scheme that we apply over the CDI was part of the model calibration in the\nMount Sarmiento Massif in the western part of the CDI (Temme et al. 2023). Thus, the\nfeasibility of the ice and firn albedo is given.\nLine 526: “correction using the Richardson-Number or the Monin-Obukhov similarity\ntheory.”\nWhich approach was ultimately used? Further, how were roughness lengths\ndetermined? Have you compared your modeled turbulent heat fluxes with\nmeasurements from glacier sites in your region to evaluate performance?\nThank you for these questions. The model set-up is summarized in Table S5 (see former\nL 529). Roughness lengths were taken from Temme et al. 2023, where the ice roughness\nlength was calibrated in the Mount Sarmiento Massif (western CDI).\nUnfortunately, there are no measurements of turbulent heat fluxes available in the\nCordillera Darwin. A direct comparison is, thus, not possible.\nLine 529: “was positively evaluated”\nThis phrase is unclear. Could you elaborate on what is meant by “positively evaluated” in\nthis context?\nThank you for the question. The model evaluation and comparison with three less\ncomplex surface mass balance models showed an overall good performance of COSIPY.\nDespite being more challenging to calibrate, results of COSIPY agreed well with the\nother models and the observations of glacier-specific geodetic mass balance and\nablation stakes used for validation (see former L531-532). Accordingly, Temme et al.\n(2023) show that the COSIPY model can be applied in the Monte Sarmiento Massif with\nsimilar performance to less complex models.\nLine 532: “COSIPY results agreed well with the other models as well as with\nobservations of ablation stakes and geodetic mass balance.”\nWhile this is a useful finding, it would be important to specify which parameters in\nCOSIPY were calibrated and how this calibration was performed. As noted earlier,\ncalibration with geodetic mass balance or in-situ data has implications for the\ninterpretation of the results and the separation of the climatic and dynamic components\nof mass balance.\nThank you for the question. The parameters calibrated in COSIPY in Temme et al. 2023\nare listed in Table 1 of that paper: albedo of ice, albedo of firn, and roughness length of\nice. In that paper, also the calibration strategy is explained in more detail.\nIn short, climatic mass balance was calibrated against the region-wide average geodetic\nmass balance of the land-terminating glaciers (same approach as for this study). Taking\nonly the land-terminating glaciers, the dynamic component is zero and the climatic and\ngeodetic mass balance are directly comparable.\nIn this study, a full calibration is not feasible due to the size of the domain. Instead,\nsensitivity runs are used for optimization of the climatic input data (see next comment).\nLine 559: “Sensitivity runs are applied for further optimization.”\nPlease clarify what parameters or inputs were varied in the sensitivity runs. Were\ndiherent datasets or methods used for calibration, or were the model parameters\nadjusted? Additionally, it is crucial to provide a breakdown of the uncertainties that\narise from your modeling approach.\nThank you for this question. COSIPY model parameters are taken from the Mount\nSarmiento Massif. In the 5 sensitivity runs, we varied the atmospheric input fields to\naddress the challenge for extrapolating from the local (AWS) scale to the regional scale.\nThe gradients across the cordillera are strong, requiring the testing of diherent\ninterpolation methods. Tests include variations in the interpolation of the relative\nhumidity and wind velocity fields as well as the application of a gradient in the\ntemperature lapse rate (based on Bravo et al. 2019, suggesting steeper gradients east of\nthe Andes compared to west). The target is the region-wide average geodetic mass\nbalance for the land terminating glaciers (= -0.27 m w.e./yr) that was met well by the\nchosen, presented run (-0.23 m w.e./yr). The sensitivity runs covered a spread between\n+0.51 and -1.58 m w.e./yr. We added this information into the text:\n“Sensitivity runs are applied for further optimization, where the methods for the\ngeneration of the atmospheric input fields (relative humidity, wind velocity, air\ntemperature) are varied, addressing the challenge to realistically reproduce the zonal\nclimatic gradients.”\nThe uncertainty of the modelled climatic mass balance is calculated in the model\nvalidation based on glacier specific geodetic mass balances. See next comment for\nmore detail.\n“Model performance is quantified by the root mean square error between the glacier-\nspecific climatic and geodetic mass balance for the individual catchments.”\nHow do you address the fact that geodetic mass balance includes both the climatic and\nice-flow components? Are you comparing glacier-wide mass balance only? Please\nprovide more details.\nThank you for this question. We are comparing the glacier-wide integrated mass balance\n(called specific mass balance) for each land-terminating glacier. As land-terminating\nglaciers have no ice-dynamically controlled losses, the two datasets are directly\ncomparable. The glacier-specific geodetic information has not been used for model\ncalibration (targeting the regional average), and is, thus, an independent validation\ndataset.\nThe information that we are only using land-terminating glaciers without frontal losses is\nstated several times in this section (former L562, 564, 565-566). We reformulated the\nfollowing sentences to increase clarity (former L560-562 & former L568-570):\n“Following this approach, we rank the sensitivity runs based on the highest agreement\nwith regional geodetic mass balance, as observed with satellite remote sensing, for all\nglaciers with no frontal ablation (region-wide average -0.27 m w.e. yr-1). The highest\nranked run (region-wide average -0.23 m w.e. yr-1) agrees well with the geodetic\nobservations and is presented in this study.”\n“Model performance is quantified by the root mean square error between the glacier-\nspecific climatic and geodetic mass balance for these glaciers, resulting in a model error\nof ±0.62 m w.e. yr-1.”\nLine 577-578: “Uncertainties of the glacier-specific CMB, constrained by model\nvalidation, directly translate into the uncertainties of frontal ablation estimations.”\nMore details are needed on how the uncertainties in glacier-specific CMB are quantified.\nFurthermore, uncertainties in geodetic mass balance estimates should also be\nconsidered. Ideally, validation of frontal ablation estimates should be conducted on a\nstudy glacier where in-situ measurements of frontal ablation, ice-flow, and surface\nmass balance are available.\nThank you for this comment. The estimation of uncertainties in the glacier-specific CMB\nhas been explained in the comment above. To consider the uncertainties in the specific\ngeodetic mass balance more explicitly, we now add the geodetic mass balance error to\nthe uncertainty analysis. The total uncertainty adds the uncertainty in the specific\nclimatic mass balance and the uncertainty in the specific geodetic mass balance. This\nway, we overestimate the inherent uncertainty because random errors in the geodetic\nmass balance may be counted twice: 1) In the geodetic mass balance error itself and 2)\nin the climatic mass balance error as it is inferred from the RMSE with the glacier-\nspecific geodetic values. We adjusted the section accordingly:\n“Uncertainties in frontal ablation consist of the uncertainties in the glacier-specific CMB\n(see Model calibration and validation) and the uncertainties in the specific geodetic\nmass balance (see Geodetic mass balance processing) following classical Gaussian\nerror propagation. Since the former uncertainty already includes random errors in the\ngeodetic mass balance, the resulting uncertainties of frontal ablation values are likely an\noverestimation.”\nThe only glacier with in-situ observations of ice thickness, ablation and surface\nvelocities is Schiaparelli Glacier. We can calculate the discharge through a flux gate\n(D ) at the location of the ice thickness measurement (Gacitúa et al. 2021). Together\nFG\nwith the climatic mass balance above this flux gate (CMB ), this value should match the\nFG\ngeodetic mass balance (GMB ) above this flux gate:\nFG\nGMB = CMB + D\nFG FG FG\nThe results agree within their uncertainty ranges:\nGMB = -0.014 ±0.004 Gt/yr\nFG\nCMB + D = -0.024 ±0.020 Gt/yr\nFG FG\nLine 582-583: “For our study site, the lack of ice thickness measurements in the CDI\nmakes ice thickness highly speculative. This directly translates into elevated\nuncertainties for frontal ablation.”\nCould you provide more details on how these uncertainties due to speculative ice\nthickness were quantified? It would strengthen the paper to explain the methodology or\nassumptions used to assess these elevated uncertainties.\nThank you for this question. With this statement we want to highlight the elevated\nuncertainty in ice thickness reconstructions in the CDI compared to other regions due to\nthe lack of observations. There is no possibility to validate those fields with in-situ\nobservations, and no in-situ observations of ice thickness are included in the modelling.\nTo quantify these uncertainties more thoroughly, we compare the available ice thickness\nproducts from modelling studies and calculate the standard deviation per pixel. While\nlocally the deviations can be extremely high (up to 250 m), the standard deviation along\nthe flux gates is smaller. The uncertainty in frontal ablation following this new approach\nincreases for some glaciers while it decreases for others (see new Figure 4). We\nadjusted the section on the flux gate approach accordingly:\n“For our study site, the lack of ice thickness measurements in the CDI makes modelled\nice thickness uncertain. To quantify the uncertainty in the ice thickness, we calculate the\nstandard deviation of the available ice thickness products from Carrivick et al.64, Millan\net al.3 and the participants in the consensus estimate covering the CDI2. Time\ndiscrepancies are corrected for by satellite-derived elevations changes.”\nResults section:\nSince you are using a surface energy balance (SEB) model for ablation, it would be\ninformative to estimate the individual contributions of key SEB components (incoming\nshortwave and longwave radiation, albedo, sensible and latent heat fluxes)\nto the total annual melt. While some information is provided, it would be beneficial to\npresent a more systematic breakdown of how each term changes over the study period,\nboth temporally and spatially. In particular, further discussion on albedo and incoming\nlongwave radiation beyond the estimates of trends would provide valuable insights.\nThank you for the comment. Most of the relevant energy and mass fluxes and their\ncontributions are provided in Fig. 3 and Fig. S6-S9. We added a figure that gives the\nannual values of those variables over the study period in the supplement (Fig. S10).\nIncoming and outgoing short- and longwave radiation only show minor annual variability,\nwhich is why we excluded those variables here for visibility reasons.\nLine 204: “Our results show that the annual CMB (Fig. 3c) is mainly controlled by air\ntemperature (Fig. S3a).”\nThe word “controlled” may not be the best choice here. Temperature influences the CMB\nmodel primarily through the bulk method for sensible heat fluxes, which you indicate\ncontribute around 30% to melt. Perhaps what you mean to say is that the inter-annual\nvariability in CMB is most strongly correlated with temperature. Additionally, have you\nconsidered correlating CMB with albedo? Several studies (e.g., Davaze et al., 2018;\nWilliamson et al., 2020; Xiao et al., 2022) demonstrate that mass balance is often\nstrongly correlated with summer albedo.\nThank you for this comment. We revised the sentence according to your suggestions:\n“Our results show that the inter-annual variability of the CMB (Fig. 3c) is mainly\ninfluenced by air temperature ...”\nFurthermore, we tested the correlation between albedo and CMB. Indeed, there is a\nsignificant correlation in summer (DJF), but also during the entire year. We included this\ninformation into the manuscript.\n“Melt energy and CMB are also linked to the annual average incoming solar radiation\n(r = 0.54 and r = -0.46, respectively) as well as the albedo (r = -0.68 and r = 0.69,\nrespectively).”\nLine 230-236:\nIt was noted earlier that the flux-gate approach carries large uncertainties due to the\nlack of ice-thickness estimates, yet the reported errors for CDI frontal ablation using this\napproach are smaller than those from the method based on the diherence between\ngeodetic and CMB estimates. How is the total error from the flux-gate approach\nassessed? It would be helpful to include more detail on this in the Methods section.\nAdditionally, how are the error estimates for frontal ablation of individual glaciers\ncalculated?\nSee reply to the comments on the Data & Methods section above. Numbers in this\nsection, the discussion and the abstract were adjusted following the revised uncertainty\nestimations.\nTable S5:\nWhile you’ve listed the roughness length for momentum, it would also be useful to\ninclude the roughness lengths for temperature and humidity, as these are also important\nin the bulk method used in your SEB model. Additionally, how were the roughness\nlengths determined? The roughness length of momentum for ice seems quite small (on\nthe order of 10^-4 m). Typically, roughness lengths for ice are closer to 10^-3 m (see\nHock, 2005 for reference). Could you clarify how this value was chosen and whether it\nmight be underestimated?\nThank you for these questions. The roughness length of ice was taken from Temme et al.\n(2023) where it was one of the calibration parameters, as given in Table S5. An\nunderestimation is not impossible, however, larger values of ice roughness length\nproduced larger deviation from the calibration targets (regional geodetic mass balance)\nand validation datasets (specific geodetic mass balance and ablation stake\nmeasurements) in that study (see Temme et al. 2023, Supplement).\nThe formulation of roughness lengths for temperature and humidity in COSIPY follows\nthe renewal theory for turbulent flow. Thus, the roughness lengths for humidity and\ntemperature are assumed to be one and two orders of magnitude smaller than the\nroughness length for momentum, respectively (Sauter et al. 2020).", "reviewer_3_attached": "Dear authors,\nThe manuscript has been improved significantly through the review process and all my\nprevious comments and additional concerns have been addressed directly or indirectly\nthrough your response to the reviewers. The remaining comments I have are minor.\nKind regards,\nNicole Schaffer, PhD.\nWe would like to thank you very much for the detailed and constructive review of our\nmanuscript. In the following, you find our point-by-point list of answers to the raised\ncomments. We are convinced that our actions have significantly improved the quality of\nthe manuscript. We sincerely hope you find our response satisfactory. Referee\ncomments are reproduced in black font color. Our response and the undertaken actions\nare formulated in green font color, text that was adjusted/added in the manuscript is\nhighlighted in italic font.