A Physically Based Parameter for Lightning Prediction and Its Calibration in Ensemble Forecasts
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A Local Large Hail Probability Equation for Columbia, Sc
EASTERN REGION TECHNICAL ATTACHMENT NO. 98-6 AUGUST, 1998 A LOCAL LARGE HAIL PROBABILITY EQUATION FOR COLUMBIA, SC Mark DeLisi NOAA/National Weather Service Forecast Office West Columbia, SC Editor’s Note: The author’s current affiliation is NWSFO Mt. Holly, NJ. 1. INTRODUCTION Skew-T/Hodograph Analysis and Research Program, or SHARP (Hart and Korotky Billet et al. (1997) derived a successful 1991). The dependent variable, hail diameter probability of large hail (diameter greater than or the absence of hail, was derived from or equal to 0.75 inch) equation as an aid in spotter reports for the CAE warning area from National Weather Service (NWS) severe May, 1995 through September, 1996. There thunderstorm warning operations. Hail of that were 136 cases used to develop the regression diameter or larger requires a severe equation. thunderstorm warning be issued by NWS offices. Shortly thereafter, a Weather The LPLH was verified using 69 spotter Surveillance Radar-1988 Doppler (WSR- reports from the period September, 1996 88D) radar probability of severe hail (POSH) through September, 1997. The POSH was became available for warning operations (Witt verified as well. Verification statistics et al. 1998). This study recreates the steps included the Brier score and the chi-square taken in Billet et al. (1997) to derive a local (32) statistic. probability of large hail equation (LPLH) for the Columbia, SC National Weather Service The goal of this study was to develop an Forecast Office (CAE) warning area, and it objective method to estimate the probability assesses the utility of the LPLH relative to the of large hail for use in forecast operations. -
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. -
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. -
Use Style: Paper Title
Environmental Conditions Producing Thunderstorms with Anomalous Vertical Polarity of Charge Structure Donald R. MacGorman Alexander J. Eddy NOAA/Nat’l Severe Storms Laboratory & Cooperative Cooperative Institute for Mesoscale Meteorological Institute for Mesoscale Meteorological Studies Studies Affiliation/ Univ. of Oklahoma and NOAA/OAR Norman, Oklahoma, USA Norman, Oklahoma, USA [email protected] Earle Williams Cameron R. Homeyer Massachusetts Insitute of Technology School of Meteorology, Univ. of Oklhaoma Cambridge, Massachusetts, USA Norman, Oklahoma, USA Abstract—+CG flashes typically comprise an unusually large Tessendorf et al. 2007, Weiss et al. 2008, Fleenor et al. 2009, fraction of CG activity in thunderstorms with anomalous vertical Emersic et al. 2011; DiGangi et al. 2016). Furthermore, charge structure. We analyzed more than a decade of NLDN previous studies have suggested that CG activity tends to be data on a 15 km x 15 km x 15 min grid spanning the contiguous delayed tens of minutes longer in these anomalous storms than United States, to identify storm cells in which +CG flashes in most storms elsewhere (MacGorman et al. 2011). constituted a large fraction of CG activity, as a proxy for thunderstorms with anomalous vertical charge structure, and For this study, we analyzed more than a decade of CG data storm cells with very low percentages of +CG lightning, as a from the National Lightning Detection Network throughout the proxy for thunderstorms with normal-polarity distributions. In contiguous United States to identify storm cells in which +CG each of seven regions, we used North American Regional flashes constituted a large fraction of CG activity, as a proxy Reanalysis data to compare the environments of anomalous for storms with anomalous vertical charge structure. -
Chapter 8 Atmospheric Statics and Stability
Chapter 8 Atmospheric Statics and Stability 1. The Hydrostatic Equation • HydroSTATIC – dw/dt = 0! • Represents the balance between the upward directed pressure gradient force and downward directed gravity. ρ = const within this slab dp A=1 dz Force balance p-dp ρ p g d z upward pressure gradient force = downward force by gravity • p=F/A. A=1 m2, so upward force on bottom of slab is p, downward force on top is p-dp, so net upward force is dp. • Weight due to gravity is F=mg=ρgdz • Force balance: dp/dz = -ρg 2. Geopotential • Like potential energy. It is the work done on a parcel of air (per unit mass, to raise that parcel from the ground to a height z. • dφ ≡ gdz, so • Geopotential height – used as vertical coordinate often in synoptic meteorology. ≡ φ( 2 • Z z)/go (where go is 9.81 m/s ). • Note: Since gravity decreases with height (only slightly in troposphere), geopotential height Z will be a little less than actual height z. 3. The Hypsometric Equation and Thickness • Combining the equation for geopotential height with the ρ hydrostatic equation and the equation of state p = Rd Tv, • Integrating and assuming a mean virtual temp (so it can be a constant and pulled outside the integral), we get the hypsometric equation: • For a given mean virtual temperature, this equation allows for calculation of the thickness of the layer between 2 given pressure levels. • For two given pressure levels, the thickness is lower when the virtual temperature is lower, (ie., denser air). • Since thickness is readily calculated from radiosonde measurements, it provides an excellent forecasting tool. -
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. -
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. -
Analysis of Lightning and Precipitation Activities in Three Severe Convective Events Based on Doppler Radar and Microwave Radiometer Over the Central China Region
atmosphere Article Analysis of Lightning and Precipitation Activities in Three Severe Convective Events Based on Doppler Radar and Microwave Radiometer over the Central China Region Jing Sun 1, Jian Chai 2, Liang Leng 1,* and Guirong Xu 1 1 Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China; [email protected] (J.S.); [email protected] (G.X.) 2 Hubei Lightning Protecting Center, Wuhan 430074, China; [email protected] * Correspondence: [email protected]; Tel.: +86-27-8180-4905 Received: 27 March 2019; Accepted: 23 May 2019; Published: 1 June 2019 Abstract: Hubei Province Region (HPR), located in Central China, is a concentrated area of severe convective weather. Three severe convective processes occurred in HPR were selected, namely 14–15 May 2015 (Case 1), 6–7 July 2013 (Case 2), and 11–12 September 2014 (Case 3). In order to investigate the differences between the three cases, the temporal and spatial distribution characteristics of cloud–ground lightning (CG) flashes and precipitation, the distribution of radar parameters, and the evolution of cloud environment characteristics (including water vapor (VD), liquid water content (LWC), relative humidity (RH), and temperature) were compared and analyzed by using the data of lightning locator, S-band Doppler radar, ground-based microwave radiometer (MWR), and automatic weather stations (AWS) in this study. The results showed that 80% of the CG flashes had an inverse correlation with the spatial distribution of heavy rainfall, 28.6% of positive CG (+CG) flashes occurred at the center of precipitation (>30 mm), and the percentage was higher than that of negative CG ( CG) − flashes (13%). -
Incident Management Situation Report Wednesday, August 2, 2000 - 0530 Mdt National Preparedness Level V
INCIDENT MANAGEMENT SITUATION REPORT WEDNESDAY, AUGUST 2, 2000 - 0530 MDT NATIONAL PREPAREDNESS LEVEL V CURRENT SITUATION: Dry lightning and very heavy initial attack activity occurred in Arizona, southern New Mexico, southern California, Nevada and Utah. Many of the new starts are unstaffed. Seventeen new large fires were reported in the Western and Eastern Great Basin, Northern Rockies, Southern California, and Southern Areas. An Area Command Team was mobilized to Northern Rockies Area. One Type I Incident Management Team was mobilized to Nevada, one was mobilized to the Eastern Great Basin Area and one was reassigned within the Northern Rockies Area. Containment goals were reached on three large fires. Numerous aircraft, equipment, crew and overhead resource orders are being processed by the National Interagency Coordination Center. All eleven western states are reporting very high to extreme fire danger indices. EASTERN GREAT BASIN AREA LARGE FIRES: Priorities are being established by the Great Basin Multi-Agency Coordinating Group based on information submitted via Wildfire Situation Analysis reports and Incident Status Summary (ICS-209) forms. LOGAN COMPLEX, Wasatch-Cache National Forest. A Type II Incident Management Team (Carr) is assigned. This complex is comprised of the High Point (600 acres) and the Millville 2 (160 acres) fires, both located near Logan, UT. The Millville is a new fire that was ignited on 7/31 near the town of Millville. Helicopters are doing bucket work to support the suppression effort. OLDROYD COMPLEX, Fishlake National Forest. A Type I Incident Management Team (Hutchinson) is assigned. This complex includes the Oldroyd, Mona West, Broad, Mourning Dove and Yance fires near Richfield, UT. -
