Seminar: Retrieving the cumulus entrainment rate remotely
Dr. Timothy Wager, Creighton University Department of Physics
Cumulus clouds are an important, yet underobserved, part of the climate system. As cumuli develop, they mix with the surrounding environment through the process of entrainment, which impacts the lifespan, droplet size, and depth of the clouds. In order to properly simulate the atmosphere for climate and weather forecasting, these impacts must be accounted for but the small spatial extent of these clouds means the entrainment process must be must be parameterized, a difficult problem due in part to the lack of available observations of entrainment. Entrainment has been traditionally measured via direct penetration of clouds by instrumented aircraft but the expense and difficulty associated with this method means that the scope of the available entrainment observations is small.
To expand the number of observations of entrainment available for analysis, a remote retrieval method using ground-based instrumentation has been developed. This method, called the Entrainment Rate In Cumulus Algorithm (ERICA) retrieves the fractional entrainment rate through a Gauss-Newton optimal estimation retrieval. High temporal resolution observations of cumuli and their environment and a guess of the entrainment rate are ingested by a cloud parcel model, in this case the Explicit Mixing Parcel Model (EMPM). The entrainment rate is iteratively adjusted until the modeled cloud matches the observations. ERICA has been shown to correspond well with other methods of retrieving the entrainment rate. Results for both shallow continental cumulus and deep tropical convection will be shown.