\nGeneral comments\nValidity: The results and conclusions of this study are valid and robust.\nSignificance: Given that the CDI is one of the largest ice bodies in the Southern\nHemisphere and contributes ~5% of the total loss in South America (Braun et al., 2019),\nthe results are quite important for the field of glaciology and climate change science.\nThe CMB data set produced provides a second method to estimate mass loss that\ncomplements the satellite-derived elevation change measurements calculated here\nand previously published. Together these provide a more robust estimate of mass loss\nfor the CDI, especially considering they are in close agreement. Confirming that climatic\nvariables exert the greatest influence on glacier evolution, insight into how these\nvariables are distributed over the CDI, and knowledge of how much loss is attributed to\nfrontal ablation and how this varies through time helps tremendously for modeling the\nevolution of these glaciers in the future.\nData and methodology: The approach is valid, reproducible, and meets the standards\npresented in published work within highly respected journals. The data quality is good\nand the figures and tables provided both in the main text and SI support the research\nand illustrate the results very ehectively. In general, the manuscript is well written.\nAnalytical approach: The analysis is robust and the statistical results presented are\nappropriate.\nClarity and context: The manuscript text is clear and accessible. Suhicient context has\nbeen provided with the appropriate references and the results have been placed in the\ncontext of previous literature. The only section that needs some work in terms of the\nreadability and clarity is the introduction (see comments in the “suggested\nimprovements” section).\nReferences: Yes, the manuscript references previous literature appropriately.\nYour expertise: With respect to the CMB I have published using more simplistic models\n(e.g. enhanced temperature-index model) and have a strong background in glaciology\nand mass balance modelling theory (MSc and PhD in glaciology), but have not published\nfirst-author articles using a full energy balance model. With respect to elevation change\nmeasurements, I have a strong background in this area with publications on the subject\nbut have not processed interferometry data sets myself. I have published articles\nincluding calculations for frontal ablation.\nSuggested improvements:\nA sub-objective of this manuscript is to gain insight and draw conclusions on the\ncontrasting glacier behavior in the last two decades. This is addressed directly and\npossibly indirectly in several locations within the results and discussion sections. For\nexample, L262-274 where the four advancing glaciers are discussed in detail. L151-160\nwhere the diversity is related to the hypsometry, aspects and MALT versus land-\ntermination of the respective glaciers. In the results/discussion the authors discuss how\nmore precipitation in the south-western part of the CDI result in more positive mass\nbalance here and more losses in the north-east (e.g. L293-296). The impact of the ELA\non mass balance is also discussed (e.g. L297-308). It would be good to bring together all\nthe above points and any other highly relevant results/information within the discussion\nsection to draw some conclusions on why we observe contrasts in mass balance over\nthe CDI. Particularly for those glaciers with a positive mass balance. Some or all of the\ntext on L151-161 and L262-274 could be deleted from the results and moved to the\ndiscussion. If relevant, incorporate the four glaciers dominated by frontal ablation into\nthis discussion. It would also be good to incorporate a very brief discussion on why MALT\nglaciers show on average a more positive CMB than land-terminating ones (1-2\nsentences).\nThank you for this comment. We added a short paragraph about the variability in glacier-\nspecific CMB and the characteristics in the Discussion section. The information about\nthe diherence in CMB between MALT and land-terminating glaciers was moved here\nfrom the results section. The reason for the diherence lies in the glacier hypsometry.\nLand-terminating glaciers cover on average lower elevations and have little glacier area\nabove 1200m, while MALT glaciers have a more even area distribution between 500 and\n1500m.\n“Glacier-specific CMB across the CDI is highly variable (Fig. 1c) and depends strongly on\nglacier hypsometry. MALT glaciers show on average a more positive CMB than land-\nterminating glaciers as their catchment area extends generally to higher altitudes (above\n1200 m). In contrast to the overall mass loss and retreat of glaciers in the CDI, few\nglaciers have advanced during the first two decades of the 21st century. An explanation\nfor this contrasting behavior may lie in the exposition and hypsometry of the glaciers.\nHigh-elevation accumulation areas and steep topography result in high snowfall\namounts and above-average accumulation-area-ratios. Southward exposures of\nGaribaldi, Guilcher Oeste and Guilcher Este glaciers further reduce surface ablation.\nGlaciers with high accumulation-area-ratio are often less sensitive to changes in ELA\nand, thus, warming due to the small and steep ablation area15.”\nA density of 900 +/- 60 kgm-3 has been used to convert geodetic change to mass change\nin this manuscript. This is the standard approach. However, it is well known that the\n“density” for geodetic volume-to-mass conversion is not constant and is systematically\nlower than ice density in most cases (Huss et al. 2013). This is due to the\naccretion/removal of low-density firn layers and changes in the firn density profile with\npositive/negative mass balance. A value of 850 +/- 60 kgm-3 is appropriate for most\nsituations. Therefore, I would suggest applying a density of 850 +/- 60 kgm-3 in addition\nto 900 +/- 60 kgm-3. This could be included within the discussion section. New\ncalculations for the dynamic component should be included and any changes to your\nmain observations/conclusions should be discussed.\nThank you for this comment. We decided to follow Braun et al. (2019) who suggest a\ndensity conversion of 900 ±60 kg m-3 for Patagonian glaciers where melt of ice plays the\nmajor role. We tested the application of a density of 850 ±60 kg m-3, and results did not\nchange significantly. The presented simulation stays the best-ranked run in the\nsensitivity tests and the calculated model error (RMSE) stays unchanged at\n±0.62 m w.e. yr-1.\nWe could provide the frontal ablation results for the second density-scenario, however,\nit is redundant in our opinion. Reducing the density from 900 to 850 kg m-3 results in a\ndecrease in geodetic mass loss by ~5%. This reduction directly translates into the frontal\nablation calculated with the mass budgeting approach. The frontal ablation will, thus,\nalso reduce by ~5%. In our opinion, the gain of information by including the second\ndensity scenario is limited. We added the following paragraph in the Discussion:\n“We apply a density conversion factor of 900 kg m-3 for volume-to-mass conversion,\nfollowing Braun et al.9. A lower conversion factor of 850 kg m-352 does not change the\nCMB model performance metric significantly and transmits linearly into the frontal\nablation estimates. This is covered by the uncertainty ranges.”\nIn general, the manuscript reads very well. The only section that needs some work in\nterms of the readability and clarity is the introduction. This section could benefit from\nsome restructuring and minor sentence modifications. To that end, I have made some\nsuggested changes and included this as a pdf with tracked changes. Here, the sentence\nstarting on L67 has been moved after the mass budgeting is explained as this seems to\nflow better. I have modified the aims of the study to improve clarity and have also made\nmany suggestions to improve the readability (see tracked changes pdf). Details of the\nstudies quoted have been removed as this breaks the flow of the introduction. These\nsentences could be incorporated nicely into the discussion (e.g. sentence on L76 could\nbe incorporated in the sentence on L309, the sentence starting on L86 could be\nincorporated in the paragraph on L339 and the sentence starting on L89 is redundant as\nthis information is already in the discussion). Finally, I have added a sentence on L70 to\nfirst to explicitly make the reader aware that most of the measurements available (e.g.\nthose described on L53-55) are geodetic and include both loss terms before discussing\nthe mass budgeting approach.\nThank you for your detailed and valuable revision on the introduction. We revised the\nintroduction based on the suggested changes.\nDetailed comments:\nIntroduction\nPlease see the tracked changes .pdf\nThank you for your detailed and valuable revision on the introduction. We implemented\nthe suggested changes.\nResults\nL110 What is “local”? Please define explicitly.\nThank you for this question. We reformulated the sentence stating more clearly what we\ncompared:\n“A comparison between a firn core in the central Cordillera Darwin and modelled\nprecipitation at the closest grid point shows…”\nL110-112 This sentence states that “A comparison of local precipitation with a firn core\nin the central Cordillera Darwin shows an overestimation”, but there is no data to back\nthis statement up. Please provide a quantitative comparison (e.g. amount of\noverestimation in SWE). Likewise, the statement “catchment-wide precipitation about\n50 km downwind indicates an underestimation” is qualitative (Figure S2). Please provide\na quantitative comparison as well (e.g. mean and standard deviation for the diherence in\nstreamflow between the stream gauges and downscaled data).\nThank you for this comment. We add the main bias between modelled precipitation and\nboth measurements (firn core and stream gauge) to the manuscript:\n“A comparison between a firn core in the central Cordillera Darwin and modelled\nprecipitation at the closest grid point shows an overestimation (mean bias of\n+0.63 m w.e. yr-1) while catchment-wide precipitation about 50 km downwind measured\nwith a stream gauge indicates an underestimation (mean bias of -0.43 m w.e. yr-1) (Fig. 1,\nFig. S2).”\nThe correlation and bias have been added to Fig. S2. The firn core data has not been\npublished yet (currently under review), which is why we cannot show the exact values\nhere.\nL114 Consider changing “ As we aim at a…” to “As our aim is a…”\nChanged, thank you.\nL121 I assume the results presented here (e.g. 5.2ᵒC) are from the downscaled climate\ndata, but it would be good to explicitly state this so it is clear.\nChanged.\nL132 Consider changing to “…wind also show an increasing …”\nChanged to “Precipitation and wind both show an increasing trend …”\nL172 consider rephrasing as “…decreasing snowfall towards the east results in CMB\ndecreases….”\nChanged.\nL237-238 Here the author indicates that “..the majority of MALT glaciers show only low\nfrontal ablation.” Can you quantify and specify what you mean by “low frontal ablation”?\nAre you referring to low frontal ablation rates for the majority of MALT glaciers compared\nto the average frontal ablation rate? It would be helpful to provide a simple reference\nvalue (e.g. the average frontal ablation of all glaciers compared to the average for 50% of\nthe glaciers with the lowest values)\nThank you for this comment. We added the information, that the majority of MALT\nglaciers has a frontal ablation < 0.03 Gt yr-1 and an average contribution to frontal\nablation of less than 1%.\n“For both approaches, the majority of MALT glaciers shows only low frontal ablation\n(<0.03 Gt yr-1) (Fig. 4) accounting on average for less than 1 % of the total amount.”\nL290 I assume you mean global warming rates. If so modify this sentence to “…exceeds\nglobal warming rates…”\nThank you for this question. The cited rates are referring to southern South America. We,\nnow, adjusted it to the results for Punta Arenas (located close to the CDI) and added this\ninformation to the sentence:\n“The warming trend for the beginning of the 21st century found in this study (+0.42 °C per\ndecade) exceeds warming rates reported for the 20th century in Punta Arenas (+0.21 °C\nper decade)35 as well as the projected warming in the Magellan region until mid of this\ncentury under a high-emission scenario (RCP8.5) (total warming of +0.5 °C until 2050)36.”\nL360 did you mean “temperate” instead of “temperature” here?\nYes, thank you.\nL353 This paragraph could be modified to improve the readability and make it more\nconcise in some places. I have simply highlighted the text that should be reviewed in the\ntracked changes pdf.\nThank you for this comment. We revised the paragraph and reformulated especially the\nhighlighted parts.\nL238 change “For few..” to “For a few…”. Same comment for L253.\nChanged.\nL251-253 The first two sentences are a bit redundant and could be reduced to: “With the\nCMB and the frontal ablation available, we can disentangle the total glacier mass\nchanges observed from remote sensing into climatical and dynamical forcing.”\nChanged as suggested, thank you.\nFigure 1 For clarity it would be good to add the years associated with the CMB data here.\nFor example, the first sentence could be modified to “…(CDI) over the period 2000-2022.”\nThank you for this comment. We adjusted it as suggested.\nFigure S2 consider modifying the figure caption from “..to precipitation over the river\ncatchment…” to “..to downscaled precipitation over the river catchment…” so it is clear\nthat the yellow data set is the downscaled data set.\nChanged as suggested, thank you.\nDiscussion\nL293 modify “…moisture, more rich in snow conditions…” to “moister, snow-rich\nconditions…”\nChanged as suggested.\nL343 change “Alike” to “Like”\nChanged.\nL378 change “of glacier…” to “and glacier…”\nWe are analyzing the climatic influence on glacier evolution. Changing the sentence as\nsuggested would change the meaning. Instead, we changed it to:\n“Furthermore, these simulations shed light on the climatic imprint of glacier evolution at\na unique location in the higher mid-latitudes of the Southern Hemisphere.”\nL378 It would be good to highlight why this location is unique and very relevant for\nclimate science. Consider modifying to: “…at this unique location which is part of the\nonly continental landmass crossed by the Southern Hemisphere westerly wind belt.”\n…or something similar that highlights why the location is unique.\nThank you. We reformulated the sentence to:\n“Furthermore, these simulations shed light on the climatic imprint of glacier evolution at\na unique location in the higher mid-latitudes of the Southern Hemisphere, the only major\nland mass disrupting the westerly wind belt.”\nL353-354 consider modifying to “…we satisfactorily constrain the CMB.”\nChanged.\nL355 consider modifying to “However, energy fluxes…”\nChanged the sentence to:\n”However, due to a lack of observations most energy fluxes are not directly verifiably.”\nL359 consider modifying to “Furthermore, the considerable…”\nChanged.