Issues Regarding the Assimilation of Cloud and Precipitation Data

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The growing impact of satellite observations sensitive to humidity, cloud and precipitation (2017, methodology): “A main benefit of the new error model was to produce nearly Gaussian FG departures, addressing another of the issues raised by Errico et al. (2007).”
Operational Implementation of the 1D+3D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model (2014, background): “However, to extract useful information about the main control variables such as temperature, humidity, or wind from the observed reflectivities is difficult as is also the case at a larger scale from satellite data covering cloud- or precipitationaffected areas (Bauer et al. 2011; Errico et al. 2007”
Satellite cloud and precipitation assimilation at operational NWP centres (2011, background): “…detection of precipitation), this can entail sub-optimalities during the minimization process; and (iii) the ‘no-rain’ issue (Lopez and Bauer, 2007; Errico et al., 2007) bars taking into account non-rainy observations and model equivalents; this is a major drawback since no rainy profiles can be…”
Observation errors in all‐sky data assimilation (2011, background): “There have been concerns (e.g. Errico et al., 2007) that these issues will bring difficulties in handling cloud- and precipitation-related observations.”