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.
Accurate prediction of convective-scale hazardous weather continues to be a major challenge. Efforts to explicitly predict convective storms using numerical models dated back to Lilly [
For over a decade, the research community has been producing experimental real time forecasts at 3-4 km convection-allowing resolutions (e.g., [
In the spring seasons of 2007 and 2008, CAPS conducted more systematic real-time experiments. Daily forecasts of 30 h or more were produced for 10-member 4 km ensembles and 2 km deterministic forecasts ([
Recognizing that producing better convective forecasts requires accurately resolving the internal structures of convective storms, the CAPS team carried out real-time 1 km resolution forecasts assimilating radar data from mid-April through early June, 2009 [
Observed composite radar reflectivity at 0300 UTC, May 26, 2008 (a) and 3-hour forecasts of the same field valid at the same time from (b) the 1 km forecast with radar data assimilation, (c) 4 km control forecast with radar data assimilation, and (d) 4 km forecast without radar data. Panel (b) includes surface wind vectors at 10 m AGL plotted at every 80th grid point.
The rest of this paper is organized as follows. Section
The 26 May 2008 test case is a more weakly forced case highlighted in X08. The 4 km realtime forecasts correspond to the control members of the 4 km storm-scale ensemble forecasts (SSEF, X08, [
All forecasts were initialized at 0000 UTC of 26 May 2008 for the test case. Forecasts C04 and C01 are, respectively, 4 and 1 km forecasts without radar data assimilation and were initialized by interpolation from the operational National Centers for Environmental Prediction (NCEP) North America Mesoscale (NAM) model 0000 UTC analysis on a 12 km grid. The 4 and 1 km forecasts with radar data assimilation, that is, CN4 and CN1, started from the analyses produced on the native model grid by the Advanced Regional Prediction System (ARPS) [
At 0000 UTC, 26 May 2008 (not shown), a low was centered over Minnesota (MN), and a weak, quasistationary cold front extended from the low center southwestward to the western Kansas (KS) border, where it intersected a dryline that extended southward along eastern New Mexico (NM) border into northern Mexico (the point where a dryline intercept a front is often referred to as the front-dryline triple point, e.g., [
During this 24 hour period, there were other regions of convection that interacted with each other. As documented by X08, the evolution of convection during this period was rather complex and the morphology of many of the convective storms was modulated by their own cold pools and gust fronts and interactions with those of other storms. Such a situation is more difficult to predict than cases where strong propagating synoptic-scale features, such as a strong cold front, play more controlling roles. We demonstrate here that in the absence of strong large-scale control, the impact of radar data can be long-lasting.
At the initial time (not shown), the composite (vertical column maximum)
Being properly initialized in CN1 and CN4, these groups of convection were accurately predicted over the first three hours (Figures
The 4 km forecast without assimilating radar or additional surface Mesonet data (C04) is clearly inferior at 3 hours (Figure
At 9 hours, a time when the direct impact of radar data measured by standard skill scores for the season average starts to diminish (X08), the positive impact of radar data is still very clear in this case in both CN1 and CN4 (Figure
As Figure
Along the Mississippi River is another narrow line of cells that was observed and also predicted accurately in CN1. An examination of radar data and satellite imagery indicates that these cells developed along the back edge of the cold pool left behind by the northeastward propagating bow-shaped convection, which is at this time barely identifiable in northwestern Kentucky (KY, Figure
The general pattern of predicted convection in CN4 (Figure
The forecast of C04 at this time is much poorer (Figure
By noon of 26 May (1800 UTC), all of the convective systems from the previous evening and night have moved out of the central Plains. The quasistationary front remained running across central KS, intersecting the dryline that extended north from the TX panhandle near the CO border (not shown). In the afternoon, convection was initiated along the dryline and, to a lesser extent, along the front. These processes were captured well in both CN1 and CN4 (Figure
As Figure
In the late afternoon hours, many hail events associated with the above convective storms were reported. Two brief tornadoes were reported near Dodge City, KS, between 2300 UTC, 26 May, and 0000 UTC, 27 May, emerging from storms that developed near the dryline-cold front triple point. At 2300 UTC, the observed composite reflectivity map of the OK-KS region shows three groups of convective cells (labeled A, B, and C in Figure
Group C, consisting of more isolated cells, formed in the warm sector south of the front and east of the dryline near KS-OK border (Figure
The corresponding storm in the CN1 prediction maintained its full intensity until after 0100 UTC. It gained some supercell characteristics in terms of the shape of the reflectivity by 2300 UTC (Figure
To complement the earlier subjective evaluation of the forecasts for May 26, 2008 test case, we calculate the equitable threat scores (ETSs) verified against hourly radar-estimated precipitation produced on a 1 km grid by the National Severe Storms Laboratory in real time [
Equitable threat scores (ETSs) of hourly accumulated precipitation at 0.1 inch (a) and 0.5 inch (b) thresholds, for the 1 km forecast with radar data (CN1, solid red), 1 km forecast without radar data (C01, dashed red), 4 km control (CN4, solid black), and 4 km run without radar data (C04, dashed black), for the 26 May 2008 case, for hour 1 through 30.
