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- Author or Editor: Rita Roberts x
- Journal of Applied Meteorology and Climatology x
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Abstract
Thirty-one microburst-producing storms from northeast Colorado were studied using single and multiple Doppler radar for the purpose of identifying radar signatures that indicated the development of a downdraft capable of producing a microburst. Descending reflectivity cores, increasing radial convergence within cloud, rotation and reflectivity notches were found to be microburst precursors, appearing typically 2–6 min prior to initial surface outflow. Descending maximum reflectivity cores coincident with increasing radial convergence within cloud (3–8 km AGL) or near cloud base is believed to be a good indicator of storm downdraft and microburst predictor, especially when coupled with low θ e air above cloud base and a dry adiabatic lapse rate below cloud base. Three conceptual models have been drawn, based on the 31 events, to summarize the radar signatures of importance in low, moderate, and high-reflectivity microburst-producing storms.
Experience indicates that Doppler radar may aid in providing 0–10 min nowcasts of microbursts. This requires the rapid perusal and assimilation of a large quantity of radar data by the forecaster. To improve upon this effort, a forecaster-computer environment is proposed to allow the forecaster to readily view radar reflectivity and Doppler velocity information in both unprocessed and analyzed form. Use of multi-image radar displays and time-height profiles of quantitative radar estimates of reflectivity and radial shear are suggested to provide an environment where rapid progress can be made in developing techniques to nowcast microbursts.
Abstract
Thirty-one microburst-producing storms from northeast Colorado were studied using single and multiple Doppler radar for the purpose of identifying radar signatures that indicated the development of a downdraft capable of producing a microburst. Descending reflectivity cores, increasing radial convergence within cloud, rotation and reflectivity notches were found to be microburst precursors, appearing typically 2–6 min prior to initial surface outflow. Descending maximum reflectivity cores coincident with increasing radial convergence within cloud (3–8 km AGL) or near cloud base is believed to be a good indicator of storm downdraft and microburst predictor, especially when coupled with low θ e air above cloud base and a dry adiabatic lapse rate below cloud base. Three conceptual models have been drawn, based on the 31 events, to summarize the radar signatures of importance in low, moderate, and high-reflectivity microburst-producing storms.
Experience indicates that Doppler radar may aid in providing 0–10 min nowcasts of microbursts. This requires the rapid perusal and assimilation of a large quantity of radar data by the forecaster. To improve upon this effort, a forecaster-computer environment is proposed to allow the forecaster to readily view radar reflectivity and Doppler velocity information in both unprocessed and analyzed form. Use of multi-image radar displays and time-height profiles of quantitative radar estimates of reflectivity and radial shear are suggested to provide an environment where rapid progress can be made in developing techniques to nowcast microbursts.
Abstract
Doppler weather radar data from the Joint Airport Weather Studies (JAWS) Project are used to determine the horizontal and vertical structure of airflow within microbursts. Typically, the associated downdraft is about 1 km wide and begins to spread horizontally at a height below 1 km. The median time from initial divergence at the surface to maximum differential wind velocity across the microburst is 5 min. The height of maximum differential velocity is ∼75 m. The median velocity differential is 22 m s−1 over an average distance of 3.1 km. The outflow is asymmetric, averaging twice as strong along the maximum shear axis compared to the minimum axis.
Doppler radar could be an effective means for identifying microbursts and warning aircraft of wind shear hazards. For microburst detection such a radar must be able to measure wind velocities in clear air as well as in heavy rain and hail. Scan update rates should be approximately every 2 min and the lowest few hundred meters of the atmosphere must be observed. Ground clutter must be considerably reduced from levels typically obtained with present Doppler radars. New antenna technology and signal processing techniques may solve this problem. Automated range and velocity unfolding is required, as well as automated identification and dissemination techniques.
