Predicting Dry Lightning Risk Nationwide Joy Drohan US Forest Service, [email protected]
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Forecasting Tropical Cyclones
Forecasting Tropical Cyclones Philippe Caroff, Sébastien Langlade, Thierry Dupont, Nicole Girardot Using ECMWF Forecasts – 4-6 june 2014 Outline . Introduction . Seasonal forecast . Monthly forecast . Medium- to short-range forecasts For each time-range we will see : the products, some elements of assessment or feedback, what is done with the products Using ECMWF Forecasts – 4-6 june 2014 RSMC La Réunion La Réunion is one of the 6 RSMC for tropical cyclone monitoring and warning. Its responsibility area is the south-west Indian Ocean. http://www.meteo.fr/temps/domtom/La_Reunion/webcmrs9.0/# Introduction Seasonal forecast Monthly forecast Medium- to short-range Other activities in La Réunion TRAINING Organisation of international training courses and workshops RESEARCH Research Centre for tropical Cyclones (collaboration with La Réunion University) LACy (Laboratoire de l’Atmosphère et des Cyclones) : https://lacy.univ-reunion.fr DEMONSTRATION SWFDP (Severe Weather Forecasting Demonstration Project) http://www.meteo.fr/extranets/page/index/affiche/id/76216 Introduction Seasonal forecast Monthly forecast Medium- to short-range Seasonal variability • The cyclone season goes from 1st of July to 30 June but more than 90% of the activity takes place between November and April • The average number of named cyclones (i.e. tropical storms) is 9. • But the number of tropical cyclones varies from year to year (from 3 to 14) Can the seasonal forecast systems give indication of this signal ? Introduction Seasonal forecast Monthly forecast Medium- to short-range Seasonal Forecast Products Forecasts of tropical cyclone activity anomaly are produced with ECMWF Seasonal Forecast System, and also with EUROSIP models (union of UKMO+ECMWF+NCEP+MF seasonal forecast systems) Other products can be informative, for example SST plots. -
Improving Lightning and Precipitation Prediction of Severe Convection Using of the Lightning Initiation Locations
PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Improving Lightning and Precipitation Prediction of Severe 10.1002/2017JD027340 Convection Using Lightning Data Assimilation Key Points: With NCAR WRF-RTFDDA • A lightning data assimilation method was developed Haoliang Wang1,2, Yubao Liu2, William Y. Y. Cheng2, Tianliang Zhao1, Mei Xu2, Yuewei Liu2, Si Shen2, • Demonstrate a method to retrieve the 3 3 graupel fields of convective clouds Kristin M. Calhoun , and Alexandre O. Fierro using total lightning data 1 • The lightning data assimilation Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information method improves the lightning and Science and Technology, Nanjing, China, 2National Center for Atmospheric Research, Boulder, CO, USA, 3Cooperative convective precipitation short-term Institute for Mesoscale Meteorological Studies (CIMMS), NOAA/National Severe Storms Laboratory, University of Oklahoma forecasts (OU), Norman, OK, USA Abstract In this study, a lightning data assimilation (LDA) scheme was developed and implemented in the Correspondence to: Y. Liu, National Center for Atmospheric Research Weather Research and Forecasting-Real-Time Four-Dimensional [email protected] Data Assimilation system. In this LDA method, graupel mixing ratio (qg) is retrieved from observed total lightning. To retrieve qg on model grid boxes, column-integrated graupel mass is first calculated using an Citation: observation-based linear formula between graupel mass and total lightning rate. Then the graupel mass is Wang, H., Liu, Y., Cheng, W. Y. Y., Zhao, distributed vertically according to the empirical qg vertical profiles constructed from model simulations. … T., Xu, M., Liu, Y., Fierro, A. O. (2017). Finally, a horizontal spread method is utilized to consider the existence of graupel in the adjacent regions Improving lightning and precipitation prediction of severe convection using of the lightning initiation locations. -
The Observation of the Lightning Induced Variations in Atmospheric Ions
