DOCSLIB.ORG

Nowcasting Applications

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Nowcasting Applications Nowcasting Applications African SWIFT Summer School Morné Gijben [email protected] Weather Research South African Weather Service Doc Ref no: RES-PPT-SWIFT-20190729-GIJ002-001.1 2020/01/10 1 What is the difference between nowcasting and forecasting? 2020/01/10 2 Definition of time ranges • Nowcasting: A description of current weather parameters and 0 to 2 hours’ description of forecast weather parameters • Very short-range weather forecasting: Up to 12 hours’ description of weather parameters • Short-range weather forecasting: Beyond 12 hours’ and up to 72 hours’ description of weather parameters • Medium-range weather forecasting: Beyond 72 hours’ and up to 240 hours’ description of weather parameters • Extended-range weather forecasting: Beyond 10 days’ and up to 30 days’ description of weather parameters. Usually averaged and expressed as a departure from climate values for that period 2020/01/10 3 Definition of time ranges • Long-range forecasting: From 30 days up to two years • Month forecast: Description of averaged weather parameters expressed as a departure (deviation, variation, anomaly) from climate values for that month at any lead-time • Seasonal forecast: Description of averaged weather parameters expressed as a departure from climate values for that season at any lead-time • Climate forecasting: Beyond two years • Climate variability prediction: Description of the expected climate parameters associated with the variation of interannual, decadal and multi-decadal climate anomalies • Climate prediction: Description of expected future climate including the effects of both natural and human influences 2020/01/10 4 Why do we need nowcasting? • Mandate of all weather services globally is to save lives and prevent losses • Monitoring weather events in real time and where they will move to in the next 2 hours (nowcasting) should lead to warnings to the public on the action which is needed to save lives and prevent damage to property • Nowcasting can warn the public on the impact of severe weather events (such as local flooding or wind/hail etc) • International trends are focusing more and nowcasting due to the impact this has on people 2020/01/10 5 • On the nowcasting to very short range forecasting time scale (first 12 hours): – we rely heavily on remote sensing since this gives us real time information – This is used for warnings • On the short to medium (and longer time scales): – NWP/EPS is more important – This is used for watches and advisories (more than a day ahead) • Between real time and 12 hours we can make use of remote sensing blended/combined with NWP to extend the remote sensing tools 2020/01/10 6 Improved observation of real time events: What can satellite provide to us for nowcasting purposes? 2020/01/10 7 The Meteosat Satellite channels Channel Band (μm) VIS0.6 0.56 – 0.71 VIS0.8 0.74 – 0.88 NIR1.6 1.50 – 1.78 IR3.9 3.40 – 4.20 IR8.7 8.30 – 9.10 IR10.8 9.80 – 11.80 IR12.0 11.00 – 13.00 WV6.2 5.35 – 7.15 WV7.3 6.85 – 7.85 IR9.7 9.38 – 9.94 IR13.4 12.40 – 14.40 HRV 0.4 – 1.1 ~3 km data sampling intervals, except HRV (~1 km) Images every 15 minutes 2020/01/10 8 Single Channels IR10.8 channel • Gives some idea of the type of clouds • Bright white color cold temperatures • Grey colors warmer clouds 2020/01/10 9 Color enhancement of IR imagery • A color palette can be added to IR channel displays to enable forecasters to see cloud top temperatures in color • This color palette makes it easier to see cloud top features • Since tall, cold clouds can be associated with severe weather, this is of interest to us all. 2020/01/10 10 Cold-U/V & Cold-ring shaped storms Definitions: Embedded warm area (spot): • smaller region of higher BT, • enclosed by a (more or less) continuous region of lower temperatures, • forms downwind of overshooting tops or in vicinity of elevated domes. The cold-U/V and cold-ring: • features are cold parts of a regular storm anvil only, • surrounding longer-lived (~ 30-40 minutes at least) and • larger-sized embedded warm areas. • It is the character and form of the embedded warm area which determines if the storm is labeled as a cold-ring-shaped or cold-U/V-shaped one. 2020/01/10 11 Cold-U/V & Cold-ring shaped storms • Short-lived embedded warm spots/areas (~ 5-20 minutes) • More frequent • Do not indicate possible severe weather • Long-lived embedded warm spots/areas (~ 1-2 hours) • Do indicate possible severe weather Documented cases showed a very close correlation with severe weather or supercells. However, this feature alone does not automatically classify a storm as a supercell !!! If observed, it indicates a possible severity of the storm, it is not a prove of the severity! 