1) The study analyzed 58 thunderstorms near Cape Canaveral to develop techniques for predicting the cessation of lightning.
2) Preliminary results found that a log-linear curve best fit the distribution of times between the last and second-to-last lightning flash. This could be used to create climatological guidance for canceling lightning advisories.
3) Log-linear and negative exponential curves provided good fits for the decaying lightning flash rates of composite and individual thunderstorms. Integrating these curves could predict when the probability of another lightning flash falls below an operational threshold.
Ilkay Altintas from the San Diego Supercomputer Center gave this talk at the HPC User Forum.
"WIFIRE is an integrated system for wildfire analysis, with specific regard to changing urban dynamics and climate. The system integrates networked observations such as heterogeneous satellite data and real-time remote sensor data, with computational techniques in signal processing, visualization, modeling, and data assimilation to provide a scalable method to monitor such phenomena as weather patterns that can help predict a wildfire's rate of spread."
Watch the video: https://wp.me/p3RLHQ-inQ
Learn more: https://wifire.ucsd.edu/https://wifire.ucsd.edu/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
The New Era of NO2 and SO2 National Ambient Air Quality StandardsAll4 Inc.
The document summarizes the new national ambient air quality standards for nitrogen dioxide and sulfur dioxide. The new 1-hour standards are very stringent, and compliance will require facilities that emit over 100 tons per year of these pollutants to conduct air quality modeling to demonstrate they do not cause violations. States will need to develop plans by 2013 to achieve the standards through measures like more stringent emission limits and monitoring requirements. Facilities should prepare for potential modeling requests from states by reviewing existing modeling and considering emission reductions.
Numerous studies have found an average increase in extreme precipitation for both the U.S. and Northern Hemisphere mid-latitude land areas, consistent with the expectations arising from the observed increase in greenhouse gas concentrations (now more than 40% above pre-industrial levels). However, there are important regional variations in these trends that are not fully explained. These trend studies are typically based on direct analyses of observational station data. Such analyses confront multiple challenges, such as incomplete data and uneven spatial coverage of stations. Central scientific questions related to this general finding are: Are there changes in weather system phenomenology that are contributing to this observed increase? What is the contribution of increases in atmospheric water vapor? There are also questions related to application of potential future changes in planning. Because of the rarity (by definition) of extreme events, trends are mostly found only when aggregating over space. When would we expect to see a signal at the local level? What are the uncertainties surrounding future changes and their potential incorporation into future design? Further development of statistical/mathematical methods, or innovative application of existing methods, is desirable to aid scientists in exploring these central scientific questions. This talk will describe characteristics of the observation record and the issues surrounding the above questions.
ERM F&GPro is 3D fire and gas mapping software that considers all facility elements to accurately map detection coverage. It models fires as area sources rather than points to produce more realistic results. ERM uses the software to conduct fire and gas mapping studies for clients according to industry standards. The methodology involves importing 3D models, determining required coverage, mapping detection areas while accounting for obstacles, and improving detector layouts if needed. Results are presented as coverage maps and detector locations.
Fuqing Zhang, Professor, Department of Meteorology and Department of Statistics; Director, Penn State Center for Advanced Data Assimilation and Predictability Techniques;
Pennsylvania State University - November 2017 UCAR Congressional Briefing
The document is Karl Nilsson's doctoral thesis which uses numerical modeling to study wind turbine wakes and wake interactions. It summarizes the key findings of the research which included: 1) validating numerical simulations of the Lillgrund wind farm against power production data, 2) analyzing uncertainties in the rotor modeling approach, and 3) evaluating the impact of including a power controller in the simulations. The research provides insights into modeling wind farm flows and optimizing wind farm layouts.
This document summarizes a thesis by Alice Gillespie that developed an artificial neural network model called NARX to forecast short-term sea surface elevation for applications in wave energy conversion. The NARX model predicts wave-by-wave surface elevation time series based on previous observations alone. Various preprocessing techniques were investigated as inputs to improve forecast accuracy, including filtering the input data in time and frequency domains and using wavelet transformations. The goal was to develop a model that could reliably forecast sea elevation for up to 3 wave periods (approximately 45 seconds) with minimal error accumulation for use in optimizing wave energy converters.
Recovery of aftershock sequences using waveform cross correlation: from catas...Ivan Kitov
Description of a software package for signal detection and association using waveform cross correlation. Recovery of aftershock sequences of the largest events: Sumatra 2004 and Tohoku 2011. Finding of a small aftershock of the September 9, 2016 DPRK test.
Ilkay Altintas from the San Diego Supercomputer Center gave this talk at the HPC User Forum.
"WIFIRE is an integrated system for wildfire analysis, with specific regard to changing urban dynamics and climate. The system integrates networked observations such as heterogeneous satellite data and real-time remote sensor data, with computational techniques in signal processing, visualization, modeling, and data assimilation to provide a scalable method to monitor such phenomena as weather patterns that can help predict a wildfire's rate of spread."
Watch the video: https://wp.me/p3RLHQ-inQ
Learn more: https://wifire.ucsd.edu/https://wifire.ucsd.edu/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
The New Era of NO2 and SO2 National Ambient Air Quality StandardsAll4 Inc.
The document summarizes the new national ambient air quality standards for nitrogen dioxide and sulfur dioxide. The new 1-hour standards are very stringent, and compliance will require facilities that emit over 100 tons per year of these pollutants to conduct air quality modeling to demonstrate they do not cause violations. States will need to develop plans by 2013 to achieve the standards through measures like more stringent emission limits and monitoring requirements. Facilities should prepare for potential modeling requests from states by reviewing existing modeling and considering emission reductions.
Numerous studies have found an average increase in extreme precipitation for both the U.S. and Northern Hemisphere mid-latitude land areas, consistent with the expectations arising from the observed increase in greenhouse gas concentrations (now more than 40% above pre-industrial levels). However, there are important regional variations in these trends that are not fully explained. These trend studies are typically based on direct analyses of observational station data. Such analyses confront multiple challenges, such as incomplete data and uneven spatial coverage of stations. Central scientific questions related to this general finding are: Are there changes in weather system phenomenology that are contributing to this observed increase? What is the contribution of increases in atmospheric water vapor? There are also questions related to application of potential future changes in planning. Because of the rarity (by definition) of extreme events, trends are mostly found only when aggregating over space. When would we expect to see a signal at the local level? What are the uncertainties surrounding future changes and their potential incorporation into future design? Further development of statistical/mathematical methods, or innovative application of existing methods, is desirable to aid scientists in exploring these central scientific questions. This talk will describe characteristics of the observation record and the issues surrounding the above questions.
ERM F&GPro is 3D fire and gas mapping software that considers all facility elements to accurately map detection coverage. It models fires as area sources rather than points to produce more realistic results. ERM uses the software to conduct fire and gas mapping studies for clients according to industry standards. The methodology involves importing 3D models, determining required coverage, mapping detection areas while accounting for obstacles, and improving detector layouts if needed. Results are presented as coverage maps and detector locations.
