2-6 December 2013 - ICTP, Trieste, Italy
The "Second CLIM-RUN WORKSHOP" on Climate Services
2-6 December 2013 - ICTP, Trieste, Italy
VIDEOS
Records: 11
Climate Local Information in the Mediterranean region Responding to User Needs
A WMO initiative: A Global Framework for Climate Services
Authors: Paolo M Ruti, Hugues Ravenel, Samuel Somot, Manfred Lange, Clare Goodess , Ghislain Dubois, Christos Giannakopoulos, Francisco J. Doblas-Reyes, Antonio Marcomini, Filippo Giorgi and Alessandro Dell’Aquila
Climate information between planning and emergency; what are the needs for a municipality
We have to consider the scenarios of climate change in planning our cities
Authors: Sandro Caparelli - Comune di Venezia, sostenibilità urbana
State-fo-the-Art Climate Forecasting for Energy
How can climate variability create risk in wind energy decisions?
How can climate forecasting minimise this risk?
Climate forecasting of wind speed, a seasonal example
What are the limitations and potential for wind energy forecasting?
Using forecasts in decision-making processes
Authors: M. Davis, F. Doblas-Reyes, F. Lienert, N. Gonzales-Riviriego, V. Torralba Fernandez
Seasonal to decadal up to climate change predictability (projections)
In seasonal and longer time scale predictions (projections) there will be clearly no (atmospheric) predictability of the first kind (Lorenz notation for initial condition dependent predictability). We cannot try to predict details of ‘weather’ more than a few weeks ahead. This is because the climate system is chaotic (lots of instabilities and nonlinearities, from daily to even decadal time-scales). But we may be able to predict the statistics of climate (e.g. mean, variability….), if there are either slowly varying (and predictable) components, such as El Nino SSTs in case of seasonal predictions or external forcing of the Earth System (e.g. Carbon Dioxide, Solar forcing, Volcanoes, Aerosols, ….) in case of climate change projections. Lorenz called this predictability of the second kind. This could give a hint then of shifts of the mean climate (or attractors in Lorenz‘ language) and its statistics.
Authors: Fred Kucharski Abdus Salam ICTP, Trieste, Italy, Earth System Physics Section
Statistical downscaling model
AOGCM: status of the art
Coarse resolution AOGCMs (100-200 Km) simulate atmospheric general circulation features well in general. At the regional scale the models display area-average biases that are highly variable from region-to-region and among models, with sub-continental areaaveraged seasonal temperature biases.
A correction is needed to apply these AOGCM outputs.
Authors: Carlo Cacciamani, Servizio Idro Meteo - Italy
Introduction to CRITERIA model
What is CRITERIA
- Modelling system aimed at the simulation of the agro-ecosystem
- Modular system
- Different versions for different applications
Authors: Giulia Villani, Agenzia Regionale Prevenzione e Ambiente Emilia Romagna - Italy
Climate service iCOLT
Aim of iCOLT is to provide a probabilistic early assessment of irrigation demand of crops for the Emilia- Romagna regional plain area and also for each of the eight reclamation consortia.
The system has been operational at ARPA-SIMC since 2010, making available the results via the agency official web site.
Authors: Giulia Villani, Agenzia Regionale Prevenzione e Ambiente Emilia Romagna - Italy
Climate change in Emilia-Romagna
The increase of temperature and the different distribution of precipitation cause an accumulation of climatic anomaly in the soil: the case of summer 2012
Authors: Giulia Villani, Agenzia Regionale Prevenzione e Ambiente Emilia Romagna - Italy
Climate change scenarios in Emilia-Romagna
Local Action Program to cope with drought and desertification
Authors: Giulia Villani, Agenzia Regionale Prevenzione e Ambiente Emilia Romagna - Italy
Learning from data: data mining approaches for Energy & Weather/Climate applications!
Outline
- Building reliable Climate Services is really challenging
- Cross-disciplinary
- We need to use the latest and most advance research and knowledge
- We need to use all available data
Authors: Matteo De Felice, ENEA - Italy