\nL386-387 The current statement about climatic warming is vague and not very\nconvincing. Consider modifying to “…climatic warming has definitively impacted CDI\nglaciers and their evolution is mainly controlled by atmospheric conditions.”\nChanged as suggested (without the word ‘definitively’).\nFigure S4 In the caption it says that “The color scheme gives the model error” while in\nthe legend the colour scheme is labeled as the “diherence climatic to geodetic mass\nbalance.” I am assuming the legend is correct, so the caption should be modified.\nChanged, thank you.\nFigure S6 change “Snowfall SNOW” to “snowfall (SNOW)”\nChanged.\nTable S1 – Consider modifying the label for column one from “Name” to “Station name”.\nAlso change the header “responsibility” to “responsible”\nChanged.\nTable S2 – label the first column (e.g. Station name).\nChanged, thank you.\nData and Methods\nL395 replace “…temperature via relative…” with “…temperature, relative…”\nReplaced as suggested.\nL429 consider removing “, which have been missing so far” as this is redundant because\nit is clear from the previous sentences that there are no outlines for this year.\nRemoved as suggested.\nL430 consider removing “oriented on inventory availability and geodetic data” since this\nis redundant. It is already mentioned in the preceding sentences.\nWe agree that the information is already mentioned in the preceding sentences. We still\nwant to keep the statement to summarize the used data.\nL442 replace “had been” with “are”\nChanged.\nTable S2 From the text it sounds like this comparison is between the downscaled\nclimate data and AWS data only (e.g. river catchment data and firn core are not used). It\nwould be good to state this explicitly by modifying the caption to: “…compared to the\nAWS observations.”\nChanged as suggested, thank you.\nReferences\nBarcaza, G., Nussbaumer, S.U., Tapia, G., Valdés, J., García, J., Videla, Y., Albornoz, A.,\nand Arias, V. (2017): Glacier inventory and recent glacier variations in the Andes of Chile,\nSouth America. Ann. Glaciol. 58, 166–180, doi:10.1017/aog.2017.28\nBravo, C., Quincey, D. J., Ross, A. N., Rivera, A., Brock, B., Miles, E., & Silva, A. (2019): Air\nTemperature Characteristics, Distribution, and Impact on Modeled Ablation for the\nSouth Patagonia Icefield. Journal of Geophysical Research 124 (2): 907-925,\nhttps://doi.org/10.1029/2018JD028857\nBravo, C., Ross, A.N., Quincey, D.J., Cisternas, S., Rivera, A. (2022): Surface ablation and\nits drivers along a west–east transect of the Southern Patagonia Icefield. Journal of\nGlaciology 68 (268), 305–318, https://doi.org/10.1017/jog.2021.92.\nGacitúa, G., Schneider, C., Arigony, J., González, I., Jaña, R., and Casassa, G. (2021):\nFirst ice thickness measurements in Tierra del Fuego at Schiaparelli Glacier, Chile, Earth\nSyst. Sci. Data, 13, 231–236, https://doi.org/10.5194/essd-13-231-2021.\nHall, D. K. & Riggs, G. A. (2021): MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid.\n(MOD10A1, Version 61), [Data Set], NASA National Snow and Ice Data Center\nDistributed Active Archive Center, https://doi.org/10.5067/MODIS/MOD10A1.061.\nIPCC (2012): Glossary of terms. In: Managing the Risks of Extreme Events and Disasters\nto Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J.\nDokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and\nP.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental\nPanel on Climate Change (IPCC). Cambridge University Press, Cambridge, UK, and New\nYork, NY, USA, pp. 555-564.\nSauter, T., Arndt, A. & Schneider, C. (2020): COSIPY v1.3 – an open-source coupled\nsnowpack and ice surface energy and mass balance model. Geoscientific Model\nDevelopment 13, 5645–5662, https://doi.org/10.5194/gmd-13-5645-2020.\nTemme, F., Farías-Barahona, D., Seehaus, T., Jaña, R., Arigony-Neto, J., Gonzalez, I.,\nArndt, A., Sauter, T., Schneider, C., and Fürst, J. J. (2023): Strategies for regional modeling\nof surface mass balance at the Monte Sarmiento Massif, Tierra del Fuego, The\nCryosphere, 17, 2343–2365, https://doi.org/10.5194/tc-17-2343-2023.\nDear editor and referees,\nWe would like to thank you for the constructive review of our manuscript. We are\nconvinced that your suggestions have improved the readability and overall quality of the\nmanuscript.\nFor reviewers 1 and 3, the requested changes were mainly of editorial nature. They are\nfully implemented in the revised version of the manuscript. Reviewer 2 raised concerns\nnot on the manuscript but on terminology used in the rebuttal to the first review round.\nTo avoid ambiguities or misunderstanding, we decided to adapt the terminology to be\nclear and specific.\nPlease find our detailed reply to the individual comments below.\nKind regards,\nFranziska Temme,\nin the name of all co-authors\nPoint-by-point response to reviewer comments\nReviewer #1 (Remarks to the Author):\nThank you to the authors for answering and clarifying my concerns regarding their\nmanuscript. I understand and agree with the answers and changes introduced in the\nmanuscript.\nJust some (very) minor comments:\nWe would like to thank you for the constructive review of our manuscript. In the\nfollowing you find a point-by-point response to the raised comments. We are convinced\nthat our actions have improved the quality and readability of the manuscript. Referee\ncomments are reproduced in black font color. Our response and the undertaken actions\nare formulated in green font color, text that was adjusted in the manuscript is\nhighlighted in italic font.\nL49-50: However, stratospheric ozone depletion also forces storm-track poleward\ntrend. Recovery of the ozone is projected so this could counteract the poleward trend.\nDo the authors analyze this scenario? And how could this affect CDI mass balance?\nThank you for this question. The counteracting effect of ozone recovery is considered in\nthe cited publication (Goyal at el. 2021). They mention that ozone depletion is seen as\nthe main forcing mechanism for the southward shift in the past few decades and\ndiscuss the counteracting effect of ozone recovery. However, they find that, for high\nemission scenarios, the effect of greenhouse gases will dominate over the effect of\nozone recovery and cause a future southward shifting.\nIn general, a southward shift of the westerlies would cause an intensification of those\nover the CDI, potentially enhancing precipitation. For our study period we observe an\nincreasing trend in wind velocities and precipitation (see L137-138) that can be\nexplained by the shift in westerlies. However, the trend for precipitation is small and we\ndo not find a significant increase in snowfall amounts (see L229-230).\nL179 and L300-313: I suggest presenting the ELA results as m a.s.l. (I'm sorry I didn't\nnote this in the first version.)\nAdjusted as suggested, thank you.\nL188: delete space between 15 and %\nAccording to the International System of Units, a non-breaking space should be added\nbetween the number and the % symbol. We found a few occasions in the text, where the\nspace was missing so far and adjusted those in the revised version of the manuscript to\nensure consistency.\nL556: so, Which one is used in the bulk-approach applied here?\nThank you for this question. In this study, we apply Monin-Obukhov similarity theory, as\nnoted in Table S5. We added this information into the text:\n“The latter is applied in this study (Table S5).”\nAnswering to the authors, there are several energy balance studies for short-term in\nPatagonia linked to Japan’s research program on Patagonia. Most of them, were\npublished in the Bulletin of Glacier Research during the 80´s and 90´s.\nThank you for this hint. Despite an extensive search, the only publication we were able\nto access is Takeuchi et al. 1999, Global and Planetary Change. We incorporated this\npublication for completeness.\nReviewer #2 (Remarks to the Author):\nDear Editor,\nI have reviewed the authors' responses to my comments; however, I have not had the\nopportunity to thoroughly review the revised manuscript itself. Based on the responses\nprovided, I am generally satisfied and believe the authors have addressed my main\ncriticisms.\nWe would like to thank you for the constructive comments on our manuscript. In the\nfollowing you find a response to the raised comments. We are convinced that our\nactions have improved the quality and readability of the manuscript. Referee comments\nare reproduced in black font color. Our response and the undertaken actions are\nformulated in green font color, text that was adjusted in the manuscript is highlighted in\nitalic font.\nThat said, I would like to bring to your attention a few minor points from their responses\nthat may require further clarification:\nThe authors state: \"Taking only the land-terminating glaciers, the dynamic component is\nzero, and the climatic and geodetic mass balance are directly comparable.\" While this\nis true when considering glacier-wide (or region-wide) mass balance, it does not hold if\ndistributed specific mass balance (e.g., mass balance versus elevation) of individual\nglaciers is considered. Geodetic mass balance for any glacier (land-terminating or not)\nalways reflects a combination of surface mass balance (climatic) and ice flow\n(dynamic). This distinction was not fully addressed in the authors’ response, and I\nsuggest that this clarification should be explicitly incorporated into the manuscript to\nensure methodological accuracy.\nThe authors also mention: \"We are comparing the glacier-wide integrated mass balance\n(called specific mass balance) for each land-terminating glacier.\" However, glacier-wide\nmass balance is not the same as specific mass balance, and these terms should not be\nconflated. This mislabeling caused confusion in their responses and could lead to\nfurther misunderstandings in the manuscript. I recommend that the authors refer to the\nGlossary of Mass Balance (https://wgms.ch/downloads/Cogley_etal_2011.pdf) to\nensure that terminology is used correctly and consistently throughout the paper.\nFinally, the authors’ use of the term \"ice dynamics\" appears to describe glacier calving\nor frontal ablation. However, ice dynamics is often synonymous with ice flow, which\noccurs in all glaciers regardless of their terminus type (land or marine). To avoid\nconfusion, I suggest the authors revise this terminology and use more precise language\nwhen describing these processes (again, see the Glossary for guidance).\nI hope these observations are helpful in guiding the final revisions. Please let me know if\nany further input is required from my side.\nThank you for your comments. Regarding the terminology of “specific mass balance” we\nunderstand your concerns and excuse for the confusion. With the term “specific mass\nbalance” we intend to refer to the glacier-wide specific mass balance, where the\nstatement that ice-dynamically controlled losses are zero for land-terminating glaciers\nholds true. We agree that this is not true in a case where not the entire glacier area but\nonly a subsection is considered. Throughout the manuscript we mainly use the term\n“glacier-specific mass balance”, which is a widely used terminology when referring to\nthe specific mass balance of an entire glacier and should resolve this ambiguity. We\nadded “glacier-“ where it was missing so far (L627 & caption of figure 1) to ensure\nconsistency. Furthermore, we added the following sentence in L149: “Glacier-wide\nspecific mass balance is used for the comparison, in the following denoted as glacier-\nspecific mass balance.”\nRegarding the terminology of “frontal ablation” and “ice-dynamically controlled mass\nloss”, we understand your concerns. In the Introduction (L65-67) (and in the last,\nsummarizing paragraph of the Discussion), we describe that frontal ablation is a loss\nterm that is controlled by ice-dynamics through calving. To avoid confusion, we now use\nthe term “frontal ablation” throughout the results and discussion sections of the\nmanuscript.\nReviewer #3 (Remarks to the Author):\nDear authors,\nThe manuscript has been improved significantly through the review process and all my\nprevious comments and additional concerns have been addressed directly or indirectly\nthrough your response to the reviewers. The remaining comments I have are minor.\nKind regards,\nNicole Schaffer, PhD.\nWe would like to thank you for the constructive review of our manuscript. In the\nfollowing you find a point-by-point response to the raised comments. We are convinced\nthat our actions have improved the quality and readability of the manuscript. Referee\ncomments are reproduced in black font color. Our response and the undertaken actions\nare formulated in green font color, text that was adjusted in the manuscript is\nhighlighted in italic font.\nDetailed comments:\nL38-39 Suggestion to delete “…with glaciers descending down to sea level..” as this is\nredundant since it can be inferred from the previous sentence. I realize this was\nincluded to respond to a comment from reviewer 1 so if you decide to keep it for that\nreason that is ok. The modification to include “..inducing high mas input..” in response\nto reviewer 1 is a helpful addition but I would suggest replacing “at the top” with\nsomething more explicit such as “at the highest elevations”.\nThank you for this comment. We adjusted the sentence as suggested.\nL46-47 suggestion to modify this sentence to “..not only the formation of clouds…but\nalso the global ocean…”\nChanged as suggested, thank you.\nL78-79 The term “this way” is somewhat vague and informal. Suggestion to replace this\nwith “With this dataset, …”. Also consider replacing “given” with a more appropriate\nword such as “produced”.\nAdjusted as suggested, thank you.\nL272-278 The sentence starting on L272 and the rest of this paragraph is mostly\nduplicated in the new discussion paragraph on advancing glaciers. Given that this part\nof the paragraph is more suited for the discussion since it is an interpretation of the\nresults, I would suggest deleting this text from the results and merging it with the new\nparagraph in the discussion (see my comments further down for that paragraph).\nThank you for this comment. We moved the paragraph to the discussion.\nL313 change “extends generally” to “generally extends”\nChanged as suggested, thank you.\nL315 Replace the term “exposition” with a more suitable term. For example, “aspect”.\nAdjusted as suggested, thank you.\nL311-320 In the second sentence within this paragraph, the author highlights that MALT\nglaciers show more positive CMB. This prompts one to question whether all the\nadvancing glaciers are MALT glaciers? I would suggest adding a sentence staring on\nL315 (if it is true that they are all MALT, otherwise modify!) to answer this question and\naid in linking the sentence on MALT to the discussion on advancing glaciers.