PAR003 Optical disdrometer data at Erasmus MC in Rotterdam

DOI:10.4121/30081ee3-a6ff-4b08-933e-6ec2ddc1a70c.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/30081ee3-a6ff-4b08-933e-6ec2ddc1a70c

Datacite citation style

Schleiss, Marc; Castro, Andre; Mackenzie, Rob; Sourzac, Mahaut (2024): PAR003 Optical disdrometer data at Erasmus MC in Rotterdam. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/30081ee3-a6ff-4b08-933e-6ec2ddc1a70c.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Delft University of Technology logo

Usage statistics

27
views
47
downloads

Geolocation

Wytemaweg 10, 3015 CN Rotterdam
lat (N): 51.912549818
lon (E): 4.4703434351
view on openstreetmap

Time coverage

From 2022-07 to 2022-09

Licence

CC BY 4.0

Interoperability

Description: In-situ measurements of raindrop size distributions, fall velocities, drop number concentrations and surface rain rates recorded by an OTT Parsivel2 disdrometer named "PAR003" on the roof of the Erasmus MC in Rotterdam, at a height of approx. 20 meters. This dataset was collected during the campaign RITA2022, which took place in the city of Rotterdam between August and September 2022. The RITA2022 campaign involved many other sensors from TU Delft and partners of the Ruisdael consortium. Some additional data collected before and after the official campaign dates are included as well.


Format: Each NetCDF file covers a full month of observations. The temporal resolution is 1 minute. Data are provided "as is", without any post-processing. The NetCDF files contain all relevant information about all the variables, attributes and units. The global attributes of the NetCDF files contain important information about the type of sensor, logging software, project contributors and history of the dataset.


Relevance: Optical disdrometer data are useful for studying the type, dynamics and microphysics of precipitation from the perspective of a fixed observer on the ground. The data can be used to help calibrate weather radars, improve quantitative precipitation estimates, calculate the absorption/attenuation/propagation of electromagnetic signals through the atmosphere, and quantify important physical quantities such as liquid water content, rain amount, intensity and kinetic energy.

History

  • 2024-10-04 first online, published, posted

Publisher

4TU.ResearchData

Format

NetCDF

Funding

  • Ruisdael Observatory (grant code 184.034.015) [more info...] Dutch Research Council (NWO)

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote Sensing

DATA

Files (4)