2020/01/10 12 Cold-U/V & Cold-ring shaped storms • Mechanism of cold-U/V and cold-ring formation still not quite well (unambiguously) explained. • Both types are most likely generated by similar mechanisms. It seems that their occurrence is supported by some specific airmass types: A strong thermal inversion above the tropopause. Upper-level wind shear (cold rings typical for lower shear, cold-U/V for higher values of wind shear. 2020/01/10 13 Cold-U/V & Cold-ring shaped storms • Embedded warm area (spot) - part of the storm above the tropopause, with warmer temperatures due to the temperature inversion above the tropopause. • The highest tops are located at the upwind side of the cold ring, and the central warm spot develops with time downwind of these, above the stratiform part of the anvil. 2020/01/10 14 Cold-U/V & Cold-ring shaped storms HRV Meteosat-9 (MSG2) 15:00 UTC IR 10.8 BT ENH DISTANT WARM AREA (DWA) CLOSE-IN WARM AREA (CWA) COLD-U 2020/01/10 26 May 2007, Germany 15 Cold-U/V & Cold-ring shaped storms HRV Meteosat-8 (MSG1) 13:45 UTC IR 10.8 BT ENH CENTRAL WARM SPOT (CWS) COLD RING 25 June 2006, Czech Republic and Austria 2020/01/10 16 MSG Channel Differences Useful to Monitor Convection Channel Diff. Application IR8.7 - IR10.8 Day/Night: optical thickness, phase IR10.8 - IR12.0 Day/Night: optical thickness NIR1.6 - VIS0.6 Day: phase (ice index), particle size IR3.9 - IR10.8 Day: particle size Night: particle size (only for warm clouds) WV6.2 - IR10.8 Day/Night: overshooting tops 2020/01/10 17 IR10.8 – IR12.0 • Uses two MSG channels (IR 10.8 and 12.0) • Identify moisture ridges and drylines • BTD IR10.8-12.0 gives indication of total moisture content • Focuses on surface features recommended by EUMETSAT Dry Moist 0600Z 0 to +1 K +2 to +4 K 1200Z 0 to +2 K +4 to +6 K 2020/01/10 18 IR10.8 – IR12.0 MOIST DRY 2020/01/10 19 IR10.8 – IR12.0 • 09:00 UTC • 13:00 UTC MOIST DRY 2020/01/10 20 IR10.8 – IR12.0 limitations • Clear skies • Influenced by diurnal variations • Low moisture hot surface = high moisture cold surface • Does not work at night • Does not work in high mountain areas • Contaminated by sandy surfaces 2020/01/10 21 MSG Red-Green-Blue(RGB) combinations 2020/01/10 22 Standard RGBs RGB Composite Applications Time RGB 10-09,09-07,09: Dust, Clouds (thickness, phase), Contrails Day & Night Fog, Ash, SO2, Low-level Humidity RGB 05-06,08-09,05 Severe Cyclones, Jets, PV Analysis Day & Night RGB 10-09,09-04,09: Clouds, Fog, Contrails, Fires Night RGB 02,04r,09: Clouds, Convection, Snow, Fog, Fires Day RGB 05-06,04-09,03-01: Severe Convection Day RGB 02,03,04r: Snow, Fog Day RGB 03,02,01: Vegetation, Snow, Smoke, Dust, Fog Day 2020/01/10 23 RGB 05-06, 04-09, 03-01 (Convective Storms) R = Difference WV6.2 - WV7.3 G = Difference IR3.9 - IR10.8 B = Difference NIR1.6 - VIS0.6 Applications: Severe Convective Storms Area: Full MSG Viewing Area Time: Day-Time 2020/01/10 24 RGB 05-06,04-09,03-01: Interpretation of Color Deep precipitating cloud Deep precipitating cloud Thin Cirrus cloud Thin Cirrus cloud (precip. not necessarily (Cb cloud with strong reaching the ground) updrafts and severe (large ice particles) (small ice particles) weather)* - high-level cloud - high-level cloud - large ice particles - small ice particles *or thick, high-level lee cloudiness with small ice particles Ocean Land 2020/01/10 25 RGB 05-06, 04-09, 03-01 (Convective Storms) Thin Ice Cloud (small ice) Maputo Thin Ice Cloud (large ice) Thick Ice Cloud Thick Ice Cloud (large ice) (small ice) MSG-1, 6 November 2004, 12:00 UTC, RGB 05-06, 04-09, 03-01 2020/01/10 26 Overshooting Top RGB • Overshooting tops are the most intense part of thunderstorms • This is where the strongest updrafts are and thus also possible severe weather • To identify this part of the thunderstorm can help with severe weather warnings. 2020/01/10 27 Overshooting Top RGB Recipe 2020/01/10 28 Example Overshooting Top RGB = Overshooting Tops Airmass RGB Overshooting Top RGB 14 September 2010, 19:45 UTC (Hurricane Julia) Slide by Jochen Kerkmann 2020/01/10 29 Satellite based instability indices 2020/01/10 30 Instability Indices • Why do we need to measure instability in the atmosphere? • How do we do it? • Is this good enough? • Typical indices? 2020/01/10 31 Instability Indices • The Global Humanitarian Forum states: • “Developing countries, which are most likely to suffer the brunt of climate change impacts, have the least number of ground-level weather data observation systems, the critical basis for efficient delivery of weather information.