\nAdditionally, moving the last sentence to L317 would help with the readability and\ncohesive flow of ideas. Finally, I would suggest merging this paragraph with the text on\nL272-278 to reduce unnecessary repetition in the manuscript as follows:\n“….century. While these advancing glaciers are all MALT, they have medium to low\nfrontal ablation which, in addition to a thickening further upstream, suggest a primarily\nclimatic control. We ascribe these climatological favorable conditions to the glaciers’\nhypsometry and aspect. All four glaciers have their origin at the high-elevated central\nplateau of the CDI (above 2000 m) and steep topography resulting in high snowfall\namounts and above-average accumulation-area-ratios (between 0.72 and 0.88\ncompared to the CDI average of 0.61). Glaciers with high accumulation-area-ratio are\noften less sensitive to changes in ELA and, thus, warming due to the small and steep\nablation area15.Southward exposures of Garibaldi, Guilcher Oeste and Guilcher Este\nglaciers further reduce surface ablation (Fig. S8a). Altogether, these characteristics\nultimately lead to high snowfall amounts together with reduced surface ablation (Fig.\n2c, Fig. S9d), favoring mass gain.”\nThank you for this comment and the detailed revision of the paragraph. We adjusted the\nparagraph following your suggestions. The advancing glaciers are all marine\nterminating. We added this information.\nL311-320 (b) Does the strong precipitation gradient across the CDI have an impact on\nthe contrasting glacier behaviour? If you consider the answer relevant and worth\nmentioning, please add a sentence to this paragraph.\nThank you for this question. We do not see the precipitation gradient as a relevant\nforcing for the contrasting glacier behavior. The reason is that we see retreating glaciers\non the west and east part of the CDI, thus there is no zonal gradient in the\nretreating/advancing behavior. The advancing glaciers are all located in the central area\nand are also surrounded by several retreating glaciers.\nL365 suggestion to replace “…ablation at the CDI…is in a similar…” with “ …ablation for\nthe CDI…is a similar…”\nAdjusted as suggested, thank you.\nL377 replace “…study are..” with “…study is…”\nAdjusted to “A major limitation of this study is the scarcity of in-situ observations, …”\nL379 replace “verifiably” with “verifiable”\nChanged as suggested, thank you.\nL380 suggestion to replace “…should be handled with certain care..” to “…should be\ninterpreted with care…”\nAdjusted as suggested, thank you.\nL443 Consider changing “Required variables comprise…” to “Required variables for this\nstudy are …”\nAdjusted as suggested, thank you.\nL445-447 consider changing sentence to “For downscaling of precipitation (53.75-\n55.50°S, 74.50-73.25°W) information about air temperature, relative humidity, wind\nvectors and geopotential height between 850 and 500 hPa is needed.” The term “we\nneed” is too informal for a publication in my opinion.\nChanged as suggested, thank you.\nL487-488 Reading the phrase “….where the cumulative distribution function of the\nmodel is transferred to the cumulative distribution function of the observation” could be\ninterpreted to mean that the cumulative distribution of the observation data is corrected\nby aligning it with the cumulative distribution of the model output. From my limited\nunderstanding of quantile mapping bias correction, I understand that the correction is\nthe other way around. The quantile distribution of the model outputs is shifted to align\nwith the quantile distribution of the observed data. Consider modifying the sentence to\n“….where the cumulative distribution function of the model is shifted to align with the\ncumulative distribution function of the observations”\nThank you for this comment. We adjusted the section to “… where the cumulative\ndistribution function of the model is adjusted to align with the cumulative distribution\nfunction of the observation”\nTable S2 The RMSE for the station Rio Azorpado is quite low (0.33). Do you know why this\nmight be? If relevant, include the explanation in the manuscript.\nWe do not have a clear explanation for the low correlation for precipitation at Río\nAzorpado. We screened the timeseries for outliers or periods of consecutive low or high\nmeasurements and found many periods of corrupt values that we deleted, but it is\npossible that this did not resolve all issues. Therefore, issues with the sensor would be\nthe most obvious explanation."}, "author_response": "Dear editor and referees,\nWe would like to thank you very much for the detailed and constructive comments to our\nmanuscript. We are convinced that the revisions have improved the overall quality of our\nmanuscript. Before we reply in detail to the individual comments, we would like to\nmention the most important changes implemented in the manuscript:\n1) The introduction was revised following the suggestions of the reviewers (mainly\nreviewer 3).\n2) We revised and streamlined the methods section and provide now more details\nespecially on the model calibration and validation and the uncertainty analysis. In this\nway, we hope to clarify the distinction between the actual calibration targets on regional\nscale and the glacier-specific observations used for uncertainty metrics.\n3) The uncertainty analysis of the frontal ablation estimation has been extended and\ncomprises now the measurement error of the (specific) geodetic mass balance. We\nfollow a statistical uncertainty propagation. Uncertainties have been updated\nthroughout the manuscript.\n4) We extended the modelling period by one year, now covering 2000-2023. Changes in\nnumbers and trends are minor, corroborating the robustness of our CMB results.\nKind regards,\nFranziska Temme, in the name of all co-authors\nPoint-by-point response to reviewer comments\nReviewer #1 (Remarks to the Author):\nIn this work, Temme and collaborators present a climatic mass balance forced by\nreanalysis data validated with in situ observations. Frontal ablation is also estimated.\nThe methods are standard for this kind of research. The novelty is related to the study\narea, as the modelling is applied to the glaciers of the Cordillera Darwin Icefield (CDI) in\nsouthernmost South America, an area poorly studied. The main conclusion is\natmospheric forcing is the main driver of the ablation in the region. The work is well-\nwritten and easy to follow and the figures are mostly clear, but I think some clarifications\nneed to be made before publication. I hope this review helps the authors improve the\nmanuscript.\nWe would like to thank you very much for the detailed and constructive review of our\nmanuscript. In the following, you find our point-by-point list of answers to the raised\ncomments. We are convinced that our actions have significantly improved the quality of\nthe manuscript. We sincerely hope you find our response satisfactory, and we have been\nable to clarify the raised points. Referee comments are reproduced in black font color.\nOur response and the undertaken actions are formulated in green font color, text that\nwas adjusted/added in the manuscript is highlighted in italic font.\nI suggest a small change in the title, including “ablation” instead of “melt”. Results of the\nmanuscript show that melt is the main component in the total ablation processes, i.e.\nhigher percentage (74%) compared to frontal ablation (26%). Melt by definition depends\non the atmosphere conditions ( could be also by oceanic or lake conditions but this is\nnot directly quantified here). If I understand, I think the title looks to remark that the\nclimate or atmosphere drives the “ablation” as stated in lines 260-261.\nThank you for this comment. We agree and changed the word ‘melt’ to ‘ablation’.\nThe sentence in L275 and repeated in L347 is a bit confusing. How the mass loss is\ncontrolled by atmospheric conditions if the CMB is positive (0.02 m w.e. yr-1) or close to\nbalance (L332)? Results show climatic ablation is quite larger than frontal ablation\n(L275-277) and this is forced by the atmosphere, I understand this, but in terms of mass\nbalance, the overall CMB is still positive for the period meaning that CDI has been\nclimatically balanced in the recent two decades (L380). In consequence, overall no\nmass loss forced by atmosphere conditions between 2000-2022. Or do you refer to the\nlast six years of CMB modelling? or just to land-terminating glaciers that show negative\nspecific CMB (L145-146)? Please clarify this.\nThank you for pointing this out. We are referring to the ablation being mainly controlled\nby atmospheric conditions (instead of dynamic). We exchanged ‘mass loss’ with\n‘ablation’ in both mentioned sentences.\nNo justification for the period. For instance, why 22 years and not 30 years? In the title,\nthe word “Climate” is used, and by definition, the climate is a 30-year period (WMO). If\nthe 22-year period is well justified, maybe change “Climate´s” to “Atmosphere´s”.\nSee response to your comment on L107 regarding the justification of the period.\nWe would like to stick to this terminology in the title. Although the WMO defines 30 years\nas the standard climate period, it is not uncommon to also use shorter periods (from 20\nyears) in this context. The IPCC Glossary explicitly names periods of 20 years as\napplicable (IPCC 2012):\n”Climate in a narrow sense is usually defined as the average weather, or more rigorously,\nas the statistical description in terms of the mean and variability of relevant quantities\nover a period of time ranging from months to thousands or millions of years. The\nclassical period for averaging these variables is 30 years, as defined by the World\nMeteorological Organization. (…) In various chapters in this report diherent averaging\nperiods, such as a period of 20 years, are also used.”\nAs usual in glacier modelling-approach investigations some choices need to be better\njustified, for instance, the use of a constant air temperature lapse rate over a spatial\nvariable lapse rate. Also, other sources of uncertainties are not (at least) mentioned in\nthe manuscript. For instance, no mention of debris cover areas. Is this area important to\nquantify melt rates at CDI?\nThank you for this comment. In the sensitivity runs, we tested the application of a zonal\ngradient in the temperature lapse rate (added in the ‘Model calibration and validation’\nsection). Such gradient diherences were reported by Bravo et al. (2019), who found\nsteeper lapse rates east of the Andes as compared to west. Comparison with the\ngeodetic mass balances (for land-terminating glaciers) showed, however, no superior\nbehavior in the calibration.\nDebris-covered glacier areas are not common in the region. The Chilean Glacier\nInventory (Barcaza et al., 2017) defines only around 1 % of the glacier area as debris\ncovered. Therefore, we are convinced that debris-cover is negligible in this study.\nMinor comments\nL 38-39: “The large altitudinal range….” I don´t understand this sentence. How do the\nlocation and the climatic conditions control the altitudinal range of the CDI? Or do you\nrefer to the climate conditions extreme gradients? Please clarify.\nThank you for this question. We are referring to the altitudinal range of the glaciers,\ndescending down to sea level. This is possible due to the extreme climatic conditions\nproducing high accumulation amounts at the top. We reformulated the sentence to\nmake the statement clearer.\n“This large altitudinal range, with glaciers descending down to sea level, is possible due\nto the extreme climatic conditions inducing high mass input at the top.”\nL59-60: Reference 17 includes a frontal reconstruction of Marinelli Glacier back to 1910.\nWe added the reference, thank you.\nL63: I suggest including the area of the marine-terminating and the lake-terminating\nglaciers separately.\nWe included the information as suggested:\n“Around half of the CDI area consists of marine- or lake-terminating (MALT) glaciers\n(35% and 13%, respectively).”\nL107: Why this period?\nWe rely on 2000 (-1 year as spin-up) as start year because of data availability. Several\ndatasets that we use are dated at ~2000. Those are the glacier inventory (Barcaza et al.\n2017), the surface topography from SRTM and the geodetic mass balance (with elevation\nchanges calculated 2000-2013). The end date is chosen as close to present day as\npossible (when we started working on the study). To model full mass balance years, we\noriented the simulation times on the hydrological year. We have, however, extended the\nclimate data and the COSIPY simulation to 2023 now.\nL110: Any insight on why the correlation with Isla Hoste AWS is low?\nWe assume that you are referring to the precipitation at AWS Hoste, since the\ncorrelation for the other variables is high. Looking at the measurements again, we\nidentify issues with the precipitation sensor starting after ~1 year of measurements. We\nshortened the timeseries accordingly and updated the statistics in table S2. The\nupdated correlation is 0.72.\nL114-115: Ok, but you also show individual glacier CMB results, for instance in Fig. 1. Are\nthese values, especially the accumulation, reliable?\nSee response to your comment on L145-146.\nL123-124: I understand what you mention here, and agree, but be aware that relative\nhumidity is an indicator of how close to saturation the atmosphere is and depends on\nthe air temperature.\nThank you for that comment. We reformulated the sentence to make the statement\nclearer:\n“While air temperature at sea level exhibits no clear west-east gradient, annual average\nrelative humidity shows a drying towards the east (Fig. S3b).”\nL145-146: Similar to a previous comment, how reliable is the CMB estimation for\nindividual glaciers? I agree that the regional CMB is a good approach for CDI considering\nthe uncertainties, lack of measurements and diherences in the accumulation rate\nreported in L114 but, along the manuscript, CMB of individual glaciers is used for\ncomparisons.\nThank you for this question. Admittedly, we do report CMB values of individual glacier\ncatchments but we do so including the specific CMB uncertainty, which is quantified in\nan objective and systematic way. With this uncertainty assessment, we think it is\nwarranted to forward values for individual glacier catchments. Let me explain the\nuncertainty assessment:\nWe are comparing the glacier-wide integrated mass balance (specific mass balance) for\neach land-terminating glacier (> 3 km2). As land-terminating glaciers have no\ndynamically controlled losses, the two datasets are directly comparable. The glacier-\nspecific geodetic information has not been used for model calibration (only the regional\naverage has been used), and is, thus, an independent validation dataset. We compare\nthe (specific) geodetic and climatic mass balance per glacier catchment and calculate\nthe root mean square error (RMSE ±0.62 m w.e. yr-1). This error presents the\naccuracy/uncertainty of the climatic mass balance on a glacier-specific basis. We\nreformulated the ‘Model calibration and validation’ section to increase clarity (former\nL553-571), especially the following sentence:\n“Model performance is quantified by the root mean square error between the glacier-\nspecific climatic and geodetic mass balance for these glaciers, resulting in a model error\nof ±0.62 m w.e. yr-1.”\nL152-153: I suggest adding a Figure (could be in Supplementary Material) to explore the\ndiherences in the CMB between land and marine-lacustrine glaciers.