Dr Chiara Piccolo
Chiara leads Satellite Applications, working on the estimation of model errors using data assimilation techniques, and as manager of the NWP Satellite Applications Facility.
Areas of expertise
Chiara's areas of expertise include:
- data assimilation
- background error covariance modelling
- remote sensing using IR instruments
- retrieval theory
Chiara works half of her time as manager of the NWP SAF. The NWP SAF is a European collaboration funded by EUMETSAT. The NWP SAF is led by the Met Office, with partners ECMWF, KNMI and Meteo France. It develops software to improve the assimilation of satellite data into NWP models, primarily for use by NWP centres in the member states. It also provides monitoring reports on various operational satellite products. The current five year phase, CDOP-2, started on 1 March 2012. CDOP-3 is planned to start on 1 March 2017 and to run for a further 5 years.
Chiara also works on the estimation of model errors using data assimilation techniques. Model error is a key factor in forecast uncertainty. In a realistic case, it is unlikely that model error can be represented exactly by a physically based scheme. An alternative approach is to treat model error as unknowable and use data assimilation techniques to deduce information about the model error from observations.This alternative approach aims to evaluate the effect of model error by using an ensemble of data assimilations to represent realisations of a stochastic model which contains a stochastic term defined by model errors.
Chiara is also interested in using adaptive mesh methods to better represent the background error. A particular application is the representation of the background error in the presence of stratocumulus clouds.
Chiara started her career at the Met Office in Summer 2007. From June 2012 to July 2014 Chiara worked part of her time as manager of the Met Office Academic Partnership. Before joining the Met Office, Chiara worked for six years as a postdoc at the AOPP at the University of Oxford on infrared remote sensing from satellite instruments and retrieval theory to get the information content when using multi-channels instruments. This work was a continuation of her PhD in Physics at the University of Florence. The main focus of Chiara's PhD project was to develop and test the Optimised Retrieval Model used to retrieve in near-real time trace gases from the MIPAS instrument on board the Envisat platform. During her degree in Physics, Chiara was involved in developing an infrared diode-laser sensor to detect small tracers in atmosphere.