The scores of C04 and C01 remain very low throughout the 30-hour-long forecasts and never exceed 0.03 (0.02 for the higher threshold). Between 2 and 19 hours, the scores of CN1 are up to 0.05 higher than those of CN4 for the lower threshold (Figure
To examine the precipitation forecast skill scores for the 4 and 1 km grids and the impact of radar data on the 4 km grid beyond the single test case present above, we discuss briefly here ETS scores for forecasts from 23 days of the 2009 CAPS spring forecast experiment on which all three forecasts are available; they are presented in Figure
Mean equitable threat scores (ETSs) of 3-hour accumulated precipitation at 0.1 inch (a) and 0.5 inch (b) thresholds, for the 1 km forecast with radar data (CN1, solid red), 4 km control (CN4, solid black), and 4 km run without radar data (C04, dashed black), for forecasts of 23 days from the CAPS 2009 spring forecast experiment.
Figure
The ETS scores for the operational 12 km NAM forecasts are consistently lower than all high resolution forecasts for the lower threshold shown (Figure
In this paper, we report on the results of the first ever test forecasts performed for a case from May 2008, at 1 km grid spacing in a domain covering almost the entire continental U.S., and the comparison of such forecasts with similarly configured forecasts produced at 4 km grid spacing in real time. These forecasts were 30 hours long, and a pair of forecasts assimilated both radial velocity and reflectivity data from all operational U.S. WSR-88D radars within the model domain, while another pair did not assimilate radar data. These 1 and 4 km forecasts with and without radar data assimilation are compared. Based on subjective evaluations, significant positive impact of radar data assimilation is found to last at least 24 hours for the test case. The 1 km forecast with radar data assimilation more accurately reproduced the observed convection than the corresponding 4 km forecast, especially in structure and intensity. It successfully predicted an isolated severe storm nearly 24 hours into the forecast, while the corresponding 4 km forecast, as well as all other 4 km members from the CAPS realtime storm-scale ensemble forecasts, failed to do so. The positive impact of radar assimilation on the precipitation forecast is even larger on both 4 and 1 km grids. Similar conclusions hold for precipitation forecasts based on mean equitable threat scores for 23 forecast days from spring 2009. This study provides evidence of the value of both convection-resolving resolution and radar data assimilation for severe weather prediction for up to 24 hours. We do want to point out that the equitable threat score examined in this paper has many limitations when applied to high-resolution precipitation forecasts due to large penalty associated with position errors. Object-based verification methods (e.g., [
This research was supported by a NOAA Collaborative Science and Technology Applied Research (CSTAR) Grant NA17RJ1227 and by the National Science Foundation Grants AGS-0738370, AGS-0802888, and EEC-0313747. The forecasts were produced at the National Institute of Computational Sciences, University of Tennessee, as part of the national Teragrid (currently Xsede) supercomputing allocation.