Ryan A. Sobash

An Overview of the 2010 Hazardous Weather Testbed Experimental Forecast Program Spring Experiment

The NOAA Hazardous Weather Testbed (HWT) conducts annual spring forecasting experiments organized by the Storm Prediction Center and National Severe Storms Laboratory to test and evaluate emerging scientific concepts and technologies for improved analysis and prediction of hazardous mesoscale weather. A primary goal is to accelerate the transfer of promising new scientific concepts and tools from research to operations through the use of intensive real-time experimental forecasting and evaluation activities conducted during the spring and early summer convective storm period. The 2010 NOAA/HWT Spring Forecasting Experiment (SE2010), conducted 17 May through 18 June, had a broad focus, with emphases on heavy rainfall and aviation weather, through collaboration with the Hydrometeorological Prediction Center (HPC) and the Aviation Weather Center (AWC), respectively. In addition, using the computing resources of the National Institute for Computational Sciences at the University of Tennessee, the Center for A...

Extracting Unique Information from High-Resolution Forecast Models: Monitoring Selected Fields and Phenomena Every Time Step

A new strategy for generating and presenting model diagnostic fields from convection-allowing forecast models is introduced. The fields are produced by computing temporal-maximum values for selected diagnostics at each horizontal grid point between scheduled output times. The two-dimensional arrays containing these maximum values are saved at the scheduled output times. The additional fields have minimal impacts on the size of the output files and the computation of most diagnostic quantities can be done very efficiently during integration of the Weather Research and Forecasting Model. Results show that these unique output fields facilitate the examination of features associated with convective storms, which can change dramatically within typical output intervals of 1‐3 h.

Probabilistic Forecast Guidance for Severe Thunderstorms Based on the Identification of Extreme Phenomena in Convection-Allowing Model Forecasts

AbstractWith the advent of convection-allowing NWP models (CAMs) comes the potential for new forms of forecast guidance. While CAMs lack the required resolution to simulate many severe phenomena associated with convection (e.g., large hail, downburst winds, and tornadoes), they can still provide unique guidance for the occurrence of these phenomena if “extreme” patterns of behavior in simulated storms are strongly correlated with observed severe phenomena. This concept is explored using output from a series of CAM forecasts generated on a daily basis during the spring of 2008. This output is mined for the presence of extreme values of updraft helicity (UH), a diagnostic field used to identify supercellular storms. Extreme values of the UH field are flagged as simulated “surrogate” severe weather reports and the spatial correspondence between these surrogate reports and actual observed severe reports is determined. In addition, probabilistic forecasts [surrogate severe probabilistic forecasts (SSPFs)] are ...

A Feasibility Study for Probabilistic Convection Initiation Forecasts Based on Explicit Numerical Guidance

Abstract The 2011 Spring Forecasting Experiment in the NOAA Hazardous Weather Testbed (HWT) featured a significant component on convection32 initiation (CI). As in previous HWT experiments, the CI study was a collaborative effort between forecasters and researchers, with 34 equal emphasis on experimental forecasting strategies and evaluation of prototype model guidance products. The overarching goal of the CI effort was to identify the primary challenges 36 of the CI-forecasting problem and establish a framework for additional studies and possible routine forecasting of CI. This study confirms that convection-allowing models with grid spacing ~ 4 km38 represent many aspects of the formation and development of deep convection clouds explicitly and with predictive utility. Further, it shows that automated algorithms can 40 skillfully identify the CI process during model integration. However, it also reveals that automated detection of individual convection cells, by itself, provides inadequate guidance for

NCAR’s Experimental Real-Time Convection-Allowing Ensemble Prediction System

AbstractThis expository paper documents an experimental, real-time, 10-member, 3-km, convection-allowing ensemble prediction system (EPS) developed at the National Center for Atmospheric Research (NCAR) in spring 2015. The EPS is particularly unique in that continuously cycling, limited-area, mesoscale ensemble Kalman filter analyses provide diverse initial conditions. In addition to describing the EPS configurations, initial forecast assessments are presented that suggest the EPS can provide valuable severe weather guidance and skillful predictions of precipitation. The EPS output is available to operational forecasters, many of whom have incorporated the products into their toolboxes. Given such rapid embrace of an experimental system by the operational community, acceleration of convection-allowing EPS development is encouraged.

