Detailed Dual-Doppler Structure of Kelvin–Helmholtz Waves from an Airborne Profiling Radar over Complex Terrain. Part I: Dynamic Structure

Kelvin–Helmholtz (KH) waves are remarkably common in deep stratiform precipitation systems associated with frontal disturbances, at least in the vicinity of complex terrain, as is evident from transects of vertical velocity and 2D circulation, obtained from a 3-mm airborne Doppler radar, the Wyoming Cloud Radar. The high range resolution of this radar (~40 m) allows detection and depiction of KH waves in fine detail. These waves are observed in a variety of wavelengths, depths, amplitudes, and turbulence intensities. Proximity rawinsonde data confirm that they are triggered in layers where the Richardson number is very small. Complex terrain may locally enhance wind shear, leading to KH instability. In some KH waves, the flow remains mostly laminar, while in other cases it breaks down into turbulence. KH waves are frequently locked to the terrain, and occur at various heights, including within the free troposphere, at the boundary layer top, and close to the surface. They are observed not only upwind of terrain barriers, as has been documented before, but also in the wake of steep terrain, where the waves can be highly turbulent. Vertical-plane dual-Doppler analyses of KH waves reveal the mixing of layers of differential momentum across the high-shear zone. Doppler radar data are used to explore the dynamics of KH waves, including the response of thermodynamic and kinematic variables above, below, and within the instability layer.

Practical Uncertainties in the Limited Predictability of the Record-Breaking Intensification of Hurricane Patricia (2015)

Hurricane Patricia (2015) was a record-breaking tropical cyclone that was difficult to forecast in real time by both operational numerical weather prediction models and operational forecasters. The current study examines the potential for improving intensity prediction for extreme cases like Hurricane Patricia. We find that Patricia’s intensity predictability is potentially limited by both initial conditions, related to the data assimilation, and model errors. First, convection-permitting assimilation of airborne Doppler radar radial velocity observations with an ensemble Kalman filter (EnKF) demonstrates notable intensity forecast improvements over assimilation of conventional observations alone. Second, decreasing the model horizontal grid spacing to 1 km and reducing the surface drag coefficient at high wind speed in the parameterization of the sea surface–atmosphere exchanges is also shown to notably improve intensity forecasts. The practical predictability of Patricia, its peak intensity, rapid intensification, and the underlying dynamics are further investigated through a high-resolution 60-member ensemble initialized with realistic initial condition uncertainties represented by the EnKF posterior analysis perturbations. Most of the ensemble members are able to predict the peak intensity of Patricia, but with greater uncertainty in the timing and rate of intensification; some members fail to reach the ultimate peak intensity before making landfall. Ensemble sensitivity analysis shows that initial differences in the region beyond the radius of maximum wind contributes the most to the differences between ensemble members in Patricia’s intensification. Ensemble members with stronger initial primary and secondary circulations beyond the radius of maximum wind intensify earlier, are able to maintain the intensification process for longer, and thus reach a greater and earlier peak intensity.

The Rapid Deployments to Wildfires Experiment (RaDFIRE): Observations from the Fire Zone

The Rapid Deployments to Wildfires Experiment (RaDFIRE) was a meteorological field campaign aimed at observing fire–atmosphere interactions during active wildfires. Using a rapidly deployable scanning Doppler lidar, airborne Doppler radar, and a suite of other instruments, the field campaign sampled 21 wildfires from 2013 to 2016 in the western United States. Observations include rotating convective plumes, plume interactions with stable layers and multilayered smoke detrainment, convective plume entrainment processes, smoke-induced density currents, and aircraft in situ observations of developing pyrocumulus. Collectively, these RaDFIRE observations highlight the range of meteorological phenomena associated with wildfires, especially plume dynamics, and will provide a valuable dataset for the modeling community.