Fuqing Zhang, Professor, Department of Meteorology and Department of Statistics; Director, Penn State Center for Advanced Data Assimilation and Predictability Techniques;
Pennsylvania State University - November 2017 UCAR Congressional Briefing
The document is Karl Nilsson's doctoral thesis which uses numerical modeling to study wind turbine wakes and wake interactions. It summarizes the key findings of the research which included: 1) validating numerical simulations of the Lillgrund wind farm against power production data, 2) analyzing uncertainties in the rotor modeling approach, and 3) evaluating the impact of including a power controller in the simulations. The research provides insights into modeling wind farm flows and optimizing wind farm layouts.
This document summarizes a thesis by Alice Gillespie that developed an artificial neural network model called NARX to forecast short-term sea surface elevation for applications in wave energy conversion. The NARX model predicts wave-by-wave surface elevation time series based on previous observations alone. Various preprocessing techniques were investigated as inputs to improve forecast accuracy, including filtering the input data in time and frequency domains and using wavelet transformations. The goal was to develop a model that could reliably forecast sea elevation for up to 3 wave periods (approximately 45 seconds) with minimal error accumulation for use in optimizing wave energy converters.
Recovery of aftershock sequences using waveform cross correlation: from catas...Ivan Kitov
Description of a software package for signal detection and association using waveform cross correlation. Recovery of aftershock sequences of the largest events: Sumatra 2004 and Tohoku 2011. Finding of a small aftershock of the September 9, 2016 DPRK test.
This document describes research conducted using the NASA/GISS Atmosphere-Ocean Model as part of the Atmospheric Model Intercomparison Project (AMIP). The researcher interpolated AMIP input files, including sea surface temperature, sea ice cover, and sea ice thickness data, from a 1x1 degree resolution to a 5x4 degree resolution for use in the NASA/GISS Model. They then replaced the Model's climatological values for those variables with the interpolated AMIP values. The researcher compared the Model's sea ice thickness results to those from AMIP and found similarities. They also produced diagnostic output files from a 17-year AMIP II simulation to be analyzed as part of ongoing AMIP research efforts.
This document provides an overview of a dissertation submitted by Ranga Perera for the degree of MSc in Technology Management. The dissertation aims to develop a consumer technology adoption model for mobile data services in Sri Lanka that incorporates both utilitarian and hedonic value propositions. The dissertation reviews relevant literature, proposes a research methodology involving surveys, and plans to test hypotheses regarding factors that influence consumer adoption of two mobile data services - short message service and mobile ringtones.
Mohammad Khanbeiki has over 10 years of experience in materials engineering, non-destructive testing, and corrosion supervision in Iran's oil and gas industry. He holds an M.S. in Materials Engineering and a B.S. in Metallurgical Engineering. His current role is Head Office at RezvanShahr Gas Office for the National Iranian Gas Company. He is fluent in English and Persian, and has extensive technical skills including operation of NDT equipment, familiarity with oil and gas standards, and experience inspecting and maintaining pipelines and pressure vessels.
This document provides a summary of Alan H. Goldsmith's experience and qualifications for an Administrator position. Over his 25+ year career, he has held several Executive Director roles within Jewish non-profit organizations, overseeing multi-million dollar budgets and managing large staffs. His experience includes financial management, facilities oversight, grant writing, and programming leadership. He holds two Master's degrees and has a proven track record of cutting costs while achieving organizational goals.
El documento trata sobre las dificultades que enfrentan las mujeres en la sociedad. Brevemente describe algunos de los desafíos a los que se enfrentan las mujeres, como la discriminación y la falta de derechos y oportunidades.
- Project Title: Seoul City Weather Data Analysis
- Course name: Principles and Practice in Data Mining
- Semester: Autumn 2016
- Professor: Yuran SEO
- Sungkyunkwan University
- Department: Consumer & Family Science
- Name: Lee dong hee
- Contact: molou@naver.com
James Ervin Glover has conducted research in several areas including:
1) Developing statistical methods and algorithms for analyzing individual differences in head-related transfer functions which measure how sound is localized.
2) Performing statistical quality control research on particulate emissions.
3) Converting engineering programs between computing platforms and environments like the Cray supercomputer and workstations.
4) Developing routines to convert data between binary formats used by different computing systems to facilitate analysis.
Использование продуктов Autodesk для автоматизации проектирования гидротехнич...SAPR-Peterburg
Использование продуктов Autodesk для автоматизации проектирования гидротехнических сооружений
Доклад начальника отдела внедрения САПР в ПГС
Бюро ESG А. Антонова
This document provides an overview of e-commerce. It defines commerce as the buying and selling of goods and e-commerce as commerce that takes place electronically over computer systems. The document then describes the different types of e-commerce including business-to-business, business-to-consumer, consumer-to-consumer, and business-to-government. The pros and cons of e-commerce are listed as reduced prices and easy access versus inability to examine products personally and risk of credit card theft. E-commerce is concluded to have brought more global connectivity and economic advancement.
1. The document summarizes the educational background and academic records of Engineer Ahmed Rafique Aziz. It includes details of his Bachelor of Science degree in Electrical and Electronics Engineering from Khulna University of Engineering and Technology, as well as his secondary and higher secondary examination results.
2. Key details include Ahmed obtaining a CGPA of 2.40 on a 4.0 scale for his bachelor's degree, equivalent to 53% marks. For his Higher Secondary Certificate, he scored 73.58%, and for Secondary School Certificate he scored 82.73%.
3. The document also outlines the course contents and materials Ahmed studied for mathematics, science, and English at different educational levels, along with his overall results analysis
The Man Made Effects on Space Weather Tiger Team was established to study potential impacts of human activities on space weather and ensure the space weather architecture study addressed these impacts. The team identified differences between natural and man-made space weather effects, such as the size and duration of electromagnetic and particle radiation. They found that space weather sensors may not adequately detect nuclear events and recommended integrating nuclear detection and space weather data, establishing an agency responsible for characterizing nuclear events, and expanding satellite coverage to reliably monitor radiation belt evolution.
This document describes a study conducted by NASA and the 45th Weather Squadron to develop new statistical methods for predicting the end of lightning in thunderstorms near Cape Canaveral. 58 local thunderstorms were analyzed to create models of lightning flash rates over time. Two approaches were taken: 1) analyzing the distribution of times between the last two lightning flashes, and 2) curve-fitting slowing flash rates in decaying storms. The goal is to predict the probability of additional lightning flashes to help forecasters end advisories more quickly while maintaining safety. Future work includes expanding the analysis and developing software to automatically predict lightning cessation in real-time.
The document describes a study that used machine learning models to predict the power output of horizontal solar photovoltaic panels using weather and location data from 12 sites in the northern hemisphere. A random forest regression model was able to predict panel power output with an R2 value of 0.94 based on variables like temperature, humidity, wind speed, and cloud ceiling without using direct solar irradiation data. The random forest model found temperature, humidity, and cloud ceiling to be the most important predictor variables. The study aims to accurately predict panel output without the challenges of modeling direct irradiation data.
This article discusses the advantages of Blunt Rod (BR) Lightning Protection over Nonconventional early streamer emission (ESE) and lightning dissipation array (LDA) approaches.