Load more

Recommended publications
  • American Meteorological Society Revised Manuscript Click Here to Download Manuscript (Non-Latex): JAMC-D-14-0252 Revision3.Docx
    AMERICAN METEOROLOGICAL SOCIETY Journal of Applied Meteorology and Climatology EARLY ONLINE RELEASE This is a preliminary PDF of the author-produced manuscript that has been peer-reviewed and accepted for publication. Since it is being posted so soon after acceptance, it has not yet been copyedited, formatted, or processed by AMS Publications. This preliminary version of the manuscript may be downloaded, distributed, and cited, but please be aware that there will be visual differences and possibly some content differences between this version and the final published version. The DOI for this manuscript is doi: 10.1175/JAMC-D-14-0252.1 The final published version of this manuscript will replace the preliminary version at the above DOI once it is available. If you would like to cite this EOR in a separate work, please use the following full citation: Wang, Y., and B. Geerts, 2015: Vertical-plane dual-Doppler radar observations of cumulus toroidal circulations. J. Appl. Meteor. Climatol. doi:10.1175/JAMC-D-14- 0252.1, in press. © 2015 American Meteorological Society Revised manuscript Click here to download Manuscript (non-LaTeX): JAMC-D-14-0252_revision3.docx Vertical-plane dual-Doppler radar observations of cumulus toroidal circulations Yonggang Wang1, and Bart Geerts University of Wyoming Submitted to J. Appl. Meteor. Climat. October 2014 Revised version submitted in May 2015 1 Corresponding author address: Yonggang Wang, Department of Atmospheric Science, University of Wyoming, Laramie WY 82071, USA; email: [email protected] 1 Profiling dual-Doppler radar observations of cumulus toroidal circulations 2 3 Abstract 4 5 6 High-resolution vertical-plane dual-Doppler velocity data, collected by an airborne profiling 7 cloud radar in transects across non-precipitating orographic cumulus clouds, are used to examine 8 vortical circulations near cloud top.
