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Press the tab key to jump to interactive markers and hotspots. 360 degree image interaction free exploration mode guided tour mode next previous step item items label marker of pause audio pause video play audio play video progress progress %total% item %total% items video video volume visited Toggle zoom to fit Transcript Autoscroll Notes Show timestamps Unmute Resume autoscroll Select track Transcripts Zoom to fit noaa/cimss probability of severe (probsevere) model alyssa bates january 2026 identify the basic characteristics of probsevere version 3 reproduce the simplified process by which probsevere’s probabilities are generated indicate the input sources of probsevere’s model and their uses list the parameters included in probwind, probhail, and probtor recall probsevere’s general reliability based on its verification articulate probsevere’s limitations and their potential effects on warning operations objectives version 1 version 2 version 1 (v1) operational since 2017 version 2 (v2) “all-hazards” operational 2019 statistical model that predicts the probability that a storm will produce severe hail, severe wind, or a tornado in the next 0-60 min version 3 (v3) operational 2025 statistical model that uses ml models to predict the probability that a storm will produce severe hail, severe wind, a tornado, or any severe in the next 0-60 min updates every 2 minutes probability of severe (probsevere) is a statistical model that incorporates many observational datasets to create a nowcast of the probability of severe weather. probsevere basics: versions version 3 probsevere is a situational awareness tool that can be used for severe thunderstorm polygon placement and as an aide for warning reissuance and updates see wdtd probsevere applications lesson (coming soon) probsevere basics: applications fits into nws probabilistic impact-based decision support services (probidss) strategic goal see resources tab for more info probsevere basics: automated probability generation storm id’d and tracked with mrms composite reflectivity and satellite growth rate run through statistical machine learning model 0-3 km agl lapse rate 1-3 km agl mean wind effective bulk shear mlcape 0-2 km mrms azimuthal shear 0-3 km agl lapse rate 1-3 km agl mean wind total lightning flash rate 0-2 and 3-6 km azimuthal shear effective bulk shear 4-6 km agl storm relative wind mlcape mrms reflectivity at -20ºc mrms mesh satellite growth rate effective bulk shear 1-3 km agl mean wind 0-3 km agl lapse rate total lightning flash rate mrms mesh mrms vil satellite growth rate hail hail hail hail hail hail see resources tab for more info all-hazards all-hazards all-hazards all-hazards all-hazards all-hazards statistical model driven by blend of observations and environmental data uses this blend of current and past conditions to predict the probability of severe hazards in the next 60 mins probsevere basics: inputs wind wind wind wind wind wind tornado tornado tornado tornado tornado tornado click on each hazard to view its inputs hourly hrrr grids 2-min conus radar scans 5-min conus satellite scans satellite, radar, lightning, and model data have different timescales probsevere probabilities change each time new data are available displays probability of severe weather within the next hour 2-min lightning files output probsevere basics: real-time operations probsevere awips2 display inner contour: maximum probability of probwind, probhail, or probtor (here, probwind) “all-hazards” outer contour: probtor probsevere awips2 display probtor probsevere awips2 display probhail see wdtd probsevere applications lesson for more displays probsevere awips2 display probwind probsevere is the probability that a storm will produce severe weather in the next 60 min and it updates with new data every 2 mins probsevere is created through this simplified process: identify a storm cell with mrms composite reflectivity and satellite growth rate analyze a storm’s properties using lightning, mrms, hrrr model data, etc. run the data through the ml statistical model generate probabilities inputs into probsevere include: 5-min goes scans hourly hrrr environmental grids 2-min lightning files 2-min conus radar scans probtor, probwind, and probhail comprised of various parameters based on severe and non-severe characteristics interim summary probsevere v3 better calibrated than v2 probabilities will be lower probsevere less skillful than forecasters (expected), but comparable 90% of hazardous weather testbed participants agreed v3 offers better lead time and warning confidence probtor least skillful of probsevere models probsevere verification: all probsevere models all-hazards probhail probtor probwind …in environments with low-to-moderate mixed-layer cape and moderate-to-high effective bulk shear. probsevere verification: all-hazards …in the great plains. probsevere verification: all-hazards all-hazards is most reliable… …in non-winter months. probsevere verification: all-hazards under-forecast over-forecast whereas