This document provides a summary of a doctoral thesis focused on uncertainty quantification in structural responses of offshore monopile wind turbines. The thesis contains six main parts: (1) introduction to the context, (2) stochastic vs. deterministic approaches, (3) aspects of the research, (4) results, (5) contributions to existing knowledge, and (6) conclusions and future agenda. Three papers are developed as part of the research, focusing on the influence of uncertainties in wave parameters, wind shear, and simulation length on extreme turbine responses. The research finds wave loading to be an important factor and develops methods to quantify sensitivity to input parameter uncertainties and flexible soil modeling.
The document describes the development of an adaptive weather sensing framework using phased array radar. The framework consists of four main processes: 1) storm cell identification using reflectivity data, 2) storm cell tracking to associate cells over time, 3) task configuration to determine optimal update times, and 4) scheduling of tasks. Simulated phased array radar observations were generated from operational WSR-88D data to test the framework. Results demonstrated the feasibility of adaptively scanning regions of interest with different update times while maintaining surveillance, allowing for higher temporal resolution compared to conventional radar sensing.
TRACKING ANALYSIS OF HURRICANE GONZALO USING AIRBORNE MICROWAVE RADIOMETERjmicro
There is a huge consideration in the use of microwave airborne radiometry for remote sensing instead of satellite, the important role of airborne way is how to provide high accuracy real time data. The airborne hurricane tracking is an important method compared with the space borne method, which is developed by NASA Marshall Space Flight center to provide high resolution measurements. By flying special aircraft equipment using synthetic thinned array radiometry technology and included all critical measurements such as hurricane eye location, speed of wind and the pressure. This paper describes the data analysis of best track positions for Hurricane Gonzalo based on the date collected by airborne microwave radiometry. Significant analysis comes from comparing the airborne data with the surface observations from ship reports. The vast majority is to estimate peak intensity and minimum central pressure of Gonzalo from 12 to 19 October 2014, based on blend of SFMR flight-level winds and pressure retrievals from observing brightness temperatures. SFMR: Stepped-Frequency Microwave Radiometer is a highly developed tool developed by the Langley Research Center that is designed to measure the wind speed at the ocean’s surface, and the rain fall rates within the storm accurately and continuously. The work also addresses the realistic details of the locations and the valuable information about the pressure and wind speed, which is very critical to predict the growth and movement to get the idea for future monitoring of the hurricane disasters. Also presents a conceptual of step frequency microwave radiometer in airborne side. The objective of this research is tracking analysis techniques based on comparing the satellite, ship and airborne reports to get higher accuracy. The system operates at four spaced frequencies in the range between 4 GHz and 7 GHz provides wide measurements between ± 45 incidence angle. Gonzalo 2014 is an example; the best results of retrieved wind speed, locations and pressure are presented. There are several national projects have been developed for earth observation, such as fire, hurricane and border surveillance. In this work, the efficient high resolution techniques of C-band, four-frequency, the work also addresses a valuable information comes from the airborne system and the prediction way of the growth and movement of hurricanes. In passive microwave remote sensing from space at C band has the penetrating advantages of atmosphere. Airborne system is able to work in full Polari-metric in four bands, C, X, S, L and P-band, which cover the wavelengths from 3 to 85 cm. The modes of measurement contain single channel operation wavelength and polarization.
This document summarizes a spatial analysis of tornado risk in East Tennessee. It analyzes tornado start point density using kernel density estimation within 25 miles of each point, focusing on the area covered by the NWS Morristown office. Statistics show areas of anomalously high density northeast of the French Broad River Valley have density values above the mean. While no definitive conclusions can be drawn, the results provide some support for previous research finding higher tornado risk near terrain features like river valleys. Future modeling studies are suggested to better understand how terrain may influence tornado formation.
This document describes research conducted using the NASA/GISS Atmosphere-Ocean Model as part of the Atmospheric Model Intercomparison Project (AMIP). The researcher interpolated AMIP input files, including sea surface temperature, sea ice cover, and sea ice thickness data, from a 1x1 degree resolution to a 5x4 degree resolution for use in the NASA/GISS Model. They then replaced the Model's climatological values for those variables with the interpolated AMIP values. The researcher compared the Model's sea ice thickness results to those from AMIP and found similarities. They also produced diagnostic output files from a 17-year AMIP II simulation to be analyzed as part of ongoing AMIP research efforts.
This document provides an overview of a dissertation submitted by Ranga Perera for the degree of MSc in Technology Management. The dissertation aims to develop a consumer technology adoption model for mobile data services in Sri Lanka that incorporates both utilitarian and hedonic value propositions. The dissertation reviews relevant literature, proposes a research methodology involving surveys, and plans to test hypotheses regarding factors that influence consumer adoption of two mobile data services - short message service and mobile ringtones.
Mohammad Khanbeiki has over 10 years of experience in materials engineering, non-destructive testing, and corrosion supervision in Iran's oil and gas industry. He holds an M.S. in Materials Engineering and a B.S. in Metallurgical Engineering. His current role is Head Office at RezvanShahr Gas Office for the National Iranian Gas Company. He is fluent in English and Persian, and has extensive technical skills including operation of NDT equipment, familiarity with oil and gas standards, and experience inspecting and maintaining pipelines and pressure vessels.
This document provides a summary of Alan H. Goldsmith's experience and qualifications for an Administrator position. Over his 25+ year career, he has held several Executive Director roles within Jewish non-profit organizations, overseeing multi-million dollar budgets and managing large staffs. His experience includes financial management, facilities oversight, grant writing, and programming leadership. He holds two Master's degrees and has a proven track record of cutting costs while achieving organizational goals.
El documento trata sobre las dificultades que enfrentan las mujeres en la sociedad. Brevemente describe algunos de los desafíos a los que se enfrentan las mujeres, como la discriminación y la falta de derechos y oportunidades.
- Project Title: Seoul City Weather Data Analysis
- Course name: Principles and Practice in Data Mining
- Semester: Autumn 2016
- Professor: Yuran SEO
- Sungkyunkwan University
- Department: Consumer & Family Science
- Name: Lee dong hee
- Contact: molou@naver.com
James Ervin Glover has conducted research in several areas including:
1) Developing statistical methods and algorithms for analyzing individual differences in head-related transfer functions which measure how sound is localized.
2) Performing statistical quality control research on particulate emissions.
3) Converting engineering programs between computing platforms and environments like the Cray supercomputer and workstations.
4) Developing routines to convert data between binary formats used by different computing systems to facilitate analysis.
Использование продуктов Autodesk для автоматизации проектирования гидротехнич...SAPR-Peterburg
Использование продуктов Autodesk для автоматизации проектирования гидротехнических сооружений
Доклад начальника отдела внедрения САПР в ПГС
Бюро ESG А. Антонова
This document provides an overview of e-commerce. It defines commerce as the buying and selling of goods and e-commerce as commerce that takes place electronically over computer systems. The document then describes the different types of e-commerce including business-to-business, business-to-consumer, consumer-to-consumer, and business-to-government. The pros and cons of e-commerce are listed as reduced prices and easy access versus inability to examine products personally and risk of credit card theft. E-commerce is concluded to have brought more global connectivity and economic advancement.
