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  1. Abstract

    Forecasting Antarctic atmospheric, oceanic, and sea ice conditions on subseasonal to seasonal scales remains a major challenge. During both the freezing and melting seasons current operational ensemble forecasting systems show a systematic overestimation of the Antarctic sea-ice edge location. The skill of sea ice cover prediction is closely related to the accuracy of cloud representation in models, as the two are strongly coupled by cloud radiative forcing. In particular, surface downward longwave radiation (DLW) deficits appear to be a common shortcoming in atmospheric models over the Southern Ocean. For example, a recent comparison of ECMWF reanalysis 5th generation (ERA5) global reanalysis with the observations from McMurdo Station revealed a year-round deficit in DLW of approximately 50 Wm−2in marine air masses due to model shortages in supercooled cloud liquid water. A comparison with the surface DLW radiation observations from the Ocean Observatories Initiative mooring in the South Pacific at 54.08° S, 89.67° W, for the time period January 2016–November 2018, confirms approximately 20 Wm−2deficit in DLW in ERA5 well north of the sea-ice edge. Using a regional ocean model, we show that when DLW is artificially increased by 50 Wm−2in the simulation driven by ERA5 atmospheric forcing, the predicted sea ice growth agrees much better with the observations. A wide variety of sensitivity tests show that the anomalously large, predicted sea-ice extent is not due to limitations in the ocean model and that by implication the cause resides with the atmospheric forcing.

     
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  2. Antarctic sea ice prediction has garnered increasing attention in recent years, particularly in the context of the recent record lows of February 2022 and 2023. As Antarctica becomes a climate change hotspot, as polar tourism booms, and as scientific expeditions continue to explore this remote continent, the capacity to anticipate sea ice conditions weeks to months in advance is in increasing demand. Spurred by recent studies that uncovered physical mechanisms of Antarctic sea ice predictability and by the intriguing large variations of the observed sea ice extent in recent years, the Sea Ice Prediction Network South (SIPN South) project was initiated in 2017, building upon the Arctic Sea Ice Prediction Network. The SIPN South project annually coordinates spring-to-summer predictions of Antarctic sea ice conditions, to allow robust evaluation and intercomparison, and to guide future development in polar prediction systems. In this paper, we present and discuss the initial SIPN South results collected over six summer seasons (December-February 2017-2018 to 2022-2023). We use data from 22 unique contributors spanning five continents that have together delivered more than 3000 individual forecasts of sea ice area and concentration. The SIPN South median forecast of the circumpolar sea ice area captures the sign of the recent negative anomalies, and the verifying observations are systematically included in the 10-90% range of the forecast distribution. These statements also hold at the regional level except in the Ross Sea where the systematic biases and the ensemble spread are the largest. A notable finding is that the group forecast, constructed by aggregating the data provided by each contributor, outperforms most of the individual forecasts, both at the circumpolar and regional levels. This indicates the value of combining predictions to average out model-specific errors. Finally, we find that dynamical model predictions (i.e., based on process-based general circulation models) generally perform worse than statistical model predictions (i.e., data-driven empirical models including machine learning) in representing the regional variability of sea ice concentration in summer. SIPN South is a collaborative community project that is hosted on a shared public repository. The forecast and verification data used in SIPN South are publicly available in near-real time for further use by the polar research community, and eventually, policymakers. 
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    Free, publicly-accessible full text available May 9, 2024
  3. null (Ed.)
    Abstract Two reports of Antarctic Region potential new record high temperature observations (18.3°C, 6 February 2020 at Esperanza station and 20.8°C, 9 February 2020 at a Brazilian automated permafrost monitoring station on Seymour Island) were evaluated by a World Meteorological Organization (WMO) panel of atmospheric scientists. The latter figure was reported as 20.75°C in the media. The panel considered the synoptic situation and instrumental setups. It determined that a large high-pressure system over the area created föhn conditions and resulted in local warming for both situations. Examination of the data and metadata of the Esperanza station observation revealed no major concerns. However, analysis of data and metadata of the Seymour Island permafrost monitoring station indicated that an improvised radiation shield led to a demonstrable thermal bias error for the temperature sensor. Consequently, the WMO has accepted the 18.3° C value for 12 noon (LST) 6 February 2020 [1500 UTC 6 February 2020] at the Argentine Esperanza station as the new “Antarctic Region [continental, including mainland and surrounding islands] highest temperature recorded observation” but rejected the 20.8° C observation at the Brazilian automated Seymour Island permafrost monitoring station as biased. The committee strongly emphasizes the permafrost monitoring station was not badly designed for its purpose, but the project investigators were forced to improvise a non-optimal radiation shield after losing the original covering. Secondly, with regard to media dissemination of this type of information, the committee urges increased caution in early announcements as many media outlets often tend to sensationalize and mischaracterize potential records. 
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  4. Abstract

