Daily automated weather station (AWS) data from Climoor fieldsite in Clocaenog Forest 1999-2015

Basic Information
Related Site
Clocaenog: Long-term monitoring site for climate change research - United Kingdom
Abstract
This dataset contains daily automated weather station (AWS) data from the Climoor field site in Clocaenog forest, North East Wales. The data are air temperature (mean, minimum and maximum), rainfall, net radiation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction. The dataset has been quality checked, and incorrect or missing values removed, data has not been infilled. Data runs from 12/6/1999 until 30/06/2015, no data was collected March 2006 and June 2008. Air temperature, rainfall and wind speed and direction were recorded since June 1999. Measurements of relative humidity, air pressure, net and solar radiation and PAR started in June 2008. Since June 2008, data are recorded in minute intervals, averaged to hourly, then to daily means that are reported here. 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/10.5285/7f2a4935-a9e8-47dc-b126-93d9e19496bd
UUID
2a879cc2-5335-45b9-afdf-426090ba1c8c
Dates
Date Range
Post date
Thursday, July 19, 2018 - 11:51
Last modified
Friday, November 29, 2019 - 11:31
Recommended citation
Recommended Citation
Reinsch, S.; Sowerby, A.; Emmett, B.A. (2015). Daily automated weather station (AWS) data from Climoor fieldsite in Clocaenog Forest 1999-2015. NERC Environmental Information Data Centre. https://doi.org/10.5285/7f2a4935-a9e8-47dc-b126-93d9e19496bd
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