Session on techniques and resources for storm-scale numerical weather prediction

The session on techniques and resources for storm-scale numerical weather prediction are reviewed. The recommendations of this group are broken down into three area: modeling and prediction, data requirements in support of modeling and prediction, and data management. The current status, modeling and technological recommendations, data requirements in support of modeling and prediction, and data management are addressed

A numerical field experiment approach for determining probabilities of microburst intensity

Several investigators had determined that some atmospheric parameters were related to the formation and severity of microbursts. For example, Caracena pointed out the relationship between a dry adiabatic lapse rate and microbursts in 'The crash of Delta Flight 191 at Dallas-Fort Worth international airport'. These early investigations led to the idea that numeric modeling of microbursts with varying atmospheric parameters might define 'signatures' that could lead to determining the probability of microburst intensity. The idea was that, by using already available sensors (such as static air temperature, pressure altitude, and radar reflectivity) onboard an aircraft, a reliable prediction of microburst existence and intensity could be formed. Such data could be used to create an 'expert meteorologist' using either artificial intelligence or other techniques that could be used in either reactive or look-ahead systems to vary sensitivity thresholds and coordinate the inputs from different detecting systems. To this end, Honeywell contracted to have the microburst simulations run. The questions to be addressed were the following: using the sensor set available to the aircraft (e.g. temperature, radar reflectivity, etc.), can we calculate the probability that (1) a microburst could be formed? and (2) that the resultant winds would be of sufficient magnitude to threaten the aircraft? Over a two year period, a data set of 1800 microburst simulations was accumulated. Verification of the microburst simulation was obtained using the results of other independent researchers and actual comparison to microburst events in Orlando and Denver. Some of the results from the simulation have already been incorporated into Honeywell's Windshear Detection and Guidance System with excellent results. Various aspects of this investigation are presented in viewgraph form

Techniques and resources for storm-scale numerical weather prediction

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software

Prediction of Convective Storms at Convection-Resolving 1 km Resolution over Continental United States with Radar Data Assimilation: An Example Case of 26 May 2008 and Precipitation Forecasts from Spring 2009

For the first time ever, convection-resolving forecasts at 1 km grid spacing were produced in realtime in spring 2009 by the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The forecasts assimilated both radial velocity and reflectivity data from all operational WSR-88D radars within a domain covering most of the continental United States. In preparation for the realtime forecasts, 1 km forecast tests were carried out using a case from spring 2008 and the forecasts with and without assimilating radar data are compared with corresponding 4 km forecasts produced in realtime. Significant positive impact of radar data assimilation is found to last at least 24 hours. The 1 km grid produced a more accurate forecast of organized convection, especially in structure and intensity details. It successfully predicted an isolated severe-weather-producing storm nearly 24 hours into the forecast, which all ten members of the 4 km real time ensemble forecasts failed to predict. This case, together with all available forecasts from 2009 CAPS realtime forecasts, provides evidence of the value of both convection-resolving 1 km grid and radar data assimilation for severe weather prediction for up to 24 hours

The Numerical Simulation of Thunderstorm Outflow Dynamics (Gust Front, Kelvin-Helmholtz Instability, Wind Shear, Microbursts)

708 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.Two high-resolution, two-dimensional numerical models are developed and used to investigate the dynamics of thunderstorm outflows. The first model employs the set of unapproximated, inviscid, fully compressible hydrodynamical equations, while the second, more economical model is based on a simplified set of inviscid, "quasi-compressible" equations. Neither model includes moist microphysical processes.The outflow models are designed with the flexibility needed to address many aspects of outflow dynamics with a high degree of physical realism. An outflow may be initialized in the models as a purely horizontal flow issuing from a lateral boundary, as a cold vertical downdraft imposed at the upper boundary (which is assumed to represent cloud base), or as a downdraft parameterized by a heat sink. The sensitivity of modeled outflow properties to these initialization techniques is addressed.Turbulent mixing in outflows, manifest as Kelvin-Helmholtz shearing instability, is successfully simulated with the outflow models. Although this type of hydrodynamical instability has long been observed in laboratory density currents (the dynamical analog of outflows), this is the first time it has ever been reproduced in modeled outflows. The characteristics of the Kelvin-Helmholtz instability are compared with linear theory and laboratory results, and the sensitivity of the associated turbulent mixing to several physical and computational parameters is discussed.The characteristics of the ambient environment are found to play key roles in the dynamics of simulated outflows. Several vertical wind shear and static stability profiles are examined in the model, and their influence on outflow behavior is addressed. Surface frictional effects are also shown to significantly alter the internal flow structure of outflows. Results of simulations with and without surface friction are compared, and several features in the modeled flows are shown to be similar to structure observed in laboratory density currents and thunderstorm outflows.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

P1.42 THE IMPACT OF SIMULATED HIGH-RESOLUTION SURFACE OBSERVATIONS FOR CONVECTIVE STORMS WITH ENSEMBLE KALMAN FILTER

Successful numerical weather prediction (NWP

46 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 23 An OSSE Framework Based on the Ensemble Square Root Kalman Filter for Evaluating the Impact of Data from Radar Networks on Thunderstorm Analysis and Forecasting

A framework for Observing System Simulation Experiments (OSSEs) based on the ensemble square root Kalman filter (EnSRF) technique for assimilating data from more than one radar network is described. Th