v2 tended to under-forecast, v3 models have a slight over-forecasting bias probhail slight under-forecasting bias at probabilities >75% most reliable in may-september note: probwind v3 is more reliable than v2 due to better skill in detecting linear severe wind events probhail and probwind exhibit more accuracy than probtor probsevere verification: probwind & probhail probhail probwind probtor least skilful of probsevere models note probtor’s trends rather than actual value exhibits over-forecasting in july–september (above 60%) and under-forecasting in january–march and october but predictions for above 60% are very rare probsevere verification: probtor under-forecast thick cirrus shields linear convective modes single radar coverage beam blockage far from radar high winds outside reflectivity core probtor: landspout tornadoes hrrr 0-1 km srh too low over-forecast probtor: near radar sites mrms products over-forecast over/under-forecasting vs. ex. marginal kinematics 0-1 km srh: 100 m2 s-2 eff. bulk shear: 30 kts 1-3 km agl mw: 20 kts ex. favorable kinematics 0-1 km srh: 200 m2 s-2 eff. bulk shear: 50 kts 1-3 km agl mw: 40 kts do not expect the same probtor probability value to give the same results for every event—the kinematic fields impact probtor! 0% 3% 30% 6% 10% 60% it is best to use probtor in a relative sense! probtor: environment matters! probsevere blog posts from hazardous weather testbed (hwt) experiments: probsevere on realearth: probsevere verification by accumulation: gibson ridge placefiles: probsevere verification by accumulation: see resources tab for links additional probsevere resources future improvements may include: probtor improvement and probsevere trends in awips probsevere introduced derived from: nwp goes-13 nexrad (mrms) probsevere improved “all hazards” probsevere including: probhail, probwind, probtor 2014 2017 2025 probsevere timeline probsevere version 3 introduced improved algorithm glm added probwind improved more predictors added for each hazard probsevere is just the beginning…. as nws leans more into probabilistic idss and short-term forecasting, new products will keep coming, including: probabilistic hazard information (phi), takes probsevere and projects it out to an hour (available in gr by request to nssl) phi recommender in hazard services-convective tornado probability algorithm (torp) to replace the tda (coming to an rpg build soon) warn-on-forecast system (wofs), a storm-based ensemble (select runs are available on the noaa vlab) a. b. c. all of these products are to be used along with your existing warning procedures and base radar data to increase your confidence in warning decision-making incorrect continue continue continue continue continue continue probsevere is the probability that a storm will produce severe weather in the next 60 min and it updates with new data every 2 mins correct continue continue continue continue continue continue 60 mins; 2 mins 60 mins; 2 mins 60 mins; 2 mins 60 mins; 2 mins 60 mins; 2 mins 60 mins; 2 mins probsevere is the probability a storm will produce severe weather in the next _________ minutes and it updates every ________ minutes. 30 mins; 2 mins 30 mins; 2 mins 30 mins; 2 mins 30 mins; 2 mins 30 mins; 2 mins 30 mins; 2 mins 30 mins; 30 mins 30 mins; 30 mins 30 mins; 30 mins 30 mins; 30 mins 30 mins; 30 mins 30 mins; 30 mins 60 mins; 5 mins 60 mins; 5 mins 60 mins; 5 mins 60 mins; 5 mins 60 mins; 5 mins 60 mins; 5 mins incorrect you did not select the correct response. continue continue continue continue continue continue probsevere is created through this simplified process: identify a storm cell with mrms composite reflectivity and satellite growth rate analyze a storm’s properties using lightning, mrms, hrrr model data, etc. run the data through the ml statistical mode generate probabilities correct continue continue continue continue continue continue put these simplified steps of the process by which probsevere is calculated in order: identify a storm cell with mrms composite reflectivity and satellite growth rate analyze a storm's properties using lightning, mrms, hrrr model data, etc. run the data through the statistical model generate probabilities incorrect continue continue continue continue continue continue inputs into probsevere include: 5-min goes scans hourly hrrr environmental grids 2-min lightning files 2-min conus radar scans correct continue continue continue continue continue continue all of the following datasets are inputs into the probsevere model except: 5-min goes scans 5-min goes scans 5-min goes scans 5-min goes scans 5-min goes scans 5-min goes scans hourly gefs environmental grids hourly gefs environmental grids hourly gefs environmental grids hourly gefs environmental grids hourly gefs environmental grids hourly gefs environmental grids 2-min lightning files 2-min lightning files 2-min lightning files 2-min lightning files 2-min lightning files 2-min lightning files 2-min conus radar scans 2-min conus radar scans 2-min conus radar scans 2-min conus radar scans 2-min conus radar scans 