Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Smeets, Paul C J P; van den Broeke, Michiel R; Boot, Wim; Cover, Giorgio; Eijkelboom, Mark; Greuell, Wouter; Tijm-Reijmer, Carleen H; Snellen, Henk; van de Wal, Roderik S W (2022): Automatic weather station data from AWS9 collected during 2017 at the Greenland ice sheet along the K-transect, West-Greenland [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.950107, In: Smeets, PCJP et al. (2022): Automatic weather station data collected from 2003 to 2021 at the Greenland ice sheet along the K-transect, West-Greenland [dataset publication series]. PANGAEA, https://doi.org/10.1594/PANGAEA.947483

Always quote citation above when using data! You can download the citation in several formats below.

RIS CitationBibTeX CitationShow MapGoogle Earth

Keyword(s):
automatic weather station; Greenland; K-transect
Coverage:
Latitude: 67.052460 * Longitude: -48.251800
Date/Time Start: 2017-01-01T00:00:00 * Date/Time End: 2017-12-31T23:30:00
Minimum Elevation: 1500.0 m * Maximum Elevation: 1500.0 m
Event(s):
K-transect_AWS9 * Latitude: 67.052460 * Longitude: -48.251800 * Date/Time: 2003-08-27T20:30:00 * Elevation: 1500.0 m * Location: Greenland icesheet * Method/Device: Automatic weather station (AWS)
Comment:
The timeseries constitutes two different types of AWS. The first is a standard type modular AWS described extensively in https://doi.org/10.1080/15230430.2017.1420954.
The second type (operational from Aug2016 at AWS5, Aug2015 at AWS6, Aug2014 at AWS9, Aug2014 at AWS10) is a very compact IMAU design AWS consisting of one integrated module containing the datalogger, energy system and multiple sensors. In addition to the datalogger unit there are also 2 independent sensors dedicated to wind speed/direction and radiation (a Young prop/vane, CNR4 radiation sensor). All three units are mounted 3 to 4m above the surface at one mast boom.
The data set is therefore divided per station in two periods depending on AWS type which are identified in the dataset in the last column no. 16 being either 0 or 1 for the first and second type AWS unit (approx. 2003-2015 and 2016-2021, respectively). Exact timing of changing from AWS type 0 to 1 (as indicated in column 16) takes place during the yearly maintenance visits at the end of the melt season (around August/September) and is different for all stations. The timing of these visits is made available in column 15 (U battery voltage) as an outstanding single value 100 once every year.
The main difference between the two station types concerns the measurement of surface melt and sensor height using different type acoustic height rangers given in column 12 and a melt wire sensor in column 13.
---
In case of AWS type 0 the data in column 12 (acoustic height sensor) always indicates surface melt since the acoustic sensor was mounted separately on a long aluminium pole that was drilled next to the AWS mast into the ice. During the melt season increasing data values represent the increase of the height of the sensor above the surface and hence lowering of the ice surface due to ice melt (or snow in spring e.g.). During wintertime increasing/decreasing values on the other hand indicate snow height variations. During maintenance visits this sensor sometimes has to be mounted on a new aluminium pole in case the old pole threatens to melt out the following year. Re-mounting happens yearly at location AWS5 (lower ablation area), once every 2 to 3 years at AWS6. When this happens a large (negative) step change is visible in the data. As mentioned before, the exact timing of maintenance visits are indicated in column 15 by an incidental value of 100. At the locations of AWS9 (equilibrium line) and AWS10 (accumulation area) such step changes can sometimes also be present for various reasons (e.g. installation of a new sensor). Therefore most of the data should be used as yearly variations in between the yearly visits and not as a continuous timeseries.