\nThank you for this comment. The diherence can be seen in Fig. 1, where both the CMB\nand the termination type of the glaciers are included. We, however, agree that the\ninformation is hard to extract from this figure. Therefore, we added a figure with the\naverage annual CMB for each glacier, color-coding the termination type, to the\nsupplement (Fig. S11).\nL176: Change Juli by July.\nChanged.\nL297-308: Why present ELA results in the Discussion section and not in the Results\nsections?\nThank you for this comment. At this point, we compare the simulated ELA results with\nresults from previous studies, which we want to keep in the Discussion section.\nHowever, we moved the first two sentences (L296-298), where we only present results,\nto the results section.\nL317-321: Any clue for this behaviour? Southern Annular Mode or another mode of\ninterannual or interdecadal variability?\nThank you for this comment. The Southern Annular Mode is claimed to be the main\nmode of climate variability over southern Patagonia. We tested correlations between the\nSAM index and the climatic mass balance, snowfall and melt energy. None of these\nvariables indicates a relation between SAM and the mass/energy balance of the CDI.\nWe clearly see that the more positive phase around 2009 - 2015 is accompanied by higher\nsnowfall amounts and less surface melt compared to the years before and after (Fig.\nS10a). Climate data shows slightly lower air temperatures and years with increased\nprecipitation amounts. However, we do not have an explanation for this variability at the\nmoment. It would certainly be an interesting future study!\nWe added the following sentences:\n“Those more positive or negative periods are strongly linked to snowfall amounts and\nsurface melt (Fig. S10a). A distinct relation to the Southern Annular Mode, which is\nproposed as the main mode of climate variability in Tierra del Fuego33, cannot reliably be\nconfirmed from our results. This finding is in agreement with a recent study focused on\nthe Patagonian Icefields44.”\nL315-328: Missing references about glacier energy balance in Patagonian glaciers that\ncould be useful to add to the discussion.\nThank you for this comment. We already give several references about glacier energy\nbalance of Patagonian glaciers in this section (Temme et al. 2023, Weidemann et al.\n2020, Weidemann et al. 2018, Schaefer et al. 2020, Minowa et al. 2023, Schneider et al.\n2007). We now added the publication of Bravo et al. (2022). These are all publications\naddressing the energy balance of Patagonian glaciers that we are aware of. If you know\nother essential studies that we overlooked for this region, we would ask you to specify\nthose so that we can include them. Thank you!\nL329: Also missing references about surface melt trends and projections in Patagonian\nglaciers. I suggest comparing your findings with previous works at regional scale.\nConsidering the uncertainties that are mentioned in the paper I suggest keeping a\nregional point of view for comparisons. Some comparison by glacier is fine, but the\napproach here is regional.\nThank you for this comment. We extended the discussion on surface mass balance and\nmelt trends and projections for Patagonia:\n“A trend analysis over the study period clearly demonstrates an extremely likely increase\nin surface melt, which is in agreement with simulations of surface melt for the Northern\nand Southern Patagonian Icefield estimating a positive trend of +0.30 m w.e. yr-1 per\ndecade (1975-2005)37. This rise in surface melt is the main driver of a likely trend towards\nmore negative mass balance in the CDI. Congruently, Bravo et al.37 present negative\ntrends in the surface mass balance of the Northern and Southern Patagonian Icefield\n(1975-2005). However, contrary results are presented in ref. 45,43,46. Despite the likely\npositive trend in precipitation amounts in the CDI, we do not find an increase in snowfall\namounts. In general, glaciers in the CDI that are covering a lower elevation range (<\n600 m) already experience more pronounced mass losses with an average CMB trend of\n-0.43 m w.e. yr-1 per decade (extremely likely). At Perito Moreno Glacier some 400 km\nnorth of the CDI, Minowa et al.41 found a virtually certain decreasing trend in the surface\nmass balance over the ablation zone of -0.90 ±0.3 m w.e. yr-1 per decade (1996-2020).\nThis decreasing trend is in general agreement with our findings for areas at similar\naltitudes in the CDI (-0.50 m w.e. yr-1 per decade). If the recent trends continue, the CDI\nwill get further out of balance and glaciers will trace a path of accelerating mass loss as\nalready indicated by the current trend in the CMB (Fig. 3c). Projections for the Northern\nand Southern Patagonian Icefield predict just such a pathway of enhanced surface melt\ncausing decreasing surface mass balance until 205037.”\nL380-381: This sentence seems more appropriate for the climate or atmosphere forcing\non mass balance.\nThank you.\nL446: Is there any reference for this velocity threshold?\nThank you for this question. In order to enable a direct comparison between the specific\ngeodetic and climatic mass balance, we need to identify all glaciers with no (or\nnegligible) frontal ablation. The Chilean Glacier Inventory (Barcaza et al. 2017), which is\nused in this study, includes a classification of the termination type, but has a large share\nof lake- and marine-terminating glaciers. Especially for the lake-terminating glaciers, we\n(visually) identified many cases where frontal ablation is negligible due to a small calving\nfront and low ice velocity.\nTherefore, we had to revise the classification for our purposes. The goal was to find an\nobjective classification to distinguish those glaciers with significant frontal losses from\nthose with no or negligible frontal losses. Ice velocity is suitable because glaciers with\nnegligible ice flow at the front also have negligible calving. The classification is a\ncompromise between on the one hand excluding glaciers from the calibration/validation\ndataset with significant calving losses to avoid biased results, and on the other hand\nguaranteeing a calibration/validation dataset that is large enough. With our approach,\nwe achieve a calibration/validation dataset that covers ~37% of the entire CDI.\nTo guarantee that glaciers that had been defined as land terminating in the Chilean\nInventory will keep this classification, the threshold velocity of 60 m yr-1 (there was a\ntypo in the text) was suitable.\nA rough assessment of the calving fluxes of newly defined land-terminating glaciers\n(=glaciers terminating in lakes or fjords but defined as land-terminating in our study)\nshows that the specific calving losses are mostly < 0.1 m w.e. yr-1.\nReviewer #2 (Remarks to the Author):\nThe study models the surface mass balance of all glaciers in the Cordillera Darwin\nIcefield (CDI) in Tierra del Fuego from 2000 to 2019, utilizing the open-source surface\nenergy balance model COSIPY (Sauter et al., 2020), which is forced by downscaled ERA5\ndata. The model parameters are primarily calibrated with in-situ mass balance\nobservations from one or a few glaciers in the region. Notably, this calibration process is\nbased on the authors’ previously published work (Temme et al., 2023). The diherence\nbetween the geodetic mass balance and the simulated surface mass balance for lake-\nand ocean-terminating glaciers is used to estimate mass loss due to frontal ablation.\nOverall, the paper is well-written, but there are areas where additional methodological\ndetail would enhance clarity (elaborated further in my specific comments). The authors\nhighlight the novelty of the study as \"the first simulation of the climatic energy and mass\nbalance of glaciers in this region.\" However, given that the same first author has\npreviously applied the COSIPY model (developed by Sauter et al., 2020) to a subset of\nglaciers in the region (Temme et al., 2023), this work may be better framed as an\nextension of that earlier study, expanding the model's application to a broader set of\nglaciers.\nThe method used to estimate frontal ablation raises some concerns, particularly\nregarding the quantification of uncertainties (detailed in my specific comments). A more\ncomprehensive uncertainty analysis would strengthen the credibility of the results,\nparticularly in relation to frontal ablation estimates.\nIn summary, while the study provides valuable insights into the region, the novelty of the\ncontribution could be more clearly articulated. Additionally, addressing some critical\nmethodological elements, such as a more rigorous uncertainty analysis, would\nsignificantly enhance the robustness of the results.\nWe would like to thank you very much for the detailed and constructive review of our\nmanuscript. In the following, you find our point-by-point list of answers to the raised\ncomments. We are convinced that our actions have significantly improved the quality of\nthe manuscript. We sincerely hope you find our response satisfactory, and we have been\nable to overcome your methodological concerns. Referee comments are reproduced in\nblack font color. Our response and the undertaken actions are formulated in green font\ncolor, text that was adjusted/added in the manuscript is highlighted in italic font.\nSpecific comments:\nAbstract: The authors should include the period of the simulations in the abstract. It\ntook me some time to determine that the simulations cover 2000–2019, and having this\ninformation up front would clarify the scope of the study.\nThank you for this comment. We added the simulation period (2000-2023).\nLine 77-78: “...melt, which is strongly linked to air temperature”\nOne of the references cited here used a positive-degree-day (PDD) model to simulate\nmelt, so linking melt to temperature is an inherent assumption of the model.\nThank you for this comment. Based on another reviewer’s comment, we removed this\nsentence. It is giving too much detail for the Introduction and those points are better\nbeing discussed in the Discussion section. For the exact reformulation, see next\ncomment.\nLine 78-79: “Despite these local ehorts to determine the mass balance of individual\nglaciers, a systematic approach for a CDI-wide estimate of the CMB is to this day\nmissing.”\nHowever, Temme et al. (2023) (reference #20) addresses not just individual glacier\nmodeling but also regional-scale modeling. The authors may want to reconsider this\nstatement, as it somewhat underrepresents the existing work in this area.\nThank you for this comment. We agree that the formulation was misleading. We revised\nthe entire introduction based on another reviewer’s comments. The sentence was\nreformulated to:\n“The climatic mass balance (CMB) has been studied in the Cordon Martial (east of the\nstudy region, located in Argentina)19 and in the Mount Sarmiento Massif20,21(western CDI),\nbut these local e`orts are insu`icient and a systematic CDI-wide estimate of the CMB is\nneeded.”\nLine 80: “This lack of knowledge can be addressed with a well-informed modelling\nproduct of CMB.”\nThe term “well-informed modeling product of CMB” is unclear. It would improve clarity\nto specify what is meant by this term and what type of model product the authors are\nreferring to.\nThank you for this comment. The statement was removed in the course of the revision of\nthe introduction section based on another reviewer’s comments.\nLine 82-83: “Thus, with the climatic loss term available, the mass budget of the CDI\nglaciers can successfully be closed and give the dynamic loss as residual.”\nThere seems to be a disconnect between this statement and the preceding one. The\ntotal mass loss is derived from geodetic estimates, not the climatic loss term. I suggest\nrephrasing this to clarify that the dynamic loss is inferred from the residual of the\nmodeled climatic mass balance (CMB) and geodetic mass balance. Additionally, errors\nin both the CMB and geodetic estimates could be significant, making it challenging to\nassume that the residual solely represents dynamic loss.\nWe added a more detailed explanation in the text, saying:\n“Thus, with the climatic mass balance term being quantified, we assume that the\nresidual with respect to the geodetic mass budget is primarily explained by frontal\nablation – an ice-dynamically controlled loss term.”\nLine 94: “In this way, an unprecedented attribution of the observed mass loss to climatic\nand ice-dynamic forcing becomes possible.”\nWhile this is an important step forward, the authors should also account for the\nuncertainty in the modeled CMB and geodetic estimates. Without addressing these\nuncertainties, the attribution may not be as straightforward as suggested here. For\ninstance, Hugonnet et al. (2021) point out that the accuracy of geodetic mass balance\nestimates can decline when moving from multi-annual to annual timescales.\nWe refined and added more details on the uncertainty analysis of the frontal ablation in\nthe Data & Methods section on ‘Frontal ablation’. See also response to your comment on\nL577-578.\nLine 96-97: “The energy and mass balance will be examined using the physically-based\nCOupled Snowpack and Ice surface energy and mass balance model in PYthon\n(COSIPY).”\nIt would be helpful to explain why COSIPY was chosen for this study. Temme et al. (2023)\ncompared COSIPY with simpler models, such as PDD approaches, and noted that some\nof the model parameters, like those in the albedo parameterization, still require\ncalibration with mass balance observations. If the model is calibrated with geodetic\nmass balance, how can it provide an independent estimate of the ice-dynamic\ncomponent? If the in-situ mass balance data from one or a few glaciers is used for\ncalibration, how do the authors address the potential issue of limited parameter\ntransferability across the CDI?\nThank you for these questions.\nFor model calibration we use the region-wide average geodetic mass balance of all land-\nterminating glaciers (> 3km2) (= -0.27 m w.e./yr). By taking the land-terminating glaciers\nonly, the dynamic component is zero and the climatic and geodetic mass balance are\ndirectly comparable. Temme et al. (2023) conclude that calibrating against regional\ngeodetic observations is the best strategy to achieve realistic regional simulations of\nclimatic/surface mass balance, and to address the limited parameter transferability. We\nfollow this strategy, and we achieve a good agreement between the geodetic (-\n0.27 m w.e./yr) and climatic mass balance (-0.23 m w.e./yr), confirming the applicability\non the CDI.\nFor validation of the climatic mass balance, we again stick to the land-terminating\nglaciers, preventing a contribution of dynamic losses. However, now we compare the\n(specific) geodetic and climatic mass balance per glacier catchment (instead of the\nregional average taken for calibration), and calculate the root mean square error (RMSE\n±0.62 m w.e. yr-1). This error presents the accuracy/uncertainty of the climatic mass\nbalance on a glacier-specific basis. In-situ ablation observations from Schiaparelli and\nMartial Este Glacier are used for additional validation information.\nWe chose the COSIPY model since its application has been proven to be successful in\nthe area before (Temme et al. 2023) and we focus not only on the climatic mass balance\nbut also on the energy balance. Less complex models (positive-degree-day or\nsimplified-energy-balance model) would not have enabled a detailed analysis of the CDI\nglaciers’ energy balance.