2-min conus radar scans hourly hrrr environmental grids hourly hrrr environmental grids hourly hrrr environmental grids hourly hrrr environmental grids hourly hrrr environmental grids hourly hrrr environmental grids incorrect you did not select the correct response. continue continue continue continue continue continue effective bulk shear 4-6 km agl storm relative wind mlcape mrms reflectivity at -20ºc mrms mesh satellite growth rate hail hail hail hail hail hail correct that's right! you selected the correct response. continue continue continue continue continue continue effective bulk shear effective bulk shear effective bulk shear effective bulk shear effective bulk shear effective bulk shear satellite growth rate satellite growth rate satellite growth rate satellite growth rate satellite growth rate satellite growth rate mlcape mlcape mlcape mlcape mlcape mlcape mrms reflectivity at –20 deg c mrms reflectivity at –20 deg c mrms reflectivity at –20 deg c mrms reflectivity at –20 deg c mrms reflectivity at –20 deg c mrms reflectivity at –20 deg c mrms mesh mrms mesh mrms mesh mrms mesh mrms mesh mrms mesh sigtor parameter sigtor parameter sigtor parameter sigtor parameter sigtor parameter sigtor parameter 4-6 km agl storm relative wind 4-6 km agl storm relative wind 4-6 km agl storm relative wind 4-6 km agl storm relative wind 4-6 km agl storm relative wind 4-6 km agl storm relative wind select all the parameters used to calculate probhail. incorrect continue continue continue continue continue continue probsevere v3 better calibrated than v2 probabilities will be lower correct continue continue continue continue continue continue true true true true true true false false false false false false probsevere v3 will generally provide lower probabilities than v2 due to being better calibrated. probsevere v3 will generally provide lower probabilities than v2 due to being better calibrated. incorrect continue continue continue continue continue continue correct continue continue continue continue continue continue probsevere limitations not probsevere limitations drag the sticky notes with known probsevere limitations to the right bulletin board and sticky notes that are not probsevere limitations to the left bulletin board. drag the sticky notes with known probsevere limitations to the right bulletin board and sticky notes that are not probsevere limitations to the left bulletin board. noaa/nws warning decision training division/university of oklahoma cooperative institute for severe and high-impact weather research and operations woc severe team (nws.wdtd.wocsevere@noaa.gov) alyssa bates (alyssa.bates@noaa.gov) noaa nesdis/university of wisconsin cooperative institute for meteorological satellite studies and noaa/nssl john cintineo (john.cintineo@noaa.gov) mike pavolonis (michael.pavolonis@noaa.gov) justin sieglaff (justin.sieglaff@ssec.wisc.edu) contact cintineo, j. l., m. j. pavolonis, j. m. sieglaff, 2024: probsevere version 3: improved exploitation of data fusion and machine learning for nowcasting severe weather. wea. forecasting, 39(12), 1937–1958. doi: https://doi.org/10.1175/waf-d-24-0076.1 sandmæl, t. n., smith, b. r., reinhart, a. e., schick, i. m., ake, m. c., madden, j. g., et al. (2023). the tornado probability algorithm: a probabilistic machine learning tornadic circulation detection algorithm. wea. forecasting, 38(3), 445–466. https://doi.org/10.1175/waf-d-22-0123.1 cintineo, j. l., and coauthors, 2018: the noaa/cimss probsevere model: incorporation of total lightning and validation. wea. forecasting, 33, 331–345, https://doi.org/10.1175/waf-d-17-0099.1 cintineo, j. l., m. j. pavolonis, j. m. sieglaff, and d.t. lindsey, 2014: an empirical model for assessing the severe weather potential of developing convection. weather and forecasting., 29, 639-653. cintineo, j. l., m. j. pavolonis, j. m. sieglaff, and a. k. heidinger, 2013: evolution of severe and non-severe convection inferred from goes-derived cloud properies. j. appl. meteorol. climatol., 52, 2009-2023. lakshmanan, v., t. smith, g. stumpf, and k. hondl, 2007: the warning decision support system-integrated information. weather and forecasting, 22, doi:10.1175/waf1009.1 pavolonis, m. j., 2010: advances in extracting cloud composition information from spaceborne infrared radiances-a robust alternative to brightness temperatures. part i: theory. journal of applied meteorology and climatology, 49, doi:10.1175/2010jamc2433.1. pavolonis, m.j., 2010: abi cloud type/phase algorithm theoretical basis document. noaa nesdis center for satellite applications and research (star), 60 pp. sieglaff, justin m., d. c. hartung, w. f. feltz, l. m. cronce, v. lakshmanan, 2013: a satellite-based convective cloud object tracking and multipurpose data fusion tool with application to developing convection. j. atmos. oceanic technol., 30, 510–525. witt, a., m. d. eilts, g. j. stumpf, j. t. johnson, e. d. w. mitchell, k. w. thomas, 1998: an enhanced hail detection algorithm for the wsr-88d. wea. forecasting, 13, 286–303. references alyssa.bates@noaa.gov <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Welcome to this Warning Decision Training Division (WDTD) lesson on the NOAA/CIMSS Probability of Severe (ProbSevere) statistical model! I’m Alyssa Bates from WDTD and OU CIWRO and I’ll be guiding you through the basics of the ProbSevere products. Before we dive in, I’d like to thank the ProbSevere development group at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (CIMSS) and the National Severe Storms Laboratory for providing content and feedback. