The Availability and Use of Satellite Pictures in Recognizing Hazardous Weather

1977 ◽  
pp. 419-435 ◽  
Author(s):  
Stanley E. Wasserman
Keyword(s):  
Hazardous Weather

scholarly journals Evolution of WRF-HAILCAST during the 2014–16 NOAA/Hazardous Weather Testbed Spring Forecasting Experiments

2019 ◽  
Vol 34 (1) ◽  
pp. 61-79 ◽  
Author(s):  
Rebecca D. Adams-Selin ◽  
Adam J. Clark ◽  
Christopher J. Melick ◽  
Scott R. Dembek ◽  
Israel L. Jirak ◽  
...  
Keyword(s):  
Threshold Values ◽  
Severe Storms ◽  
Object Based ◽  
Storm Prediction ◽  
Horizontal Grid ◽  
Grid Based ◽  
Hazardous Weather

Abstract Four different versions of the HAILCAST hail model have been tested as part of the 2014–16 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments. HAILCAST was run as part of the National Severe Storms Laboratory (NSSL) WRF Ensemble during 2014–16 and the Community Leveraged Unified Ensemble (CLUE) in 2016. Objective verification using the Multi-Radar Multi-Sensor maximum expected size of hail (MRMS MESH) product was conducted using both object-based and neighborhood grid-based verification. Subjective verification and feedback was provided by HWT participants. Hourly maximum storm surrogate fields at a variety of thresholds and Storm Prediction Center (SPC) convective outlooks were also evaluated for comparison. HAILCAST was found to improve with each version due to feedback from the 2014–16 HWTs. The 2016 version of HAILCAST was equivalent to or exceeded the skill of the tested storm surrogates across a variety of thresholds. The post-2016 version of HAILCAST was found to improve 50-mm hail forecasts through object-based verification, but 25-mm hail forecasting ability declined as measured through neighborhood grid-based verification. The skill of the storm surrogate fields varied widely as the threshold values used to determine hail size were varied. HAILCAST was found not to require such tuning, as it produced consistent results even when used across different model configurations and horizontal grid spacings. Additionally, different storm surrogate fields performed at varying levels of skill when forecasting 25- versus 50-mm hail, hinting at the different convective modes typically associated with small versus large sizes of hail. HAILCAST was able to match results relatively consistently with the best-performing storm surrogate field across multiple hail size thresholds.

Evaluation of a Probabilistic Forecasting Methodology for Severe Convective Weather in the 2014 Hazardous Weather Testbed

2015 ◽  
Vol 30 (6) ◽  
pp. 1551-1570 ◽  
Author(s):  
Christopher D. Karstens ◽  
Greg Stumpf ◽  
Chen Ling ◽  
Lesheng Hua ◽  
Darrel Kingfield ◽  
...  
Keyword(s):  
Hazard Identification ◽  
Control Test ◽  
Test Bed ◽  
Probabilistic Forecasting ◽  
Test Experiment ◽  
Tornado Warnings ◽  
Probabilistic Forecasts ◽  
Verification Methodology ◽  
Convective Weather ◽  
Hazardous Weather

Abstract A proposed new method for hazard identification and prediction was evaluated with forecasters in the National Oceanic and Atmospheric Administration Hazardous Weather Testbed during 2014. This method combines hazard-following objects with forecaster-issued trends of exceedance probabilities to produce probabilistic hazard information, as opposed to the static, deterministic polygon and attendant text product methodology presently employed by the National Weather Service to issue severe thunderstorm and tornado warnings. Three components of the test bed activities are discussed: usage of the new tools, verification of storm-based warnings and probabilistic forecasts from a control–test experiment, and subjective feedback on the proposed paradigm change. Forecasters were able to quickly adapt to the new tools and concepts and ultimately produced probabilistic hazard information in a timely manner. The probabilistic forecasts from two severe hail events tested in a control–test experiment were more skillful than storm-based warnings and were found to have reliability in the low-probability spectrum. False alarm area decreased while the traditional verification metrics degraded with increasing probability thresholds. The latter finding is attributable to a limitation in applying the current verification methodology to probabilistic forecasts. Relaxation of on-the-fence decisions exposed a need to provide information for hazard areas below the decision-point thresholds of current warnings. Automated guidance information was helpful in combating potential workload issues, and forecasters raised a need for improved guidance and training to inform consistent and reliable forecasts.

scholarly journals Effects of Probabilistic Risk Situation Awareness Tool (RSAT) on Aeronautical Weather-Hazard Decision Making

2020 ◽  
Vol 11 ◽  
Author(s):  
Sweta Parmar ◽  
Rickey P. Thomas
Keyword(s):  
Decision Making ◽  
Situation Awareness ◽  
Cumulative Risk ◽  
Support Condition ◽  
Radar Images ◽  
Awareness Tool ◽  
Risk Situation ◽  
Nexrad Radar ◽  
Uncertainty Information ◽  
Hazardous Weather

We argue that providing cumulative risk as an estimate of the uncertainty in dynamically changing risky environments can help decision-makers meet mission-critical goals. Specifically, we constructed a simplified aviation-like weather decision-making task incorporating Next-Generation Radar (NEXRAD) images of convective weather. NEXRAD radar images provide information about geographically referenced precipitation. NEXRAD radar images are used by both pilots and laypeople to support decision-making about the level of risk posed by future weather-hazard movements. Using NEXRAD, people and professionals have to infer the uncertainty in the meteorological information to understand current hazards and extrapolate future conditions. Recent advancements in meteorology modeling afford the possibility of providing uncertainty information concerning hazardous weather for the current flight. Although there are systematic biases that plague people’s use of uncertainty information, there is evidence that presenting forecast uncertainty can improve weather-related decision-making. The current study augments NEXRAD by providing flight-path risk, referred to as the Risk Situational Awareness Tool (RSAT). RSAT provides the probability that a route will come within 20 NMI radius (FAA recommended safety distance) of hazardous weather within the next 45 min of flight. The study evaluates four NEXRAD displays integrated with RSAT, providing varying levels of support. The “no” support condition has no RSAT (the NEXRAD only condition). The “baseline” support condition employs an RSAT whose accuracy is consistent with current capability in meteorological modeling. The “moderate” support condition applies an RSAT whose accuracy is likely at the top of what is achievable in meteorology in the near future. The “high” support condition provides a level of support that is likely unachievable in an aviation weather decision-making context without considerable technological innovation. The results indicate that the operators relied on the RSAT and improved their performance as a consequence. We discuss the implications of the findings for the safe introduction of probabilistic tools in future general aviation cockpits and other dynamic decision-making contexts. Moreover, we discuss how the results contribute to research in the fields of dynamic risk and uncertainty, risk situation awareness, cumulative risk, and risk communication.

scholarly journals How Well Does an FV3‐Based Model Predict Precipitation at a Convection‐Allowing Resolution? Results From CAPS Forecasts for the 2018 NOAA Hazardous Weather Test Bed With Different Physics Combinations

2019 ◽  
Vol 46 (6) ◽  
pp. 3523-3531 ◽  
Author(s):  
Chunxi Zhang ◽  
Ming Xue ◽  
Timothy A. Supinie ◽  
Fanyou Kong ◽  
Nathan Snook ◽  
...  
Keyword(s):  
Test Bed ◽  
Hazardous Weather
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