Gretchen L. Mullendore

Hydrometeorological Analysis of Tropical Storm Hermine and Central Texas Flash Flooding, September 2010

AbstractHeavy rainfall and flooding associated with Tropical Storm Hermine occurred on 7–8 September 2010 across central Texas, resulting in several flood-related fatalities and extensive property damage. The largest rainfall totals were received near Austin, Texas, and immediately north, with 24-h accumulations at several locations reaching a 500-yr recurrence interval. Among the most heavily impacted drainage basins was the Bull Creek watershed (58 km2) in Austin, where peak flows exceeded 500 m3 s−1. Storm cells were trained over the small watershed for approximately 6 h because of the combination of a quasi-stationary synoptic feature slowing the storm, orographic enhancement from the Balcones Escarpment, and moist air masses from the Gulf of Mexico sustaining the storm. Weather Research and Forecasting Model simulations with and without the Balcones Escarpment terrain indicate that orographic enhancement affected rainfall. The basin received nearly 300 mm of precipitation, with maximum sustained inte...

A Containerized Mesoscale Model and Analysis Toolkit to Accelerate Classroom Learning, Collaborative Research, and Uncertainty Quantification

AbstractNumerical weather prediction (NWP) experiments can be complex and time consuming; results depend on computational environments and numerous input parameters. Delays in learning and obtaining research results are inevitable. Students face disproportionate effort in the classroom or beginning graduate-level NWP research. Published NWP research is generally not reproducible, introducing uncertainty and slowing efforts that build on past results. This work exploits the rapid emergence of software container technology to produce a transformative research and education environment. The Weather Research and Forecasting (WRF) Model anchors a set of linked Linux-based containers, which include software to initialize and run the model, to analyze results, and to serve output to collaborators. The containers are demonstrated with a WRF simulation of Hurricane Sandy. The demonstration illustrates the following: 1) how the often-difficult exercise in compiling the WRF and its many dependencies is eliminated, 2...

Storm Labeling in Three Dimensions (SL3D): A Volumetric Radar Echo and Dual-Polarization Updraft Classification Algorithm

AbstractThis study presents a new storm classification method for objectively stratifying three-dimensional radar echo into five categories: convection, convective updraft, precipitating stratiform, nonprecipitating stratiform, and ice-only anvil. The Storm Labeling in Three Dimensions (SL3D) algorithm utilizes volumetric radar data to classify radar echo based on storm height, depth, and intensity in order to provide a new method for updraft classification and improve upon the limitations of traditional storm classification algorithms. Convective updrafts are identified by searching for three known polarimetric radar signatures: weak-echo regions (bounded and unbounded) in the radar reflectivity factor at horizontal polarization (), differential radar reflectivity () columns, and specific differential phase () columns. Additionally, leveraging the three-dimensional information allows SL3D to improve upon missed identifications of weak convection and intense stratiform rain in traditional two-dimensional ...

Determining the Best Method for Estimating the Observed Level of Maximum Detrainment Based on Radar Reflectivity

AbstractConvective mass transport is the transport of mass from near the surface up to the upper troposphere and lower stratosphere (UTLS) by a deep convective updraft. This transport can alter the chemical makeup and water vapor balance of the UTLS, which affects cloud formation and the radiative properties of the atmosphere. It is, therefore, important to understand the exact altitudes at which mass is detrained from convection. The purpose of this study was to improve upon previously published methodologies for estimating the level of maximum detrainment (LMD) within convection using data from a single ground-based radar. Four methods were used to identify the LMD and validated against dual-Doppler-derived vertical mass divergence fields for six cases with a variety of storm types. The best method for locating the LMD was determined to be the method that used a reflectivity texture technique to determine convective cores and a multilayer echo identification to determine anvil locations. Although an imp...

Modulation of Soil Initial State on WRF Model Performance Over China

The soil state (e.g. temperature and moisture) in a mesoscale numerical prediction model is typically initialized by reanalysis or analysis data that may be subject to large bias. Such bias may lead to unrealistic land–atmosphere interactions. This study shows that the Climate Forecast System Reanalysis (CFSR) dramatically underestimates soil temperature and overestimates soil moisture over most parts of China in the first (0-10cm) and second (10-25cm) soil layers compared to in situ observations in July, 2013. A correction based on the global optimal dual kriging is employed to correct CFSR bias in soil temperature and moisture using in situ observations. To investigate the impacts of the corrected soil state on model forecasts, two numerical model simulations—a control run with CFSR soil state and a disturbed run with the corrected soil state—were conducted using the Weather Research and Forecasting model. All the simulations are initiated four times per day and run 48 hours. Model results show that the corrected soil state, i.e. warmer and drier surface over the most parts of China, can enhance evaporation over wet regions, which changes the overlying atmospheric temperature and moisture. The changes of the lifting condensation level, level of free convection, and water transport due to corrected soil state favor precipitation over wet regions, while prohibiting precipitation over dry regions. Moreover, diagnoses indicate that the remote moisture flux convergence plays a dominant role in the precipitation changes over the wet regions.