1. The document summarizes the educational background and academic records of Engineer Ahmed Rafique Aziz. It includes details of his Bachelor of Science degree in Electrical and Electronics Engineering from Khulna University of Engineering and Technology, as well as his secondary and higher secondary examination results.
2. Key details include Ahmed obtaining a CGPA of 2.40 on a 4.0 scale for his bachelor's degree, equivalent to 53% marks. For his Higher Secondary Certificate, he scored 73.58%, and for Secondary School Certificate he scored 82.73%.
3. The document also outlines the course contents and materials Ahmed studied for mathematics, science, and English at different educational levels, along with his overall results analysis
The Man Made Effects on Space Weather Tiger Team was established to study potential impacts of human activities on space weather and ensure the space weather architecture study addressed these impacts. The team identified differences between natural and man-made space weather effects, such as the size and duration of electromagnetic and particle radiation. They found that space weather sensors may not adequately detect nuclear events and recommended integrating nuclear detection and space weather data, establishing an agency responsible for characterizing nuclear events, and expanding satellite coverage to reliably monitor radiation belt evolution.
This document describes a study conducted by NASA and the 45th Weather Squadron to develop new statistical methods for predicting the end of lightning in thunderstorms near Cape Canaveral. 58 local thunderstorms were analyzed to create models of lightning flash rates over time. Two approaches were taken: 1) analyzing the distribution of times between the last two lightning flashes, and 2) curve-fitting slowing flash rates in decaying storms. The goal is to predict the probability of additional lightning flashes to help forecasters end advisories more quickly while maintaining safety. Future work includes expanding the analysis and developing software to automatically predict lightning cessation in real-time.
The document describes a study that used machine learning models to predict the power output of horizontal solar photovoltaic panels using weather and location data from 12 sites in the northern hemisphere. A random forest regression model was able to predict panel power output with an R2 value of 0.94 based on variables like temperature, humidity, wind speed, and cloud ceiling without using direct solar irradiation data. The random forest model found temperature, humidity, and cloud ceiling to be the most important predictor variables. The study aims to accurately predict panel output without the challenges of modeling direct irradiation data.
This article discusses the advantages of Blunt Rod (BR) Lightning Protection over Nonconventional early streamer emission (ESE) and lightning dissipation array (LDA) approaches.
This document provides a summary of a doctoral thesis focused on uncertainty quantification in structural responses of offshore monopile wind turbines. The thesis contains six main parts: (1) introduction to the context, (2) stochastic vs. deterministic approaches, (3) aspects of the research, (4) results, (5) contributions to existing knowledge, and (6) conclusions and future agenda. Three papers are developed as part of the research, focusing on the influence of uncertainties in wave parameters, wind shear, and simulation length on extreme turbine responses. The research finds wave loading to be an important factor and develops methods to quantify sensitivity to input parameter uncertainties and flexible soil modeling.
The document describes the development of an adaptive weather sensing framework using phased array radar. The framework consists of four main processes: 1) storm cell identification using reflectivity data, 2) storm cell tracking to associate cells over time, 3) task configuration to determine optimal update times, and 4) scheduling of tasks. Simulated phased array radar observations were generated from operational WSR-88D data to test the framework. Results demonstrated the feasibility of adaptively scanning regions of interest with different update times while maintaining surveillance, allowing for higher temporal resolution compared to conventional radar sensing.
TRACKING ANALYSIS OF HURRICANE GONZALO USING AIRBORNE MICROWAVE RADIOMETERjmicro
There is a huge consideration in the use of microwave airborne radiometry for remote sensing instead of satellite, the important role of airborne way is how to provide high accuracy real time data. The airborne hurricane tracking is an important method compared with the space borne method, which is developed by NASA Marshall Space Flight center to provide high resolution measurements. By flying special aircraft equipment using synthetic thinned array radiometry technology and included all critical measurements such as hurricane eye location, speed of wind and the pressure. This paper describes the data analysis of best track positions for Hurricane Gonzalo based on the date collected by airborne microwave radiometry. Significant analysis comes from comparing the airborne data with the surface observations from ship reports. The vast majority is to estimate peak intensity and minimum central pressure of Gonzalo from 12 to 19 October 2014, based on blend of SFMR flight-level winds and pressure retrievals from observing brightness temperatures. SFMR: Stepped-Frequency Microwave Radiometer is a highly developed tool developed by the Langley Research Center that is designed to measure the wind speed at the ocean’s surface, and the rain fall rates within the storm accurately and continuously. The work also addresses the realistic details of the locations and the valuable information about the pressure and wind speed, which is very critical to predict the growth and movement to get the idea for future monitoring of the hurricane disasters. Also presents a conceptual of step frequency microwave radiometer in airborne side. The objective of this research is tracking analysis techniques based on comparing the satellite, ship and airborne reports to get higher accuracy. The system operates at four spaced frequencies in the range between 4 GHz and 7 GHz provides wide measurements between ± 45 incidence angle. Gonzalo 2014 is an example; the best results of retrieved wind speed, locations and pressure are presented. There are several national projects have been developed for earth observation, such as fire, hurricane and border surveillance. In this work, the efficient high resolution techniques of C-band, four-frequency, the work also addresses a valuable information comes from the airborne system and the prediction way of the growth and movement of hurricanes. In passive microwave remote sensing from space at C band has the penetrating advantages of atmosphere. Airborne system is able to work in full Polari-metric in four bands, C, X, S, L and P-band, which cover the wavelengths from 3 to 85 cm. The modes of measurement contain single channel operation wavelength and polarization.
This document summarizes a spatial analysis of tornado risk in East Tennessee. It analyzes tornado start point density using kernel density estimation within 25 miles of each point, focusing on the area covered by the NWS Morristown office. Statistics show areas of anomalously high density northeast of the French Broad River Valley have density values above the mean. While no definitive conclusions can be drawn, the results provide some support for previous research finding higher tornado risk near terrain features like river valleys. Future modeling studies are suggested to better understand how terrain may influence tornado formation.
This study investigates the relationship between lightning jumps and three storm metrics - reflectivity, estimated hail size, and precipitation echo tops - in 35 thunderstorm cells. A lightning jump is defined as a rapid increase in flash rate of 1.5 times the standard deviation. The study found that 14 of the 35 cells contained lightning jumps. It also found that cells containing jumps had higher average values and maximum increases in the three storm metrics, indicating higher storm intensity. This suggests lightning jumps may signal rapid storm strengthening.
The document discusses guidelines for site investigation and analysis of nuclear facilities from regulatory perspectives in the US, France, and internationally. It describes guidelines established by the US Nuclear Regulatory Commission and International Atomic Energy Agency for collecting geologic, geotechnical, and seismic data for safety reports. It also discusses how different countries apply these guidelines and have developed some of their own procedures. New guidelines have been developed in response to the 2011 Fukushima disaster to address seismic and flooding risks, including by the IAEA, USNRC, and French and Japanese regulators.
