Abstract:
The data consists of 30 minute observations recorded by an automatic weather station (iWS 18) in Cabinet Inlet on Larsen C Ice Shelf on the Antarctic Peninsula. The iWS consists of a custom-built weather station unit, assembled at the Institute of Marine and Atmospheric research Utrecht (IMAU). There are sensors for air temperature, surface air pressure, relative humidity, as well as a GPS, an acoustic snow height sensor, an ARGOS communication antenna, and three Lithium batteries that fuel the unit when solar radiation is absent. The unit is complemented by a propeller-vane Young anemometer measuring wind direction and speed. Additionally, all radiation fluxes are measured with a Kipp and Zonen CNR4 radiometer. This dataset runs from 25 November 2014 to 13 November 2017.
Funding was provided by the NERC grant NE/L005409/1.
Keywords:
Automatic weather station, Larsen C Ice Shelf
Bevan, S., Kuipers Munneke, P., Luckman, A., Smeets, P., & van den Broeke, M. (2020). Dataset from iWS 18 in Cabinet Inlet, Larsen C Ice Shelf, Antarctica, 2014-2017 - VERSION 2.0 (Version 2.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/4337ee2a-b428-4f78-a694-7c8b8e41d4bf
| Access Constraints: | No restrictions apply. |
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| Use Constraints: | This data is governed by the NERC data policy http://www.nerc.ac.uk/research/sites/data/policy/ and supplied under Open Government Licence v3 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/. |
| Creation Date: | 2020-04-27 |
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| Dataset Progress: | Complete |
| Dataset Language: | English |
| ISO Topic Categories: |
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| Parameters: |
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| Personnel: | |
| Name | UK PDC |
| Role(s) | Metadata Author |
| Organisation | British Antarctic Survey |
| Name | Suzanne Bevan |
| Role(s) | Investigator |
| Organisation | Swansea University |
| Name | Peter Kuipers Munneke |
| Role(s) | Investigator |
| Organisation | Institute for Marine and Atmospheric research Utrecht (IMAU) |
| Name | Adrian Luckman |
| Role(s) | Investigator |
| Organisation | Swansea University |
| Name | Paul Smeets |
| Role(s) | Investigator |
| Organisation | Institute for Marine and Atmospheric research Utrecht (IMAU) |
| Name | Michiel van den Broeke |
| Role(s) | Investigator |
| Organisation | Institute for Marine and Atmospheric research Utrecht (IMAU) |
| Parent Dataset: | N/A |
| Reference: | Elvidge, A.D., Kuipers Munneke, P., King, J.C., Renfrew, I.A., Gilbert, E., 2020. Atmospheric drivers of melt on Larsen C Ice Shelf: surface energy budget regimes and the impact of foehn. Journal Of Geophysical Research, accepted. Smeets, P.C., Kuipers Munneke, P., Van As, D., van den Broeke, M.R., Boot, W., Oerlemans, H., Snellen, H., Reijmer, C.H. and van de Wal, R.S., 2018. The K-transect in west Greenland: Automatic weather station data (1993-2016). Arctic, Antarctic, and Alpine Research, 50(1), p.S100002, DOI: 10.1080/15230430.2017.1420954 Bevan, S.L., Luckman, A.J., Kuipers Munneke, P., Hubbard, B., Kulessa, B. and Ashmore, D.W., 2018. Decline in surface melt duration on Larsen C Ice Shelf revealed by the advanced scatterometer (ASCAT). Earth and Space Science, 5(10), pp.578-591, DOI: 10.1029/2018ea000421 Kuipers Munneke, P., Van den Broeke, M.R., Reijmer, C.H., Helsen, M.M., Boot, W., Schneebeli, M. and Steffen, K., 2009. The role of radiation penetration in the energy budget of the snowpack at Summit, Greenland. The Cryosphere, 3, 155-165, DOI: 10.5194/tc-3-155-2009 |
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| Quality: | A number of corrections and adjustments to the raw data were applied for this dataset. For further details see Elvidge et al. (2020). 1) The temperature sensor is not artificially ventilated. This leads to a positive bias in temperature measurements under conditions of high insolation and low wind speed. Simultaneous observations from a thin-wire thermocouple provided a correction procedure, detailed in Smeets et al. (2018). 2) The relative humidity sensor is placed within the unit and experiences elevated temperature under sunny conditions. Internally-observed temperature of the sensor allows the calculation of a dew point, which gives a relative humidity for the observed air temperature. Next, relative humidity is corrected for observations over ice rather than over water. And finally, a well-known underestimation of RH-observations at low temperatures is corrected for by fitting a polynomial through the upper percentile of data and define that polynomial as a RH of 100%. Relative humidity can sometimes greatly exceed 100%, especially in very cold conditions. It is unknown if this is a sensor characteristic or real supersaturation. If required, RH can be capped at 100% without a large error in the corresponding absolute, specific humidity. 3) Longwave radiation observations are corrected for the internal instrument temperature, and for window heating under high insolation conditions. 4) Acoustic snow height observations are corrected for the dependency of sound propagation on air temperature. 5) A few small data 30- to 60-minute data gaps were filled by linear interpolation. |
