Recent Posts

I have recently moved in North Holland and in the past weeks the weather was particularly fortunate: for many (consecutive) days there was no rain and the temperature have been very high for this area (the maximum temperature was easily above 25° degrees). Given that I have no experience yet for this weather, I asked around how frequently this happens and I got diverse answers. Then, I have decided to look at some historical time-series of temperature and precipitation to try to satisfy my curiosity.


To evaluate the performances of the probabilistic forecasts provided by seasonal forecasting it is very common the use of skill scores. A skill score is normally defined as a ratio between a specific accuracy measure computed on the forecast and the same measure applied to a reference forecast. In the case of seasonal forecasts, as reference forecast is commonly used the climatological probability, that is the observed frequency of the target event (the event predicted by the forecast) in the past.


Recently I had the occasion to contribute to a document providing a feedback on European Commission public consultation on directives 2003/98/EC and 2013/37/EU. The work has been coordinated by Robbie Morrison, an important contributor to the OpenMod Initiative (and not only). The document is available at this link, and it discusses all the concerns related to the (re-)use of public information and the needs from energy modellers community. It is also related to my recent experience in the C3S ECEM service where, with a bunch of smart and enthusiastic people from the energy & meteorology community, I had the possibility to really understand the potentialities and limitations in the use of public available data for the modelling of European power systems in relation to the link with meteorological variables.


I am not exaggerating when I say that the main reason to develop in R is the presence of the tidyverse and the plethora of packages that let you to explore data and deal easily with the most common tasks (splitting, grouping, temporal aggregation, etc.). Unfortunately, the biggest limitation in R is its capability to manipulate effectively arrays of data (data cubes), especially nowadays when it is normal to deal with very large data sets (please, don’t say “big”).


Selected Publications

Air temperature is an effective predictor for electricity demand, especially during hot periods where the need of electric air conditioning can be high. This paper presents for the first time an assessment of the use of seasonal climate forecasts of temperature for medium-term electricity demand prediction…
Applied Energy, 2014

Electricity demand forecasting is a critical task for energy management of power grids. Due to the wide use of refrigeration and residential air-conditioning devices, electricity demand in Italy is influenced by weather conditions, especially during summer…
Electric Power Systems Research, 2013

Recent Publications

More Publications

. What is users' next best alternative to the use of dynamical seasonal predictions?. EarthArXiv Preprints, 2018.


. Data-driven upscaling methods for regional photovoltaic power estimation and forecast using satellite and numerical weather prediction data. Solar Energy, 2017.


. Status quo of the air-conditioning market in europe: Assessment of the building stock. Energies, 2017.


. Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users. Climate Dynamics, 2017.


. Deterministic and stochastic approaches for day-ahead solar power forecasting. Journal of Solar Energy Engineering, 2016.


. Smart City Projects Implementation in Europe: Assessment of Barriers and Drivers. International Journal of Contemporary Energy, 2016.


. Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth. Climate Dynamics, pp. 1–23, 2016.


. Multi-Model Ensemble for day ahead prediction of photovoltaic generation. Solar Energy, 2016.

. Future development of the air-conditioning market in Europe: an outlook until 2020. Wiley Interdisciplinary Reviews: Energy and Environment, 2016.

. Observationally based analysis of land-atmosphere coupling. Earth System Dynamics, 2016.


Recent & Upcoming Talks

5 Mar 2018 1:00 PM



European Climatic Energy Mixes


Turning climate-related information into added value for traditional MEDiterranean Grape, OLive and Durum wheat food systems

H2020 S2S4E

Sub-Seasonal to Seasonal Climate Prediction For Energy


the Added Value of Seasonal Climate Forecasts for Integrated Risk Management Decisions

Interreg V-A STRATUS

Strategie Ambientali per un Turismo Sostenibile


European Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale


European Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale


Climate Local Information in the Mediterranean region Responding to User Needs