Publication Date:
2023-03-01
Description:
Long-term, continuous in situ observations of the near-surface atmospheric boundary layer are critical for many weather and climate applications. Although there is a proliferation of surface stations globally, especially in and around populous areas, there are notably fewer tall meteorological towers with multiple instrumented levels. This is particularly true in remote and extreme environments such as the Eastern Antarctic plateau. In the article, we present and analyze 10 years (2010-2019) of data from 6 levels of meteorological instrumentation mounted on a 45-m tower located at Dome C, East Antarctica near the Concordia research station, producing a unique climatology of the near-surface environment. Large seasonal differences are evident in the monthly mean temperature and wind data, depending on the presence or absence of solar surface forcing. Strong vertical temperature gradients (inversions) frequently develop in calm, winter conditions, while vertical convective mixing occurs in the summer leading to near-uniform temperatures along the tower. Seasonal variation in wind speed is much less notable at this location than the temperature variation as the winds are less influenced by the solar cycle; there are no katabatic winds as Dome C is quite flat. Harmonic analysis confirms that most of the energy in the power spectrum is at diurnal, annual and semi-annual scales. Analysis of observational uncertainty and comparison to reanalysis data from ERA-5 indicate that wind speed is particularly difficult to measure at this location.
Keywords:
Antarctic Plateau; Antartic field data for CALibration and VAlidation of meteorological and climate models and satellite retrievals, Antarctic Coast to Dome C; boundary layer; CALVA; Date/Time local; DOME_C_CALVA; Dome C, Antarctica; meteorology; Profile; Temperature; Tower; Weather station/meteorological observation; wind; Wind monitor, R.M. Young, model 05103; Wind speed; WST
Type:
Dataset
Format:
text/tab-separated-values, 911449 data points
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