This document summarizes a study analyzing thunderstorm prediction in Gangetic West Bengal, India using Doppler weather radar and upper air data. The study analyzed 70 thunderstorms that occurred in 2005 using radar reflectivity and velocity data from the Kolkata Doppler radar along with upper air measurements. Standard convective indices like CAPE, CINE, LI, BRN and VGP were evaluated to determine thresholds for predicting thunderstorm occurrence. The validity of these indices was then checked against 34 thunderstorms recorded in 2006-2007. The results showed nowcasting of thunderstorms was possible 2-3 hours in advance using Doppler radar data alone, but lead time could be improved further by also analyzing convective indices. A simple
The document describes models developed to predict soiling-caused photovoltaic (PV) power output degradation in Doha, Qatar based on environmental variables. Field data on PV performance and dust concentration, wind speed, and relative humidity were collected. A linear model and a semi-physical model were developed to correlate daily changes in PV performance (∆CI) with the daily average environmental conditions. The semi-physical model, which considers dust deposition and resuspension processes, predicted daily ∆CI slightly more accurately than the linear model based on R-squared values. However, both models performed roughly the same in predicting ∆CI over longer periods. The results suggest it is possible to use the models to estimate PV
Meteorological conditions in northern indiaECRD IN
1. The document discusses meteorological conditions and air pollution dispersion modelling in northern India. It emphasizes the importance of understanding local meteorology and collecting location-specific data for accurate modelling.
2. Key meteorological parameters like wind speed, direction, temperature and stability class that influence pollutant dispersion are identified. Reliable modelling requires data on these parameters, especially at the point of emission.
3. Thermal stratification and inversions are significant as they can limit vertical mixing and dispersion of pollutants. Understanding local inversion characteristics is critical for meaningful pollution modelling.
The document describes a project to develop statistical models for forecasting lightning cessation in thunderstorms. It aims to analyze lightning flash rates over time in decaying storms to estimate the probability of additional flashes and determine optimal times to cancel lightning advisories. The project involved analyzing 58 storms and developing climatological distributions and curve fits of flash rates. Preliminary results provided probability thresholds and wait times that could guide decisions on when to end advisories. Further work was proposed to refine the models and develop software to apply the statistical techniques in operations.
Advanced weather forecasting for RES applications: Smart4RES developments tow...Leonardo ENERGY
Recording at: https://youtu.be/45Zpjog95QU
This is the 3rd Smart4RES webinar that will address technological and market challenges in RES prediction and will introduce the Smart4RES strategy to improve weather forecasting models with high resolution.
Through wind and solar applications, Innovative Numerical Weather Prediction and Large-Eddy Simulation approaches will be presented.
Directional Analysis and Filtering for Dust Storm detection in NOAA-AVHRR Ima...Pioneer Natural Resources
This document proposes techniques for detecting dust storms and determining their direction of transport using NOAA-AVHRR satellite imagery. It introduces a two-part approach using image processing algorithms: 1) A visualization technique uses filters, edge detectors and classification to locate dust sources. 2) An automation technique performs power spectrum analysis to detect dust storm direction by analyzing texture orientation in image blocks. The goal is to automatically detect and track dust storms for applications like hazard monitoring.
1) Multiple micro-pulse lidar (MPL) systems were deployed around the Baltimore-Washington region as part of NASA's 2011 DISCOVER-AQ field campaign to study air quality and atmospheric conditions.
2) In addition to existing MPL sites, four portable Sigma Space MPLs were loaned for additional locations to provide a regional-scale assessment of aerosol profiles.
3) The MPL data provides continuous vertical profiles of aerosols and clouds to help understand satellite measurements of column properties and relate surface, airborne, and space-based observations over the study period in July 2011.
This document summarizes a study on improving operational ocean wave ensemble forecasts. It reviews current state-of-the-art wave ensemble prediction centers and their validation against buoy data. Statistical methods like clustering and Empirical Orthogonal Functions are investigated to allow running higher resolution ensemble forecasts at lower computational cost. Very high resolution ensemble forecasts are validated but found to have limited reliability due to uncertainties in wind fields and model parameters. Further research is needed on improving bathymetry and wind forcing data to enhance forecast accuracy.
This document outlines operational procedures for cloud research using a Braa King Air aircraft. It discusses objectives such as characterizing aerosols, cloud droplets, drizzle development, and ice phase processes. Flight strategies are described to accomplish instrumentation testing, ambient aerosol surveys, cloud microstructure documentation, exploratory seeding flights, and coordinated seeding research. Potential seeding strategies and hypotheses involving hygroscopic and glaciogenic techniques are summarized. The assessment of seeding effects will be based on physical measurements, case studies of seeding signatures, randomized seeding studies, and modeling results. Tables provide details on the characteristics of flares used for seeding and planned seeding actions.
This document summarizes the calibration of the broadband photometric system for the RCT 1.3-meter Robotic Telescope. It finds that the linear color transformations and extinction corrections are consistent with similar KPNO facilities, with a photometric precision of 10% at 1 sigma. Some instrumental errors were identified that likely contributed to the overall uncertainty, related to engineering and maintenance issues for the new robotic facility. A preliminary verification showed the calibration solution is robust, perhaps to a higher precision than indicated by the initial calibration. The RCT has been executing regular science operations since 2009.
This document contains contact information for James Ervin Glover and Theresa Ann Glover, who provide mathematical and statistical consulting services through their company JE Glover Consulting, including search engine optimization, predictive modeling, simulation, market research, software development, algorithm development, statistical analysis, and forecasting services in areas like seismology, meteorology and oceanography. It includes their profiles on LinkedIn and other websites, as well as multiple email addresses and URLs.
This document contains contact information for James Ervin Glover and Theresa Ann Glover, who operate JE Glover Consulting providing mathematical and statistical consulting services such as predictive modeling, simulation, risk minimization, and software development. It lists their areas of expertise and provides multiple web addresses and an email for contacting them.
This document contains contact information for James Ervin Glover and Theresa Ann Glover, who operate JE Glover Consulting. It lists their services such as search engine optimization, predictive modeling, simulation, market research, software development, security, algorithms, statistics, and forecasting. It provides several website and email addresses for contacting James Ervin Glover.
This document provides a glossary describing over 3470 statistical pattern generation and trend analysis programs in the COMP-U-STAT system. The programs use interpolation polynomials up to the 10th degree to predict response values from given predictor values or coefficients. The programs can process single polynomials or sequences of polynomials to analyze time series or generate high-probability event vectors for further analysis. Output response values are recorded in cumulative files.
The document describes a statistical pattern generator and mathematical trend analyzer called COMP-U-STAT. It consists of over 3470 modular programs to generate novel statistical patterns and analyze trends from random variables. The document provides an abstract for programs 2593 through 2596, which relate to alphanumeric and non-alphanumeric encryption and decryption algorithms using techniques like congruences and binary addition modulo 2.
This document lists the national service and professional expertise of an individual including various visiting scientist/research fellow roles from 1995-2004 at organizations such as NASA, the Department of Defense, Naval Research Laboratory, Naval SPAWAR Systems Center, Air Force Headquarters, and Trans World Airlines. The roles involved atmospheric and ocean modeling, climate simulations, internet tools development, satellite applications to weather prediction, acoustic research, and statistical quality control.