    [Show full text]
  • Äikesega) Kaasnevad Ohtlikud Ilmanähtused
    TALLINNA TEHNIKAÜLIKOOL Eesti Mereakadeemia Merenduskeskus Veeteede lektoraat Raldo Täll RÜNKSAJUPILVEDEGA KAASNEVAD OHTLIKUD ILMANÄHTUSED LÄÄNEMEREL Lõputöö Juhendajad: Jüri Kamenik Lia Pahapill Tallinn 2016 SISUKORD SISUKORD ................................................................................................................................ 2 SÕNASTIK ................................................................................................................................ 4 SISSEJUHATUS ........................................................................................................................ 6 1. RÜNKSAJUPILVED JA ÄIKE ............................................................................................. 8 1.1. Äikese tekkimine ja areng ............................................................................................. 10 1.1.1. Äikese arengustaadiumid ........................................................................................ 11 1.2. Äikeste klassifikatsioon ................................................................................................. 14 1.2.1. Sünoptilise olukorra põhine liigitus ........................................................................ 14 1.2.2. Äikese seos tsüklonitega ......................................................................................... 15 1.2.3. Organiseerumispõhine liigitus ................................................................................ 16 2. RÜNKSAJUPILVEDEGA (ÄIKESEGA) KAASNEVAD OHTLIKUD ILMANÄHTUSED
    [Show full text]
  • Session 8.Pdf
    MARTIN SETVÁK [email protected] CZECH HYDROMETEOROLOGICAL INSTITUTE ČESKÝ HYDROMETEOROLOGICKÝ ÚSTAV http://www.chmi.cz http://www.setvak.cz Anticipated benefits of improved temporal and spatial resolution (with focus on deep convective clouds) EUMeTrain Event Week on MTG-I Satellite, 7 – 11 November 2016 Martin Setvák version: 2016-11-11 Introduction The most significant impact of improved spatial resolution and shorter scan interval: observations (detection, monitoring, nowcasting, …) and studies of short-lived and small scale features or phenomena e.g. fires, valley fog, shallow convection, and tops of deep convective clouds (storms) – namely their overshooting tops Martin Setvák Introduction The most significant impact of improved spatial resolution and shorter scan interval: observations (detection, monitoring, nowcasting, …) and studies of short-lived and small scale features or phenomena e.g. fires, valley fog, shallow convection, and tops of deep convective clouds (storms) – namely their overshooting tops geometrical properties and characteristics (visible and near-IR bands), cloud microphysics, cloud-top brightness temperature (BT) Martin Setvák Overshooting tops definition and appearance OVERSHOOTING TOP (anvil dome, penetrating top): A domelike protrusion above a cumulonimbus anvil, representing the intrusion of an updraft through its equilibrium level (level of neutral buoyancy). It is usually a transient feature because the rising parcel's momentum acquired during its buoyant ascent carries it past the point where it is
    [Show full text]
  • Severe Weather in the United States
    Module 18: Severe Thunderstorms in the United States Tuscaloosa, Alabama May 18, 2011 Dan Koopman 2011 What is “Severe Weather”? Any meteorological condition that has potential to cause damage, serious social disruption, or loss of human life. American Meteorological Society: In general, any destructive storm, but usually applied to severe local storms in particular, that is, intense thunderstorms, hailstorms, and tornadoes. Three Stages of Thunderstorm Development Stage 1: Cumulus • A warm parcel of air begins ascending vertically into the atmosphere. • In an unstable environment, the parcel will continue to rise as long as it is warmer than the air around it. • Billowing, puffy Cumulus Congestus Clouds continue to build in towers. Stage 2: Mature • At a certain altitude, the parcel is no longer warmer than its environment. It is unable to rise any further and develops the distinctive “Anvil” shape as seen in this figure. • In cases of particularly strong updrafts, the vertical velocity of the updraft may be sufficient to penetrate this altitude causing an “overshooting top” to develop above the flat top of the anvil. Stage 3: Dissipating • Convective inflow shut off by strong downdrafts, no more cloud droplet formation, downdrafts continue and gradually weaken until light precipitation rains out • Water droplets aloft being to coalesce until they are too heavy to support and begin to fall to the surface, strengthening the downdraft. Basic Ingredients for Thunderstorms • Moisture • Unstable Air • Forcing Mechanism Moisture Thunderstorms development generally requires dewpoints > 50°F Unstable Air Stable is resistant to change. When the air is stable, even if a parcel of air is lifted above its original position (say by a mountain for example), its temperature will always remain cooler than its environment, meaning that it will resist upwards movement.
