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PROCEED

PROCess-based sEamless development of useful Earth system predictions over lanD

Total Cost €

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EC-Contrib. €

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Partnership

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Project "PROCEED" data sheet

The following table provides information about the project.

Coordinator
KONINKLIJK NEDERLANDS METEOROLOGISCH INSTITUUT-KNMI 

Organization address
address: UTRECHTSEWEG 297
city: DE BILT
postcode: 3731 GA
website: www.knmi.nl

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Project website http://projects.knmi.nl/proceed/
 Total cost 177˙598 €
 EC max contribution 177˙598 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-01-01   to  2019-07-03

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KONINKLIJK NEDERLANDS METEOROLOGISCH INSTITUUT-KNMI NL (DE BILT) coordinator 177˙598.00

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 Project objective

The modelling community achieved steady progress in dynamical climate prediction using Earth System models and the last decade has seen an accelerated development for the land surface component. This has led to predictions that are now considered useful for some societal applications over “hot-spot” land areas such as the Euro-Mediterranean. However, forecasts performance over land is still substantially weaker compared with ocean, due to the lack of observations, which has hampered the development of well-constrained land processes models. While benefiting from daily verification, the models used for the prediction of the short time-scales (from weather to seasons) include only that part of the surface variability for which observations are available and that can be modeled/initialized to positively contribute to the forecasts (verification-based approach). As a consequence, they unavoidably lack some processes such as those related to ecosystems and their variability. On the other hand, longer time-scales (interannual to centennial) models used for climate variability/change research contain comprehensive vegetation and soil schemes intended to represent as many processes as possible, even those that are still poorly constrained or understood. Through the synergy between process-based and verification-based approaches the ambitious objective of this project is to obtain a practicable seamless development across scales of the land modelling applied to Earth System predictions. The main goal will be to obtain verifiable land processes models to enhance the performance of the predictions across scales and to demonstrate unprecedented useful applications for the energy sector. A fundamental contribution to fill in the gap between short- and long-term Earth System predictions will come from the emerging availability of reliable land surface observations from remotely sensed satellite campaigns that will provide novel observational constraints to land processes models.

 Publications

year authors and title journal last update
List of publications.
2019 G. Di Capua, M. Kretschmer, J. Runge, A. Alessandri, R.V. Donner, B. van den Hurk, R. Vellore, R. Krishnan, D. Coumou
Long-lead statistical forecasts of the Indian Summer Monsoon Rainfall based on causal precursors
published pages: , ISSN: 0882-8156, DOI: 10.1175/waf-d-19-0002.1
Weather and Forecasting 2020-01-30
2017 Andrea Alessandri, Franco Catalano, Matteo De Felice, Bart Van Den Hurk, Francisco Doblas Reyes, Souhail Boussetta, Gianpaolo Balsamo, Paul A. Miller
Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth
published pages: 1215-1237, ISSN: 0930-7575, DOI: 10.1007/s00382-016-3372-4
Climate Dynamics 49/4 2020-01-30
2019 Matteo De Felice, Marta Bruno Soares, Andrea Alessandri, Alberto Troccoli
Scoping the potential usefulness of seasonal climate forecasts for solar power management
published pages: 215-223, ISSN: 0960-1481, DOI: 10.1016/j.renene.2019.03.134
Renewable Energy 142 2020-01-30
2018 Andrea Alessandri, Matteo De Felice, Franco Catalano, June-Yi Lee, Bin Wang, Doo Young Lee, Jin-Ho Yoo, Antije Weisheimer
Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users
published pages: 2719-2738, ISSN: 0930-7575, DOI: 10.1007/s00382-017-3766-y
Climate Dynamics 50/7-8 2020-01-30

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