The document lists the professional accomplishments of an individual in their service and outreach roles. It details their involvement in establishing several centers of excellence in mathematics, computer science, and quantum technologies. It also outlines their work securing grant funding, developing educational software, collaborating with local schools, and recruiting additional faculty members to expand opportunities for students.
This document lists the various courses taught by the author at different institutions between 1994 and 2012, including undergraduate courses in statistics, calculus, linear algebra, differential equations, complex variables, abstract algebra, number theory, discrete mathematics and foundations of advanced math. Graduate level courses included business information management and seminars on Mathematica/Maple software.
J.E. Glover has authored or co-authored numerous research publications spanning topics in gene regulatory networks, data structures performance, 3D crystal construction, statistical forecasting of lightning cessation, atmospheric modeling, head-related transfer function mathematics, cloud structure and tropical cyclone prediction, toxic air contaminant analysis, finite element structural analysis, stress intensity fracture algorithms, and construction of almost resolvable Mendelsohn triple systems. The publications span over 30 years from 1978 to 2011 and were presented at various conferences and published in peer-reviewed journals.
1) The document discusses research related to analyzing loads on the Titan IV rocket during launch. Various programs were ported to different computing environments and data formats were converted for analysis.
2) Binary data from CRAY and IBM systems was converted to IEEE format for use on workstations. Routines were developed to handle the different floating point and numeric representations between systems.
3) An algorithm was developed with Dr. Gibson to solve the Year 2000 problem by modifying the month digit of dates while keeping the appearance of normal dates when files are viewed.
This study developed statistical methods to forecast the end of lightning activity in thunderstorms near Cape Canaveral, Florida. 58 local thunderstorms were analyzed to create models of lightning flash rates over time. Two approaches were used: 1) analyzing the time between the last two lightning flashes to estimate the probability of additional flashes. 2) Curve-fitting slowing flash rates over a storm's decay phase to predict the probability of additional flashes. The goal is to automatically analyze storms in real-time and flag when lightning advisories can safely be ended to reduce costs and delays for launches. Future work includes testing the techniques on new data and expanding the analysis.
1. P1.8 PRELIMINARY RESULTS FROM PHASE-1 OF THE
STATISTICAL FORECASTING OF LIGHTNING CESSATION PROJECT
William P. Roeder James Ervin Glover, Ph.D.
45th Weather Squadron Oral Roberts University
Patrick Air Force Base, FL Tulsa, OK
1. INTRODUCTION
The 45th Weather Squadron (45 WS) provides
comprehensive weather services to America’s space
program at Cape Canaveral Air Force Station (CCAFS)
and NASA Kennedy Space Center (KSC) (Harms et al.,
1999). One of the most important of these services is
lightning advisories. The 45 WS lightning advisory
requirements are among the most challenging in
operational meteorology (Weems et al., 2002). Lightning
advisories are the most frequent 45 WS product. The
lighting advisories are issued for 13 points (figure 1) and
include all types of lightning, including lightning aloft, not
just cloud-to-ground lightning. The 45 WS uses the
Lightning Detection And Ranging (LDAR) system that
detects all lightning (Roeder et al., 2003). A Phase-1
lightning advisory is issued when lightning is expected
with a desired lead-time of 30 min within 5 NM of the
point(s). A Phase-2 advisory is issued when lightning is
imminent or occurring in the circle(s). The advisories are
cancelled when no longer required.
Some research has been done on forecasting the
initiation of lightning, but has focused mostly on cloud-to-
ground lightning, not ‘all lightning’, as required by 45 WS.
Based on that research and on local experience, the
45 WS developed operational guidelines for forecasting
the start of lightning. This lightning onset guidance uses
mostly radar (thresholds, depth, and duration of
reflectivity versus temperature levels for thunderstorms,
anvil and debris clouds). For lightning in the local area,
the onset prediction is supplemented with low altitude
convergence calculated from 41 weather towers and 31
local surface electric field mills. The 45 WS techniques
for forecasting the start of lightning are summarized in
Roeder and Pinder (1988) and Roeder et al. (2002).
Unfortunately, very little research has been done on
predicting the cessation of lightning (Hinson, 1997). As a
result, the 45 WS operational guidance for canceling
lightning advisories is not as well developed. The timing
for the last lightning flash is especially problematic. The
45 WS techniques for terminating lightning advisories
consist of waiting until the onset rules are no longer met,
and waiting some variable time after the last observed
lightning flash. The length of that time varies based on
each storm, professional subjective judgment and
experience. For decaying thunderstorms over the
immediate area, the 31 surface electric field mills also
supplement the decision to cancel the advisory. Both
research and local experience indicate that predicting
lightning cessation is exceedingly difficult.
Corresponding author: William Roeder, 45 WS/SYR, 1201 E. H. White
II St., MS 7302, Patrick AFB, FL 32925; william.roeder@patrick.af.mil
(hot link), htps://www.patrick.af.mil/45og/45ws/index.htm (hot link)
Figure 1. 45 WS Lightning Advisory Areas. Each of the
thirteen circles represents a point for which 45 WS
issues two-tiered advisories for lightning within 5 NM of
the point.
The 45 WS lightning advisories must necessarily be
terminated conservatively, erring on the side of safety,
given the relative lack of objective techniques for
forecasting the end of lightning, and since these
advisories protect over 25,000 people. After-the-fact
analysis confirms that 45 WS tends to leave their
lightning advisories in effect longer than is optimal.
While this is prudent, since personnel safety is the
highest priority, it does cause extra financial costs and
delays in preparing space launch vehicles and payloads.
The development of objective reliable high-performance
techniques to predict lightning cessation is the top
operational research requirement and a strategic goal of
45 WS. Improved termination of lightning advisories is
the activity most needing improvement in 45 WS
operations.
2. 2. THE STATISTICAL FORECASTING OF
LIGHTNING CESSATION PROJECT
The 45 WS teamed with KSC to begin a new
research project to improve forecasting of lightning
cessation. The ‘Statistical Forecasting Of Lightning
Cessation’ project was funded under the NASA Faculty
Fellowship Program (www.nasa.gov/audience/
foreducators/postsecondary/grants/NFFP.html (hot
link)). This project brought Dr. Glover from the
department of computer sciences and mathematics at
Oral Roberts University to CCAFS/KSC for 9 weeks
during the summer of 2004 to conduct this research.
The purpose of this project is to develop
techniques that are highly focused on helping the
operational forecaster. The forecaster can usually
easily identify when thunderstorms are decaying based
on radar and lightning flash rate. If several minutes
have passed since the last flash, the forecaster is faced
with the challenge to decide if that was actually the last
flash and the advisory can be cancelled, or how likely is
another lightning flash. This forecaster mindset
inspired the statistical approach for this project and
suggested two methodologies.