    [Show full text]
  • Flash Flooding
    NationalNational OceanicOceanic andand AtmosphericAtmospheric AdministrationAdministration (NOAA)(NOAA) NationalNational WeatherWeather ServiceService (NWS)(NWS) PresentsPresents SevereSevere WeatherWeather ObserverObserver andand SafetySafety TrainingTraining 20052005 Severe Weather Spotter Line 1-888-668-3344 Spotter Reports E-mail: www.crh.noaa.gov/espotter Homepage Address: www.crh.noaa.gov/iwx 2 GoalsGoals ofof thethe TrainingTraining You will learn: • Definitions of important weather terms and severe weather criteria • How thunderstorms develop and why some become severe • How to correctly identify cloud features that may or may not be associated with severe weather • What information the observer is to report and how to report it • Ways to receive weather information before and during severe weather events • Observer Safety! 3 WFOWFO NorthernNorthern IndianaIndiana (WFO(WFO IWX)IWX) CountyCounty WarningWarning andand ForecastForecast AreaArea (CWFA)(CWFA) Work with public, state and local officials Dedicated team of highly trained professionals 24 hours a day/7 days a week Prepare forecasts and warnings for 2.3 million people in 37 counties 4 SKYWARNSKYWARN (Severe(Severe Weather)Weather) ObserversObservers Why Are You Critical to NWS Operations? • Help overcome Doppler Radar limitations • Provide ground truth which can be correlated with radar signatures prior to, during, and after severe weather • Ground truth reports in warnings heighten public awareness and allow us to have confidence in our warning decisions 5 SKYWARNSKYWARN (Severe(Severe Weather)Weather) ObserversObservers Why Are You Critical to NWS Operations? • The NWS receives hundreds of reports of “False” or “Mis-Identified” funnel clouds and tornadoes each year • We strongly rely on the “2 out of 3” Rule before issuing a warning. Of the following, we like to have 2 out of 3 present before sending out a warning.
    [Show full text]
  • Glossary of Severe Weather Terms
    Glossary of Severe Weather Terms -A- Anvil The flat, spreading top of a cloud, often shaped like an anvil. Thunderstorm anvils may spread hundreds of miles downwind from the thunderstorm itself, and sometimes may spread upwind. Anvil Dome A large overshooting top or penetrating top. -B- Back-building Thunderstorm A thunderstorm in which new development takes place on the upwind side (usually the west or southwest side), such that the storm seems to remain stationary or propagate in a backward direction. Back-sheared Anvil [Slang], a thunderstorm anvil which spreads upwind, against the flow aloft. A back-sheared anvil often implies a very strong updraft and a high severe weather potential. Beaver ('s) Tail [Slang], a particular type of inflow band with a relatively broad, flat appearance suggestive of a beaver's tail. It is attached to a supercell's general updraft and is oriented roughly parallel to the pseudo-warm front, i.e., usually east to west or southeast to northwest. As with any inflow band, cloud elements move toward the updraft, i.e., toward the west or northwest. Its size and shape change as the strength of the inflow changes. Spotters should note the distinction between a beaver tail and a tail cloud. A "true" tail cloud typically is attached to the wall cloud and has a cloud base at about the same level as the wall cloud itself. A beaver tail, on the other hand, is not attached to the wall cloud and has a cloud base at about the same height as the updraft base (which by definition is higher than the wall cloud).
    [Show full text]
  • Objective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness Temperature Gradients
    VOLUME 49 JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY FEBRUARY 2010 Objective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness Temperature Gradients KRISTOPHER BEDKA,JASON BRUNNER,RICHARD DWORAK,WAYNE FELTZ, JASON OTKIN, AND THOMAS GREENWALD Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin (Manuscript received 19 May 2009, in final form 31 August 2009) ABSTRACT Deep convective storms with overshooting tops (OTs) are capable of producing hazardous weather con- ditions such as aviation turbulence, frequent lightning, heavy rainfall, large hail, damaging wind, and tor- nadoes. This paper presents a new objective infrared-only satellite OT detection method called infrared window (IRW)-texture. This method uses a combination of 1) infrared window channel brightness temper- ature (BT) gradients, 2) an NWP tropopause temperature forecast, and 3) OT size and BT criteria defined through analysis of 450 thunderstorm events within 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) imagery. Qualitative validation of the IRW-texture and the well-documented water vapor (WV) minus IRW BT difference (BTD) technique is performed using visible channel imagery, CloudSat Cloud Profiling Radar, and/or Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud-top height for selected cases. Quantitative validation of these two techniques is obtained though comparison with OT detections from synthetic satellite imagery derived from a cloud-resolving NWP simulation. The results show that the IRW-texture method false-alarm rate ranges from 4.2% to 38.8%, depending upon the magnitude of the overshooting and algo- rithm quality control settings.