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Here are the objectives for this lesson. Take a moment to review them before moving on, as you will be quizzed on this content."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Let’s get started! So what is ProbSevere? Technically called Probability of Severe, it’s a statistical model that incorporates many different observational datasets to create a nowcast of the probability of severe weather. There are 3 versions of ProbSevere. The first version was released in 2017. The next version of ProbSevere, v2 or “All-Hazards,” is a statistical model that predicts the probability that a storm will produce severe hail, severe wind, or a tornado in the next 0-60 minutes. Most recently, ProbSevere has been upgraded yet again to Version 3, or v3. v3 is a statistical model that uses machine learning models to predict the probability that a storm will produce severe hail, severe wind, a tornado, or any severe in the next 0-60 min. It updates every 2 minutes. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="It is important to use the model output in a situational awareness manner. It can be used to help a forecaster make the decision to first warn a storm. Or, the model probabilities can help determine if warning re-issuance is needed or not. More detailed examples of potential ProbSevere applications can be found in the WDTD companion Applications lesson. In all cases, ProbSevere should be used as an additional guidance, combined with forecaster experience and traditional analysis techniques when determining if one should issue a warning.
"> <Style FontSize="12" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="
"> <Style FontSize="12" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Also, note ProbSevere fits into the NWS’ Probabilistic Impact-Based Decision Support Services (ProbIDSS) strategic goal. We’ll talk a little bit more about new initiatives in this area later in this lesson."> <Style FontSize="12" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Now we’ll give a very generalized overview of how the statistical model works. First, the computer is trained to track thunderstorms using radar and satellite. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Once a developing storm exhibits moderate reflectivity and inherits the parent cloud’s satellite growth information, a combination of methods is used to track the cell. Additionally, total lightning, including terrestrial and GLM, information is obtained for each tracked storm. Then, all the data is input into the statistical machine learning model to derive the probability of severe weather occurring within a given hour."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text="From where is the statistical model getting its data? Let’s explore some example database directories from which it ingests data. Click on each folder label to see the different datasets. 
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Since ProbSevere was developed at a mesoscale satellite research organization, its foundation lies in satellite data. ProbSevere includes the could top growth/cooling rate because it gives an estimate for how much a developing storm top cools over a period of time. It’s also a proxy for vertical growth of convective clouds (and thus updraft strength). In v3, a new product called the Intense Convection Probability is now ingested into ProbSevere. Generated by an independent ML model trained to detect “intense” convection, its probability is influenced by features like strong overshooting tops, high texture in visible ABI imagery, strong anvil-edge gradients, and elevated GLM flash rates.
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="As of Version 3, ProbSevere ingests data from the High-Resolution Rapid Refresh (HRRR) model. Effective bulk shear (EBS) is useful for discriminating between supercellular and non-supercellular convection. Several convective available potential energy (CAPE) and convective inhibition (CIN) variables are also ingested. These variables give an estimate for updraft strength and whether a storm’s growth is being inhibited. Another included parameter is 0-1 km storm-relative helicity (SRH). Used in ProbTor, it provides a measure of potential for cyclonic updraft rotation. Precipitable water values are used to measure the amount of moisture for hail growth potential. Version 3 adds 1-3 km AGL Mean Wind, Low- and Mid-Level Storm-Relative Wind, Low and Mid-Level Lapse Rates, Surface Lifting Condensation Level (LCL), and Downdraft CAPE (DCAPE).
