David C. Dowell

Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: Ensemble Kalman filter experiments

Abstract The feasibility of using an ensemble Kalman filter (EnKF) to retrieve the wind and temperature fields in an isolated convective storm has been tested by applying the technique to observations of the 17 May 1981 Arcadia, Oklahoma, tornadic supercell. Radial-velocity and reflectivity observations from a single radar were assimilated into a nonhydrostatic, anelastic numerical model initialized with an idealized (horizontally homogeneous) base state. The assimilation results were compared to observations from another Doppler radar, the results of dual-Doppler wind syntheses, and in situ measurements from an instrumented tower. Observation errors make it more difficult to assess EnKF performance than in previous storm-scale EnKF experiments that employed synthetic observations and a perfect model; nevertheless, the comparisons in this case indicate that the locations of the main updraft and mesocyclone in the Arcadia storm were determined rather accurately, especially at midlevels. The magnitudes of v...

A Multicase Comparative Assessment of the Ensemble Kalman Filter for Assimilation of Radar Observations. Part I: Storm-Scale Analyses

Abstract The effectiveness of the ensemble Kalman filter (EnKF) for assimilating radar observations at convective scales is investigated for cases whose behaviors span supercellular, linear, and multicellular organization. The parallel EnKF algorithm of the Data Assimilation Research Testbed (DART) is used for data assimilation, while the Weather Research and Forecasting (WRF) Model is employed as a simplified cloud model at 2-km horizontal grid spacing. In each case, reflectivity and radial velocity measurements are utilized from a single Weather Surveillance Radar-1988 Doppler (WSR-88D) within the U.S. operational network. Observations are assimilated every 2 min for a duration of 60 min and correction of folded radial velocities occurs within the EnKF. Initial ensemble uncertainty includes random perturbations to the horizontal wind components of the initial environmental sounding. The EnKF performs effectively and with robust results across all the cases. Over the first 18–30 min of assimilation, the ...

The Bow Echo and MCV Experiment: Observations and Opportunities

The Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) is a research investigation using highly mobile platforms to examine the life cycles of mesoscale convective systems. It represents a combination of two related investigations to study (a) bow echoes, principally those that produce damaging surface winds and last at least 4 h, and (b) larger convective systems that produce long-lived mesoscale convective vortices (MCVs). The field phase of BAMEX utilized three instrumented research aircraft and an array of mobile ground-based instruments. Two long-range turboprop aircraft were equipped with pseudo-dual-Doppler radar capability, the third aircraft was a jet equipped with dropsondes. The aircraft documented the environmental structure of mesoscale convective systems (MCSs), observed the kinematic and thermodynamic structure of the convective line and stratiform regions (where rear-inflow jets and MCVs reside), and captured the structure of mature MCVs. The ground-based instruments augmented sou...

A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh

AbstractThe Rapid Refresh (RAP), an hourly updated assimilation and model forecast system, replaced the Rapid Update Cycle (RUC) as an operational regional analysis and forecast system among the suite of models at the NOAA/National Centers for Environmental Prediction (NCEP) in 2012. The need for an effective hourly updated assimilation and modeling system for the United States for situational awareness and related decision-making has continued to increase for various applications including aviation (and transportation in general), severe weather, and energy. The RAP is distinct from the previous RUC in three primary aspects: a larger geographical domain (covering North America), use of the community-based Advanced Research version of the Weather Research and Forecasting (WRF) Model (ARW) replacing the RUC forecast model, and use of the Gridpoint Statistical Interpolation analysis system (GSI) instead of the RUC three-dimensional variational data assimilation (3DVar). As part of the RAP development, modif...

Centrifuging of Hydrometeors and Debris in Tornadoes: Radar-Reflectivity Patterns and Wind-Measurement Errors

High-resolution Doppler radar observations of tornadoes reveal a distinctive tornado-scale signature with the following properties: a reflectivity minimum aloft inside the tornado core (described previously as an “eye”), a high-reflectivity tube aloft that is slightly wider than the tornado core, and a tapering of this high-reflectivity tube near the ground. The results of simple one-dimensional and two-dimensional models demonstrate how these characteristics develop. Important processes in the models include centrifugal ejection of hydrometeors and/or debris by the rotating flow and recycling of some objects by the nearsurface inflow and updraft. Doppler radars sample the motion of objects within the tornado rather than the actual airflow. Since objects move at different speeds and along different trajectories than the air, error is introduced into kinematic analyses of tornadoes based on radar observations. In a steady, axisymmetric tornado, objects move outward relative to the air and move more slowly than the air in the tangential direction; in addition, the vertical air-relative speed of an object is less than it is in still air. The differences between air motion and object motion are greater for objects with greater characteristic fall speeds (i.e., larger, denser objects) and can have magnitudes of tens of meters per second. Estimates of these differences for specified object and tornado characteristics can be obtained from an approximation of the one-dimensional model. Doppler On Wheels observations of the 30 May 1998 Spencer, South Dakota, tornado demonstrate how the apparent tornado structure can change when the radar-scatterer type changes. When the Spencer tornado entered the town and started lofting debris, changes occurred in the Doppler velocity and reflectivity fields that are consistent with an increase in mean scatterer size.