    [Show full text]
  • PICTURE of the MONTH Some Frequently Overlooked Severe
    JUNE 2004 PICTURE OF THE MONTH 1529 PICTURE OF THE MONTH Some Frequently Overlooked Severe Thunderstorm Characteristics Observed on GOES Imagery: A Topic for Future Research JOHN F. W EAVER AND DAN LINDSEY NOAA/NESDIS/RAMM Team, Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado 23 October 2003 and 23 December 2003 ABSTRACT Several examples of Geostationary Operational Environmental Satellite (GOES) visible satellite images de- picting cloud features often associated with the transition to, or intensi®cation of, supercell thunderstorms are presented. The accompanying discussion describes what is known about these features, and what is left to learn. The examples are presented to increase awareness among meteorologists of these potentially signi®cant storm features. 1. Introduction dom 1976, 1983; Weaver 1980; Weaver and Nelson The role of satellite imagery in de®ning the near- 1982; Purdom and Sco®eld 1986; Weaver and Purdom storm environment of severe/tornadic thunderstorms has 1995; Browning et al. 1997; Weaver et al. 1994, 2000; been well documented over the past three decades (Pur- 2002; Bikos et al. 2002). Additionally, several papers have been written concerning storm-top characteristics of severe storms (Heyms®eld et al. 1983; McCann 1983; Corresponding author address: John F. Weaver, NOAA/NESDIS/ Adler and Mack 1986; SetvaÂk and Doswell 1991). Much RAMM, CIRA BuildingÐFoothills Campus, Colorado State Uni- versity, Fort Collins, CO 80523. less has been written concerning low-level,
    [Show full text]
  • Weather Spotter's Field Guide
    Weather Spotter’s Field Guide © Roger Edwards A Guide to Being a SKYWARN® Spotter U.S. DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration National Weather Service Ⓡ June 2011 The Spotter’s Role Section 1 The SKYWARN® Spotter and the Spotter’s Role The United States is the most severe weather- prone country in the world. Each year, people in this country cope with an average of 10,000 thunderstorms, 5,000 floods, 1,200 tornadoes, and two landfalling hurricanes. Approximately 90% of all presidentially Ⓡ declared disasters are weather-related, causing around 500 deaths each year and nearly $14 billion in damage. SKYWARN® is a National Weather Service (NWS) program developed in the 1960s that consists of trained weather spotters who provide reports of severe and hazardous weather to help meteorologists make life-saving warning decisions. Spotters are concerned citizens, amateur radio operators, truck drivers, mariners, airplane pilots, emergency management personnel, and public safety officials who volunteer their time and energy to report on hazardous weather impacting their community. Although, NWS has access to data from Doppler radar, satellite, and surface weather stations, technology cannot detect every instance of hazardous weather. Spotters help fill in the gaps by reporting hail, wind damage, flooding, heavy snow, tornadoes and waterspouts. Radar is an excellent tool, but it is just that: one tool among many that NWS uses. We need spotters to report how storms and other hydrometeorological phenomena are impacting their area. SKYWARN® spotter reports provide vital “ground truth” to the NWS. They act as our eyes and ears in the field.
    [Show full text]
  • Aviation Weather Testbed – Final Evaluation
    Aviation Weather Testbed – Final Evaluation Project Title: 2014 GOES-R/JPSS Demonstration Organization: NOAA’s Aviation Weather Testbed (AWT) Evaluator(s): Aviation Weather Center (AWC) forecasters, Central Weather Service Unit (CWSU) forecasters, Federal Aviation Administration (FAA) personnel, and general aviation personnel Duration of Evaluation: 1 February 2014 – 1 September 2014 Prepared By: Amanda Terborg (UW/CIMSS and NOAA/AWC) Final Submitted Date: 19 September 2014 Table of Contents Contents ...........................................................................................................................................1 1. Summary ......................................................................................................................................2 2. Introduction ..................................................................................................................................2 3. GOES-R Products Evaluated .......................................................................................................4 3.1 Aircraft Flight Icing Threat ........................................................................................................5 3.2 ACHA Cloud Algorithms ..........................................................................................................6 3.3 Convective Toolkit.....................................................................................................................8 3.3.1 GOES-R Convective Initiation ...................................................................................8