In case of AWS type 1 the acoustic height ranger is installed inside the logger box and this was mounted at the AWS mast at the same height as the sensor boom. Therefore the data from this sensor now represents the sensor height variations but also snow height variations. In case of substantial ice melt at a location a draw wire sensor is installed (at sites 5 and 6) for which data is available in column 13. This column therefore only contains data in case of AWS type 1 at locations 5 and 6. The sensor is mounted at the AWS mast at about 1.5m height above the surface and contains a steel wire that is rolled into a housing using a spring and connected to a potentiometer. Upon installation a hole is drilled 10 to 15m deep into the ice surface and the steel wire is unrolled into the hole with a weight at its end thereby fixing it into the ice. When melt occurs the mast lowers along with the surface and the wire is rolled up and the distance change is measured indicative for ice melt – note tat this means that the data values decrease when melt occurs.
In summary, in case of the first AWS type (0 in column 16) data in column 12 represents ice surface melt or snow height variations and column 13 is empty. In case of the second AWS type (1 in column 16) the data inn column 12 represents the sensor height and snow height variations while column 13 gives the amount of ice melt. Note that given the characteristics of the sensors the acoustic data (column 12) increase while those for the draw wire (column 13) decrease as ice melt occurs.
---
Main limitations due to location climate conditions are described below, corrections mentioned are described in https://doi.org/10.1080/15230430.2017.1420954.
1) General issue for radiation measurements in polar regions: the measurements may be affected sometimes by riming - mostly during the winter and more likely at the higher locations where ventilation due to sustained katabatic winds is lacking (i.e., low winds, high humidity, temperatures below 0C).
2) The natural ventilation of the thermometer/hygrometer becomes gradually more insufficient when short wave radiation increase and wind speed decreases. A wind speed/radiation depending correction is applied to compensate for excess temperatures.
3) Longwave radiation sensors suffer from so-called window heating - a yearly instrument specific correction is calculated and applied.
4) Mast tilt affects (mainly) the short wave incoming radiation data. During the melt season AWS masts located in ablation areas can suffer from erratic tilt variations in time due to ice surface melt events. Up to date we did not apply a correction to the data.
5) Wind speed measurements from propellor vane anemometers (Young 05103) suffer from a high threshold value of 1 (m/s). Wind speed data values below 1 (m/s) should therefore be used with caution. Additionally - for wind speed below 0.1m/s we removed the wind direction data as it has a meaningless value.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1DATE/TIMEDate/TimeSmeets, Paul C J PGPS receiver u -blox NEO-7NGeocode
2Wind directiondddegSmeets, Paul C J PAnemometer, R.M. Young 05103
3Wind speedffm/sSmeets, Paul C J PAnemometer, R.M. Young 05103
4Short-wave downward (GLOBAL) radiationSWDW/m2Smeets, Paul C J PNet radiometer, Kipp & Zonen, CNR 4
5Short-wave upward (REFLEX) radiationSWUW/m2Smeets, Paul C J PNet radiometer, Kipp & Zonen, CNR 4
6Long-wave downward radiationLWDW/m2Smeets, Paul C J PNet radiometer, Kipp & Zonen, CNR 4
7Long-wave upward radiationLWUW/m2Smeets, Paul C J PNet radiometer, Kipp & Zonen, CNR 4
8Temperature, body, radiometerT body°CSmeets, Paul C J PNet radiometer, Kipp & Zonen, CNR 4
9Temperature, airTTT°CSmeets, Paul C J PNTC Thermistor
10Humidity, relativeRH%Smeets, Paul C J PSensirion SHT35
11Pressure, atmosphericPPPPhPaSmeets, Paul C J PFreescale Xtrinsic MPL3115A2
12Height, relativeHeight relmSmeets, Paul C J PSonic height ranger, MaxBotix HRXL MaxSonar WRSsurface melt OR observed sensor height (acoustic sensors)
13Temperature, technicalT tech°CSmeets, Paul C J PNTC Thermistorinternal loggerbox
14Logger voltageVlogVSmeets, Paul C J PInternal microprocessorcontains once a year an indicator value == 100 at the time that the yearly maintenance visit takes place
15IdentificationIDSmeets, Paul C J PAWS identifier, 0 - first AWS type (2003-2015), 1 - second AWS type (2016-2021), see dataset comment for details
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
241418 data points

Download Data

Download dataset as tab-delimited text — use the following character encoding:

View dataset as HTML (shows only first 2000 rows)