\nLine 422: “...since comparison with the Randolph Glacier Inventory (V6) has revealed\nstrong weaknesses of the latter for the southern Andes.”\nThe term “weaknesses” seems too vague and possibly unsuitable here. It would be more\ninformative to specify what shortcomings of the Randolph Glacier Inventory were\nidentified in the region. Does it poorly represent glacier outlines in this area?\nThank you. We reformulated the sentence for more clarity:\n“Glacier outlines are taken from the DGA glacier inventory 55,56 since the Randolph\nGlacier Inventory (V6) has revealed poor representation of outlines for the southern\nAndes, especially for smaller glaciers58.”\nLine 428-430: “Since elevation changes cover the period 2000 to 2013, we manually\nproduced outlines for 2013, which have been missing so far. Thus, inventories available\nin this study cover years 2000, 2013 and 2019 oriented on inventory availability and\ngeodetic data.”\nThe phrase “oriented on inventory availability” is unclear. I suggest rewording for clarity.\nAlso, more detail is needed on how the 2013 outlines were manually produced, as this is\na crucial methodological step.\nThank you for this comment. The outlines for 2013 were produced using satellite images\nfrom late summer 2013 and 2014, and manually adjusting the outlines to the 2013\nglacier extent. Satellite images used are Landsat 7 and 8 (March 2013) as well as ASTER\n(Advanced Spaceborne Thermal Emission and Reflection Radiometer) (January to March\n2013 and 2014).\nWe reformulated the section to: “Since elevation changes cover the period 2000 to 2013,\nwe manually produced outlines for 2013. Therefore, we used late-summer images from\nLandsat 7 and 8 (2013) and ASTER (Advanced Spaceborne Thermal Emission and\nReflection Radiometer) (2013 and 2014) and manually adjusted the outlines to the\ncurrent glacier extent. Thus, inventories available in this study cover years 2000, 2013\nand 2019.”\nLine 431-441: What is the final output of this method? Is it glacier-wide geodetic mass\nchanges over the entire period? Please clarify the time period and spatial scale covered\nby these mass change estimates.\nThe details on the processing and output of the method are given in (former) L533-552,\nwhile in this section only the data itself is described. To highlight the time period more\nclearly, we added it in (former) L 552: “The mean regional observation period of the\nelevation change rate measurement is 12.97 years (2000-2013).”\nLine 464: Why was a radiation model used instead of directly employing incoming solar\nradiation from ERA5? Have you evaluated ERA5’s radiation data for this region, and if so,\nwhy was it deemed unsuitable for glacier-scale modeling? Additionally, if you use\ncloudiness data from ERA5 for the radiation model, how reliable is this parameter, given\nthat ERA5 cloud data may be less accurate than its radiation estimates?\nThank you for this question. The coarse resolution of ERA5 data does not resolve the\nlocal topography, and is thus not directly applicable for our high-resolution (200x200m)\nstudy. A topographic correction would have been required. The applied radiation model\nruns on the target resolution and, thus, the topography is well resolved, incorporating\ncorrections for slope and aspect of the topography as well as topographic shading.\nIn our study, we follow in general the approach and setup of Temme et al. (2023) in the\nMount Sarmiento Massif, where COSIPY was carefully calibrated. In this study, the same\nradiation model was employed. To ensure transferability, the methodology must remain\nconsistent.\nThe performance of the modelled radiation is validated with available AWS\nmeasurements (Table S2).\nLine 481: “...which is obtained by removing the orographic component from the ERA5\nprecipitation.”\nDoes ERA5 provide an orographic component of precipitation? Based on Hersbach et al.\n(2020), ERA5 supplies large-scale and convective precipitation, but not explicitly an\norographic component. Please clarify this point, as convective precipitation is not\nsynonymous with orographic precipitation.\nThank you for this question. The orographic component of ERA5 is calculated by running\nthe orographic precipitation model on the ERA5 elevation model. This ERA5 orographic\nprecipitation is subtracted from the ERA5 total precipitation, giving the large-scale\nprecipitation without an orographic component. We reformulated the section\naccordingly:\n“The total precipitation is calculated by adding the orographic precipitation calculated in\nthe model to the large-scale precipitation. The large-scale precipitation is obtained by\nremoving the orographic component, calculated by running the orographic precipitation\nmodel on the ERA5 topography, from the ERA5 total precipitation.”\nLine 523: “Albedo values are differentiated between snow, firn and ice surfaces. The\ndecay of surface albedo due to snow aging is parameterized following the scheme of\nOerlemans and Knap.”\nGiven the critical role of albedo in surface energy balance (SEB) modeling, have you\nevaluated the modeled albedo against observations from your study area? If in-situ\nalbedo data is unavailable, MODIS-derived albedo could be a useful comparison.\nWithout any evaluation, it’s unclear how reliable the albedo model is for this region, and\nits validation elsewhere (e.g., in the European Alps) may not be suhicient due to spatial\nvariability in albedo characteristics.\nThank you for this comment. Unfortunately, there are no in-situ observations of albedo\navailable in the Cordillera Darwin to our knowledge. The albedo scheme of Oerlemans\nand Knap was applied and validated, however, at the Southern Patagonian Icefield\nbased on satellite observations (Bravo et al. 2022).\nFollowing your suggestion, we extracted daily values of surface albedo of the\nMODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 61 dataset (Hall and\nRiggs 2021) for the period 2000-2022. We use the \"Snow_Albedo_Daily_Tile\" band\n(https://nsidc.org/data/mod10a1/versions/61#anchor-documentation) provided by the\nNational Snow and Ice Data Center (NSIDC). As anticipated, the spatial and temporal\ncoverage over the CDI is very low due to persistent cloud coverage of the majority of\nglacierized areas. Using MODIS data directly as an input to the model would thus not be\nfeasible. Instead, we decided to derive seasonal-average-tiles for winter (JJA) and\nsummer (DFJ) (see figures below). Also in those fields, we observe incomplete coverage\nand many pixels with few observations. Furthermore, we do not see a clear elevation\ndependent albedo as we would have expected it. At several points, neighboring pixels\nshow extreme diherences.\nEven in winter (JJA), when snowfall is extremely frequent, many pixels show albedo\nvalues around 40-50% in the central plateau (>1500 m a.s.l.), as can be seen for the\nexample year 2020 below (the year with the best coverage). A possible explanation for\nthese inconsistencies could be a misclassification of pixels, indicating clear sky\nconditions while clouds are still present over the ice surface. We strongly doubt these\nvalues.\nIn summer (DJF), the largest part of the CDI has no albedo observations which we relate\nto cloud coverage and/or misclassifications of the albedo product over the snow-\ncovered areas (see example from year 2011/12 below).\nDue to these complications, we unfortunately don’t see a way to make use of the\nMODIS-derived albedo for our study site.\nThe albedo scheme that we apply over the CDI was part of the model calibration in the\nMount Sarmiento Massif in the western part of the CDI (Temme et al. 2023). Thus, the\nfeasibility of the ice and firn albedo is given.\nLine 526: “correction using the Richardson-Number or the Monin-Obukhov similarity\ntheory.”\nWhich approach was ultimately used? Further, how were roughness lengths\ndetermined? Have you compared your modeled turbulent heat fluxes with\nmeasurements from glacier sites in your region to evaluate performance?\nThank you for these questions. The model set-up is summarized in Table S5 (see former\nL 529). Roughness lengths were taken from Temme et al. 2023, where the ice roughness\nlength was calibrated in the Mount Sarmiento Massif (western CDI).\nUnfortunately, there are no measurements of turbulent heat fluxes available in the\nCordillera Darwin. A direct comparison is, thus, not possible.\nLine 529: “was positively evaluated”\nThis phrase is unclear. Could you elaborate on what is meant by “positively evaluated” in\nthis context?\nThank you for the question. The model evaluation and comparison with three less\ncomplex surface mass balance models showed an overall good performance of COSIPY.\nDespite being more challenging to calibrate, results of COSIPY agreed well with the\nother models and the observations of glacier-specific geodetic mass balance and\nablation stakes used for validation (see former L531-532). Accordingly, Temme et al.\n(2023) show that the COSIPY model can be applied in the Monte Sarmiento Massif with\nsimilar performance to less complex models.\nLine 532: “COSIPY results agreed well with the other models as well as with\nobservations of ablation stakes and geodetic mass balance.”\nWhile this is a useful finding, it would be important to specify which parameters in\nCOSIPY were calibrated and how this calibration was performed. As noted earlier,\ncalibration with geodetic mass balance or in-situ data has implications for the\ninterpretation of the results and the separation of the climatic and dynamic components\nof mass balance.\nThank you for the question. The parameters calibrated in COSIPY in Temme et al. 2023\nare listed in Table 1 of that paper: albedo of ice, albedo of firn, and roughness length of\nice. In that paper, also the calibration strategy is explained in more detail.\nIn short, climatic mass balance was calibrated against the region-wide average geodetic\nmass balance of the land-terminating glaciers (same approach as for this study). Taking\nonly the land-terminating glaciers, the dynamic component is zero and the climatic and\ngeodetic mass balance are directly comparable.\nIn this study, a full calibration is not feasible due to the size of the domain. Instead,\nsensitivity runs are used for optimization of the climatic input data (see next comment).\nLine 559: “Sensitivity runs are applied for further optimization.”\nPlease clarify what parameters or inputs were varied in the sensitivity runs. Were\ndiherent datasets or methods used for calibration, or were the model parameters\nadjusted? Additionally, it is crucial to provide a breakdown of the uncertainties that\narise from your modeling approach.\nThank you for this question. COSIPY model parameters are taken from the Mount\nSarmiento Massif. In the 5 sensitivity runs, we varied the atmospheric input fields to\naddress the challenge for extrapolating from the local (AWS) scale to the regional scale.\nThe gradients across the cordillera are strong, requiring the testing of diherent\ninterpolation methods. Tests include variations in the interpolation of the relative\nhumidity and wind velocity fields as well as the application of a gradient in the\ntemperature lapse rate (based on Bravo et al. 2019, suggesting steeper gradients east of\nthe Andes compared to west). The target is the region-wide average geodetic mass\nbalance for the land terminating glaciers (= -0.27 m w.e./yr) that was met well by the\nchosen, presented run (-0.23 m w.e./yr). The sensitivity runs covered a spread between\n+0.51 and -1.58 m w.e./yr. We added this information into the text:\n“Sensitivity runs are applied for further optimization, where the methods for the\ngeneration of the atmospheric input fields (relative humidity, wind velocity, air\ntemperature) are varied, addressing the challenge to realistically reproduce the zonal\nclimatic gradients.”\nThe uncertainty of the modelled climatic mass balance is calculated in the model\nvalidation based on glacier specific geodetic mass balances. See next comment for\nmore detail.\n“Model performance is quantified by the root mean square error between the glacier-\nspecific climatic and geodetic mass balance for the individual catchments.”\nHow do you address the fact that geodetic mass balance includes both the climatic and\nice-flow components? Are you comparing glacier-wide mass balance only? Please\nprovide more details.\nThank you for this question. We are comparing the glacier-wide integrated mass balance\n(called specific mass balance) for each land-terminating glacier. As land-terminating\nglaciers have no ice-dynamically controlled losses, the two datasets are directly\ncomparable. The glacier-specific geodetic information has not been used for model\ncalibration (targeting the regional average), and is, thus, an independent validation\ndataset.\nThe information that we are only using land-terminating glaciers without frontal losses is\nstated several times in this section (former L562, 564, 565-566). We reformulated the\nfollowing sentences to increase clarity (former L560-562 & former L568-570):\n“Following this approach, we rank the sensitivity runs based on the highest agreement\nwith regional geodetic mass balance, as observed with satellite remote sensing, for all\nglaciers with no frontal ablation (region-wide average -0.27 m w.e. yr-1). The highest\nranked run (region-wide average -0.23 m w.e. yr-1) agrees well with the geodetic\nobservations and is presented in this study.”\n“Model performance is quantified by the root mean square error between the glacier-\nspecific climatic and geodetic mass balance for these glaciers, resulting in a model error\nof ±0.62 m w.e. yr-1.”\nLine 577-578: “Uncertainties of the glacier-specific CMB, constrained by model\nvalidation, directly translate into the uncertainties of frontal ablation estimations.”\nMore details are needed on how the uncertainties in glacier-specific CMB are quantified.\nFurthermore, uncertainties in geodetic mass balance estimates should also be\nconsidered. Ideally, validation of frontal ablation estimates should be conducted on a\nstudy glacier where in-situ measurements of frontal ablation, ice-flow, and surface\nmass balance are available.\nThank you for this comment. The estimation of uncertainties in the glacier-specific CMB\nhas been explained in the comment above. To consider the uncertainties in the specific\ngeodetic mass balance more explicitly, we now add the geodetic mass balance error to\nthe uncertainty analysis. The total uncertainty adds the uncertainty in the specific\nclimatic mass balance and the uncertainty in the specific geodetic mass balance. This\nway, we overestimate the inherent uncertainty because random errors in the geodetic\nmass balance may be counted twice: 1) In the geodetic mass balance error itself and 2)\nin the climatic mass balance error as it is inferred from the RMSE with the glacier-\nspecific geodetic values. We adjusted the section accordingly:\n“Uncertainties in frontal ablation consist of the uncertainties in the glacier-specific CMB\n(see Model calibration and validation) and the uncertainties in the specific geodetic\nmass balance (see Geodetic mass balance processing) following classical Gaussian\nerror propagation. Since the former uncertainty already includes random errors in the\ngeodetic mass balance, the resulting uncertainties of frontal ablation values are likely an\noverestimation.”