    [Show full text]
  • Prmet Ch14 Thunderstorm Fundamentals
    Copyright © 2015 by Roland Stull. Practical Meteorology: An Algebra-based Survey of Atmospheric Science. 14 THUNDERSTORM FUNDAMENTALS Contents Thunderstorm Characteristics 481 Thunderstorm characteristics, formation, and Appearance 482 forecasting are covered in this chapter. The next Clouds Associated with Thunderstorms 482 chapter covers thunderstorm hazards including Cells & Evolution 484 hail, gust fronts, lightning, and tornadoes. Thunderstorm Types & Organization 486 Basic Storms 486 Mesoscale Convective Systems 488 Supercell Thunderstorms 492 INFO • Derecho 494 Thunderstorm Formation 496 ThundersTorm CharacterisTiCs Favorable Conditions 496 Key Altitudes 496 Thunderstorms are convective clouds INFO • Cap vs. Capping Inversion 497 with large vertical extent, often with tops near the High Humidity in the ABL 499 tropopause and bases near the top of the boundary INFO • Median, Quartiles, Percentiles 502 layer. Their official name is cumulonimbus (see Instability, CAPE & Updrafts 503 the Clouds Chapter), for which the abbreviation is Convective Available Potential Energy 503 Cb. On weather maps the symbol represents Updraft Velocity 508 thunderstorms, with a dot •, asterisk *, or triangle Wind Shear in the Environment 509 ∆ drawn just above the top of the symbol to indicate Hodograph Basics 510 rain, snow, or hail, respectively. For severe thunder- Using Hodographs 514 storms, the symbol is . Shear Across a Single Layer 514 Mean Wind Shear Vector 514 Total Shear Magnitude 515 Mean Environmental Wind (Normal Storm Mo- tion) 516 Supercell Storm Motion 518 Bulk Richardson Number 521 Triggering vs. Convective Inhibition 522 Convective Inhibition (CIN) 523 Triggers 525 Thunderstorm Forecasting 527 Outlooks, Watches & Warnings 528 INFO • A Tornado Watch (WW) 529 Stability Indices for Thunderstorms 530 Review 533 Homework Exercises 533 Broaden Knowledge & Comprehension 533 © Gene Rhoden / weatherpix.com Apply 534 Figure 14.1 Evaluate & Analyze 537 Air-mass thunderstorm.
    [Show full text]
  • Evidence for Ice Particles in the Tropical Stratosphere from In-Situ Measurements
    Atmos. Chem. Phys. Discuss., 8, 19313–19355, 2008 Atmospheric www.atmos-chem-phys-discuss.net/8/19313/2008/ Chemistry © Author(s) 2008. This work is distributed under and Physics the Creative Commons Attribution 3.0 License. Discussions This discussion paper is/has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP if available. Evidence for ice particles in the tropical stratosphere from in-situ measurements M. de Reus1,2, S. Borrmann1,2, A. J. Heymsfield3, R. Weigel4, C. Schiller5, V. Mitev6, W. Frey2, D. Kunkel2, A. Kurten¨ 7, J. Curtius8, N. M. Sitnikov9, A. Ulanovsky9, and F. Ravegnani10 1Max Planck Institute for Chemistry, Particle Chemistry Department, Mainz, Germany 2Institute for Atmospheric Physics, Mainz University, Germany 3National Center for Atmospheric Research, Boulder, USA 4Laboratoire de Met´ eorologie´ Physique, Universite´ Blaise Pascal, Clermont-Ferrand, France 5Institute of Chemistry and Dynamics of the Geosphere, Research Centre Julich,¨ Germany 6Swiss Centre for Electronics and Microtechnology, Neuchatel,ˆ Switzerland 7Div. of Engineering and Applied Science California Inst. of Technology, Pasadena, Ca., USA 8Institute for Atmospheric and Environmental Sciences, Goethe Univ. of Frankfurt, Germany 9Central Aerological Observatory, Dolgoprudny, Moskow Region, Russia 10Institute of Atmospheric Sciences and Climate, Bologna, Italy Received: 19 August 2008 – Accepted: 24 September 2008 – Published: 14 November 2008 Correspondence to: M. de Reus ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. 19313 Abstract In-situ ice crystal size distribution measurements are presented within the tropical tro- posphere and lower stratosphere. The measurements were performed using a combi- nation of a Forward Scattering Spectrometer Probe (FSSP-100) and a Cloud Imaging 5 Probe (CIP) which were installed on the Russian high altitude research aircraft M55 “Geophysica” during the SCOUT-O3 campaign in Darwin, Australia.
    [Show full text]