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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 FROM AUTHOR]

Despite a variety of efforts made to measure snow accumulation at the South Pole (SP), snow accumulation changes and their mechanism have not yet been fully explained. Here, SP stake farm measurements, global sea surface temperature observations, and atmospheric circulation data from European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 were used to investigate the annual and seasonal snow accumulation changes at the SP during 1983–2020, and their association with central tropical Pacific Sea surface temperature variations. SP annual snow accumulation decreased significantly for the 1983–2007 period at a rate of −39.7 ± 1.4 mm decade−1, but switched to a dramatically positive trend during 2008–2020 (108.7 ± 2.7 mm decade−1), with the strongest increase in the austral autumn. The switch to a dramatically upward trend can largely be attributed to a cyclonic anomaly over the South Atlantic and an anticyclonic anomaly over the Drake Passage, causing the enhanced advection of warm and wet air into the SP. These circulation patterns were generated by an atmospheric Rossby wave train forced by rapid warming in the central tropical Pacific during 2008–2020. Plain Language Summary: Snowfall on the surface of Antarctica stores ocean water in solid form, which is pivotal for the mass balance of the Antarctic ice sheet, and the fluctuations of snow accumulation therefore have an important impact on the sea level variation. However, snow accumulation changes and its mechanisms at the South Pole have not been fully explained until now. This study investigated snow accumulation changes at the South Pole since 1983, and further analyzed the mechanisms affecting it. Annual snow accumulation rates at the South Pole experienced a significant decrease from1983 to 2007 but shifted to a dramatic increase during 2008–2020, with the greatest increase in the austral autumn. The significantly upward trend after 2008 is largely caused by the anomalous atmospheric circulations around Antarctica, driving warm and wet air into the Antarctic interior, which resulted in more snowfall at the South Pole. These circulation patterns were triggered by rapid warming in the central tropical Pacific Ocean since 2008. These results improve the understanding of snow accumulation changes and their mechanisms at the South Pole, which helps to better predict the contribution of snow accumulation changes to future global sea level rise. Key Points: Annual snow accumulation at South Pole decreased significantly before 2007, but switched to a dramatically upward trend during 2008–2020The upward trend of snow accumulation after 2008 is closely associated with the anomalous cyclones and anticyclones around AntarcticaThe anomalous circulations are driven by tropical convection in the central tropical Pacific via the atmospheric Rossby train since 2008 [ABSTRACT FROM AUTHOR]

Total solar eclipses (TSEs) are impressive astronomical events that have attracted people's curiosity since ancient times. Their abrupt alterations to the radiation balance have stimulated studies on "eclipse meteorology," most of them documenting events in the Northern Hemisphere while only one TSE (23 November 2003) has been described over Antarctica. On 4 December 2021--just a few days before the austral summer solstice--the moon blocked the sun over the austral high latitudes, with the path of totality arching from the Weddell Sea to the Amundsen Sea, thus producing a ~2-min central TSE. In this work we present high-resolution meteorological observations from Union Glacier Camp (80°S, 83°W), the only location with a working station under totality, and South Pole station. These observations were complemented with meteorological records from 37 surface stations across Antarctica. Notably, the largest cooling (~5°C) was observed over the East Antarctic dome, where obscurity was ~85% while many sectors experienced insignificant temperature changes. This heterogenous cooling distribution, at odds with the seemingly homogeneous land surface of Antarctica, is partially captured by a simple radiative model. To further diagnose the effect of the eclipse on the surface meteorology, we ran multiple pairs of simulations (eclipse enabled and disabled) using the Weather Research and Forecasting (WRF) Model. The overall pattern and magnitude of the simulated cooling agree well with the observations and reveal that, in addition to the solar radiation deficit and cloud cover, low-level winds and the height of the planetary boundary layer are key determinants of the temperature changes and their spatial variability. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

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. Plain Language Summary: On the Antarctic Peninsula (AP), when ice shelves break up, glaciers flow faster from the land into the sea, leading to ice loss and increasing sea level rise. Surface warming is projected to double by 2050 over Antarctica and may have led to ice shelf collapse. Two phenomena that enhance surface warming are atmospheric rivers, (long corridors of moisture in the atmosphere) and leeside foehn effects (cooler and moist air advection on the upwind side that becomes warmer and drier when descending on the leeside). Here we study two combined atmospheric river and foehn events that led to surface warming on the AP, occurring in December 2018 and February 2022. The main warming mechanism in the northeastern AP during the nighttime was transfer of heat from the air to the ice surface (sensible heat flux), while the main mechanism during the daytime was intense sunlight, which was able to reach the surface because of clear skies on the opposite (lee) side caused by foehn. However, complicating the picture, there are gaps in the AP mountain range that let the atmospheric river through, allowing clouds to form on the other side, which then blocked some of the sunlight. Key Points: This study investigates the atmospheric river and foehn warming over the Antarctic Peninsula via observations and model simulationsAtmospheric rivers led to stronger precipitation on the upwind side and favored the foehn‐related sensible heat transfer on the leesideUnder the combined atmospheric rivers and foehn, shortwave radiation contributed the most to the ice surface warming, followed by sensible heat flux [ABSTRACT FROM AUTHOR]

