A Case Study on the Impact of Moisture Variability on Convection Initiation Using Radar Refractivity Retrievals

Abstract

A case study illustrating the impact of moisture variability on convection initiation in a synoptically active environment without strong moisture gradients is presented. The preconvective environment on 30 April 2007 nearly satisfied the three conditions for convection initiation: moisture, instability, and a low-level lifting mechanism. However, a sounding analysis showed that a low-level inversion layer and high LFC would prevent convection initiation because the convective updraft velocities required to overcome the convective inhibition (CIN) were much higher than updraft velocities typically observed in convergence zones. Radar refractivity retrievals from the Twin Lakes, Oklahoma (KTLX), Weather Surveillance Radar-1988 Doppler (WSR-88D) showed a moisture pool contributing up to a 28C increase in dewpoint temperature where the initial storm-scale convergence was observed. The analysis of the storm-relative wind field revealed that the developing storm ingested the higher moisture associated with the moisture pool. Sounding analyses showed that the moisture pool reduced or nearly eliminated CIN, lowered the LFC by about 500 m, and increased CAPE by 2.5 times. Thus, these small-scale moisture changes increased the likelihood of convection initiation within the moisture pool by creating a more favorable thermodynamic environment. The results suggest that refractivity data could improve convection initiation forecasts by assessing moisture variability at finer scales than the current observation network.

The Effect of Phase-Correlated Returns and Spatial Smoothing on the Accuracy of Radar Refractivity Retrievals

“…This may explain some of the extreme refractivity differences, often around 20 N units and at times as large as 30 N units, reported by Bodine et al (2011) concerning a NEXRAD (KTLX) in comparison with Mesonet surface observations in central Oklahoma and also the refractivity ''shifts'' using reference maps made at different times of the day. Bodine et al (2011) attributed these large discrepancies to differences in the height of the radar targets relative to the 2.5-m Mesonet observations, as dn/dh between 2.5-and 9-m observations at one of these stations at times exceeded 21000 ppm km 21 . These discrepancies often occurred at all Mesonet stations in the radar domain simultaneously and for longer periods than the maximum gradients were observed (e.g., on 29 September in their Fig.…”

“…We shall consider two categories of radars and the refractivity algorithms that have been applied in the literature: 1) NEXRAD WSR-88Ds (e.g., Bodine et al 2011) with a range resolution of 235 m using the refractivity algorithm from Cheong et al (2008), and 2) S-Pol (e.g., 9.6 9.6 9.6 9.6 9.5 9.4 9.2 8.9 4-gate 5 4.9 4.9 4.9 4.9 4.8 4.8 4.8 4.8 10 9.8 9.8 9.8 9.8 9.8 9.8 9. 6.5 6.5 6.5 6.5 6.4 6.3 6.1 5.8 4-gate 6.6 6.6 6.6 6.6 6.6 6.6 6.6 6.5 Weckwerth et al 2005) and the McGill radar (e.g., Fabry 2004), both with range resolutions of 150 m using the refractivity algorithm described in Fabry (2004).…”

“…The range resolution and range-gate separation for both these radars is 150 m, hence aliasing occurs beyond jDNj folding ' 200 (assuming no noise in the phase changes), whereas for the 250-m gate separation of the Next Generation Weather Radar (NEXRAD) Weather Surveillance Radar-1988 Doppler (WSR-88D) radars (Bodine et al 2010(Bodine et al , 2011, aliasing occurs beyond jDNj folding ' 120. Since the seasonal (and often annual) range of N will often be less than 6120, if a ''reference period'' can be found when N is approximately constant over the clutter domain (i.e., the ground clutter coverage at a particular elevation), then one might expect reliable retrievals to be obtained throughout the year relative to N ref , the reference refractivity field.…”

Sensitivity of Convective Initiation Prediction to Near-Surface Moisture When Assimilating Radar Refractivity: Impact Tests Using OSSEs

“…Processed refractivity data from radar generally have a resolution of about 2-4 km spatially and 4-10 min temporally, depending on radar type, scan strategy, and clutter target density. Given the high demand for high-resolution moisture measurements, studies have been conducted concerning the meteorological applications of refractivity measurements (e.g., Bodine et al 2009Bodine et al , 2011Weckwerth et al 2005). In particular, IHOP_2002 contained a convective initiation component (Weckwerth and Parsons 2006) that also exploited the utilities of radar refractivity data.…”

La réfractivité radar : vers une cartographie de l'humidité en très basse couche de l'atmosphère

“…En été, les variations de réfractivité sont principalement dues à des changements d'humidité et le champ de réfractivité peut être utilisé pour estimer le champ d'humidité dans les très basses couches (Weckwerth et al, 2005 ;Roberts et al, 2008). Les variations d'humidité de petite échelle, accessibles par le biais de la réfractivité par radar, présentent un intérêt météorologique certain, en particulier pour l'étude de l'initiation de la convection (Weckwerth et al, 2005 ;Demoz et al, 2006 ;Fabry, 2006 ;Wakimoto et Murphey, 2010 ;Bodine et al, 2010). En particulier, des études (Montmerle et al, 2002 ;Sun, 2005) ont souligné que la réfractivité radar pouvait être intéressante pour l'assimilation de données dans les modèles numériques de prévision du temps.…”