MCS Rainfall Forecast Accuracy as a Function of Large-Scale Forcing

Abstract

The large-scale forcing associated with 20 mesoscale convective system (MCS) events has been evaluated to determine how the magnitude of that forcing influences the rainfall forecasts made with a 10-km grid spacing version of the Eta Model. Different convective parameterizations and initialization modifications were used to simulate these Upper Midwest events. Cases were simulated using both the Betts-Miller-JanjiÄ ‡ (BMJ) and the Kain-Fritsch (KF) convective parameterizations, and three different techniques were used to improve the initialization of mesoscale features important to later MCS evolution. These techniques included a cold pool initialization, vertical assimilation of surface mesoscale observations, and an adjustment to initialized relative humidity based on radar echo coverage. As an additional aspect in this work, a morphology analysis of the 20 MCSs was included. Results suggest that the model using both schemes performs better when net large-scale forcing is strong, which typically is the case when a cold front moves across the domain. When net forcing is weak, which is often the case in midsummer situations north of a warm or stationary front, both versions of the model perform poorly. Runs with the BMJ scheme seem to be more affected by the magnitude of surface frontogenesis than the KF runs. Runs with the KF scheme are more sensitive to the CAPE amount than the BMJ runs. A fairly well-defined split in morphology was observed, with squall lines having trading stratiform regions likely in scenarios associated with higher equitable threat scores (ETSs) and nonlinear convective clusters strongly dominating the more poorly forecast weakly forced events.

On the Impact of WRF Model Vertical Grid Resolution on Midwest Summer Rainfall Forecasts

“…3a), a result common for warm-season events (e.g., Gallus and Segal 2001;Jankov and Gallus 2004). The ETS values were noticeably worse in 62L than in 31L for the lowest rainfall threshold for five microphysical schemes, possibly because of the more frequent grid cell saturation that was found (as evaluated later in this section), which lead to higher biases (more grid points with rainfall) and higher bias errors (Fig.…”

The Impact of Large-Scale Forcing on Skill of Simulated Convective Initiation and Upscale Evolution with Convection-Allowing Grid Spacings in the WRF*

“…The present study followed the method used in Jankov and Gallus (2004) to determine the large-scale forcing present at initiation. RUC 20-km analyses 1 (on NCEP grid 252) were used to represent observations.…”

“…The strength of forcing for initiation on the large scale and the clarity of definition of surface boundaries that force surface-based deep, moist convection have been shown to impact how well a numerical model is able to predict initiation (Jankov and Gallus 2004;Szoke et al 2004;Wilson and Roberts 2006). Wilson and Roberts (2006) noted a 10-km grid spacing version of the Rapid Update Cycle (RUC) model predicted the initiation of storms better when the forcing mechanism was a synoptic front as opposed to a gust front.…”

“…Jankov and Gallus (2004) discovered using traditional contingency table skill measures applied to 10-km Eta Model output that QPF skill for MCSs was better when the large-scale forcing was stronger. The present study examines if the same relationship holds for 3-km grid spacing using the Weather Research and Forecasting model (WRF), but focuses instead on initiation and upscale evolution using object-based and neighborhood-based measures of skill as well as the traditional skill measures equitable threat score (ETS) and frequency bias.…”

Prediction of Convective Morphology in Near-Cloud-Permitting WRF Model Simulations

“…The test showed cases with scores under 0.50 tended to have significantly warmer potential temperatures at the level of maximum theta-E and significantly lower 0-6 km bulk shear values than cases with scores over 0.50 with at least 90% confidence (Table 4) reflects the large-scale forcing, this result implies mode might be better predicted for cases with stronger larger-scale forcing than weaker forcing, a result found to be true for QPF in convection-parameterized model runs (Jankov and Gallus 2004). The average potential temperature at the level of maximum theta-E was 3.3 K warmer in the low-scoring cases than the better scoring cases.…”