Abstract
Doppler weather radar data from the Joint Airport Weather Studies (JAWS) Project are used to determine the horizontal and vertical structure of airflow within microbursts. Typically, the associated downdraft is about 1 km wide and begins to spread horizontally at a height below 1 km. The median time from initial divergence at the surface to maximum differential wind velocity across the microburst is 5 min. The height of maximum differential velocity is ∼75 m. The median velocity differential is 22 m s−1 over an average distance of 3.1 km. The outflow is asymmetric, averaging twice as strong along the maximum shear axis compared to the minimum axis.
Doppler radar could be an effective means for identifying microbursts and warning aircraft of wind shear hazards. For microburst detection such a radar must be able to measure wind velocities in clear air as well as in heavy rain and hail. Scan update rates should be approximately every 2 min and the lowest few hundred meters of the atmosphere must be observed. Ground clutter must be considerably reduced from levels typically obtained with present Doppler radars. New antenna technology and signal processing techniques may solve this problem. Automated range and velocity unfolding is required, as well as automated identification and dissemination techniques.
Abstract
This paper describes important characteristics of an uncoupled high-resolution land data assimilation system (HRLDAS) and presents a systematic evaluation of 18-month-long HRLDAS numerical experiments, conducted in two nested domains (with 12- and 4-km grid spacing) for the period from 1 January 2001 to 30 June 2002, in the context of the International H2O Project (IHOP_2002). HRLDAS was developed at the National Center for Atmospheric Research (NCAR) to initialize land-state variables of the coupled Weather Research and Forecasting (WRF)–land surface model (LSM) for high-resolution applications. Both uncoupled HRDLAS and coupled WRF are executed on the same grid, sharing the same LSM, land use, soil texture, terrain height, time-varying vegetation fields, and LSM parameters to ensure the same soil moisture climatological description between the two modeling systems so that HRLDAS soil state variables can be used to initialize WRF–LSM without conversion and interpolation. If HRLDAS is initialized with soil conditions previously spun up from other models, it requires roughly 8–10 months for HRLDAS to reach quasi equilibrium and is highly dependent on soil texture. However, the HRLDAS surface heat fluxes can reach quasi-equilibrium state within 3 months for most soil texture categories. Atmospheric forcing conditions used to drive HRLDAS were evaluated against Oklahoma Mesonet data, and the response of HRLDAS to typical errors in each atmospheric forcing variable was examined. HRLDAS-simulated finescale (4 km) soil moisture, temperature, and surface heat fluxes agreed well with the Oklahoma Mesonet and IHOP_2002 field data. One case study shows high correlation between HRLDAS evaporation and the low-level water vapor field derived from radar analysis.
Abstract
This paper describes important characteristics of an uncoupled high-resolution land data assimilation system (HRLDAS) and presents a systematic evaluation of 18-month-long HRLDAS numerical experiments, conducted in two nested domains (with 12- and 4-km grid spacing) for the period from 1 January 2001 to 30 June 2002, in the context of the International H2O Project (IHOP_2002). HRLDAS was developed at the National Center for Atmospheric Research (NCAR) to initialize land-state variables of the coupled Weather Research and Forecasting (WRF)–land surface model (LSM) for high-resolution applications. Both uncoupled HRDLAS and coupled WRF are executed on the same grid, sharing the same LSM, land use, soil texture, terrain height, time-varying vegetation fields, and LSM parameters to ensure the same soil moisture climatological description between the two modeling systems so that HRLDAS soil state variables can be used to initialize WRF–LSM without conversion and interpolation. If HRLDAS is initialized with soil conditions previously spun up from other models, it requires roughly 8–10 months for HRLDAS to reach quasi equilibrium and is highly dependent on soil texture. However, the HRLDAS surface heat fluxes can reach quasi-equilibrium state within 3 months for most soil texture categories. Atmospheric forcing conditions used to drive HRLDAS were evaluated against Oklahoma Mesonet data, and the response of HRLDAS to typical errors in each atmospheric forcing variable was examined. HRLDAS-simulated finescale (4 km) soil moisture, temperature, and surface heat fluxes agreed well with the Oklahoma Mesonet and IHOP_2002 field data. One case study shows high correlation between HRLDAS evaporation and the low-level water vapor field derived from radar analysis.
