Israel L. Jirak

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...

Effect of Air Pollution on Precipitation along the Front Range of the Rocky Mountains

Abstract Air pollution generated in industrial and urban areas can act to suppress precipitation by creating a narrow cloud droplet spectrum, which inhibits the collision and coalescence process. In fact, precipitation ratios of elevated sites to upwind coastal urban areas have decreased during the twentieth century for locations in California and Israel while pollution emissions have increased. Precipitation suppression by pollution should also be evident in other areas of the world where shallow, orographic clouds produce precipitation. This study investigates the precipitation trends for sites along the Front Range of the Rocky Mountains to determine the effect of air pollution on precipitation in this region. The examination of precipitation trends reveals that the ratio of upslope precipitation for elevated sites west of Denver and Colorado Springs, Colorado, to upwind urban sites has decreased by approximately 30% over the past half-century. Similar precipitation trends were not found for more prist...

Satellite and radar survey of mesoscale convective system development

Abstract An investigation of several hundred mesoscale convective systems (MCSs) during the warm seasons (April–August) of 1996–98 is presented. Circular and elongated MCSs on both the large and small scales were classified and analyzed in this study using satellite and radar data. The satellite classification scheme used for this study includes two previously defined categories and two new categories: mesoscale convective complexes (MCCs), persistent elongated convective systems (PECSs), meso-β circular convective systems (MβCCSs), and meso-β elongated convective systems (MβECSs). Around two-thirds of the MCSs in the study fell into the larger satellite-defined categories (MCCs and PECSs). These larger systems produced more severe weather, generated much more precipitation, and reached a peak frequency earlier in the convective season than the smaller, meso-β systems. Overall, PECSs were found to be the dominant satellite-defined MCS, as they were the largest, most common, most severe, and most prolific ...

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

Observational Analysis of the Predictability of Mesoscale Convective Systems

Abstract Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environme...

Collaborative Efforts between the United States and United Kingdom to Advance Prediction of High-Impact Weather

AbstractIn recent years, a growing partnership has emerged between the Met Office and the designated U.S. national centers for expertise in severe weather research and forecasting, that is, the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory (NSSL) and the NOAA Storm Prediction Center (SPC). The driving force behind this partnership is a compelling set of mutual interests related to predicting and understanding high-impact weather and using high-resolution numerical weather prediction models as foundational tools to explore these interests.The forum for this collaborative activity is the NOAA Hazardous Weather Testbed, where annual Spring Forecasting Experiments (SFEs) are conducted by NSSL and SPC. For the last decade, NSSL and SPC have used these experiments to find ways that high-resolution models can help achieve greater success in the prediction of tornadoes, large hail, and damaging winds. Beginning in 2012, the Met Office became a contributing partner in ann...

Blended Probabilistic Tornado Forecasts: Combining Climatological Frequencies with NSSL–WRF Ensemble Forecasts

AbstractAttempts at probabilistic tornado forecasting using convection-allowing models (CAMs) have thus far used CAM attribute [e.g., hourly maximum 2–5-km updraft helicity (UH)] thresholds, treati...

Breaking New Ground in Severe Weather Prediction: The 2015 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment

AbstractLed by NOAA’s Storm Prediction Center and National Severe Storms Laboratory, annual spring forecasting experiments (SFEs) in the Hazardous Weather Testbed test and evaluate cutting-edge technologies and concepts for improving severe weather prediction through intensive real-time forecasting and evaluation activities. Experimental forecast guidance is provided through collaborations with several U.S. government and academic institutions, as well as the Met Office. The purpose of this article is to summarize activities, insights, and preliminary findings from recent SFEs, emphasizing SFE 2015. Several innovative aspects of recent experiments are discussed, including the 1) use of convection-allowing model (CAM) ensembles with advanced ensemble data assimilation, 2) generation of severe weather outlooks valid at time periods shorter than those issued operationally (e.g., 1–4 h), 3) use of CAMs to issue outlooks beyond the day 1 period, 4) increased interaction through software allowing participants t...

The Community Leveraged Unified Ensemble (CLUE) in the 2016 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment

CapsuleThe CLUE system represents an unprecedented effort to leverage several academic and government research institutions to help guide NOAA’s operational environmental modeling efforts at the convection-allowing scale.

Evaluation of Multiple Planetary Boundary Layer Parameterization Schemes in Southeast U.S. Cold Season Severe Thunderstorm Environments

AbstractSoutheast U.S. cold season severe weather events can be difficult to predict because of the marginality of the supporting thermodynamic instability in this regime. The sensitivity of this environment to prognoses of instability encourages additional research on ways in which mesoscale models represent turbulent processes within the lower atmosphere that directly influence thermodynamic profiles and forecasts of instability. This work summarizes characteristics of the southeast U.S. cold season severe weather environment and planetary boundary layer (PBL) parameterization schemes used in mesoscale modeling and proceeds with a focused investigation of the performance of nine different representations of the PBL in this environment by comparing simulated thermodynamic and kinematic profiles to observationally influenced ones. It is demonstrated that simultaneous representation of both nonlocal and local mixing in the Asymmetric Convective Model, version 2 (ACM2), scheme has the lowest overall errors ...