A Real-Time Convection-Allowing Ensemble Prediction System Initialized by Mesoscale Ensemble Kalman Filter Analyses

AbstractIn May and June 2013, the National Center for Atmospheric Research produced real-time 48-h convection-allowing ensemble forecasts at 3-km horizontal grid spacing using the Weather Research and Forecasting (WRF) Model in support of the Mesoscale Predictability Experiment field program. The ensemble forecasts were initialized twice daily at 0000 and 1200 UTC from analysis members of a continuously cycling, limited-area, mesoscale (15 km) ensemble Kalman filter (EnKF) data assimilation system and evaluated with a focus on precipitation and severe weather guidance. Deterministic WRF Model forecasts initialized from GFS analyses were also examined. Subjectively, the ensemble forecasts often produced areas of intense convection over regions where severe weather was observed. Objective statistics confirmed these subjective impressions and indicated that the ensemble was skillful at predicting precipitation and severe weather events. Forecasts initialized at 1200 UTC were more skillful regarding precipita...

The Frequency and Characteristics of Lake-Effect Precipitation Events Associated with the New York State Finger Lakes

Abstract This study presents a climatological analysis of the frequency and characteristics of lake-effect precipitation events that were initiated or enhanced by lakes within the New York State (NYS) Finger Lakes region for the 11 winters (October–March) from 1995/96 through 2005/06. Weather Surveillance Radar-1988 Doppler (WSR-88D) data from Binghamton, New York, were used to identify 125 lake-effect events. Events occurred as 1) a well-defined, isolated precipitation band over and downwind of a lake, 2) an enhancement of mesoscale lake-effect precipitation originating from Lake Ontario and extending southward over an individual Finger Lake, 3) a quasi-stationary mesoscale precipitation band positioned over a lake embedded within extensive regional precipitation from a synoptic weather system, or 4) a transition from one type to another. Results show that lake-effect precipitation routinely develops over lakes that are considerably smaller than lakes previously discussed as being associated with lake-ef...

Climatological Conditions of Lake-Effect Precipitation Events Associated with the New York State Finger Lakes

Abstract A climatological analysis was conducted of the environmental and atmospheric conditions that occurred during 125 identified lake-effect (LE) precipitation events in the New York State Finger Lakes region for the 11 winters (October–March) from 1995/96 through 2005/06. The results complement findings from an earlier study reporting on the frequency and temporal characteristics of Finger Lakes LE events that occurred as 1) isolated precipitation bands over and downwind of a lake (NYSFL events), 2) an enhancement of LE precipitation originating from Lake Ontario (LOenh events), 3) an LE precipitation band embedded within widespread synoptic precipitation (SYNOP events), or 4) a transition from one type to another. In comparison with SYNOP and LOenh events, NYSFL events developed with the 1) coldest temperatures, 2) largest lake–air temperature differences, 3) weakest wind speeds, 4) highest sea level pressure, and 5) lowest height of the stable-layer base. Several significant differences in conditio...

The Impact of Covariance Localization for Radar Data on EnKF Analyses of a Developing MCS: Observing System Simulation Experiments

AbstractSeveral observing system simulation experiments (OSSEs) were performed to assess the impact of covariance localization of radar data on ensemble Kalman filter (EnKF) analyses of a developing convective system. Simulated Weather Surveillance Radar-1988 Doppler (WSR-88D) observations were extracted from a truth simulation and assimilated into experiments with localization cutoff choices of 6, 12, and 18 km in the horizontal and 3, 6, and 12 km in the vertical. Overall, increasing the horizontal localization and decreasing the vertical localization produced analyses with the smallest RMSE for most of the state variables. The convective mode of the analyzed system had an impact on the localization results. During cell mergers, larger horizontal localization improved the results. Prior state correlations between the observations and state variables were used to construct reverse cumulative density functions (RCDFs) to identify the correlation length scales for various observation-state pairs. The OSSE ...

Assimilating Surface Mesonet Observations with the EnKF to Improve Ensemble Forecasts of Convection Initiation on 29 May 2012

AbstractSurface data assimilation (DA) has the potential to improve forecasts of convection initiation (CI) and short-term forecasts of convective evolution. Since the processes driving CI occur on scales inadequately observed by conventional observation networks, mesoscale surface networks could be especially beneficial given their higher temporal and spatial resolution. This work aims to assess the impact of high-frequency assimilation of mesonet surface DA on ensemble forecasts of CI initialized with ensemble Kalman filter (EnKF) analyses of the 29 May 2012 convective event over the southern Great Plains.Mesonet and conventional surface observations were assimilated every 5 min for 3 h from 1800 to 2100 UTC and 3-h ensemble forecasts were produced. Forecasts of CI timing and location were improved by assimilating the surface datasets in comparison to experiments where mesonet data were withheld. This primarily occurred due to a more accurate representation of the boundary layer moisture profile across ...