Understanding Severe Weather Processes
Convection Initiation Research (IHOP)
A key focus of the International H2O Project (IHOP_2002) was the observation of the atmospheric convective boundary layer (BL) on the U.S. southern Great Plains with a dense array of mobile observing systems, with the main objective of deducing the processes governing convection initiation (CI) near surface-based boundaries. An NSSL armada led by Conrad Ziegler and Erik Rasmussen provided IHOP with observations from a mobile 5-cm SMART radar, 9 mobile mesonets, a mobile sounding system, and 2 mobile digital cloud field cameras. Three “Doppler-on-Wheels” mobile radars were coordinated with the SMART radar by Profs. Yvette Richardson and Paul Markowski (Penn State University), allowing detailed analysis of Doppler-derived BL airflow in post-analysis. NSSL’s mobile platforms were closely coordinated via the NSSL field coordination (FC) vehicle with other microwave and millimeter-wavelength Doppler radars, differential absorption (water vapor sensing) lidars, research aircraft, and both mobile and fixed sounding and profiling systems and airborne dropsondes. In response to the USWRP objective to improve storm forecasts, IHOP directly addressed several key aspects of the USWRP’s warm-season quantitative precipitation forecasting (QPF) theme. One of several foci of IHOP was to learn how the coevolving fields of BL airflow, temperature, and water vapor control the initiation or suppression of deep, moist convection.
NSSL scientists are investigating various aspects of cumulus formation and the CI process with IHOP data. The objectives are to understand how rolls and boundaries such as fronts and drylines develop and force cloud and storm formation and to use improved process knowledge to help improve convection initiation forecasting. Special emphases include cloud-mesoscale analysis of field observations along with modeling and data assimilation studies. A three-dimensional cloud-mesoscale model is used with either real-data or parametric initialization approaches to identify important mesoscale processes and sensitivities influencing boundary evolution and CI. Data assimilation research investigates optimal strategies for blending the various remote and in-situ observations to obtain complete and internally consistent 4-D analysis fields of wind, pressure, virtual temperature, water vapor mixing ratio, and clouds in the BL.