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Next, several Multi-Radar/Multi-Sensor (MRMS) products are incorporated into the ProbSevere model. The Maximum Estimated Size of Hail (MESH) product estimates hail size based on thermally-weighted vertical integration of reflectivity above the melting level. Derived from radial velocity, Low- and Mid-Level Azimuthal Shear (AzShear) is used as a proxy for low- and mid-level rotation, respectively. Next, the Composite Reflectivity product is employed by the algorithm to identify and track storm objects. Also, the Vertically Integrated Liquid (VIL) Density product is included. V3 has added Isothermal Reflectivity, the 50 dBZ Echo Top Height, and the Height of 50 dBZ at 0 degrees Celsius thickness. 
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="The final datasets ingested into ProbSevere at this time are lightning data. These include Earth Networks Total Lightning Network (ENTLN) flashes. Cloud-to-ground and intra-cloud flashes are summed within each radar object. This data is used as an indicator of storm severity. Additionally, the flash extent density and average group area are two Geostationary Lightning Mapper (GLM) products that are used for storm severity and as a proxy for the spatial extent of lightning respectively. "> <Style FontSize="12" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Next, we’ll explore the most important predictors to create each hazard probability. After the ML model was run, a predictor-importance analysis determined the following inputs are the most important factors in determining the probabilities. Click on each hazard to see its most important predictors. For All-Hazards, the most important inputs are effective bulk shear, 1-3 km AGL mean wind, 0-3 km AGL lapse rate, total lightning flash rate, MRMS MESH, MRMS VIL, and the satellite growth rate. For hail, the most impactful parameters are effective bulk shear, 4-6 km AGL storm relative wind, MLCAPE, MRMS reflectivity at –20 deg C, MRMS MESH, and the satellite growth rate. Wind’s important inputs are 0-3 km AGL lapse rate, 1-3 km AGL mean wind, total lightning flash rate, and 0-2 and 3-6 km MRMS azimuthal shear. Last, the most impactful parameters for tornadoes are 0-3 km AGL lapse rate, 1-3 km AGL mean wind, effective bulk shear, MLCAPE, and 0-2 km MRMS azimuthal shear. Fundamentally, ProbSevere is a statistical model that is driven by a blend of observational and environmental data. It uses this blend of current and past observations to predict the probability of severe hazards in the next hour."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="You’re probably wondering… what does all this mean to you, the operational forecasters? Let’s break down what this looks like in operations. All of the following happens within an hour. First, the GOES data updates every 5 minutes. Next, the HRRR composite updates every hour. Then, the ENI total lightning data updates every 2 minutes. Finally, the MRMS products update every 2 minutes. So that you are provided with the timeliest information, that means ProbSevere updates on your workstation EVERY 2 MINUTES. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="However, this does NOT mean it’s giving you a 2 minute-probability. Because each dataset input into ProbSevere updates at a different frequency, ProbSevere’s probability values change every time new data is available—every 2 minutes. But it’s giving you the probability a storm will produce severe weather in the next HOUR. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="In the next few slides, we’ll cover the different ways ProbSevere can be displayed in your AWIPS workstation. Note that these displays are as of AWIPS build 23.4.2. The primary display of ProbSevere Version 3 is what’s called the “All-Hazards” display. In its sampling mode, it shows each hazard probability value above all the input parameters that have been combined in the processes described earlier. This display also has a unique feature of a double contour. The inner contour shown will be the maximum value of ProbWind, ProbHail, or ProbTor. In this case, ProbWind is 79% so it’s the displayed inner contour. The outer contour will always be ProbTor. This ProbTor contour will display probabilities greater than 3% by default, and this value is customizable. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="If you don’t want to see all the hazard probabilities at once, you can display them individually. Here’s ProbTor. When sampling, it shows you the input values used in calculating that probability. In this case, strong low-level azimuthal shear and a good environment contribute to giving this object a relatively high ProbTor value. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Next, ProbHail can be displayed in a similar fashion. In this example, MESH above severe criteria and a favorable hail environment contribute to this high ProbHail value. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Finally, ProbWind is shown here with a favorable severe wind gust environment contributing to a moderate ProbWind value. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="We’ve covered a lot of ground. Let’s pause for a minute and recap what we’ve learned so far. ProbSevere is the probability that a storm will produce severe weather in the next 60 minutes, and it updates with new data every 2 minutes. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="ProbSevere is created by identifying a storm using MRMS composite reflectivity and satellite growth rate, followed by analyzing a storm’s other properties, then running the data through the ML statistical model, and finally generating the probabilities. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="ProbSevere includes 5-min GOES scans, hourly HRRR environmental grids, 2-min lightning files, and 2-min CONUS MRMS radar scans