XV International Conference on Atmospheric Electricity, 15-20 June 2014, Norman, Oklahoma, U.S.A. The Observation of the Lightning Induced Variations in Atmospheric Ions Xuemeng Chen1,*, Hanna E. Manninen1,2, Pasi Aalto1, Petri Keronen1, Antti Mäkelä3, Jussi Paatero3, Tuukka Petäjä1 and Markku Kulmala1 1. Department of Physics, University of Helsinki, Helsinki, Finland 2. Institute of Physics, University of Tartu, Estonia 3. Finnish Meteorological Institute, Helsinki, Finland ABSTRACT: Variations in atmospheric ion concentration were studied in a boreal forest in Finland, with emphasis on the effect of lightning. In general, changes in ion concentrations have diurnal and seasonal patterns. Distinct features were found in ions of different size ranges, namely small ions (0.8 – 1.7 nm) and intermediate ions (1.7 – 7 nm). Preliminary results on two case studies of lightning effect are present, one with rain effect and the other not. Bursts in the concentrations of small ions and intermediate ions were observed in both cases. However, different trends in trace gases were observed for the two cases. Further investigation is needed to reveal the nature of lightning ions and the mechanism in their formation. The work is under progress. INTRODUCTION Atmospheric ions, or air ions, refer to electric charge carriers present in the atmosphere. Distinct features exist in their chemical composition, mass, size as well as number of carried charges. According to Tammet [1998], atmospheric ions can be classified into small or cluster ions, intermediate ions, and large ions based on their mobility (Z) in air, being Z > 0.5 cm2V-1s-1, 0.5 cm2V-1s-1 ≤ Z ≥ 0.03 cm2V-1s-1 and Z< 0.03 cm2V-1s-1, respectively. -
Winter 2020/2021 Volume 18
NATIONAL WEATHER SERVICE GREEN BAY Winter 2020/2021 Volume 18 Lake Michigan water levels remain near record highs BY: mike cellitti Inside this issue: In December 2012 and January 2013, the Lake Michigan-Huron basin (Lake Michigan and Lake Huron are treated as one lake from a hydrologic perspective) East River Watershed 3 Resiliency Project observed record low water levels, making it the 14th consecutive year of below normal water levels. These record low water levels garnered national attention 2020-21 Winter Forecast 4 raising concerns for the shipping industry, climate impacts, and the long-term future Ambassador of Excellence 6 of the Great Lakes water levels. Since this minimum in water levels 6 years ago, Lake Kotenberg Joins NWS 7 Michigan-Huron has been on the rise, culminating in record high water levels for much of this year (Figure 1). In fact, Lake Michigan-Huron set monthly mean record Severe Weather Spotters 7 high water levels from January to August, peaking in July at greater than 3 inches Thank You Observers! 8 above the previous record. Word Search 9 The water level on the Great Lakes can fluctuate on a monthly, seasonal, and annual basis depending upon a variety of factors including the amount of precipitation, evaporation, and rainfall induced runoff. Precipitation and runoff typically peak in late spring and summer as a result of snowmelt and thunderstorm activity. Although it is difficult to measure, evaporation occurs the most when cold air flows over the relatively warm waters of the Great Lakes during the fall and winter months. East River The record high water levels of Lake Michigan-Huron are largely a result of well Flooding above normal precipitation across the basin over the past 5 years. -
Impact of Air Pollution Controls on Radiation Fog Frequency in the Central Valley of California
RESEARCH ARTICLE Impact of Air Pollution Controls on Radiation Fog 10.1029/2018JD029419 Frequency in the Central Valley of California Special Section: Ellyn Gray1 , S. Gilardoni2 , Dennis Baldocchi1 , Brian C. McDonald3,4 , Fog: Atmosphere, biosphere, 2 1,5 land, and ocean interactions Maria Cristina Facchini , and Allen H. Goldstein 1Department of Environmental Science, Policy and Management, Division of Ecosystem Sciences, University of 2 Key Points: California, Berkeley, CA, USA, Institute of Atmospheric Sciences and Climate ‐ National Research Council (ISAC‐CNR), • Central Valley fog frequency Bologna, BO, Italy, 3Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, CO, increased 85% from 1930 to 1970, USA, 4Chemical Sciences Division, NOAA Earth System Research Laboratory, Boulder, CO, USA, 5Department of Civil then declined 76% in the last 36 and Environmental Engineering, University of California, Berkeley, CA, USA winters, with large short‐term variability • Short‐term fog variability is dominantly driven by climate Abstract In California's Central Valley, tule fog frequency increased 85% from 1930 to 1970, then fluctuations