The first methodology is to develop climatology for
the distribution of times between the last and second-
last flash. Given some low operationally determined
probability of acceptable risk, this distribution of times
between last-2nd last lightning flashes could be
integrated for guidance on how long to wait in general
before canceling lightning advisories. After all, the first
step in most forecast processes is climatology, but
climatology for terminating lightning advisories did not
exist. While far from a final solution, the low risk,
speed of development, and initial utility made this a
worthwhile goal of this project.
The second methodology is to determine if a
specific family of curve can model the slowing lightning
flash in decaying thunderstorms in general. Then find
the best fit of that family of curves to the flash rate in
an individual decaying thunderstorm. Finally, integrate
that best fit curve to find the time when the probability
of no more lightning drops below the operationally
acceptable threshold. This second methodology was
considered high-risk, given the extreme technical
difficulty in forecasting the end of lightning and that the
proposed approach is purely statistical with no explicit
meteorological science. This second methodology was
also considered potentially high-return, since it might
deliver a large leap forward to 45 WS capability.
2.1 Phase-1 Design
The first phase of this project was considered a
proof-of-concept to answer two main questions:
1) could a good curve be found for the distribution of
times between last and 2nd last lightning flashes from
many thunderstorms, and 2) did the concept of a decay
curve to lightning flash rate in individual thunderstorms
to predict the probability of another lightning flash have
any validity. Because this phase of the project was
considered proof-of-concept, and given the short time
the summer visiting scientist was available (9 weeks),
this preliminary research was restricted to only cloud-
to-ground lightning. The lightning data were easily
available from the Cloud-to-Ground Lightning
Surveillance System (CGLSS) database (Roeder et al.,
2005). The ‘all lightning’ data are also available from
LDAR archive, but are very difficult to use quickly due
to the shear volume of data (hundreds of step leaders
per flash) and the tabular 4-D data format. Without a
visualization tool, determining which step leader points
go with which flash, and which flashes go with which
thunderstorm, can not be determined quickly. The
CGLSS is a local system, similar to the National
Lightning Detection Network, but with better
performance (Boyd et al., 2005). Because this phase
of the project did not analyze ‘all lightning’, the results
are not immediately useful for 45 WS lightning
advisories.
The 45 WS is interested in research to convert the
LDAR step leader archive into a lightning flash
database. An optimized ‘step leader to lightning flash’
conversion algorithm is needed. A simple algorithm for
this already exists, but there is considerable room for
improvement (McNamara, 2002). A ‘thunderstorm-ID
assignment’ algorithm is also required and would
presumably be based on clustering the flash starting
points in x-y location and time, with perhaps some
weak cluster in z-location. Considering the time series
of flash rate and morphology of flash might allow
automatic identification of the lightning cloud
classification: thunderstorm, anvil, or debris cloud
lightning. These algorithms could be applied to the 10+
years of LDAR step leader observations to create a
much easier to use lightning flash database. This
LDAR flash database would facilitate many lightning
research projects, including future phases of the
‘statistical forecasting of lightning cessation’ project.
Phase-1 analyzed 58 thunderstorms near
CCAFS/KSC, which were sampled from five convective
seasons during the summer convective season (May-
Sep) as shown in Table-1 and Table-2. This was done
to avoid any seasonal or monthly biases in the results.
The timeline of flashes from one storm is shown in
figure 2. Such timelines were part of the inspiration for
this project, since anecdotally some sort of decay curve
seemed to apply. Likely candidates for the decay curve
included negative exponential, Poisson, log-linear, etc.
The 58 storms were used to create a 59th composite
“thunderstorm” that represents the average behavior of
all the storms.
Table 1.
58 thunderstorms analyzed during Phase-1 of this
project by season (May-Sep)
YEAR NUMBER OF THUNDERSTORMS
1999 12 (May: 2, Jun: 2, Jul: 2, Aug: 4, Sep: 2)
2000 13 (May: 0, Jun: 4, Jul: 6, Aug: 1, Sep: 2)
2001 14 (May: 0, Jun: 5, Jul: 3, Aug: 5, Sep: 1)
2002 7 (May: 0, Jun: 1, Jul: 2, Aug: 4, Sep: 0)
2003 12 (May: 0, Jun: 2, Jul: 3, Aug: 7, Sep: 0)
Table 2.
58 thunderstorms analyzed during Phase-1 of this
project by Month (May-Sep)
3. YEAR NUMBER OF THUNDERSTORMS
May 2
Jun 14
Jul 16
Aug 21
Sep 5
Figure 2. Timeline from one thunderstorm.
The 58 cases were actually all cloud-to-ground
lightning observed in a ± 10 NM box centered on
CCAFS/KSC. Therefore, flashes from more than one
thunderstorm might have been included, although the
person providing that cases tried to provide only
isolated thunderstorms in the sample box, so this was
not likely a significant problem. Likewise, flashes from
thunderstorms moving into and out of the sample box
could have contaminated the analysis, e.g. a storm of
constant activity could appear to be decaying as it
moves out of the sample box. However, again the
person providing the cases tried to provide
thunderstorms centered in box. Given that most of our
thunderstorms are organized on relatively slow moving
sea-breeze fronts, this centering of the data led this to
not be considered a significant problem either. These
compromises in sampling were required due to the
short time the visiting scientist was available (9 weeks)
and the lack of appropriate software for visualizing
saved CGLSS lightning data at 45 WS. The
thunderstorms sampled tended to be more active
storms with above average lighting flash rates, though
they were still mostly pulse thunderstorms on sea
breeze fronts and other boundary interactions, as
opposed to extremely lightning active squall lines. This
was needed to provide enough flashes during the
decaying part of the thunderstorm lifecycle to allow for
effective curve fitting. This was a sample bias for
which compensation could not be applied. However,
the authors know of no reason why above average
lightning storms should behave significantly different
from other pulse more typical thunderstorms during
their decay phases, so this may not be a significant
problem either.
2.2 Phase-1 Results
Phase-1 of this project was a proof-of-concept
effort to determine the promise of a statistical approach
to forecasting lightning cessation. Phase-1 was
successful and further development under future
phases is justified.
2.2.1. Climatological distribution of times between last
and 2nd to last lightning flashes:
The time differences between the last and 2nd last
lightning flash were used to create a probability density
function of the time differences (figure 3). Several
standard statistical curves were fit to this probability
density function. The best fit was a log-linear curve,
with the following coefficients and constants,
P(∆t) = -0.0469 Ln(∆t) + 0.1493, where ∆t is the time
difference between last and 2nd last flash and P(∆t) is
it’s probability density function. This best fit curve
yielded a correlation coefficient of 0.8665, so that 75%
of the variation is explained by the log-linear curve
(r2
= 0.7509). Since the logarithmic function tends to
produce a more linear result than the original curve, a
Z-Score of Ln(∆t) was used to check if the log-linear fit
was appropriate. As shown in figure 4, the Z-Score is
very linear, with a correlation coefficient of 0.9985, so
that 99.7% of the variance is explained by the log-linear
curve (r2
= 0.997). Therefore, the log-linear fit is
accepted as reasonable.
If a similar curve had been fit to for ‘all lightning’,
such as from the LDAR sensor, then a climatological
tool for canceling 45 WS lightning advisories could be
created. Integrating the probability density function
from various times to infinity would produce a table of
recommended times to wait after the last observed
flash to achieve various probabilities of another flash
occurring. A hypothetical example is shown in Table 3.
