Home > Publications database > Standardized precipitation measurements within ICOS: rain, snowfall and snow depth: a review > print |
001 | 859076 | ||
005 | 20210131030854.0 | ||
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100 | 1 | _ | |a Dengel, Sigrid |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
245 | _ | _ | |a Standardized precipitation measurements within ICOS: rain, snowfall and snow depth: a review |
260 | _ | _ | |a Lublin |c 2018 |b IA PAS |
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520 | _ | _ | |a 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. |
536 | _ | _ | |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) |0 G:(DE-HGF)POF3-255 |c POF3-255 |f POF III |x 0 |
536 | _ | _ | |a ICOS - Integrated Carbon Observation System (211574) |0 G:(EU-Grant)211574 |c 211574 |f FP7-INFRASTRUCTURES-2007-1 |x 1 |
536 | _ | _ | |a IDAS-GHG - Instrumental and Data-driven Approaches to Source-Partitioning of Greenhouse Gas Fluxes: Comparison, Combination, Advancement (BMBF-01LN1313A) |0 G:(DE-Juel1)BMBF-01LN1313A |c BMBF-01LN1313A |f Nachwuchsgruppen Globaler Wandel 4+1 |x 2 |
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700 | 1 | _ | |a Hehn, Markus |0 P:(DE-HGF)0 |b 3 |
700 | 1 | _ | |a Kolari, Pasi |0 P:(DE-HGF)0 |b 4 |
700 | 1 | _ | |a Löfvenius, Mikaell Ottosson |0 P:(DE-HGF)0 |b 5 |
700 | 1 | _ | |a Merbold, Lutz |0 P:(DE-HGF)0 |b 6 |
700 | 1 | _ | |a Nicolini, Giacomo |0 P:(DE-HGF)0 |b 7 |
700 | 1 | _ | |a Pavelka, Marian |0 P:(DE-HGF)0 |b 8 |
773 | _ | _ | |a 10.1515/intag-2017-0046 |g Vol. 32, no. 4, p. 607 - 617 |0 PERI:(DE-600)2235638-1 |n 4 |p 607 - 617 |t International agrophysics |v 32 |y 2018 |x 2300-8725 |
856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/859076/files/Dengel_graf_2018_IntAgrophys_ICOS.pdf |
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