\nThe only glacier with in-situ observations of ice thickness, ablation and surface\nvelocities is Schiaparelli Glacier. We can calculate the discharge through a flux gate\n(D ) at the location of the ice thickness measurement (Gacitúa et al. 2021). Together\nFG\nwith the climatic mass balance above this flux gate (CMB ), this value should match the\nFG\ngeodetic mass balance (GMB ) above this flux gate:\nFG\nGMB = CMB + D\nFG FG FG\nThe results agree within their uncertainty ranges:\nGMB = -0.014 ±0.004 Gt/yr\nFG\nCMB + D = -0.024 ±0.020 Gt/yr\nFG FG\nLine 582-583: “For our study site, the lack of ice thickness measurements in the CDI\nmakes ice thickness highly speculative. This directly translates into elevated\nuncertainties for frontal ablation.”\nCould you provide more details on how these uncertainties due to speculative ice\nthickness were quantified? It would strengthen the paper to explain the methodology or\nassumptions used to assess these elevated uncertainties.\nThank you for this question. With this statement we want to highlight the elevated\nuncertainty in ice thickness reconstructions in the CDI compared to other regions due to\nthe lack of observations. There is no possibility to validate those fields with in-situ\nobservations, and no in-situ observations of ice thickness are included in the modelling.\nTo quantify these uncertainties more thoroughly, we compare the available ice thickness\nproducts from modelling studies and calculate the standard deviation per pixel. While\nlocally the deviations can be extremely high (up to 250 m), the standard deviation along\nthe flux gates is smaller. The uncertainty in frontal ablation following this new approach\nincreases for some glaciers while it decreases for others (see new Figure 4). We\nadjusted the section on the flux gate approach accordingly:\n“For our study site, the lack of ice thickness measurements in the CDI makes modelled\nice thickness uncertain. To quantify the uncertainty in the ice thickness, we calculate the\nstandard deviation of the available ice thickness products from Carrivick et al.64, Millan\net al.3 and the participants in the consensus estimate covering the CDI2. Time\ndiscrepancies are corrected for by satellite-derived elevations changes.”\nResults section:\nSince you are using a surface energy balance (SEB) model for ablation, it would be\ninformative to estimate the individual contributions of key SEB components (incoming\nshortwave and longwave radiation, albedo, sensible and latent heat fluxes)\nto the total annual melt. While some information is provided, it would be beneficial to\npresent a more systematic breakdown of how each term changes over the study period,\nboth temporally and spatially. In particular, further discussion on albedo and incoming\nlongwave radiation beyond the estimates of trends would provide valuable insights.\nThank you for the comment. Most of the relevant energy and mass fluxes and their\ncontributions are provided in Fig. 3 and Fig. S6-S9. We added a figure that gives the\nannual values of those variables over the study period in the supplement (Fig. S10).\nIncoming and outgoing short- and longwave radiation only show minor annual variability,\nwhich is why we excluded those variables here for visibility reasons.\nLine 204: “Our results show that the annual CMB (Fig. 3c) is mainly controlled by air\ntemperature (Fig. S3a).”\nThe word “controlled” may not be the best choice here. Temperature influences the CMB\nmodel primarily through the bulk method for sensible heat fluxes, which you indicate\ncontribute around 30% to melt. Perhaps what you mean to say is that the inter-annual\nvariability in CMB is most strongly correlated with temperature. Additionally, have you\nconsidered correlating CMB with albedo? Several studies (e.g., Davaze et al., 2018;\nWilliamson et al., 2020; Xiao et al., 2022) demonstrate that mass balance is often\nstrongly correlated with summer albedo.\nThank you for this comment. We revised the sentence according to your suggestions:\n“Our results show that the inter-annual variability of the CMB (Fig. 3c) is mainly\ninfluenced by air temperature ...”\nFurthermore, we tested the correlation between albedo and CMB. Indeed, there is a\nsignificant correlation in summer (DJF), but also during the entire year. We included this\ninformation into the manuscript.\n“Melt energy and CMB are also linked to the annual average incoming solar radiation\n(r = 0.54 and r = -0.46, respectively) as well as the albedo (r = -0.68 and r = 0.69,\nrespectively).”\nLine 230-236:\nIt was noted earlier that the flux-gate approach carries large uncertainties due to the\nlack of ice-thickness estimates, yet the reported errors for CDI frontal ablation using this\napproach are smaller than those from the method based on the diherence between\ngeodetic and CMB estimates. How is the total error from the flux-gate approach\nassessed? It would be helpful to include more detail on this in the Methods section.\nAdditionally, how are the error estimates for frontal ablation of individual glaciers\ncalculated?\nSee reply to the comments on the Data & Methods section above. Numbers in this\nsection, the discussion and the abstract were adjusted following the revised uncertainty\nestimations.\nTable S5:\nWhile you’ve listed the roughness length for momentum, it would also be useful to\ninclude the roughness lengths for temperature and humidity, as these are also important\nin the bulk method used in your SEB model. Additionally, how were the roughness\nlengths determined? The roughness length of momentum for ice seems quite small (on\nthe order of 10^-4 m). Typically, roughness lengths for ice are closer to 10^-3 m (see\nHock, 2005 for reference). Could you clarify how this value was chosen and whether it\nmight be underestimated?\nThank you for these questions. The roughness length of ice was taken from Temme et al.\n(2023) where it was one of the calibration parameters, as given in Table S5. An\nunderestimation is not impossible, however, larger values of ice roughness length\nproduced larger deviation from the calibration targets (regional geodetic mass balance)\nand validation datasets (specific geodetic mass balance and ablation stake\nmeasurements) in that study (see Temme et al. 2023, Supplement).\nThe formulation of roughness lengths for temperature and humidity in COSIPY follows\nthe renewal theory for turbulent flow. Thus, the roughness lengths for humidity and\ntemperature are assumed to be one and two orders of magnitude smaller than the\nroughness length for momentum, respectively (Sauter et al. 2020)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Thank you to the authors for answering and clarifying my concerns regarding their manuscript. I understand and agree with the answers and changes introduced in the manuscript.\nJust some (very) minor comments:\nL49-50: However, stratospheric ozone depletion also forces storm-track poleward trend. Recovery of the ozone is projected so this could counteract the poleward trend. Do the authors analyze this scenario? And how could this affect CDI mass balance?\nL179 and L300-313: I suggest presenting the ELA results as m a.s.l. (I'm sorry I didn't note this in the first version.)\nL188: delete space between 15 and %\nL556: so, Which one is used in the bulk-approach applied here?\nAnswering to the authors, there are several energy balance studies for short-term in Patagonia linked to Japan’s research program on Patagonia. Most of them, were published in the Bulletin of Glacier Research during the 80´s and 90´s.", "reviewer_2": "Dear Editor,\nI have reviewed the authors' responses to my comments; however, I have not had the opportunity to thoroughly review the revised manuscript itself. Based on the responses provided, I am generally satisfied and believe the authors have addressed my main criticisms.\nThat said, I would like to bring to your attention a few minor points from their responses that may require further clarification:\nThe authors state: \"Taking only the land-terminating glaciers, the dynamic component is zero, and the climatic and geodetic mass balance are directly comparable.\" While this is true when considering glacier-wide (or region-wide) mass balance, it does not hold if distributed specific mass balance (e.g., mass balance versus elevation) of individual glaciers is considered. Geodetic mass balance for any glacier (land-terminating or not) always reflects a combination of surface mass balance (climatic) and ice flow (dynamic). This distinction was not fully addressed in the authors’ response, and I suggest that this clarification should be explicitly incorporated into the manuscript to ensure methodological accuracy.\nThe authors also mention: \"We are comparing the glacier-wide integrated mass balance (called specific mass balance) for each land-terminating glacier.\" However, glacier-wide mass balance is not the same as specific mass balance, and these terms should not be conflated. This mislabeling caused confusion in their responses and could lead to further misunderstandings in the manuscript. I recommend that the authors refer to the Glossary of Mass Balance (https://wgms.ch/downloads/Cogley_etal_2011.pdf) to ensure that terminology is used correctly and consistently throughout the paper.\nFinally, the authors’ use of the term \"ice dynamics\" appears to describe glacier calving or frontal ablation. However, ice dynamics is often synonymous with ice flow, which occurs in all glaciers regardless of their terminus type (land or marine). To avoid confusion, I suggest the authors revise this terminology and use more precise language when describing these processes (again, see the Glossary for guidance).\nI hope these observations are helpful in guiding the final revisions. Please let me know if any further input is required from my side.", "reviewer_3": "Dear authors,\nThe manuscript has been improved significantly through the review process and all my previous comments and additional concerns have been addressed directly or indirectly through your response to the reviewers. The remaining comments I have are minor.\nKind regards,\nNicole Schaffer, PhD.\nDetailed comments:\nL38-39 Suggestion to delete “…with glaciers descending down to sea level..” as this is redundant since it can be inferred from the previous sentence. I realize this was included to respond to a comment from reviewer 1 so if you decide to keep it for that reason that is ok. The modification to include “..inducing high mas input..” in response to reviewer 1 is a helpful addition but I would suggest replacing “at the top” with something more explicit such as “at the highest elevations”.\nL46-47 suggestion to modify this sentence to “..not only the formation of clouds…but also the global ocean…”\nL78-79 The term “this way” is somewhat vague and informal. Suggestion to replace this with “With this dataset, …”. Also consider replacing “given” with a more appropriate word such as “produced”.\nL272-278 The sentence starting on L272 and the rest of this paragraph is mostly duplicated in the new discussion paragraph on advancing glaciers. Given that this part of the paragraph is more suited for the discussion since it is an interpretation of the results, I would suggest deleting this text from the results and merging it with the new paragraph in the discussion (see my comments further down for that paragraph).\nL313 change “extends generally” to “generally extends”\nL315 Replace the term “exposition” with a more suitable term. For example, “aspect”.\nL311-320 In the second sentence within this paragraph, the author highlights that MALT glaciers show more positive CMB. This prompts one to question whether all the advancing glaciers are MALT glaciers? I would suggest adding a sentence staring on L315 (if it is true that they are all MALT, otherwise modify!) to answer this question and aid in linking the sentence on MALT to the discussion on advancing glaciers. Additionally, moving the last sentence to L317 would help with the readability and cohesive flow of ideas. Finally, I would suggest merging this paragraph with the text on L272-278 to reduce unnecessary repetition in the manuscript as follows:\n“….century. While these advancing glaciers are all MALT, they have medium to low frontal ablation which, in addition to a thickening further upstream, suggest a primarily climatic control. We ascribe these climatological favorable conditions to the glaciers’ hypsometry and aspect. All four glaciers have their origin at the high-elevated central plateau of the CDI (above 2000 m) and steep topography resulting in high snowfall amounts and above-average accumulation-area-ratios (between 0.72 and 0.88 compared to the CDI average of 0.61). Glaciers with high accumulation-area-ratio are often less sensitive to changes in ELA and, thus, warming due to the small and steep ablation area15.Southward exposures of Garibaldi, Guilcher Oeste and Guilcher Este glaciers further reduce surface ablation (Fig. S8a). Altogether, these characteristics ultimately lead to high snowfall amounts together with reduced surface ablation (Fig. 2c, Fig. S9d), favoring mass gain.”\nL311-320 (b) Does the strong precipitation gradient across the CDI have an impact on the contrasting glacier behaviour? If you consider the answer relevant and worth mentioning, please add a sentence to this paragraph.\nL365 suggestion to replace “…ablation at the CDI…is in a similar…” with “ …ablation for the CDI…is a similar…”\nL377 replace “…study are..” with “…study is…”\nL379 replace “verifiably” with “verifiable”\nL380 suggestion to replace “…should be handled with certain care..” to “…should be interpreted with care…”\nL443 Consider changing “Required variables comprise…” to “Required variables for this study are …”\nL445-447 consider changing sentence to “For downscaling of precipitation (53.75-55.50°S, 74.50-73.25°W) information about air temperature, relative humidity, wind vectors and geopotential height between 850 and 500 hPa is needed.” The term “we need” is too informal for a publication in my opinion.\nL487-488 Reading the phrase “….where the cumulative distribution function of the model is transferred to the cumulative distribution function of the observation” could be interpreted to mean that the cumulative distribution of the observation data is corrected by aligning it with the cumulative distribution of the model output. From my limited understanding of quantile mapping bias correction, I understand that the correction is the other way around. The quantile distribution of the model outputs is shifted to align with the quantile distribution of the observed data. Consider modifying the sentence to “….where the cumulative distribution function of the model is shifted to align with the cumulative distribution function of the observations”\nTable S2 The RMSE for the station Rio Azorpado is quite low (0.33). Do you know why this might be? If relevant, include the explanation in the manuscript."