Daily automated weather station (AWS) data from Climoor field site in Clocaenog Forest 2015-2016

Basic Information
Related Site
Clocaenog: Long-term monitoring site for climate change research - United Kingdom
Abstract

This dataset combines daily automated weather station (AWS) from the Climoor field site in Clocaenog forest, North East Wales The data are on relative humidity (percent), air temperature (degrees Celsius), rainfall (millimetres), air pressure (millibars), net radiation (millivolts), solar radiation (Kilowatts per square metre per second), photosynthetic active radiation (PAR), (micromol per square metre per second), wind speed (metres per second) and wind direction (degrees). These data are an extension for the Daily automated weather station dataset (1998-2015) for the time period July 2015 to August 2016. Data were not collected between 9th October 2015 and 3rd November 2015 due to problems with the sensors. Data are recorded in minute intervals. Up to January 2016 the data were averaged hourly, after January 2016 data were averaged half hourly. Data are then to averaged to daily values, which are reported here. Data collection, processing and quality checking was carried out by members of CEH Bangor staff.

The Climoor field experiment intends to answer questions regarding the effects of warming and drought on ecosystem processes. The reported data are collected to monitor site specific environmental conditions and their development with time. These data are important to interpret results that are collected from the climate change manipulations imposed in the field.
Keywords
eLTER VA
temperature manipulation
heathland and shrub
long term monitoring
air temperature
droughts
climate change
Contact
Sabine Reinsch
Metadata Provider
Sabine Reinsch
DOI
https://doi.org/10.5285/3a88f547-376d-4a7e-8817-9b5f9ccd5b82
UUID
dd2080f1-520b-47b9-a744-e4890e88c809
Dates
Date Range
Post date
Thursday, July 19, 2018 - 12:21
Last modified
Friday, November 29, 2019 - 11:31
Recommended citation
Recommended Citation
Reinsch, S.; Brooks, M.R.; Winterbourn, J.B.; Harvey, R.J.; Robinson, D.A.; Emmett, B.A. (2016). Daily automated weather station (AWS) data from Climoor field site in Clocaenog Forest 2015-2016. NERC Environmental Information Data Centre. https://doi.org/10.5285/3a88f547-376d-4a7e-8817-9b5f9ccd5b82
Geographic
Show details for observation location(s):
Clocaenog: Long-term monitoring site for climate change research
Additional information
Method Description
An automated weather station (AWS) that provides meteorological data is located on site ? from here in referred to as AWS met data. There is also a range of sensors in the treatment plots ? from here in referred to as micro-met plot data. As well as meteorological data, we have collected a range of abiotic and biotic data from within the plots. Summary of the data collected at the Clocaenog field site: Relative humidity, air temperature, Rainfall, Air pressure, Net radiation, Solar radiation, PAR, Wind speed and direction.

Initially the AWS sensors were placed at 1m above the soil surface, however after repeated thefts from the site in 2007, we had to mount it on a secured mast in a higher (4m) position. In the AWS, the following measures are taken with the indicated sensors:

Air temperature (degrees Celcius) measured with HMP 45C sensor from Campbell Scientific
Relative humidity (0-100%) measured with HMP45C from Campbell Scientific
Solar radiation (W per m2) measured with Skye SP1110 pyranometer from Skye Instruments
Photosynthetic active radiation (PAR in umol per m2 per sec) measured with SKP215 Quantum Sensor from Skye Instruments
Net radiation (W per m2) measured with NR-Lites from Campbell Scientific
Barometric pressure (mbar) measured with CS100 Barometer from Campbell Scientific
Rainfall (mm) measured with ARG 100 Tipping Bucket from Campbell Scientific
Wind speed and direction (m per sec) measured with Windsonic 2D Ultrasonic Anemomenter from Windsonic

For each of the sensors, measurements are sampled every minute and are provided in the form of hourly averages. Data quality control was performed using basic graphic tools in excel to visually examine the data and trends for all measurements. Although this method seems less exact than setting prescribed limits that data must fit within, it does allow for human interpretation and memory of conditions at the site ? for example, an automated limit in a script will fail to remember if it was a particularly cold week, etc.
Spatial Design
regular
Spatial Scale
plot
Principal and granted permission
Public » Free for access and use upon request