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Abstract. The Ross Ice Shelf, West Antarctica, experienced an extensive melt event in January 2016. We examine the representation of this event by the HIRHAM5 and MetUM high-resolution regional atmospheric models, as well as a sophisticated offline-coupled firn model forced with their outputs. The model results are compared with satellite-based estimates of melt days. The firn model estimates of the number of melt days are in good agreement with the observations over the eastern and central sectors of the ice shelf, while the HIRHAM5 and MetUM estimates based on their own surface schemes are considerably underestimated, possibly due to deficiencies in these schemes and an absence of spin-up. However, the firn model simulates sustained melting over the western sector of the ice shelf, in disagreement with the observations that show this region as being a melt-free area. This is attributed to deficiencies in the HIRHAM5 and MetUM output and particularly a likely overestimation of night-time net surface radiative flux. This occurs in response to an increase in night-time downwelling longwave flux from around 180–200 to 280 W m−2 over the course of a few days, leading to an excessive amount of energy at the surface available for melt. Satellite-based observations show that this change coincides with a transition from clear-sky to cloudy conditions, with clouds containing both liquid water and ice water. The models capture the initial clear-sky conditions but seemingly struggle to correctly represent cloud properties associated with the cloudy conditions, which we suggest is responsible for the radiative flux errors. 

Abstract. The Ross Ice Shelf, West Antarctica, experienced an extensive melt event in January 2016. We examine the representation of this event by the HIRHAM5 and MetUM high-resolution regional atmospheric models, as well as a sophisticated offline coupled firn model forced with their outputs. The model results are compared with satellite-based estimates of melt days. The firn model estimates of the number of melt days are in good agreement with the observations over the eastern and central sectors of the ice shelf, while the HIRHAM5 and MetUM estimates based on their own surface schemes are considerably underestimated, possibly due to deficiencies in these schemes and an absence of spin-up. However, the firn model simulates sustained melting over the western sector of the ice shelf, in disagreement with the observations that show this region as being melt-free. This is attributed to deficiencies in the HIRHAM5 and MetUM output, and particularly a likely overestimation of nighttime net surface radiative flux. This occurs in response to an increase in nighttime downwelling longwave flux from around 180–200 W m-2 to 280 W m-2 over the course of a few days, leading to an excessive amount of energy at the surface available for melt. Satellite-based observations show that this change coincides with a transition from clear-sky conditions to clouds containing both liquid-water and ice-water. The models capture the initial clear-sky conditions but seemingly struggle to correctly represent the ice-to-liquid mass partitioning associated with the cloudy conditions, which we suggest is responsible for the radiative flux errors. 

Abstract The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven targeted observing periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5–10-day duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed-phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high-time-resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The Sea Ice Prediction Network South (SIPN South) analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase. 

Abstract Environmental sensors are crucial for monitoring weather conditions and the impacts of climate change. However, it is challenging to place sensors in a way that maximises the informativeness of their measurements, particularly in remote regions like Antarctica. Probabilistic machine learning models can suggest informative sensor placements by finding sites that maximally reduce prediction uncertainty. Gaussian process (GP) models are widely used for this purpose, but they struggle with capturing complex non-stationary behaviour and scaling to large datasets. This paper proposes using a convolutional Gaussian neural process (ConvGNP) to address these issues. A ConvGNP uses neural networks to parameterise a joint Gaussian distribution at arbitrary target locations, enabling flexibility and scalability. Using simulated surface air temperature anomaly over Antarctica as training data, the ConvGNP learns spatial and seasonal non-stationarities, outperforming a non-stationary GP baseline. In a simulated sensor placement experiment, the ConvGNP better predicts the performance boost obtained from new observations than GP baselines, leading to more informative sensor placements. We contrast our approach with physics-based sensor placement methods and propose future steps towards an operational sensor placement recommendation system. Our work could help to realise environmental digital twins that actively direct measurement sampling to improve the digital representation of reality. 

Abstract The Antarctic Peninsula (AP) experienced a new extreme warm event and record-high surface melt in February 2022, rivaling the recent temperature records from 2015 and 2020, and contributing to the alarming series of extreme warm events over this region showing stronger warming compared to the rest of Antarctica. Here, the drivers and impacts of the event are analyzed in detail using a range of observational and modeling data. The northern/northwestern AP was directly impacted by an intense atmospheric river (AR) attaining category 3 on the AR scale, which brought anomalous heat and rainfall, while the AR-enhanced foehn effect further warmed its northeastern side. The event was triggered by multiple large-scale atmospheric circulation patterns linking the AR formation to tropical convection anomalies and stationary Rossby waves, with an anomalous Amundsen Sea Low and a record-breaking high-pressure system east of the AP. This multivariate and spatial compound event culminated in widespread and intense surface melt across the AP. Circulation analog analysis shows that global warming played a role in the amplification and increased probability of the event. Increasing frequency of such events can undermine the stability of the AP ice shelves, with multiple local to global impacts, including acceleration of the AP ice mass loss and changes in sensitive ecosystems. 

Abstract From 5 July to 11 September 2012, the Amundsen–Scott South Pole station experienced an unprecedented 78 days in a row with a maximum temperature at or below −50°C. Aircraft and ground-based activity cannot function without risk below this temperature. Lengthy periods of extreme cold temperatures are characterized by a drop in pressure of around 15 hPa over 4 days, accompanied by winds from grid east. Periodic influxes of warm air from the Weddell Sea raise the temperature as the wind shifts to grid north. The end of the event occurs when the temperature increase is enough to move past the −50°C threshold. This study also examines the length of extreme cold periods. The number of days below −50°C in early winter has been decreasing since 1999, and this trend is statistically significant at the 5% level. Late winter shows an increase in the number of days below −50°C for the same period, but this trend is not statistically significant. Changes in the southern annular mode, El Niño–Southern Oscillation, and the interdecadal Pacific oscillation/tripole index are investigated in relation to the initiation of extreme cold events. None of the correlations are statistically significant. A positive southern annular mode and a La Niña event or a central Pacific El Niño–Southern Oscillation pattern would position the upper-level circulation to favor a strong, symmetrical polar vortex with strong westerlies over the Southern Ocean, leading to a cold pattern over the South Pole. Significance Statement The Amundsen–Scott South Pole station is the coldest Antarctic station staffed year-round by U.S. personnel. Access to the station is primarily by airplane, especially during the winter months. Ambient temperature limits air access as planes cannot operate at minimum temperatures below −50°C. The station gets supplies during the winter months if needed, and medical emergencies can happen requiring evacuations. Knowing when planes would be able to fly is crucial, especially for life-saving efforts. During 2012, a record 78 continuous days of temperatures below −50°C occurred. A positive southern annular mode denoting strong westerly winds over the Pacific Ocean and a strong polar vortex over the South Pole contribute to the maintenance of long periods of extremely cold temperatures.