Alternatively, if a specific probability of another flash is
required for a specific operation, that time to wait after
the last observed flash could also be calculated.
Figure 3. Probability density function of the times
between last and 2nd last lightning flashes.
4. Figure 4. Z-Score of Ln(∆t), which helps confirm that
the log-linear curve, is a reasonable fit.
Table 3.
Hypothetical example of climatological tool for
canceling lightning advisories (not for operational use!)
% PROBABILITY OF
ANOTHER FLASH
AVERAGE TIME
25% 10 min
10% 15 min
5% 20 min
1% 25 min
0.1% 50 min
2.2.2. Curve fitting of lightning flash rates in decaying
thunderstorms:
Several standard statistical curves were fit to the
decaying lighting rate in the composite thunderstorm,
which represents the average behavior of the 58
individual thunderstorms in this analysis. The log-
linear equation again provided the best fit curve with
the following parameterization,
P(t) = -0.2821 Ln(t) + 1.5115 (figure 5). The coefficient
of regression was 0.8977, which explained 81% of the
variation (r2
= 0.8058). A linear fit with a slope of
-0.0102 and intercept of 0.998 provided a better fit
(r2
= 0.9999), but the log-linear fit is preferred since this
curve was one of the curves expected a priori, and
agrees with the best fit curve to the entire composite
thunderstorm lifecycle (P(t) = -0.3085 Ln(t) + 1.7599,
r2
= 0.8642). The linear fit having a higher correlation
coefficient may be an artifact of identifying the start of
the decay phase of the composite thunderstorm too
late in the lifecycle. An example of a best-fit curve to
the decaying flash rate from an individual thunderstorm
is shown in figure 6. In this case, a negative
exponential was the best-fit curve; P(flash rate) =
0.8551e-0.5876(t)
. This equation yielded a correlation
coefficient of r = 0.9839, which explains 97% of the
variance (r2
= 0.9681). This is consistent with the
recent research on decaying flash rates of ‘all lightning’
in Dallas, TX (Holle and Murphy, 2003). If similar
curves were fit to the decaying flash rate of ‘all
lightning’ from a thunderstorm in real time, the
integration of the equation could help predict the time
when the probability of another flash would fall below
some low operational threshold.
Survivability of Strike Rates for the Composite
Storm (Decay Phase)
y = -0.2821Ln(x) + 1.5115
R
2
= 0.8058
-0.5
0
0.5
1
1.5
2
0 50 100 150
Time ( t+121) Minutes
Reliability(t+121)
Series1
Log. (Series1)
Linear (Series1)
Figure 5. Probability density function of the times
between last and 2nd last lightning flash from the 58
thunderstorms in this analysis and the best-fit curve.
Figure 6. Probability density function and best-fit
curve for an individual thunderstorm.
2.3 Future Phases
Phase-1 indicated that statistical forecasting of
lightning cessation has promise and further
development is justified. If funding is approved,
Phase-2 and Phase-3 might be done during the
summer of 2005 and the summer 2006, respectively.
2.3.1. Phase-2 Proposal:
Phase-2 would repeat the work of Phase-1 but
using ‘all lightning’ from the LDAR sensor, rather than
just cloud-to-ground lightning. Climatology for the
distribution of time differences between last and 2nd
last lightning flashes for ‘all lightning’ would be built.
Since the climatology would be based on ‘all lightning’,
matching 45 WS lightning advisory procedures, this
climatology might be used immediately as guidance in
ending lightning advisories operationally. Also, curve
fitting to the ‘all lightning’ flash rate from decaying
individual thunderstorms would be explored. The
potential sampling shortfalls discussed previously
would be explicitly avoided to ensure that all lightning
would be recorded throughout the decaying lifecycle
from only one thunderstorm. Verification against
independent data would also be accomplished. Finally,
estimation of the performance of the curve fitting
approach in the real world would begin. Lightning
flashes from individual decaying thunderstorms would
5. be used to update the best-fit curve for each flash and
integrated to estimate the timing for various
probabilities of last flash, which would be verified
against the actual last flashes. The average
performance of the climatological and curve fitting
methods would be compared against average
performance of the 45 WS termination of advisories,
especially as regards safely terminating the advisories
sooner.
2.3.2. Phase-3 Proposal:
If justified by Phase-2 results, Phase-3 would
enlarge the sample size of the climatology and curve
fitting approach for ‘all lightning’. In addition, the
performance verification on independent data would be
extended and completed. A performance comparison
would be conducted between the climatological and
curve fitting methods and 45 WS termination of
lightning advisories on a sample of independent
thunderstorms. Finally, a proposal for future research
and preliminary design would be drafted to support the
long-range goal of automated guidance for forecasting
lightning cessation and terminating 45 WS lightning
advisories.
3. LONG RANGE GOAL
The long-range goal is to create a system that
would provide automated guidance on which
thunderstorms are decaying, the expected time for the
probability of another flash to drop below some low
operational threshold, and flag storms that have
already fallen below that operational threshold. Such
an automated system would need an ‘all lightning’
detection system, such as LDAR. Special post-
processing software would also be required. The first
function of this post-processing software would be to
assign each lightning flash to a specific thunderstorm,
presumably via a statistical cluster algorithm operating
on the x-y location, time, and to a lesser degree ‘z’
location of the starting point of the lightning flashes.
The second function of the post-processing software
would be to identify when thunderstorms start
decaying, presumably through a simple analysis of a
smoothed time-series of flash rate from individual
thunderstorms. Finally, the post-processing software
would calculate the best-fit coefficients for the
appropriate family of curve for each thunderstorm and
calculate when the integration of that best fit equation
would suggest that the probability of another flash
reaches a low operational threshold. As each flash
occurs, the best fit coefficients of the curve and a new
integration would be recalculated to update the timing
guidance. Even more advanced systems could
combine data from radar and electric field mills for
even better lightning cessation guidance.
Automated guidance on lightning cessation will not
be available for many years. In the meantime, interim
techniques on how to cancel lightning advisories is
required by 45 WS, such as climatology of the
distribution of times between last and 2nd last flashes
from all lightning.
4. SUMMARY
The 45 WS needs to terminate their lightning
advisories sooner without compromising safety.
Unfortunately, the lack of research on this topic makes
improving the forecasting of lightning cessation very
difficult. A preliminary examination of a new statistical
approach was performed during summer 2004. Initial
results were encouraging and further research on this
statistical approach is justified.
Acknowledgments: The NASA Faculty Fellowship Program
funded this research. Mr. Weems of 45 WS was instrumental in
providing lightning cases studies from the CGLSS database.
The Applied Meteorology Unit provided office space and use of a
personal computer, technical advice from Dr. Short and
Dr. Bauman, and office hardware and software assistance from
Mr. Case. Dr. Merceret of the KSC Weather Office provided
technical advice and mentoring on effective communication. This
research would not have been possible without the support for
operational research from Colonel LaFebre, 45 WS Commander,
and previous 45 WS commanders.
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