A new meteorological dataset derived from records of Antarctic automatic weather stations (here called the AntAWS dataset) at 3 h, daily and monthly resolutions including quality control information is presented here. This dataset integrates the measurements of air temperature, air pressure, relative humidity, and wind speed and direction from 267 Antarctic AWSs obtained from 1980 to 2021. The AWS spatial distribution remains heterogeneous, with the majority of instruments located in near-coastal areas and only a few inland on the East Antarctic Plateau. Among these 267 AWSs, 63 have been operating for more than 20 years and 27 of them in excess of more than 30 years. Of the five meteorological parameters, the measurements of air temperature have the best continuity and the highest data integrity. The overarching aim of this comprehensive compilation of AWS observations is to make these data easily and widely accessible for efficient use in local, regional and continental studies; it may be accessed at 10.48567/key7-ch19 (Wang et al., 2022). This dataset is invaluable for improved characterization of the surface climatology across the Antarctic continent, to improve our understanding of Antarctic surface snow–atmosphere interactions including precipitation events associated with atmospheric rivers and to evaluate regional climate models or meteorological reanalysis products. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

Physiological and pathological processes including embryogenesis and tumorigenesis rely on the ability of individual cells to work collectively to form multicell patterns. In these heterogeneous multicell systems, cell-cell signaling induces differential adhesion between cells that leads to tissue-level patterning. However, the sensitivity of pattern formation to changes in the strengths of signaling or cell adhesion processes is not well understood. Prior work has explored these issues using synthetically engineered heterogeneous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models of these systems may be leveraged to explore more systematically how specific combinations of signaling and adhesion parameters can drive the emergence of unique patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for previously described cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. Systematic exploration of model predictions, some of which were experimentally validated, revealed how cell seeding parameters, the order of signaling events, probabilities of induced cadherin expression, and homotypic adhesion strengths affect pattern formation. Unsupervised clustering was also used to map combinations of signaling and adhesion parameters to these unique spheroid patterns predicted by the ABM. Finally, we demonstrated how the model may be deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern. Author summary: The remarkable ability of cells to self-organize is critical for the assembly of functional tissues during embryogenesis and is impaired by the molecular aberrations that lead to tumorigenesis and metastasis. Learning the rules of cellular self-assembly will provide a new way to understand such physiological and pathophysiological processes and create an instruction manual for designing tissues from scratch for therapeutic applications. Biologists have begun to learn the rules of self-assembly through reverse engineering–that is, through engineering biochemical circuits that control how cells adhere to one another. These approaches can yield simple, multi-cell structures that self-assemble into a core of one cell type surrounded by a shell of another cell type, for example. However, engineering more complex tissue patterns requires exploring a large domain of circuit structures and parameters. To facilitate this exploration in a guided and systematic manner, we created a computational model that predicts how mixtures of cells with different circuity for expressing adhesion proteins will interact to form varied patterns in spheroidal tissues comprised of hundreds of cells. Our model enables the design of internal molecular signaling circuitry that permits cells to be used as building blocks for self-assembled tissues with specific structures, and ultimately functions. [ABSTRACT FROM AUTHOR]

A new dataset of meteorological records from Antarctic automatic weather stations (here called AntAWS dataset) at 3-hourly, daily and monthly resolutions is constructed with quality control. This dataset compiles the measurements of air temperature, air pressure, relative humidity, and wind speed and direction from 216 AWSs available during 1980-2021. Their spatial distribution remains heterogeneous, with a majority of instrumented sites located on the coastal areas, and less at the inland East Antarctic Plateau. Among the 216 AWSs, 55 of them have the records spanning more than 20 years, and 25 of them spanning more than 30 years. Among the five meteorological parameters, the air temperature measurement data have the best continuity and the highest data integrity. The comprehensive compilation of AWS observations has the main aim to make them easy and time-saving to be used for local, regional and continental studies, which can be accessed at https://doi.org/10.48567/key7-ch19 (Wang et al., 2022). This dataset will be valuable for better characterizing surface climatology throughout the continent of Antarctica, improving our understanding of Antarctic surface snow-atmosphere interactions, and estimating regional climate models or meteorological reanalysis products. [ABSTRACT FROM AUTHOR]