declined 76% in the last 36 winters. Throughout these changes, fog frequency exhibited a consistent • ‐ Long term temporal and spatial north‐south trend, with maxima in southern latitudes. We analyzed seven decades of meteorological data trends in fog are dominantly driven by changes in air pollution and five decades of air pollution data to determine the most likely drivers changing fog, including temperature, dew point depression, precipitation, wind speed, and NOx (oxides of nitrogen) concentration. Supporting Information: Climate variables, most critically dew point depression, strongly influence the short‐term (annual) • Supporting Information S1 variability in fog frequency; however, the frequency of optimal conditions for fog formation show no • Table S1 • Table S2 observable trend from 1980 to 2016. -
Wind Energy Forecasting: a Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy
Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy Keith Parks Xcel Energy Denver, Colorado Yih-Huei Wan National Renewable Energy Laboratory Golden, Colorado Gerry Wiener and Yubao Liu University Corporation for Atmospheric Research (UCAR) Boulder, Colorado NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. S ubcontract Report NREL/SR-5500-52233 October 2011 Contract No. DE-AC36-08GO28308 Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy Keith Parks Xcel Energy Denver, Colorado Yih-Huei Wan National Renewable Energy Laboratory Golden, Colorado Gerry Wiener and Yubao Liu University Corporation for Atmospheric Research (UCAR) Boulder, Colorado NREL Technical Monitor: Erik Ela Prepared under Subcontract No. AFW-0-99427-01 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory Subcontract Report 1617 Cole Boulevard NREL/SR-5500-52233 Golden, Colorado 80401 October 2011 303-275-3000 • www.nrel.gov Contract No. DE-AC36-08GO28308 This publication received minimal editorial review at NREL. NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. -
The Error Is the Feature: How to Forecast Lightning Using a Model Prediction Error [Applied Data Science Track, Category Evidential]
The Error is the Feature: How to Forecast Lightning using a Model Prediction Error [Applied Data Science Track, Category Evidential] Christian Schön Jens Dittrich Richard Müller Saarland Informatics Campus Saarland Informatics Campus German Meteorological Service Big Data Analytics Group Big Data Analytics Group Offenbach, Germany ABSTRACT ACM Reference Format: Despite the progress within the last decades, weather forecasting Christian Schön, Jens Dittrich, and Richard Müller. 2019. The Error is the is still a challenging and computationally expensive task. Current Feature: How to Forecast Lightning using a Model Prediction Error: [Ap- plied Data Science Track, Category Evidential]. In Proceedings of 25th ACM satellite-based approaches to predict thunderstorms are usually SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19). based on the analysis of the observed brightness temperatures in ACM, New York, NY, USA, 10 pages. different spectral channels and emit a warning if a critical threshold is reached. Recent progress in data science however demonstrates 1 INTRODUCTION that machine learning can be successfully applied to many research fields in science, especially in areas dealing with large datasets. Weather forecasting is a very complex and challenging task requir- We therefore present a new approach to the problem of predicting ing extremely complex models running on large supercomputers. thunderstorms based on machine learning. The core idea of our Besides delivering forecasts for variables such as the temperature, work is to use the error of two-dimensional optical flow algorithms one key task for meteorological services is the detection and pre- applied to images of meteorological satellites as a feature for ma- diction of severe weather conditions. -
USING a LIGHTNING SAFETY TOOLKIT for OUTDOOR VENUES Charles C
