Sensitivity of Dryline Convection Forecasts to Upstream Forecast Errors for Two Weakly Forced MPEX Cases

Abstract

The sensitivity of convective forecasts along the Texas dryline to upstream forecast fields at earlier lead times is evaluated for two consecutive days (27-28 May) characterized by no clear synoptic forcing for convection initiation (CI) during the 2013 Mesoscale Predictability Experiment (MPEX) by applying the ensemble-based sensitivity technique to convection-allowing WRF ensemble forecasts. For both cases, the members with stronger convection are characterized by higher water vapor just above the top of the boundary layer, which is associated with lower convective inhibition (CIN) at the time of CI. Forecast convection is sensitive to the lowertropospheric water vapor and zonal wind at earlier lead times farther south along the dryline, such that increasing the water vapor and/or making the wind more easterly is associated with more convection. For 28 May, the water vapor along the dryline is also sensitive to the convection that occurs around 0600 UTC, which leads to cold pool-induced surface divergence that subsequently shifts the dryline north or south. Ensemble members that correctly have decreased convection in the Texas Panhandle on 28 May have more accurate forecasts of water vapor and meridional wind with respect to dropwindsondes in the sensitive region 9 h prior to CI compared to members with more extensive convection. Reducing the 0-h water vapor within the sensitive region can suppress convection in members with extensive convection; however, increasing the 0-h water vapor does not lead to more convection in members without convection.

Large impact of tiny model domain shifts for the Pentecost 2014 mesoscale convective system over Germany

“…Recent studies by Schneider et al (2019) and Keil et al (2019) have also shown that different assumptions for the number of cloud condensation nuclei could be included in convective-scale ensemble forecasting but only if the model employs a double-moment microphysics scheme. Because of the fundamental uncertainties in the simulations due to nonlinearities of the model equations, several studies have noted the significant impact of initial boundary conditions (IBCs) and lateral boundary conditions (LBCs) on the simulation of convective precipitation for some situations (e.g., Hohenegger et al, 2006;Trentmann et al, 2009;Richard et al, 2011;Bouttier and Raynaud, 2018) and that ensemble members with the most accurate initial and boundary conditions are most skillful at predicting the location of convective initiation (Barrett et al, 2015). One common approach for accounting for uncertainties in the initial and boundary conditions is that perturbations entering the model from the lateral boundaries can be provided by different driving ensemble prediction system (EPS) members as is the case for COSMO-LEPS (Montani et al, 2011) or COSMO-DE-EPS (Gebhardt et al, 2011;Kühnlein et al, 2014).…”

Review: Large impact of tiny model domain shifts for the Pentecost 2014 MCS over Germany

“…I do have some concerns regarding the motivation and methodology for this work. While the authors motivate the work as a worthwhile approach to improve convectionallowing model (CAM) forecasts, effectively creating sufficient spread across the forecast distribution, I struggle to see the benefit of this domain-shifting approach over other well-documented lateral boundary perturbation techniques (e.g., Torn et al 2016), and I don't feel the author's sufficiently demonstrated this benefit in the introduction. Additionally, I believe the authors try to attribute the forecast variability to their methodology (i.e., domain shifting), but I do not feel there is substantial corroborating evidence to support this conclusion.…”

“…Sensitivity approaches such as those demonstrated by Schumacher and Davis (2010) and Ancell and Hakim (2007) could be valuable additions to the analysis. I invite the authors to consult a number of papers that apply sensitivity analyses to convection-resolving forecasts as well: Bednarczyk and Ancell (2015), Hill et al (2016), Limpert and Houston (2018), and Torn et al (2016). Additionally, other aspects of predictability could be garnered through initializing ensemble forecasts at later times, which may answer the particular question of whether CI is the limiting factor of predictability.…”

“…6. Lines 85-91: What benefit does "domain shifting" have over other traditional lateral boundary perturbation techniques (e.g., Torn et al 2016)? I have not been convinced in the introduction that there is significant benefit in developing a new technique to perturb boundary conditions.…”

“…Alternatively, the authors could instead focus on the true predictability of the event (rather than the domain shifting idea) and include some additional predictability analysis (e.g., ensemble sensitivity). See Schumacher and Davis (2010), Ancell and Hakim (2007), Bednarczyk and Ancell (2015), Hill et al (2016), andTorn et al (2016) for some examples of sensitivity analysis for precipitation and high-impact weather forecasts. (Major comment above) 7.…”