Normally, the small amount of albumin which passes through the glomerular capillary wall is almost completely reabsorbed in the proximal tubule, via an endocytic mechanism, but the reabsorptive process can be overwhelmed if the filtered load of albumin is too large. To examine the factors that control the fractional reabsorption of albumin (f), we developed a mathematical model which assumes saturable endocytosis kinetics with a maximum reabsorptive capacity, [V.sub.max], and which includes the effects of flow and diffusion in the lumen. Limitations in albumin transport from the bulk tubule fluid to the endocytic sites at the bases of the microvilli had only a modest (8%) effect on the value of [V.sub.max] needed to fit micropuncture data on tubule albumin concentrations in rats. For moderate changes in filtered load, there was much greater sensitivity off to SNGFR than to the albumin concentration of the filtrate ([C.sub.0]). A 50% increase in SNGFR was predicted to cause four- to fivefold increases in albumin excretion in rats or humans. For large increases in [C.sub.0], as might result from defects in glomerular sieving, there was a threshold at which the reabsorptive process became saturated and f fell sharply. That threshold corresponded to sieving coefficients of [10.sup.-3] to [10.sup.-2], the higher values occurring at reduced SNGFR. The predictions of the present model contrast with those of one proposed recently by Smithies (32), which does not include the effects of tubule flow rate. tubule flow rate; protein microanalysis; endocytosis

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. [ABSTRACT FROM AUTHOR]

High surface temperatures are important in Antarctica because of their role in ice melt and sea level rise. We investigate a high temperature event in December 1989 that gave record temperatures in coastal East Antarctica between 60° and 100°E. The high temperatures were associated with a pool of warm lower tropospheric air with December temperature anomalies of >14°C that developed in two stages over the Amery Ice Shelf. First, there was near‐record poleward warm advection within an atmospheric river. Second, synoptically driven downslope flow from the interior reached unprecedented December strength over a large area, leading to strong descent and further warming in the coastal region. The coastal easterly winds were unusually deep and strong, and the warm pool was advected westwards, giving a short period of high temperatures at coastal locations, including a surface temperature of 9.3°C at Mawson, the second highest in its 66‐year record. Plain Language Summary: The Antarctic continent contains 90 percent of the world's freshwater ice, so any significant melt has serious implications for sea level rise. To date, most ice loss has occurred when warm ocean currents melt coastal ice from below. However, the higher air temperatures predicted for the coming decades are expected to increase surface melt, leading to an additional contribution to sea level rise. We present a case study of an event that occurred in coastal East Antarctica during December 1989 that illustrates how surface temperatures can rise to record levels leading to significant surface ice melt. The event unfolded in two stages. First, a narrow band of warm, moist air arrived in the coastal region from lower latitudes as an "atmospheric river", raising the temperature to a high, but not extreme level. Second, winds of record summer strength flowed from the interior of the Antarctic to the coastal region, drawing air down to lower levels of the atmosphere. This led to warming of the coastal air through compression, with it reaching 9.3°C at the Australian Mawson station, which was the second highest surface temperature in the 66‐year record. Key Points: Sustained horizontal warm advection toward the coast of East Antarctic via an atmospheric river led to marked warmingDownslope surface winds of record strength for the summer resulted in descent and adiabatic warming inland of the coastExtremely strong lower tropospheric easterly winds carried the warm air westwards leading to ice melt and record high surface temperatures [ABSTRACT FROM AUTHOR]

Networks of observations ideally provide adequate sampling of parameters to be monitored for climate and weather forecasting applications. This is a challenge for any network, but is particularly difficult in the harsh environment of the Antarctic continent. We evaluate a network design method providing objective information on station siting for optimal sampling of a variable, here taken to be surface air temperature. The method uses the concept of ensemble sensitivity to predict locations reducing the most total ensemble variance, that is, uncertainty, across the continent. The method is applied to a network of frequently-reporting stations, and validation is performed using results from assimilating station observations. A cost-efficient “offline” data assimilation framework is used to allow testing over a large sample of experiments, including a large number of randomly chosen networks that serve as a null hypothesis. Network design predictions agree well with observed error reductions from assimilation. The important role of stations on the East Antarctic Plateau in monitoring surface air temperature is evident in network design and data assimilation results, followed by stations in West Antarctica and the Ross Ice Shelf region. Antarctic coastal and Peninsula stations are found to provide the smallest information content integrated over the continent. Validation results are also robust to covariance localization, an essential factor for ensemble methods. Optimal networks outperform randomly chosen-networks in all cases, by up to nearly 50%, depending on the size of the network and the covariance localization distance. [ABSTRACT FROM AUTHOR]