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="ProbTor, ProbWind, and ProbHail are comprised of various sets of parameters based on a predictor importance analysis."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Now that we know how ProbSevere works and what it looks like, let’s make sure you have a general understanding of its performance and reliability. For all of the ProbSevere v3 models, all of them perform better and are better calibrated than v2. This means that, overall, its probabilities will be lower than they were in v2. We’ll cover that in a little more detail in the Applications lesson. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Compared to NWS forecasters, v3 is still less skillful. But a majority of forecaster participants in the NOAA Hazardous Weather Testbed agreed that v3 offers better lead time and warning confidence than v2. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Out of all the ProbSevere models, ProbTor is the least skillful. We’ll talk more about ProbTor in a few slides."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Diving into the specific ProbSevere models’ performance and reliability, we’ll start with All-Hazards. To put it simply, All-Hazards is most reliable during these 3 conditions: …in non-winter months. The bottom graph here shows All-Hazards has its lowest reliability in the winter. …in the Great Plains. It’s not surprising that All-Hazards is most reliable in the Great Plains where a majority of tornadic and large hail events occur. And finally, …in environments with low to moderate mixed-layer CAPE and moderate- to-high effective bulk shear. So ProbSevere All-Hazards is most reliable in high-shear, low CAPE environments as well as medium intensity environments."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="The reliability of the individual hazard probabilities is our next topic. In general, both ProbHail and ProbWind v3 are significantly more reliable than their v2 counterparts. However, they do have a slight overforecasting bias, which is different from v2 that had an underforeasating bias. ProbHail does have a slight under-forecasting bias at high probabilities. Note that ProbWind v3 is more reliable than v2 due to better skill in detecting linear severe wind events, so don’t be afraid to use ProbWind for those. Also, as mentioned earlier, ProbHail and ProbWind exhibit better reliability than ProbTor."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Finally, let’s look at ProbTor’s verification statistics. One final time, I’ll note that ProbTor is the least skillful of the ProbSevere models, so note it’s relative trends rather than its actual values. We’ll talk about another ProbTor-specific caveat in a little bit. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Meantime, note that ProbTor v3 exhibits an over-forecasting bias at probabilities greater than 60%, but it’s rare for ProbTor to output values greater than 60% so you shouldn’t encounter that too often. ProbTor can also under-forecast in the winter months and October. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="While the model performance is good, there are some biases that should be considered when using the ProbSevere model. This is not an exhaustive list, and the biases may not be present in all cases. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Let’s cover the under-forecasting biases. First, storms far from radar sites, and storms encountering radar beam blockage could produce a ProbSevere under-forecast.
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="A couple more under-forecasting instances are storms developing beneath thick cirrus shields or anvils are generally underforecast. There could also be some model data errors.
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Additionally, there are some hazard-specific under-forecasting circumstances. ProbTor may under-forecast landspout tornadoes, and ProbWind underestimates winds outside reflectivity cores. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Uniquely, there are some situations that encounter both forecasting circumstances. First, storms that are only sampled by one radar may by underforecast or overforecast since the benefits of the MRMS data are not gained. And once developing convection transitions to linear modes, the probabilities can over- or underforecast. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="There are just a couple known instances of over-forecasting biases. MRMS products are known to over-foreccast, and this could be reflected in ProbSevere products. And finally, ProbTor can over-forecast near radar sites due to erroneous MRMS Azimuthal Shear."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Let me take a second to focus on ProbTor. Although it has been shown to be well-calibrated, ProbTor values vary with given background environments. Namely, a day with more marginal kinematics will in general have lower probabilities than a day with more favorable kinematics. Here’s an example. Say we have 3 storms in a marginal environment with the displayed characteristics. The largest ProbTor probability is 30%, which may not appear to be significant. But if we take those same 3 storms and put them in a kinematic environment that’s favorable for tornadoes, notice the ProbTor values, especially on the middle storm, increase significantly. The ProbTor on this middle storm needs to be given the same amount of attention in either environment. It is best to use ProbTor in a RELATIVE sense! Note which storms—in this case, the middle one—stand out relative to its neighbors."> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text="Take note of these considerations when using ProbSevere during warning operations. Click on each sticky note for more specifics. Once you have gone through all the notes, click the "next" button. 
