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) measurements are affected by sensitivity to the highly variable land surface emissivity and similar optical properties of cloud water and light rainfall that limit the detectability and retrieval accuracy of either component. Current observations also lack sensitivity to drizzle and snowfall. Specific workshop recommendations regarding observations include 1) expanding the use of ARM site observations and conducting well-planned field campaigns to provide better validation of satellite cloud and
) measurements are affected by sensitivity to the highly variable land surface emissivity and similar optical properties of cloud water and light rainfall that limit the detectability and retrieval accuracy of either component. Current observations also lack sensitivity to drizzle and snowfall. Specific workshop recommendations regarding observations include 1) expanding the use of ARM site observations and conducting well-planned field campaigns to provide better validation of satellite cloud and
: growing or decaying. Cloud droplet size increases with height during the developing stage due to condensation growth. Once a collision process starts, larger droplets tend to fall to the lower levels of the cloud. Therefore, the DER at cloud base is small for developing clouds and large for drizzling clouds. So the DER at the cloud base is more correlated with rainfall than DER at the cloud top. There were some previous studies that utilized the vertical DER variation to differentiate precipitating
: growing or decaying. Cloud droplet size increases with height during the developing stage due to condensation growth. Once a collision process starts, larger droplets tend to fall to the lower levels of the cloud. Therefore, the DER at cloud base is small for developing clouds and large for drizzling clouds. So the DER at the cloud base is more correlated with rainfall than DER at the cloud top. There were some previous studies that utilized the vertical DER variation to differentiate precipitating
, the expected level of details, the small time step (less than 1 min), and the high horizontal resolution (less than 1 km) have led to the development of complex and computationally expensive parameterizations of moist processes. Schemes of this type would usually include separate prognostic variables for cloud liquid water, drizzle, rainwater, small ice particles, graupel, snow, and hail; different PDFs for each variable; and a detailed representation of microphysical exchanges between categories
, the expected level of details, the small time step (less than 1 min), and the high horizontal resolution (less than 1 km) have led to the development of complex and computationally expensive parameterizations of moist processes. Schemes of this type would usually include separate prognostic variables for cloud liquid water, drizzle, rainwater, small ice particles, graupel, snow, and hail; different PDFs for each variable; and a detailed representation of microphysical exchanges between categories
are most commonly used to classify those MW radiance scenes that are most likely to contain precipitation. In reality, drizzle and light precipitation are ubiquitous features of warm layered clouds and shallow convection (e.g., Stevens et al. 2003 ) and the separation between precipitation and cloud and its relationship to LWP is certainly not simple nor entirely understood. (As discussed in relation to Fig. 14 , this same issue also causes parallel difficulties to the estimation of
are most commonly used to classify those MW radiance scenes that are most likely to contain precipitation. In reality, drizzle and light precipitation are ubiquitous features of warm layered clouds and shallow convection (e.g., Stevens et al. 2003 ) and the separation between precipitation and cloud and its relationship to LWP is certainly not simple nor entirely understood. (As discussed in relation to Fig. 14 , this same issue also causes parallel difficulties to the estimation of
