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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. [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]

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]

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]

Surface temperature measurements with naturally ventilated (NV) sensors over the Antarctic Plateau are largely subject to systematic errors caused by solar radiative heating. Here we examined the radiative heating error in Dronning Maud Land on the East Antarctic Plateau using both the newly installed automatic weather stations (AWSs) at NDF and Relay Station and the existing AWSs at Relay Station and Dome Fuji. Two types of NV shields were used in these AWSs: a multiplate radiation shield and a simple cylinder-shaped shield. In austral summer, the temperature bias between the force-ventilated (FV) sensor and the NV sensor never reached zero because of continuous sunlight. The hourly mean temperature errors reached up to 8°C at noon on a sunny day with weak wind conditions. The errors increased linearly with increasing reflected shortwave radiation and decreased nonlinearly with increasing wind speed. These features were observed in both the multiplate and the cylinder-shaped shields. The magnitude of the errors of the multiplate shield was much larger than that of the cylinder-shaped shield. To quantify the radiative errors, we applied an existing correction model based on the regression approach and successfully reduced the errors by more than 70% after the correction. This indicates that we can use the corrected temperature data instead of quality controlled data, which removed warm bias during weak winds in inland Dronning Maud Land. [ABSTRACT FROM AUTHOR]

A World Meteorological Organization (WMO) Extremes Evaluation Committee investigated an observation of −69.6 °C by Klinck Automatic Weather Station (AWS) in Greenland on 22 December 1991 as the lowest temperature observed in Greenland, thereby making it the lowest recorded near‐surface air temperature for the Northern and Western Hemispheres and for WMO Region VI. The committee examined the metadata and observations of the station as well as the regional synoptic circulation. The committee concluded that the observation is credible in terms of instrument calibration, monitoring of the station and the synoptic situation. Consequently, the WMO Rapporteur accepted the observation as the officially lowest observed near‐surface air temperature for Greenland, the Northern and Western Hemisphere and for WMO Region VI. As a supplement to this investigation, the committee also recommends that opportunities be investigated such that AWS data from Greenland can be efficiently incorporated into real‐time weather forecasts and hence into reanalysis datasets. [ABSTRACT FROM AUTHOR]

Recent analyses of weather station data and satellite thermal mapping of the upper East Antarctic Plateau in winter has revealed several sites with surface snow temperatures below -95°C. These sites are found near but not on the ice divide ridge, particularly on the upper southern flank at elevations above 3800 m, within local topographic depressions of a few meters depth and a few kilometers horizontal scale. Although no weather stations exist in the coldest temperature locations, nearby automated weather stations (AWS) at Pole of Inaccessibility, Plateau B, and Dome A, record conditions that broadly corroborate the satellite thermal mapping, although they indicate very strong near-surface air temperature gradients due to intense thermal air inversion. Given that the conditions leading to inversion are common in Antarctic winter throughout the continent, and that snowfall constantly changes the measurement height on automated weather stations (until they are reset by a visiting team), we explore the potential for automated station data to appear to present cooling trends as snow accumulation moves the temperature sensor closer to the surface. Moreover, we examine the potential for local topography to control the near-surface gradient by causing the coldest air to pool (in a topographic low) or flow rapidly away (in a local topographic dome or ridge). A parameterization of the air gradients in winter conditions is likely necessary to understand AWS data when used for climate trend analysis. Moreover, AWS on ice sheets should include snow height measurement sensors and dual temperature sensors at different heights to allow estimation of, and correction for, the air temperature gradient. [ABSTRACT FROM AUTHOR]