A Generalized Navigation Correction Method for Airborne Doppler Radar Data

Uncertainties in aircraft inertial navigation system and radar-pointing angles can have a large impact on the accuracy of airborne dual-Doppler analyses. The Testud et al. (THL) method has been routinely applied to data collected by airborne tail Doppler radars over flat and nonmoving terrain. The navigation correction method proposed in Georgis et al. (GRH) extended the THL method over complex terrain and moving ocean surfaces by using a variational formulation but its capability over ocean has yet to be tested. Recognizing the limitations of the THL method, Bosart et al. (BLW) proposed to derive ground speed, tilt, and drift errors by statistically comparing aircraft in situ wind with dual-Doppler wind at the flight level. When combined with the THL method, the BLW method can retrieve all navigation errors accurately; however, it can be applied only to flat surfaces, and it is rather difficult to automate. This paper presents a generalized navigation correction method (GNCM) based on the GRH method that will serve as a single algorithm for airborne tail Doppler radar navigation correction for all possible surface conditions. The GNCM includes all possible corrections in the cost function and implements a new closure assumption by taking advantage of an accurate aircraft ground speed derived from GPS technology. The GNCM is tested extensively using synthetic airborne Doppler radar data with known navigation errors and published datasets from previous field campaigns. Both tests show the GNCM is able to correct the navigation errors associated with airborne tail Doppler radar data with adequate accuracy.

The Relationship between Spatial Variations in the Structure of Convective Bursts and Tropical Cyclone Intensification as Determined by Airborne Doppler Radar

The relationship between radial and azimuthal variations in the composite characteristics of convective bursts (CBs), that is, regions of the most intense upward motion in tropical cyclones (TCs), and TC intensity change is examined using NOAA P-3 tail Doppler radar. Aircraft passes collected over a 13-yr period are examined in a coordinate system rotated relative to the deep-layer vertical wind shear vector and normalized by the low-level radius of maximum winds (RMW). The characteristics of CBs are investigated to determine how the radial and azimuthal variations of their structures are related to hurricane intensity change. In general, CBs have elevated reflectivity just below the updraft axis, enhanced tangential wind below and radially outward of the updraft, enhanced vorticity near the updraft, and divergent radial flow at the top of the updraft. When examining CB structure by shear-relative quadrant, the downshear-right (upshear left) region has updrafts at the lowest (highest) altitudes and weakest (strongest) magnitudes. When further stratifying by intensity change, the greatest differences are seen upshear. Intensifying storms have updrafts on the upshear side at a higher altitude and stronger magnitude than steady-state storms. This distribution provides a greater projection of diabatic heating onto the azimuthal mean, resulting in a more efficient vortex spinup. For variations based on radial location, CBs located inside the RMW show stronger updrafts at a higher altitude for intensifying storms. Stronger and deeper updrafts inside the RMW can spin up the vortex through greater angular momentum convergence and a more efficient vortex response to the diabatic heating.

Rewriting the Tropical Record Books: The Extraordinary Intensification of Hurricane Patricia (2015)

Hurricane Patricia was a historic tropical cyclone that broke many records, such as intensification rate, peak intensity, and overwater weakening rate, during its brief 4-day lifetime in late October 2015 in the eastern Pacific basin. Patricia confounded all of the intensity forecast guidance owing to its rapid intensity changes. Fortunately, the hurricane-penetrating National Oceanic and Atmospheric Administration WP-3D and U.S. Air Force C-130 aircraft and the National Aeronautics and Space Administration WB-57 high-altitude jet, under support of the Office of Naval Research, conducted missions through and over Patricia prior to and during its extreme intensity changes on all 4 days, while an extensive array of pressure sensors sampled Patricia after landfall. The observations collected from these missions include traditional data sources such as airborne Doppler radar and flight-level instruments as well as new data sources like a high-density array of dropsondes released from high-altitude and wide-swath radiometer. The combination of data from these sources and from satellites provides an excellent opportunity to investigate the physical processes responsible for Patricia’s structure and evolution and offers the potential to improve forecasts of tropical cyclone rapid intensity changes. This paper provides an overview of Patricia as well as the data collected during the aircraft missions.

Improved rain rate and drop size retrievals from airborne Doppler radar

Satellite remote sensing of rain is important for quantifying the hydrological cycle, atmospheric energy budget, and cloud and precipitation processes; however, radar retrievals of rain rate are sensitive to assumptions about the raindrop size distribution. The upcoming EarthCARE satellite will feature a 94 GHz Doppler radar alongside lidar and radiometer instruments, presenting opportunities for enhanced retrievals of the raindrop size distribution.