Standardized precipitation measurements within ICOS: rain, snowfall and snow depth: a review
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1
Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, United States
2
Institute of Bio- and Geosciences, Agrosphere (IBG-3), Forschungszentrum Jülich, Wilhelm-Johnen-Straße, 52428 Jülich, Germany
3
Institute of Hydrology and Meteorology, Technische Universität Dresden, 01062 Dresden, Germany
4
Department of Physics, University of Helsinki, 00014 Helsinki, Finland
5
Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Skogsmarksgränd,
SE-901 83 Umeå, Sweden
6
Department of Environmental System Sciences, Institute of Agricultural Sciences, ETH Zurich, Universitaetsstrasse 2,
8092 Zurich, Switzerland
7
Mazingira Centre, International Livestock Research Institute (ILRI), P.O. Box 30709, 00100, Nairobi, Kenya
8
Department of Innovation in Biological Agro-food and Forest Systems, University of Tuscia, Via San Camillo de Lellis,
01100 Viterbo, Italy
9
Department of Matters and Energy Fluxes, CzechGlobe, Global Change Research Institute CAS, 603 00 Brno, Czech Republic
Publication date: 2018-11-18
Int. Agrophys. 2018, 32(4): 607-617
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ABSTRACT
Precipitation is one of the most important abiotic variables related to plant growth. Using standardised measurements improves the comparability and quality of precipitation data as well as all other data within the Integrated Carbon Observation System network. Despite the spatial and temporal variation of some types of precipitation, a single point measurement satisfies the requirement as an ancillary variable for eddy covariance measurements. Here the term precipitation includes: rain, snowfall (liquid water equivalent) and snow depth, with the latter two being of interest only where occurring. Weighing gauges defined as Integrated Carbon Observation System standard with the capacity of continuously measuring liquid and solid precipitation are installed free-standing, away from obstacles obstructing rain or snowfall. In order to minimise wind-induced errors, gauges are shielded either naturally or artificially to reduce the adverse effect of wind speed on the measurements. Following standardised methods strengthens the compatibility and comparability of data with other standardised environmental observation networks while opening the possibility for synthesis studies of different precipitation measurement methodologies and types including a wide range of ecosystems and geolocations across Europe.