    Data impact experiments are conducted employing the Polar Weather Research and Forecasting (WRF) model during the YOPP‐SH summer special observing period (SOP) using the Antarctic Mesoscale Prediction System (AMPS) framework to determine the forecast impact of numerous additional radiosondes collected during the SOP. Hybrid variational‐ensemble three‐dimensional data assimilation is performed on model forecast domains over Antarctica and the Southern Ocean using all regular observations normally available (Experiment “NoSOP”) and using the same set plus the extra soundings launched for the SOP (Experiment “SOP”). The SOP results show better near‐surface temperature and wind‐speed forecasts than the NoSOP results, primarily over West Antarctica. Radiosonde profiles confirm that temperature and wind‐speed forecasts are improved throughout the troposphere with the addition of the SOP radiosonde data, but the results for relative humidity are variable. Temperatures are improved at lower levels early in the forecasts, whereas wind speeds are better at higher levels later in the forecasts. An evaluation against the ERA5 global reanalysis that provides a much broader perspective reveals that the improved forecast skill for the SOP experiment persists up to 72 hours for temperature, wind speed, and relative humidity. The gains, however, are primarily confined to the Antarctic continent, consistent with the additional radiosonde spatial coverage being mainly poleward of 60°S. With extra radiosondes concentrated over the Antarctic Peninsula, SOP forecasts of the region downstream of the Peninsula were significantly improved compared to NoSOP forecasts. In addition, it is found that the assimilation of the additional radiosonde data can have a greater impact on the forecasts of strong cyclones, as shown for a major coastal cyclone affecting West Antarctica, with improvements in its magnitude and track. The results also suggest that increasing radiosonde launches at lower southern latitudes would improve forecasts over the Southern Ocean, especially during austral winter.

     
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  5. Abstract

    The Antarctica Peninsula (AP) has experienced more frequent and intense surface melting recently, jeopardizing the stability of ice shelves and ultimately leading to ice loss. Among the key phenomena that can initiate surface melting are atmospheric rivers (ARs) and leeside foehn; the combined impact of ARs and foehn led to moderate surface warming over the AP in December 2018 and record‐breaking surface melting in February 2022. Focusing on the more intense 2022 case, this study uses high‐resolution Polar WRF simulations with advanced model configurations, Reference Elevation Model of Antarctica topography, and observed surface albedo to better understand the relationship between ARs and foehn and their impacts on surface warming. With an intense AR (AR3) intrusion during the 2022 event, weak low‐level blocking and heavy orographic precipitation on the upwind side resulted in latent heat release, which led to a more deep‐foehn like case. On the leeside, sensible heat flux associated with the foehn magnitude was the major driver during the night and the secondary contributor during the day due to a stationary orographic gravity wave. Downward shortwave radiation was enhanced via cloud clearance and dominated surface melting during the daytime, especially after the peak of the AR/foehn events. However, due to the complex terrain of the AP, ARs can complicate the foehn event by transporting extra moisture to the leeside via gap flows. During the peak of the 2022 foehn warming, cloud formation on the leeside hampered the downward shortwave radiation and slightly increased the downward longwave radiation.

     
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  6. Abstract

    We calculate a regional surface “melt potential” index (MPI) over Antarctic ice shelves that describes the frequency (MPI-freq; %) and intensity (MPI-int; K) of daily maximum summer temperatures exceeding a melt threshold of 273.15 K. This is used to determine which ice shelves are vulnerable to melt-induced hydrofracture and is calculated using near-surface temperature output for each summer from 1979/80 to 2018/19 from two high-resolution regional atmospheric model hindcasts (using the MetUM and HIRHAM5). MPI is highest for Antarctic Peninsula ice shelves (MPI-freq 23%–35%, MPI-int 1.2–2.1 K), lowest (2%–3%, <0 K) for the Ronne–Filchner and Ross ice shelves, and around 10%–24% and 0.6–1.7 K for the other West and East Antarctic ice shelves. Hotspots of MPI are apparent over many ice shelves, and they also show a decreasing trend in MPI-freq. The regional circulation patterns associated with high MPI values over West and East Antarctic ice shelves are remarkably consistent for their respective region but tied to different large-scale climate forcings. The West Antarctic circulation resembles the central Pacific El Niño pattern with a stationary Rossby wave and a strong anticyclone over the high-latitude South Pacific. By contrast, the East Antarctic circulation comprises a zonally symmetric negative Southern Annular Mode pattern with a strong regional anticyclone on the plateau and enhanced coastal easterlies/weakened Southern Ocean westerlies. Values of MPI are 3–4 times larger for a lower temperature/melt threshold of 271.15 K used in a sensitivity test, as melting can occur at temperatures lower than 273.15 K depending on snowpack properties.

     
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