  When Charge Coupled Devices are used for scientific observations, their dark
signal is a hindrance. In their pristine state, most CCD pixels are `cool';
they exhibit low, quasi uniform dark current, which can be estimated and
corrected for. In space, after having been hit by an energetic particle, pixels
can turn `hot'. They start delivering excessive, less predictable, dark
current. The hot pixels need therefore to be flagged so that subsequent
analysis may ignore them. The image data of the PICARD SODISM solar telescope
(Meftah et al. 2013) require dark signal correction and hot pixel
identification. Its frame transfer E2V 42-80 CCD operates at -7{\deg}C. Both
image and memory zones thus accumulate dark current during, respectively,
integration and readout time. These two components must be separated to
estimate the dark signal for any observation. This is the purpose of the Dark
Signal Model presented in this paper. The dark signal time series of every
pixel is processed by the Unbalanced Haar Technique (Fryzlewicz 2007) in order
to timestamp when its dark signal is expected to change. In-between those
instants, both components are assumed constant and a robust linear regression
vs. integration time provides first estimates and a quality coefficient. The
latter serves to assign definitive estimates. Our model is part of the SODISM
Level 1 data production scheme. To check its reliability, we verify on dark
frames that it leaves a negligible residual bias (5 e-), and generates a small
RMS error (25 e- rms). The cool pixel level is found to be 4 e-/pxl/s, in
agreement with the predicted value. The emergence rate of hot pixels is
investigated too. It legitimates a threshold criterion at 50 e-/pxl/s. The
growth rate is found to be 4% of the frame area per year. Aspects of the method
(adaptation of the Unbalanced Haar Technique, dedicated robust linear
regression) have a generic interest.
