Retrieving Latent Heat 3D Structures from ARM radar suites

Description

Latent Heat released by precipitation plays a vital role in the hydrologic and energy cycle in the Earth climate system. Changes in cloud and precipitation profiles result in changes in LH profiles. Consequently, this LH release influences the ambient environment and atmospheric motions, causing significant atmospheric responses through multiple layers. It is crucial to understand the physical links of microphysical processes with dynamics in terms of latent heating profiles that are associated with cloud and precipitation profiles. We conducted a study of developing physics-based LH algorithms in which the measured cloud water and rain rate vertical profiles are directly used to calculate LH rate at each layer: i.e., Min et al. (2013) and Li et al. (2013). The physical linkage is established through comprehensive parameterizations with the aid of the cloud-resolving model (CRM). The performance of the LH algorithm in both boundary layer clouds and deep convective clouds is demonstrated through an evaluation and validation study with CRM simulations. Furthermore, we explore more robust LH retrievals with three key observables, i.e., cloud water content, rain rate, and vertical velocity profiles. The preliminary algorithm has applied to MC3E collocated multiple radar observations to derive 3D LH structures. It demonstrates the possibility to produce a time series of 3D LH structures or 4D LH structures from ARM observation suite. The retrieved LH products are useful for evaluation of high-resolution cloud resolving models, as well as large-scale climate models.