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbSevere will not provide lead time for every storm:
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Lead time will be greatest when the satellite can observe the development of the storm from immature cumulus to cumulonimbus
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbSevere does not discern storm mode:
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="It does not differentiate between supercells, multicells, etc.
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Notes on ProbSevere objects:
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbSevere requires an identifiable object in radar reflectivity
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Mostly in linear modes, object identification can become more difficult--the absence of an object (and ProbSevere value) does not mean there is no severe weather threat!
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbTor object centered on Z, not V-don’t use for tornado warning polygon placement!
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbSevere is impacted by radar beam blockage and increasing beam height away from radar:
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Probabilities may be affected, but can still give a good estimate of severe criteria in poor radar coverage areas
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbSevere depends on MRMS and model data:
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Latencies associated with MRMS and model data reflect in ProbSevere values and object placement
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbSevere values may fluctuate based on one input, for example MRMS MESH, so always be aware of the input values
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="For storms within ~10 miles of NEXRAD sites, use ProbWind and ProbTor with caution as MRMS AzShear values may be artificially high 
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbWind probabilities will be underforecast for strong winds located outside the reflectivity core:
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="ProbSevere does not handle features like gust fronts and outflow boundaries well
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Tornadogenesis mechanisms not represented in ProbTor predictors:
"> <Style FontSize="12" /> </Span> </Block> <Block> <Style /> <Span Text="Since ProbTor does not include microscale tornadogenesis data, do not use ONLY ProbTor to issue a tornado warning!"> <Style FontSize="12" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="There are several sources for ProbSevere data and extra information outside of AWIPS. Here are just a few. Gibson Ridge placefiles exist for ProbSevere. The URL to access those placefiles is in the PDF shown. Next, a great source of ProbSevere information is hosted by its developers at the University of Wisconsin. Termed RealEarth, ProbSevere data can be displayed on this site. If you click on a ProbSevere object’s ID, you can view time series plots of the ProbSevere probabilities and all its input parameters. Forecasters in the NOAA Hazardous Weather Testbed (HWT) found these plots very helpful during simulated warning operations. Another resource on the RealEarth site is ProbSevere graphic verification against warnings and storm reports. Finally, on this blog, you can see posts by ProbSevere developers and forecasters who participated in the HWT. "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="ProbSevere has undergone major improvements in the past 11 years, and more are to come. Those include possible improvements to ProbTor and we might see the ProbSevere Trends in AWIPS when AWIPS goes into the cloud! "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="ProbSevere is just the tip of the iceberg when it comes to probabilistic products in the convective warning space. As the NWS leans more into probabilistic IDSS and near-term forecasting, new products will be coming operational. These include Probabilistic Hazard Information or PHI which uses ProbSevere as the base for Severe PHI, that’s currently available in GR and will be a recommender in Hazard Services-Convective soon, the Tornado Probability Algorithm to replace the current TDA, and the Warn-on-Forecast System, a storm-based ensemble. I’ll re-emphasize that all these products, including ProbSevere, will be most useful when incorporated into your "> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> <Span Text="existing warning procedures"> <Style FontFamily="+major" FontSize="12" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> <Span Text=" and can help increase confidence in issuing, maintaining, and canceling warnings. Next up will be the quiz!"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="If you have any questions about this module, feel free to contact any of the NWS training contacts listed here. The ProbSevere developers at CIMSS and NSSL would like you to contact them with questions, suggestions, etc. at the email addresses provided. 
