Work

Data for journal article: "Automated precipitation monitoring with the Thies disdrometer: Biases and ways for improvement"

Year: 2020

Type: dataset

Abstract: This dataset contains data used for the journal article" Automated precipitation monitoring with the Thies disdrometer: Biases and ways for improvement" submitted to Atmospheric Measurement Techniques.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.3895296

Authors: Fehlmann, Michael, Rohrer, Mario, von Lerber, Annakaisa, Stoffel, Markus

Institutions: University of Geneva, Finnish Meteorological Institute

Language: English

Topic: Precipitation Measurement and Analysis

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: green

Funder: European Commission

Award: EnhANcing emergencY management and response to extreme WeatHER and climate Events

OpenAlex ID: W4393463449

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