Surface Data Assimilation Using an Ensemble Kalman Filter Approach with Initial Condition and Model Physics Uncertainties

Abstract The assimilation of surface observations using an ensemble Kalman filter (EnKF) approach is evaluated for the potential to improve short-range forecasting. Two severe weather cases are examined, in which the assimilation is performed over a 6-h period using hourly surface observations followed by an 18-h simulation period. Ensembles are created in three different ways—by using different initial and boundary conditions, by using different model physical process schemes, and by using both different initial and boundary conditions and different model physical process schemes. The ensembles are compared in order to investigate the role of uncertainties in the initial and boundary conditions and physical process schemes in EnKF data assimilation. In the initial condition ensemble, spread is associated largely with the displacement of atmospheric baroclinic systems. In the physics ensemble, spread comes from the differences in model physics, which results in larger spread in temperature and dewpoint te...

Ensemble Kalman Filter Assimilation of Radar Observations of the 8 May 2003 Oklahoma City Supercell: Influences of Reflectivity Observations on Storm-Scale Analyses

Abstract Ensemble Kalman filter (EnKF) techniques have been proposed for obtaining atmospheric state estimates on the scale of individual convective storms from radar and other observations, but tests of these methods with observations of real convective storms are still very limited. In the current study, radar observations of the 8 May 2003 Oklahoma City tornadic supercell thunderstorm were assimilated into the National Severe Storms Laboratory (NSSL) Collaborative Model for Multiscale Atmospheric Simulation (NCOMMAS) with an EnKF method. The cloud model employed 1-km horizontal grid spacing, a single-moment bulk precipitation-microphysics scheme, and a base state initialized with sounding data. A 50-member ensemble was produced by randomly perturbing base-state wind profiles and by regularly adding random local perturbations to the horizontal wind, temperature, and water vapor fields in and near observed precipitation. In a reference experiment, only Doppler-velocity observations were assimilated into ...

The Second Verification of the Origins of Rotation in Tornadoes Experiment: VORTEX2

The second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2), which had its field phases in May and June of 2009 and 2010, was designed to explore i) the physical processes of tornadogenesis, maintenance, and demise; ii) the relationships among tornadoes, tornadic storms, and the larger-scale environment; iii) numerical weather prediction and forecasting of supercell thunderstorms and tornadoes; and iv) the wind field near the ground in tornadoes. VORTEX2 is by far the largest and most ambitious observational and modeling study of tornadoes and tornadic storms ever undertaken. It employed 13 mobile mesonet–instrumented vehicles, 11 ground-based mobile radars (several of which had dual-polarization capability and two of which were phased-array rapid scan), a mobile Doppler lidar, four mobile balloon sounding systems, 42 deployable in situ observational weather stations, an unmanned aerial system, video and photogrammetric teams, damage survey teams, deployable disdrometers, and othe...

Additive Noise for Storm-Scale Ensemble Data Assimilation

Abstract An “additive noise” method for initializing ensemble forecasts of convective storms and maintaining ensemble spread during data assimilation is developed and tested for a simplified numerical cloud model (no radiation, terrain, or surface fluxes) and radar observations of the 8 May 2003 Oklahoma City supercell. Every 5 min during a 90-min data-assimilation window, local perturbations in the wind, temperature, and water-vapor fields are added to each ensemble member where the reflectivity observations indicate precipitation. These perturbations are random but have been smoothed so that they have correlation length scales of a few kilometers. An ensemble Kalman filter technique is used to assimilate Doppler velocity observations into the cloud model. The supercell and other nearby cells that develop in the model are qualitatively similar to those that were observed. Relative to previous storm-scale ensemble methods, the additive-noise technique reduces the number of spurious cells and their negativ...

A Multicase Comparative Assessment of the Ensemble Kalman Filter for Assimilation of Radar Observations. Part II: Short-Range Ensemble Forecasts

The quality of convective-scale ensemble forecasts, initialized from analysis ensembles obtained through the assimilation of radar observations using an ensemble Kalman filter (EnKF), is investigated for cases whose behaviors span supercellular, linear, and multicellular organization. This work is the companion to Part I, which focused on the quality of analyses during the 60-min analysis period. Here, the focus is on 30-min ensemble forecasts initialized at the end of that period. As in Part I, the Weather Research and Forecasting (WRF) model is employed as a simplified cloud model at 2-km horizontal grid spacing. Various observationspace and state-space verification metrics, computed both for ensemble means and individual ensemble members, are employed to assess the quality of ensemble forecasts comparatively across cases. While the cases exhibit noticeable differences in predictability, the forecast skill in each case, as measured by various metrics, decays on a time scale of tens of minutes. The ensemble spread also increases rapidly but significant outlier members or clustering among members are not encountered. Forecast quality is seen to be influenced to varying degrees by the respective initial soundings. While radar data assimilation is able to partially mitigate some of the negative effects in some situations, the supercell case, in particular, remains difficult to predict even after 60 min of data assimilation.