Radar Kinematic Information As Surrogate of Thermodynamic Information in Stratiform Precipitation Systems

Field campaigns studying precipitation systems typically are rich in kinematic information from Doppler radar systems, but poor in thermodynamic information. Thermodynamic information (temperature, humidity) can be inferred from a variety of remote sensing techniques, but they are challenged in precipitation. Lidar systems only work in optically clear air, and passive microwave radiometers as well as AERIs are less resolved and their temperature and humidity profile retrievals are less certain in clouds and precipitation. This explains why the old technology of radiosondes is still in high demand in field campaigns, even though radiosondes are just 1D. Weather radars penetrate precipitating systems - any - e.g. frontal systems, orographic precipitation, MCSs, and describe the reflectivity and the (Doppler) flow field in 2D or 3D in fine detail. This mismatch between kinematics and thermodynamics has long been a frustration in observational atmospheric research. Doppler radial velocities are being assimilated in NWP models, but NWP models would be much better off with thermodynamic information at corresponding resolution, because the wind field dynamically responds to the distribution of potential temperature, which is more conserved than the wind field.

Here we describe a serendipitous discovery that the dual-Doppler-derived horizontal vorticity in stratiform (laminar) flow appears in persistent thin filaments in a vertical plane. These filaments depict baroclinic boundaries, gravity waves etc. A comparison of the radar-derived vertical-plane vorticity field with model output of isentropes suggest that the vorticity filaments describe material surfaces, i.e., the distribution of a “conserved" variable. Model output itself further confirms the alignment of isentropes with vorticity in vertical transects. Thus vorticity (a kinematic conserved variable) may serve as a suitable proxy for a thermodynamic conserved variable (equivalent potential temperature) in stratiform precipitation systems. The reason this simple discovery has not been made before is that scanning ground-based radars have rather poor and range-dependent vertical resolution. Here we use data from an airborne radar, with a fine and constant vertical resolution. But the same info can be inferred from RHI scans by radars on the ground, at least at close range.