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| Lineage: | IMAU iWS 18 has sensors for air and surface temperature, air pressure and humidity, as well as an acoustic snow height sensor, a propeller-vane anemometer measuring wind direction and speed, and a radiometer for measuring downward and upward shortwave and longwave radiative fluxes. The Incoming and Reflected SW and LW fluxes provided are corrected values. A bulk-algorithm-based SEB model (described in Kuipers Munneke et al., 2009) has been used to derive surface sensible and latent heat fluxes and the ground heat flux. The energy available for melt is also derived from this model, given as the SEB residual when the surface temperature, Tsfc, is above freezing point. Compared to direct eddy correlation observations of turbulent fluxes (e.g., by using a 3-D ultrasonic anemometer), the bulk method that we apply to the AWS observations yields similar results with a root-mean-square difference of typically 3-4 W m-2 at Antarctic sites experiencing frequent air flow (e.g. Van den Broeke et al., 2005). With the wind sensor being at a height of 2-3 m, the bulk method captures most of the turbulent eddies while at the same time not severely violating the assumption of constant flux in the layer between the surface and the instrument height. For further details see Elvidge et al. (2020). | |
| Temporal Coverage: | |
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| Start Date | 2014-11-25 |
| End Date | 2017-11-13 |
| Spatial Coverage: | |
| Latitude | |
| Southernmost | -66.4023 |
| Northernmost | -66.4023 |
| Longitude | |
| Westernmost | -63.3711 |
| Easternmost | -63.3711 |
| Altitude | |
| Min Altitude | ~ 70 m above mean sea level |
| Max Altitude | ~ 70 m above mean sea level |
| Depth | |
| Min Depth | N/A |
| Max Depth | N/A |
| Location: | |
| Location | Antarctica |
| Detailed Location | Cabinet Inlet, Larsen C Ice Shelf |
| Data Collection: | The iWS consists of a custom-built weather station unit, assembled at the Institute of Marine and Atmospheric research Utrecht (IMAU). The unit consists of a 3D-printed plastic housing with an array of miniature solar panels on top. In the housing, there are sensors for air temperature, surface air pressure, relative humidity, as well as a GPS, an acoustic snow height sensor, an ARGOS communication antenna, and three Lithium batteries that fuel the unit when solar radiation is absent. The unit is complemented by a propeller-vane Young anemometer measuring wind direction and speed. Additionally, all radiation fluxes are measured with a Kipp and Zonen CNR4 radiometer. Due to malfunctioning, no subsurface temperature measurements are available. |
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| Distribution: | |
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| Distribution Media | Online Internet (HTTP) |
| Distribution Size | 7.9 MB |
| Distribution Format | ASCII |
| Fees | N/A |
| Data Storage: | The dataset format is described below: Date Year Hour [hhmm] Time [decimal day of year] Air temperature [C] Relative humidity [%] Surface air pressure [hPa] Horizontal wind speed [m/s] Wind direction [deg] Surface temperature [C] Incoming SW [W/m2] Reflected SW [W/m2] Downwelling LW [W/m2] Upwelling LW [W/m2] Sensible heat flux [W/m2] Latent heat flux [W/m2] Ground heat flux [W/m2] Surface melt flux [W/m2] Instrument height [m] Snow depth [m] The date represents the end of a 30-minute interval. So observations reported for 12:30 are instantaneous values of air temperature, relative humidity, surface air pressure, and instrument height/snow depth, and the average value of the other parameters between 12:00 and 12:30. Incoming SW, Downwelling LW, Sensible Heat and Latent Heat fluxes are all expressed as positive values when directed downwards (towards the surface). Reflected SW, Upwelling LW and Ground heat fluxes are all expressed as positive values when directed upwards (away from the surface for Reflected SW and Upwelling LW, and towards the surface for Ground heat). Instrument height is the height between the weather station unit and the snow surface, as measured with an acoustic snow height ranger. Instrument height represents the height above the surface of the temperature, humidity, pressure, and radiation sensors. For the wind sensor, add +0.40 m. Snow depth is a virtual quantity (no initial snow depth is known) that varies proportional to the observed instrument height. |