Date (Creation)

2020-04-27

Date (Revision)

2020-04-27

Date (Publication)

2020-04-27

Date (released)

2020-04-27

Edition

2.0

Unique resource identifier

https://doi.org/10.5285/4337ee2a-b428-4f78-a694-7c8b8e41d4bf

Codespace

doi

Unique resource identifier

GB/NERC/BAS/PDC/01324

Codespace

https://data.bas.ac.uk/

Unique resource identifier

NE/L005409/1

Codespace

award

Other citation details

Please cite this item as: 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

Credit

No credit.

Status

Completed

Point of contact

Organisation name	Individual name	Electronic mail address	Role
Swansea University	Bevan, Suzanne		Author
Institute for Marine and Atmospheric research Utrecht (IMAU)	Kuipers Munneke, Peter		Author
Swansea University	Luckman, Adrian		Author
Institute for Marine and Atmospheric research Utrecht (IMAU)	Smeets, Paul		Author
Institute for Marine and Atmospheric research Utrecht (IMAU)	van den Broeke, Michiel		Author
NERC EDS UK Polar Data Centre		PDCServiceDesk@bas.ac.uk	Point of contact

Maintenance and update frequency

As needed

Maintenance note

Completed

Global Change Master Directory (GCMD) Science Keywords

• EARTH SCIENCE > Atmosphere > Atmospheric Pressure > Surface Pressure
• EARTH SCIENCE > Atmosphere > Atmospheric Temperature > Air Temperature
• EARTH SCIENCE > Atmosphere > Atmospheric Water Vapor > Humidity
• EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Glaciers
• EARTH SCIENCE > Climate Indicators > Air Temperature Indices
• EARTH SCIENCE > Climate Indicators > Humidity Indices

Theme

• Automatic weather station

• Larsen C Ice Shelf

Place

• Cabinet Inlet, Larsen C Ice Shelf Antarctica

GEMET - INSPIRE themes, version 1.0

• Atmospheric conditions
• Elevation
• Meteorological geographical features

Access constraints

Other restrictions

Other constraints

no limitations to public access

Access constraints

Other restrictions

Other constraints

no limitations

Use constraints

License

Other constraints

Open Government Licence v3.0

Use constraints

Other restrictions

Other constraints

This data is governed by the NERC Data Policy: https://www.ukri.org/who-we-are/nerc/our-policies-and-standards/nerc-data-policy/

Use constraints

Other restrictions

Other constraints

This data is governed by the NERC data policy and supplied under Open Government Licence v3

Use constraints

Other restrictions

Other constraints

No restrictions apply.

Unique resource identifier

doi

Codespace

doi

Association Type

Cross reference

Unique resource identifier

doi

Codespace

doi

Association Type

Cross reference

Unique resource identifier

doi

Codespace

doi

Association Type

Cross reference

Unique resource identifier

url

Codespace

url

Association Type

Cross reference

Spatial representation type

Text, table

Language

English

Character set

UTF8

Topic category

• Climatology, meteorology, atmosphere
• Environment

Begin date

2014-11-25

End date

2017-11-13

Supplemental Information

It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk.

Title

European Petroleum Survey Group (EPSG) Geodetic Parameter Registry

Date (Publication)

2008-11-12

Cited responsible party

Organisation name	Individual name	Electronic mail address	Role
European Petroleum Survey Group		EPSGadministrator@iogp.org	Publisher

Unique resource identifier

urn:ogc:def:crs:EPSG::3031

Version

6.18.3

Hierarchy level

Dataset

Statement

Methodology:

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).

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.

Data 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.

Metadata

File identifier

4337ee2a-b428-4f78-a694-7c8b8e41d4bf XML

Metadata language

English

Character set

UTF8

Hierarchy level

Dataset

Hierarchy level name

dataset

Date stamp

2020-04-27

Metadata standard name

ISO 19115 Geographic Information - Metadata

Metadata standard version

ISO 19115:2003(E)

Metadata author

Organisation name	Individual name	Electronic mail address	Role
NERC EDS UK Polar Data Centre		polardatacentre@bas.ac.uk	Point of contact