USING A LIGHTNING SAFETY TOOLKIT FOR OUTDOOR VENUES Charles C. Woodrum Meteorologist National Weather Service, NOAA Pittsburgh, Pennsylvania Donna Franklin Office of Climate, Water, and Weather Services National Weather Service, NOAA Silver Spring, Maryland _________________________ Abstract guidelines that are used as a template for creating a new plan or enhancing an existing plan. The toolkit The threat of fatal lightning strikes at outdoor was developed within the framework of NCAA venues continues to be a pressing concern for event Guideline 1d. The NWS used plans from the managers. Several delays were documented in 2010 University of Tampa, the University of Maryland, and and 2011 in which spectators did not have enough time Vanderbilt University along with guidance from to evacuate, or chose to wait out delays in unsafe emergency management at the University of locations. To address this issue, the National Weather Tennessee and Florida State University as assistance Service (NWS) developed a lightning safety toolkit and to develop the toolkit. recognition program to help meteorologists work with venue officials to encourage sound and proactive Guidelines established for venue decisions when thunderstorms threaten their venue. management include: redundant data reception sources; effective decision support standards; 1. Introduction and Background multiple effective communication methods; a public notification plan; protection program with shelters; and Every year, hundreds of outdoor venue education of staff and patrons. The toolkit template managers are challenged to determine when an event safety plan helps venues meet these guidelines by delay is necessary due to thunderstorm hazards. In providing steps to follow before, during, and after the 2000, “ninety-two percent of National Collegiate Athletic event. -
CALIFORNIA STATE UNIVERSITY, NORTHRIDGE FORECASTING CALIFORNIA THUNDERSTORMS a Thesis Submitted in Partial Fulfillment of the Re
CALIFORNIA STATE UNIVERSITY, NORTHRIDGE FORECASTING CALIFORNIA THUNDERSTORMS A thesis submitted in partial fulfillment of the requirements For the degree of Master of Arts in Geography By Ilya Neyman May 2013 The thesis of Ilya Neyman is approved: _______________________ _________________ Dr. Steve LaDochy Date _______________________ _________________ Dr. Ron Davidson Date _______________________ _________________ Dr. James Hayes, Chair Date California State University, Northridge ii TABLE OF CONTENTS SIGNATURE PAGE ii ABSTRACT iv INTRODUCTION 1 THESIS STATEMENT 12 IMPORTANT TERMS AND DEFINITIONS 13 LITERATURE REVIEW 17 APPROACH AND METHODOLOGY 24 TRADITIONALLY RECOGNIZED TORNADIC PARAMETERS 28 CASE STUDY 1: SEPTEMBER 10, 2011 33 CASE STUDY 2: JULY 29, 2003 48 CASE STUDY 3: JANUARY 19, 2010 62 CASE STUDY 4: MAY 22, 2008 91 CONCLUSIONS 111 REFERENCES 116 iii ABSTRACT FORECASTING CALIFORNIA THUNDERSTORMS By Ilya Neyman Master of Arts in Geography Thunderstorms are a significant forecasting concern for southern California. Even though convection across this region is less frequent than in many other parts of the country significant thunderstorm events and occasional severe weather does occur. It has been found that a further challenge in convective forecasting across southern California is due to the variety of sub-regions that exist including coastal plains, inland valleys, mountains and deserts, each of which is associated with different weather conditions and sometimes drastically different convective parameters. In this paper four recent thunderstorm case studies were conducted, with each one representative of a different category of seasonal and synoptic patterns that are known to affect southern California. In addition to supporting points made in prior literature there were numerous new and unique findings that were discovered during the scope of this research and these are discussed as they are investigated in their respective case study as applicable. -
Climatic Information of Western Sahel F
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Clim. Past Discuss., 10, 3877–3900, 2014 www.clim-past-discuss.net/10/3877/2014/ doi:10.5194/cpd-10-3877-2014 CPD © Author(s) 2014. CC Attribution 3.0 License. 10, 3877–3900, 2014 This discussion paper is/has been under review for the journal Climate of the Past (CP). Climatic information Please refer to the corresponding final paper in CP if available. of Western Sahel V. Millán and Climatic information of Western Sahel F. S. Rodrigo (1535–1793 AD) in original documentary sources Title Page Abstract Introduction V. Millán and F. S. Rodrigo Conclusions References Department of Applied Physics, University of Almería, Carretera de San Urbano, s/n, 04120, Almería, Spain Tables Figures Received: 11 September 2014 – Accepted: 12 September 2014 – Published: 26 September J I 2014 Correspondence to: F. S. Rodrigo ([email protected]) J I Published by Copernicus Publications on behalf of the European Geosciences Union. Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion 3877 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract CPD The Sahel is the semi-arid transition zone between arid Sahara and humid tropical Africa, extending approximately 10–20◦ N from Mauritania in the West to Sudan in the 10, 3877–3900, 2014 East. The African continent, one of the most vulnerable regions to climate change, 5 is subject to frequent droughts and famine. One climate challenge research is to iso- Climatic information late those aspects of climate variability that are natural from those that are related of Western Sahel to human influences. -
Forecasting of Thunderstorms in the Pre-Monsoon Season at Delhi
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Publications of the IAS Fellows Meteorol. Appl. 6, 29–38 (1999) Forecasting of thunderstorms in the pre-monsoon season at Delhi N Ravi1, U C Mohanty1, O P Madan1 and R K Paliwal2 1Centre for Atmospheric Sciences, Indian Institute of Technology, New Delhi 110 016, India 2National Centre for Medium Range Weather Forecasting, Mausam Bhavan Complex, Lodi Road, New Delhi 110 003, India Accurate prediction of thunderstorms during the pre-monsoon season (April–June) in India is essential for human activities such as construction, aviation and agriculture. Two objective forecasting methods are developed using data from May and June for 1985–89. The developed methods are tested with independent data sets of the recent years, namely May and June for the years 1994 and 1995. The first method is based on a graphical technique. Fifteen different types of stability index are used in combinations of different pairs. It is found that Showalter index versus Totals total index and Jefferson’s modified index versus George index can cluster cases of occurrence of thunderstorms mixed with a few cases of non-occurrence along a zone. The zones are demarcated and further sub-zones are created for clarity. The probability of occurrence/non-occurrence of thunderstorms in each sub-zone is then calculated. The second approach uses a multiple regression method to predict the occurrence/non- occurrence of thunderstorms. A total of 274 potential predictors are subjected to stepwise screening and nine significant predictors are selected to formulate a multiple regression equation that gives the forecast in probabilistic terms. -
Severe Thunderstorms and Tornadoes Toolkit
SEVERE THUNDERSTORMS AND TORNADOES TOOLKIT A planning guide for public health and emergency response professionals WISCONSIN CLIMATE AND HEALTH PROGRAM Bureau of Environmental and Occupational Health dhs.wisconsin.gov/climate | SEPTEMBER 2016 | [email protected] State of Wisconsin | Department of Health Services | Division of Public Health | P-01037 (Rev. 09/2016) 1 CONTENTS Introduction Definitions Guides Guide 1: Tornado Categories Guide 2: Recognizing Tornadoes Guide 3: Planning for Severe Storms Guide 4: Staying Safe in a Tornado Guide 5: Staying Safe in a Thunderstorm Guide 6: Lightning Safety Guide 7: After a Severe Storm or Tornado Guide 8: Straight-Line Winds Safety Guide 9: Talking Points Guide 10: Message Maps Appendices Appendix A: References Appendix B: Additional Resources ACKNOWLEDGEMENTS The Wisconsin Severe Thunderstorms and Tornadoes Toolkit was made possible through funding from cooperative agreement 5UE1/EH001043-02 from the Centers for Disease Control and Prevention (CDC) and the commitment of many individuals at the Wisconsin Department of Health Services (DHS), Bureau of Environmental and Occupational Health (BEOH), who contributed their valuable time and knowledge to its development. Special thanks to: Jeffrey Phillips, RS, Director of the Bureau of Environmental and Occupational Health, DHS Megan Christenson, MS,MPH, Epidemiologist, DHS Stephanie Krueger, Public Health Associate, CDC/ DHS Margaret Thelen, BRACE LTE Angelina Hansen, BRACE LTE For more information, please contact: Colleen Moran, MS, MPH Climate and Health Program Manager Bureau of Environmental and Occupational Health 1 W. Wilson St., Room 150 Madison, WI 53703 [email protected] 608-266-6761 2 INTRODUCTION Purpose The purpose of the Wisconsin Severe Thunderstorms and Tornadoes Toolkit is to provide information to local governments, health departments, and citizens in Wisconsin about preparing for and responding to severe storm events, including tornadoes.