}, "author_response": "Dear editor and referees,\nWe would like to thank you for the constructive review of our manuscript. We are\nconvinced that your suggestions have improved the readability and overall quality of the\nmanuscript.\nFor reviewers 1 and 3, the requested changes were mainly of editorial nature. They are\nfully implemented in the revised version of the manuscript. Reviewer 2 raised concerns\nnot on the manuscript but on terminology used in the rebuttal to the first review round.\nTo avoid ambiguities or misunderstanding, we decided to adapt the terminology to be\nclear and specific.\nPlease find our detailed reply to the individual comments below.\nKind regards,\nFranziska Temme,\nin the name of all co-authors\nPoint-by-point response to reviewer comments\nReviewer #1 (Remarks to the Author):\nThank you to the authors for answering and clarifying my concerns regarding their\nmanuscript. I understand and agree with the answers and changes introduced in the\nmanuscript.\nJust some (very) minor comments:\nWe would like to thank you for the constructive review of our manuscript. In the\nfollowing you find a point-by-point response to the raised comments. We are convinced\nthat our actions have improved the quality and readability of the manuscript. Referee\ncomments are reproduced in black font color. Our response and the undertaken actions\nare formulated in green font color, text that was adjusted in the manuscript is\nhighlighted in italic font.\nL49-50: However, stratospheric ozone depletion also forces storm-track poleward\ntrend. Recovery of the ozone is projected so this could counteract the poleward trend.\nDo the authors analyze this scenario? And how could this affect CDI mass balance?\nThank you for this question. The counteracting effect of ozone recovery is considered in\nthe cited publication (Goyal at el. 2021). They mention that ozone depletion is seen as\nthe main forcing mechanism for the southward shift in the past few decades and\ndiscuss the counteracting effect of ozone recovery. However, they find that, for high\nemission scenarios, the effect of greenhouse gases will dominate over the effect of\nozone recovery and cause a future southward shifting.\nIn general, a southward shift of the westerlies would cause an intensification of those\nover the CDI, potentially enhancing precipitation. For our study period we observe an\nincreasing trend in wind velocities and precipitation (see L137-138) that can be\nexplained by the shift in westerlies. However, the trend for precipitation is small and we\ndo not find a significant increase in snowfall amounts (see L229-230).\nL179 and L300-313: I suggest presenting the ELA results as m a.s.l. (I'm sorry I didn't\nnote this in the first version.)\nAdjusted as suggested, thank you.\nL188: delete space between 15 and %\nAccording to the International System of Units, a non-breaking space should be added\nbetween the number and the % symbol. We found a few occasions in the text, where the\nspace was missing so far and adjusted those in the revised version of the manuscript to\nensure consistency.\nL556: so, Which one is used in the bulk-approach applied here?\nThank you for this question. In this study, we apply Monin-Obukhov similarity theory, as\nnoted in Table S5. We added this information into the text:\n“The latter is applied in this study (Table S5).”\nAnswering to the authors, there are several energy balance studies for short-term in\nPatagonia linked to Japan’s research program on Patagonia. Most of them, were\npublished in the Bulletin of Glacier Research during the 80´s and 90´s.\nThank you for this hint. Despite an extensive search, the only publication we were able\nto access is Takeuchi et al. 1999, Global and Planetary Change. We incorporated this\npublication for completeness.\nReviewer #2 (Remarks to the Author):\nDear Editor,\nI have reviewed the authors' responses to my comments; however, I have not had the\nopportunity to thoroughly review the revised manuscript itself. Based on the responses\nprovided, I am generally satisfied and believe the authors have addressed my main\ncriticisms.\nWe would like to thank you for the constructive comments on our manuscript. In the\nfollowing you find a response to the raised comments. We are convinced that our\nactions have improved the quality and readability of the manuscript. Referee comments\nare reproduced in black font color. Our response and the undertaken actions are\nformulated in green font color, text that was adjusted in the manuscript is highlighted in\nitalic font.\nThat said, I would like to bring to your attention a few minor points from their responses\nthat may require further clarification:\nThe authors state: \"Taking only the land-terminating glaciers, the dynamic component is\nzero, and the climatic and geodetic mass balance are directly comparable.\" While this\nis true when considering glacier-wide (or region-wide) mass balance, it does not hold if\ndistributed specific mass balance (e.g., mass balance versus elevation) of individual\nglaciers is considered. Geodetic mass balance for any glacier (land-terminating or not)\nalways reflects a combination of surface mass balance (climatic) and ice flow\n(dynamic). This distinction was not fully addressed in the authors’ response, and I\nsuggest that this clarification should be explicitly incorporated into the manuscript to\nensure methodological accuracy.\nThe authors also mention: \"We are comparing the glacier-wide integrated mass balance\n(called specific mass balance) for each land-terminating glacier.\" However, glacier-wide\nmass balance is not the same as specific mass balance, and these terms should not be\nconflated. This mislabeling caused confusion in their responses and could lead to\nfurther misunderstandings in the manuscript. I recommend that the authors refer to the\nGlossary of Mass Balance (https://wgms.ch/downloads/Cogley_etal_2011.pdf) to\nensure that terminology is used correctly and consistently throughout the paper.\nFinally, the authors’ use of the term \"ice dynamics\" appears to describe glacier calving\nor frontal ablation. However, ice dynamics is often synonymous with ice flow, which\noccurs in all glaciers regardless of their terminus type (land or marine). To avoid\nconfusion, I suggest the authors revise this terminology and use more precise language\nwhen describing these processes (again, see the Glossary for guidance).\nI hope these observations are helpful in guiding the final revisions. Please let me know if\nany further input is required from my side.\nThank you for your comments. Regarding the terminology of “specific mass balance” we\nunderstand your concerns and excuse for the confusion. With the term “specific mass\nbalance” we intend to refer to the glacier-wide specific mass balance, where the\nstatement that ice-dynamically controlled losses are zero for land-terminating glaciers\nholds true. We agree that this is not true in a case where not the entire glacier area but\nonly a subsection is considered. Throughout the manuscript we mainly use the term\n“glacier-specific mass balance”, which is a widely used terminology when referring to\nthe specific mass balance of an entire glacier and should resolve this ambiguity. We\nadded “glacier-“ where it was missing so far (L627 & caption of figure 1) to ensure\nconsistency. Furthermore, we added the following sentence in L149: “Glacier-wide\nspecific mass balance is used for the comparison, in the following denoted as glacier-\nspecific mass balance.”\nRegarding the terminology of “frontal ablation” and “ice-dynamically controlled mass\nloss”, we understand your concerns. In the Introduction (L65-67) (and in the last,\nsummarizing paragraph of the Discussion), we describe that frontal ablation is a loss\nterm that is controlled by ice-dynamics through calving. To avoid confusion, we now use\nthe term “frontal ablation” throughout the results and discussion sections of the\nmanuscript.\nReviewer #3 (Remarks to the Author):\nDear authors,\nThe manuscript has been improved significantly through the review process and all my\nprevious comments and additional concerns have been addressed directly or indirectly\nthrough your response to the reviewers. The remaining comments I have are minor.\nKind regards,\nNicole Schaffer, PhD.\nWe would like to thank you for the constructive review of our manuscript. In the\nfollowing you find a point-by-point response to the raised comments. We are convinced\nthat our actions have improved the quality and readability of the manuscript. Referee\ncomments are reproduced in black font color. Our response and the undertaken actions\nare formulated in green font color, text that was adjusted in the manuscript is\nhighlighted in italic font.\nDetailed comments:\nL38-39 Suggestion to delete “…with glaciers descending down to sea level..” as this is\nredundant since it can be inferred from the previous sentence. I realize this was\nincluded to respond to a comment from reviewer 1 so if you decide to keep it for that\nreason that is ok. The modification to include “..inducing high mas input..” in response\nto reviewer 1 is a helpful addition but I would suggest replacing “at the top” with\nsomething more explicit such as “at the highest elevations”.\nThank you for this comment. We adjusted the sentence as suggested.\nL46-47 suggestion to modify this sentence to “..not only the formation of clouds…but\nalso the global ocean…”\nChanged as suggested, thank you.\nL78-79 The term “this way” is somewhat vague and informal. Suggestion to replace this\nwith “With this dataset, …”. Also consider replacing “given” with a more appropriate\nword such as “produced”.\nAdjusted as suggested, thank you.\nL272-278 The sentence starting on L272 and the rest of this paragraph is mostly\nduplicated in the new discussion paragraph on advancing glaciers. Given that this part\nof the paragraph is more suited for the discussion since it is an interpretation of the\nresults, I would suggest deleting this text from the results and merging it with the new\nparagraph in the discussion (see my comments further down for that paragraph).\nThank you for this comment. We moved the paragraph to the discussion.\nL313 change “extends generally” to “generally extends”\nChanged as suggested, thank you.\nL315 Replace the term “exposition” with a more suitable term. For example, “aspect”.\nAdjusted as suggested, thank you.\nL311-320 In the second sentence within this paragraph, the author highlights that MALT\nglaciers show more positive CMB. This prompts one to question whether all the\nadvancing glaciers are MALT glaciers? I would suggest adding a sentence staring on\nL315 (if it is true that they are all MALT, otherwise modify!) to answer this question and\naid in linking the sentence on MALT to the discussion on advancing glaciers.\nAdditionally, moving the last sentence to L317 would help with the readability and\ncohesive flow of ideas. Finally, I would suggest merging this paragraph with the text on\nL272-278 to reduce unnecessary repetition in the manuscript as follows:\n“….century. While these advancing glaciers are all MALT, they have medium to low\nfrontal ablation which, in addition to a thickening further upstream, suggest a primarily\nclimatic control. We ascribe these climatological favorable conditions to the glaciers’\nhypsometry and aspect. All four glaciers have their origin at the high-elevated central\nplateau of the CDI (above 2000 m) and steep topography resulting in high snowfall\namounts and above-average accumulation-area-ratios (between 0.72 and 0.88\ncompared to the CDI average of 0.61). Glaciers with high accumulation-area-ratio are\noften less sensitive to changes in ELA and, thus, warming due to the small and steep\nablation area15.Southward exposures of Garibaldi, Guilcher Oeste and Guilcher Este\nglaciers further reduce surface ablation (Fig. S8a). Altogether, these characteristics\nultimately lead to high snowfall amounts together with reduced surface ablation (Fig.\n2c, Fig. S9d), favoring mass gain.”\nThank you for this comment and the detailed revision of the paragraph. We adjusted the\nparagraph following your suggestions. The advancing glaciers are all marine\nterminating. We added this information.\nL311-320 (b) Does the strong precipitation gradient across the CDI have an impact on\nthe contrasting glacier behaviour? If you consider the answer relevant and worth\nmentioning, please add a sentence to this paragraph.\nThank you for this question. We do not see the precipitation gradient as a relevant\nforcing for the contrasting glacier behavior. The reason is that we see retreating glaciers\non the west and east part of the CDI, thus there is no zonal gradient in the\nretreating/advancing behavior. The advancing glaciers are all located in the central area\nand are also surrounded by several retreating glaciers.\nL365 suggestion to replace “…ablation at the CDI…is in a similar…” with “ …ablation for\nthe CDI…is a similar…”\nAdjusted as suggested, thank you.\nL377 replace “…study are..” with “…study is…”\nAdjusted to “A major limitation of this study is the scarcity of in-situ observations, …”\nL379 replace “verifiably” with “verifiable”\nChanged as suggested, thank you.\nL380 suggestion to replace “…should be handled with certain care..” to “…should be\ninterpreted with care…”\nAdjusted as suggested, thank you.\nL443 Consider changing “Required variables comprise…” to “Required variables for this\nstudy are …”\nAdjusted as suggested, thank you.\nL445-447 consider changing sentence to “For downscaling of precipitation (53.75-\n55.50°S, 74.50-73.25°W) information about air temperature, relative humidity, wind\nvectors and geopotential height between 850 and 500 hPa is needed.” The term “we\nneed” is too informal for a publication in my opinion.\nChanged as suggested, thank you.\nL487-488 Reading the phrase “….where the cumulative distribution function of the\nmodel is transferred to the cumulative distribution function of the observation” could be\ninterpreted to mean that the cumulative distribution of the observation data is corrected\nby aligning it with the cumulative distribution of the model output. From my limited\nunderstanding of quantile mapping bias correction, I understand that the correction is\nthe other way around. The quantile distribution of the model outputs is shifted to align\nwith the quantile distribution of the observed data. Consider modifying the sentence to\n“….where the cumulative distribution function of the model is shifted to align with the\ncumulative distribution function of the observations”\nThank you for this comment. We adjusted the section to “… where the cumulative\ndistribution function of the model is adjusted to align with the cumulative distribution\nfunction of the observation”\nTable S2 The RMSE for the station Rio Azorpado is quite low (0.33). Do you know why this\nmight be? If relevant, include the explanation in the manuscript.\nWe do not have a clear explanation for the low correlation for precipitation at Río\nAzorpado. We screened the timeseries for outliers or periods of consecutive low or high\nmeasurements and found many periods of corrupt values that we deleted, but it is\npossible that this did not resolve all issues. Therefore, issues with the sensor would be\nthe most obvious explanation."}]

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