EUCLIPSE

EU Cloud Intercomparison, Process Study & Evaluation Project (EUCLIPSE)

Cloud feedbacks in Earth System Models (ESMs) remain the largest source of uncertainty in projections of future climate. They are also a major contributor to uncertainty in other feedbacks (e.g., surface albedo, carbon cycle) in the Earth System. Through interactions with the large-scale circulation, cloud processes also contribute to synoptic circulations and regional climate. They are therefore critical to the prediction of future changes in precipitation patterns, climate variability and extreme events.

The central objective of EUCLIPSE is to reduce the uncertainty in the representation of cloud processes and feedbacks in the new generation of Earth System Models (ESMs), in support of the IPCC's fifth assessment report. Novel, process-oriented evaluations of clouds in present-day and by leading future climate simulations made by the leading European ESMs will identify the cloud types and processes responsible for the spread in climate sensitivity and future precipitation changes across the models, and for deficiencies in the simulation of the present-day climate. The new diagnostics and metrics developed in EUCLIPSE will inform targeted sensitivity experiments to isolate the processes responsible for cloud feedback uncertainty.

In EUCLIPSE, four distinct communities will work together across a set of integrated work packages over a four-year period: the observational community will provide state-of-the-art measurements from ground- and space-based active and passive remote sensing; the numerical weather prediction community will provide analyses of short timescale model biases induced by cloud processes; the cloud modelling community will provide fine-scale models as an additional tool for understanding cloud behaviour in a changing climate; finally, the climate modelling community will synthesize the physical understanding and observational constraints identified by the other communities to improve the representation and assessment of cloud processes in ESMs and so improve the predictive skill of ESMs.

Work at ECMWF

ECMWF, which will focus on the weather forecasting component of this project, leads Task 4.1.1:

Task 4.1.1 "will compare the 'Initial Tendency technique' developed by Rodwell and Palmer (2007) to the 'Transpose-AMIP' technique developed by Phillips et al. (2004). The former has the advantage of being able to identify biases that appear in the first six hours of a climate-resolution model forecast, before interactions with the resolved flow and non-linearities have had time to complicate the forecast error. The disadvantage is that it requires the forecasting model to have been employed within the data assimilation process (that is used to produce the initiating analyses). Hence this technique can, at present, only be applied to a few of the world's climate models (EC Earth, ARPEGE, UKMO, and depending on progress in the ongoing development of an assimilation system for ECHAM also this model). The Transpose-AMIP technique is more easy to apply, but is best suited to identifying errors that don’t involve non-linear interactions with the evolving flow".

Coordination

EUCLIPSE is coordinated by Prof. Pier Siebesma at Delft University of Technology in The Netherlands.

This project has received funding from the European Union’s Framework Programme under grant agreement number 244067.