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Contacts:
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="NOAA/NWS Warning Decision Training Division
"> <Style FontFamily="+major" FontSize="14" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#8A0D00" Elevation="Normal" DisplayCase="AsIs" LinkColor="#8A0D00" /> </Span> </Block> <Block> <Style LeadingMargin="45" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="Bullet" ListTypeFormat="Plain" Start="0" Color="#000000,00" Size="100" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="WOC Severe Team ("> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#2E75B6" Elevation="Normal" DisplayCase="AsIs" LinkColor="#2E75B6" /> </Span> <Span Text="nws.wdtd.wocsevere@noaa.gov"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#CC6600" Elevation="Normal" DisplayCase="AsIs" LinkColor="#CC6600" /> </Span> <Span Text=")
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="dk1,00" Elevation="Normal" DisplayCase="AsIs" LinkColor="dk1,00" /> </Span> </Block> <Block> <Style LeadingMargin="45" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="Bullet" ListTypeFormat="Plain" Start="0" Color="#000000,00" Size="100" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Alyssa Bates ("> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#2E75B6" Elevation="Normal" DisplayCase="AsIs" LinkColor="#2E75B6" /> </Span> <Span Text="alyssa.bates@noaa.gov"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#CC6600" Elevation="Normal" DisplayCase="AsIs" LinkColor="#CC6600" /> </Span> <Span Text=")"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#548235" Elevation="Normal" DisplayCase="AsIs" LinkColor="#548235" /> </Span> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#2E75B6" Elevation="Normal" DisplayCase="AsIs" LinkColor="#2E75B6" /> </Span> </Block> <Block> <Style LeadingMargin="45" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0" /> <Span Text="
"> <Style FontFamily="+major" FontSize="12" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#2E75B6" Elevation="Normal" DisplayCase="AsIs" LinkColor="#2E75B6" /> </Span> </Block> <Block> <Style LeadingMargin="0" FirstLineMargin="0" Justification="Left" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="None" ListTypeFormat="Plain" Start="0" Color="#000000,00" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="NOAA NESDIS/University of Wisconsin Cooperative Institute for Meteorological Satellite Studies and NOAA/OAR/NSSL
"> <Style FontFamily="+major" FontSize="14" FontIsBold="False" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" ForegroundColor="#8A0D00" Elevation="Normal" DisplayCase="AsIs" LinkColor="#8A0D00" /> </Span> </Block> <Block> <Style FlowDirection="LeftToRight" LeadingMargin="45" TrailingMargin="0" FirstLineMargin="0" Justification="Left" DefaultTabStop="48" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="Bullet" ListTypeFormat="Plain" Start="0" Color="#000000,00" Size="100" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="John Cintineo ("> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#2A2A2A" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#2A2A2A"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text="john.cintineo@noaa.gov"> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#CC6600" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#CC6600"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text=")"> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#007E7E" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#007E7E"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text="
"> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#2A2A2A" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#2A2A2A"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> </Block> <Block> <Style FlowDirection="LeftToRight" LeadingMargin="45" TrailingMargin="0" FirstLineMargin="0" Justification="Left" DefaultTabStop="48" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="Bullet" ListTypeFormat="Plain" Start="0" Color="#000000,00" Size="100" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Mike Pavolonis "> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#2A2A2A" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#2A2A2A"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text="("> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#000000" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#000000"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text="michael.pavolonis@noaa.gov"> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#CC6600" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#CC6600"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text=")
"> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#2A2A2A" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#2A2A2A"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> </Block> <Block> <Style FlowDirection="LeftToRight" LeadingMargin="45" TrailingMargin="0" FirstLineMargin="0" Justification="Left" DefaultTabStop="48" ListLevel="1" LineSpacingRule="Multiple" LineSpacing="20" SpacingBefore="0" SpacingAfter="0"> <ListStyle ListType="Bullet" ListTypeFormat="Plain" Start="0" Color="#000000,00" Size="100" BulletChar="•" BulletFont="Arial"> <BulletPicture Size="0x0" /> </ListStyle> </Style> <Span Text="Justin Sieglaff ("> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#2A2A2A" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#2A2A2A"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text="justin.sieglaff@ssec.wisc.edu"> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#CC6600" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#CC6600"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> <Span Text=")"> <Style FontFamily="Calibri" FontSize="16" FontIsBold="True" FontIsItalic="False" FontIsUnderline="False" FontIsStrikeout="False" UnderlineStyle="Normal" ForegroundColor="#2A2A2A" BackgroundColor="#000000,00" UnderlineColor="#000000,00" Elevation="Normal" Spacing="0" IgnoreKerningTable="False" DisplayCase="AsIs" LanguageId="0" LinkColor="#2A2A2A"> <Shadow Offset="0x0" Color="#FFFFFF,00" /> </Style> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text="Here’s a list of references for this lesson. You can find some of these in the links provided in the Resources tab."> <Style FontSize="12" /> </Span> </Block> </Content> </Document> <Document xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"> <Content> <Block> <Style /> <Span Text="That concludes this lesson. Again, please feel free to reach out to these contacts for questions about this lesson. You may now move onto the next lesson."> <Style FontSize="12" /> </Span> </Block> </Content> </Document>