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Sang-Ki Lee, Hosmay Lopez, Dongmin Kim, Andrew T. Wittenberg, and Arun Kumar

Abstract

This study presents an experimental model for Seasonal Probabilistic Outlook for Tornadoes (SPOTter) in the contiguous United States for March, April, and May and evaluates its forecast skill. This forecast model uses the leading empirical orthogonal function modes of regional variability in tornadic environmental parameters (i.e., low-level vertical wind shear and convective available potential energy), derived from the NCEP Coupled Forecast System, version 2, as the primary predictors. A multiple linear regression is applied to the predicted modes of tornadic environmental parameters to estimate U.S. tornado activity, which is presented as the probability for above-, near-, and below-normal categories. The initial forecast is carried out in late February for March–April U.S. tornado activity and then is updated in late March for April–May activity. A series of reforecast skill tests, including the jackknife cross-validation test, shows that the probabilistic reforecast is overall skillful for predicting the above- and below-normal area-averaged activity in the contiguous United States for the target months of both March–April and April–May. The forecast model also successfully reforecasts the 2011 super-tornado-outbreak season and the other three most active U.S. tornado seasons in 1982, 1991, and 2008, and thus it may be suitable for an operational use for predicting future active and inactive U.S. tornado seasons. However, additional tests show that the regional reforecast is skillful for March–April activity only in the Ohio Valley and South and for April–May activity only in the Southeast and Upper Midwest. These and other limitations of the current model, along with the future advances needed to improve the U.S. regional-scale tornado forecast, are discussed.

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Myung-Sook Park, Myong-In Lee, Dongmin Kim, Michael M. Bell, Dong-Hyun Cha, and Russell L. Elsberry

Abstract

The effects of land-based convection on the formation of Tropical Storm Mekkhala (2008) off the west coast of the Philippines are investigated using the Weather Research and Forecasting Model with 4-km horizontal grid spacing. Five simulations with Thompson microphysics are utilized to select the control-land experiment that reasonably replicates the observed sea level pressure evolution. To demonstrate the contribution of the land-based convection, sensitivity experiments are performed by changing the land of the northern Philippines to water, and all five of these no-land experiments fail to develop Mekkhala.

The Mekkhala tropical depression develops when an intense, well-organized land-based mesoscale convective system moves offshore from Luzon and interacts with an oceanic mesoscale system embedded in a strong monsoon westerly flow. Because of this interaction, a midtropospheric mesoscale convective vortex (MCV) organizes offshore from Luzon, where monsoon convection continues to contribute to low-level vorticity enhancement below the midlevel vortex center. In the no-land experiments, widespread oceanic convection induces a weaker midlevel vortex farther south in a strong vertical wind shear zone and subsequently farther east in a weaker monsoon vortex region. Thus, the monsoon convection–induced low-level vorticity remained separate from the midtropospheric MCV, which finally resulted in a failure of the low-level spinup. This study suggests that land-based convection can play an advantageous role in TC formation by influencing the intensity and the placement of the incipient midtropospheric MCV to be more favorable for TC low-level circulation development.

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