Exercise 10: Cumulus Cloud with Bulk Cloud Physics
Exercise Hints Tasks Results Exercise 10: Cumulus Cloud With Bulk Cloud Physics PALM group Institute of Meteorology and Climatology, Leibniz Universität Hannover last update: 21st September 2015 PALM group PALM Seminar 1 / 16 I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. I Trigger the cloud by a bubble of rising warm air. I Parameterize condensation using a simple bulk cloud physics scheme. I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: PALM group PALM Seminar 2 / 16 I Trigger the cloud by a bubble of rising warm air. I Parameterize condensation using a simple bulk cloud physics scheme. I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. PALM group PALM Seminar 2 / 16 I Parameterize condensation using a simple bulk cloud physics scheme. I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. I Trigger the cloud by a bubble of rising warm air. PALM group PALM Seminar 2 / 16 I Learn how to carry out conditional averages. Exercise Hints Tasks Results Exercise Exercise 10: Cumulus Cloud With Bulk Cloud Physics Simulate a cumulus cloud: I Initialize the simulation with a marine, cumulus-topped, trade-wind region boundary layer. -
DEPARTMENT of GEOSCIENCES Name______San Francisco State University May 7, 2013 Spring 2009
DEPARTMENT OF GEOSCIENCES Name_____________ San Francisco State University May 7, 2013 Spring 2009 Monteverdi Metr 201 Quiz #4 100 pts. A. Definitions. (3 points each for a total of 15 points in this section). (a) Convective Condensation Level --The elevation at which a lofted surface parcel heated to its Convective Temperature will be saturated and above which will be warmer than the surrounding air at the same elevation. (b) Convective Temperature --The surface temperature that must be met or exceeded in order to convert an absolutely stable sounding to an absolutely unstable sounding (because of elimination, usually, of the elevated inversion characteristic of the Loaded Gun Sounding). (c) Lifted Index -- the difference in temperature (in C or K) between the surrounding air and the parcel ascent curve at 500 mb. (d) wave cyclone -- a cyclone in which a frontal system is centered in a wave-like configuration, normally with a cold front on the west and a warm front on the east. (e) conditionally unstable sounding (conceptual definition) –a sounding for which the parcel ascent curve shows an LFC not at the ground, implying that the sounding is unstable only on the condition that a surface parcel is force lofted to the LFC. B. Units. (2 pts each for a total of 8 pts) Provide the units used conventionally for the following: θ ____ Ko * o o Td ______C ___or F ___________ PGA -2 ( )z ______m s _______________** w ____ m s-1_____________*** *θ = Theta = Potential Temperature **PGA = Pressure Gradient Acceleration *** At Equilibrium Level of Severe Thunderstorms € 1 C. Sounding (3 pts each for a total of 27 points in this section). -
Exam 2: Cloud Physics April 16, 2008 Physical Meteorology 3440
Name ____________________________ Exam 2: Cloud Physics April 16, 2008 Physical Meteorology 3440 Questions 1-10 are worth 5 points each. Questions 11-15 are worth 10 points each. 1. Rank the concentrations of the following from lowest (1) to highest (3): cloud condensation nuclei (3) cloud droplets (2) raindrops (1) 2. Match the following particles with their typical size cloud condensation nuclei 10 μm cloud droplets 0.1 μm raindrops 1000 μm 3. Why do ice crystals grow at the expense of supercooled water droplets? The saturation vapor pressure over liquid is higher than the saturation vapor pressure over ice. Therefore, the environment will be more supersaturated with respect to ice than with respect to liquid, and the ice crystals will grow more quickly. At some point, the ice crystals may bring S (with respect to ice) down to 1, in which case Sl (with respect to liquid) is less than 1, causing the liquid drops to evaporate. 4. Match the following particles with their most likely means of growth 5 μm cloud drop accretion 5 μm ice crystal aggregation 100 μm dendritic ice crystals in ice cloud depositional growth 500 μm ice crystal in mixed-phase cloud condensational growth 100 μm cloud drop collision-coalescence 5. Fill in the blanks: Not all clouds with temperatures below the freezing point of water contain ice, because of the scarcity of ice nuclei in the atmosphere, and the temperature at which they nucleate ice. As the cloud temperature decreases, the probability of ice increases to the 1 temperature of -40 °C, at which point homogeneous freezing occurs.