DROP: a DROught Probabilistic near-real time monitoring tool

DOI

DROP is a global land gridded dataset to monitoring DROught from Probabilistic approach. This enhances previously available climate datasets, which were static in nature or that not provide uncertainty estimations. An ensemble approach, similarly to weather/climate prediction studies, has been applied for DROP, where the members are different observations-based products (see https://drop.shinyapps.io/DROP/). Full source code is available from the gitlab repository https://github.com/marcoturco/DROP.

Identifier
DOI https://doi.org/10.23728/b2share.3146138a23ef48849d3f71ef332c086d
Source https://b2share.eudat.eu/records/3146138a23ef48849d3f71ef332c086d
Metadata Access https://b2share.eudat.eu/api/oai2d?verb=GetRecord&metadataPrefix=eudatcore&identifier=oai:b2share.eudat.eu:b2rec/3146138a23ef48849d3f71ef332c086d
Provenance
Creator Marco Turco, Sonia Jerez, Markus Donat, Andrea Toreti, Sergio M. Vicente-Serrano and Francisco J. Doblas-Reyes
Publisher EUDAT B2SHARE
Publication Year 2020
Rights Public Domain Mark (PD); info:eu-repo/semantics/openAccess
OpenAccess true
Contact turco.mrc(at)gmail.com
Representation
Format nc
Size 573.3 MB; 4 files
Version 1.0
Discipline 2.7.4.2 → Physical geography → Climatology