Selected Baseline Prediction Data For Impact Studies (D4.1)

About this document Deliverable: D4.1 Work package in charge: WP4 Actual delivery date for this deliverable: Project‐month 6 (June 2017) Dissemination level: The general public (PU) Abstract During the course of the project, it was realized that the data needed by the WP5 case studies can also be pr...

Full description

Bibliographic Details
Main Authors: Matei, Daniela, Lesser, Pamela, Toivonen, Jusu, Kolstad, Erik, Payne, Mark, Aarnes, Øivin, Keil, Kathrin, Valeeva, Vilena, Ballester, Joan, Baehr, Johanna, Bearzotti, Chiara
Format: Text
Language:English
Published: Zenodo 2017
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.1317903
https://zenodo.org/record/1317903
id ftdatacite:10.5281/zenodo.1317903
record_format openpolar
spelling ftdatacite:10.5281/zenodo.1317903 2023-05-15T15:00:43+02:00 Selected Baseline Prediction Data For Impact Studies (D4.1) Matei, Daniela Lesser, Pamela Toivonen, Jusu Kolstad, Erik Payne, Mark Aarnes, Øivin Keil, Kathrin Valeeva, Vilena Ballester, Joan Baehr, Johanna Bearzotti, Chiara 2017 https://dx.doi.org/10.5281/zenodo.1317903 https://zenodo.org/record/1317903 en eng Zenodo https://dx.doi.org/10.5281/zenodo.1317902 Open Access Creative Commons Attribution 4.0 https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess CC-BY Text Project deliverable article-journal ScholarlyArticle 2017 ftdatacite https://doi.org/10.5281/zenodo.1317903 https://doi.org/10.5281/zenodo.1317902 2021-11-05T12:55:41Z About this document Deliverable: D4.1 Work package in charge: WP4 Actual delivery date for this deliverable: Project‐month 6 (June 2017) Dissemination level: The general public (PU) Abstract During the course of the project, it was realized that the data needed by the WP5 case studies can also be provided by the WP1 “Improving seasonal long range forecast skill of risks for hazardous weather and climate events” and not only by the WP4 “Enhancing the capacity of seasonal‐to‐decadal predictions in the Arctic and over the Northern Hemisphere”. This was realized at the kick‐off meeting, when the timescales of interest emerged. Since WP`1 focuses on the subseasonal to seasonal scale, and both of the forecast systems used in WP1 (that is the CMCC system and the MPI‐ESM based system) offer initialized hindcast experiments from (sub)seasonal to decadal, all case studies focusing on seasonal predictability established connections to WP1 at the kick‐off meeting. That is why this deliverable has now seen the broader interaction of several teams in WP1 and WP5 as well. This deliverable indicates how the five case studies have received data from WP1/WP4 and how these data are currently being used for the implementation of the activities in each case study. 1. Winter tourism centers in Finland 2. Temperature‐related human mortality in European regions 3. Extreme weather risks to maritime activities 4. Climate services for marine fisheries 5. Russian Arctic resource extraction More information on these case studies can be found here: http://www.blueaction.eu/index.php?id=4139 : The Blue-Action project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 727852 http://www.blueaction.eu/ Text Arctic DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
description About this document Deliverable: D4.1 Work package in charge: WP4 Actual delivery date for this deliverable: Project‐month 6 (June 2017) Dissemination level: The general public (PU) Abstract During the course of the project, it was realized that the data needed by the WP5 case studies can also be provided by the WP1 “Improving seasonal long range forecast skill of risks for hazardous weather and climate events” and not only by the WP4 “Enhancing the capacity of seasonal‐to‐decadal predictions in the Arctic and over the Northern Hemisphere”. This was realized at the kick‐off meeting, when the timescales of interest emerged. Since WP`1 focuses on the subseasonal to seasonal scale, and both of the forecast systems used in WP1 (that is the CMCC system and the MPI‐ESM based system) offer initialized hindcast experiments from (sub)seasonal to decadal, all case studies focusing on seasonal predictability established connections to WP1 at the kick‐off meeting. That is why this deliverable has now seen the broader interaction of several teams in WP1 and WP5 as well. This deliverable indicates how the five case studies have received data from WP1/WP4 and how these data are currently being used for the implementation of the activities in each case study. 1. Winter tourism centers in Finland 2. Temperature‐related human mortality in European regions 3. Extreme weather risks to maritime activities 4. Climate services for marine fisheries 5. Russian Arctic resource extraction More information on these case studies can be found here: http://www.blueaction.eu/index.php?id=4139 : The Blue-Action project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 727852 http://www.blueaction.eu/
format Text
author Matei, Daniela
Lesser, Pamela
Toivonen, Jusu
Kolstad, Erik
Payne, Mark
Aarnes, Øivin
Keil, Kathrin
Valeeva, Vilena
Ballester, Joan
Baehr, Johanna
Bearzotti, Chiara
spellingShingle Matei, Daniela
Lesser, Pamela
Toivonen, Jusu
Kolstad, Erik
Payne, Mark
Aarnes, Øivin
Keil, Kathrin
Valeeva, Vilena
Ballester, Joan
Baehr, Johanna
Bearzotti, Chiara
Selected Baseline Prediction Data For Impact Studies (D4.1)
author_facet Matei, Daniela
Lesser, Pamela
Toivonen, Jusu
Kolstad, Erik
Payne, Mark
Aarnes, Øivin
Keil, Kathrin
Valeeva, Vilena
Ballester, Joan
Baehr, Johanna
Bearzotti, Chiara
author_sort Matei, Daniela
title Selected Baseline Prediction Data For Impact Studies (D4.1)
title_short Selected Baseline Prediction Data For Impact Studies (D4.1)
title_full Selected Baseline Prediction Data For Impact Studies (D4.1)
title_fullStr Selected Baseline Prediction Data For Impact Studies (D4.1)
title_full_unstemmed Selected Baseline Prediction Data For Impact Studies (D4.1)
title_sort selected baseline prediction data for impact studies (d4.1)
publisher Zenodo
publishDate 2017
url https://dx.doi.org/10.5281/zenodo.1317903
https://zenodo.org/record/1317903
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation https://dx.doi.org/10.5281/zenodo.1317902
op_rights Open Access
Creative Commons Attribution 4.0
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.1317903
https://doi.org/10.5281/zenodo.1317902
_version_ 1766332795004649472